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Foraging for Foundations in Decision Neuroscience: Insights from Ethology

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Foraging for Foundations in Decision Neuroscience: Insights from Ethology PERSPECTIVES neurophysiological, optogenetic and OPINION neuroimaging paradigms are regularly integrated in decision neuroscience. Foraging for foundations in decision Central features of most work in decision neuroscience are carefully controlled and structured environments neuroscience: insights from ethology that rigorously specify the costs and benefits of behaviours — that is, what Dean Mobbs, Pete C. Trimmer, Daniel T. Blumstein and Peter Dayan needs to be optimized and under what constraints. This has led to many functional Abstract | Modern decision neuroscience offers a powerful and broad account of MRI (fMRI) studies making use of only human behaviour using computational techniques that link psychological and a relatively modest collection of tasks neuroscientific approaches to the ways that individuals can generate near-optimal that reflect aspects of the structural and choices in complex controlled environments. However, until recently , relatively functional implementation of choice. little attention has been paid to the extent to which the structure of experimental However, whether these tasks are environments relates to natural scenarios, and the survival problems that individuals ethologically credible and comprehensive is not always clear. These two questions have evolved to solve. This situation not only risks leaving decision-theoretic are of particular importance given the accounts ungrounded but also makes various aspects of the solutions, such as influential observation in decision theory hard-wired or Pavlovian policies, difficult to interpret in the natural world. Here, we that completely optimal behaviour is suggest importing concepts, paradigms and approaches from the fields of ethology uncommon because of its computational and behavioural ecology , which concentrate on the contextual and functional and mnestic complexity, implying that approximations must be ubiquitous. Such correlates of decisions made about foraging and escape and address these lacunae. approximations are presumably tailored to work well in common and relevant It begins to be difficult, and even in some cases These theories fall into the global environments at the expense of rare ones; impossible, to say where ethology stops and frameworks of Huxley, Mayr and Tinbergen thus, it is vital to consider problems that neurophysiology begins. Tinbergen, 1963 (BOx 1), which seek to answer wider are ethologically well founded and thus questions of the proximate (for example, functionally relevant. Ethology, the scientific study of animal physiological) and ultimate (for example, In this Opinion article, we lay out behaviour under natural conditions, and adaptive or Darwinian fitness-increasing) a blueprint for a closer integration of its offspring, behavioural ecology, which repercussions of an animal’s decisions. ethological and behavioural ecological studies how behaviour may vary adaptively By contrast, decision neuroscience has approaches with work on the neural in response to environmental variation, built accounts of the proximate causes of basis of decision-making. The objective have provided valuable insights into animal behaviour that tie optimizing theories such is to build biological realism into decision-making in the natural world. as dynamic programming and Bayesian decision neuroscience with a focus on The paradigms used by ethologists and decision theory to their psychological and translating the extensive work that has behavioural ecologists examine decisions neurobiological substrates. Such optimizing been conducted on non-human animals relating to the exploitation of resources and theories are shared with ethology and to the study of humans. We concentrate optimal foraging, the ways that predators behavioural ecology, along with other on foraging, which is an early harbinger can be avoided and deterred, the reduction fields such as economics, operations of this approach13–17. We consider three of competition and the maximization of research and control theory. However, the constraints on foraging that are of interest reproductive success1. Such decisions are bulk of the work in decision neuroscience for human decision neuroscience: first, often complex because individuals need to focuses on building and understanding energy-based decisions in which metabolic balance energy costs with other survival process models, such as models of needs, including energy consumption needs; a central lesson from behavioural inference (for example, diffusion-to- and fuelling, need to be balanced; ecology is that trade-offs are ubiquitous. In bound decision-making8, realized in second, competitive foraging; and, third, addition, the computations that characterize neural substrates such as the parietal and foraging under the risk of predation, these decisions are described in formal prefrontal cortex9) and learning models when the requirement is to be strategic mathematical accounts — such as optimal (for example, rules based on prediction about averting threats and facilitating escape theory2, foraging theories3 including error, such as the Rescorla–Wagner rule10, the possibility of escape. Along with the marginal value theorem (MVT)4, or temporal-difference learning11, which these examples, we discuss formal tools ideal free distribution (IFD) theory5 and is realized in substrates such as the phasic developed by behavioural ecologists to state-dependent valuation6 — using methods activity of dopamine neurons12). Data from examine various decisions that are made by such as stochastic dynamic programming7. a wealth of anatomical, pharmacological, animals. Taken together, these constraints NATURE REVIEWS | NEUROSCIENCE © 2018 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. PERSPECTIVES and tools provide new insights and help neuroscience is the bandit modelling example, trust games23) and intertemporal integrate human decision-making into approach, which involves binary (or choice24,25. This relatively limited in number the guiding frameworks (BOx 1). Indeed, multiple) choice static or restless ‘bandits’ set of paradigms, together with their we note that this form of integration is that deliver rewards and punishments. This offshoots, has provided us with our current already becoming popular in comparative approach is used to measure value-based set of potentially oversimplified tests of how neuroscience13,18,19. and explore-or-exploit decision processes20. the brain computes decisions. Crucially, Other paradigms have been used to measure most realizations of the aforementioned Decision neuroscience other aspects of the decision processes, paradigms leave substantial gaps in our Human decision neuroscience has drawn including working memory (for example, understanding of the ways that decisions upon a set of experimental decision the AX-continuous performance task21), are made in the real world, or indeed of paradigms from the fields of economics sequential information integration and solutions to “The problems that the brain and psychology. These approaches have diffusion-to-bound decision-making (for evolved to solve” (REF.26). been highly successful because they example, motion discrimination using More broadly, ecologically important, carefully control the variables of interest random dot kinematograms9), retrospective fitness-determining decisions relate to and constrain computational models that and prospective planning (for example, the core problems that all animals face. These fit the data. One stalwart of human decision two-step task22), social decision-making (for decisions include rules underlying fighting, foraging, fleeing and reproduction. Such rules are under strong selection pressures Box 1 | The overlapping frameworks of Huxley, Tinbergen, Mayr and Marr and probably underpin all decision It has long been recognized that there are two fundamentally different classes of questions that processes26. Although it is widely understood biologists can ask: why a behaviour or neural structure takes the form it does and how this comes to that the brain contains a set of heuristic happen, with subtle and complex nuances within each class. Many different authors in cognitive mechanisms that evolved to make fast and 18,108 107,110,111 science and ethology have proposed versions of these questions. One of the first to offer accurate decisions with as little effort as guidelines for biobehavioural questioning was Julian Huxley, who proposed that one should attempt possible, there has been less work in decision to address three issues. First, what are the behavioural and neurobiological mechanisms that facilitate ecological decision-making (the mechanistic-physiological question)? Second, what is the neuroscience paying due heed to the functional or survival value of such decisions (the adaptive-function question)? Last, what is the selection pressures or the bounds on their evolutionary course of the physiology or behaviour that, for example, supports decision-making use (when one task paradigm transitions to processes (the historic (palaeontological) question)? These three questions were extended and another). Ethologically inspired theorists further refined by Tinbergen107, who proposed that biologists should also answer questions of the have begun to consider the evolutionary ontogeny of the behaviour and biology (how does decision-making change over an individual’s roots of human decision-making to lifespan?). Mayr combined these four questions to form two core questions. First, what are the explain
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