Cyclical Metapopulation Mechanism Hypothesis:

Generationally varying birth cohort specic hypothalamic hormone levels create physiological, cognitive, and behavioral dierences in cyclical animal populations, including human populations

Text: Janne Miettinen | PDF-version | ResearchGate: project page

Work-in-progress | First draft: Oct 2018 | Last update: Oct 2, 2021

Abstract

Known animal population cycles are from approximately 4 years (small rodents) to 38 years (moose), but why the cycles exist remains unknown after a century of research. Even though the length of the cycle varies between species, the cycles of different species all share distinctly similar phase-dependent variations to average physiological and behavioral properties of individual animals, including size, age of reproductive maturity, and aggression.

It is presented here that since hormone levels modulate the average physiological and behavioral properties in animals, the cyclical animal populations are a manifestation of a multiannual population-wide hormone cycle. This hypothesis details how the multiannual hormone cycle defines the average birth cohort specific levels of hypothalamic hormones of a cyclical population, thus creating generations with differing average hormone levels.

The mechanism creating the generational hormone cycles is suggested to be a neural mechanism that accelerates evolution by varying hormone levels of succeeding generations, and that this occurs in synchrony between populations on a metapopulation level, as the cycles can be in synchrony over a 1000 mile range. The population cycles have a migration phase that creates new populations, and because the migration phase also increases gene flow between populations, the population cycles are viewed as a combination of recognized evolutionary mechanisms; the cycles are presented to be a holistic evolutionary metapopulation mechanism that accelerates evolution.

Human populations are also presented to undergo a generational hormone cycle, and that the length of a human population cycle is approximately 80 years. Statistics from human populations are used to establish that the same generational hormone cycle exist in human populations as in other cyclical animal populations. A historical framework, the Strauss-Howe generational theory, details an 80 year long generational cycle repeating for centuries in the US population: four 20 year generations, with each generation having their own typical behavioral traits. This hypothesis presents evidence that the Strauss-Howe generational theory is in fact a description of a generational hormone cycle in the US population as well as in many other nations on the Northern hemisphere, where also the other cyclical animal populations exist. Table of Contents:

1 Hormones and cycles 1.1 Animal population cycles 1.2 Evolutionary benefits of the cyclical metapopulation mechanism 1.3 Cyclical human populations & review of contents

2 Generational history and hormone levels 2.1 Generational hormone theory 2.2 The Strauss-Howe generational theory 2.3 Historical oxytocin levels … 2.3.1 Oxytocin and parenting intensity … 2.3.2 Oxytocin and breastfeeding rates … 2.3.3 Oxytocin and maternal age … 2.3.4 Oxytocin and divorce rates … 2.3.5 Oxytocin and alcohol consumption … 2.3.6 A model of generational oxytocin levels 2.4 Historical dopamine and vasopressin levels … 2.4.1 Dopamine levels … 2.4.2 Group coherence and territoriality 2.5 Generational social hormone levels … 2.5.1 A model of generational social hormone levels … 2.5.2 Social hormones and political ideology 2.6 Other hypothalamic hormone levels … 2.6.1 Sex hormone levels … 2.6.2 Growth and thyroid hormone levels

3 Social hormones and group behavior 3.1 Social hormones and societal trends 3.2 Social hormones and societal group behavior 3.3 Neural in-group vs. out-group separation 3.4 Social hormones and populist nationalism

4 Group division and conflict 4.1 Group division 4.2 Societal paths of tightening group coherence 4.3 In-group empathy and scapegoating of the out-group

5 Initial conclusions 5.1 Possible societal trajectories 5.2 A review of societal actions 5.3 Unresolved questions

References 1 Hormones and cycles

1.1 Animal population cycles

Many animal species have population cycles that are very repetitive. For example, the length of population cycles are about 4 years for small mammals like lemmings and voles, 9 years for larch budmoth, 10 years for snowshoe hare and forest Lepidoptera, and 35 years for moose. (Myers, 2018​1)​ (Wang et al., 2009​2)​ (Krebs, 2010​3​)(Krebs et al., 2014​4​)(Hansson & Henttonen, 1985​5)​

There are over 1000 years of records of larch budmoth cycles that demonstrate the consistency of these cycles. (Esper et al., 2006​6​) Below is a statistic from the last century as an example of how highly regular the cycles can be in both length and amplitude.

Values 0.001-1000 indicate larch budmoth population density. (S)

Cyclical populations are very common in nature according to this study: “…we analyzed nearly 700 long (25+ years) time series of animal field populations, looking for large-scale patterns in cycles. Nearly 30% of the time series were cyclic.” … “The incidence of cycles varied among taxonomic classes, being most common in fish and mammal populations. Fully 70% of the fish and mammal species comprised at least one cyclic population…” (Kendall et al., 1998/2002​7)​

Predators, limited food supply, and diseases have been suggested to drive the animal cycles, but because the cycles do manifest even when these factors are excluded, it is probable that something else is creating and controlling the length of these cycles: “…lemmings on islands are known to be without predators and yet still undergo a 4 year population cycle.” (Ginzburg & Colyvan 8​, p. 79) “Numerous experiments have been done in attempts to delay the decline or stop the population cycles of lemmings and voles by feeding or excluding predators. These have had mixed results and Krebs concluded that predators can ‘modify’ population cycles, but that predator removal cannot stop cyclic dynamics. Similarly, food addition experiments can modify vole densities but not drive cycles.” … “Overall, experimentally stopping or starting population cycles has proven to be largely impossible.” (Myers, 2018​1)​

Increasing stress levels through increasing population density has also been used as a theory to explain the cycles, but this idea too has been disproven: “In 1967, Dennis Chitty proposed that larger and more aggressive voles would be selected for in increasing and high densities, and smaller voles with delayed reproductive maturity in low densities. The ‘Chitty Hypothesis’ predicted that variable selection would lead to a genetic shift over the 3 to 4 year cycle of voles. However, the genetic shifts predicted by this hypothesis have not been observed and the levels of heritability of traits required for the shift were unrealistically high.” (Myers, 2018​1)​

The end result is, that after a century of research into animal population cycles, not even one hypothesis exists that explains even one species’ cycles, while taking into account the findings made by Krebs and others about the environmental factors not starting or stopping the cycles, resulting in a situation where all explanations and theoretical models have been severely lacking in evidence and/or repeatability. (Andreassen et al., 2020​9​)(Oli, 2019​10​)(Myers, 2018​1)​ (Oli, 2003 11​) Since environmental factors cannot explain the cycles, what does explain the recurring appearance and characteristics of the cycles regardless of the species or the environment?

It is presented here that the real explanation for the cycles lies within the endocrine system that controls animal hormone levels and therefore modulates both their behavior and biological traits throughout the cycle. Only a biological mechanism that controls the generational hormone levels can explain the populations cycles in a way that is not dependent on environmental factors like predators or food supply, while giving answers to all of the previously unexplained questions regarding the cycles.

It is important to note that the term ‘ hormone levels‘ used throughout this text means that the hypothalamic neurons that secrete hormones are either small and inefficient or large and more efficient, like is presented in the lemming and vole studies below. In addition, the term ‘hormone’ will be used throughout the text, even though some of the same molecules also work as neurotransmitters in the brain, where the levels of these neurotransmitters modulate behavior. (S)

Two Russian neurobiological studies have focused on the generational changes to the endocrine system in voles and lemmings during their four year population cycles, and these studies state that there are large variances between generational hormone levels, including dopamine, oxytocin, vasopressin, and other hormones secreted by the hypothalamus. (Arshavskaya et al., 1989​12/​ PDF)(Vladimirova et al., 2006​13​) This is due to generational changes/differences in the parts of the hypothalamus that produce and secrete hormones. These two studies will be used as a template for the suggested human generational hormone cycle. Other studies regarding cyclical populations have largely made similar findings using external measurements such as larger testicles during the increase phase and higher ACTH/cortisol levels during the decline phase. (Sheriff et al., 2011​14​)

Below is a key excerpt from the mentioned lemming study as examples displaying the hormonal nature of the four year cycle: the 1989 lemming study measured the changes to the mass of the hypothalamic neurons and their effects on the endocrine system, and the study confirmed large generational variance in the different regions of the hypothalamus. The picture below largely represent the study’s key findings regarding generational hormone levels in a cyclical lemming population: the neurons in the hypothalamus change in size and efficiency according to the phase of the cycle, resulting in animals born in different phases of the cycle having differing (average) hormone levels.

Generational variance in the lemming endocrine system during different phases of the cycle, where the size of hypothalamic neurons secreting hormones/neurotransmitters affects the sizes of organs that secrete hormones. Phases II and III roughly represent the changes during the cycle’s last year/quarter. (Arshavskaya et al., 1989​12/​ PDF)

The endocrine system uses hormone levels to control and coordinate for instance the development of an organism and its size, age of reproductive maturity and reproductive behavior, stress response. Because cyclical animal populations see hormone levels fluctuate throughout the cycle, this means that a cyclical population’s average physiological and behavioral traits are also fluctuating generationally. This also means that the location in the cycle where an individual is born determines the probability of this individual having a certain configuration of hormone levels and the physiological and behavioral traits that these hormone levels promote. Listed below are a few of the key physical and behavioral properties that change according to the phase of the cycle when a cohort is born, accompanied by the hypothalamic hormone that primarily modulates the listed property in animals, and also the phases of a cycle when those hormone levels are at their highest levels, when a cycle is divided into 4 phases. Also listed are cyclical animal population studies that indicate these cyclical hormone levels during a cycle. [List to be expanded during Sep – Oct 2021.]

1. Increased fertility when sex hormone (GnRH) levels are high: phases 1 & 2. – Lemming (Arshavskaya et al., 1989​12)​ – Snowshoe hare (Cary & Keith, 1979​15)​

2. Increased physical size and strength when growth hormone (GHRH) levels are high: phases 2 & 3. – Lemming and vole (Oli, 1999​16)​ (Fauteux et al., 2015​17)​ – Snowshoe hare (Cary & Keith, 1979​15)​

3. Delayed or unfulfilled reproductive maturity when oxytocin levels are high: phases 3 & 4.

4. Lower level of aggression when dopamine levels are high: phases 4 & 1.

5. Increased territoriality when vasopressin levels are high: phases 4 & 1. (Johnsen et al., 2019​18​)

(6. Immune system: cortisol (CRH), phase 4, not yet implemented)

The graph below is a representation of the generationally oscillating average hormone levels (listed above) during an animal population cycle’s four phases.

The presumed hormone levels in the graph above have been adopted from studies mentioned in chapter 1.1 and proxy-statistics in chapter 2. 1.2 Evolutionary benets of the cyclical metapopulation mechanism

This chapter presents the multiple ways the presented cyclical metapopulation mechanism can increase the speed of evolution inside populations. [In its current state this chapter presents the premises in a highly compressed manner, but the chapter will be expanded in a future updates into sub-chapters, especially regarding the developmental effects of hormones.]

The endocrine system affects development through hormone levels from the embryonic stages of an organism by affecting gene expression, including the expression of HOX genes. (Daftary & Taylor, 2006​19)​ (Lutchmaya et al., 2004​20​) Because the birth cohort hormone levels vary annually in a cyclical population, the generational hormone cycle theoretically accelerates evolution by testing different average physiological and behavioral traits in a cyclical populations faster than in non-cyclical populations, and natural selection plays a role after this, as only the animals with the most suitable traits from each generation survive. Another way to express this mechanism is that birth cohort specific hormone levels modulate the development of birth cohorts differently, which expands the variation available to natural selection; the generational hormone cycle produces larger numbers of physiological and behavioral extremes in a population in comparison to a non-cyclical populations that have less pronounced extremes on average.

In animal ecology, the Hardy-Weinberg Equilibrium presents a state of stalled evolution in a population: when there are 1) no mutations, 2) mating is random, 3) natural selection is not a factor, 4) population size is large, and 5) there is no gene flow, the equilibrium causes a population’s allele and genotype frequencies to stay constant. However, according to the Red Queen hypothesis, a population that does not evolve loses in time to a population that does evolve. (Brochurst et al., 2014​21)​ (Strotz et al., 2018​22)​

Since the multiannual cycles of cyclical populations cause 1) more mutations due to a phase of large population numbers, 2) annual changes to mating behavior due to varying levels of sex hormones, 3) natural selection being a factor due to increased emigration and immigration, 4) annually varying population sizes, and 5) increased emigration and migration, thus increasing gene flow between populations, the cycle essentially accelerates evolution by removing the elements described in the Hardy-Weinberg Equilibrium that de-accelerate evolution. Therefore, the cyclical evolutionary metapopulation mechanism would give an advantage for a cyclical metapopulation when compared to a non-cyclical metapopulation, according to the Red Queen hypothesis.

Gene flow between cyclical animal populations increases during the high population numbers, since the animals move beyond the habitats they normally occupy during non-cyclical years, which results in increased gene flow between populations through migration. “During the peaks, the accumulation of new alleles (i.e., alleles not discovered before within the population) and the appearance of a homogenous population structure suggest higher migration rates and, consequently, increased gene flow within the population compared to the crash periods.” (Rikalainen et al., 2012​23​) Another study based on data from seven cyclical lemming population states: “High genetic variability thus implies high gene flow over a considerable area for lemmings… Examination of empirical data suggests that high genetic diversity may be the rule rather than the exception in cyclic populations.” (Ehrich & Jorde, 2005​24​) The gene flow effect is enhanced by the fact that the cycles are often in sync between nearby cyclical populations, or the cycle travels as a “wave” through the terrain: “Then, the observed higher scale of gene flow in the direction parallel to the wave front may result from the recurrent redistribution of the genetic diversity during each outbreak between populations fluctuating in synchrony.” (Berthier et al., 2013​25)​

The generational hormone cycle would be an efficient evolutionary mechanism of creating new subspecies and ultimately new species, because it increases population migration into new areas compared to non-cyclical populations, thus producing new populations and expanding the metapopulation faster compared to non-cyclical populations. A March 2020 paper has proven Darwin’s claim of new species forming through the evolution of subspecies to be correct: “The research explored whether subspecies could be considered an early stage of speciation – the formation of a new species. van Holstein said: “The answer was yes.” (S/Van Holstein & Foley, 2020​26)​ Because the animal cycles increase seeking of new habitats, details depending on the species, it seems logical that the cyclical metapopulation mechanism creates new subspecies (faster than non- cyclical populations), that may evolve into new species as time progresses. For example, vole populations are known to be often cyclical with large fluctuations in population size, which may be the reason for their fast evolution: “The study focuses on 60 species within the vole genus Microtus, which has evolved in the last 500,000 to 2 million years. This means voles are evolving 60- 100 times faster than the average vertebrate in terms of creating different species.” (Fletcher et al., 2019​27/​ S)

The high population number phase can accelerate evolution through higher rates of beneficial mutations, since larger populations are more likely to find beneficial mutations. (Vahdati et al., 2017​28​)

During the crash phase of the cycles, the immune system is compromised in many observed cyclical animal populations, and this has been attributed to high ACTH secretion levels. (Sources to be added…) Along with low rates of reproductions, this last phase creates an evolutionary population “bottleneck” (S), where only the survivors get the reproduce and create a population for the next cycle, one that is possibly more resistant to disease. The crash phase does not seem to create populations with a narrow gene pool: “However, we did not find a bottleneck signature, that is, heterozygosity excess, in the population after the crash phases.” (Rikalainen et al., 2012​23​) Even though some populations in a metapopulation may go extinct during the phase of low population numbers, the evolutionary benefits for the metapopulation as an entity may be worth sacrificing some of the populations within the metapopulation. (Franklin et al., 2014​29)​

Predator avoidance can also be theoretically more efficient in a cyclical population compared to a non-cyclical population: the average physical and behavioral attributes of the prey population changes annually, whereas in a non-cyclical population there is less change year-to-year, which would make it easier for the predator to adapt to the prey’s behavioral and physiological properties. But the possible effects of the cycles increasing predator avoidance may not be very important when compared to the other evolutionary benefits of the cyclical metapopulation mechanism presented in this chapter.

1.3 Cyclical human populations & review of contents Human populations are presented to undergo the same multiannual hormone cycle as other cyclical animal populations. Humans are mammals, and mammal populations are among the more frequently cyclic animal populations. (Kendall et al., 2002​7)​ There exists a historical cycle theory that describes an 80 year long generational cycle going on for centuries in the US, and the theory’s cycle includes four phases very similar to the four phases in the animal population cycles: the Strauss-Howe generational theory describes in detail how four generations, born during the 80 year long cycle, each have distinct average behavioral traits, and that these generations repeat in the same order during every cycle, which is a characteristic of animal population cycles.

This hypothesis presents a generational hormone theory, that lays out a theoretical base and presents evidence from Western human populations that are presumably undergoing the same generational hormone level oscillations to their hormone/endocrine system as the cyclical animal populations. Therefore, the generational hormone theory suggests that Western cyclical human populations have differing physiological and behavioral traits among generations due to these generations having their unique average hormone levels.

Statistics and proxy-statistics from human populations and the documented findings from the cyclical animal population studies will be used throughout this hypothesis to demonstrate that humans have a similar generational hormone cycle, and that this cycle is in sync with the Strauss-Howe generational theory’s observations about generational behavioral traits and historical societal change, which they have extensively documented. The presented generational hormone theory concentrates on the Western nations, since the Strauss-Howe generational theory covers mainly the US generations, but also makes references to other Western nations.

Nearby cyclical animal populations are often in sync regarding the phases of the cycles ( Krebs et al., 2017​30)​ (Tähkä et al., Endocrine aspects of population regulation in the genus Clethrionymus , Mem. Soc. fauna Flora Fenn., 1984), and traveling waves are a typical characteristic of the cyclical animal populations, which makes (Sherratt & Smith, 2008​31​)(Jepsen et al. 2016​32​)(Berthier et al., 2013​25)​ In Western human populations the wave is presumably beginning from the US, and then travels towards north to Canada, east to the Western Europe, and from there further east and also to the south, like Spain, that lags the Western Europe’s phase by a few years in statistics, while many Eastern European countries are lagging roughly 5-10 years. Russia lags about 15 years behind the US in the presented statistics, almost an entire (20 year long) phase of the 80 year long cycle. Most of the cyclical animal populations are located between northern latitudes 30 and 70, and those latitudes also include all the Western nations on the Northern Hemisphere and Russia. (Kendall et al., 1998/2002​7)​

– After the introductory chapter 1, chapter 2.2 presents the Strauss-Howe generational cycle in more detail; 2.2.1 reviews how time spent with children is linked to the parent’s oxytocin levels; 2.2.2 reviews historical evidence of breastfeeding initiation and its connection to oxytocin; 2.2.3 reviews the average maternal/paternal age and its connection to oxytocin; 2.2.4 reviews historical divorce rates and their connection to oxytocin levels; 2.2.5 ties generational oxytocin levels to changing alcohol consumption rates in history; 2.2.6 presents the generational oxytocin levels based on the previously presented proxy statistics; 2.3.1 review proxy statistics to find generational dopamine levels; 2.3.2 ties eras of high/low group coherence to fluctuating dopamine levels and vasopressin into eras of high/low territoriality; 2.4.1 presents a model of the generational hormone cycle with oxytocin, dopamine, and vasopressin included in it; 2.4.2 reviews how generational social hormone levels presumably modulate generational voting behavior; 2.5.1 links lower levels of sex hormones to the reproductive difficulties experienced during the early 21st century and other health issues; 2.5.2 reviews growth and thyroid hormones.

– Chapter 3.1 lays out the current societal trends; 3.2 is a short introduction to how hormone levels are related to history; 3.3 is an introduction to oxytocin, dopamine, and vasopressin and their effects on individual and group behavior; 3.4 looks at how social hormone related traits.

– Chapter 4.1 takes a closer look at a chimpanzee population exhibiting group division patterns; 4.2 presents the common paths small and large groups undergo when group coherence tightens; 4.3 ties the biological roots of scapegoating to increasing in-group empathy.

– Chapter 5.1 presents initial conclusions based on the findings made throughout this hypothesis; 5.2 lists commonly suggested ideas on how to suppress populism; 5.3 includes some currently open questions.

Genetic factors of individuals are confined out of this hypothesis, since on a level of a population the genetic differences between individuals and generations are evened out. Hormone receptor SNPs are negated at this point for the same reason. There are differences in the mean genetic and SNP distribution between nations and continents, but for the moment, this fact is left aside, although it is very relevant in the context of population-scale behavioral differences between different geographic locations. (Allocco et al., 2007 ​33)​

Transgenerational epigenetic effects are left aside for now, because they are more case sensitive, but could theoretically contribute to the generational traits in some ways, since stress receptivity of generations presumably changes during the cycle. And since hormones act as epigenetic signals in development, epigenetics are taken into account, but not in a transgenerational way. [In 2019 this hypothesis included a theoretical framework on how the fluctuations in hormone levels might be due to epigenetic effects between generations, but this framework was abandoned due to several reasons, one of them being that it would be highly unrealistic for such a epigenetic cycle – for all hypothalamic hormones – to manifest as coherently as what the cycles have been documented to be between different species and also different environments.]

Differences in hormone effects between sexes are currently mostly negated, but will be implemented later on. Biologically the proposed human generational hormone cycle is very similar to the documented lemming and vole generational hormone cycles. Because functions of the hypothalamus have been tightly conserved through the mammalian evolution, this makes findings from rodents largely translatable to humans. (Caldwell & Albers, 2015​34)​ (S) Hypothalamic hormones have a multitude of physiological and behavioral effects in different species, but only those hormone effects are accounted for that have 1) behavioral effects relevant to this hypothesis and 2) physiological functions that are used to find historical hormone levels by using proxy statistics (like breastfeeding statistics for oxytocin). This hypothesis has been a personal project and a byproduct of research done while writing a master’s thesis starting in 2017 looking at oxytocin and vasopressin levels being connected to empathy and aggression, and simultaneously reading about the Strauss-Howe generational theory, and then evaluating if generational hormone levels could explain the generational behavioral traits that the Strauss-Howe generational theory details. (McLean et al., 2017​35​)(S) This hypothesis has been growing without any other specific aims than to find out if there is a generational hormone cycle in human populations, and then in early 2019 finding the two mentioned Russian neurobiological studies that present how cyclical animal populations undergo a similar hormone cycle than what this hypothesis had previously theoreticized for the Western human populations.

Sources used are mainly from the fields of neurobiology, neuropsychology, chronobiology, and sociology; the combination of these can be described as sociochronobiology. (S) Quotes are used to underscore some of the most important aspects of the biological and historical evidence central to this hypothesis. Sources are linked mostly only once in their most relevant context, and at times are a collection page that may not be a strictly scientific source. Although much more could be stated about many aspects regarding this hypothesis, the text is streamlined in its current state to be as coherent and easily accessible as possible.

2 Generational history and hormone levels

2.1 Generational hormone theory

To shortly characterize the premises of the generational hormone theory: most Western nations have generationally varying/oscillating hormone levels that shape the typical behavioral and physiological traits of generations. These are the very same generational traits that the Strauss- Howe generational theory presents from the Anglo-Saxon generational history. These varying hormone levels also affect group coherence and the “in-group vs. out-group” setting, that has already been established through a multitude of studies in both social psychology and neurology, and these changes to group coherence follow the Strauss-Howe generational theory’s 80 year cycle of low/high group coherence. (Lewis et al., 2010​36​)(Lewis & Bates, 2017​37​) (S)(S) (Dopamine levels have a major effect on the coherence of large social groups, and dopamine levels are presumed to be in sync with the generational vasopressin levels that are presented in chapter 2.)

The graph below presents the presumed average birth cohort hormone levels found in Western nations. It is important to note that the graph below represents presumed birth cohort levels of hormones, while some other graphs present presumed societal effects of hormones, which manifest roughly 30 years later after a birth cohort has been born, as is explained later in more detail. (An example would be that, according to the graph below, the highest point in sex hormone levels in young adults in the Western societies during the 21st century was presumably close to the year 1970, and the following lowest point was close to the year 2010.) Theoretical average birth cohort specific hormone levels in Western nations, backed up by statistics that are presented in chapter 2. The percentages are merely directional. ‘Sex hormones’ represent presumed gonadotropin-releasing hormone levels. The ‘growth hormone’ curve represents the presumed levels of the growth-hormone-releasing hormone that is secreted by the hypothalamus.

The generation hormone theory aims at providing a biological basis for the Strauss-Howe generational theory and uses it as a framework along with historical proxy statistics and the animal population cycle studies to establish a generational hormone cycle for human populations. Especially oxytocin, dopamine, and vasopressin are at the center of this theory, since those are hypothalamic social hormones that modulate group behavior in general: oxytocin is relevant in the context of family and friends, dopamine is relevant to large-scale group coherence, and vasopressin is relevant in the context of territoriality and group aggression. It is important to note that there obviously are other hormones that affect social group behavior, but since they are not secreted from the hypothalamus, they are not taken into account in this hypothesis.

The generational hormone theory aims at binding these hormone’s behavioral effects into societal phenomena, especially large-scale in-group vs. out-group behavior, and after that connect these established types of group behavior into historical eras in order to find correlating points in history that are repeating regularly every 80 years. From the viewpoint of sociology, the generational hormone theory takes both micro and macro levels into account by looking separately at individual and group behavior, both of which are modulated by hormone levels.

It should be noted that terms like nationalism and globalism are only social constructions that are always tied to their historical context. Nationalism and globalism could be replaced with terms of tribalism vs. cosmopolitanism or some other way to convey the idea of a society’s social coherence and a society being more open/closed to outside groups. The effects of social hormones on ideology cannot therefore be bound too much to any terms of language because the roots of ideological tendencies are situated in biology as is presented in later chapters: the societal effects of low/high hormone levels manifest in different ways depending on the social structure of the selected point in history, be it a feudal kingdom in 12th century England, a Germanic tribe in 15th century, or a nation belonging to the EU in the 2020s. This is why mainly the terms nationalism and globalism will be used to in order to illustrate differences between eras of low and high group coherence.

The historical observations made throughout the generational hormone hypothesis are made only to create a link between 1) presumed changes in generational hormone levels in human populations that are similar to the animal population cycles and 2) the Strauss-Howe generational theory, but not to suggest that hormone levels in some way have created historical events.

To better explain the presumed generational cycle, an example of varying hormone levels through a period in time is the menstrual cycle: women in their reproductive years tend to have mood swings that are caused by changing hormone levels during their menstrual cycle, and the women react according to their mood, like with increased anxiety, depending on the phase of the cycle. But the menstrual cycle also has an effect on memory and spatial skills for instance, demonstrating that varying hormone levels impact both behavior and cognitive skills (and even the structure of the brain). (Pletzer et al. 2019​38)​ (S)

Women’s cognitive skills change during the menstrual cycle due to fluctuating hormone levels. (S)

Even though menstrual synchrony among women is still a debated subject (S), if the synchrony was occurring, it would mean that there would be also behavioral and physiological trait synchrony among those women during different phases of the month. This is essentially the same thing that this the generational hormone theory is suggesting to be happening in an 80 year cycle with generations: birth cohort specific average hormone levels affect each generations’ average behavioral and physiological traits, and these traits are presumably listed by the Strauss-Howe generational theory. And just like the menstrual cycle, that is a ‘multi- oscillatory circadian system’, the generational hormone cycle is presumed to have different ​39​ phases with different hormone level configuration. (Simonneaux & Bahougne, 2015​39​)

And very similarly to the animal population cycles not being sufficiently explained by any traditional methods that look only at environmental factors, not a single species’ menstrual cycle length variations have been successfully explained by using environmental factors: “Although cyclical temperature changes are experienced by many species, as are fluctuations in food supply, rainfall, and salinity, their precise effects and those of many other stimuli, independently or in combination, have not yet been defined for any species.” This leads to suspect that menstrual cycles are also presumably controlled by something else than environmental factors.

2.2 The Strauss-Howe generational theory

During the 1980s, historians William Strauss and Neil Howe started to write a book about the history of the US generations labeled Generations. (1991 C-SPAN interview) In 1997 they released The Fourth Turning book, that went even further in describing the dynamics of their theoretical generational cycle. (1997 C-SPAN interview) According to the interviews of these generational historians, before this they had come across the repeating generational cycle (presented in this chapter) independently in their studies, and only after this meeting each other and combining their research towards a common goal of presenting the history of US generations.

The Strauss-Howe generational theory details a four generation cycle that goes on roughly at intervals of 2030-2010 | 2010-1990 | 1990-1970 | 1970-1950, etc., with each of the four generation having detectable individual and group behavioral traits. (S) The years are approximations and vary slightly between the books and this theory, since the books are based on historical observations while this theory is based on a more coherent biological cycle. (S)

The cyclical four 20 year generations are introduced next, and then it is explained how they form a repeating cycle of 80 years in total like William Strauss & Neil Howe have documented in their books including Generations (1991) and The Fourth Turning (1997). (S) One full 80 year cycle is called an Anglo-American saeculum, and the repeating four generations span all the way back to the 15th century England. Since this chapter includes a lot of historical claims, the sources and quotes are not presented to be indisputable facts, but are used to construct a “bridge” between the Strauss-Howe generational theory and the presumed generational hormone levels in many Western nation that are presented in this chapter, which seem to be very similar to the fluctuating population-wide hormone levels in different phases of cyclical animal populations.

Strauss & Howe use the word ‘turning’ to describe a roughly 20-year long phase. A 1st generation is born during a 1st turning, and that generation is the Boomers in the current generational cycle. The generations and their traits were easily observable during the 20th century (Baby Boomers, Generation-X, Millennials) in most Western nations, especially in the U.S., due to the increasing societal freedoms and consumerism of the past century. Changes to youth culture mostly generated in the U.S. and spread on from there to other Western nations that were receptive to these movements, presumably by them having similar cyclical hormone levels (as is presented later on), which would be similar to the cyclical animal populations that have their cycles in sync with other nearby cyclical populations. The most volatile point in the 80 year Strauss & Howe generational cycle has historically been the last (4th) turning, when a 1st generation, the so called Prophet/revolutionary generation (Baby Boomers in the current cycle), is largely holding the places of maximum civic and economic power. This has historically been a time of societal turmoil: old beliefs are challenged, group coherence tightens, institutions are reshaped to serve the new goals, and the status quo is changing rapidly towards the end of a 4th turning. (More on how institutions evolve through increasing group coherence in chapter 2.3.2.)

Strauss & Howe are not the only ones to have noticed such a generational pattern in history, as sociologist and historian Jack Goldstone has also observed a generational pattern manifesting throughout human history: “Goldstone was also encouraged by the publication in 1978 of Colin McEvedy and Richard Jones’s Atlas of World Population History, in which they highlighted an “astonishing synchronicity” in population booms and busts across Eurasia over millennia. A few months into his number-crunching, he had his eureka moment: “It was astounding: there really was a three-generation surge in population growth before every major revolution or rebellion in history.”” (S)

Other historians that Strauss & Howe have listed in The Fourth Turning, including Arnold Toynbee and Quincy Wrigth, also have located similar cyclical generational patterns in many historical cultures. Strauss & Howe note that even the renowned political philosopher Polybius found a very similar generational cycle in second century B.C. when he studied the histories of Greco-Roman city-states.

Below are short descriptions of the four turnings accompanied by short quotes from the book The Fourth Turning (and approximate years of birth from the current cycle).

1st turning (1943-1960): “An upbeat era of strengthening institutions and weakening individualism, when a new civic order implants and the old values regime decays.” The society is unified and there is optimism about the future, institutions are trusted. The society eventually starts a movement towards globalism and liberalism, but nationalistic/patriotic pride is still strong. A 1st generation is born into an era of cooperation, and is a more optimistic, daring and selfish generation than the previous (4th) generation. This sense of optimism has been observed even in the offspring of holocaust survivors. (S) A 1st generation is historically the populist generation once they gain major political power during a 4th turning.

2nd turning (1961-1981): “A passionate era of spiritual upheaval, when the civic order comes under attack from a new values regime.” In a second turning the 1st generation leads the youth revolution and the more rigid nationalistic culture of the first turning makes way for a strong culture of liberalism, much through 1st generation young adults. A 2nd generation is born and raised very loosely, becoming a generation of independent individuals, driving the rise of individualism in their young adulthood during the next (3rd) turning.

3rd turning (1982-2004): “A downcast era of strengthening individualism and weakening institutions, when the old civic order decays and the new values regime implants.” In the 3rd turning the family structures are weak, individualism is strong, and anti-social behavior like crime is common. A 3rd generation is born into a relatively peaceful liberal world, and they become more cosmopolitan in their ideological views than the previous generations. General trust towards institutions starts to decay, and this accelerates during the next (4th) turning.

4th turning (2005-2027): “A decisive era of secular upheaval, when the values regime propels the replacement of the old civic order with a new one.” In a 4th turning the 1st generation enters positions of most political power and nationalistic coherence (or divide) tends to reach its peak towards the end of the turning (different paths are assessed in chapter 4). (S) The 1st generation with their confidence and capital power tend to drive the economic bubbles to new heights before a bust, like in 1929 and 2007. (S) Group tightness and coherence increases, ideological sides are being chosen at an accelerating pace, and cooperation among (possible) opposing factions of society deteriorates. This crisis era will basically either unify or divide a society even further. Information outlets and individuals with large audiences like celebrities begin to weigh in their opinions more and more in the increasingly polarized public ideological debate. A 4th generation is born, they are sensitive, sentimental, and their stress receptivity is high, just like today’s youth is often referred to as “snowflakes” by the older (and also bolder) generations. “The social mood changes” Strauss & Howe often remind their readers of what happens in a 4th turning once the so called crisis era begins.

The Strauss-Howe generational theory states that if a society has issues within, these problems will grow larger once the anxieties of a 4th turning begin, and this is presumably due to increasing vasopressin levels, which correlate with higher anxiety levels, since vasopressin is anxiogenic. (Neumann & Landgraf, 2012​40)​ High vasopressin and dopamine levels therefore result in anxious and polarizing group behavior, which is exactly what the Western nations experienced during the 2010s, just like the Strauss-Howe generational theory has predicted. This movement can be observed for example in the US statistic below that illustrates the party divide beginning to increase even though the issues have not become more polarized.

The political party affiliation in the US has grown since the late 00s, The political party affiliation in the US has grown since the late 00s, even as the stances on issues have not become as divided, but remained much steadier. (S)

In other words, the stance on political issues has not changed much on average in over 20 years, but the group affiliation to political parties has become much stronger. Since a party is an ideological in-group, this statistics essentially tells how the in-group identification has gotten stronger. The partisan divide began between 2004 and 2011, and a similar trend can be observed to have happened in the UK in the beginning of the 2010s.

Polarization in the UK (by birth cohort) begun in the early 2010s. (S)

There obviously are differences in individual hormone levels and behavior, but looking at a generation as a whole averages out these individual differences and, for example, youth culture and voting behavior are good indicators of how a generation acts and what are their preferences and behavioral traits. As most people are married to and have a majority of their friends from their own generation, this enhances the effects of hormone levels to individual and group behavior through behavioral synchrony. (Sources to be added…)

To very shortly further characterize the generations by echoing the Strauss-Howe generational theory, listed below are youth culture examples from the current cycle, highlighting the generational social mood found in music and movies for the 1st (revolutionary/optimistic), 2nd (individualistic/darker), 3rd (communal/heroic) and 4th (sentimental/caring) generations. Aesthetic experiences like music activates the brain’s reward system (Sachs et al., 2016​41​), and the four generations have different preferences in what kind of music they prefer to listen to. Since aesthetic experience is basically a biological mechanism reacting to sensory input, this implies that different generations have different brain structures that affects their behavior, and different hormone levels can change the brain structure due to brain plasticity. (Rajamani et al., 2018​42​)(S)

1st: Boomers | Music: The Beatles, The Rolling Stones, Elvis. | Movies: Rebel Without a Cause, Easy Rider. 2nd: Generation X | Music: Nirvana, Metallica, Madonna. | Movies: Star Wars and Halloween franchises. 3rd: Millennials | Music: Foo Fighters, Spice Girls, Lady Gaga. | Movies: Harry Potter and Marvel franchises. 4th: Generation Z | Music: Ed Sheeran, Shawn Mendes, Billie Eilish. | Movies: The Hunger Games and The Maze Runner franchises. (More cultural examples, especially from and beyond the 20th century, can be found in books by Strauss & Howe, which address the typical cultural interests of the four generations.)

Since hormones act as epigenetic signals in development, the presumed hormone cycle could presumably modulate the average phenotypes of entire generations, resulting in synchronized average generational behavioral and physiological traits. (Fowden & Forhead, 2009​43)​ This would result in generations to have their unique generational behavioral phenotypes when comparing different generations inside one full cycle. (Crawley, 2008​44)​ (S) (The term ‘behavioral phenotypes’ has sometimes been used to describe mental illnesses, but here it is used to describe the presumed average behavioral traits of generations.)

To back up the claim that the four different generations have different hormone levels, this chapter 2 presents evidence of generational oxytocin, dopamine, vasopressin, sex, growth, and thyroid hormone levels, and inserts them to the theoretical generational hormone level chart. Chapter 2.3 presents historical proxy statistics of child nurture intensity, breastfeeding, maternal/paternal age, divorce, and alcohol consumption rates in order to establish common points in history when oxytocin levels have been high or low. Chapter 2.4 looks at dopamine and vasopressin levels using other proxy statistics. These findings are bound together in chapter 2.5, where it is presented that different generations have different levels of social hormones (on average), and how these varying levels of social hormones affect the generational behavioral traits and the social mood during the different turnings as is described in the Strauss-Howe generational theory.

Although only proxy statistics are available for dopamine, vasopressin, and oxytocin levels regarding human populations, the proxy statistics may actually be a much more accurate way of measuring birth cohort specific hormone levels than direct measurements from blood samples. This is because the mentioned hormones are secreted when needed (compared to hormones like testosterone, which have more of a timed and longitudinal secretion rate), but if the hypothalamic neurons are small and ineffective, the effects do not manifest like they would if the hypothalamic neurons were large and effective. This is why proxy statistics give “real world results” in comparison to laboratory measurements.

For example, oxytocin is released when a baby sucks on the mothers nipple, and if not enough of oxytocin is released, there will not be milk ejection. The situation will also result in less of a bond between the child and a mother, meaning that the mother’s nurture will likely be less intensive as the child grows. So what is good about the proxy statistics is that they are tied to both the amounts of hormones secreted and the situation at hand, not to a single measurement in a lab like how hormone levels are conventionally measured.

2.3 Historical oxytocin levels 2.3.1 Oxytocin and parenting intensity

Higher oxytocin levels in parents leads to more time spent with children. ( Gordon et al., 2010​45​) The Strauss-Howe generational theory states the following about child nurture (S) intensity: 1st turning nurture is relaxing, 2nd turning nurture is underprotective, 3rd turning nurture is tightening, and 4th turning nurture is overprotective, after which the next 1st turning child nurture is once again loosening. The graphic below, that is taken from the book Generations (1991), illustrates the 80 year cycle in nurture intensity (where the 2nd turning is roughly from 1965 to 1985 in the current cycle).

‘Turnings’ and ‘generations’ (red text) have been later added for clarity. Social ‘eras’ are explained in detail in Strauss & Howe’s books Generations (1991) and The Fourth Turning (1997).

According to the statistic below, it seems that the 1970s were the time when American parents spent the least time with their children. The statistic shows a pattern similar to the breastfeeding initiation and maternal/paternal age statistics that are reviewed next. The bottom year is close to 1975 and the top year seems to be close to 2005-2010, repeating the same years as with the breastfeeding rate and paternal age statistics. There is also a steeper climb from 1975 to 1985 like with the breastfeeding rate and maternal/paternal age statistics (reviewed next). Weekly hours spent with children under age 5, the low peak being in the 1970s, and the high peak being in the 2000s. (S)

The statistic highly correlates with the Strauss-Howe generational theory regarding nurture intensity. In the 1970s bringing up children was much more carefree than in the 2000s. (S) Other Western nations also show large increases in parenting time since the 1970s. (Sani & Treas, 2016 46​)

2.3.2 Oxytocin and breastfeeding rates

Breastfeeding initiation statistics should correlate with oxytocin levels, as breastfeeding requires oxytocin to enable the milk let-down reflex. (Augustine et al., 2017​47​)(S)(S) “Circulating oxytocin is critical for normal birth and lactation. Oxytocin is synthesized by hypothalamic supraoptic and paraventricular neurons and is released from the posterior pituitary gland into the circulation… While it might be controversial as to whether oxytocin plays an indispensable role in parturition, the critical role that oxytocin plays in milk let-down during lactation is not disputed. The release of milk is mediated by secretion of oxytocin from the posterior pituitary gland, and oxytocin’s action at OTR [oxytocin receptor] in the mammary gland induces a rise in intra-mammary pressure and release of ​48​ milk: an oxytocin-mediated reflex upon suckling.” (Scott & Brown, 2013​48)​

Available breastfeeding statistics from Western countries indicate that there is a low point in breastfeeding rates close to 1965-1975: U.S. (Albanesi & Olivetti, 2009 ​49​)(Ryan, 1997​50​), Australia (S), Norway (S), Sweden (S), New Zealand, and England & Wales. Even Japan shows a similar curve. (Inoue et al., 2012​51)​

US breastfeeding statistics

A verbal statement about the US rates reinforces the statistics that the rates were higher in the 1930s than in the 1970s: “Seventy-seven percent of the infants born between 1936 and 1940 were breastfed; the incidence declined during the subsequent decades to about 25% by 1970.” (Institute of Medicine, 1991​52)​

When looking at earlier centuries for similar patterns of low points in breastfeeding in the US, there unfortunately are no breastfeeding statistics from the 19th century, but here is a quote from the year 1887 that provides answers: “Then, bizarrely, American women ran out of milk. “Every physician is becoming convinced that the number of mothers able to nurse their own children is decreasing.” Another reported that there was “something wrong with the mammary glands of the mothers in this country.”…In the United States, nineteenth- and early-twentieth-century physicians, far from pressing formula on their patients, told women that they ought to breast-feed. Many women, however, refused. They insisted that they lacked for milk, mammals no more.” (S) The inability to breastfeed is a probable indicator of low oxytocin levels, and like the Strauss-Howe generational theory states, nurture intensity was also low during this period.

And from 80 years earlier, this text may provide answers: “As with so many popular trends, there came a backlash against the use of wet nurses. Come the late 1700s/early 1800s—as part of the reform movements that swept across the social landscape of Europe and the United States—many women and men were calling for a return to in-home breastfeeding of babies by their own mothers.” (S) If there were calls to return to breastfeeding, that could indicate that the breastfeeding rates by biological mothers quite possibly have been low during that point in history. (And as a side note, the quote also mentions the social reform movements happening at the same time, just like during the 1960s and 70s, decades of large social reforms in Western nations.)

Historical UK breastfeeding rates closely echo the findings from the U.S. The following quote enforces this presumption: “The interwar [between WW1 and WW2] years saw the start of a long, steady decline in breastfeeding… breastfeeding rates in mothers leaving the postnatal wards dropped to below 20 per cent around 1970… there is no doubt that the 1970s represent a nadir in breastfeeding rates… But, for whatever reason, it is a fact that breastfeeding rates were much lower in the 1970s than in the decades before, and lower than they are now [2007].” (S)

In addition, since oxytocin is also required for parturition, and there is a negative correlation between caesarean section and breastfeeding rates, this enforces the presumption that breastfeeding statistics would correlate with the mother’s oxytocin levels. (Blanks & Thornton, 2003​53​)(Hobbs et al. 2016​54​)(Smith, 2007​55)​

As for the connection between child the child nurture intensity, Generation X, a 2nd generation, was born during 1965-1983 (estimations slightly differ between Western nations and but also between generational historians) and would, according to the Strauss-Howe generational theory, be a 2nd generation that received underprotective nurture. (S) Parent’s high oxytocin rates lead to more affectionate/intense nurture, and low oxytocin rates lead to less affectionate/intense nurture. (Gordon et al., 2010​45​) The Australian breastfeeding, which are probably more accurate than the US statistic (that are comprised of three different sources), illustrates that rates are at the lowest point during the birth of Generation X, which correlates with low nurture intensity, and this is presumably due to low oxytocin levels in the parents. (Gordon et al., 2010​45​)(S) The Strauss-Howe generational theory’s nurture intensity is lowest for the 2nd generation, and the Generation X in Australia was born in 1965-1983.

The statistical evidence therefore supports the presumption that the Strauss-Howe generational theory’s 80 year nurturing intensity cycle is actually a generational oxytocin cycle with a span of 80 years. Maternal/paternal age, divorce rates and alcohol consumption rates reviewed next add more support to this claim.

2.3.3 Oxytocin and maternal age

Higher oxytocin levels have been linked to higher maternal age. (Erickson et al., 2019​56)​ Taking the years 1970-75 as the presumed low point for oxytocin levels like with the breastfeeding statistics, there seems to be a high degree of correlation: the UK (S), Canada (S), Australia (S), Denmark (S), Austria (S), the US (S)(S), the Netherlands (S), Norway (S), and France (S) all show very similar statistics with low points occurring close to the year 1970. (In the US the lowest point was actually closer to 1965, but the curve starts to go up close to 1970-75.) Japan is showing a similar but less pronounced effect (S) with only a minor decrease in maternal age, but the breastfeeding stats are also less varied in Japan when compared to other nations where stats are available.

The similarity between these statistics is very apparent, and they also share a high degree of similarity with the breastfeeding charts. If these proxy statistics indeed do indicate oxytocin levels, it would implicate that the average age of motherhood may be strongly modulated by oxytocin levels.

What is possibly even more important to note is that the statistics display that physiological and behavioral effects of oxytocin go hand in hand, indicating that hormone levels have a large impact on the decision of at what age to have children, something that is normally considered to be a very personal decision. Since parenting intensity is also linked to these same curves, it enforces the idea that generational oxytocin levels modulate both behavior and physiological effects at the same time.

Previous statistics have taken only mothers into account, but the statistic below of average paternal age show yet again a very similar curve when compared to the maternal age and breastfeeding statistics. (S) Men become fathers being a few years older than women on average, which is why the stats lag a few years from the statistics of maternal age. (S) The graph is very similar to the maternal ages presented before with the lowest point being during the 1970s, with only a few European countries lagging behind: Russia, Poland, Hungary, Estonia, Czech Republic from the east and Spain from the south. (S)

Mean paternal age in European countries. (S)

Having children later in life is very similar to the lemming cycle, since they reproduce later (and less) during the peak phase of their cycle (Erlinge et al., 2010​57)​ , their peak being roughly equivalent to a 4th turning. In human studies higher baseline levels of oxytocin has been attributed to higher prevalence of infertility, which implicates that reproductive systems are less efficient during high levels of oxytocin, that being again during the 4th turning. (Lui et al., 2010​58​) (Chapter 5.1 addresses issues related to sex hormone levels and fertility.)

As for other possible explanations why the maternal age has risen from the 1970s, a commonly held belief by many in the field of sociology is that labor force participation percentage of females would somehow affect the age when women have children. But looking at longitudinal statistics from the US, Canada, and the UK, it is quite evident that these statistics have little in common with the other statistics presented in this chapter. This implicates that the commonly held belief of female labor force participation affecting maternal age is likely a false belief. Long-run perspective on female labor force participation rates, 1890 to 2016. (S)

2.3.4 Oxytocin and divorce rates

Divorce rates are presumed to be connected to oxytocin levels, as studies show that lower oxytocin levels correlate with higher divorce rates. (S) Lower oxytocin levels lead to higher rates of break-ups in non-married couples as well. (Sunahara et al, 2019​59)​ Therefore it is not a surprise to see the start of the 1970s to witness a large increase in divorce rates in many Western countries as the statistics below illustrate, because that is also approximately the low point in the oxytocin levels as indicated by the breastfeeding initiation charts. Statistic from the U.S. suggest that average oxytocin levels for married couples were at their lowest point at around the 1970s and then went higher again during the 1980s.

Legislative restrictions held back the divorce rates in countries like Australia ( S) and New Zealand (S), which explains the very clear spikes in divorce rates once those legislative bottlenecks were removed. This is a good example how a demand for something through low/high hormone levels can create demands for new legislation.

In addition to the divorce rates increasing, the percentages for marital quality dropped at the same time: “…marital quality fell during the ’70s and early ’80s. In the early 1970s, 70% of married men and 67% of married women reported being very happy in their marriages; by the early ’80s, these figures had fallen to 63% for men and 62% for women.” (S) The Strauss-Howe generational theory states that a 2nd generation is born and receiving underprotective nurture during these years. It should be noted that there was also an increase in marriage rates in the 1960s and 70s, but the divorce rates increased relatively more. (S)

Divorce statistics should be further divided into different age groups to find possible differences in the generational oxytocin levels. The graph below from the U.S. shows that divorce rates have gone down for younger generations and higher for older generations (S), and it supports the assumption that oxytocin levels are higher for Millennials and Gen Z. In the 1970s divorce rates rose for all generations, but divorce rates rates stabilized once the years those couples had children on average passed the year 1975. For example, a couple aged approx. 40 years in 1990s were born in 50s, had children in the 70s, and then high rates of divorce in 90s. But a couple aged 35 years in 2000s were born in the 60s, had children in the 80s, and then about the same divorce rates than a decade before.

It is therefore important to note that the older generations, whose children were born before the 70s, slowly if ever recovered from the divorce rate boom. But the younger generations did “recover”, not continuing the trend set by the older generations. The chart implies that higher breastfeeding rates (higher oxytocin levels) correlate with lower divorce numbers, but the effect is weaker for generations that are older when oxytocin levels rise for new children. According to the most recent studies, the total divorce numbers are still going down due to the low divorce rates among the youngest generations (S) and their marriages are steadier compared to the older generations (S) which is also an indicator of them having higher oxytocin levels, since high oxytocin levels promote monogamy (Scheele et al., 2013​60​/S) and other attributes that contribute to maintaining a stable marriage. (Schaer et al., 2009​61)​ It should be noted that divorces have been found to spread through social circles ( McDermott et al., 2013​62)​ , and since social circles largely consist of people in the same generation, this is a good example of how generations gain unique social traits through generationally varying oxytocin levels and how social interaction – through communication in one form or another – enhances those traits.

2.3.5 Oxytocin and alcohol consumption

Alcohol consumption statistics should reveal changes in historically varying oxytocin levels because alcohol and oxytocin have similar effects (Mitchell et al., 2015​63​), and oxytocin has been shown to inhibit the effects and lessen the cravings for alcohol. (Bowen et al., 2015​64​)(King & Becker, 2019​65)​ If these studies are accurate, then low oxytocin levels could lead to higher alcohol consumption and higher oxytocin levels could lead to lower alcohol consumption in the population. The Fourth Turning book states the following about per capita alcohol consumption rates following the 80 year generational cycle: “They begin rising late in a 1st turning, peak near the end of the 2nd turning, and then begin a decline during the 3rd turning amid growing public disapproval.” The graph below shows that the 3rd turnings in recent centuries (1830-1850 and 1910-1930) indeed saw large sudden decreases in per capita alcohol consumption.

Per capita alcohol consumption in the US form 1710 to 1970. (S)

Just like with the changes to divorce legislation, the prohibition laws in many Western nations in the 1910s and 20s display how higher or lower hormone levels have effects on legislation. (S) Two more statistics are available from the 19th and 20th century, and both show similar behavior in alcohol consumption: low points of alcohol consumption are in the 1840s and 1920s when compared to the previous decades in the UK (S)(S) and the Netherlands (S).

There was once again a similar drop in the alcohol consumption 80 years after the low point of 1920s, as roughly the year 2000 was a low point in the U.S. alcohol consumption, preceded by a high point in the 1980s. (S) Most Western nations show this same pattern of year 2000s having lower alcohol consumption rates compared to the 1980s. (S) Especially adolescence alcohol consumption has greatly gone down for the last two decades in the Western nations (S)(S)(S), while Boomers’ consumption has gone up in several nations. (S)(S) These statistics are directly in sync with the previously made presumption that the younger generations (Millennials, Gen Z) have higher oxytocin levels than the older generations (Boomers, Gen X). But the trend for adolescents should be turning around 2020-2025 according to this the generational hormone theory, and first signs of this are possibly already showing for instance in Sweden. (S)

All the alcohol statistics presented point to the fact that the Strauss & Howe were correct in their observations and that the overall alcohol consumption drops sharply once the 3rd generation is being born. (S) It should also be pointed out that the sudden drops in alcohol consumption rates takes about 10 years, just like the breastfeeding rates go up in about 10 years, and some breastfeeding statistics show quick movement upwards towards the late 1990s like in Norway and the US.

Dopamine levels should be also taken into account when looking at alcohol consumption rates, and this is reviewed in chapter 2.3.1. It is presumed that low dopamine levels drive up the alcohol consumption, which peaks close to the beginning of the 3rd turning (close to the year 1990 in this cycle), and then starts a sharp decline that ends before the 3rd turning comes to a close.

2.3.6 A model of generational oxytocin levels

Below are the presumed levels of oxytocin on a societal level compiled to a graph. All data points are not available from all centuries listed, but at this point, are assumed to be similar. The graph demonstrates the societal effects of oxytocin, which are presumed to be linked to new mothers, which is why the presumed birth cohort levels can be found by going backwards by about 30 years. (A more detailed explanation on this is located in chapter 2.4.) Levels at birth can be calculated by going back roughly 30 years from the years listed below. The percentages are only rough assumptions based on the vole study presented in chapter 1.1.

If the curve is accurate, oxytocin levels among new parents will start to go down during the 2020s, it is likely that breastfeeding rates and maternal and paternal age will also go downwards. In the 21st century oxytocin is given as a nasal spray at hospital for mothers that are unable to breastfeed after giving birth, which may skew some statistics from the 21st century. But there are statistics implicating that breastfeeding rates in some countries like Sweden may have already started to slowly go downwards after 2005. (Ericson et al., 2016​66​)

2.4 Historical dopamine and vasopressin levels

2.4.1 Dopamine levels

While oxytocin levels modulate social coherence in the context of family, friends, and other small-scale social connections, dopamine modulates group coherence in large-scale social networks. (Pearce et al., 2017​67)​ Dopamine modulates an individual’s feeling of being a part of a large-scale social network like a political party, religious group, or a nation. The feeling of belonging to an in-group is stronger for an individual that has high levels of dopamine, and the feeling is weaker for an individual that has low levels of dopamine. Therefore a society experiencing high levels of dopamine would exhibit high levels of group coherence, leading to higher levels of in-group favoritism and out-group derogation.

Although there is no direct way to measure the brain’s dopamine levels, low dopamine levels predispose an individual to having learning problems, impulsive and aggressive behavior, and proneness to substance abuse and addiction. (Chester et al., 2015​68​)(Leyton & Vezina, 2014​69​) (Gold et al., 2014​70​)(S)(S)(S) Therefore birth cohorts exhibiting these behavioral traits should indicate low levels of dopamine. Strauss & Howe have noted that birth cohorts from 1961 to 1964 display the kind of behavioral traits mentioned above, even though they have not been able to connect the traits to low dopamine levels in the 1990s, because back then the effects of dopamine were not understood as well as they are today. The chart from Generations (1991) illustrates how the birth cohorts from the early 1960s fare poorly at school, show high levels of addition to substance use, and exhibit various impulsive behavioral traits. (S) behavioral traits. (S)

As for criminal behavior, the peak in crime statistics occurred 3o years later after the early 1960s as the 1980s and 90s show a distinctive peak in crime rates in the majority of Western nations, and the reasons for this still largely remain ‘a mystery’ to researchers who have been studying the closely concurrent phenomenon in different countries. (Tonry, 2014​71)​ (Lappi-Seppälä & Lehti, 2014​72)​ (S)(S)

Rate of violent crime in the US peaked in 1991. (S)

Rate of crime in Canada peaked in 1991. (S) Rate of crime in the UK peaked in 1995. (S)

The Strauss-Howe generational theory states that a noticeable increase in crime happens during a 2rd turning, and the crime rates start to drop during the 3rd turning, and they stay relatively low during a 4th turning (exception: hate crimes usually become more common during a 4th turning), and the statistics from the current cycle confirm their premises regarding crime at different phases of the 80 year cycle. Since most of crime is committed by individuals during young adulthood, and crime peaked in most Western nations in the early 90s, it would mean that the lowest levels of dopamine are found in the birth cohorts born during the 1960s.

Impulsive behavior is connected to a low resting heart rate (Portnoy et al., 2014​73​)(Baker et al., 2008​74​), and it is considered to be the best-replicated biological correlate of antisocial behavior. Since low dopamine levels result in lower resting heart rate and lower blood pressure. (Ziegler et al., 1985​75)​ Violent and non-violent criminals have been found to have a lower heart resting rate and lower blood pressure compared to the population as a whole. (Latvala et al., 2015​76​)(Murray et al., 2016​77)​ (Culpepper & Froom, 1980​78​) Low resting rate has been linked to anti

As the feeling of social detachment from the larger community presumably increases with low dopamine levels, it becomes easier for the individual to break the common rules, that being the written law, and also the unwritten social rules of a society.

And as with the proxy statistics for oxytocin, Russia lags about 15 years behind the US in the crime rate statistics with a clear peak in the mid 2000s. Rite of crime in Russia. (S)

These statistics of mid-cycle aggressive behavior are also in line with the observations regarding many animal populations during the mid-cycle (2nd and 3rd phases): “animals in high-density phases are much more aggressive than those in low-density phases.” (Oli, 2019​10​) (Matthiopoulos et al., 2002​79​)(Piertney et al, 2008​80)​

As for dopamine’s effect on alcohol consumption, chapter 2.2.5 already established the fact that the Baby Boomers (a 1st generation) have the highest rates of alcohol consumption, but the statistic below from the UK shows how the birth cohorts from the early 1960s also have the lowest levels of abstinence.

Birth cohort percentage of men (cubes) and women (triangles) abstainers in the UK. (Meng Birth cohort percentage of men (cubes) and women (triangles) abstainers in the UK. (Meng et al., 2013​81)​

As for dopamine’s effect on learning, looking at SAT scores in the US, it is clear that the birth cohorts from the early 1960s have the worst test scores, since the SAT test is taken at the age of 17 or 18.

SAT math scores statistic illustrates the poor test results from the birth cohorts of the early 1960s. (S)

The UK statistics show similar results of increasing test scores in the late 1980s and then reaching top scores around the year 2010. (S)(S) The years 2009-2012 represent the top in the OECD Pisa test scores in each category that are reading, math, and science. (S) (The OECD is comprised mainly of European nations. (S)) Combining all these results mean that the worst performers in school were born close to the year 1960 and the best performers were born close to the year 1990. It should be noted that dopamine obviously is not the only hormone affecting educational performance, but it does have an effect on memory, learning, motivation, and concentration. (S) This means that test results cannot be used very reliably as proxy statistics, but do correlate with the presumed generational dopamine levels at least to a small degree.

The listed proxy statistics for presumed dopamine levels regarding criminal behavior, alcohol consumption, and educational performance are put together in the graph below. While it is true that the test scores reached their peak for birth cohorts born in early 1990s, the teenage alcohol usage statistics have started to level off only in the recent years, indicating that the birth cohorts with the highest dopamine levels could be closer to the year 2000. (S)(S) The percentages are only rough assumptions based on the vole study mentioned in chapter 1.1. Societal effects manifest roughly 25-30 years later after a cohort is born as is presented in the next chapter. (Note: The curve above should be slightly sharper at the bottom.)

2.4.2 Group coherence and territoriality

This chapter presents how varying dopamine levels affect the strength of group coherence and vasopressin levels affect territoriality. Vasopressin levels may not detectable from historical statistics in a similar way as oxytocin and dopamine, but seasons of heightened nationalism seem to go hand in hand with increasing group coherence, thus the presumption that the generational vasopressin levels go hand in hand with the dopamine levels.

Placing dopamine in the center of human social evolution is actually not a novel idea, since it

​82​ has been suggested before. (Previc, 2009​82​) In addition, a recent study enforces this idea, because what sets humans apart from other apes is abnormally high levels of dopamine: “However, in line with another recent study on gene expression, humans had dramatically more dopamine in their striatum than apes… Humans also had less acetylcholine, a neurochemical linked to dominant and territorial behavior, than gorillas or chimpanzees. The combination “is a key difference that sets apart humans from all other species”… Those differences in neurochemistry may have set in motion other evolutionary changes, such as the development of monogamy and language in humans… As human ancestors got better at cooperating, they shared the know-how for making tools and eventually developed language—all in a feedback loop fueled by surging levels of dopamine.” (Raghanti et al., 2018​83/​ S/S)

During vole population peak years, that being the 2nd and 3rd phases, immigration increases, territory boundaries are reduced, and co-existence with other species of voles increases. (Johnsen et al., 2019​18​)(Tähkä et al., Endocrine aspects of population regulation in the genus Clethrionymus, Mem. Soc. fauna Flora Fenn., 1984) In human populations this kind of behavior would mean that the 2nd and 3rd turnings are more cosmopolitan eras of low nationalism and group coherence, which would be the years 1970-2010 in the current cycle.

During the last year/quarter of the vole cycle, group coherence and territoriality increase. Group coherence, territoriality, and nationalism have risen in many Western nations during the past 4th turnings: 1930-1950, 1850-1870, and 1770-1790 have witnessed it, and in 2010-2030 the same thing is very evidently happening again. Going further in history, during the 4th turning of 1690-1710 there was a movement towards increased centralized power of kings and the Pope, even though the concept of a nation was not yet largely adopted in Europe. Even the 4th turning years of 1610-1630 were “nationalistic” and had populistic tendencies (chapter 4.3 has more on this). These event are taken into account in the graph below, which represents both the presumed dopamine levels affecting group coherence (levels at birth were presented in the previous chapter 2.3.1) and presumed vasopressin levels affecting territoriality. The 4th year is also when the cyclical vole populations see increasing territoriality and decreasing co-existence with other vole species. ‘Group coherence and territoriality’ largely reflects the political/ideological uprisings/revolutions, which are often occurring during or close to the 4th turnings. The percentages are only rough assumptions based on the vole study mentioned in chapter 1.1.

To further elaborate the effects of dopamine, the graph below illustrates the effect to group coherence in a society when the levels of social hormones are either low or high. The circles represent figurative outer limits of social, ideological and cultural norms. The out-groups left outside have historically often been immigrants, Jews, and other cultural and ideological minorities, suspect of ending up as scapegoats for many societal problems when demands for tighter social coherence increase. The spots can represent either individuals or groups (depending on the scale).

Strauss & Howe write about tightening social (group) cohesion being a part of a 4th turning and that keeping good social relations within one’s existing social circles is important, because those individuals who are shunned outside social circles will end up without much social support as the social coherence tightens. (More on group coherence and scapegoating in chapter 4.) Quick examples of increasing group coherence in civic life during the current 4th turning are the “PC culture” and MeToo-movement. These movements have been about enforcing tightening unwritten in-group rules, but the new tighter rules have also been enforced through the justice system, which represents the written rules. Together these written and unwritten rules form an in-group’s behavioral and ideological boundaries, and these boundaries are tighter in a 4th turning due to increased group coherence.

The PC culture became mainstream during the 2000s and has become stronger ever since, evolving into an outrage culture (aka. cancel culture). It began as an movement to tighten in- group rules to be more inclusive of out-groups, but ever since the ideological spectrum widened during the 2010s, it became a movement primarily in the left-wing ideological in-group. The MeToo-movement was founded in 2006, became mainstream in 2017, and spawned a multitude of other call-out movements aimed at reducing many old behavioral traits that were deemed bad towards others in an in-group, but were more tolerated during the 2nd and 3rd turnings. The call-out culture has been spreading through the Western nations quickly, and those who have not complied with the new social rules have been shunned out of social groups, just like Strauss & Howe predicted three decades ago.

Another example of this tightening in-group coherence is the destruction of statues that represent figures from the past that, in their time, have had opinions that are no longer tolerated at all, like statesmen who were proponents of slavery. Books and other platforms presenting the opposing side’s ideals may be banned or destroyed. This is the same behavior that is often witnessed after a war has ended: the winners write the history, and the losing side’s institutions are molded to represent the winning side’s ideology.

Higher vasopressin levels are associated with nationalism and territoriality. (Caldwell, 2017​84)​ (S) Territoriality is essentially national in-group defense against out-groups. The two graphs below represent a simplified expression of higher and lower group coherence (dopamine) and territoriality (vasopressin) effects in history of the Western cultures, especially in the U.S., and how it affects group coherence. The idea is not to suggest that hormone levels have caused any of these historical events, but if dopamine and vasopressin levels have been higher during certain eras, it might have facilitated some eras and event that display a low/high degree of group coherence.

The blue line represents presumed high/low dopamine (group coherence, etc.) and vasopressin (territoriality, etc.) effects.

The blue line represents presumed high/low dopamine (group coherence, etc.) and vasopressin (territoriality, etc.) effects. Populist nationalism tends to be higher during the 4th turnings, but there has been populism during other turnings too, like the Jacksonian populism in the US, but it occurred only in the US. When group coherence increases, the demand for institutions grows, since institutions are what binds the individuals in a society together. Institutions represent feelings of individuals as moral values in their rules and aims. (More on this in this video from a MIT professor in psychology.) The Strauss-Howe generational theory states that institutions peak in power during the 1st turning, which is when the social coherence is also the strongest, before it starts to decline again. Institutions enforce the common rules through the rule of law, but also through other means of influence. If the institutions do not represent the general will, aka ‘volonté générale‘ like Jean-Jacques Rousseau called it (S), there may be a revolt to overturn those institutions, something that has often happened during the 4th turnings in history. (Chapter 4.2 explains the three basic paths societies usually take during eras of increasing group coherence.)

Institutions are basically “stable, valued, recurring patterns of behavior”. (S) Institutions on general can be divided into public (government and laws), private (companies and organizations), and cultural institutions (common traditions and language). Cultural advances largely rely on functional institutions. When taking a long historical perspective, the largest and most influential expansive empires and dynasties, with a common culture that is enforced by institutions, have existed in and spread on from the northern latitudes of 30 to 70, which is also where the cyclical animal populations exist: the Roman Empire, the British Empire, the Mongol Empire, the Ottoman Empire, the Spanish Empire, the French Empire, the Achaemenid Empire, the Macedonian Empire, and the dynasties of Ancient Egypt and China’s to name a few.

There are many ways to sort empires by influence, but here the strength of institutions (including social institutions like languages and cultural traditions) and expansive growth are given a priority, since they fit the model of cyclical evolution; eras of low and high social coherence and territoriality. As for empires in the tropic, the Mayan and Aztec empires were not very expansive, and African cultures have been quite lacking in institutions that would have made the empires and their legacy more permanent. And to this day, the majority of sub-Saharan African nations, and many other nations located in the tropic, have comparatively weak and dysfunctional institutions. (Nganje, 2015) These kinds of assertions are obviously extremely speculative, but examples from history do show a tendency for the northern latitudes to have stronger institutions on general compared to the tropic.

While at first it may seem overly simplifying to equate human populations to other animal populations, it should be stated that the modulating power of hormones on behavior is strong. (Oliveira, 2009​85​) If humans were able to resist their urges that are due to hormonal activity, there would probably be no obesity epidemic, addictions like smoking and drugs would be easy to end, people could override their emotions when making decisions, women would not experience changes to their mood during different stages of their menstrual cycles, and individual and group behavior during puberty would be more rational when compared to behavior before and after puberty. (S)

2.5 Generational social hormone levels 2.5.1 A model of generational social hormone levels

This (unfinished) chapter contains the proposed model of generational cyclical oxytocin, dopamine, and vasopressin hormone levels. The graphs are based on previously presented breastfeeding, maternal age, divorce rate, and alcohol consumption statistics for oxytocin, and historical observations of increasing and decreasing nationalism (or other manifestations of high societal in-group cohesion) for dopamine and vasopressin, that is the more aggressive variant of the social hormones regarding territorial aggression. (Caldwell et al., 2008​86​)

Since the breastfeeding statistics appear to share a similar historical curve with paternal age and parenting intensity, it is likely that the size and efficiency are shared between the hypothalamic neurons secreting hormones to both the brain and blood circulation. Below are all the proxy statistics combined as has been presented in the previous chapters, now forming a generational hormone cycle.

Theoretical average birth cohort specific hormone levels in Western nations, backed up by statistics that are presented in chapter 2. ‘Sex hormones’ represent presumed gonadotropin-releasing hormone levels.The ‘growth hormone’ curve represents the presumed levels of the growth-hormone-releasing hormone that is secreted by the hypothalamus.

Below is the same graph but as societal effects of the hormones, as they come into effect some 30 years later after a cohort is born. Presumed generational hormone levels of parents (the birth cohort levels from roughly 30 years earlier are presented later in this chapter). The percentages are only rough assumptions based on the vole study mentioned in chapter 1.1.

The generational hormone levels presented in the graph above are presumed to spread among populations, but the presumed mechanism is not known yet. Research done on couples demonstrates hormonal synchronization to be an occurring phenomenon (S)(S), as smelling sweat for instance has been shown to alter hormone levels (Wyart et al., 2007​87​), meaning that sweat works as a chemosignal similarly to pheromones found in other animals like moths and mice. This assumption is enhanced by the fact that nasal administration of oxytocin and vasopressin does increase their behavioral effects, but as hypothalamic hormones are likely released into brain areas straight from the hypothalamic neurons (S), it could mean that the hypothalamus is stimulated to secrete oxytocin and vasopressin by the main olfactory cortex (S) once it detects the chemosignals in the air via the olfactory bulb.

A study done on a red grouse populations showed that injecting testosterone into some males would result in increased testosterone levels in the other males living in the same area. (Vergara & Martínes-Padilla, 2012​88)​ Interestingly enough, the comb size increased on the individuals receiving injections, but not on the other males, even though they too had elevated testosterone levels. Increases in testosterone levels increased aggressive behavior, meaning that the increased testosterone levels that “spread” from the individuals receiving injections had behavioral but not physiological effects. This would mean that even some individuals or perhaps those in reproductive ages could be the “primers” that affect the hormone levels of an entire population. But only regarding behavioral aspects, as the physiological aspects of hormones would still be determined by the birth hormone levels. This is obviously highly speculative, but would explain why the ‘social mood’ changes during the 80 year long Strauss-Howe generational cycle even though the presumed hormone levels received at birth would not change physiological traits. (This part will be revised when the hypothesis is more complete…) In addition, it has been found that during the peak phase in population density in the red grouse population cycles (marking the middle phases of the population cycle), their comb sizes are at their largest, accompanied by aggressive behavior (by a minor lag). (Piertney et al, 2008​80)​ This makes it likely that their testosterone levels are elevated from the beginning of the cycle, and evidence of this same phenomenon occurring in other populations and human populations is presented in chapter 2.6.1.

Hypothalamic structural plasticity has been observed for example during the menstrual cycle and periods of lactation, displaying that the structures inside the hypothalamus are able to change in size and efficiency quite rapidly. (Baroncini et al., 2010​89​)(Theodosis et al., 1986​90​)

Since nasally injected oxytocin and vasopressin increase the behavioral traits of these hormones, it would be logical to assume that the mechanism is the same with human interactions: oxytocin in the air reaches the nose and triggers neural oxytocin release into the brain. It would also explain the occurrence of cross-species adoption, nurture and even lactation without the adopting “parent” ever being pregnant (Carzon et al., 2019​91)​ (S), and this is theoretically entirely possible since oxytocin serves the same functions for different mammal species. (Lactation also requires for example estrogen-mediated prolactin secretion, so the suggested airborne oxytocin transportation would obviously be only a one part of the suggested mechanism. (S)) Animals taken out of a population – that is undergoing a cycle – into laboratory end up developing differently regarding their endocrine system, which suggests that the development is regulated by a biological mechanism involving proximity, making the chemosignals a potential candidate.

Another explanation for the generational hormone levels, and currently looking to be the much stronger candidate, would be an oscillating developmental cycle, where the year of birth during the cycle determines the starting hormone levels (=generationally varying hypothalamic neural size and efficiency, but all generations still undergo the same pattern of fluctuating hormone levels – only the starting point differs between generations. But for the moment, the exact mechanism is still unknown.

It is theoretically possible that the hormone secretion from the paraventricular nucleus of oxytocin, vasopressin and CRH into the bloodstream solely modulates all of the hormone levels (some of which are presented in the following chapters), since these hormones work as antagonists for sex hormones (blocked by oxytocin), growth hormones (blocked by CRH and dopamine), and dopamine (increased by vasopressin).

In this situation the hypothalamic hormone levels would oscillate according to oxytocin, vasopressin and released from the paraventricular nucleus.

Whatever the mechanism is, it is likely that the biological clock keeping time of years is linked to the yearly changes in light periods (and possibly changes in light intensity and temperature. Like previously stated, the cyclical species are almost solely located in the northern 30 to 70 degrees latitude, where the mentioned annual environmental changes are noticeable when compared to the tropic. Hours of light each latitude receives annually per day. (S)

There is evidence from cyclical populations that the cloudiness of a winter may dampen the cyclic dynamics, and also of a possible timing mechanism driven by the 9.3-year nodal half- cycle of the moon. (Archibald, 2014​92)​

Going back to the plasticity of the hypothalamus, there have been studies on human hypothalamic neurons that secrete oxytocin, and those studies show that age and/or birth cohort has an impact on the neuron size and efficiency. (Ishunina & Swaab, 1999​93​) What these studies unfortunately do not show is the specific birth cohort/generation information, and this data would be required to assess if the generational size of neurons coincide with the theoretical generational hormone cycle. But what the linked study does show is major differences in those areas of the hypothalamus that both produce and secrete oxytocin and vasopressin. For example, the older women in this study have over 60% larger volume in vasopressin secreting neurons than the younger women.

As an further example of generational hormone levels, a 3rd generation show traits of high oxytocin levels, like higher amounts of prosocial cooperation (De Boer, 2017​94​) compared to a 2nd generation, which is ‘abandoned in old age’ according to the Strauss-Howe generational theory. This is happening likely due to them not creating and fostering as many friendships and other strong social bonds during their lifespan compared to a 3rd gen. The Strauss-Howe generational theory states that the 2nd generation is the least social and the 3rd generation is the most social generation. These phenomena are explained through generational oxytocin levels, because oxytocin promotes pro-sociality.

Childhood seems to be a time of impact for how an individual’s hormone levels affect the behavior for the entire lifespan: “Miller and Caldwell (2015) suggested that Oxytocin has an impact during critical developmental stages for humans in regards to hormonal changes, specifically prenatal, postnatal and peripubertal stages of life. Manipulation of Oxytocin during these stages could affect adult behaviour by altering neural structure and function.” (Power, 2015) As young individuals spend most of their time with children inside their own birth cohorts, like at school and other activities, the generational behavioral traits are amplified through social synchrony. (Fitzpatrick et al., 2018​95)​

It has been widely speculated why so many couples stayed together during the 1930s Great Depression, and one popular idea is that couples could not afford to move apart. But the answer could be very simple: oxytocin levels were high at that time, and because oxytocin is needed to bind couples, families, and other groups together. The 1970s oil/economic crisis seemed to cause a lot of divorces, but as the oxytocin levels were presumably at a low point at that time in history, the stress inducing economic difficulties were efficient in breaking up marriages. And during the 2007/2008 Great Recession the oxytocin levels were presumably high once again, thus the divorce rates did not spike due to economic distress.

The changing social mood in the Strauss-Howe generational theory is basically explained by the changing societal hormonal levels, because hormone levels alter an individual’s mood. For example, during the 20th century transition from 1st to 2nd turning, when the vasopressin levels dropped, war protests broke out all over the Western nations in the 1970s, and this attitude change could also be observed in how war veterans were treated in the Western nations, suddenly having societal shame cast on them by the general public. The situation has changed during the 21st century once the average vasopressin levels have presumably once again started to rise higher. This example demonstrates how the social mood changes to be more supporting of peace due to generally lower vasopressin levels and vice versa. Therefore the changing social mood in the Strauss-Howe generational theory can be basically explained by varying social hormone levels in a society, since hormone levels affect mood.

The average generational hormone levels can be assessed by going backwards about 30 years from the proxy statistics presented previously. Presumed oxytocin, dopamine, and vasopressin levels at birth. The percentages are only rough assumptions based on the vole study mentioned in chapter 1.1.

On average, at birth: 1st gen has low oxytocin, dopamine, and vasopressin levels; 2nd gen has high oxytocin but low dopamine and vasopressin levels; 3rd gen has high oxytocin, dopamine, and vasopressin levels; 4th gen has low oxytocin but high dopamine and vasopressin levels.

The cyclical pattern of the social hormones resembles the vole hormonal pattern (presented below) during different phases of their generational population cycle. (Vladimirova et al., 2006 13​) When comparing the proposed human generational hormone cycle to an animal cycle, a similar curve can be drawn to the SON portions of the vole cycle. It should be stated again that percentage levels in the human cycle were assumptions based on the vole study, which is why the curves look similar. The intention is not to present potentially misleading information, but only to point out that there is resemblance in the highs and lows between the vole cycle and the generational hormone cycle of human population, as even by adding both the hormone values of PVN and SON together would result in a similar graph regarding the high and low points.

Oxytocin and vasopressin levels during the vole population cycle. (Vladimirova et al., 2006​13​) The lines are only presumed lines, not actual measurements, but instead drawn to illustrate how the hormone levels are similar to human birth cohorts’ presumed hormone levels. The human generations born during the “peak” in this graph reach adulthood during the 4th turning, which coincides with the presumably high vasopressin levels.

2.5.2 Social hormones and political ideology

This chapter presents a possible close connection between the social hormone levels and political ideology, since there seems to be noticeable connection between voting behavior and the presumed social hormone levels. It should be stated that linking ideology and the social hormone levels was never a goal for this hypothesis, but like much of this hypothesis, this possibility has arisen by chance.

The left vs. right ideological spectrum is still the fundamental political divider in Western nations, but especially in the US, where the divide is very clear with two major parties presenting the left vs. right political divide in major societal issues. Most of the central arguments on important issues like tax rates, welfare, gun rights, etc. can be drawn from the basic attitude towards the society: on average, individual rights and responsibilities (aka. self reliance) are more important for the right-wing voter, and shared rights and responsibilities (aka. the common good) are more important for the left-wing voter.

It could also be said that even as all humans are capable of empathy, the circle of empathy is different between the left-wing and right-wing voters: left-wing voters tend to have a circle of empathy that usually covers minority groups such as immigrants and the least wealthy, and in comparison, the right-wing voters have a slightly tighter circle of empathy that is usually more centered on those who are the most beneficial to the society and thus increase the society’s success when competing against other societies. Although these terms are in no way exclusive to either side, left-wing voters tend to identify themselves as more of citizens of the world and the right-wing voters tend to identify themselves as patriots. (This is a coarse characterization, and should not be taken as anything else than that.)

Therefore it could be theoreticized that higher levels of social hormone effects manifest as more left-leaning ideological behavior, since higher levels of social hormones leads to increased prosocial behavior. Lower levels of social hormones leads to less social behavior and increased self reliance, thus the presumed inclination to lean right.

A clear connection between oxytocin and ideological behavior seems to be that oxytocin increases openness to experiences in individuals (Cardoso et al., 2011​96​)(Pearce et al., 2019​97​), and simultaneously openness to experience has been found the be the most consistent indicator of ideology: “Our findings show that, in line with the congruency model of personality, Openness to Experience is the best and most consistent correlate of political ideology, with politicians high on Openness to Experience being more likely to be found among the more progressive left-wing political parties.” (Joly et al., 2018​98​) This indicates that higher oxytocin levels may lead to a tendency towards a left-wing ideology.

Placing a divider so 50% of the cohorts with low/high levels of the social hormones are on both sides produces the chart below. The presumably right leaning birth cohorts were born approximately from 1930 to 1970, but there is a small short left leaning cohort born around the year 1950. Presumed oxytocin, dopamine, and vasopressin levels at birth, along with a line witch divides the generations with the low/high levels of social hormones. Each ideological side is allocated about 40 years, that being 50% of the 80 year cycle. The percentages are only rough assumptions based on the vole study mentioned in chapter 1.1.

And by adding a divider, to whenever either the oxytocin or the dopamine & vasopressin curve is at its lowest value, produces the following graph. A divider has been added to show what birth cohorts presumably have either the lowest oxytocin or the lowest dopamine & vasopressin levels.

The birth cohort voting preference curve in the graph (above) resembles curve the US voting trend by birth cohort (below). The voting statistics are very much in line with the presumption that generations born roughly from 1930 to 1970 tend to vote right, with a small leftist peak close to 1950, and the highest leftist peak is close to 1990 in both graphs. “The peaks and valleys occur in almost identical locations, strongly suggesting a generational trend.” (S) The y-axis represents political alignment on the left vs. right ideological axis, meaning that the higher the line goes, the more likely individuals in those birth cohorts are to vote left.

If the presumption is correct of social hormone levels affecting generational voting behavior, it would seem that low vasopressin and/or dopamine levels may have a stronger effect on the cohort leaning right than low oxytocin levels.

In addition to birth cohorts displaying ideological preferences, a well known dividing factor in the left vs. right political spectrum is the “urban vs. rural” divide, since generally urban voters lean left and rural voters lean right. (S)(S)(S) This implicates that breastfeeding rates are therefore lower in rural areas, which is confirmed by studies. (S)(S) (Since population density is lower in rural areas, this leads to speculate if individuals with less efficient oxytocin systems prefer a rural environment due to them being less socially active compared to individuals with highly functional oxytocin systems, who are living in urban environments.)

Another connection between oxytocin and political ideology is that oxytocin increases gaze cues (for emotional faces) (Tollenaar et al., 2013​99​), and since individuals leaning left have been found to follow gaze cues more than individuals leaning right (Dodd et al., 2010​100​/S), this adds to the evidence of high oxytocin levels being possibly connected to a left-wing ideology. The dopamine receptor system has been found to affect political preferences (through the receptor alleles), which enforces the premise that dopamine levels also modulate ideological preferences. (Hatemi et al., 2014​101)​ (Settle et al., 2010​102)​ But can the endocrine system directly modulate ideological preferences? The following study implicates that this is entirely possible.

“The phylogenetically ancient neuropeptide oxytocin has been linked to a plethora of social behaviors. Here, we argue that the action of oxytocin is not restricted to the downstream level of emotional responses, but substantially alters higher representations of attitudes and values by exerting a distant modulatory influence on cortical areas and their reciprocal interplay with subcortical regions and hormonal systems… Notably, a recent longitudinal epigenetic study detected a positive link between methylation of the OXT [oxytocin] receptor gene at birth and callous-unemotional traits at age 13, which corroborates the hypothesis of abnormalities in the oxytocin system as a core element of developmental pathways to callous-unemotional traits. These findings, together with the relationship between variations in common polymorphisms of the OXT receptor gene and antisocial behavior, and high callous-unemotional traits, all point to an involvement of the OXT system in upstream attitudinal representations… OXT also influences, and interacts with, representations of attitudes and values in more recently developed cortical regions…” (Hurlemann et al., 2017​103​)

What is important to note is that the study’s result “…corroborates the hypothesis of abnormalities in the oxytocin system as a core element of developmental pathways to callous-unemotional traits”, which are detectable by a persistent pattern of behavior that reflects a disregard for others, and also a lack of empathy and generally deficient affect. (S) These characterizations best fit the 1st and 2nd generations in the Strauss-Howe generational theory, and these generations lean ideologically mostly to right.

According to a recent study, voting is much less rational and more based on emotions than what has been previously thought to be the case.

“But how should we treat questions of control, free will, and responsibility, given the growing body of findings about the dubious value of conscious control? An interesting possibility is that humans possess some automatic control processes for socially relevant thinking and behavior, just as we have automatic control processes for autonomic regulation. Violent behavior, for example, is likely inhibited (for most people) through automatic control mechanisms that do not require one to stop and think about consequences. Emotions may play key roles in such automatic regulation of behavior. Moreover, the very associative memory processes that sometimes promote bias can work to prevent bias. Changes in attitudes and associations can be learned through classical or instrumental conditioning, just as prejudices and bad habits can be unlearned. Attitudes toward same-sex marriage, for example, have undergone rapid change over the past several decades, and it seems clear this cannot be fully explained through generational replacement. New beliefs and feelings have been widely adopted, and we believe it is unlikely this was the result of careful reconsideration of priors. It is much more likely, we think, that these new attitudes and considerations have formed unconsciously through direct and indirect experience and an increasingly consistent societal message of support for marriage equality. The most interesting and important questions about human behavior concern cause, responsibility, and control, but we do not yet have a satisfactory understanding of the basic underlying mechanisms that give meaning to these questions. Our research exploring automaticity in political-information processing and our dual-process theory that roots feeling, thinking, and doing in the associative architecture of memory is a valuable early step toward a process-valid model of political behavior… As it stands, JQP [John Q. Public Model of Political Information Processing] paints a very pessimistic view of human possibilities. We fear this portrait of “the cognitive monster” may be accurate, but we think control processes deserve more study. Our gut tells us this last optimism may be rationalization.” (Taber & Lodge, 2016​104​)

It should be noted that individual voting behavior is affected by a myriad of different factors such as who is leading in the polls (S), what images are seen shortly before the voting, etc. ( S) And like in all decision making, cognitive biases come into play. (S) Things like the ideological affiliations of college friends can also have an effect on voting behavior, but the effect is quite small, possibly due to the brain being already quite mature in young adulthood. (S) But even as these mentioned factors do play a role in voting behavior, they are not that significant when looking at population-wide statistics over a period of several decades.

2.6 Other hypothalamic hormone levels

2.6.1 Sex hormone levels

This chapter reviews the effects of the 80 year generational hormone cycle to the human reproductive system. Most Western nations have seen low birth rates during the 2010s and infertility is more common than before, and poor sperm quality is the cause in most cases. (S) Sperm counts have also decreased significantly during the past decades with drops of 50% in many countries during the past 40 years. (Levine et al., 2017​105)​ This has been accompanied by falling testosterone levels and the younger generations having less sex than the Baby Boom and Gen X generations. (Travison et al., 2007​106​)(S)(S)

Phase II generation below, roughly representing human birth cohorts who are in their reproductive ages during the first half of a 4th turning, shows greatly diminished size in the lemming gonadotropic cells, which has resulted in less sex hormones and therefore much smaller testes compared to the phase I and phase III cohorts.

Phase II in the lemming cycle represents roughly the first half of a 4th turning, and phase III represents roughly the latter half of a 4th turning. (S)

The same increases in both sex hormone levels and testicular size has been documented in the cyclical snowshoe hare populations, and the population decline phase is associated with lower levels of sex hormones. (Davis & Meyer, 1973​107)​ Human male testicular size is therefore presumably lower for the age cohorts in reproductive ages during a 4th turning, which would have a negative effect on sperm quality (Condorelli et al., 2013​108​) and testosterone levels, which is in line with the current situation in the Western nations.

For women, low estrogen levels can produce many of the same symptoms that low testosterone levels cause for men, like infertility and depression. (Weiss & Clapauch, 2013​109​)(S) Lower amounts of estrogen could be the cause for why this 4th turning has many childless women, just like 80 years ago in the 1930s when many women born in the early 20th century were childless, which the statistic below of childlessness by year of birth confirms.

Percentage of childless women by year of birth shows a high degree of synchrony across many Western nations. (S)

It should be noted that the curves between the countries correlate quite tightly, with Spain lagging by a few years with its low point, just like with Spain’s paternal age statistics (in chapter 2.2.3) were lagging by about 10 years when compared to statistics from the US and the UK. (This puts even more weight on the suggestion that Southern Europe has the same generational hormone cycle as Western Europe does, but they are lagging by about 5-10 years.) Austria and Switzerland also have very similar statistics regarding childlessness by year of birth with birth cohorts close to the year 1940 having the least amount of childless women. (Burkimsher & Zeman, 2017​110)​

If the statistic above indicates estrogen hormone levels, then it would mean that the birth cohorts born close to 1980, 1900, 1820, 1740, etc. have the lowest levels of sex hormones, which can lead to childlessness. Strauss & Howe note that over five centuries, every 4th turning has been marked by low birthrates, which correlates with the presented statistics, and also with the lemming hormone cycle study. (Generations, 1991)

In addition, when looking at birth cohort fertility rates, there is a striking similarity between the English speaking Western nations presented below. Although the trend has been downward for a few centuries, there is a clear bump upwards from the 1910 to the 1950 birth cohorts.

Birth cohort total fertility rates for women in Australia, Canada, New Zealand, and the US show very similar curves. (S) The peak fertility rate is close to the 1935 birth cohort in the US.

The birth cohorts with the highest levels of sex hormones were presumably born in the 1930s and 40s, which would help explain the significant baby boom of the 1950s and 60s that is displayed in the graph below. Spain is once again lagging by about 10 years behind others in this statistic, just like with the infertility rates and also oxytocin proxy statistics.

Fertility rates in the US, the UK, France (FR), Germany (DE), Switzerland (CH), Sweden (SE), and Spain (ES). (S) The peak is close to 1965.

As for the previous century, the changes in fertility rates are less pronounced in the US and the UK, that are presumably the two most likely cyclical nations, but the decades around 1880s are clearly above the trendline in the UK, and in the US, the source statistic does not show much variance in the 19th century. (S)(S) Many Western nations show a similar trend with the UK, as the decades after 1880s are generally decades of steep decline in fertility rates, while the previous decades have been more of a plateau (as a rough generalization). (S)

Putting together the proxy statistics of presumed testosterone and estrogen levels produces the curve presented below.

Birth cohorts with high fertility/infertility. The effects, both individual and societal, manifest roughly 25-30 years later when the cohorts are at reproductive ages. The percentages are only rough assumptions based on the vole study mentioned in chapter 1.1.

But why are there no clear population cycles in the Western nations if there would be a similar hormone cycle like in the cyclical animal populations? On average, humans today live to be much older than before (Gurven & Kaplan, 2007 ​111​), and if humans still lived shorter lives like human populations who lived in the wild/nature, this would be more easily visible in population numbers. But since most of the Boomers are still alive in 2020, the population numbers have not plummeted as much.

As for the societal effects of sex hormone levels, the curve in the graph above is roughly in line with the Strauss-Howe generational theory, which states that the gender gap between the reaches it is maximum width during a 1st turning, meaning that the gonadotropic cells are presumably once again more active and secreting more of sex hormones during that period of time (societal effects presumably manifest roughly 25-30 years later as the birth cohorts mature), reflecting phases I and II in the lemming cycle. Higher levels of sex hormones would thus explain the sexual revolution of the late 60s, when the sex hormone levels were presumably high, resulting in more sexual activity, especially among the young. (S)(S) Group coherence was loosening simultaneously, presumably due to decreasing dopamine levels, resulting in looser unwritten societal rules in the Western nations. (S) According to the Strauss-Howe generational theory, the gender gap is widest during a 1st turning, and this could be attributed to high levels of sex hormones especially in the birth cohorts in fertile ages during a 1st turning.

The presumed sex hormone levels are added below to the chart of generational hormone levels that are presumably received at birth (although especially sex, growth, etc. hormones start to be secreted more only once puberty hits).

Presumed oxytocin, dopamine, vasopressin, and sex hormone levels at birth. The percentages are only rough assumptions based on the vole study mentioned in chapter 1.1. The oxytocin and vasopressin curves have been slightly smoothed in order to better represent the oscillating hormone levels.

Apart from issues related to sexual behavior and reproduction, low testosterone levels have other significant impacts to male health, including a heightened risk for developing metabolic syndrome, type 2 diabetes, and coronary artery disease. (Goodale et al., 2017​112​) Low testosterone levels have also been linked to depressive symptoms in men, and according to a meta-analysis, testosterone treatments have resulted in significant reductions in depressive symptoms. (Walther et al., 2019​113)​

If the predictions about sex hormone levels are correct, fertility and birth rates will increase during 2020s and continue that trend during the 30s and 40s in the US and other Western nations.

2.6.2 Growth and thyroid hormone levels

Growth-hormone-releasing hormone, that stimulates growth hormone secretion, is secreted from the hypothalamus, meaning that if it is included in the presumed generationally fluctuating hypothalamic hormones, this would lead to changing body mass in animal during population cycles, since higher levels of growth hormone secretion leads to higher body mass. (Furigo et al., 2019​114/​ S) And this seems to be the case for cyclical animal populations: “An important biological feature of cyclic populations of voles and lemmings is phase-related changes in average body mass, with adults in high-density phases being 20–30% heavier than those in low- density phases of a cycle. This observation, called the “Chitty effect”, is considered to be a ubiquitous feature of cyclic populations… The Chitty effect is predicted to be most pronounced at the late increase or peak phase of a population cycle.” (Oli, 1999​16)​

Placing the hormone level’s peak to the latter part of the peak, that being after the peak in the sex hormone levels, results in the graph below. Since the average weight in Western nations has gone significantly up during the last century due to easily available calories and decreasing physical activity, it is difficult to find proxy data from human populations that could verify the presumed generational fluctuations in the growth hormone levels. (S)(S)(S)

Presumed oxytocin, dopamine, vasopressin, and sex hormone levels at birth. The percentages are only rough assumptions based on the vole study mentioned in chapter 1.1. The ‘growth hormone’ curve represents the presumed levels of the growth- based on the vole study mentioned in chapter 1.1. The ‘growth hormone’ curve represents the presumed levels of the growth- hormone-releasing hormone that is secreted by the hypothalamus.

The lemming graph in the previous chapter also shows smaller thyrotropic cell area during phases II and III, which could manifest as increasing prevalence of hypothyroidism among the population during the past few decades, and this seems to be the case according to studies conducted in the Western nations. (S) As for hyperthyroidism, the evidence is less certain what the direction has been during the past few decades. (S) The evidence at this point is still very scarce, so the thyroid hormones are yet to be placed in the hormone graphs.

3 Social hormones and group behavior

3.1 Social hormones and societal trends

This chapter presents how the hormones presented in chapter 2 can have population-wide effects to individual and group behavior. The idea of hormone levels having effects on a societal level is relatively novel, but neuroscience can be used in this manner not only to explain individual behavior, but also to explain formation and behavior of 1) groups and 2) institutions. (Stanley & Adolphs, 2013​115​) (On how feelings shape institutions and organizations: a short video from a MIT professor in psychology.)

When looking at the current political and ideological trends, it is clear that nationalism, populism, and xenophobia have been on the rise in the Western cultures for approximately the last twenty years. Both globalism and multilateralism are increasingly rejected. (S) Ideological polarizations are getting stronger every year. (S)(S)(S) Social divisions based on ideological identity can be clearly seen in basically all Western nations today, as two or more sides are separating from each other, creating ideological rifts. (S)(S) Hate crimes are becoming more common (S)(S), including anti-Semitism. (S)(S)(S) Many scholars have compared the 2010s to the 1930s, since many of the same societal effects can be observed to have become more prevalent during those decades that are 80 years apart.

Continuing listing the current societal trends: the status quo of global(istic) politics is being challenged at an accelerating pace. (S) Press freedom is increasingly being restricted by state actors (S)(S), free speech is being restricted by non-state actors ( S), and religious freedoms are being suppressed. (S) News outlets are increasingly ideologically divided (S), fake news are more frequent, and lying on behalf of one’s own ideological beliefs (S) is becoming more common. Not even the scientific community is safe from the effects of the post-truth era. (S)(S)(S)

Most studies and pundits explain the movement towards populist nationalism, and more generally the polarization of opinions in political and civic life, by explaining that they happen because of different societal phenomena like mass immigration, economic inequality and social media platforms that are polarizing opinions by forming echo chambers and allowing the distribution of fake news. (S)(S) These phenomena are assumed to create anxieties for the voters of populist nationalists, and the so called “liberal elites” are said to be out of touch. But none of the explanations or explanatory models built on these observations can predict or explain the rise of populist nationalism or the other mentioned phenomena with satisfactory accuracy, and the accuracy gets even worse when trying to apply these explanatory models to several or all of the Western nations, or to similar societal situations throughout the history.

Tendencies towards populist nationalism are growing basically in every democratic nation in Europe, and this movement started well before any big immigration or economic crisis of the 2010s. Nationalism grew as the economic situation in Europe was good and it has kept rising through the worse economic times. Financial crises do raise populist support for a while, but in a historical perspective populist support has generally leveled out in about 4 years after a crisis. (S) It is the same thing with immigration crises: the pace of the rise of nationalism and support for populist parties has not changed much through the years, not on the far-right or the far-left end. Nationalism and populism are not the same thing, but nationalistic parties are more often populist than not, especially on the far-right of the political spectrum.

Populist vote share in Europe from 1998 to 2018. (S)

The overall increasing support for populist nationalism in Europe has been very clear and steady over the past 20 years. The incremental maps below from 1998 to 2018 illustrate how each European country has followed its path to the current situation of higher than average support for populist parties.

Populist vote share in Europe from 1998 to 2018. (S) After these maps were published, nationalists made their way to the parliaments of Latvia in October 2018 (S), Estonia in March 2019 (S), and Portugal in October 2019 (S). This means that there is not even one European nation without nationalists in their parliament in 2020.

According to Gini statistics below, economic inequality cannot explain the rise of nationalism and populism, as income inequality has not changed much in the EU, and has actually gone down for most countries during the last 20 years. In the U.S. income inequality has risen, but attempts to raise taxes on the top earners or otherwise level out economic inequality have been pretty rare even on the left, highlights being the candidacy of Bernie Sanders and movements against the big banks (and neither can be said to be very much associated with populist nationalism).

Gini income inequality index from 1988 to 2016. (S)

Gini is not the only indicator that should be looked at, as low interest rates and quantitative easing by the worlds central banks have had a lifting effect on rent prices in Europe and the U.S., which has affected mostly low-income workers and may contribute to the dissent against the so called “elites”. But still, the economic conditions and employment numbers have generally gotten better during the last five years, and yet populism has increased at the same time. (S) Poland is a prime example of a nation that has had record economic success during recent years, but in spite of this, populist nationalism and xenophobia have risen sharply:

“This is not 1937. Nevertheless, a parallel transformation is taking place in my own time, in the Europe that I inhabit and in Poland, a country whose citizenship I have acquired. And it is taking place without the excuse of an economic crisis of the kind Europe suffered in the 1930s. Poland’s economy has been the most consistently successful in Europe over the past quarter century. Even after the global financial collapse in 2008, the country saw no recession. What’s more, the refugee wave that has hit other European countries has not been felt here at all. There are no migrant camps, and there is no Islamist terrorism, or terrorism of any kind.” (S) But if Poland was undergoing an economic depression today, the situation would very likely be used as a reason for the current increases in nationalism and xenophobia. Outside of Europe, Australia is not much different from Poland, as their uninterrupted economic boom has been going on for almost three decades, and nationalism is on the rise at the same time as it is in Europe and the U.S. (S)(S)

Social media platforms on the other hand seem to accelerate the divisions between individuals with diverging ideological stances: “Social media use tends to diversify communication within social networks by making people aware of what others think and feel about political and social issues. Social media enhance the perception of difference, and interpersonal contacts in these environments are typically rated less positively than interpersonal contacts in face-to-face communication.” (S) Moral- emotional posts tend to spread more effectively on social media platforms (S), and the platforms do play a role in the increasing polarization, but mainly as a catalyst: “Despite these limitations, this study has provided evidence that social media contribute to the growth of negative affect in political communication. Moreover, this negative affect is related to the comparatively high degree of perceived political disagreement that people encounter in social media settings. Thus, to a certain extent, perceived disagreement in social media settings has its roots in affective communication processes.” (S) So if social media is mainly intensifying the current societal trends, whatever they may be at a certain point in time, what could be the root cause for the increases in populist nationalism among Western nations?

The generational hormone theory presented here suggests that the studies and pundits blaming the economic disparities, immigration, social media, and other “usual suspects” for the rise of populist nationalism are probably correct in their observations of these phenomena occurring at the same time or before the rise of populist nationalism, but at the same time are fundamentally incorrect in how these phenomena affect the societal change, and thus cannot build working models to explain the rise of populist nationalism in detail. This is because these mentioned societal phenomena are expected to mainly work as catalysts for a generational movement, a generational cycle to be more precise, which is affecting the rise and fall of nationalism in Western nations at intervals of roughly 80 years.

It is suggested that these (catalytic) events essentially hide a significant reason for the rise of xenophobia and populist nationalism, just like the Great Depression of 1930s has often been claimed to be the main reason for the rise of nationalism and anti-Semitism in pre-WW2 Germany and elsewhere. (S) The goal is to demonstrate that generationally varying levels of social hormones oxytocin, dopamine, and vasopressin largely modulate the historical increases and decreases of societal phenomena like populist nationalism and xenophobia.

The generational hormone theory presents that hypothalamic hormone levels undergo large variances throughout an 80 year cycle, creating behavioral trait differences between generations, and that the varying social hormone levels create rising tides of nationalism, that essentially consists of tightening in-group cohesion and territoriality, a phenomenon that seems to occur every 80 years in many Western nations. In history this era is usually preceded by roughly four decades of globalism, liberalism and relatively peaceful times. All of these different eras and generations will be reviewed, but as they have already been presented extensively by historians William Strauss and Neil Howe in their books Generations and The Fourth Turning (summaries at Wikipedia and LifeCourse), the larger goal is to review how oxytocin, dopamine, and vasopressin modulate social behavior and how these hormones are linked to the Strauss- Howe generational theory of 4 x 20 year generations, an 80 year cycle in total.

Presenting a cyclical theory solely on the basis of biology would be very difficult, because there are so few longitudinal / multi-generational studies including direct measurements of hypothalamic hormones. But by reviewing presumed hormone levels through proxy statistics, like breastfeeding statistics for oxytocin levels, and combining these findings with presumed hormone modulated behavior in history, especially the observations made by Strauss & Howe, this combination should reveal a generational hormone cycle if there is one to be found.

3.2 Social hormones and societal group behavior

Oxytocin, dopamine, and vasopressin are the paramount hypothalamic social hormones in mammals. (S) The larger intent of chapter 3 is to point out that many of the current societal trends presented in the previous chapter, especially the rise of populist nationalism and its related phenomena, are presumably created by high levels of oxytocin, dopamine, and vasopressin in human populations. The human endocrine system is still not completely understood by science, especially regarding the behavioral aspects, which is why the statements made here are not presented as anything else than a slice of the current knowledge, and mostly aimed at building a bridge between hormonal activity and societal phenomena.

As a broad generalization of human behavior, humans are social animals that live and act in groups. (Young, 2008​116)​ (S) Humans have created extensive tools for communication, science, and culture, but these are basically extensions of animal behavior, since other species too can communicate and learn new languages and dialects, they can build tools and do math, and they can pass on their culture to their offspring. (Whitehead et al., 2019​117​) But more importantly, in addition to animals experiencing the more “apparent” feelings like fear or excitement, animals have been found to have the “more complex” feelings that humans have, such as empathy, altruism, grief, contempt, and jealousy to name a few. Hormone levels modulate these feelings in humans and other animal species.

The standard viewpoints to history concentrates on the societal events and actions taken by individuals, but the generational hormone theory adds a layer of internal biological responsiveness in the form of (presumed) generational hormone levels. Hormone levels modulate individual and group behavior, and also group formation and group coherence; the larger the hypothalamic neurons that secrete hormones are, the stronger the (hormone specific) reaction to others and the environment is.

Human behavior essentially consist of the responses of individuals and groups to external stimuli, and hormone levels modulate these responses because they modulate feelings. Average hormone levels affect how individuals and groups react to:

1) other individuals; 2) groups; 3) their surroundings/environment.

History will thus be mostly viewed and presented here as group behavior, that being further divided into in-group and out-group behavior. Typical in-groups are family, friends, gender, nation, culture, ethnicity, religion, political ideology, etc. Out-groups are basically comprised of people belonging to other in-groups than one’s own in-groups. Dopamine modulates large- scale social network group coherence, whereas oxytocin modulates social coherence in the context of family, friends, and other small-scale social connections. (Pearce et al., 2017​67)​ Vasopressin modulates territoriality, but does have other behavioral effects too as is presented later on.

Looking at history as group behavior is a divergence from the more traditional setting of mainly analyzing individual leaders and their associates, and how their actions have impacted history. The intent is not to entirely disregard historical individuals who for example want to advance their own cause and rise to power by using populist messaging, but instead the generational hormone theory aims to explain when and why individuals are open, or possibly even inclined, to receive populist messaging, largely negating the belief that this happens solely due to societal issues, but instead mostly due to a hormone cycle that’s presumably repeating every 80 years.

3.3 Neural in-group vs. out-group separation

Oxytocin promotes closeness for small-scale social networks, and also promotes defending that network against those who are different. (S) Oxytocin can deepen the wedge towards “the others” who think or look different, those who are often outside their own social networks. (De Dreu et al., 2011​118)​ Higher oxytocin levels lead to a more active separation between in-group and out-group, a sorting of “us vs. them”. As an example, the graph below illustrates the biobehavioral system of how oxytocin affects identification of and behavior towards an individuals in-group and out-group.

(De Dreu & Kret, 2015​119)​

This group psychology modulation by oxytocin can turn higher oxytocin (and vasopressin) levels into higher levels of xenophobia and nationalism. (De Dreu, 2011​118)​ (S) This social psychology study links in-group division to nationalism: “In explaining differences between groups, people ascribe the human essence to their in-group and consider out-groups as less human. This phenomenon, called infra-humanization, occurs outside people’s awareness. Because secondary emotions (e.g. love, hope, contempt, resentment) are considered uniquely human emotions, people not only attribute more secondary emotions to their in-group than to out-groups, but are reluctant to associate these emotions with out-groups. Moreover, people behave less cooperatively (in terms of altruism, imitation, and approach) with an out-group member who expresses himself through secondary emotions… Yet, preliminary results show that subjective essentialism and in-group identification may mediate the effects of infra-humanization. A connection is made between nationalism and infra-humanization… We believe that infra-humanization and nationalism are the two sides of the same coin.” (Leyens et al., 2003​120)​

The same study also suggests an another path to how nationalism rises: “There is still another possibility, which may better apply, we believe, to nationalism. Nationalism occurs in situations in which external forces induce people to consider their in-group and a given out-group as parts of a common superordinate group.” Both of the suggestions laid out here basically fit the theory of oxytocin (and vasopressin) related rise of nationalism, the in-group mechanism towards populism and also the latter mechanism regarding external forces, which could widely be labeled as populism. Populism is the most efficient way to incite and spread nationalism, and the tendency for nationalism rises with increased social hormone levels. (It is important to note that oxytocin stimulates dopamine secretion (Love, 2014​121​), which in part increases group coherence.)

Oxytocin has also been found to increase affection towards the flag of one’s own country, which is an in-group, which adds to the reasoning that oxytocin (and vasopressin*) increase nationalism. (Ma et al., 2014​122​) A nations flags is essentially an in-group symbol that represents a territory. *Vasopressin is very similar in structure and can upregulate oxytocin receptors (S) if in high amounts: “Given the similarity in the structure of OT and AVP, OT can bind to AVP receptors with a lower affinity compared to OT receptors and vice versa. V1A [receptor] is expressed in the forebrain and is the receptor that is most often linked to the regulation of social behavior…”. (Andari et al., 2018​123)​ Vasopressin is generally known to increase anxiety-like behaviors, stress responsiveness, aggressiveness, and territoriality. (Carter, 2017​124)​ (S)

On the evolution of cooperation within in-group and hate of out-group: “Although cooperation between groups is not unusual, most forms of human cooperation are in-group bounded and, sometimes, motivated by the desire to ward-off and subordinate rivaling out-groups. Building on evolutionary perspectives and models, we propose that humans evolved a capacity for parochial cooperation, which entails in-group love: the tendency to cooperate with and extend trust toward those others who are similar, familiar rather than unfamiliar, and belong to one’s own group; and out-group hate: a willingness to fight against rivaling out-groups. This chapter reviews our own work, and that of others, showing that parochial cooperation emerges especially when it benefits individuals’ within-group reputation, affects one’s within-group status, is more prominent among individuals with chronic prosocial rather than proself value orientation, and is sustained and motivated by oxytocin, an evolutionary ancient hypothalamic neuropeptide pivotal in social bonding, pair–bond formation, and empathic responding. Across the board, findings resonate well with relatively recent evolutionary theory on (inter)group relations and add to classic theory in social psychology.” (S)

Other studies show similar results regarding oxytocin and group bias: “Results show that oxytocin creates intergroup bias because oxytocin motivates in-group favoritism and, to a lesser extent, out- group derogation.” (De Dreu et al., 2011​118)​ A good example of oxytocin’s xenophobic effects is in the Dutch study on whether you sacrifice a person who has a typical Dutch name, or if you sacrifice a man with a foreign Muslim name. Increase the person’s oxytocin levels who is making the choice, and the choice that is made will show more xenophobic tendencies; an individual will now more likely to sacrifice the man with a Muslim name. (S) The rationalization by the test subject does not really matter, as it can be pretty much anything, but the changing end result does matter. And this is what oxytocin can influence; it can change the end result of a decision that associates ideological and cultural values, no matter the rationalization formed in the individual’s thoughts.

Oxytocin not only promotes in-group conformity, it also alters perceptions of trust and fairness, which could further ease the conforming to in-groups opinions: “The results reported here demonstrate that oxytocin stimulates in-group conformity. When asked to rate novel visual stimuli on attractiveness and when in-group and out-group members exhibited opposing preferences, individuals given oxytocin expressed preferences that were closer to those of the in-group than the out-group. This finding provides novel evidence that oxytocin is involved in influencing people’s preferences about actual stimuli, complementing earlier work demonstrating that oxytocin alters perceptions of more abstract concepts, such as generosity, trust, and fairness.” (Stallen et al., 2012​125​)

In addition to oxytocin altering perceptions, it also produces group-serving dishonesty: “We report here the results of a double-blind, placebo-controlled experiment showing that the hormone oxytocin promotes group-serving dishonesty. Compared with participants receiving placebo, participants receiving oxytocin lied more to benefit their groups, did so quicker, and did so without expectation of reciprocal dishonesty from their group members… Apparently, oxytocin boosts group- serving behavior, rather than adherence to general moral codes, a conclusion that fits work showing that oxytocin sustains and enables social bonding as well as trust and cooperation, especially toward those belonging to one’s own group. Thus, rather than being a neurohormonal modulator of moral tendencies and universal cooperation, oxytocin appears to function to serve group interests, whether it is through parochial cooperation and self-sacrifice, through lashing out against those who threaten group members, or as shown here, through dishonesty and moral code breaking.” (Shalvi & De Dreu, 2014​126)​

It should be noted that oxytocin did not promote lying to gain individual benefits in the study, the lying was done only in order to gain benefits specifically for their own group. But since oxytocin has been found to ramp up the innate social reasoning skills, it is likely that higher levels of oxytocin enable more dishonesty without losing the feeling of integrity. (S)

Altruism can be seen as a good force in the human behavior, but it has its limitations that seem to follow conformity and herd mentality: “Some of the most fundamental questions concerning our evolutionary origins, our social relations, and the organization of society are centered around issues of altruism and selfishness. Experimental evidence indicates that human altruism is a powerful force and is unique in the animal world. However, there is much individual heterogeneity and the interaction between altruists and selfish individuals is vital to human cooperation. Depending on the environment, a minority of altruists can force a majority of selfish individuals to cooperate or, conversely, a few egoists can induce a large number of altruists to defect.” (Fehr & Fischbacher, 2003 127)​

Oxytocin also promotes altruistic punishment: “…our results suggest a different perspective on the popularly known ‘moral molecule’, as we show that OT [oxytocin], rather than having an effect on positive emotions, amplifies strong negative emotions (i.e. anger) towards non-cooperators within small groups… Consistent with the finding that emotions, in addition to rational considerations, work as a proximate mechanism to induce norm-enforcing behavior, our data suggests that OT might have an amplifying effect on social emotions, including negative, which ultimately triggers the punishment of defective behavior and leads to the enforcement of social norms.” (Aydogan et al., 2017​128)​

These mentioned cooperative models of group behavior have been shown to be evolutionarily efficient by mathematical and game theory models (Shiramizu & Yamamoto, 2017​129)​ , and it also important to note that these behavioral cooperative mechanisms have a neurobiological basis that is innate to humans, and also detectable in how human societies are comprised. (Lewis & Bates 2010​36​)(Lewis & Bates 2017​37​)

3.4 Social hormones and populist nationalism

To sum up the findings in the previous chapter, below is a short list of expected changes in individual and group behavior when oxytocin and vasopressin levels increase.

1. More nationalism, xenophobia and demands for in-group cohesion. 2. Negative emotions towards in-group non-cooperators. 3. Perceptions of trust and fairness are altered as group-serving lying is promoted, which is enforced by higher innate social reasoning skills. 4. Infra-humanization of out-groups and willingness to fight out-groups.

Points 1 and 2 are often a big part of populist ideology, point 3 basically lays out the post-truth aka. fake news era. Points 1-3 of these group behavior changes have been on the rise for the last 20 years or so in the Western nations when compared to the 1990s. Only point 4 is yet to fully materialize, but there are growing efforts to label Muslims and other culturally differing groups in the Western nations increasingly as out-groups, and there have been a large number of terrorist attacks between Muslims and “natives” opposing Islam and its cultural teachings. (S) (S) The number of hate groups has also increased in the US and the EU. ( S)(S)

Increased oxytocin levels lead to higher levels of empathy (Geng et al., 2018​130​), but since the separation between in-groups and out-groups is increasing at the same time, this combination can lead to a “wrong kind” of empathy, as the rising feelings of empathy is directed towards the tightening in-group, and coupled with vasopressin this empathy can even lead to aggressive behavior (Buffone & Poulin, 2014​131)​ towards in-group non-cooperators and out-groups (explained further in chapter 4). Advocates for populist nationalism use the feelings of empathy constantly to their advantage in their messaging.

Since higher levels of oxytocin increases anxiety towards unpredictable threats ( Grillon et al., 2013​132)​ , and vasopressin increases anxiety, populist nationalist leaders gain support by talking about these in-group and out-group threats by presenting ways to address them straight on. Many experts on populist nationalism claim that anxiety among populist voters is created by economic worries, but this does not seem to be the case, as these anxieties are actually created through emotions – especially fear:

“Populism peddles a politics of fear—of crime, terrorism, unemployment, economic decline, the loss of national values and tradition—and asserts that other parties are leading their countries to disaster. Surveys make clear that populist voters are extremely pessimistic: they believe the past was better than the present and are extremely anxious about the future. But pessimism has infected Western societies more generally. A recent PEW survey for example revealed that even though growing percentages of European citizens view their country’s economic situation as dramatically better than a decade ago, this has not translated into greater optimism about the future. Indeed, in many European countries the “experience-expectation” differential has grown: in the Netherlands, Sweden and Germany, for example, approximately 80 percent or more say the economy is doing well, but less than 40 percent believe the next generation will be better off than their parents. These views reflect a troubling reality: particularly in times of change and uncertainty, people’s views are shaped more by emotions than rationality.” (S)

Populist leaders can therefore gain support through creating/compounding economic anxieties. As an example, Brexit supporters claimed that exiting EU would be beneficial to the UK economy (which is quite probably not true), and Donald Trump targeted China (and expressed empathy towards coal miners in his presidential campaign). Anxieties related to xenophobia seem to most often be an efficient way of gaining populist votes, but a combination of anxieties towards immigrants and economic worries seems to be an even more efficient combination for populists in many instances: “illegal immigrants stealing the jobs and committing crimes” or “selfish Jews hoarding capital at the top” for example are commonly used. These kinds of combinations of oxytocin and vasopressin enhanced anxieties have been used in order to make scapegoats and gain popularity through thousands of years of political history. (S)(S)(S) It should be noted that scapegoating is a mechanism that is common among social mammal species. (S)

In addition, a 2018 study reveals that higher levels of oxytocin and especially vasopressin flatten social hierarchy: “OT [oxytocin] reduces differences in social behavior between dominant and subordinate monkeys, thereby flattening the status hierarchy. OT also increases behavioral synchrony within a pair. Intranasal delivery of aerosolized AVP [vasopressin] reproduces the effects of OT with greater efficacy. Remarkably, all behavioral effects are replicated when OT or AVP [vasopressin] is injected focally into the anterior cingulate gyrus (ACCg), a brain area linked to empathy and other- regarding behavior.” (Jiang & Platt, 2018​133​) The findings could further explain why so many of the populist leaders achieve success by claiming to be “a man of the people”, and also why the “liberal elites” and Jews, who are often seen as holding places of power, are increasingly despised during times of rising populist nationalism. Even though this particular though the study was done on rhesus monkeys, the social hormones have similar effects primates (although there are some differences among different species).

Based on all of the presented studies, it can be stated that increased levels of social hormones may indeed manifest as stronger levels of documented group behavior like in-group favoritism, out-group homogeneity, and group conformity (i.e. large-scale behavioral synchrony). (Everett et al., 2015​134​)(Huang et al., 2019​135)​ (S)(S)

4 Group division and conict 4.1 Group division

This (highly unfinished) chapter focuses on the mechanism of growing in-group cleavage leading up to a division into two camps. Other in-group and out-group social dynamics are also reviewed. The presumption of increasing oxytocin and vasopressin levels leading to “negative emotions toward in-group non-cooperators” (reviewed in chapter 3) is tested. Both humans and chimpanzees are taken a look at, since chimpanzees along with bonobos are the closest relatives of humans, and because a group split of a chimpanzee community happened in 1972 in Gombe. (Feldblum et al., 2018​136​)(S) The split in the chimp community led to a four-year war between the newly formed chimp groups, a civil war of sorts. Comparing chimp group behavior to human group behavior should offer insight into how they may show similar patterns related to increased social hormone levels, including tightening in-groups and increased territorial behavior.

The slowly growing division in the Gombe chimp social network map from 1970 to 1972 (graphic on the left) resembles the increasing left vs. right political cleavages in the US from 1994 to 2014 (bottom right), which have progressed in a similar fashion in several Western nations, and Twitter graphs (top right) help to illustrate how these are comparable to the chimpanzee division in Gombe: two groups are slowly drifting apart.

Visualizations of increasing group cleavages in chimpanzee and human groups. (S)(S)(S)

The statistic below illustrates grooming intensity to chimps taking sides in Gombe. Oxytocin levels increase with grooming in primates (S), but only with an existing (S) social bond partner. The same effect has been observed with humans: “Holt-Lunstad et al. found that couples engaged in a program of affiliative touch over a 4-week period resulted in higher post-treatment salivary oxytocin levels than couples in the non-intervention group…” In addition, “Across mammals, infants require physical affiliative contact, whereas in adults proximity may be sufficient [to increase oxytocin levels]…”. (S)

There were two chimps competing for the alpha male status when the in-group split started to materialize during 1970, and this occurred during the time of increasing grooming and presumably increasing oxytocin levels. This in not to imply that the presumed rising oxytocin levels caused the division, but instead that they facilitated it through increasing polarization of the two camps supporting different alpha males.

The heavy grooming stage marks the final division (statistic below) in the chimpanzee community that took place during 1971-1972, as can be seen in the chimp social network graph above left and the grooming intensity graph below: grooming leads to increasing oxytocin levels -> sides are being chosen (‘follows’ increase) -> division into two groups (‘arrivals’ and ‘follows’ finish the division) -> leads to a conflict between the two new groups in the end (vasopressin is also likely involved here).

Grooming intensity by year. (S)

The presumption is that the path is similar with humans: it is the rise of oxytocin and especially vasopressin levels and increased levels of empathy towards in-group members that increases the wedge towards non in-group members. This seems be occurring today among Western nations as the ideological cleavages and polarizations deepen between large-scale social networks, all the way up to the size of nations.

Even if a nation is very unified so that divisions are not a possibility, there still appears to be some growing divide among its citizens during a 4th turning, which manifests as the rise of xenophobia (or even fear/scapegoating/defaming individuals or groups of individuals as witches, as is explained in chapter 4.2). The ones singled out could be for example an ideological and/or religious minority, but it seems like there must be an opposite side or scapegoats to blame for pressing societal problems when social hormone levels are high during a 4th turning. When nationalism rises there most often is a minority group (or groups) that the populists target, and thus the ones who belong to that minority group become scapegoats who will be blamed for many of the most pressing problems a society faces, and these can be real or made up problems: economic depression or economic inequality, crimes, disease, famine or any other problem that affects the community as a whole. History shows that it really does not matter who they are, basically any minority (out-)group can be used as an scapegoat if empathy is high towards the in-group. (A thorough book on empathy and its pitfalls is ‘Against Empathy: The Case for Rational Compassion’ by Paul Bloom, professor of psychology and cognitive science at Yale University. A video about group empathy and another video about empathy, bias, and dehumanization by Bloom.)

Assumably, when social hormone levels rise in human and chimp communities, a similar pattern repeats with both species: tightening of social networks and singling out “the others”. For example, when chimp oxytocin levels rise, they start to patrol their borders more. (Samuni ​137​ et al., 2017​137)​ In hamsters vasopressin has been found to increase territorial aggression. ( Young & Flanagan-Cato, 2012​138​) These increased territorial instincts could be compared to increased human territorial behavior, which is often heightened during eras of high nationalism. Similar movements have been whitnessed in many European countries as demands to more or less shut down the borders and decrease/stop immigration have been growing stronger during the past decase, at least when it comes to the refugees from countries with different cultural values compared to the traditional values in the nation receiving the immigrants. These immigrants can be “legal” like in the case of Brexit or “illegal” like in the case of the U.S. border wall debate (not forgetting the recent bans on immigrants from several predominantly Muslim countries).

In addition, if the chimp alpha male does not show enough empathy towards the in-group members, they can be removed from their position. (S) This may be the reason for the growing distrust towards the so called “liberal elites”, who on average support more open borders and higher levels of immigration than the populist nationalists, thus they may be seen as lacking in empathy towards the perceived in-group during a 4th turning.

So what exactly could happen in humans when social hormone levels rise and is the pattern same as with chimps, can demands for group conformity divide a previous relatively coherent in-group into two or more groups? The holocaust is an obvious example of growing in-group hatred/division towards (perceived) non-cooperators, and the persecution of Jews begun about six years prior to any offensive aggression towards neighboring nations. Jews were blamed for the economic woes as well as many other problems.

The following study explains how increasing oxytocin levels leads to declining morality in these situations: “Justifications may promote unethical behavior because they constitute a convenient loophole through which people can gain from immoral behavior and preserve a positive self-image at the same time. A justification that is widely used is rooted in conformity: Unethical choices become more permissible because one’s peers are expected to make the same unethical choices. In the current study, we tested whether an exogenous alteration of conformity led to a lower inclination to adhere to a widely accepted norm (i.e., honesty) under the pressure of competition. We took advantage of the well-known effects of intranasally applied oxytocin on affiliation, in-group conformity, and in-group favoritism in humans. We found that conformity was enhanced by oxytocin, and this enhancement had a detrimental effect on honesty in a competitive environment but not in a noncompetitive environment. Our findings contribute to recent evidence showing that competition may lead to unethical behavior and erode moral values.” (Aydogan et al., 2017​128)​

Blaming Jews for hoarding the capital during an economic downturn could therefore have led to declining morality and unethical choices by introducing a “competitive environment” and through higher levels of empathy towards the own in-group. Oxytocin regulates feelings of empathy and empathy is the source of aggression according to this study: “This study negates previous beliefs that characteristics like impulsiveness, trait aggression, trait or state anger trigger aggression, and shows that, not the personality, but empathic feelings trigger aggression.” (S) (Buffone & Poulin 2014​131)​ Lower requirements towards honesty from other in-group members (mentioned in the first quote) could have made individuals accept weak arguments to explain the unethical actions taken towards the Jews while maintaining a feeling of personal integrity. This effect of oxytocin inducing dishonesty to serve one’s in-group in a competitive environment would also explain the current post-truth era in politics (S) and science (Iyengar & Massey, 2018​139​) that begun around 2015. Since ideologies have departed so far from the center out, this could be interpreted as an competitive environment that can induce “detrimental effect on honesty” into anything that is related to political ideologies, including many scientific areas like climate change (S), abortion (S), and vaccine resistance (S) (that has actually been linked to the support for populist parties (S)). Because humans are hardwired to dismiss facts that do not fit their worldview, the increasing cleavages on issues like climate change are only made worse by better knowledge regarding the issue, since a larger knowledge base can enhance one’s ideologically motivated reasoning. (Bolsen et al., 2015​140​/S)

4.2 Paths of tightening group coherence

This (unfinished) chapter puts the proposed generational hormone theory to test by looking at an earlier peaks of nationalism, as the early 17th century contains clear signs of populism and rising feelings of early nationalism. 4th turnings are estimated to have happened roughly every 80 years: 1530-1550 | 1610-1630 | 1690-1710 | 1770-1790 | 1850-70 | 1930-1950 and currently 2010-2030.

The graphs in this chapter coarsely illustrate how tightening group coherence during a 4th turning leads to different end results depending on the starting point that exists at the ending of a 3rd turning. This is in line with the Strauss-Howe generational theory: a society’s direction in a 4th turning is largely dependent on the situation it is in when a 4th turning begins, and that the beginning is marked by a catalytic event that starts the process towards a new order in the civic life as well.

Path 1 is the most common path and was explained earlier (chapter 2.3.1). Path 2 presents a situation where the ideological divides/cleavages are already strong when entering a 4th turning, thus there is a risk of the divisions eventually splitting the main group into two (or possibly more) separate in-groups. The division into separate in-groups may eventually escalate into a conflict, but this would depend entirely on the contentious societal issues at hand. In this situation virtually everyone is situated on one side or another, thus scapegoating is rare because both sides try to garner as much supporters as possible, and the opposing group is blamed/scapegoated for at least the most pressing societal issues/problems.

But an external threat may also accomplish an unification during a 4th turning even if it is difficult otherwise, just like the rise of the Nazi Germany mostly suppressed the populist movements (but not nationalism) in many of the war waging countries during WW2, because the war efforts required cooperation basically at every level of a society. So path 2 can change into path 1 if the external threat is strong enough to unify the society.

Path 3 presented below is typical for dictatorships, kingdoms, and monarchies that have accumulated most if not all of the power to a small elite at the top.

Below are examples of the paths taken regarding the US during the past three 4th turnings.

1) The American Revolutionary War was preceded by path 3. The British were the out-group (although one third of the American colonists fought on the side of England). 2) The American Civil War was preceded by path 2. There were two distinct in-groups, the North and the South, and there were virtually no scapegoats apart from the other side. 3) WW2 was preceded by path 1, while communists and fascists were the out-groups/scapegoats, and this way of thinking continued after the war.

In 2020 it would seem that the current 4th turning paths in the US and the UK are closest to path 2, which is not surprising due to the two-party systems, but the political polarizations in the 2010s have been much stronger compared to the 1930s and the 40s (the previous 4th turning). This obviously is not to imply that the divisions would eventually manifest as a divide, but the ideological cleavages have been getting stronger every year, especially in the US. Most of the Western nations seem to be undergoing path 1.

When group coherence tightens in a society, institutions will be used (or at least tried to be used) to advance the benefit of the in-group, often to derogate an out-group. The usual targets of this are the justice system, army leadership, state media, and the schooling system, which are increasingly subjugated under the ruling party. People leading these institution are often replaced by individuals who are willing to advance the in-group’s cause, and sometimes by any means necessary, because anyone who is perceived to advance the in-group’s agenda is often rewarded with fame and fortune. (This is also true for war heroes, movie stars, and helpers of the least fortunate inside their own in-group.)

If there are free media organizations, they are silenced if possible, and a good example of this is what has happened during the recent years in Hungary. If no group can control the media, the free media tends to polarize into two opposing camps due to consumer group behavior, but possibly also due to ownership demands. Media tycoons are often highly regarded inside their in-groups, and they can get even more influence inside their in-group by catering to their demands. This mobilization of institutions in order to further the current societal causes – what ever they might be – is what has happened during the 4th turnings in history according to Strauss & Howe.

4.3 In-group empathy and scapegoating of the out-group

When nationalism rises and the unification is successful (or the society was already unified), there most often is a minority group or groups that the nationalists target, and the ones who belong to that minority group become scapegoats who will be blamed for many of the most pressing problems (real or made up problems) a nation faces: economic depression or economic inequality, crimes, disease, famine, or any other problem that affects the community negatively. Because scapegoating has been around for thousands of years and since scapegoating is found also in other animal species, it seems that it is an innate biological mechanism in humans, which utilizes the neural in-group vs. out-group setting. (S)

History shows that it really does not matter who the scapegoats are, basically any minority group can be used as a scapegoat. Since there must be someone to blame, suggests that if a community is very homogeneous in culture and ethnicity, like the Western European countries very much were during the 16th and 17th centuries, there can be imaginary scapegoats of groups/individuals like witches, who were blamed for things like disease or a village losing crops. (On a sidenote, witch hunts are still happening in modern times for instance in India and Tanzania.)

Catholic and Protestant churches used witch-hunts to advance the spread of their ideological views: “Among both Catholics and Protestants, witch-hunting became a prime service for attracting and appeasing the masses by demonstrating their Satan-fighting prowess… When it comes to winning people to your side, after all, there’s no better method than stoking fears about an outside threat—and then assuring them that you, and you alone, offer the best protection.” This means that the church gave in to populism. In addition, it was very similar to what is happening today with the ideological battles between political parties: “Similar to how contemporary Republican and Democrat candidates focus campaign activity in political battlegrounds during elections to attract the loyalty of undecided voters, historical Catholic and Protestant officials focused witch-trial activity in confessional battlegrounds during the Reformation and Counter-Reformation to attract the loyalty of undecided Christians.” (S)

Applying the declining moral standards and tolerance for unethical decisions with rising oxytocin levels from the previous chapter, the witch hunts may have seemed more reasonable during times of presumably higher oxytocin levels (higher in-group empathy) than with lower oxytocin levels (lower in-group empathy). The witch hunts were often justified by claiming they were done in order to protect the children, and this fits to the idea of rising oxytocin levels increasing empathy towards the weakest of an in-group. The elderly and war veterans are also similar groups which are not so much respected during 2nd and 3rd turnings, but gain back respect during 4th and 1st turnings.

After the witch hunts had peaked in Central Europe, the following Thirty Years’ War ( S) was not so much of a war between countries but instead between areas of groups which had adopted one of the two main ideologies; Protestants vs. Catholics. The Thirty Years’ War was fought between Catholic and Protestant states in Central Europe from 1618 to 1648. The conflicts eventually drew in the great powers of Europe, resulting in one of the longest, most destructive, and deadliest conflicts in European history. In addition, concurrently rising nationalism in Switzerland, Denmark, Sweden, France and the Netherlands also had a role in the escalating conflict. (S) So populism and nationalism were at play, just like during less than a century before when Luther’s ideas about religion defined a new in-group, Lutherans, who steered away from the power of the Pope.

“Beyond that immediate matter of dispute, however, their conflict represented the clash of two contrasting world views—those of the Renaissance and the Reformation. Erasmus was an internationalist who sought to establish a borderless Christian union; Luther was a nationalist who appealed to the patriotism of the German people… For years, they waged a battle of ideas, with each seeking to win over Europe to his side, but Erasmus’s reformist and universalist creed could not match Luther’s more emotional and nationalistic one; even some of Erasmus’s closest disciples eventually defected to Luther’s camp. Erasmus became an increasingly marginal figure, scorned by both Catholics, for being too critical of the Church, and Lutherans, for being too timid. In a turbulent and polarized age, he was the archetypal reasonable liberal… In The Complaint of Peace, he decried the nationalist enmities that were splitting the continent.” (S)

The timing presumably was on the side of Luther, because populist nationalism is high during a 4th turning. This is not to say that Luther was a populist or nationalist, but his ideas seem to have resonated among to those who did have tendencies towards populist nationalism. (Luther himself did authorize executions of witches, which may imply that he had populistic tendencies, although he did believe in witches according to his own writings.)

But can high oxytocin and especially vasopressin levels lead to intergroup violence? Empathy can drive aggression even when it makes no moral sense according to recent studies. (S) Higher oxytocin levels lead to increased empathy and lower oxytocin levels lead to reduced empathy (Andari et al., 2018​123)​ (S) Likewise, test subjects who by genetic differences have higher sensitivity to oxytocin and vasopressin show greater connection between empathy and aggression. (S page 195.) It should be noted that aggression and violence are complicated mechanisms, which to there is no one simple answer to explain them, but higher levels of vasopressin heighten the possibility of such states of mind occurring: “There is compelling evidence from several mammalian species including humans that vasopressin enhances aggression. The activity of the vasopressin appears linked to the serotonin system providing a

​141​ mechanism for enhancing and suppressing aggressive behavior.” (Ferris, 2005​141)​

The following study deepens the understanding towards how oxytocin and vasopressin create aggression by utilizing empathy towards one’s in-group:

“Although the idea that people aggress on behalf of others is not new at all, we believe the idea that empathy can drive aggression absent provocation or injustice to be quite novel… We had specifically predicted that the effects of empathy on aggression would be accounted for by the actions of the neurohormones vasopressin and oxytocin. Our finding that variation in vasopressin and oxytocin receptor genes moderate empathy’s effects supports this prediction. More broadly, a role of these neurohormones in empathy’s effects is consistent with the possibility that empathy facilitates a broad array of behaviors—whether kind or aggressive—geared toward benefiting vulnerable others… Specifically, Study 1 showed that when participants reported feeling higher levels of empathy during a past episode when a close other was threatened and felt distressed, participants were more likely to report having aggressed on the close other’s behalf… Similarly, the combination of target distress and empathy significantly predicted increased empathy-linked aggression for individuals with the GG genotype of OXTR rs53576, but reduced aggression for those with the AG or AA genotypes. Together, these results suggest that empathy may have predicted aggression due to its effects on vasopressin and oxytocin… In sum, the present work represents the first evidence that empathy predicts aggressive behavior on its own, even independent of provocation, and in conjunction with the empathy-linked hormones/neuropeptides oxytocin and vasopressin.” (Buffone & Poulin, 2014​131)​

More on intergroup conflict and how oxytocin regulates it through defensive and cooperative mechanisms:

“Recent evolutionary models suggest that parochial altruism, the link between in-group favoritism and the benefit of others at a cost to oneself, is key to understanding the evolution of humans’ cooperative traits and propensity for intergroup violence. Intergroup conflict is ubiquitous across human societies, repeatedly leading to devastating results of prejudice, war, and genocide. Individuals contribute to these patterns both by supporting in-group members and acting with hostility toward the out-group. When such a combination contributes to success in intergroup conflicts, parochial altruism could have evolved, and biological mechanisms that sustain and promote it are likely adaptive. One such proposed biological mechanism involves the neuropeptide hormone oxytocin, previously linked with various aspects of human sociality, particularly the development of mother– offspring bonds, but also tolerance, coordination, and cooperation between nonkin adults. Owing to its anxiolytic and prosocial effects, oxytocin is proposed to facilitate cooperation during risk, a mechanism potentially co-opted from maternal defense circuitry. Intranasal administration of oxytocin enhances in-group co-operation and trust and out-group defensive, but not offensive, competition in men. This suggests that oxytocin triggers a “tend and defend” form of parochial altruism, accentuating co- operative behavior toward the in-group as well as defensive behavior toward out-groups.” (Samuni et al., 2016​137)​

In addition, vasopressin enhances the likelihood of a preemptive strike, which underscores the hormone’s aggressive effects on human behavior:“Overall, our study clearly illustrates a role for AVP in human defensive aggression during an experience of potential resource threat. …animal results endorse the idea that vasopressin, which serves basic sexual and protective functions, can be coopted to regulate more complicated social behaviors in species that live in large, complex groups, like humans and monkeys. Although parallel evidence about humans is still elusive, these earlier studies suggest that neuropeptides may deeply regulate human social behavior as well. In this sense, investigating those processes will be essential toward better understanding and possibly regulating various social phenomena in our societies.” (Kawada et al., 2019​142)​

Applying these aspects of oxytocin and vasopressin (higher possibility of defensive aggression and preemptive attacks) to the witch hunts and Confessional Battles show a similar pattern to what was witnessed before and during the WW2 in Germany for instance, where the separation of the out-group Jews from the in-group started years before the war (and in the Soviet Union and Japan during WW2, as war efforts were accompanied by mass killings of non-conforming in-group members, who were essentially seen as out-group members (S)).

The charts below illustrate that there is a familiar pattern of 1) in-group separation and then defensive aggression towards the singled out scapegoats (witches) when oxytocin levels are high, after which comes 2) aggression, possibly preemptive, towards outside threats/out- groups by rising vasopressin and also dopamine levels. The charts below indicates this path of behavior in the decades during the European witch hunts leading to the Thirty Years’ War. (S)

The peak in witch hunts is followed by territorial aggression.

It is important to note that witch hunts are still happening in the 2020s for example in India and Tanzania, and the pattern is the same as 500 years ago: the one who is scapegoated is typically an old lonely woman who lives on the outskirts of the community, and can be seen as not being a part of the in-group that is engaging in the scapegoating. The two Ngram statistics (S) below illustrates the amplitude of the UK and the US witch hunts through the usage of word ‘witch’, which spiked in British English and American English books regularly every 80 years at the beginning of 4th turnings. (S)

The usage of the word ‘witch’ in British English coincides with the peak of the European witch trial activity presented before. A red pillar marks the beginning of a 4th turning: 1610 … 1690 | 1770 | 1850 | 1930 | 2010.

The American witch hunts were much smaller in size during the 1610s than in Europe ( S), but they peaked higher during the next cycle when the Salem witch trials began in 1692 at the beginning of a 4th turning, marking the peak of American witch hunts.

The usage of the word ‘witch’ in American English. A red pillar marks the beginning of a 4th turning: 1610 | 1690 | 1770 … 1850 | 1930 | 2010. During the 19th century the concept of ‘a witch’ transferred over to the side of fiction literature (S), but before this the books about witches were considered to be non-fiction in nature, even academic, like the Hammer of Witches (S)(S) that was a best-selling book for 200 years, only behind the Bible in sold copies.

The last US witch trials with significance occurred close to 1760, as the graph indicates. ( S) The generational hormone theory is not about explaining the roots of witch hunts and trials, but it is important to highlight that these statistical peaks in the history of scapegoating display a cyclical nature that follows the 80 year Strauss-Howe generational cycle. And in the 2010s, the phenomenon of scapegoating came about once again, just like in the 1610s, as anti-Semitism started to increase towards the end of the decade seemingly out of nowhere, as most of the acts against Jews have been perpetrated by individuals, not by organized groups.

5 Initial conclusions

5.1 Possible societal trajectories

To sum up the findings made in this hypothesis, there is now a theoretical framework and a number of statistics that are in support of the existence of cyclically varying hormone levels in cyclical animal populations and among the generations in Western nations.

It cannot be emphasized enough that hormone levels impact decision making on an unconscious level. Hormone levels impact actions and reactions of individuals and groups. This coupled with generational variances in hormone levels creates the generational traits listed by the Strauss- Howe generational theory, and gives the traits a biological basis similar to many other cyclical mammal species. In addition, the generational hormone theory implies that individual and group behavior of humans is closer to other species than previously thought, because individual and group decision making is apparently largely influenced by social (and other) hormones on an unconscious level.

Even though populist nationalism has had different ways of manifesting, as structures of countries and also types of available ideologies have varied through the centuries, it has detectable similarities across centuries. This strongly indicates that the phenomenon has its roots in biology.

The strength of the generational hormone theory is in the relative simplicity which allows overlooking individual differences received from genetics and environments by reviewing entire generations’ traits and actions. When looking at the current societal developments, the presented generational hormone theory is the only theory that addresses basically all of the central phenomena related to the rise of populist nationalism like rising feelings of nationalism, xenophobia (anti-Semitism, anti-Muslim sentiments, etc.), ideological and political polarization, and group serving lying (aka. post-truth era). The theory also addresses questions like why these phenomena are occurring today and why they are happening all around the Western nations – even in those nations that have not experienced major economic or civic difficulties for over two decades. The theory gives ground to the current slow abandonment of the “liberal status quo” inside many Western liberal democracies.

The more conventional and traditional viewpoints on history can be seen as “actions leading to consequences”, and then succeeding actions taken upon these consequences. The example used in the introductory chapter was the often repeated claim that the Great Depression of the 1930s largely caused the Nazi party to get to power in the pre-WW2 Germany. But such suggestions do not explain why the 1970s oil crisis did not cause any nationalistic movements. Obviously there were other reasons as well for the rise of the Nazi’s to power, such as the Treaty of Versailles, but such treaties have not commonly led to the rise of nationalism. So the explanation is a soup of consequences and actions which rarely solely cause large increases in nationalism, but together they somehow did. But even this does not explain the simultaneous rise of nationalism and anti-Semitism during the 1930s in other European nations.

Presuming that the generational hormone cycle is at least somewhat accurate, predictions could be made about the upcoming years in general. But these predictions would obviously be only like weather forecasts, that combine historical models of past 4th turnings with the current events. The Fourth Turning book links the turnings to seasons of nature, which is fitting, as the conditions of the seasons cannot be known beforehand, but the seasons do run their course – with very familiar and predictable patterns. This is also true regarding the animal population cycles.

‘Predicting the future’ of human societies has a dubious ring to it, but is it predicting the future that a pre-pubertal individual will soon undergo years of increased irritability, mood swings, and changing sexual behavior? Or is it predicting the future to say that a woman close to her period may have increased irritability, mood swings, and changing sexual behavior? Or that a cyclical lemming population at the beginning of the cycle will first become less territorial and socially coherent for the next two years, and after that more territorial and socially coherent for the next two years. Presumably, all of these are predetermined hormonal events, where the timing is executed by biological clocks.

History cannot predict the future, but taking (the presumed) varying hormone levels among human populations into account could provide more background to why historical events have happened the way they have happened, and also to what direction the current societal issues are pivoting towards. That being said, if the predictions about the hormone levels are correct, for the remainder of this 4th turning, the trends listed below will presumably spread and gain popularity in the Western nations due to increasing feelings of in-group coherence (dopamine) and territoriality (vasopressin).

1) More populist nationalism and political polarization, and centrist parties will continue to lose support. The U.S. will keep turning into a propaganda democracy with two diverging partisan ideological realities with different sets of facts. 2) Ideologically influenced news and also “fake news” will become increasingly efficient as receptivity for them increases. Conspiracy theories built around opposing in-group’s activities become more wide-spread. 2) More xenophobia and hate crimes in different forms towards out-groups, including hate speech, as acts of violence are increasingly based on intergroup issues. Armed militias and gangs will become more common. 4) Institutions and organizations (including companies), both public and private, will be increasingly demanded to take sides on societal issues or face the threat of boycotts.

Many European countries will presumably stay on the path on becoming more nationalistic and the EU may start to malfunction as individual countries oppose EU regulations regarding their internal agendas. More problems for example with(in) Austria, Poland, Hungary, and Italy are to be expected. As populist parties grow in size, they may be increasingly accepted into governments. A lengthened economic recession or depression would very likely increase the “us vs. them” tensions greatly, since “they” (out-groups) are most often blamed for causing the economic downturn and/or making things worse during it.

[APRIL 2020 UPDATE TO RECENT EVENTS: All of the predictions above have come true on average in the Western nations, with notable increases in support for populist nationalists, anti-Semitism, and other societal movements that indicate increasing intergroup cleavages. The current coronavirus crisis environment will presumably increase stress levels across the Western nations, which presumably leads to more nationalism and support for populism. International institutions and organizations will presumably continue to derogate as political support and funding becomes increasingly hard to find from inside the member nations due to increasing nationalism and economic turmoil.]

[MAY 2021 UPDATE TO RECENT EVENTS: As predicted in the previous April 2020 update, since the pandemic started last year, nationalism has stayed at a high level and intergroup cleavages have increased. (S) The US and German parliaments were attacked by groups consisting (mostly) of far-right nationalists. (S)(S) BLM protests and riots were also clear signs of in- group tightening especially on the left-wing side of the political spectrum, and there were BLM protests around the Western nations. (S) Interest and support for Qanon increased noticeably once the pandemic started (S), and this trend has continued in 2021. ( S) Anti-Semitism has stayed at high levels, breaking records in some countries despite the restrictions set due to the pandemic. (S)(S) Cancel culture has remained strong in the Western nations. ( S)(S)]

5.2 A review of societal actions

If one were to view the rise of populist nationalism as a problem/threat, which depends entirely on one’s viewpoint, below are suggestions that several pundits have made on “how to solve the problem of increasing populism”, followed by reasons why they will not work very well according to the presented theory of continuing rise of nationalist populism.

1. “Europe will soon enter a time of post-populism once the voters realize that the populists can’t eradicate the pressing societal problems with easy solutions.” Even if the populist governments cannot solve the problems, they will find ways to blame others for them, like the EU, other nations, minorities or past liberal policies still hurting the country. These explanations will keep the populists in power.

2. “More direct democracy will solve the problem of hate against the elites.” This may work for a while in suppressing the populistic messaging, as it may ease the anxiousness of not having a voice to change the society, but eventually the direction towards nationalism will continue and populist agendas will gain popularity again.

3. “Reduce immigration and influx of refugees to suppress populism.” This may also work for a while, as populistic parties gain power much through the anti-immigrant stances they hold. Unfortunately this will not solve the problems a nation may already have with the growing dissent against the minorities that are already in the country.

4. “Reduce socio-economic inequalities to suppress populism.” Emmanuel Macron tried this recently in France in a quick response to the so called yellow vest protests, and final results are yet to be seen. This is a slow and possibly costly process overall, likely to be led by tax cuts.

5. “Use economic sanctions for non-compliant EU countries if they suppress democracy, justice system or free press.” This may prevent some of the more radical plans of some nationalistic leaders, but will erode trust and cooperation between member nations, driving the EU towards and internal political crisis. But a crisis inside the EU is to be expected sooner or later, as the parties with highly nationalistic agendas will likely join forces in the European Parliament against the parties with the more liberal and globalist views of Europe. If a “union of nationalist parties” reaches a majority in the European Parliament, the results could be unpredictable. To prevent this from happening the traditional parties will probably bend to some of the more populistic demands in order to stay in power, altering Europe’s internal direction and external relations in the process.

6. “Stop hate speech online and elsewhere with ad campaigns and other messaging.” This article explains why this suggestion probably would not work: https://www.psychologytoday.com/us/blog/values-matter/201909/why-stop-bigotry-won-t- stop-bigotry

5.3 Unresolved questions

1) The hypothesis could be easily verified by looking at the size of hypothalamic neurons in the cyclical species’ individuals at the different parts of the cycle by using electron microscopes. The same tests could be done in the animal populations that experience population explosions. As for humans, the current imaging devices (MRI) are not accurate enough to see individual neurons in the brain.

2) The remaining hypothalamic hormones that are yet to be included in this hypothesis are corticotropin-releasing hormone and somatostatin.

3) Finding historical proxy statistics for vasopressin levels would solidify the premise of the dopamine and vasopressin hormone level curve.

4) What could be controlling a generational oscillation in the endocrine system? In theory, the presumed infradian clock could be counting years from the amount of light, seasonal temperatures, or some other annual external variable (or a combination of variables).

The most logical answer would be the suprachiasmic nucleus (SCN) that controls the body’s biological clocks: “Outside of the tropics (where day length remains relatively consistent throughout the year), the changing photoperiod is a reliable and predictable seasonal signal that presents an opportunity for organisms to adapt to seasonal changes in factors such as temperature and resource availability in an anticipatory fashion… The SCN receives input from the retina directed towards its ventrolateral subregion, while its dorsomedial region features numerous direct and indirect projections to other hypothalamic nuclei controlling homeostatic function and to the rest of the brain.” (Tackenberg & McMahon, 2018​143​) “…the SCN perceives and encodes changes in day length and drives seasonal changes in downstream pathways and structures…” (Coomans et al., 2014​144​) Virtually all cyclical animal populations exist in the area between 30 to 70 degrees northern latitude, which could be due to these latitudes having strong annual rhythms of nature. (Sinclair 145)​ (Kendall et al., 2002​7)​ The occurrence and amplitude of the cycles is strongest on the northern latitude 55, which very closely corresponds with the minimum latitude in which nautical twilight can last all night near the summer solstice. During nautical twilight the illumination is such that the horizon is still visible even on a moonless night, meaning that it gets very dark even in the summer (compared to more northern latitudes), but the length of day is still very long (compared to more southern latitudes). (S) This latitude is where the changes in the length of day are the most pronounced, while still having a dark period every day of the year, which could be the explanation why this latitude sees the highest occurrence and amplitude regarding the cycles.

The tropic (between the Tropic of Cancer and the Tropic of Capricorn), that has very small annual changes to light periods, has fewer regular population cycles, but instead more population outbreaks, like huge swarms of grasshoppers. The smaller amount of cyclical populations could therefore be because there is only little variation in the annual light periods. This presumption is enhanced by the fact that there apparently are no (primary) population cycles in populations of nocturnal species. (Sources to be added…)

In addition to the changing photoperiod, light’s wavelength also has an effect on the SCN. ( Wahl et al., 2019​146​)(Duffy & Czeisler, 2009​147)​ In humans, blue light has the largest effect on setting the SCN’s circadian rhythm. The image below illustrates how the human eye detects different wavelengths of light.

“As outlined above, light is the key zeitgeber in the circadian system and interacts with the master clock in the SCN via non-image-forming pathways connecting retina and SCN.” (S)

Another possibility is that the animal population cycles are timed by lunar cycles. ( S)

5) Assuming that the premises presented in this hypothesis are correct, a question remains that Strauss & Howe pondered in their books: what would the modern history of the Western cultures look like without the generational cycle? What if the The Hardy-Weinberg Equilibrium remained stable like it is in non-cyclical populations? What if there weren’t eras of low group coherence that create high rates of individualism and crime, or eras of high group coherence that create high rates of nationalism and scapegoating other groups?

The year 2005 is a good reference point: no ideological battles that consume everything in politics, low levels of populism, relatively good relations between most nations, no large-scale wars between coalitions, no significant culture of over-selfishness nor ideological groupthink, and individuals are relatively stress free and reasonably – but not overly – optimistic about the future. This could be roughly the status quo without the theoretical generational hormone cycle.

On the other hand, where would the Western societies be without eras of high group coherence that have been associated with such things as the French Revolution and the following century of forming many European nations? What would the social norms be today without such breakouts as the sexual revolution of the 1960/70s or the MeToo-movement and other recent movements against anti-social behaviors? And how much less variance would the cultural life have without these changes to the social and civic life over centuries? If the main premises of this hypothesis are accurate, it would offer a novel viewpoint to social evolution of populations.

Could the the strength/amplitude of the presumed wave movements determine the speed of evolution? This is obviously an essential hypothetical question when looking at cyclical animal populations, but also when looking at human history, but also a question that cannot be answered easily. This is obviously not the place to make such an analysis in any meaningful length, and the topic is extremely speculative, but it is important to note how the generational cycle could have possibly been active also during previous millenniums.

Hypothesis web-link: https://jannemiettinen.fi/FourthTurning/ Contact: [email protected] / https://www.facebook.com/janne.miettinen

References

1. 1. Myers JH. Population cycles: generalities, exceptions and remaining mysteries. Proc R Soc B. Published online March 21, 2018:20172841. doi:10.1098/rspb.2017.2841 2. 2. Wang H, Nagy JD, Gilg O, Kuang Y. The roles of predator maturation delay and functional response in determining the periodicity of predator–prey cycles. Mathematical Biosciences. Published online September 2009:1-10. doi:10.1016/j.mbs.2009.06.004 3. 3. Krebs CJ. Of lemmings and snowshoe hares: the ecology of northern Canada. Proc R Soc B. Published online October 27, 2010:481-489. doi:10.1098/rspb.2010.1992 4. 4. Krebs CJ, Bryant J, Kielland K, et al. What factors determine cyclic amplitude in the snowshoe hare (Lepus americanus) cycle? Can J Zool. Published online December 2014:1039-1048. doi:10.1139/cjz-2014-0159 5. 5. Hansson L, Henttonen H. Gradients in density variations of small rodents: the importance of latitude and snow cover. Oecologia. Published online October 1985:394-402. doi:10.1007/bf00384946 6. 6. Esper J, Büntgen U, Frank DC, Nievergelt D, Liebhold A. 1200 years of regular outbreaks in alpine insects. Proc R Soc B. Published online December 12, 2006:671-679. doi:10.1098/rspb.2006.0191 7. 7. Kendall, Prendergast, Bjornstad. The macroecology of population dynamics: taxonomic and biogeographic patterns in population cycles. Ecol Letters. Published online November 1998:160-164. doi:10.1046/j.1461-0248.1998.00037.x 8. 8. Ecological orbits: how planets move and populations grow. Choice Reviews Online. Published online February 1, 2005:42-3404-42-3404. doi:10.5860/choice.42-3404 9. 9. Andreassen HP, Sundell J, Ecke F, et al. Population cycles and outbreaks of small rodents: ten essential questions we still need to solve. Oecologia. Published online December 28, 2020:601-622. doi:10.1007/s00442-020-04810-w 10. 10. Oli MK. Population cycles in voles and lemmings: state of the science and future directions. Mam Rev. Published online May 10, 2019:226-239. doi:10.1111/mam.12156 11. 11. Oli MK. Population cycles of small rodents are caused by specialist predators: or are they? Trends in Ecology & Evolution. Published online March 2003:105-107. doi:10.1016/s0169- 5347(03)00005-3 12. 12. Arshavskaya T, Polenov A, Tkachev A. The hypothalamo-hypophysial system of the lemming, Dicrostonyx torquatus Pallas. III. Population aspects of neuroendocrine regulation. Z Mikrosk Anat Forsch. 1989;103(4):627-647. https://www.ncbi.nlm.nih.gov/pubmed/2683448 13. 13. Vladimirova EG, Chernigovskaya EV, Danilova OA. Hypothalamo-pituitary neurosecretory system of the Northern redbacked vole Clethrionomys rutilus in the course of population cycle. J Evol Biochem Phys. Published online March 2006:208-216. doi:10.1134/s002209300602013x 14. 14. Sheriff MJ, Krebs CJ, Boonstra R. From process to pattern: how fluctuating predation risk impacts the stress axis of snowshoe hares during the 10-year cycle. Oecologia. Published online January 19, 2011:593-605. doi:10.1007/s00442-011-1907-2 15. 15. Cary JR, Keith LB. Reproductive change in the 10-year cycle of snowshoe hares. Can J Zool. Published online February 1, 1979:375-390. doi:10.1139/z79-044 16. 16. Oli MK. The Chitty Effect: A Consequence of Dynamic Energy Allocation in a Fluctuating Environment. Theoretical Population Biology. Published online December 1999:293-300. doi:10.1006/tpbi.1999.1427 17. 17. Fauteux D, Gauthier G, Berteaux D. Seasonal demography of a cyclic lemming population in the Canadian Arctic. Ims R, ed. J Anim Ecol. Published online July 15, 2015:1412-1422. doi:10.1111/1365-2656.12385 18. 18. Johnsen K, Devineau O, Andreassen HP. Phase- and season-dependent changes in social behaviour in cyclic vole populations. BMC Ecol. Published online January 25, 2019. doi:10.1186/s12898-019-0222-3 19. 19. Daftary GS, Taylor HS. Endocrine Regulation of HOX Genes. Endocrine Reviews. Published online April 21, 2006:331-355. doi:10.1210/er.2005-0018 20. 20. Lutchmaya S, Baron-Cohen S, Raggatt P, Knickmeyer R, Manning JT. 2nd to 4th digit ratios, fetal testosterone and estradiol. Early Human Development. Published online April 2004:23- 28. doi:10.1016/j.earlhumdev.2003.12.002 21. 21. Brockhurst MA, Chapman T, King KC, Mank JE, Paterson S, Hurst GDD. Running with the Red Queen: the role of biotic conflicts in evolution. Proc R Soc B. Published online December 22, 2014:20141382. doi:10.1098/rspb.2014.1382 22. 22. Strotz LC, Simões M, Girard MG, Breitkreuz L, Kimmig J, Lieberman BS. Getting somewhere with the Red Queen: chasing a biologically modern definition of the hypothesis. Biol Lett. Published online May 2018:20170734. doi:10.1098/rsbl.2017.0734 23. 23. Rikalainen K, Aspi J, Galarza JA, Koskela E, Mappes T. Maintenance of genetic diversity in cyclic populations-a longitudinal analysis inMyodes glareolus. Ecology and Evolution. Published online June 11, 2012:1491-1502. doi:10.1002/ece3.277 24. 24. Ehrich D, Jorde PE. HIGH GENETIC VARIABILITY DESPITE HIGH-AMPLITUDE POPULATION CYCLES IN LEMMINGS. Journal of Mammalogy. Published online April 2005:380-385. doi:10.1644/ber-126.1 25. 25. Berthier K, Piry S, Cosson J-F, et al. Dispersal, landscape and travelling waves in cyclic vole populations. Liebhold A, ed. Ecol Lett. Published online November 17, 2013:53-64. doi:10.1111/ele.12207 26. 26. van Holstein L, Foley RA. Terrestrial habitats decouple the relationship between species and subspecies diversification in mammals. Proc R Soc B. Published online March 18, 2020:20192702. doi:10.1098/rspb.2019.2702 27. 27. Fletcher NK, Acevedo P, Herman JS, Paupério J, Alves PC, Searle JB. Glacial cycles drive rapid divergence of cryptic field vole species. Ecol Evol. Published online November 23, 2019:14101- 14113. doi:10.1002/ece3.5846 28. 28. Vahdati AR, Sprouffske K, Wagner A. Effect of Population Size and Mutation Rate on the Evolution of RNA Sequences on an Adaptive Landscape Determined by RNA Folding. Int J Biol Sci. Published online 2017:1138-1151. doi:10.7150/ijbs.19436 29. 29. Franklin MT, Myers JH, Cory JS. Genetic Similarity of Island Populations of Tent Caterpillars during Successive Outbreaks. López-Vaamonde C, ed. PLoS ONE. Published online May 23, 2014:e96679. doi:10.1371/journal.pone.0096679 30. 30. Krebs CJ, Boonstra R, Boutin S. Using experimentation to understand the 10‐year snowshoe hare cycle in the boreal forest of North America. Wilson K, ed. J Anim Ecol. Published online July 24, 2017:87-100. doi:10.1111/1365-2656.12720 31. 31. Sherratt JA, Smith MJ. Periodic travelling waves in cyclic populations: field studies and reaction–diffusion models. J R Soc Interface. Published online January 22, 2008:483-505. doi:10.1098/rsif.2007.1327 32. 32. Jepsen JU, Vindstad OPL, Barraquand F, Ims RA, Yoccoz NG. Continental-scale travelling waves in forest geometrids in Europe: an evaluation of the evidence. White A, ed. J Anim Ecol. Published online January 16, 2016:385-390. doi:10.1111/1365-2656.12444 33. 33. Allocco DJ, Song Q, Gibbons GH, Ramoni MF, Kohane IS. Geography and genography: prediction of continental origin using randomly selected single nucleotide polymorphisms. BMC Genomics. Published online 2007:68. doi:10.1186/1471-2164-8-68 34. 34. Caldwell HK, Albers HE. Oxytocin, Vasopressin, and the Motivational Forces that Drive Social Behaviors. In: Behavioral Neuroscience of Motivation. Springer International Publishing; 2015:51-103. doi:10.1007/7854_2015_390 35. 35. MacLean EL, Gesquiere LR, Gruen ME, Sherman BL, Martin WL, Carter CS. Endogenous Oxytocin, Vasopressin, and Aggression in Domestic Dogs. Front Psychol. Published online September 27, 2017. doi:10.3389/fpsyg.2017.01613 36. 36. Lewis GJ, Bates TC. Genetic Evidence for Multiple Biological Mechanisms Underlying In- Group Favoritism. Psychol Sci. Published online October 25, 2010:1623-1628. doi:10.1177/0956797610387439 37. 37. Lewis GJ, Bates TC. The Temporal Stability of In-Group Favoritism Is Mostly Attributable to Genetic Factors. Social Psychological and Personality Science . Published online June 7, 2017:897-903. doi:10.1177/1948550617699250 38. 38. Pletzer B, Harris T-A, Scheuringer A, Hidalgo-Lopez E. The cycling brain: menstrual cycle related fluctuations in hippocampal and fronto-striatal activation and connectivity during cognitive tasks. Neuropsychopharmacol. Published online June 13, 2019:1867-1875. doi:10.1038/s41386-019-0435-3 39. 39. Simonneaux V, Bahougne T. A Multi-Oscillatory Circadian System Times Female Reproduction. Front Endocrinol. Published online October 20, 2015. doi:10.3389/fendo.2015.00157 40. 40. Neumann ID, Landgraf R. Balance of brain oxytocin and vasopressin: implications for anxiety, depression, and social behaviors. Trends in Neurosciences. Published online November 2012:649-659. doi:10.1016/j.tins.2012.08.004 41. 41. Sachs ME, Ellis RJ, Schlaug G, Loui P. Brain connectivity reflects human aesthetic responses to music. Social Cognitive and Affective Neuroscience. Published online March 10, 2016:884-891. doi:10.1093/scan/nsw009 42. 42. Rajamani KT, Wagner S, Grinevich V, Harony-Nicolas H. Oxytocin as a Modulator of Synaptic Plasticity: Implications for Neurodevelopmental Disorders. Front Synaptic Neurosci. Published online June 19, 2018. doi:10.3389/fnsyn.2018.00017 43. 43. Fowden AL, Forhead AJ. Hormones as epigenetic signals in developmental programming. Experimental Physiology. Published online May 14, 2009:607-625. doi:10.1113/expphysiol.2008.046359 44. 44. Crawley JN. Behavioral Phenotyping Strategies for Mutant Mice. Neuron. Published online March 2008:809-818. doi:10.1016/j.neuron.2008.03.001 45. 45. Gordon I, Zagoory-Sharon O, Leckman JF, Feldman R. Oxytocin and the Development of Parenting in Humans. Biological Psychiatry. Published online August 2010:377-382. doi:10.1016/j.biopsych.2010.02.005 46. 46. Dotti Sani GM, Treas J. Educational Gradients in Parents’ Child-Care Time Across Countries, 1965-2012. Fam Relat. Published online April 19, 2016:1083-1096. doi:10.1111/jomf.12305 47. 47. Augustine RA, Ladyman SR, Bouwer GT, et al. Prolactin regulation of oxytocin neurone activity in pregnancy and lactation. J Physiol. Published online March 23, 2017:3591-3605. doi:10.1113/jp273712 48. 48. Scott V, Brown CH. Beyond the GnRH Axis: Kisspeptin Regulation of the Oxytocin System in Pregnancy and Lactation. In: Advances in Experimental Medicine and Biology. Springer New York; 2013:201-218. doi:10.1007/978-1-4614-6199-9_10 49. 49. Albanesi S, Olivetti C. Gender Roles and Medical Progress. Journal of Political Economy. Published online June 2016:650-695. doi:10.1086/686035 50. 50. Ryan AS. The Resurgence of Breastfeeding in the United States. PEDIATRICS. Published online April 1, 1997:e12-e12. doi:10.1542/peds.99.4.e12 51. 51. Inoue M, Binns CW, Otsuka K, Jimba M, Matsubara M. Infant feeding practices and breastfeeding duration in Japan: A review. Int Breastfeed J. Published online 2012:15. doi:10.1186/1746-4358-7-15 52. 52. Nutrition During Lactation. National Academies Press; 1991. doi:10.17226/1577 53. 53. BLANKS A. The role of oxytocin in parturition. BJOG: An International Journal of Obstetrics and Gynaecology. Published online April 2003:46-51. doi:10.1016/s1470-0328(03)00024-7 54. 54. Hobbs AJ, Mannion CA, McDonald SW, Brockway M, Tough SC. The impact of caesarean section on breastfeeding initiation, duration and difficulties in the first four months postpartum. BMC Pregnancy Childbirth. Published online April 26, 2016. doi:10.1186/s12884- 016-0876-1 55. 55. Smith LJ. Impact of Birthing Practices on the Breastfeeding Dyad. Journal of Midwifery & Women’s Health. Published online November 12, 2007:621-630. doi:10.1016/j.jmwh.2007.07.019 56. 56. Erickson EN, Carter CS, Emeis CL. Oxytocin, Vasopressin and Prolactin in New Breastfeeding Mothers: Relationship to Clinical Characteristics and Infant Weight Loss. J Hum Lact. Published online April 29, 2019:136-145. doi:10.1177/0890334419838225 57. 57. Erlinge S, Hasselquist D, Svensson M, Frodin P, Nilsson P. Reproductive behaviour of female Siberian lemmings during the increase and peak phase of the lemming cycle. Oecologia. Published online May 3, 2000:200-207. doi:10.1007/s004420051006 58. 58. Lui C, Cui X, Wang Y, You Z, Xu D. Association between neuropeptide oxytocin and male infertility. J Assist Reprod Genet. Published online August 14, 2010:525-531. doi:10.1007/s10815-010-9451-2 59. 59. Sunahara CS, Zelkowitz P, Bolger N, et al. Maternal oxytocin predicts relationship survival during the perinatal transition period: Preliminary evidence. International Journal of Psychophysiology. Published online February 2019:33-38. doi:10.1016/j.ijpsycho.2018.04.009 60. 60. Scheele D, Wille A, Kendrick KM, et al. Oxytocin enhances brain reward system responses in men viewing the face of their female partner. Proceedings of the National Academy of Sciences . Published online November 25, 2013:20308-20313. doi:10.1073/pnas.1314190110 61. 61. Ditzen B, Schaer M, Gabriel B, Bodenmann G, Ehlert U, Heinrichs M. Intranasal Oxytocin Increases Positive Communication and Reduces Cortisol Levels During Couple Conflict. Biological Psychiatry. Published online May 2009:728-731. doi:10.1016/j.biopsych.2008.10.011 62. 62. McDermott R, Fowler JH, Christakis NA. Breaking Up Is Hard to Do, Unless Everyone Else Is Doing It Too: Social Network Effects on Divorce in a Longitudinal Sample. Social Forces. Published online October 8, 2013:491-519. doi:10.1093/sf/sot096 63. 63. Mitchell IJ, Gillespie SM, Abu-Akel A. Similar effects of intranasal oxytocin administration and acute alcohol consumption on socio-cognitions, emotions and behaviour: Implications for the mechanisms of action. Neuroscience & Biobehavioral Reviews. Published online August 2015:98-106. doi:10.1016/j.neubiorev.2015.04.018 64. 64. Bowen MT, Peters ST, Absalom N, Chebib M, Neumann ID, McGregor IS. Oxytocin prevents ethanol actions at δ subunit-containing GABAA receptors and attenuates ethanol-induced motor impairment in rats. Proc Natl Acad Sci USA. Published online February 23, 2015:3104- 3109. doi:10.1073/pnas.1416900112 65. 65. King CE, Becker HC. Oxytocin attenuates stress-induced reinstatement of alcohol seeking behavior in male and female mice. Psychopharmacology. Published online March 28, 2019:2613-2622. doi:10.1007/s00213-019-05233-z 66. 66. Ericson J, Flacking R, Hellström-Westas L, Eriksson M. Changes in the prevalence of breast feeding in preterm infants discharged from neonatal units: a register study over 10 years. BMJ Open. Published online December 2016:e012900. doi:10.1136/bmjopen-2016-012900 67. 67. Pearce E, Wlodarski R, Machin A, Dunbar RIM. Variation in the β-endorphin, oxytocin, and dopamine receptor genes is associated with different dimensions of human sociality. Proc Natl Acad Sci USA. Published online May 1, 2017:5300-5305. doi:10.1073/pnas.1700712114 68. 68. Chester DS, DeWall CN, Derefinko KJ, et al. Looking for reward in all the wrong places: dopamine receptor gene polymorphisms indirectly affect aggression through sensation- seeking. Social Neuroscience. Published online December 7, 2015:487-494. doi:10.1080/17470919.2015.1119191 69. 69. Leyton M, Vezina P. Dopamine ups and downs in vulnerability to addictions: a neurodevelopmental model. Trends in Pharmacological Sciences. Published online June 2014:268-276. doi:10.1016/j.tips.2014.04.002 70. 70. Gold MS, Blum K, Oscar–Berman M, Braverman ER. Low Dopamine Function in Attention Deficit/Hyperactivity Disorder: Should Genotyping Signify Early Diagnosis in Children? Postgraduate Medicine. Published online January 2014:153-177. doi:10.3810/pgm.2014.01.2735 71. 71. Tonry M. Why Crime Rates Are Falling throughout the Western World. Crime and Justice. Published online September 2014:1-63. doi:10.1086/678181 72. 72. Lappi-Seppälä T, Lehti M. Cross-Comparative Perspectives on Global Homicide Trends. Crime and Justice. Published online September 2014:135-230. doi:10.1086/677979 73. 73. PORTNOY J, RAINE A, CHEN FR, PARDINI D, LOEBER R, JENNINGS JR. HEART RATE AND ANTISOCIAL BEHAVIOR: THE MEDIATING ROLE OF IMPULSIVE SENSATION SEEKING. Criminology. Published online April 9, 2014:292-311. doi:10.1111/1745-9125.12038 74. 74. Baker LA, Tuvblad C, Reynolds C, Zheng M, Lozano DI, Raine A. Resting heart rate and the development of antisocial behavior from age 9 to 14: Genetic and environmental influences. Dev Psychopathol. Published online July 7, 2009:939-960. doi:10.1017/s0954579409000509 75. 75. Ziegler M, Kennedy B, Holland O, Murphy D, Lake C. The effects of dopamine agonists on human cardiovascular and sympathetic nervous systems. Int J Clin Pharmacol Ther Toxicol . 1985;23(4):175-179. https://www.ncbi.nlm.nih.gov/pubmed/3158615 76. 76. Latvala A, Kuja-Halkola R, Almqvist C, Larsson H, Lichtenstein P. A Longitudinal Study of Resting Heart Rate and Violent Criminality in More Than 700 000 Men. JAMA Psychiatry. Published online October 1, 2015:971. doi:10.1001/jamapsychiatry.2015.1165 77. 77. Murray J, Hallal PC, Mielke GI, et al. Low resting heart rate is associated with violence in late adolescence: a prospective birth cohort study in Brazil. Int J Epidemiol. Published online January 28, 2016:491-500. doi:10.1093/ije/dyv340 78. 78. Culpepper L, Froom J. Incarceration and blood pressure. Social Science & Medicine Part A: Medical Psychology & Medical Sociology. Published online December 1980:571-574. doi:10.1016/s0271-7123(80)80064-2 79. 79. Matthiopoulos J, Moss R, Lambin X. The kin facilitation hypothesis for red grouse population cycles: territorial dynamics of the family cluster. Ecological Modelling. Published online January 2002:291-307. doi:10.1016/s0304-3800(01)00420-3 80. 80. PIERTNEY SB, LAMBIN X, MACCOLL ADC, et al. Temporal changes in kin structure through a population cycle in a territorial bird, the red grouse Lagopus lagopus scoticus. Molecular Ecology. Published online April 22, 2008:2544-2551. doi:10.1111/j.1365-294x.2008.03778.x 81. 81. Meng Y, Holmes J, Hill-McManus D, Brennan A, Meier PS. Trend analysis and modelling of gender-specific age, period and birth cohort effects on alcohol abstention and consumption level for drinkers in Great Britain using the General Lifestyle Survey 1984-2009. Addiction. Published online September 13, 2013:206-215. doi:10.1111/add.12330 82. 82. Previc FH. The Dopaminergic Mind in Human Evolution and History. Published online 2009. doi:10.1017/cbo9780511581366 83. 83. Raghanti MA, Edler MK, Stephenson AR, et al. A neurochemical hypothesis for the origin of hominids. Proc Natl Acad Sci USA. Published online January 22, 2018:E1108-E1116. doi:10.1073/pnas.1719666115 84. 84. Caldwell HK. Oxytocin and Vasopressin: Powerful Regulators of Social Behavior. Neuroscientist. Published online May 11, 2017:517-528. doi:10.1177/1073858417708284 85. 85. Oliveira RF. Social behavior in context: Hormonal modulation of behavioral plasticity and social competence. Integrative and Comparative Biology. Published online July 21, 2009:423- 440. doi:10.1093/icb/icp055 86. 86. Caldwell HK, Lee H-J, Macbeth AH, Young WS III. Vasopressin: Behavioral roles of an “original” neuropeptide. Progress in Neurobiology. Published online January 2008:1-24. doi:10.1016/j.pneurobio.2007.10.007 87. 87. Wyart C, Webster WW, Chen JH, et al. Smelling a Single Component of Male Sweat Alters Levels of Cortisol in Women. Journal of Neuroscience. Published online February 7, 2007:1261- 1265. doi:10.1523/jneurosci.4430-06.2007 88. 88. Vergara P, Martínez-Padilla J. Social context decouples the relationship between a sexual ornament and testosterone levels in a male wild bird. Hormones and Behavior. Published online September 2012:407-412. doi:10.1016/j.yhbeh.2012.07.007 89. 89. Baroncini M, Jissendi P, Catteau-Jonard S, et al. Sex steroid hormones-related structural plasticity in the human hypothalamus. NeuroImage. Published online April 2010:428-433. doi:10.1016/j.neuroimage.2009.11.074 90. 90. Theodosis DT, Chapman DB, Montagnese C, Poulain DA, Morris JF. Structural plasticity in the hypothalamic supraoptic nucleus at lactation affects oxytocin-, but not vasopressin- secreting neurones. Neuroscience. Published online March 1986:661-678. doi:10.1016/0306- 4522(86)90038-2 91. 91. Carzon P, Delfour F, Dudzinski K, Oremus M, Clua É. Cross‐genus adoptions in delphinids: One example with taxonomic discussion. Ethology. Published online June 25, 2019:669-676. doi:10.1111/eth.12916 92. 92. Archibald HL. The enigma of the 10-year wildlife population cycle solved? Evidence that the periodicity and regularity of the cycle are driven by a lunar zeitgeber. Can Field Nat. Published online January 28, 2015:327. doi:10.22621/cfn.v128i4.1626 93. 93. Ishunina TA, Swaab DF. Vasopressin and Oxytocin Neurons of the Human Supraoptic and Paraventricular Nucleus; Size Changes in Relation to Age and Sex. The Journal of Clinical Endocrinology & Metabolism. Published online December 1999:4637-4644. doi:10.1210/jcem.84.12.6187 94. 94. de Boer M, Kokal I, Blokpoel M, et al. Oxytocin modulates human communication by enhancing cognitive exploration. Psychoneuroendocrinology. Published online December 2017:64-72. doi:10.1016/j.psyneuen.2017.09.010 95. 95. Fitzpatrick P, Frazier JA, Cochran D, Mitchell T, Coleman C, Schmidt RC. Relationship Between Theory of Mind, Emotion Recognition, and Social Synchrony in Adolescents With and Without Autism. Front Psychol. Published online July 31, 2018. doi:10.3389/fpsyg.2018.01337 96. 96. Cardoso C, Ellenbogen MA, Linnen A-M. Acute intranasal oxytocin improves positive self- perceptions of personality. Psychopharmacology. Published online October 20, 2011:741-749. doi:10.1007/s00213-011-2527-6 97. 97. Pearce E, Wlodarski R, Machin A, Dunbar RIM. Genetic Influences on Social Relationships: Sex Differences in the Mediating Role of Personality and Social Cognition. Adaptive Human Behavior and Physiology. Published online November 26, 2019:331-351. doi:10.1007/s40750- 019-00120-5 98. 98. Joly JK, Hofmans J, Loewen P. Personality and Party Ideology Among Politicians. A Closer Look at Political Elites From Canada and Belgium. Front Psychol. Published online April 17, 2018. doi:10.3389/fpsyg.2018.00552 99. 99. Tollenaar MS, Chatzimanoli M, van der Wee NJA, Putman P. Enhanced orienting of attention in response to emotional gaze cues after oxytocin administration in healthy young men. Psychoneuroendocrinology. Published online September 2013:1797-1802. doi:10.1016/j.psyneuen.2013.02.018 100. 100. Dodd MD, Hibbing JR, Smith KB. The politics of attention: gaze-cuing effects are moderated by political temperament. Atten Percept Psychophys. Published online November 4, 2010:24- 29. doi:10.3758/s13414-010-0001-x 101. 101. Hatemi PK, Medland SE, Klemmensen R, et al. Genetic Influences on Political Ideologies: Twin Analyses of 19 Measures of Political Ideologies from Five Democracies and Genome- Wide Findings from Three Populations. Behav Genet. Published online February 26, 2014:282- 294. doi:10.1007/s10519-014-9648-8 102. 102. Settle JE, Dawes CT, Christakis NA, Fowler JH. Friendships Moderate an Association between a Dopamine Gene Variant and Political Ideology. The Journal of Politics. Published online October 2010:1189-1198. doi:10.1017/s0022381610000617 103. 103. Hurlemann R, Marsh N, Schultz J, Scheele D. Oxytocin shapes the priorities and neural representations of attitudes and values. Behav Brain Sci. Published online 2017. doi:10.1017/s0140525x16000807 104. 104. Taber CS, Lodge M. The Illusion of Choice in Democratic Politics: The Unconscious Impact of Motivated Political Reasoning. Political Psychology. Published online January 22, 2016:61-85. doi:10.1111/pops.12321 105. 105. Levine H, Jørgensen N, Martino-Andrade A, et al. Temporal trends in sperm count: a systematic review and meta-regression analysis. Human Reproduction Update. Published online July 25, 2017:646-659. doi:10.1093/humupd/dmx022 106. 106. Travison TG, Araujo AB, O’Donnell AB, Kupelian V, McKinlay JB. A Population-Level Decline in Serum Testosterone Levels in American Men. The Journal of Clinical Endocrinology & Metabolism. Published online January 1, 2007:196-202. doi:10.1210/jc.2006-1375 107. 107. Davis GJ, Meyer RK. FSH and LH in the snowshoe hare during the increasing phase of the 10- year cycle. General and Comparative Endocrinology. Published online February 1973:53-60. doi:10.1016/0016-6480(73)90129-9 108. 108. Condorelli R, Calogero AE, La Vignera S. Relationship between Testicular Volume and Conventional or Nonconventional Sperm Parameters. International Journal of Endocrinology. Published online 2013:1-6. doi:10.1155/2013/145792 109. 109. Weiss RV, Clapauch R. Female infertility of endocrine origin. Arq Bras Endocrinol Metab. Published online March 2014:144-152. doi:10.1590/0004-2730000003021 110. 110. Burkimsher M, Zeman K. Childlessness in Switzerland and Austria. In: Demographic Research Monographs. Springer International Publishing; 2017:115-137. doi:10.1007/978-3-319- 44667-7_6 111. 111. Gurven M, Kaplan H. Longevity Among Hunter- Gatherers: A Cross-Cultural Examination. Population & Development Review. Published online June 2007:321-365. doi:10.1111/j.1728- 4457.2007.00171.x 112. 112. Goodale T, Sadhu A, Petak S, Robbins R. Testosterone and the Heart. Methodist DeBakey Cardiovascular Journal. Published online April 2017:68-72. doi:10.14797/mdcj-13-2-68 113. 113. Walther A, Breidenstein J, Miller R. Association of Testosterone Treatment With Alleviation of Depressive Symptoms in Men. JAMA Psychiatry. Published online January 1, 2019:31. doi:10.1001/jamapsychiatry.2018.2734 114. 114. Furigo IC, Teixeira PDS, de Souza GO, et al. Growth hormone regulates neuroendocrine responses to weight loss via AgRP neurons. Nat Commun. Published online February 8, 2019. doi:10.1038/s41467-019-08607-1 115. 115. Stanley DA, Adolphs R. Toward a Neural Basis for Social Behavior. Neuron. Published online October 2013:816-826. doi:10.1016/j.neuron.2013.10.038 116. 116. Young S. The neurobiology of human social behaviour: an important but neglected topic. J Psychiatry Neurosci. 2008;33(5):391-392. https://www.ncbi.nlm.nih.gov/pubmed/18787656 117. 117. Whitehead H, Laland KN, Rendell L, Thorogood R, Whiten A. The reach of gene–culture coevolution in animals. Nat Commun. Published online June 3, 2019. doi:10.1038/s41467-019- 10293-y 118. 118. De Dreu CKW, Greer LL, Van Kleef GA, Shalvi S, Handgraaf MJJ. Oxytocin promotes human ethnocentrism. Proceedings of the National Academy of Sciences . Published online January 10, 2011:1262-1266. doi:10.1073/pnas.1015316108 119. 119. De Dreu CKW, Kret ME. Oxytocin Conditions Intergroup Relations Through Upregulated In- Group Empathy, Cooperation, Conformity, and Defense. Biological Psychiatry. Published online February 2016:165-173. doi:10.1016/j.biopsych.2015.03.020 120. 120. Leyens J-P, Cortes B, Demoulin S, et al. Emotional prejudice, essentialism, and nationalism The 2002 Tajfel lecture. Eur J Soc Psychol. Published online 2003:703-717. doi:10.1002/ejsp.170 121. 121. Love TM. Oxytocin, motivation and the role of dopamine. Pharmacology Biochemistry and Behavior. Published online April 2014:49-60. doi:10.1016/j.pbb.2013.06.011 122. 122. Ma X, Luo L, Geng Y, Zhao W, Zhang Q, Kendrick KM. Oxytocin increases liking for a country’s people and national flag but not for other cultural symbols or consumer products. Front Behav Neurosci. Published online August 5, 2014. doi:10.3389/fnbeh.2014.00266 123. 123. Andari E, Hurlemann R, Young L. A Precision Medicine Approach to Oxytocin Trials. Curr Top Behav Neurosci. 2018;35:559-590. doi:10.1007/7854_2017_29 124. 124. Carter CS. The Oxytocin–Vasopressin Pathway in the Context of Love and Fear. Front Endocrinol. Published online December 22, 2017. doi:10.3389/fendo.2017.00356 125. 125. Stallen M, De Dreu CKW, Shalvi S, Smidts A, Sanfey AG. The Herding Hormone. Psychol Sci. Published online September 18, 2012:1288-1292. doi:10.1177/0956797612446026 126. 126. Shalvi S, De Dreu CKW. Oxytocin promotes group-serving dishonesty. Proceedings of the National Academy of Sciences. Published online March 31, 2014:5503-5507. doi:10.1073/pnas.1400724111 127. 127. Fehr E, Fischbacher U. The nature of human altruism. Nature. Published online October 2003:785-791. doi:10.1038/nature02043 128. 128. Aydogan G, Furtner NC, Kern B, Jobst A, Müller N, Kocher MG. Oxytocin promotes altruistic punishment. Social Cognitive and Affective Neuroscience. Published online August 29, 2017:1740-1747. doi:10.1093/scan/nsx101 129. 129. Shiramizu VKM, Yamamoto ME. “In x Out”: Reviewing the Group Bias through the Biological Perspective. Temas Psicol. Published online 2017:1441-1502. doi:10.9788/tp2017.3-23en 130. 130. Geng Y, Zhao W, Zhou F, et al. Oxytocin Enhancement of Emotional Empathy: Generalization Across Cultures and Effects on Amygdala Activity. Front Neurosci. Published online July 31, 2018. doi:10.3389/fnins.2018.00512 131. 131. Buffone AEK, Poulin MJ. Empathy, Target Distress, and Neurohormone Genes Interact to Predict Aggression for Others–Even Without Provocation. Pers Soc Psychol Bull. Published online September 10, 2014:1406-1422. doi:10.1177/0146167214549320 132. 132. Grillon C, Krimsky M, Charney DR, Vytal K, Ernst M, Cornwell B. Oxytocin increases anxiety to unpredictable threat. Mol Psychiatry. Published online November 13, 2012:958-960. doi:10.1038/mp.2012.156 133. 133. Jiang Y, Platt ML. Oxytocin and vasopressin flatten dominance hierarchy and enhance behavioral synchrony in part via anterior cingulate cortex. Sci Rep. Published online May 29, 2018. doi:10.1038/s41598-018-25607-1 134. 134. Everett JAC, Faber NS, Crockett M. Preferences and beliefs in ingroup favoritism. Front Behav Neurosci. Published online February 13, 2015. doi:10.3389/fnbeh.2015.00015 135. 135. Huang Y, Zhen S, Yu R. Distinct neural patterns underlying ingroup and outgroup conformity. Proc Natl Acad Sci USA. Published online February 19, 2019:4758-4759. doi:10.1073/pnas.1819421116 136. 136. Feldblum JT, Manfredi S, Gilby IC, Pusey AE. The timing and causes of a unique chimpanzee community fission preceding Gombe’s “Four-Year War.” Am J Phys Anthropol. Published online March 22, 2018:730-744. doi:10.1002/ajpa.23462 137. 137. Samuni L, Preis A, Mundry R, Deschner T, Crockford C, Wittig RM. Oxytocin reactivity during intergroup conflict in wild chimpanzees. Proc Natl Acad Sci USA. Published online December 27, 2016:268-273. doi:10.1073/pnas.1616812114 138. 138. Young LJ, Flanagan-Cato LM. Editorial comment: Oxytocin, vasopressin and social behavior. Hormones and Behavior. Published online March 2012:227-229. doi:10.1016/j.yhbeh.2012.02.019 139. 139. Iyengar S, Massey DS. Scientific communication in a post-truth society. Proc Natl Acad Sci USA. Published online November 26, 2018:7656-7661. doi:10.1073/pnas.1805868115 140. 140. Bolsen T, Druckman JN, Cook FL. Citizens’, Scientists’, and Policy Advisors’ Beliefs about Global Warming. The ANNALS of the American Academy of Political and Social Science . Published online February 8, 2015:271-295. doi:10.1177/0002716214558393 141. 141. Ferris C. Vasopressin/oxytocin and aggression. Novartis Found Symp. 2005;268:190-198; discussion 198-200, 242-253. https://www.ncbi.nlm.nih.gov/pubmed/16206881 142. 142. Kawada A, Nagasawa M, Murata A, et al. Vasopressin enhances human preemptive strike in both males and females. Sci Rep. Published online July 4, 2019. doi:10.1038/s41598-019- 45953-y 143. 143. Tackenberg MC, McMahon DG. Photoperiodic Programming of the SCN and Its Role in Photoperiodic Output. Neural Plasticity. Published online 2018:1-9. doi:10.1155/2018/8217345 144. 144. Coomans CP, Ramkisoensing A, Meijer JH. The suprachiasmatic nuclei as a seasonal clock. Frontiers in Neuroendocrinology. Published online April 2015:29-42. doi:10.1016/j.yfrne.2014.11.002 145. 145. Sinclair ARE. Mammal population regulation, keystone processes and ecosystem dynamics. Phil Trans R Soc Lond B. Published online August 28, 2003:1729-1740. doi:10.1098/rstb.2003.1359 146. 146. Wahl S, Engelhardt M, Schaupp P, Lappe C, Ivanov IV. The inner clock—Blue light sets the human rhythm. J Biophotonics. Published online September 2, 2019. doi:10.1002/jbio.201900102 147. 147. Duffy JF, Czeisler CA. Effect of Light on Human Circadian Physiology. Sleep Medicine Clinics. Published online June 2009:165-177. doi:10.1016/j.jsmc.2009.01.004

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