The neurobiology of emotioncognition interactions fundamental questions and strategies for future research [PDF] - Free Document Online (2023)

REVIEW ARTICLE published: 17 February 2015 doi: 10.3389/fnhum.2015.00058 The neurobiology of emotion–cognition interactions: fundamental questions and strategies for future research Hadas Okon-Singer 1 *† , Talma Hendler 2 , Luiz Pessoa 3 and Alexander J. Shackman 3 *† 1 Department of Psychology, University of Haifa, Haifa, Israel 2 Functional Brain Center, Wohl Institute of Advanced Imaging, and School of Psychological Sciences, Faculty of Medicine and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel 3 Department of Psychology, Neuroscience and Cognitive Science Program, and Maryland Neuroimaging Center, University of Maryland, College Park, College Park, MD, USA Edited by: Recent years have witnessed the emergence of powerful new tools for assaying the Leonhard Schilbach, University brain and a remarkable acceleration of research focused on the interplay of emotion and Hospital Cologne, Germany cognition. This work has begun to yield new insights into fundamental questions about the Reviewed by: Christian Sorg, Klinikum rechts der nature of the mind and important clues about the origins of mental illness. In particular, Isar Technische Universität München, this research demonstrates that stress, anxiety, and other kinds of emotion can profoundly Germany influence key elements of cognition, including selective attention, working memory, and Elliot Berkman, University of Oregon, cognitive control. Often, this influence persists beyond the duration of transient emotional USA challenges, partially reflecting the slower molecular dynamics of catecholamine and hor- *Correspondence: Hadas Okon-Singer, Department of monal neurochemistry. In turn, circuits involved in attention, executive control, and working Psychology, University of Haifa, memory contribute to the regulation of emotion. The distinction between the ‘emotional’ Mount Carmel, Haifa 3498838, Israel and the ‘cognitive’ brain is fuzzy and context-dependent. Indeed, there is compelling e-mail: [emailprotected]; evidence that brain territories and psychological processes commonly associated with Alexander J. Shackman, Department of Psychology, Neuroscience and cognition, such as the dorsolateral prefrontal cortex and working memory, play a central Cognitive Science Program, and role in emotion. Furthermore, putatively emotional and cognitive regions influence one Maryland Neuroimaging Center, another via a complex web of connections in ways that jointly contribute to adaptive University of Maryland, 3123G and maladaptive behavior. This work demonstrates that emotion and cognition are deeply Biology-Psychology Building, College Park, MD 20742, USA interwoven in the fabric of the brain, suggesting that widely held beliefs about the key e-mail: [emailprotected] constituents of ‘the emotional brain’ and ‘the cognitive brain’ are fundamentally flawed. We †These authors have contributed conclude by outlining several strategies for enhancing future research. Developing a deeper equally to this work. understanding of the emotional-cognitive brain is important, not just for understanding the mind but also for elucidating the root causes of its disorders. Keywords: ACC, amygdala, anxiety, depression, emotion control and regulation, EEG/ERP, fMRI, PFC Until the 20th century, the study of emotion and cognition was of the science will motivate new and impactful research. Clearly, largely a philosophical matter. Although modern perspectives on our understanding of emotion–cognition interactions remains far the mind and its disorders remain heavily influenced by the intro- from complete. Indeed, we are reminded of Ekman and Davidson’s spective measures that defined this earlier era of scholarship, the comment: “There are many promising findings, many more leads, last several decades have witnessed the emergence of powerful [and] a variety of theoretical stances” (Ekman and Davidson, 1994, new tools for assaying the brain and a remarkable acceleration p. 3). We conclude by outlining several strategies for enhancing of research to elucidate the interplay of emotion and cognition future research. With continuing effort, some of the fundamental (Pessoa, 2013; Braver et al., 2014; Dolcos and Denkova, 2014). questions will be decisively addressed. In some cases, the ques- The immediate goal of our Special Research Topic was to survey tions themselves will evolve, as in other areas of the biological recent advances in understanding how emotional and cognitive sciences. processes interact, how they are integrated in the brain, and the implications for understanding the mind and its disorders (Okon- HOW DOES EMOTION INFLUENCE COGNITION? Singer et al., 2014b; Figure 1). Here, we consider ways in which Many of our contributors highlighted evidence that the perception this rapidly growing body of work begins to address some more of emotionally-salient stimuli and the experience of emotional fundamental questions about the nature of cognition–emotion states can profoundly alter cognition. interactions, highlighting key points of consensus. By focusing attention on the most important outstanding questions, we hope EMOTIONAL CUES GRAB EXOGENOUS ATTENTION AND MODULATE to move the field forward. First, we hope that answers provided ENDOGENOUS ATTENTION by our contributors will stimulate discussion. Second, we hope There is abundant evidence that emotionally-salient cues— that juxtaposing clear theoretical goals against the current state snakes, spiders, and angry faces—strongly influence attention Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 1

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Okon-Singer et al. Emotion–cognition interactions FIGURE 1 | The top 200 scientific terms used in the Special Research Topic. The typeface is scaled proportional to the frequency of each term. The figure was generated using http://www.wordle.net. (e.g., Siman-Tov et al., 2009; Lerner et al., 2012; Pour- ATTENTIONAL BIASES TO EMOTIONAL CUES ARE PLASTIC tois et al., 2013; Carretié, 2014) the ability to selectively Anxious individuals tend to allocate excess attention to threat and respond to relevant aspects of the environment while inhibit- there is evidence that this cognitive bias causally contributes to the ing potential sources of distraction and competing courses development and maintenance of anxiety disorders (Bar-Haim of action (Desimone and Duncan, 1995; Miller and Cohen, et al., 2007; Hakamata et al., 2010; MacLeod and Mathews, 2012; 2001). The focus of attention is determined by the perva- Singer et al., 2012; Van Bockstaele et al., 2013; MacLeod and Clarke, sive competition between exogenous (often termed ‘stimulus- 2015). Extreme anxiety and behavioral inhibition often emerges driven’ or ‘bottom–up’) and endogenous (often termed ‘goal- early in development (Fox et al., 2005a; Blackford and Pine, 2012; directed’ or ‘top–down’ attention) mechanisms (Egeth and Yantis, Fox and Kalin, 2014), raising important questions about the degree 1997). to which childhood attentional biases to threat are plastic and With respect to exogenous attention, a number of contrib- can be influenced by early experience (Shechner et al., 2012; Bar- utors describe new evidence that emotionally-charged cues are Haim and Pine, 2013; Henderson et al., 2014; MacLeod and Clarke, more attention-grabbing than neutral cues and highlight recent 2015). efforts to specify the mechanisms underlying this bias (Holtmann Here, Kessel et al. (2013) provide tantalizing correlative evi- et al., 2013; McHugo et al., 2013; Peers et al., 2013; Stollstorff dence that emotional biases in attention are influenced by et al., 2013). Along the way, McHugo et al. (2013) provide a caregiver style. Using an innovative combination of behavioral useful tutorial on methods for quantifying the capture of atten- and electrophysiological techniques, they show that although tion by emotional cues (e.g., dot-probe, emotional attentional temperamentally inhibited children allocate more attention to blink). aversive cues, this is reduced among the offspring of par- Importantly, attention can also be guided in an endogenous ents who rely on encouragement, affection, and appreci- fashion by internal goals (e.g., rules, instructions, and plans) ation to reinforce positive behavior. A key challenge for as well as moods and motivational states (e.g., feeling anx- future research will be to test whether targeted interven- ious or hungry). Mohanty and Sussman (2013) discuss evidence tions aimed at cultivating more salubrious parenting styles demonstrating that emotion and motivation can guide atten- have similar consequences. Prospective designs (e.g., before tion to congruent cues (e.g., food when hungry). In particular, and after exposure to a negative life event or trauma) they show that subcortical regions proximally involved in deter- would provide another powerful approach for understand- mining value and orchestrating emotional states (e.g., amygdala, ing the plasticity of emotional attention (Admon et al., 2009, substantia nigra) can facilitate endogenous attentional processes 2012). implemented in frontoparietal regions and can strengthen activa- tion in relevant sensory regions (e.g., face-selective regions of the EMOTION EXERTS PERSISTENT EFFECTS ON ATTENTION fusiform gyrus when anticipating an angry face). This extended Emotions are often conceptualized as fleeting and most imaging network, encompassing sensory, attentional, and emotional cir- and psychophysiological studies of emotion focus on transient cuits, facilitates the rapid detection of emotionally-significant responses to punctate emotional challenges. Yet, there is grow- information. ing evidence that emotions can have lingering consequences for Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 2

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Okon-Singer et al. Emotion–cognition interactions cognition and behavior (Davidson, 2004; Suls and Martin, 2005; DISTRACTING EMOTIONAL CUES DISRUPT COGNITIVE CONTROL AND Hajcak and Olvet, 2008; Qin et al., 2009). WORKING MEMORY Here, for example, Vaisvaser et al. (2013) combined serial Classically, cognition and emotion have been viewed as oppo- measures of emotional state, neuroendocrine activity, and resting- sitional forces (Damasio, 2005a; Okon-Singer et al., 2007, 2011; state brain activity to demonstrate that alterations in amygdala– Shackman et al., in press). From this perspective, moods and hippocampal functional connectivity persist for more than 2 h other kinds of emotional states are responsible for short-circuiting following exposure to intense social stress. Along conceptually cognition. similar lines, Morriss et al. (2013) use electrophysiological tech- Consistent with this view, Kalanthroff et al. (2013) show that niques to show that endogenous attention is potentiated for several emotional distractors disrupt cognitive control. Cognitive control seconds following brief emotional challenges (i.e., standardized encompasses the range of processes (e.g., endogenous attention, emotional images). inhibition, and learning) that are engaged when habitual responses Several threads of evidence highlight the importance of under- are not sufficient to sustain goal-directed behavior, as in stop- standing the mechanisms that govern variation in the speed signal, go/no-go, Stroop, and Eriksen flanker tasks (Shackman of recovery from emotional perturbation. In particular, indi- et al., 2011b). Here, the authors demonstrate that the brief presen- vidual differences in emotional recovery (a) strongly predict tation of emotional images disrupts performance in the stop-signal personality traits, such as neuroticism, that confer increased task, a widely used index of inhibitory control (see also Pessoa et al., risk of developing psychopathology (e.g., Blackford et al., 2009; 2012). Schuyler et al., 2014); and (b) are sensitive to adversity and Likewise, Iordan et al. (2013) review evidence that emotional chronic stress exposure, two other well-established risk fac- distractors disrupt working memory. Converging with other work tors (Lapate et al., 2014). An important challenge for future focused on emotion-related distraction (Bishop, 2007; Etkin, research will be to identify the neural circuitry and molecu- 2012; Bishop and Forster, 2013; Etkin et al., 2013; Okon-Singer lar pathways that support the enduring effects of emotion on et al., 2014a; van Ast et al., 2014), they suggest that degraded endogenous attention and to clarify the intermediate processes performance reflects two processes: (a) increased engagement that link variation in emotional recovery to mental health and of regions involved in processing socio-emotional information disease. and orchestrating emotional expressions (e.g., amygdala), and (b) a reduction of delay-spanning activity in frontoparietal DISTRACTING EMOTIONAL CUES READILY PENETRATE THE GATE cortex. PROTECTING WORKING MEMORY Endogenous attention is tightly linked with working memory EMOTION STRENGTHENS SOME COGNITIVE PROCESSES WHILE (Postle, 2006; D’Esposito and Postle, 2014; Sreenivasan et al., WEAKENING OTHERS 2014). The transient representation of task-sets, goals, and other With the ascent of evolutionary theory in the 19th century (Dar- kinds of information in working memory plays a crucial role win, 1872/2009, 1872), many scientists adopted the view that in sustaining goal-directed attention and guiding behavior in emotions are functional and enhance fitness (Susskind et al., 2008; the face of potential distraction (Miller and Cohen, 2001). In Todd et al., 2012; Sandi, 2013; Schwabe and Wolf, 2013; Todd short, information held in working memory is a key deter- and Anderson, 2013); in short, that emotions are more adaptive minant of our momentary thoughts, feelings, and behavior. than not and “that there is typically more cooperation than strife” Importantly, the capacity of working memory is strongly deter- between emotion and cognition (Levenson, 1994). mined by the ability to filter or gate irrelevant information Consistent with this more nuanced perspective, the contribu- (Vogel et al., 2005; McNab and Klingberg, 2007; Awh and Vogel, tions from Clarke and Johnstone (2013), Morriss et al. (2013), 2008). Robinson et al. (2013a, 2013b), Vytal et al. (2013) provide evi- Here, Stout et al. (2013) used a well-established electrophys- dence that experimentally-elicited anxiety facilitates some kinds iological marker of working memory storage (i.e., contralateral of information processing, while degrading others. In particular, delay activity; Vogel and Machizawa, 2004) to show that threat- they provide considerable evidence that anxiety: (a) enhances vig- related distractors (i.e., task-irrelevant fearful faces) are stored ilance, potentiating early sensory cortical responses to innocuous in working memory and that this filtering inefficiency is exag- environmental stimuli, increasing the likelihood that emotionally gerated in dispositionally-anxious individuals. Once in working salient information will be detected; and (b) disrupts working memory, emotional information is poised to hijack endogenous memory. attention and other kinds of top–down control mechanisms. From The molecular basis of emotion’s deleterious impact on work- a psychiatric perspective, this emotional gating deficit may help ing memory is reviewed by Shansky and Lipps (2013). Building to explain the persistence of heightened negative affect (e.g., anxi- on pioneering work by Arnsten and Goldman-Rakic (1998) and ety, sadness) among patients with emotional disorders (Grupe and Arnsten (2009), the authors describe evidence that stress strongly Nitschke, 2013; Cohen et al., 2014; Stout et al., 2014). An important influences catecholamine (i.e., dopamine and norepinephrine) challenge for future studies will be to use hemodynamic imaging and glucocorticoid levels in the prefrontal cortex (PFC) in ways techniques, such as fMRI, to clarify the neural circuitry underlying that degrade delay-spanning neuronal activity. emotional gating deficits. A variety of evidence suggests that the Shansky and Lipps (2013) also describe important new evi- pulvinar may play an important role (Pessoa and Adolphs, 2010; dence that sex hormones, such as estrogen, can exacerbate the Arend et al., 2014). impact of stress on prefrontal function. Along these lines, Sacher Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 3

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Okon-Singer et al. Emotion–cognition interactions et al. (2013) review human imaging studies showing that the can influence “cold” cognition (Shackman et al., 2006; Eysenck structure and function of brain circuits involved in emotion gen- et al., 2007; Bishop, 2009; Berggren and Derakshan, 2013, 2014; eration and regulation are strongly and dynamically modulated Cavanagh and Shackman, 2014), a point that we develop more fully by cyclic fluctuations in sex hormones (see also Sacher et al., in the subsequent section focused on the integration of emotion 2012). Taken together, these observations underscore the plastic- and cognition. ity of emotion–cognition interactions and provide promising clues about the origins of well-established sex differences in the preva- HOW DOES EMOTION INFLUENCE EMOTION? lence of stress-related disorders, such as anxiety and depression An important but rarely addressed question in psychology and (Kessler et al., 2012; Kendler and Gardner, 2014). psychiatry concerns the potential influence of emotions on one another and concomitant motivational states. For example, are we EMOTIONAL STATES PROMOTE MOOD-CONGRUENT THOUGHTS AND less likely to experience excitement or joy on a day where we’re ACTIONS feeling frazzled, depressed, or worn out (Arnsten, 1998, 2009; Moods and other, more transient emotional states tend to Pizzagalli, 2014)? encourage congruent thoughts and actions (e.g., Lerner et al., 2015), a process that is necessarily mediated by enduring EMOTION ALTERS REINFORCER SENSITIVITY changes in brain activity and connectivity (cf. Vaisvaser et al., Building on earlier work by Bogdan and Pizzagalli (2006), 2013). Here, Van Dessel and Vogt (2012) demonstrate that Pizzagalli et al. (2007), Bogdan et al. (2010), and Berghorst et al. mood increases the amount of attention allocated to mood- (2013) demonstrate that experimentally-elicited anxiety selec- congruent cues. Schick et al. (2013) provide evidence that indi- tively reduces sensitivity to reward, suggesting a mechanism viduals at risk for developing depression interpret motivationally that may contribute to the high rate of comorbidity between ambiguous cues in a less positive light. Harlé et al. (2013) anxiety and anhedonia (Southwick et al., 2005). Notably, this describe a novel Bayesian computational framework for under- effect was only observed in the subset of subjects who were standing the mechanisms underlying mood-congruency effects. most responsive to the anxiety induction (i.e., threat of nox- An important advantage of this framework is that it gener- ious electric shock). Given evidence that many individuals will ates explicit mechanistic hypotheses. For example, the model never experience a mood or anxiety disorder (Kessler et al., predicts that anxiety facilitates behavioral avoidance because 2012), this paradigm may provide a means of identifying those it leads to inflated expectations about the need for avoidant at greatest risk. Methodologically, this observation underscores behavior and increased expectations of punishment or error. the necessity of including independent measures of emotion Furthermore, fitting model parameters to observable behavior in studies of emotion–cognition interactions (Shackman et al., affords an opportunity to identify the underlying determinants 2006). of mood-congruency effects in healthy and clinical popula- tions. HOW DOES COGNITION INFLUENCE AND REGULATE EMOTION? EMOTIONAL TRAITS INFLUENCE COGNITIVE PERFORMANCE, EVEN Humans frequently regulate their emotions and they do so using a WHEN EMOTIONAL CUES, AND CHALLENGES ARE ABSENT variety of implicit and explicit cognitive strategies (Gross, 1998a,b; Emotional traits are often conceptualized as diatheses for emo- Gross and Thompson, 2007; Gross et al., 2011; Webb et al., 2012; tional states (Matthews et al., 2009). Thus, individuals with high Okon-Singer et al., 2013). Implicit strategies are unintentional and levels of neuroticism or negative emotionality are thought to be appear to occur without effort or insight. In contrast, explicit prone to exaggerated anxiety in the face of trait-relevant cues, strategies are voluntary and demand a degree of effortful control. contexts, and challenges (e.g., punishment, negative feedback), as Several contributors to our Special Research Topic described illustrated in the contributions from Kessel et al. (2013), Moser new insights into the mechanisms supporting the cognitive regu- et al. (2013), and Proudfit et al. (2013). Yet, a considerable body lation of emotion and the role of emotion regulation in psychiatric of neurophysiological evidence indicates that emotional traits disorders, such as depression. are embodied in the on-going activity and connectivity of the brain (Canli et al., 2005; Fox et al., 2008; Shackman et al., 2009; ATTENTION REGULATES EMOTION Rohr et al., 2013; Birn et al., 2014a,b). Likewise, the sustained Perhaps the most basic strategy for reducing distress is attentional levels of heightened vigilance and distress characteristic of indi- avoidance; that is, to simply look away from the source of distress viduals with anxiety disorders are most apparent in the absence (Xing and Isaacowitz, 2006). Overt attentional redeployment is a of clear and imminent threat (Davis et al., 2010; Lissek, 2012; potent means of regulating the engagement of subcortical struc- Grupe and Nitschke, 2013). These observations raise the possibil- tures, such as the amygdala, that play a key role in orchestrating ity that emotional traits could influence cognition in the absence emotional states (Pessoa et al., 2002; Dalton et al., 2005; Dalton of explicit emotional distraction or challenge (Watson and Clark, et al., 2007; van Reekum et al., 2007; Urry, 2010; Okon-Singer 1984; Bolger and Schilling, 1991; Suls and Martin, 2005). et al., 2014a). Here, Berggren et al. (2013) provide compelling evidence that Here, Aue et al. (2013b) employed an innovative combina- trait anxiety is associated with degraded cognitive control, indexed tion of eyetracking, psychophysiology, and fMRI to explore using an anti-saccade task under load. This new observation visual avoidance in spider phobics. Taking an individual differ- adds to a growing literature showing that “hot” emotional traits ences approach, they demonstrate that enhanced activation in Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 4

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Okon-Singer et al. Emotion–cognition interactions the amygdala and dorsal striatum to spider images was predictive emotional and cognitive processes in the brain (e.g., Shackman of increased visual avoidance among arachnophobes. Peripheral et al., 2011b; Raz et al., 2012, 2014). The neural integration of measures of autonomic arousal showed a similar pattern, sug- emotion and cognition should not be surprising—after all, the gesting that arachnophobes endogenously redirect attention as a human brain did not evolve to optimize performance on lab- means of regulating their extreme fear, a strategy that might be oratory measures of ‘cold’ cognition or to passively respond non-adaptive in the long term (Grupe and Nitschke, 2013). A key to experimental manipulations of emotion, such as threat of challenge for future research will be to clarify the order of these shock. Our brain, like that of other animals, is the product effects (i.e., fear → attention avoidance → reduced fear), per- of evolutionary pressures that demanded neural systems capa- haps by leveraging the millisecond temporal resolution afforded by ble of using information about pleasure and pain, derived from facial electromyography (e.g., Lee et al., 2009; Heller et al., 2014). stimuli saturated with hedonic and motivational significance, Elucidating the mechanisms supporting the recursive interplay to adaptively regulate attention, learning, somatic arousal, and of emotion and attention and the mutual influences of different action. processing biases (Aue et al., 2013a) would inform our understand- A number of contributors highlighted advances in our under- ing of disorders, like post-traumatic stress, that are characterized standing of the neural mechanisms that serve to integrate emotion by dysregulated emotion and aberrant attention to emotionally- and cognition. salient cues (e.g., Admon et al., 2013; Wald et al., 2013) and set the stage for developing improved interventions (MacLeod and CANONICAL TERRITORIES OF THE ‘COGNITIVE’ BRAIN REGULATE Mathews, 2012; Bar-Haim and Pine, 2013; MacLeod and Clarke, EMOTION 2015). The dorsolateral prefrontal cortex (dlPFC) is a canonically ‘cogni- tive’ region of the brain, well known for its critical role in reasoning THE CHOICE OF COGNITIVE REGULATION STRATEGY DEPENDS ON THE and higher cognition (e.g., endogenous attention, working mem- SITUATION ory, and cognitive control; Roberts et al., 1998; Miller and Cohen, Sheppes and Levin (2013) emphasize that humans frequently use 2001; D’Esposito and Postle, 2014). Yet, there is growing evidence effortful cognitive strategies to cope with and regulate their emo- that the dlPFC plays a key role in the top–down control of emo- tions (e.g., Egloff et al., 2006; Ehring et al., 2010). For example, tion and motivated behavior (Fox et al., 2005b; Koenigs et al., 2008; they may try to distract themselves or they may try to reappraise Zaretsky et al., 2010; Buhle et al., 2013; Frank et al., 2014; Treadway the situation in a more positive light. Sheppes and Levin (2013) et al., 2014). provide evidence that not only do individuals have the capacity Here, Clarke and Johnstone (2013) and Iordan et al. (2013) pro- to flexibly choose emotion regulation strategies, but that they do vide tantalizing, albeit correlational, evidence that dlPFC acts to so in ways that are strongly influenced by the emotional context protect the contents of working memory from emotional distrac- (e.g., choosing to reappraise when presented with mild nega- tion. This converges with work by Peers et al. (2013) and Stollstorff tive pictures, and to distract themselves in face of highly aversive et al. (2013) indicating that dlPFC plays a key role in regulating the stimulation). focus of attention in the face of potentially distracting emotional cues. WORKING MEMORY REGULATES EMOTION Rolls (2013) extends this perspective to decision-making, argu- Some strategies for regulating emotional distress, such as reap- ing that behavior reflects a pervasive, dynamic competition praisal, require the effortful maintenance of an explicit regulatory between two kinds of brain systems: (a) emotional systems, includ- goal. Rolls (2013) reviews evidence suggesting that this critically ing circuits centered on the amygdala and ventral striatum, that depends on working memory. More broadly, he suggests that goals, have been genetically programmed by our phylogenetic history attentional sets, and other kinds of declarative knowledge held in (e.g., fear elicited by danger, joy elicited by sweets and fat); and working memory play a central role in regulating the output of (b) cognitive systems, such as the frontoparietal network, that are emotional systems. informed by our ontogenetic history and governed by our declar- ative knowledge and explicit goals (i.e., pick the healthy orange, HOW ARE EMOTION AND COGNITION INTEGRATED? not the unhealthy candy bar; cf. Hare et al., 2008, 2009). Rolls Humans tend to experience cognition and emotion as funda- emphasizes that the lateral PFC can override the output of emo- mentally different. Emotion is infused with feelings of plea- tion circuitry, biasing behavior in favor of our explicit goals. John sure or pain and manifests in readily discerned changes in et al. (2013) articulate a complementary perspective, reviewing the body, whereas cognition often appears devoid of substan- evidence that the PFC and amygdala functionally interact via a tial hedonic, motivational, or somatic features. These apparent complex anatomical network of recurrent cortical and thalamic differences in phenomenological experience and peripheral phys- projections and intra-amygdalar microcircuits (see also Pessoa and iology led many classical scholars to treat emotion and cognition Adolphs, 2010; Pessoa, 2012; Pessoa et al., 2012; Birn et al., 2014a,b; as distinct mental faculties (de Sousa, 2014; Schmitter, 2014). Treadway et al., 2014). But contemporary theorists have increasingly rejected the claim Evidence linking the dlPFC to mood and anxiety disorders, as that emotion and cognition are categorically different (Dama- in the papers contributed by Crocker et al. (2013) and Warren et al. sio, 2005b; Duncan and Barrett, 2007; Lindquist and Barrett, (2013), underscores the importance of developing a more sophis- 2012; Barrett and Satpute, 2013; Pessoa, 2013), motivated in ticated understanding of the role played by ‘cognitive’ regions in part by recent imaging evidence demonstrating the overlap of normal and disordered emotion. Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 5

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Okon-Singer et al. Emotion–cognition interactions CANONICAL TERRITORIES OF THE ‘COGNITIVE’ BRAIN ARE REGULATED allocation, action selection) in ways that support adaptive behav- BY EMOTION ior (for convergent perspectives, see the contributions from Rolls, Regulation is a two-way street. Just as ‘cognitive’ systems (e.g., 2013, and John et al., 2013). dlPFC) regulate emotion, ‘emotion’ systems (e.g., amygdala) are Dreisbach and Fischer (2012) describe other evidence consis- well positioned to regulate ‘cognitive’ systems via their influ- tent with this integrative perspective. In particular, they show that ence over the brainstem neurotransmitter systems that govern ‘cognitive’ conflict is aversive. This converges with a growing body the quality of information processing (e.g., neuronal signal-to- of evidence demonstrating that conflict and other prompts for noise) in cortical regions, as highlighted in the review contributed increased control (e.g., errors, punishment), are experienced as by Shansky and Lipps (2013). Via these mechanisms, the amyg- unpleasant and facilitate avoidance (Botvinick, 2007; Kool et al., dala is endowed with the capacity to transiently assume enhanced 2010; Dreisbach and Fischer, 2012; Schouppe et al., 2012; Lind- control over attention and behavior in situations that favor imme- ström et al., 2013; Proudfit et al., 2013; Shenhav and Buckner, diate responses over slower, more deliberate reasoning (Davis and 2014). Whalen, 2001; Arnsten, 2009). If negative emotions are indeed integrated with control pro- cesses, we would expect that anxiety and control should covary. ADAPTIVE AND MALADAPTIVE BEHAVIOR REFLECTS THE INTEGRATED That is, one would expect a degree of functional convergence CONTRIBUTIONS OF EMOTION AND COGNITIVE CONTROL between measures of anxiety and control-related activity in the Oftentimes, cognitive control is associated with laboratory tasks MCC or other regions (i.e., convergent validity; Campbell and that require the detection and adjudication of response conflict, Fiske, 1959). Consistent with this possibility, Moser et al. (2013) as with incongruent trials of the Stroop, Eriksen Flanker, and provide compelling meta-analytic evidence that error-related sig- go/no-go tasks. Yet, it is clear that control processes are engaged nals generated in the MCC are enhanced among anxiety patients by a much broader range of cognitive and emotional challenges and individuals with heightened negative emotionality. This indi- (e.g., Pochon et al., 2008; Shenhav et al., 2013). In particular, cates that negative emotionality, a fundamental dimension of control is engaged when there is uncertainty about the optimal childhood temperament and adult personality (Caspi et al., 2005), course of action (e.g., probabilistic learning), when potential involves systematic differences in the way that the brain responds actions are associated with the possibility of error or punish- to prompts for cognitive control. ment, or when there is competition between alternative courses McDermott et al. (2013) describe important new evidence, of action (e.g., flee/freeze, go/no-go). These features are hall- gleaned from the study of Romanian orphans, that MCC con- marks of dangerous environments, both in the real world and trol signals are plastic. In particular, they demonstrate that in laboratory studies of fear, anxiety, and pain. Consequently, MCC-generated control signals are profoundly shaped by early it has long been thought that control processes are engaged in experience in ways that confer risk or resilience for later socio- threatening environments in order to monitor risk, optimize emotional problems. This underscores the need to clarify the learning, and avoid potentially catastrophic actions (Norman and neurodevelopmental mechanisms that serve to integrate emotion Shallice, 1986; Gray and McNaughton, 2000). These theoretical and cognition in the laboratory and in daily life. considerations raise the possibility that the neural circuitry under- lying ‘cognitive’ control also contributes to the negative emotions UNDERSTANDING THE INTERPLAY OF EMOTION AND elicited by potential threat. Indeed, there is compelling evidence COGNITION: STRATEGIES FOR FUTURE RESEARCH from functional imaging studies that negative affect and cogni- Despite substantial progress, a number of important questions tive control paradigms consistently activate an overlapping region about the interaction of emotion and cognition remain unan- of the midcingulate cortex (MCC; Shackman et al., 2011b; Lin swered. In this final section, we highlight three strategies for et al., 2014). This overlap is consistent with anatomical evidence enhancing research in the cognitive-affective sciences (for more suggesting that the MCC represents a hub where information general recommendations about best research practices, see about pain, threat, and other more abstract forms of potential Button et al., 2013a,b,c; David et al., 2013; Chalmers et al., 2014; punishment and negative feedback are synthesized into a bias- Ioannidis et al., 2014a,b). ing signal that modulates regions involved in expressing fear and anxiety, executing goal-directed behaviors, and biasing the UNDERSTANDING THE SIGNIFICANCE OF EMOTIONAL-COGNITION focus of selective attention (Shackman et al., 2011b; Cavanagh INTERACTIONS IN THE LABORATORY REQUIRES MORE SOPHISTICATED and Shackman, 2014). Taken together, these observations sug- MEASURES OF BEHAVIOR IN THE REAL WORLD gest that anxiety and other emotions are tightly integrated with Most investigations of emotion, cognition, and their interplay control processes implemented in the MCC and other brain rely on a small number of well-controlled, but highly artificial regions. paradigms for manipulating emotion and cognition (e.g., static Along these lines, Morrison et al. (2013) show that even sim- aversive images and threat of shock to elicit anxiety; Coan and ple, phylogenetically-ancient kinds of motivated behavior, such Allen, 2007). Although these methods have afforded a number as the reflexive withdrawal from pain or the learned avoidance of critical insights, their real-world significance remains poorly of pain-related contexts, are dynamically shaped by complex, understood. For example, are attentional biases to threat, as hierarchically-organized networks of feedforward and feedback indexed by the dot-probe or other laboratory assays, predictive of connections that serve to integrate ‘emotional’ (e.g., value, risk) elevated behavioral inhibition or distress in daily life? Is amygdala and ‘cognitive’ computations (e.g., prediction error, attention activation to fearful faces predictive of heightened social reticence Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 6

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Okon-Singer et al. Emotion–cognition interactions or risk avoidance outside the scanner (see Admon et al., 2009 functional coalitions of brain regions (Kinnison et al., 2012; Raz for preliminary affirmative evidence)? Does the eliciting stimulus et al., 2012, 2014; Anticevic et al., 2013; McMenamin et al., 2014; (e.g., faces or aversive images) matter? Are measures of functional Uddin et al., 2014). A key challenge for future research will connectivity or network-based metrics (e.g., node centrality; cf. be to harness new techniques (e.g., EEG/fMRI fusions, slid- McMenamin et al., 2014) more predictive than regional activation ing window analyses of functional connectivity, EEG source of behavior in the real world? models of connectivity) for understanding how network activ- Given the limitations of ambulatory measures of brain ity dynamically changes across the broad range of time scales activity—there is no ‘fMRI helmet’ as yet—addressing these fun- on which emotion and cognition interact (Pessoa and Adolphs, damental questions requires pairing assays of brain and behavior 2010; Shackman et al., 2011a; Johnson et al., 2012; Raz et al., 2012, obtained in the laboratory with measures of thoughts, feelings, 2014). and behavior obtained in the field. Recent work combining fMRI Computationally explicit strategies (i.e., where quantitative with ecological momentary assessment (EMA) techniques, in parameters of an abstract computational model are fit to behav- which surveys are repeatedly delivered to participants’ mobile ioral or physiological measures), already common in the neuroe- devices, highlights the value of this approach for identifying the conomics literature, and information-based approaches, such as neural systems underlying naturalistic variation in mood and multivoxel pattern analysis (MVPA), that are increasingly com- behavior, a central goal of psychology, psychiatry, and the behav- mon in the cognitive neuroscience literature, provide powerful ioral neurosciences (Forbes et al., 2009; Berkman and Falk, 2013; tools for discovering the functional significance of regions and Lopez et al., 2014; Wilson et al., 2014). The widespread dissem- networks associated with emotional and cognitive perturbations ination of smart phone technology affords additional, largely and disorders (e.g., Hartley and Phelps, 2012; Montague et al., unrealized opportunities for objectively and unobtrusively quan- 2012; Lewis-Peacock and Norman, 2013). For example, tradi- tifying daily behavior (e.g., assessments of activity and context tional univariate fMRI analyses use regression to predict the based on accelerometer and geographical positioning system data activity of voxels, one-by-one, given some mental state (e.g., (Gosling and Mason, 2015). In short, combining EMA with lab- experiencing pain). While this strategy has proven enormously oratory assays provides a critical means of testing theoretical generative, it does not provide strong evidence as to whether validity and clinical relevance (e.g., does activation of the ven- overlapping patterns of fMRI activation (e.g., during physical tral striatum support craving and approach?), a novel strategy for and social pain; Wager et al., 2013; Woo et al., 2014) reflect assessing and dissociating the functional significance of new assays the same mental representation. MVPA provides a means of and derivative measures (e.g., functional connectivity between addressing this problem. MVPA classifies mental states given a the striatum and PFC), and an impetus for the development pattern of activity across voxels; in effect, treating each voxel of laboratory probes that more closely resemble the challenges as a weighted source of information about mental state. This we routinely encounter in life (e.g., appetitive social cues and contributes to the identification of the combinatorial code (i.e., temptations). pattern of activity across voxels) instantiating a particular men- tal state (e.g., experiencing anxiety) and to test whether that UNDERSTANDING THE INTERPLAY OF EMOTION AND COGNITION neural signature is reinstated at other times (e.g., performing a REQUIRES A DYNAMIC NETWORK PERSPECTIVE cognitive control task), an essential step in elucidating the func- Emotion and cognition emerge from the dynamic interactions of tional contributions of territories that are commonly recruited by large-scale brain networks. Put simply, fear, joy, attention, working cognitive and emotional challenges (e.g., dlPFC, MCC, anterior memory, and other psychological constructs cannot be mapped to insula). isolated brain regions because no one region is both necessary and Embracing a network perspective also reminds us that the func- sufficient. Likewise, similar profiles of impairment can emerge tional circuitry underlying the interplay of emotion and cognition from damage to different regions located within in the same func- is likely to be complex and need not recapitulate the simpler pat- tional network (Karnath and Smith, 2014; Oler et al., in press). This tern of direct projections revealed by invasive anatomical tracing is not a new or contentious idea; pioneers like Mesulam, Goldman- techniques [cf. the contributions from John et al. (2013), Morri- Rakic, and LeDoux highlighted the importance of distributed son et al. (2013), and Rolls (2013)]. Indeed, there is ample evidence neural circuits more than two decades ago and there is widespread of robust functional connectivity between brain regions that lack agreement amongst basic and translational researchers (Goldman- direct structural connections and increasing evidence that reg- Rakic, 1988; LeDoux, 1995; Mesulam, 1998; Bullmore and Sporns, ulatory signals can rapidly propagate across complex, indirect 2012; LeDoux, 2012; Uhlhaas and Singer, 2012; Anticevic et al., pathways in ways that enable emotion (e.g., motivational salience 2013). or value) to be integrated with perception and other kinds of Thus, understanding the interplay of emotion and cogni- on-going information processing (Vincent et al., 2007; Ekstrom tion requires that we accelerate the transition from localiza- et al., 2008; Honey et al., 2009; Pessoa and Adolphs, 2010; Adachi tion strategies (i.e., mapping isolated brain structures to func- et al., 2012; Birn et al., 2014a). Deciphering the functional signifi- tion; sometimes termed ‘neo-phrenology’) to a network-centered cance of this ‘connectomic’ complexity is likely to require more approach. This will require harnessing the kinds of analytic advanced analytic approaches, such as probabilistic machine- tools (e.g., functional connectivity fingerprinting, graph-theoretic learning techniques (Murphy, 2012). The combination of ongoing and machine-learning approaches) that are necessary for elu- advances in computational methods as well as developments in cidating how adaptive and maladaptive behavior emerges from brain imaging acquisition techniques (e.g., those supported by Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 7

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Okon-Singer et al. Emotion–cognition interactions the U.S. BRAIN initiative) will undoubtedly contribute to these ‘the emotional brain’ and ‘the cognitive brain’ are fundamentally efforts. flawed. Developing a deeper understanding will require a greater UNDERSTANDING THE INTERPLAY OF EMOTION AND COGNITION emphasis on (a) assessing the real-world relevance of labora- REQUIRES MECHANISTIC RESEARCH tory assays, including measures of brain activity; (b) a net- Most of the contributors to the Special Research Topic used non- work approach to characterizing the neurobiology of emotion– invasive techniques, such as fMRI, to trace associations between cognition interactions, and (c) mechanistic research. Adopting emotion and cognition, on the one hand, and brain function these strategies mandates collaboration among researchers from on the other. Aside from unresolved questions about the ori- different disciplines, with expertise in different species, popu- gins and significance of the measured signals (e.g., Logothetis, lations, measurement tools, analytic strategies, and conceptual 2008), the most important limitation of these techniques is that approaches. they do not address causation. A crucial challenge for future Addressing the interplay of emotion and cognition is a matter of studies is to develop a mechanistic understanding of the dis- theoretical as well as practical importance. In particular, many of tributed networks that support the interplay of emotion and the most common and costly neuropsychiatric disorders—anxiety, cognition. This can be achieved by combining mechanistic tech- depression, schizophrenia, substance abuse, chronic pain, autism, niques (e.g., optogenetics) or invasive analyses of neuromolecular and so on—involve prominent disturbances of cognition and pathways in animal models with the same whole-brain imaging emotion (Millan, 2013). Fundamentally, they are disorders of the strategies routinely applied in humans (Borsook et al., 2006; Ler- emotional-cognitive brain. Collectively, these disorders far out- man et al., 2007; Fox et al., 2010, 2012; Lee et al., 2010; Desai strip the global burden of cancer or cardiovascular disease (Collins et al., 2011; Casey et al., 2013; Narayanan et al., 2013; Roseboom et al., 2011; Whiteford et al., 2013; DiLuca and Olesen, 2014), et al., 2014). Similar strategies can be used with patients with underscoring the importance of accelerating efforts to understand circumscribed brain damage (e.g., Nomura et al., 2010; Grat- the neural systems underlying the interaction and integration of ton et al., 2012; Motzkin et al., 2014). Combining fMRI or EEG emotion and cognition. with non-invasive perturbation techniques (e.g., transcranial mag- netic stimulation or transcranial direct current stimulation) or GLOSSARY OF TERMS NOT DEFINED IN THE MAIN TEXT pharmacological manipulations provides another opportunity for Affect: The experience or expression of emotion (see also Barrett understanding how regional changes in brain activity alter net- et al., 2007). work function and, ultimately, behavior (Paulus et al., 2005; Anxiety: A sustained state of heightened apprehension in response Guller et al., 2012; Chen et al., 2013; Reinhart and Woodman, to uncertain, distal, or diffuse threat (Davis et al., 2010). 2014). Prospective longitudinal designs represent another fruitful approach to identifying candidate mechanisms, especially in rela- Cognition: Cognition is a fuzzy category that conventionally tion to the development of neuropsychiatric disorders (Admon includes processes involved in knowing or ‘thinking,’ including et al., 2013). attention, imagination, language, learning, memory, and percep- tion (for discussion, see Duncan and Barrett, 2007). CONCLUSION Emotion: Like ‘cognition,’ ‘emotion’ is a fuzzy, contentious cate- The last decade has witnessed an explosion of interest in the inter- gory that conventionally includes valenced processes (e.g., action play of emotion and cognition. The research embodied in this tendencies, attention, overt behavior, subjective feelings, and alter- Special Research Topic highlights the tremendous advances that ations in peripheral physiology) that are triggered by specific have already been made. In particular, this work demonstrates external or internal stimuli (e.g., actual or remembered threat for that emotional cues, emotional states, and emotional traits can fear); often taken to include states of anger, disgust, fear, happi- strongly influence key elements of on-going information process- ness, and sadness (e.g., Ekman and Davidson, 1994; Duncan and ing, including selective attention, working memory, and cognitive Barrett, 2007; Gendron and Barrett, 2009; LeDoux, 2012, 2014). control. Often, this influence persists beyond the duration of transient emotional challenges, perhaps reflecting slower changes Mood: A low-intensity emotional state that persists in the absence in neurochemistry. In turn, circuits involved in attention and of an explicit triggering stimulus (Ekman and Davidson, 1994). working memory contribute to the voluntary regulation of emo- Motivation: Internal states that are elicited by reinforcers and tion. The distinction between the ‘emotional’ and the ‘cognitive’ serve to organize behavioral direction (i.e., approach or avoidance) brain is blurry and context-dependent. Indeed, there is com- and intensity. Emotional states involve alterations in motivation pelling evidence that territories (e.g., dlPFC, MCC) and processes (e.g., increased avoidance in the case of fear). However, moti- (e.g., working memory, cognitive control) conventionally associ- vation can be altered by homeostatic processes, such as hunger ated with cognition play a central role in emotion. Furthermore, and satiety, that are not conventionally considered emotional putatively emotional and cognitive regions dynamically influ- (Rolls, 1999). ence one another via a complex web of recurrent, often indirect anatomical connections in ways that jointly contribute to adap- Neuroticism/Negative Emotionality: A fundamental dimension tive behavior. Collectively, these observations show that emotion of childhood temperament and adult personality; individuals with and cognition are deeply interwoven in the fabric of the brain, high levels of Neuroticism/Negative Emotionality are susceptible suggesting that widely held beliefs about the key constituents of to more intense or long-lasting negative emotions, including anger, Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 8

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Okon-Singer et al. Emotion–cognition interactions anxiety, fear, guilt, and sadness (Watson and Clark, 1984; Caspi Bar-Haim, Y., and Pine, D. S. (2013). Cognitive training research and the search for a et al., 2005). transformative, translational, developmental cognitive neuroscience. Dev. Cogn. Neurosci. 4, 1–2. doi: 10.1016/j.dcn.2013.02.001 Reinforcer: Rewards and punishments; anything an organism will Barrett, L. F., Mesquita, B., Ochsner, K. N., and Gross, J. J. (2007). work to approach or avoid (Rolls, 1999). The experience of emotion. Annu. Rev. Psychol. 58, 373. doi: 10.1146/annurev.psych.58.110405.085709 Barrett, L. F., and Satpute, A. B. (2013). Large-scale brain networks in affective and AUTHOR CONTRIBUTIONS social neuroscience: towards an integrative functional architecture of the brain. All the authors supervised the Special Research Topic. Hadas Curr. Opin. Neurobiol. 23, 361–372. doi: 10.1016/j.conb.2012.12.012 Okon-Singer and Alexander J. Shackman wrote the paper. All the Berggren, N., and Derakshan, N. (2013). Attentional control deficits in trait anx- authors edited and revised the paper. iety: why you see them and why you don’t. Biol. Psychol. 92, 440–446. doi: 10.1016/j.biopsycho.2012.03.007 Berggren, N., and Derakshan, N. (2014). Inhibitory deficits in trait anxiety: increased ACKNOWLEDGMENTS stimulus-based or response-based interference? Psychon. Bull. Rev. 21, 1339– We thank the many contributors and staff who made the Special 1345. doi: 10.3758/s13423-014-0611-8 Research Topic possible. We acknowledge the assistance of L. Berggren, N., Richards, A., Taylor, J., and Derakshan, N. (2013). Affec- Friedman and support of the European Commission (Follow- tive attention under cognitive load: reduced emotional biases but emergent anxiety-related costs to inhibitory control. Front. Hum. Neurosci. 7:188. doi: ship #334206 to Hadas Okon-Singer and Grant #602186 to Talma 10.3389/fnhum.2013.00188 Hendler), Israeli Center of Research Excellence, Israeli Science Berghorst, L. H., Bogdan, R., Frank, M. J., and Pizzagalli, D. A. (2013). Acute Foundation (Grant #51/11 to Talma Hendler), National Institute stress selectively reduces reward sensitivity. Front. Hum. Neurosci. 7:133. doi: of Mental Health (MH071589 to Luiz Pessoa), and University of 10.3389/fnhum.2013.00133 Maryland (Alexander J. Shackman and Luiz Pessoa). Berkman, E. T., and Falk, E. B. (2013). Beyond brain mapping: using neural mea- sures to predict real-world outcomes. Curr. Dir. Psychol. Sci. 22:45–50. doi: 10.1177/0963721412469394 REFERENCES Birn, R. M., Shackman, A. J., Oler, J. A., Williams, L. E., Mcfarlin, D. R., Rogers, Adachi, Y., Osada, T., Sporns, O., Watanabe, T., Matsui, T., Miyamoto, K., G. M., et al. (2014a). Evolutionarily conserved prefrontal-amygdalar dysfunction et al. (2012). 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Neural activity predicts individ- Citation: Okon-Singer H, Hendler T, Pessoa L and Shackman AJ (2015) The neurobiol- ual differences in visual working memory capacity. Nature 428, 748–751. doi: ogy of emotion–cognition interactions: fundamental questions and strategies for future 10.1038/nature02447 research. Front. Hum. Neurosci. 9:58. doi: 10.3389/fnhum.2015.00058 Vogel, E. K., Mccollough, A. W., and Machizawa, M. G. (2005). Neural measures This article was submitted to the journal Frontiers in Human Neuroscience. reveal individual differences in controlling access to working memory. Nature Copyright © 2015 Okon-Singer, Hendler, Pessoa and Shackman. This is an open- 438, 500–503. doi: 10.1038/nature04171 access article distributed under the terms of the Creative Commons Attribution License Vytal, K. E., Cornwell, B. R., Letkiewicz, A. M., Arkin, N. E., and Gril- (CC BY). The use, distribution or reproduction in other forums is permitted, provided lon, C. (2013). The complex interaction between anxiety and cognition: insight the original author(s) or licensor are credited and that the original publication in this from spatial and verbal working memory. Front. Hum. Neurosci. 7:93. doi: journal is cited, in accordance with accepted academic practice. No use, distribution or 10.3389/fnhum.2013.00093 reproduction is permitted which does not comply with these terms. Frontiers in Human Neuroscience www.frontiersin.org February 2015 | Volume 9 | Article 58 | 14

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