Trait Anxiety, Neuroticism, and the Brain Basis of Vulnerability to Affective Disorder

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CHAPTER 24 Trait Anxiety, Neuroticism, and the Brain Basis of Vulnerability to Affective Disorder

Sonia Bishop & Sophie Forster

Studies of the brain basis of “norma- pathways through which risk to affective ill- tive” or “healthy” processing of emotion- ness is conferred. ally salient stimuli have flourished over Understanding the brain basis of vulner- the last two decades. An initial focus on ability to affective disorder goes hand in regions implicated in the detection of emo- hand with a focus on individual variation tionally salient stimuli (Morris et al., 1996; and, in particular, trait differences in the Whalen et al., 1998) has broadened to mechanisms supporting the detection and include discussion of mechanisms support- controlled processing of emotional stimuli. ing regulatory functions (Bishop, Duncan, How do we study trait differences in vul- Brett, & Lawrence, 2004; Davidson, 2002; nerability to anxiety and depressive disor- Ochsner, Bunge, Gross, & Gabrieli, 2002; ders and try to unpack the brain mechanisms Kim, Somerville, Johnstone, Alexander, & though which these might act? A number of Whalen, 2003; Phelps, Delgado, Nearing, & approaches have been adopted, with both LeDoux, 2004). Running in parallel to this shared and unique advantages and limita- literature, psychiatric imaging studies have tions. described alterations in brain function across Studies of the brain basis of vulnerabil- a wide range of anxiety and depressive dis- ity to affective disorders typically rely on orders (for reviews and meta-analyses see recruiting nonclinical volunteer samples and Etkin & Wager, 2007; Ressler & Mayberg, then regressing scores on self-report mea- 2007; Shin & Liberzon, 2010;Stein2009). The sures of trait affect or experience of disorder- study of the brain mechanisms underlying related symptomatology against indices of vulnerability to disorder has, for some rea- brain function or structure. It is important son, fallen outside of the primary spotlight. to remember that this approach is correla- We argue that work of this nature is criti- tional in nature, and hence no conclusions cal to bridging studies in healthy volunteer can be drawn about the direction of causal- and patient groups and to identifying the ity. For example, if we find that, in a student

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population, elevated scores on a measure category uses measures taken from the per- of neuroticism are linked to poor frontal sonality literature, such as the Neuroticism recruitment, this could equally plausibly scale from either the Eysenck Personality reflect individuals scoring high on neuroti- Questionnaire (EPQ; Eysenck & Eysenck, cism being less able to cope with envi- 1975) or the NEO Personality Inventory ronmental stress, resulting in diminished (Costa & MacCrae, 1992). The third cat- frontal function; individuals with compro- egory focuses on genetic markers that mised frontal function being more likely differ among individuals (functional poly- to develop a neurotic personality style; morphisms with two or more common vari- both elevated neuroticism and compro- ants) and that have been linked to differ- mised frontal function stemming from a pri- ences in affect-related behaviors in humans mary disruption to neurotransmitter func- and other species. In this chapter, we focus tion; or all of these factors in combination. on the first two of these categories, com- There are also important methodological menting only briefly on the third (for issues pertaining to good practice in con- further discussion, see Chapter 25). The ducting correlational analyses of brain activ- majority of studies on the brain basis of vul- ity, which are discussed briefly later in the nerability to affective disorder falling within chapter. these categories have used measures of trait A shared positive feature of studies in this anxiety (category 1) or neuroticism (cate- area is that constructs such as trait anxiety or gory 2). We use these examples to explore neuroticism can be examined as continuous the state of the field as it stands and to factors, facilitating exploration of their lin- address outstanding questions for future ear and nonlinear relationships with regional research. brain activity. This allows for a more com- plex and potentially accurate picture to be drawn than one that solely uses DSM cat- Trait Anxiety and Neuroticism: egorical assessments of the binary presence Indexing Vulnerability to Affective or absence of a given disease state; the lat- Disorders through Self-Report ter “diagnostic” approach faces limitations arising from difficulties in applying cate- The trait subscale of the Spielberger State gorical cutoffs, high comorbidity between Trait Anxiety Inventory (Spielberger et al., many anxiety and depressive disorders, and 1983) is a widely used measure of trait poor diagnostic reliability (Brown & Barlow, propensity to anxiety. It has been shown 2009). to have good concurrent validity, with Studies of the brain basis of vulnerabil- patients with anxiety disorders (ADs) scor- ity to affective disorder can be categorized ing higher on the STAI trait subscale than according to the measure used to assess controls (Bieling, Antony, & Swinson, 1998). individual differences in trait affective style. Although fewer studies have examined pre- Arguably there are three main categories. dictive validity, pretrauma STAI trait scores The first involves measures derived from have been found to predict levels of post- the clinical literature and normed for use traumatic stress disorder symptomatology in nonclinical populations to assess individu- after trauma (Weems et al., 2007). How- als’ tendency to show disorder-related symp- ever, the STAI has been criticized for having tomatology, affective and cognitive styles. poor discriminative validity, with individu- A prominent example is the Spielberger als with major depressive disorder (MDD) State Trait Anxiety Inventory (STAI; Spiel- also showing elevated scores on the trait berger, Gorsuch, Lushene, Vagg, & Jacobs, subscale (Mathews, Ridgway, & Williamson, 1983), widely used in studies of the cog- 1996). One possibility is that this low dis- nitive correlates of trait anxiety within criminant validity reflects a poor choice nonselected student samples. The second of anxiety-specific items for the scale. A Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

TRAIT ANXIETY, NEUROTICISM, AND THE BRAIN BASIS OF VULNERABILITY TO AFFECTIVE DISORDER 555

second is that there is genuine shared vari- ance underlying vulnerability to both ADs and MDD. Not only are STAI trait scores elevated in patients with MDD but scores on this and other anxiety scales, such as the Tay- lor Manifest Anxiety Scale (Taylor, 1953), have also been found to correlate highly with scores on self-report measures of depres- sive symptomatology; for example, the Beck Depression Inventory (BDI; Beck Ward, Mendelson, Mock, & Erbaugh, 1961)and personality indices of neuroticism (Luteijn & Bouman, 1988). Neuroticism is charac- terized by a propensity for negative affect (Watson & Clark, 1984). This trait, measured by widely used instruments such as the NEO Personality Inventory and the Eysenck Per- sonality Questionnaire, has emerged over the last century as one of the most widely studied personality traits (Costa & Mac- Crae, 1992; Eysenck & Eysenck, 1975; John, 1990). The relationship with vulnerability to affective disorder has arguably been inves- tigated more thoroughly for neuroticism than for any other dimension of personal- ity (Brown, 2007; Brown & Rosellini, 2011, Kendler, Gardner, Gatz, & Pedersen, 2007). There is strong evidence to support not only shared variance but also common genetic influences among neuroticism, anxiety dis- 24 1 orders, and depressive disorders (Hettema Figure . . Anxiety, neuroticism and et al., 2008; Kendler et al., 2007). depression: overlapping constructs? Three alternate models. (A). Self-report measures of A likely interpretation of the high corre- anxiety, depression, and neuroticism could lations observed among indices of anxiety, potentially all be tapping the same single depression, and neuroticism is that they tap, underlying trait. (B). Alternatively, anxiety and at least in part, into a common underlying depression might be separate components of the trait (Figure 24.1). According to the popular broader trait of neuroticism. In keeping with this tripartite model, anxiety and depression not perspective, the NEO-PI-R includes anxiety and only have a shared component – a propen- depression as subfactors, or “facets,” of sity to negative affect (which arguably maps neuroticism (Costa & McCrae; 1995). (C). A on to the construct of neuroticism) – but third theoretical stance, represented by Clark 1991 also unique components of anxious arousal and Watson’s ( ) tripartite model, asserts that and anhedonia, respectively (Clark & Wat- anxiety and depression not only have a shared component of negative affect or general distress son, 1991). This conception has led to the (potentially corresponding to the construct of development of the Mood and Anxiety neuroticism) but also unique components of Symptoms Questionnaire (MASQ; Watson “anxious arousal” (autonomic hyperactivity) and & Clark, 1991), which aims to measure “anhedonic depression” (low positive both these shared and unique components. affect). Unfortunately the MASQ focuses on “state” Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

556 SONIA BISHOP & SOPHIE FORSTER

or current mood levels and not on trait dif- subject to criticism (Vul, Harris, Winkiel- ferences between individuals. Indeed, the man, & Pashler, 2009). However, many of scarcity of trait measures of the propensity the issues raised – pertaining to whole-brain to anxiety and depression poses a major dif- correlational analyses, insufficient correc- ficulty for researchers aiming to investigate tion for multiple comparisons, and biased the brain basis of these tendencies. Not only selection of regions of interest – can be the MASQ but also the major depressive avoided if investigations of differences in inventories – including both the BDI and the regional brain function associated with per- Center for Epidemiologic Studies Depres- sonality indices or trait affective style are sion Scale (CES-D; Radloff 1977) – focus on constrained to ones that specifically test the- current levels of symptomatology. This may ories derived from the cognitive or social explain why several imaging studies have psychological literature. An elegant argu- used neuroticism as a proxy for vulnerability ment for this approach was initially made to depression, but doing so inevitably hin- by Kosslyn et al. (2002). In this article, Koss- ders attempts to disentangle the extent to lyn and colleagues take the proposal put which neuroticism, trait anxiety, and trait forward by Underwood (1975) – that nat- depression involve disruption to common or urally occurring individual differences can unique mechanisms at either a cognitive or be used to test psychological theories and systems (regional brain structure and func- to reveal the structure of psychological pro- tion) level of analysis. cesses, potentially providing greater insights than group-based methods – and argue that the same logic can be applied to the use Studying Affective Trait-Related of individual differences to investigate the Differences in Cognitive and Brain biological mechanisms that underpin cogni- Function: Lessons from the Last tive processes. The authors make the case Decade that there is natural variation around every central tendency, that individuals may differ Over the last 10 years, much progress has in the efficiency and recruitment of mecha- been made in using neuroimaging tech- nisms (which can be studied at various lev- niques to study individual differences in els including both regional brain activation neurocognitive function; recent challenges and cognitive processing), and that pooling and developments set the stage for equiva- information across individuals may be unin- lent progress over the next decade. In the formative or misleading. They also point out early 2000s, neuroimaging studies of person- that the main dangers of unguided correla- ality led to a conceptual shift in the approach tional studies can be avoided by theoretically to the investigation of human brain func- grounding the study design and the analy- tion. These studies argued that individual sis and interpretation of results, with alter- variation need not simply be treated as a nate theoretical explanations of observed source of noise in group studies of “nor- correlations being used to generate further mative” neurocognitive function but that hypotheses than can in turn be tested. In between-subject differences could be stud- the sections that follow, we illustrate how ied in their own right by examining associa- the approach proposed by Kosslyn and col- tions between traits such as extraversion or leagues can be applied, using the example of neuroticism and regional brain function (for studies that have investigated the brain basis a review see Canli, 2004). of the association between trait anxiety and Although these studies were ground- attentional capture by threat. In addition, breaking in advancing the investigation we explore if we can ascertain whether neu- of individual differences in neurocognitive roticism shows a similar, potentially com- function, as with many first steps in a new mon, relationship to the function of these field, several of these studies have since been mechanisms. Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

TRAIT ANXIETY, NEUROTICISM, AND THE BRAIN BASIS OF VULNERABILITY TO AFFECTIVE DISORDER 557

Top-down attentional control mechanisms

Competition among stimuli Output to response for representation and memory systems

Bottom-up sensory- driven mechanisms

Figure 24.2. According to the biased-competition model of selective attention (Desimone & Duncan, 1995; Kastner & Ungerleider, 2000), top-down attentional control mechanisms, which favor task-relevant stimuli, and bottom-up sensory-driven mechanisms, sensitive to stimulus salience, jointly determine which stimuli are selected for further processing. Adapted from Bishop (2008) and Kastner and Ungerleider (2000), with permission.

(a) (b)

**

TUMOR

APPLE TUMOR

Figure 24.3. Two widely used paradigms in the attention to threat literature. (A) In the Emotional Stroop task, participants are asked to name the font color of a word (here green/gray), ignoring its meaning, which can be either threat-related or neutral in valence. High trait anxious subjects show RT slowing for threat-related words. (B) In the dot probe task, participants are presented with two words, followed by a “probe” (the two asterisks presented here) in the location of one of the words. They are typically asked either to indicate when the probe appears or to specify its orientation. On key trials, one word is threat- related, and the other is neutral. High trait anxious individuals show RT speeding when the location of the probe was previously occupied by a threat word (as in the example here), suggesting that attention was allocated to the location of the threat word. Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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Trait Anxiety, Neuroticism, and models typically propose that anxiety acts Threat-Related Biases in Selective by amplifying the signal from a bottom- Attention: Cognitive Models and up preattentive threat detection mecha- Findings nism that biases attentional competition in favor of threat-related stimuli. When these Both AD patients and high trait anxious par- stimuli are distracters (non- task-relevant), ticipants show elevated attentional capture this is held to interfere with the process- by threat-related stimuli (Mathews & Mack- ing of target stimuli, as indexed by slowed intosh, 1998). According to biased compe- reaction times (RTs) and/or elevated error tition models of selective attention, atten- rates. These models have not, in the most tional competition is influenced both by part, argued for disrupted top-down or con- “bottom-up” sensory mechanisms that prior- trolled processing of threat-related stimuli in itize the processing of salient stimuli and by anxiety. “top-down” attentional control mechanisms A number of studies have used vari- that support the processing of task-relevant ants of the probe detection task to examine stimuli (Figure 24.2; Desimone & Duncan, whether attentional biases are also associ- 1995; Kastner & Ungerleider, 2000). Stimu- ated with elevated neuroticism (“N”) scores. lus valence – the extent to which a given These have produced rather mixed results. stimulus is threat or reward related – is an Reed and Derryberry (1995) found evidence important dimension of stimulus salience. for a correlation between N scores and atten- A number of selective attention tasks have tional bias toward negative trait adjectives been adapted to examine how stimulus previously rated as self-applicable. How- valence, especially threat-relatedness, influ- ever, this correlation was only observed ences attentional competition. Two notable at one of three alternate adjective-probe examples are the Emotional Stroop and stimulus-onset asynchronies (500 ms, not probe detection tasks (Figure 24.3). In the 250 ms or 750 ms). In addition, Chan, Emotional Stroop task, participants name Goodwin, and Harmer (2007) and Rijs- the ink color of a stimulus word while ignor- dijk et al. (2009) failed to find any rela- ing its semantic content. On this task, high tionship between neuroticism and perfor- trait anxious individuals show slower color mance on probe detection tasks using social naming of threat-related words than emo- threat words and subliminally presented tionally neutral words; in low trait anxious threat-related faces, respectively. Differ- individuals this slowing is reduced or absent ences among these studies in the choice (Richards & Millwood, 1989). In the probe of stimuli, stimulus onset asynchrony SOA, detection task, participants are presented and neuroticism scale (EPQ versus NEO) with two words or pictures (e.g., faces) fol- further complicate interpretation of these lowed by a single dot or pair of dots in the findings. position previously occupied by one of the Interestingly, the limited evidence for an two stimuli. Here, high trait anxious indi- association between neuroticism and atten- viduals are faster to detect the presence of a tional bias toward negatively valenced stim- single dot or to determine the orientation uli parallels similarly mixed findings within of a pair of dots, when the dot probe is the subclinical depression literature. Here, presented in the position previously occu- two studies using the Emotional Stroop pied by a threat-related stimulus (Macleod task have reported increased RT slowing &Mathews,1988). for color naming of negatively valenced These findings have informed cognitive words as a function of scores on the Beck models of anxiety that extend the biased Depression Inventory (BDI). These effects competition model of selective attention to were strongest in participants with elevated specifically deal with attentional capture by BDI scores at two time points a year apart threat-related stimuli (Mathews & Mackin- (Williams & Nulty, 1986) and were not found tosh, 1998; Mogg & Bradley, 1998). These when a depressed mood was induced in par- Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

TRAIT ANXIETY, NEUROTICISM, AND THE BRAIN BASIS OF VULNERABILITY TO AFFECTIVE DISORDER 559

ticipants with low BDI scores (Gotlib & whether neuroticism is linked to a simi- McCann, 1984), potentially suggesting the lar pattern of task-specific hyperactivity and role of an enduring trait conferring vulnera- hypo-recruitment. Studies that have begun bility to depression, rather than simply state to address this question are reviewed next. affect. Other studies have found no rela- tionship between individual differences in subclinical levels of depression and atten- From Networks to Modules and Back tional bias toward negative or threat-related Again stimuli across both the Emotional Stroop and probe detection tasks (Bradley, Mogg, The late 1930s through to the early 1950s Falla, & Hamilton, 1998; Gotlib, MacLachan, saw the advent of theories that proposed &Katz,1988; Hill & Dutton, 1989; Hill & that networks of brain regions including Knowles, 1991; Macleod & Hagan, 1992). areas such as the hippocampus, cingulate One possibility is that a partial corre- gyrus, amygdala, and orbital frontal cortex late of depression scores, such as trait anx- were responsible for emotional processing iety levels, rather than depression itself, (MacLean 1949; Papez, 1937). Support for might be responsible for the intermittently the “Papez circuit” and “limbic system” was reported attentional interference effects. A countered by criticisms that these accounts similar argument can be made for neuroti- were more descriptive than functional and cism. The NEO measure of neuroticism lacked a clear rationale for inclusion of cer- comprises different subfacets, one of which tain regions and the exclusion of others is especially related to anxiety and another to (for more extensive discussion of these crit- depression (Costa & MacCrae, 1992; see also icisms,see Chapter 9 in Gazzaniga Ivry, & Figure 24.1). Variability among studies in Mangun, 2009; Early neuroimaging studies the items that high-N participants endorse of emotion conducted in the late 1990sand might explain the occasional but inconsis- early 2000s took a more modular approach. tent findings of attentional biases reported Much research was focused on the amygdala by studies using this measure. and its role in the detection or evaluation It is also possible that multiple mecha- of threat (Morris et al., 1996; Vuilleumier, nisms contribute to attentional capture by Armony, Driver, & Dolan, 2001;Whalen threat stimuli – with trait anxiety, neu- et al., 1998, 2004) Indeed, a number of stud- roticism, and depression potentially sharing ies from the later part of this era used scan a common relationship with one of these parameters that focused data acquisition on mechanisms but differing in their associa- a narrow slab of slices covering the amygdala tion with others. The most obvious can- but omitting much of the rest of the brain. didate mechanisms are those involved in In contrast, within the last 5 to 10 years, bottom-up responsivity to threat versus top- there has been an increasing focus on the down attentional control. Investigation of interplay of regions involved in the evalua- the brain basis of these mechanisms opens tion of threat stimuli with those that enable up a new door for examining how different the regulation of emotional state and phys- trait characteristics are linked to the func- iological fear responses, the (re)appraisal of tion of these component processes. Specif- stimuli, and the control of attentional focus ically, it is possible to build on what is (Bishop, Duncan, Brett, & Lawrence, 2004a; known about the function of different brain Kim et al., 2003; Ochsner et al., 2002;Phelps regions to explore whether trait anxiety et al., 2004). This focus has been accom- is associated with increased activation of panied by a shift from examining brain brain mechanisms involved in processing regions in isolation and toward conceptu- stimulus threat value, with impoverished alizing regions as nodes within intercon- recruitment of brain mechanisms involved nected networks, the activation of which in attentional control, or with altered func- varies with task engagement and may be tion of both processes. We can also explore meaningful even at “rest” (Deco, Jirso, & Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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McIntosh, 2011). Neuroimaging investiga- dala response to threat-related distracters tions of the association between trait anxiety (Bishop, Duncan, & Lawrence, 2004). and brain function and structure have simi- However, in that study, it was state rather larly evolved across this time period. In the than trait anxiety that showed a relationship remaining sections of this chapter, we exam- to the amygdala response to unattended ine what these studies can tell us about the threat stimuli. In addition, these results do brain basis of the association between trait not necessarily indicate that high anxious anxiety and attentional capture by threat, individuals show an increased preattentive the shared or distinct relationship with neu- amygdala response to threat-related dis- roticism, and the potential common under- tracters. An alternate possibility is that pinning of function across other domains of attentional resources may not have been emotional processing. fully occupied by the primary task, with attentional “spillover” facilitating the pro- cessing of threat-related distracters. Indeed, Amygdala and Frontal Mechanisms it has been demonstrated that when the underlying Attentional Capture by perceptual demands or “load” of the main Threat: Hyper- and Hypo-Activity task is increased, a differential amygdala Linked to Trait Anxiety response to threat-related versus neutral distracters is no longer observed (Pessoa, Based on findings from the basic neuro- McKenna, Gutierrez, & Ungerleider, 2002); science literature, a relatively widely held between-participant differences in the view (which has recently come under amygdala response to threat distracters as renewed scrutiny; Pessoa and Adolphs, a function of anxiety also being eliminated 2010; see also Chapter 15)isthata (Bishop, Jenkins, & Lawrence, 2007). direct subcortico-thalamo-amygdala path- An interesting model, of value in con- way facilitates the preattentive processing of ceptualizing these findings, is the load the- threat-related stimuli (LeDoux, 2000;Tami- ory put forward by Lavie (e.g., Lavie, 2005). etto & de Gelder, 2010). In line with this Lavie argues that the debate between “early” position, a number of neuroimaging stud- and late” accounts of selective visual atten- ies conducted in the early 2000s reported tion (i.e., whether or not the processing of that the amygdala response to threat-related certain stimulus characteristics is obligatory stimuli such as fearful faces is not modulated and unconstrained by attentional resources) by the focus of spatial attention (Anderson, may be resolved by taking into account Christoff, Panitz, De Rosa, & Gabrieli, 2003; the perceptual load of the task at hand Vuilleumier et al., 2001). These findings lent and allowing for two separate stages of support to the proposition that the amyg- attentional competition. According to this dala might provide the biological under- model, there is, first, a stage of early per- pinning, or instantiation, of the preatten- ceptual competition. The processing of dis- tive threat detection mechanism described tracters terminates at this stage when the in cognitive models of anxiety. Accord- perceptual load of the primary task is high. ing to this proposal, amygdaloid activation Second, under conditions of low percep- might influence the competitive success of tual load, competition is held to occur threat-related stimuli in winning attentional for further processing resources, including resources through a gain function analogous the initiation of behavioral responses, with to that held to underlie the facilitation of active recruitment of control mechanisms the processing of targets by top-down atten- being required to inhibit the processing of tional control (see Chapter 14). salient distracters and support task-related Further support for this position processing. Lavie’s hybrid early/late model appeared, initially, to be provided by find- has primarily been used to account for ings that individuals with elevated anxiety findings showing that increasing perceptual levels show a stronger selective amyg- load reduces or eliminates the processing Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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of affectively neutral salient distracters, attentional control under task conditions such as moving dot patterns, lexical stim- where these mechanisms are needed to reg- uli that promote competing responses to ulate trial-by-trial fluctuations in process- that required by the current target, and col- ing competition from emotionally salient orful or novel scenes (Lavie, 2005; Rees, distracters. Frith, & Lavie, 1997). It is, however, inter- This raises two further questions. First, esting to speculate whether the finding can we say anything about the relative that the amygdala response to threat dis- attentional control functions of the lateral tracters is diminished under high load prefrontal and anterior cingulate cortical (Bishop et al., 2007; Pessoa et al., 2002) regions shown to be under-recruited by high might be consistent with amygdaloid pro- trait anxious individuals? Second, if trait cessing of threat-related stimuli being sub- anxiety is linked to difficulties in the use ject to similar perceptual processing limi- of these frontal regions to regulate atten- tations that have been found to affect the tion, will they also be apparent when dis- processing of other classes of salient visual tracter salience is unrelated to threat value? stimuli. In regard to the former question, it has been An alternate theoretical stance to that suggested that specific subregions of the pre- put forward by Mathews and Mackintosh frontal cortex may play differing roles in (1998) is that elevated trait anxiety is asso- top-down attentional control, with the ACC ciated with impoverished recruitment of involved in detecting the presence of com- the frontal mechanisms required for task- petition for processing resources and the lat- focused attentional control. If high trait eral prefrontal cortex (LPFC) responding to anxious participants show impaired recruit- increased expectation of processing compe- ment of attentional control mechanisms, tition by augmenting top-down control to this could result in increased “capture” of support the processing of task-relevant stim- attentional resources by threat-related dis- uli (Botnivick, Cohen, & Carter, 2004;see tracters. As just outlined, Lavie argues that Figure 24.4 for illustration of the regions con- the active recruitment of attentional con- cerned). Evidence for this account has pri- trol mechanisms to support the processing marily come from studies using response- of targets and inhibit the processing of dis- competition tasks with affectively neutral tracters is particularly required under con- stimuli (e.g., Carter et al., 2000; Macdon- ditions of low perceptual load to prevent ald, Cohen, Stenger, & Carter, 2000), includ- salient distracters from receiving further ing ones that manipulate the frequency, and processing. In support of this claim, Lavie hence the expectancy, of high competition cites findings that groups characterized by trials (Carter et al., 2000). Through appli- weakened attentional control – specifically cation of an equivalent frequency manipu- the elderly and children – show particularly lation to a task requiring attentional con- large response competition effects under trol over threat distracters, it is possible low perceptual load conditions (Huang- to investigate whether ACC and LPFC Pollock, Carr, & Nigg, 2002; Maylor & Lavie, regions show parallel differential responses 1998). In an interesting parallel, elevated to unexpected (infrequent) and expected trait anxiety was found to be associated (frequent) threat-related distracters, respec- with diminished activation of the dorsolat- tively. This was indeed found to be the eral prefrontal cortex (DLPFC), ventrolat- case (Bishop, Duncan, Brett, & Lawrence, eral prefrontal cortex (VLPFC), and ante- 2004). Further, the results of this study indi- rior cingulate cortex (ACC) in response to cated that individuals with high levels of threat distracters under conditions of low anxiety showed impoverished recruitment but not high perceptual load (Bishop et of both these mechanisms (state anxiety al., 2007). This finding suggests that trait analyses were reported, similar results were anxiety might be linked to impoverished observed with trait anxiety, unpublished recruitment of frontal regions required for data). Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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Lateral surface Medial wall Dorsolateral Dorsal anterior prefrontal cortex Parietal (mid) cingulate (DLPFC) cortex cortex (dACC)

Rostral anterior cingulate cortex (rACC)

Striatum: Ventrolateral caudate & putamen prefrontal cortex (VLPFC)

Cerebellum

Figure 24.4. Frontal brain regions implicated in attentional regulation of emotionally and non-emotionally salient stimuli include the dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex, (VLPFC), rostral anterior cingulate cortex (rACC), and dorsal anterior (mid) cingulate cortex (dACC). Subgenual anterior cingulate cortex is not shown here. Adapted with permission from Bush, 2010.

Intriguingly, a more recent study has pro- tional distracter and response-competition duced findings that are discrepant from both paradigms. One hopes that these discrepant those of Bishop and colleagues (2004)and findings will spark further research that may those from the earlier response-competition help resolve and unite these results and literature. Using a “face/word” version of advance our theoretical understanding of the Stroop task, Etkin, Peraza, Kandel, and the role of the ACC and LPFC in the detec- Hirsch (2006) asked volunteers to indicate tion and resolution of different types of pro- whether faces showed fearful or happy cessing competition. expressions while ignoring the word “happy” A further point worth considering here or “fearful” superimposed on each face. concerns the role of rostral versus dor- They reported that activation of the ACC, sal subdivisions of the ACC (see Figure rather than the LPFC, increased when pro- 24.4). Early studies reported dorsal ACC cessing competition was expected (frequent activity when processing competition arose face/word incongruent trials) and that LPFC from response competition, and rostral activity increased when processing compe- ACC activity when processing competition tition was infrequent or unexpected. One was caused by the presence of emotion- interesting difference from the study by ally salient but task-irrelevant distracters Bishop, Duncan, Brett, and Lawrence (2004) (Bishop, Duncan, Brett, & Lawrence, 2004; is that in Etkin”s task, both the distracters Bush, Luu, & Posner, 2000). This distinc- and targets were emotionally valenced, with tion is also apparent within the psychiatric the valence of targets and distracters being imaging literature (Bush et al., 1999;Shin balanced across “high-conflict” and “low- et al., 2001). However, more recently this conflict” trials; those conditions differed distinction has been challenged by a range instead in face/word congruence. It is diffi- of studies suggesting a role for the dorsal cult to disentangle effects of emotional con- ACC in emotional processing – not only in gruency from response congruency in this emotional distracter tasks but also in stud- design. However, this still does not easily ies investigating the anticipation and expe- explain why the conditions under which rience of pain and the expression of con- the LPFC and ACC were activated differed ditioned fear (Bishop et al., 2007; Milad, from those previously observed in both emo- Quirk, et al., 2007; see Shackman et al., 2011, Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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for a comprehensive review). This also calls independent relationship between trait anx- for further investigation of the precise func- iety and impoverished recruitment of frontal tion of this region. The difference in nomen- attentional control mechanisms comes from clature conventions used across groups and the ERP literature. Using an antisaccade the changes in those terms across time com- task (where volunteers must saccade away plicate this investigation. In this chapter we from the position in which a cue is pre- follow the nomenclature convention intro- sented), Ansari and Derakshan (2011) found duced by Mayberg and colleagues (1999) that high trait anxious individuals showed and adopted in our earlier work (Bishop, longer antisaccade latencies together with Duncan, Brett, & Lawrence, 2004 , 2007) reduced frontocentral activity during anti- whereby rostral ACC excludes subgenual saccade preparation. ACC (the region ventral to the corpus callo- The studies discussed here provide some sum). The subdivision referred to here as the initial evidence that trait anxiety is linked to dorsal ACC or dACC (see Figure 24.4)has impoverished recruitment of frontal regions elsewhere been renamed the dorsal anterior important for attentional control both when mid-cingulate gyrus since this term arguably processing competition is caused by threat- reflects more accurately the region under related distracters and when it is caused by consideration (Bush, 2010). response conflict. This raises the question The second question raised above con- of whether this deficient recruitment can be cerns the nature of the association between remediated by cognitive interventions such trait anxiety and the deficient recruitment as attentional training. A number of early tri- of frontal attentional control mechanisms. Is als provide some initial hope that this might this association specific to attentional con- indeed be the case (Amir, Weber, Beard, trol over threat, perhaps being secondary Bomyea, & Taylor, 2008; Hakamata et al., to hyper-responsivity of the amygdala to 2010). threat-related stimuli? Or does it reflect a Although work reviewed here suggests more general dysregulation of frontal atten- a relationship between trait anxiety and tional function that is independent of amyg- frontal dysfunction in the absence of task- dala responsivity to threat? The cognitive lit- related differences in amygdala activity erature provides some suggestion that the (Bishop, 2009), this leaves open the question latter might be the case, with findings link- as to whether trait anxiety is also linked to ing trait anxiety to impoverished or inef- amygdala hyper-responsivity to threat in the ficient attentional control (Derryberry & absence of differential activation of frontal Reed, 2002; Eysenck, Derakshan, Santos, mechanisms. To address this question, we & Calvo, 2007). In a test of the hypoth- need to turn to tasks that require the rel- esis that trait anxiety is associated with atively passive processing of threat-related reduced recruitment of frontal attentional stimuli in the absence of demands on atten- control mechanisms even in the absence tion or other executive processes. Surpris- of threat-related stimuli, Bishop (2009) ingly few such studies exist that meet the examined DLPFC recruitment while volun- constraints of having examined amygdala teers performed a response-competition task function and also having measured indi- under conditions of low versus high per- vidual differences in trait anxiety. In one ceptual load. High trait anxious volunteers early study, Etkin et al. (2004) reported that showed reduced DLPFC recruitment to trait anxiety was associated with elevated high response-competition trials under con- amygdala responsivity to masked threat- ditions of low but not high perceptual load, related faces, but not to unmasked threat- in line with the Lavie model and consis- related faces. In a second study, Stein, Sim- tent with trait-anxiety-related dysregulation mons, Feinstein, and Paulus (2007) reported of frontal attentional mechanisms extending that elevated STAI trait scores were linked beyond the specific case of attentional con- to greater amygdala activity during condi- trol over threat. Further support for a threat- tions requiring matching of facial emotions Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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than during conditions requiring matching trait anxiety only partially covary in their of basic shapes. relationship with the function of discrete One intriguing possibility is that an asso- brain mechanisms as might, for example, be ciation between trait anxiety and amyg- predicted by Clark and Watson’s tripartiate dala responsivity to threat-related stimuli model (see Figure 24.1). might primarily be seen when the stimuli At the time of writing, three studies are ambiguous or require some form of res- have examined the correlates of neuroti- olution of their threat value (Whalen, 2007). cism while participants perform fMRI tasks This is arguably more the case for masked involving manipulation of selective atten- than for unmasked threat-related faces and tion and emotional stimuli. Two of the also potentially the case when different faces three – one using the Emotional Stroop task with varying emotional expressions need to and the other the probe detection task – be judged for their equivalence in expres- reported no significant association between sion. This is clearly a tentative hypothesis, neuroticism scores and regional brain activ- and it remains to be more firmly established ity during conditions of attentional compe- under precisely which conditions trait anxi- tition from emotional stimuli (Amin, Con- ety is linked to amygdala hyper-responsivity stable, & Canli, 2004; Canli, Amin, Haas, to threat. Furthermore, given the possibil- Omura, & Constable, 2004). However, given ity that frontal mechanisms may be impor- that the sample size in each case was fairly tant for certain forms of ambiguity resolu- small for a correlational study (12 or fewer tion (Kim et al., 2003; Nomura et al., 2003), subjects), it is difficult to draw strong con- it will also be important to confirm that clusions from these null results. trait-anxiety-related differences in amygdala In a subsequent larger study (n = 36), responsivity to weak or ambiguous threat Haas, Omura, Constable, and Canli (2007) stimuli are not secondary to the differential administered a Stroop-like task, similar to recruitment of frontal mechanisms. that of Etkin et al. (2006), in which tri- als differed in the emotional congruence of target words and the expressions of Neuroticism and the Brain background faces. In this study, the words Mechanisms Influencing Attentional did not map directly onto the names of Capture by Threat the facial expressions, thereby reducing the association between emotional incongru- As reviewed in previous sections of this ency and response conflict. Individuals with chapter, in recent years an increasing num- high neuroticism levels were found to show ber of studies have examined the relation- increased amygdala and subgenual anterior ship between trait anxiety and recruitment cingulate activity to trials with emotion- of the frontal and amygdaloid mechanisms ally incongruent face/word pairs (collapsing implicated in attentional control over threat positive-face/negative-word and negative- distracters. This makes it possible to start face/positive-word trials). This result is to ask relatively specific questions about intriguing, but difficult to relate to find- which parts of the neural circuitry influ- ings from imaging studies examining the encing attentional capture by threat show influence of trait anxiety on the neural altered function in high trait anxious indi- mechanisms regulating selective attention viduals. Although the corresponding litera- to threat, because the task manipulation ture on neuroticism is more limited, we can used by Haas and colleagues (emotional con- look at the initial studies available to begin gruency) is not one of distracter threat- to assess whether neuroticism and trait anx- relatedness, being orthogonal to distracter iety show similar relationships with regional valence. One possibility is that the height- brain function – as might be expected if ened amygdala responsivity to emotion- they both represent the same single underly- ally incongruent stimuli in high-N individ- ing construct – or whether neuroticism and uals reported here might primarily reflect Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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sensitivity to stimuli that are ambiguous in nisms supporting attentional control, during their emotional significance, in line with the nonemotional task performance, in a similar proposals put forward by Whalen and col- manner to that observed for trait anxiety. leagues (Whalen, 2007). There is little existing work that pertains to To explore the “ambiguity sensitivity” this issue. Using an oddball detection task, hypothesis further, we review studies that Eisenberger, Lieberman, and Satpute (2005) have examined the influence of neuroti- found that neuroticism was associated with cism on regional brain activity to emotional reduced lateral prefrontal cortical and ros- stimuli using passive viewing or cognitively tral ACC recruitment but increased dorsal undemanding tasks. Here, the question of ACC activity. Further detailed investigation interest is whether neuroticism is particu- of the relationship between neuroticism and larly linked to heightened amygdala respon- recruitment of lateral frontal and anterior sivity to emotional stimuli when these stim- cingulate subregions is required to form a uli are in some form ambiguous in their clearer picture of the commonalities and dif- valence or threat-relatedness. Canli and col- ferences in the relationship between neu- leagues reported that although the amygdala roticism and trait anxiety with regional brain response to happy faces and positive images function. In particular, as noted earlier, the was predicted by extraversion, there was no precise role of the dorsal ACC in cognitive relationship between neuroticism and amyg- and emotional processing remains an issue dala responsivity to either negative emo- under active debate. tional faces or negative emotional images It is hoped that this chapter has provided (Canli et al. 2001, 2002). Similarly, Britton, a flavor of how, in line with the case made Ho, Taylor, and Liberzon (2007) found no by Kosslyn and colleagues, it is possible relationship between neuroticism and amyg- to conduct neuroimaging studies that may dala responsivity during the passive view- advance both our understanding of the brain ing of emotional images, facial expressions, mechanisms supporting attentional capture and emotional films. Cremers et al. (2010) by threat and the relationship between trait also found no relationship between neuroti- anxiety and variation in the function of these cism and the amygdala response to negative mechanisms. Although there are fewer stud- emotional faces during a gender discrimi- ies pertaining to neuroticism, the available nation task. The one exception is a study studies serve to generate hypotheses that by Chan, Norbury, Goodwin, and Harmer could form the basis of future research. (2009) that examined amygdala responsiv- The work reviewed here also raises ques- ity to fearful, happy, neutral, and morphed tions as to the extent to which the associ- facial expressions during a gender discrim- ation among trait predisposition to anxiety, ination task in individuals high and low amygdala hyperactivity, and frontal hypoac- in neuroticism. Here high N scores were tivity is dependent on task domain. Specif- associated with stronger amygdala activity ically, will the associations reported here to faces with expressions “morphed” part- also be observed in the context of per- way between neutral and fear. It could be formance of other tasks? Or even in the argued that these morphed facial stimuli are absence of any task? Studies pertaining to milder or more ambiguous in their threat these questions are reviewed in the next two value than the “fully” negative stimuli used sections. in the other studies. However, this one find- ing does not permit any definitive conclu- sions to be drawn in favor of the “ambi- Trait Anxiety and Hyper-Amygdala guity” account without further empirical and Hypo-Frontal Function: The Case investigation. of Fear Conditioning It also remains to be established whether neuroticism is associated with impover- The rodent fear conditioning literature pro- ished recruitment of the frontal mecha- vides strong evidence for the role of frontal Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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inhibitory influences on the amygdala in to note that the medial and lateral regions the attenuation of physiological and behav- of ventral prefrontal cortex reported in ioral fear responses. Findings indicate that this study, the activation of which was the amygdala is involved in the acqui- associated with lower cued and contextual sition and expression of cued fear, with fear responses, overlap with those reported medial prefrontal cortical inputs inhibit- elsewhere to be activated during deliberate ing amygdala responsivity to conditioned emotion regulation and affective stimulus fear stimuli (CSs) following extinction train- reappraisal (see Chapter 16). Delgado ing (Maren & Quirk, 2004; Sotres-Bayon, and colleagues have further reported that Bush, & LeDoux, 2004). Human studies activation of similar ventral PFC regions of conditioned fear have implicated simi- accompanies a reduction in conditioned lar circuitry with ventral medial regions of fear, regardless of whether it occurs due to prefrontal cortex (vmPFC) facilitating extinction or emotion regulation (Delgado, context-specific recall of “CS – uncondi- Nearing, LeDoux, & Phelps, 2008). tioned stimulus (UCS) absent” associations Together with the work reviewed ear- formed during extinction training (Milad, lier, these findings raise the possibility that Wright, et al., 2007; Phelps et al., 2004). individual variation in the recruitment of Disruption to this circuitry has been doc- different subregions of frontal cortex may umented in adults with posttraumatic stress influence volunteers’ ability to regulate their disorder (Milad et al., 2009) and has been emotional responses to the anticipation of proposed to be of potential relevance to aversive stimuli, as well as their locus of other anxiety disorders. attention when threat-related visual stimuli Recently, a handful of studies have begun are presented. It is important to note that to address whether trait vulnerability to characteristics such as trait anxiety may map anxiety is linked to altered functioning of onto individual differences not only in the this circuitry. Two initial studies reported ability to regulate responses to aversive stim- that high trait anxious individuals showed uli but also in the nature of the regulation elevated amygdala activity during extinction strategy selected. Initial studies have begun (Barrett & Armony, 2009; Sehlmeyer et to examine the brain regions activated by al., 2011). Associations of extinction-related different emotion regulation strategies (e.g., ACC activity with trait anxiety were also Vrticka,ˇ Sander, & Vuilleumier, 2011), but reported, but the directionality and specific as yet this work has not been integrated locus of these effects did not replicate across with investigation of individual differences the two studies. In recent work from our in strategy selection or success in implemen- own lab, we found that elevated amygdala tation. activity to a CS that predicted an aversive stimulus (the UCS) mediated the relation- ship between trait anxiety and the strength Trait Vulnerability to Affective of initial acquisition of skin conductance Disorder: What Might We Learn from responses to the predictive CS (Indovina et Resting State Studies? al., 2011). We also found that trait anxiety was negatively related to recruitment of Recently, there has been increasing inter- ventral frontal regions linked to context- est in whether the functional and structural appropriate down-regulation of both cued connectivity between different brain regions and contextual fear prior to omission of may be informative even in the absence of the UCS. Hierarchical regression revealed task performance. One high-profile exam- that the relationship between trait anxiety ple is the recently launched Human Con- and amygdala responsivity to the predictive nectome Project, which aims to “compre- CS was independent of that between hensively map human brain circuitry . . . trait anxiety and context-appropriate using cutting-edge methods of noninva- ventral PFC recruitment. It is interesting sive neuroimaging ...yield[ing] invaluable Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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information about brain connectivity, its of this nature. Second, an issue that per- relationship to behavior, and the con- tains to all resting state studies is that it is tributions of genetic and environmental not clear how to interpret negative versus factors to individual differences in brain positive patterns of BOLD connectivity at circuitry” (http://humanconnectome.org/). rest. Are inhibitory connections at the neu- This interest has been accompanied by a ronal level likely to be reflected as negative renewed emphasis on examining the func- BOLD connectivity patterns? This is often tion of brain regions in the context of assumed but far from established. A third the networks in which they are embedded problem is that it is unclear as to what crite- as “nodes.” It has also brought increased ria should be used for including or excluding recognition of the need to study individual regions in different “resting state” networks, differences in order to understand norma- raising spectra of the criticisms applied to tive brain function. It is beyond the scope the circuits of Papez (1937) and MacLean of the current chapter to provide a com- (1949). Specifically, with both seed-based prehensive review of this literature (see and component-based approaches, the same Deco et al., 2011). We limit this section to question occurs as to what threshold to a consideration of a few findings to date use – whether in terms of significance lev- that may inform our understanding of the els for whole-brain seed-driven analyses or brain basis of trait vulnerability to affective the number of components for indepen- disorder. dent or principal-components-based anal- Roy et al. (2009) provided a detailed yses. As the field develops, the challenge report of connectivity between the amyg- will be to find ways to address these dala and other brain regions at rest. issues. Positive correlations were found between Building on the work by Roy and col- resting state blood-oxygen-level-dependent leagues, Kim et al. (2011) examined the (BOLD) activity in the amygdala and a num- influence of individual differences in self- ber of brain regions, including the medial reported pre-scan anxiety on resting state frontal gyrus, rostral ACC, dorsal ACC, functional connectivity. They reported that insula, thalamus, and striatum. Negative anxiety levels significantly modulated con- correlations were also observed between the nectivity between the amygdala and only amygdala and areas, including the superior two regions. High state anxious individu- frontal gyrus, bilateral middle frontal gyrus, als showed negative amygdala-vmPFC con- posterior cingulate cortex, precuneus, and nectivity contrasting with positive func- parietal and occipital lobes. Further anal- tional connectivity between these regions yses were conducted to profile the con- in low state anxious individuals. In addi- nections of different amygdala subnuclei. tion, they also showed an absence of the These provided some suggestion of nega- negative connectivity between the amyg- tive connectivity between the basolateral dala and dorsal medial PFC observed in nucleus and central nucleus of the amyg- low state anxious volunteers. The effects dala, as well as opposing patterns of con- of anxiety in this study are particularly of nectivity between these subnuclei with the interest because of their selectivity. In medial frontal gyrus and anterior cingulate advancing our understanding of trait vul- cortex. nerability to affective disorder, a limita- These findings are intriguing, but have tion is that the primary analyses presented several limitations. First, as noted by used state anxiety measures, with anal- the authors, it is extremely difficult to yses using trait anxiety measures being specify amygdala subnuclei on echoplanar described as showing similar but weaker images. Although the probabilistic approach trends. One hopes that future studies will adopted by Roy and colleagues can provide further explore the extent to which anxiety- an estimate, it is not clear if the level of related variability in amygdala-frontal func- accuracy achieved is sufficient for analyses tional connectivity at rest reflects stable Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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individual differences versus effects of a amygdala network, with contrasting pat- temporary mood state. terns of dendritic change being reported in the frontal cortex and amygdala. Whereas amygdaloid dendrites increase (Vyas, Mitra, Trait Vulnerability to Affective Shankaranarayano Rao, & Chattarji, 2002), Disorder: From Correlation to neurons in the PFC show a reduction in Causation? dendritic branches, which appears linked to deficient performance on measures of exec- If, based on the studies reviewed in this utive control (see Holmes & Wellman, 2009, chapter, we come to the conclusion that for a review). Genetic differences, including there are stable trait-related differences in common genetic polymorphisms influenc- the function of amygdala-frontal circuitry, ing catecholamine metabolism in the frontal what might cause these differences? There cortex (e.g., the COMT val 158 met poly- are a number of possibilities, which are morphism), as well as ones affecting sero- by no means mutually exclusive. These tonergic modulation of amygdala activity include structural or functional differences (e.g., polymorphisms in the serotonin trans- in one or both regions reflecting either porter gene), may well interact with such genetic or environmental influences, differ- environmental influences (Hyde, Bogdan, & ences in the integrity of tracts connect- Hariri, 2011) and also with the effects of ing these regions, and differences in neuro- early life stress on gene expression (Francis, chemical modulation of one or both regions, Champagne, Liu, & Meaney, 1999). Hence, again potentially reflecting either genetic a combination of genetic and environmen- or environmental influences uniquely or in tal influences potentially leads to changes combination. in both frontal and amygdala integrity and The evidence pertaining to these alter- function. Increased integration of the stress, natives is relatively limited. Diffusion ten- epigenetics, and functional genomics litera- sor imaging findings suggest that reduced tures with that reviewed in the earlier sec- integrity of white matter tracts (as indexed tions of this chapter may/might enable us by fractional anisotrophy) that link the to move beyond description of the cognitive amygdala to vmPFC in humans may indeed and neural correlates of trait vulnerability to be associated with trait vulnerability to anx- affective disorders to begin to outline causal iety (Kim & Whalen, 2009). Positron emis- trajectories underlying observed individ- sion topography studies meanwhile point to ual differences in affective style, disorder- a relationship between neuroticism and rest- related symptomatology, processing of emo- ing state frontal hypo-perfusion (Deckers- tionally salient stimuli, and associated brain bach et al., 2006). Arguably the most intrigu- function. ing findings are those emerging from the rodent and human literature on the effects of stress and gene-environment interactions Conclusions on amygdala-frontal circuitry (see Arnsten, 2009, and Chapters 22 and 25). Periods of Studying trait vulnerability to affective dis- acute stress are associated with neurochem- order may both inform our understand- ical changes, including elevated levels of ing of healthy brain function and pro- noradrenaline and dopamine release (Gold- vide an important bridge to studies of stein, Rasmusson, Bunney, & Roth, 1996). psychiatric disorder. It may also enable High levels of these catecholamines enhance us to establish markers of elevated risk amygdala function (Debiec & LeDoux, for psychiatric illness that could be used 2006), but undermine prefrontal corti- to identify individuals who might benefit cal function (Arnsten, Mathew, Ubriani, from preventive interventions (e.g., cogni- Taylor, & Li, 1999). Chronic stress leads tive training) before a deepening spiral into to long-term alterations in the frontal- clinically significant illness occurs. To date, Trim: 7in × 10in Top: 0.5in Gutter: 0.875in CUUS1847-24 CUUS1847/Armony ISBN: 978 1 107 00111 4 October 14, 2012 18:56

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