Fear-related psychophysiological patterns are situation and individual dependent: A Bayesian model comparison approach

Is there a universal mapping of physiology to emotion, or do these mappings vary substantially by person or situation? Psychologists, philosophers, and neuroscientists have debated this question for decades. Most previous studies have focused on differentiating emotions on the basis of accompanying autonomic responses using analytical approaches that often assume within-category homogeneity. In the present study, we took an alternative approach to this question. We determined the extent to which the relationship between subjective experience and autonomic reactivity generalizes across, or depends upon, the individual and situation for instances of a single emotion category, specifically, fear. Electrodermal activity and cardiac activity-two autonomic measures that are often assumed to show robust relationships with instances of fear-were recorded while participants reported fear experience in response to dozens of fear-evoking videos related to three distinct situations: spiders, heights, and social encounters. We formally translated assumptions from diverse theoretical models into a common framework for model comparison analyses. Results exceedingly favored a model that assumed situation-dependency in the relationship between fear experience and autonomic reactivity, with subject variance also significant but constrained by situation. Models that assumed generalization across situations and/or individuals performed much worse by comparison. These results call into question the assumption of generalizability of autonomic-subjective mappings across instances of fear, as required in translational research from nonhuman animals to humans, and advance a situated approach to understanding the autonomic correlates of fear experience. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Fluency generating emotion words correlates with verbal measures but not emotion regulation, alexithymia, or depressive symptoms

How do you feel? To answer this question, one must first think of potential emotion words before choosing the best fit. However, we have little insight into how the ability to rapidly bring to mind emotion words-emotion fluency-relates to emotion functioning or general verbal abilities. In this study, we measured emotion fluency by counting how many emotion words participants could generate in 60 s. Participants (N = 151 in 2011-2012) also completed a behavioral measure of verbal fluency (i.e., how many words starting with "P" or "J" participants could produce in 60 s), a cognitive reappraisal emotion regulation task, and emotion functioning questionnaires. In preregistered analyses, we found that participants produced more negative emotion words than positive words and more positive words than neutral words in the emotion fluency task. As hypothesized, emotion fluency was positively related to verbal fluency, but contrary to hypotheses, emotion fluency was not related to self-reported or task-based emotion functioning (e.g., alexithymia, depression, and emotion regulation ability). As such, in community samples, emotion fluency may reflect general cognitive abilities rather than processes crucial to emotional well-being. While emotion fluency as measured here does not track indices of well-being, future research is needed to investigate potential contexts in which verbal fluency for emotion words may be key to emotion regulation. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Cortical and subcortical mapping of the allostatic-interoceptive system in the human brain: replication and extension with 7 Tesla fMRI

The brain continuously anticipates the energetic needs of the body and prepares to meet those needs before they arise, a process called allostasis. In support of allostasis, the brain continually models the internal state of the body, a process called interoception. Using published tract-tracing studies in non-human animals as a guide, we previously identified a large-scale system supporting allostasis and interoception in the human brain with functional magnetic resonance imaging (fMRI) at 3 Tesla. In the present study, we replicated and extended this system in humans using 7 Tesla fMRI (N = 91), improving the precision of subgenual and pregenual anterior cingulate topography as well as brainstem nuclei mapping. We verified over 90% of the anatomical connections in the hypothesized allostatic-interoceptive system observed in non-human animal research. We also identified functional connectivity hubs verified in tract-tracing studies but not previously detected using 3 Tesla fMRI. Finally, we demonstrated that individuals with stronger fMRI connectivity between system hubs self-reported greater interoceptive awareness, building on construct validity evidence from our earlier paper. Taken together, these results strengthen evidence for the existence of a whole-brain system supporting interoception in the service of allostasis and we consider the implications for mental and physical health.

The impact of sociality and affective valence on brain activation: A meta-analysis

Thirty years of neuroimaging reveal the set of brain regions consistently associated with pleasant and unpleasant affect in humans-or the neural reference space for valence. Yet some of humans' most potent affective states occur in the context of other humans. Prior work has yet to differentiate how the neural reference space for valence varies as a product of the sociality of affective stimuli. To address this question, we meta-analyzed across 614 social and non-social affective neuroimaging contrasts, summarizing the brain regions that are consistently activated for social and non-social affective information. We demonstrate that across the literature, social and non-social affective stimuli yield overlapping activations within regions associated with visceromotor control, including the amygdala, hypothalamus, anterior cingulate cortex and insula. However, we find that social processing differs from non-social affective processing in that it involves additional cortical activations in the medial prefrontal and posterior cingulum that have been associated with mentalizing and prediction. A Bayesian classifier was able to differentiate unpleasant from pleasant affect, but not social from non-social affective states. Moreover, it was not able to classify unpleasantness from pleasantness at the highest levels of sociality. These findings suggest that highly social scenarios may be equally salient to humans, regardless of their valence.

Using citation network analysis to enhance scholarship in psychological science: A case study of the human aggression literature

Researchers cannot keep up with the volume of articles being published each year. In order to develop adequate expertise in a given field of study, students and early career scientists must be strategic in what they decide to read. Here we propose using citation network analysis to characterize the literature topology of a given area. We used the human aggression literature as our example. Our citation network analysis identified 15 research communities on aggression. The five largest communities were: “media and video games”, “stress, traits and aggression”, “rumination and displaced aggression”, “role of testosterone”, and “social aggression”. We examined the growth of these research communities over time, and we used graph theoretic approaches to identify the most influential papers within each community and the “bridging” articles that linked distinct communities to one another. Finally, we also examined whether our citation network analysis would help mitigate gender bias relative to focusing on total citation counts. The percentage of articles with women first authors doubled when identifying influential articles by community structure versus citation count. Our approach of characterizing literature topologies using citation network analysis may provide a valuable resource for psychological scientists by outlining research communities and their growth over time, identifying influential papers within each community (including bridging papers), and providing opportunities to increase gender equity in the field.

Sinful pleasures and pious woes? Using fMRI to examine evaluative and hedonic emotion knowledge

Traditionally, lust and pride have been considered pleasurable, yet sinful in the West. Conversely, guilt is often considered aversive, yet valuable. These emotions illustrate how evaluations about specific emotions and beliefs about their hedonic properties may often diverge. Evaluations about specific emotions may shape important aspects of emotional life (e.g. in emotion regulation, emotion experience and acquisition of emotion concepts). Yet these evaluations are often understudied in affective neuroscience. Prior work in emotion regulation, affective experience, evaluation/attitudes and decision-making point to anterior prefrontal areas as candidates for supporting evaluative emotion knowledge. Thus, we examined the brain areas associated with evaluative and hedonic emotion knowledge, with a focus on the anterior prefrontal cortex. Participants (N = 25) made evaluative and hedonic ratings about emotion knowledge during functional magnetic resonance imaging (fMRI). We found that greater activity in the medial prefrontal cortex (mPFC), ventromedial PFC (vmPFC) and precuneus was associated with an evaluative (vs hedonic) focus on emotion knowledge. Our results suggest that the mPFC and vmPFC, in particular, may play a role in evaluating discrete emotions.

Variation is the Norm: Brain State Dynamics Evoked By Emotional Video Clips

For the last several decades, emotion research has attempted to identify a "biomarker" or consistent pattern of brain activity to characterize a single category of emotion (e.g., fear) that will remain consistent across all instances of that category, regardless of individual and context. In this study, we investigated variation rather than consistency during emotional experiences while people watched video clips chosen to evoke instances of specific emotion categories. Specifically, we developed a sequential probabilistic approach to model the temporal dynamics in a participant's brain activity during video viewing. We characterized brain states during these clips as distinct state occupancy periods between state transitions in blood oxygen level dependent (BOLD) signal patterns. We found substantial variation in the state occupancy probability distributions across individuals watching the same video, supporting the hypothesis that when it comes to the brain correlates of emotional experience, variation may indeed be the norm.

Neural effects of antidepressant medication and psychological treatments: a quantitative synthesis across three meta-analyses

BACKGROUND

Influential theories predict that antidepressant medication and psychological therapies evoke distinct neural changes.

AIMS

To test the convergence and divergence of antidepressant- and psychotherapy-evoked neural changes, and their overlap with the brain's affect network.

METHOD

We employed a quantitative synthesis of three meta-analyses (n = 4206). First, we assessed the common and distinct neural changes evoked by antidepressant medication and psychotherapy, by contrasting two comparable meta-analyses reporting the neural effects of these treatments. Both meta-analyses included patients with affective disorders, including major depressive disorder, generalised anxiety disorder and panic disorder. The majority were assessed using negative-valence tasks during neuroimaging. Next, we assessed whether the neural changes evoked by antidepressants and psychotherapy overlapped with the brain's affect network, using data from a third meta-analysis of affect-based neural activation.

RESULTS

Neural changes from psychotherapy and antidepressant medication did not significantly converge on any region. Antidepressants evoked neural changes in the amygdala, whereas psychotherapy evoked anatomically distinct changes in the medial prefrontal cortex. Both psychotherapy- and antidepressant-related changes separately converged on regions of the affect network.

CONCLUSIONS

This supports the notion of treatment-specific brain effects of antidepressants and psychotherapy. Both treatments induce changes in the affect network, but our results suggest that their effects on affect processing occur via distinct proximal neurocognitive mechanisms of action.

Predictive processing models and affective neuroscience

The neural bases of affective experience remain elusive. Early neuroscience models of affect searched for specific brain regions that uniquely carried out the computations that underlie dimensions of valence and arousal. However, a growing body of work has failed to identify these circuits. Research turned to multivariate analyses, but these strategies, too, have made limited progress. Predictive processing models offer exciting new directions to address this problem. Here, we use predictive processing models as a lens to critique prevailing functional neuroimaging research practices in affective neuroscience. Our review highlights how much work relies on rigid assumptions that are inconsistent with a predictive processing approach. We outline the central aspects of a predictive processing model and draw out their implications for research in affective and cognitive neuroscience. Predictive models motivate a reformulation of "reverse inference" in cognitive neuroscience, and placing a greater emphasis on external validity in experimental design.

A human colliculus-pulvinar-amygdala pathway encodes negative emotion

Animals must rapidly respond to threats to survive. In rodents, threat-related signals are processed through a subcortical pathway from the superior colliculus to the amygdala, a putative "low road" to affective behavior. This pathway has not been well characterized in humans. We developed a novel pathway identification framework that uses pattern recognition to identify connected neural populations and optimize measurement of inter-region connectivity. We first verified that the model identifies known thalamocortical pathways with high sensitivity and specificity in 7 T (n = 56) and 3 T (n = 48) fMRI experiments. Then we identified a human functional superior colliculus-pulvinar-amygdala pathway. Activity in this pathway encodes the intensity of normative emotional responses to negative images and sounds but not pleasant images or painful stimuli. These results provide a functional description of a human "low road" pathway selective for negative exteroceptive events and demonstrate a promising method for characterizing human functional brain pathways.

Emotion Naming Impedes Both Cognitive Reappraisal and Mindful Acceptance Strategies of Emotion Regulation

Friends and therapists often encourage people in distress to say how they feel (i.e., name their emotions) with the hope that identifying their emotions will help them cope. Although lay and some psychological theories posit that emotion naming should facilitate subsequent emotion regulation, there is little research directly testing this question. Here, we report on two experimental studies that test how naming the emotions evoked by aversive images impacts subsequent regulation of those emotions. In study 1 (N = 80), participants were randomly assigned into one of four between-subjects conditions in which they either (i) passively observed aversive images, (ii) named the emotions that these images made them feel, (iii) regulated their emotions by reappraising the meaning of images, or (iv) both named and regulated their emotions. Analyses of self-reported negative affect revealed that emotion naming impeded emotion regulation via reappraisal. Participants who named their emotions before reappraising reported feeling worse than those who regulated without naming. Study 2 (N = 60) replicated these findings in a within-participants design, demonstrated that emotion naming also impeded regulation via mindful acceptance, and showed that observed effects were unrelated to a measure of social desirability, thereby mitigating the concern of experimenter demand. Together, these studies show that the impact of emotion naming on emotion regulation opposes common intuitions: instead of facilitating emotion regulation via reappraisal or acceptance, constructing an instance of a specific emotion category by giving it a name may "crystalize" one's affective experience and make it more resistant to modification.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42761-021-00036-y.

Comparing supervised and unsupervised approaches to emotion categorization in the human brain, body, and subjective experience

Machine learning methods provide powerful tools to map physical measurements to scientific categories. But are such methods suitable for discovering the ground truth about psychological categories? We use the science of emotion as a test case to explore this question. In studies of emotion, researchers use supervised classifiers, guided by emotion labels, to attempt to discover biomarkers in the brain or body for the corresponding emotion categories. This practice relies on the assumption that the labels refer to objective categories that can be discovered. Here, we critically examine this approach across three distinct datasets collected during emotional episodes—measuring the human brain, body, and subjective experience—and compare supervised classification solutions with those from unsupervised clustering in which no labels are assigned to the data. We conclude with a set of recommendations to guide researchers towards meaningful, data-driven discoveries in the science of emotion and beyond.

Affect in the Aging Brain: A Neuroimaging Meta-Analysis of Older Vs. Younger Adult Affective Experience and Perception

We report the first functional neuroimaging meta-analysis on age-related differences in adult neural activity during affect. We identified and coded experimental contrasts from 27 studies (published 1997-2018) with 490 older adults (55-87 years, M _age  = 69 years) and 470 younger adults (18-39 years, M _age  = 24 years). Using multilevel kernel density analysis, we assessed functional brain activation contrasts for older vs. younger adult affect across in-scanner tasks (i.e., affect induction and perception). Relative to older adults, younger adults showed more reliable activation in subcortical structures (e.g., amygdala, thalamus, caudate) and in relatively more posterior aspects of specific brain structures (e.g., posterior insula, mid- and posterior cingulate). In contrast, older adults exhibited more reliable activation in the prefrontal cortex and more anterior aspects of specific brain structures (e.g., anterior insula, anterior cingulate). Meta-analytic coactivation network analyses further revealed that in younger adults, the amygdala and mid-cingulate were more central, locally efficient network nodes, whereas in older adults, regions in the superior and medial prefrontal cortex were more central, locally efficient network nodes. Collectively, these findings help characterize age differences in the brain basis of affect and provide insights for future investigations into the neural mechanisms underlying affective aging.

The influence of fear on risk taking: a meta-analysis

A common finding in the study of emotion and decision making is the tendency for fear and anxiety to decrease risk taking. The current meta-analysis summarises the strength and variability of this effect in the extant empirical literature. Our analysis of 136 effect sizes, derived from 68 independent samples and 9,544 participants, included studies that experimentally manipulated fear or measured naturally varying levels of fear or anxiety in both clinical and non-clinical samples, and studies measuring risky decision making and risk estimation. A multilevel random effects model estimated a small to moderate average effect size (r = 0.22), such that fear was related to decreased risky decision making and increased risk estimation. There was also high heterogeneity in the effect sizes. Moderator analyses showed that effect sizes were greater when risk tasks used tangible (e.g. monetary) outcomes and when studies used clinically anxious participants. However, there also remained considerable variability in effect sizes, the sources of which remain unknown. We posit several potential factors that may contribute to observed variability in this effect for future study, including factors concerning both the nature of fear experience and the risk taking context.

The Default Mode Network's Role in Discrete Emotion

Emotions are often assumed to manifest in subcortical limbic and brainstem structures. While these areas are clearly important for representing affect (e.g., valence and arousal), we propose that the default mode network (DMN) is additionally important for constructing discrete emotional experiences (of anger, fear, disgust, etc.). Findings from neuroimaging studies, invasive electrical stimulation studies, and lesion studies support this proposal. Importantly, our framework builds on a constructionist theory of emotion to explain how instances involving diverse physiological and behavioral patterns can be conceptualized as belonging to the same emotion category. We argue that this ability requires abstraction (from concrete features to broad mental categories), which the DMN is well positioned to support, and we make novel predictions from our proposed framework.

The impact of affective information on working memory: A pair of meta-analytic reviews of behavioral and neuroimaging evidence

Everyday life is defined by goal states that are continuously reprioritized based on available, often affective information. To pursue these goals, individuals need to process and maintain goal-relevant information, while ignoring potentially salient information that distracts resources from these goals. Empirically, this ability has typically been operationalized as working memory (WM) capacity. A growing body of research is investigating the impact of information’s affective salience on WM capacity. In the present review we address this question by exploring the potential differential impact of affective compared with neutral information on WM, and the underlying neural substrates. One-hundred and 65 studies (N = 7,433) were included in the meta-analysis. Results showed negligible to small (d̂ = −.07–.20) effects of affective information on behavioral measures of WM in healthy individuals (n = 4,936) that varied as a function of valence and task-relevance. Heterogeneity analyses were significant, demonstrating the need to identify further study-specific factors and individual differences that moderate affective WM. At the neural level (33 studies; n = 683), processing affective versus neutral material during WM tasks was associated with more frequent recruitment of the vlPFC, the amygdala, and the temporo-occipital cortex. In contrast to healthy individuals, across behavioral studies those suffering from mental health problems (n = 2,041) showed impaired WM accuracy (d̂ = −0.21) in the presence of affective material. These findings highlight the importance of integrating behavioral and neural levels of analysis. Finally, these findings suggest that affective WM capacity may be a transdiagnostic mechanism associated with poor mental health.

The behavioral and neuroimaging meta-analyses showed that in psychologically healthy individuals there was limited support for behavioral working memory (WM) performance to be affected by affective information, whereas at the neural level WM in the presence of affective relative to neutral information was associated with differential recruitment of the salience network and the fronto-parietal control network. These findings highlight the importance of combining behavioral and neuroimaging research syntheses. Second, in individuals with mental health problems WM was significantly impaired by affective material. This suggests that WM performance on tasks including affective compared with neutral information may be a sensitive and transdiagnostic cognitive marker of mental health status.

Historical pitfalls and new directions in the neuroscience of emotion

In this article, we offer a brief history summarizing the last century of neuroscientific study of emotion, highlighting dominant themes that run through various schools of thought. We then summarize the current state of the field, followed by six key points for scientific progress that are inspired by a multi-level constructivist theory of emotion.

Deconstructing arousal into wakeful, autonomic and affective varieties

Arousal plays a central role in a wide variety of phenomena, including wakefulness, autonomic function, affect and emotion. Despite its importance, it remains unclear as to how the neural mechanisms for arousal are organized across them. In this article, we review neuroscience findings for three of the most common origins of arousal: wakeful arousal, autonomic arousal, and affective arousal. Our review makes two overarching points. First, research conducted primarily in non-human animals underscores the importance of several subcortical nuclei that contribute to various sources of arousal, motivating the need for an integrative framework. Thus, we outline an integrative neural reference space as a key first step in developing a more systematic understanding of central nervous system contributions to arousal. Second, there is a translational gap between research on non-human animals, which emphasizes subcortical nuclei, and research on humans using non-invasive neuroimaging techniques, which focuses more on gross anatomical characterizations of cortical (e.g. network architectures including the default mode network) and subcortical structures. We forecast the importance of high-field neuroimaging in bridging this gap to examine how the various networks within the neural reference space for arousal operate across varieties of arousal-related phenomena.

The role of language in the experience and perception of emotion: a neuroimaging meta-analysis

Recent behavioral and neuroimaging studies demonstrate that labeling one's emotional experiences and perceptions alters those states. Here, we used a comprehensive meta-analysis of the neuroimaging literature to systematically explore whether the presence of emotion words in experimental tasks has an impact on the neural representation of emotional experiences and perceptions across studies. Using a database of 386 studies, we assessed brain activity when emotion words (e.g. 'anger', 'disgust') and more general affect words (e.g. 'pleasant', 'unpleasant') were present in experimental tasks vs not present. As predicted, when emotion words were present, we observed more frequent activations in regions related to semantic processing. When emotion words were not present, we observed more frequent activations in the amygdala and parahippocampal gyrus, bilaterally. The presence of affect words did not have the same effect on the neural representation of emotional experiences and perceptions, suggesting that our observed effects are specific to emotion words. These findings are consistent with the psychological constructionist prediction that in the absence of accessible emotion concepts, the meaning of affective experiences and perceptions are ambiguous. Findings are also consistent with the regulatory role of 'affect labeling'. Implications of the role of language in emotion construction and regulation are discussed.

Contextual connectivity: A framework for understanding the intrinsic dynamic architecture of large-scale functional brain networks

Investigations of the human brain's connectomic architecture have produced two alternative models: one describes the brain's spatial structure in terms of static localized networks, and the other describes the brain's temporal structure in terms of dynamic whole-brain states. Here, we used tools from connectivity dynamics to develop a synthesis that bridges these models. Using resting fMRI data, we investigated the assumptions undergirding current models of the human connectome. Consistent with state-based models, our results suggest that static localized networks are superordinate approximations of underlying dynamic states. Furthermore, each of these localized, dynamic connectivity states is associated with global changes in the whole-brain functional connectome. By nesting localized dynamic connectivity states within their whole-brain contexts, we demonstrate the relative temporal independence of brain networks. Our assay for functional autonomy of coordinated neural systems is broadly applicable, and our findings provide evidence of structure in temporal state dynamics that complements the well-described static spatial organization of the brain.

Novel response patterns during repeated presentation of affective and neutral stimuli

Repeated stimulus presentations are commonly used in social and affective neuroimaging tasks, but much remains to be known about how the brain processes such repetitions. Using functional magnetic resonance imaging, we found three groups of brain regions with distinct response patterns during repeated presentations of natural scene images. One group consisted of several limbic, paralimbic, frontoparietal and medial prefrontal areas and showed a habituation-like response across pleasant, unpleasant, and neutral image categories. A second group of occipital and adjacent posterior cortical regions showed a pattern of diminishing responses with repeated presentations of affective images but not for neutral images, and also plateaued to activation levels above baseline for all image categories. A third group involved bilateral frontopolar areas and the precuneus and exhibited a novel, non-monotonic response pattern. Activity was low on the first presentation, peaked upon the second presentation (first repetition) and subsequently diminished. These findings indicate that the transition from novel to increasingly familiar, and also arousing to less arousing, involves a broad array of neural mechanisms alluding to both passive learning and active inference strategies.

Emotions in "Black and White" or Shades of Gray? How We Think About Emotion Shapes Our Perception and Neural Representation of Emotion

The demands of social life often require categorically judging whether someone's continuously varying facial movements express "calm" or "fear," or whether one's fluctuating internal states mean one feels "good" or "bad." In two studies, we asked whether this kind of categorical, "black and white," thinking can shape the perception and neural representation of emotion. Using psychometric and neuroimaging methods, we found that (a) across participants, judging emotions using a categorical, "black and white" scale relative to judging emotions using a continuous, "shades of gray," scale shifted subjective emotion perception thresholds; (b) these shifts corresponded with activity in brain regions previously associated with affective responding (i.e., the amygdala and ventral anterior insula); and (c) connectivity of these regions with the medial prefrontal cortex correlated with the magnitude of categorization-related shifts. These findings suggest that categorical thinking about emotions may actively shape the perception and neural representation of the emotions in question.

Involvement of Sensory Regions in Affective Experience: A Meta-Analysis

A growing body of work suggests that sensory processes may also contribute to affective experience. In this study, we performed a meta-analysis of affective experiences driven through visual, auditory, olfactory, gustatory, and somatosensory stimulus modalities including study contrasts that compared affective stimuli to matched neutral control stimuli. We found, first, that limbic and paralimbic regions, including the amygdala, anterior insula, pre-supplementary motor area, and portions of orbitofrontal cortex were consistently engaged across two or more modalities. Second, early sensory input regions in occipital, temporal, piriform, mid-insular, and primary sensory cortex were frequently engaged during affective experiences driven by visual, auditory, olfactory, gustatory, and somatosensory inputs. A classification analysis demonstrated that the pattern of neural activity across a contrast map diagnosed the stimulus modality driving the affective experience. These findings suggest that affective experiences are constructed from activity that is distributed across limbic and paralimbic brain regions and also activity in sensory cortical regions.

Does language do more than communicate emotion?

Language can certainly communicate emotions, but growing research suggests that language also helps constitute emotion by cohering sensations into specific perceptions of "anger," "disgust," "fear," etc. The powerful role of language in emotion is predicted by a constructionist approach, which suggests that emotions occur when sensations are categorized using emotion category knowledge supported by language. We discuss the accumulating evidence from social cognitive, neuropsychological, cross-cultural, and neuroimaging studies that emotion words go beyond communication to help constitute emotional perceptions, and perhaps even emotional experiences. We look forward to current directions in research on emotional intelligence, emotion regulation, and psychotherapy.

A Bayesian model of category-specific emotional brain responses

Understanding emotion is critical for a science of healthy and disordered brain function, but the neurophysiological basis of emotional experience is still poorly understood. We analyzed human brain activity patterns from 148 studies of emotion categories (2159 total participants) using a novel hierarchical Bayesian model. The model allowed us to classify which of five categories--fear, anger, disgust, sadness, or happiness--is engaged by a study with 66% accuracy (43-86% across categories). Analyses of the activity patterns encoded in the model revealed that each emotion category is associated with unique, prototypical patterns of activity across multiple brain systems including the cortex, thalamus, amygdala, and other structures. The results indicate that emotion categories are not contained within any one region or system, but are represented as configurations across multiple brain networks. The model provides a precise summary of the prototypical patterns for each emotion category, and demonstrates that a sufficient characterization of emotion categories relies on (a) differential patterns of involvement in neocortical systems that differ between humans and other species, and (b) distinctive patterns of cortical-subcortical interactions. Thus, these findings are incompatible with several contemporary theories of emotion, including those that emphasize emotion-dedicated brain systems and those that propose emotion is localized primarily in subcortical activity. They are consistent with componential and constructionist views, which propose that emotions are differentiated by a combination of perceptual, mnemonic, prospective, and motivational elements. Such brain-based models of emotion provide a foundation for new translational and clinical approaches.

The Brain Basis of Positive and Negative Affect: Evidence from a Meta-Analysis of the Human Neuroimaging Literature

The ability to experience pleasant or unpleasant feelings or to represent objects as "positive" or "negative" is known as representing hedonic "valence." Although scientists overwhelmingly agree that valence is a basic psychological phenomenon, debate continues about how to best conceptualize it scientifically. We used a meta-analysis of 397 functional magnetic resonance imaging (fMRI) and positron emission tomography studies (containing 914 experimental contrasts and 6827 participants) to test 3 competing hypotheses about the brain basis of valence: the bipolarity hypothesis that positive and negative affect are supported by a brain system that monotonically increases and/or decreases along the valence dimension, the bivalent hypothesis that positive and negative affect are supported by independent brain systems, and the affective workspace hypothesis that positive and negative affect are supported by a flexible set of valence-general regions. We found little evidence for the bipolar or bivalent hypotheses. Findings instead supported the hypothesis that, at the level of brain activity measurable by fMRI, valence is flexibly implemented across instances by a set of valence-general limbic and paralimbic brain regions.

Distinct regions of prefrontal cortex are associated with the controlled retrieval and selection of social information

Research in social neuroscience has uncovered a social knowledge network that is particularly attuned to making social judgments. However, the processes that are being performed by both regions within this network and those outside of this network that are nevertheless engaged in the service of making a social judgment remain unclear. To help address this, we drew upon research in semantic memory, which suggests that making a semantic judgment engages 2 distinct control processes: A controlled retrieval process, which aids in bringing goal-relevant information to mind from long-term stores, and a selection process, which aids in selecting the information that is goal-relevant from the information retrieved. In a neuroimaging study, we investigated whether controlled retrieval and selection for social information engage distinct portions of both the social knowledge network and regions outside this network. Controlled retrieval for social information engaged an anterior ventrolateral portion of the prefrontal cortex, whereas selection engaged both the dorsomedial prefrontal cortex and temporoparietal junction within the social knowledge network. These results suggest that the social knowledge network may be more involved with the selection of social information than the controlled retrieval of it and incorporates lateral prefrontal regions in accessing memory for making social judgments.

The functional neural architecture of self-reports of affective experience

BACKGROUND

The ability to self-report on affective experience is essential to both our everyday communication about emotion and our scientific understanding of it. However, the underlying cognitive and neural mechanisms for how people construct statements even as simple as "I feel bad!" remain unclear. We examined whether the neural architecture underlying the ability to make statements about affective experience is composed of distinct functional systems.

METHODS

In a novel functional magnetic neuroimaging paradigm, 20 participants were shown images varying in affective intensity; they were required either to attend to and judge the affective response versus to nonaffective aspects of the stimulus and either to categorize their response into a verbal label or report on a scale that did not require verbal labeling.

RESULTS

We found that the ability to report on affective states involves (at least) three separable systems, one for directing attention to the affective response and making attributions about it that involves the dorsomedial prefrontal cortex, one for categorizing the response into a verbal label or word that involves the ventrolateral prefrontal cortex, and one sensitive to the intensity of the affective response including the ventral anterior insula and amygdala.

CONCLUSIONS

These results suggest that unified statements about affective experience rely on integrating information from several distinct neural systems. Results are discussed in the context of how disruptions to one or another of these systems may produce unique deficits in the ability to describe affective states and the implications this may hold for clinical populations.

Neural reactivation links unconscious thought to decision-making performance

Brief periods of unconscious thought (UT) have been shown to improve decision making compared with making an immediate decision (ID). We reveal a neural mechanism for UT in decision making using blood oxygen level-dependent (BOLD) functional magnetic resonance imaging. Participants (N = 33) encoded information on a set of consumer products (e.g. 48 attributes describing four different cars), and we manipulated whether participants (i) consciously thought about this information (conscious thought), (ii) completed a difficult 2-back working memory task (UT) or (iii) made an immediate decision about the consumer products (ID) in a within-subjects blocked design. To differentiate UT neural activity from 2-back working memory neural activity, participants completed an independent 2-back task and this neural activity was subtracted from neural activity occurring during the UT 2-back task. Consistent with a neural reactivation account, we found that the same regions activated during the encoding of complex decision information (right dorsolateral prefrontal cortex and left intermediate visual cortex) continued to be activated during a subsequent 2-min UT period. Moreover, neural reactivation in these regions was predictive of subsequent behavioral decision-making performance after the UT period. These results provide initial evidence for post-encoding unconscious neural reactivation in facilitating decision making.

Human anterior and posterior hippocampus respond distinctly to state and trait anxiety

We examined whether anterior and posterior hippocampal subregions in humans show distinct relationships to state and trait anxiety. In rodents, the ventral (but not dorsal) hippocampus is critically involved in contextual anxiety, whereas dorsal hippocampus is affected by chronic stress and genetically bred trait anxiety. These studies suggest that state forms of anxiety may be more associated with anterior (ventral in rodents) hippocampus, whereas trait forms of anxiety maybe more associated with posterior (dorsal in rodents) hippocampus. Participants were placed under alternating blocks of threat of shock and safety conditions while performing a secondary task, and state and trait anxiety measures were obtained. Using subject-specific anatomically defined masks, we found that state anxiety was related to activity in anterior but not posterior hippocampus, whereas trait anxiety showed the opposite pattern. Additionally, a psychophysiological connectivity analysis showed that activity in anterior hippocampus was more strongly related to activity in ventromedial prefrontal cortex under threat than under safety conditions, significantly more so than activity in posterior hippocampus was. Hence, anterior hippocampus shows a distinct moment-to-moment connectivity profile with other neural regions during threat relative to posterior hippocampus. The findings provide several lines of evidence for functional differentiation of anterior and posterior hippocampal involvement across state and trait components of anxiety in humans.

Identifying the What, Why, and How of an Observed Action: An fMRI Study of Mentalizing and Mechanizing during Action Observation

Humans commonly understand the unobservable mental states of others by observing their actions. Embodied simulation theories suggest that this ability may be based in areas of the fronto-parietal mirror neuron system, yet neuroimaging studies that explicitly investigate the human ability to draw mental state inferences point to the involvement of a “mentalizing” system consisting of regions that do not overlap with the mirror neuron system. For the present study, we developed a novel action identification paradigm that allowed us to explicitly investigate the neural bases of mentalizing observed actions. Across repeated viewings of a set of ecologically valid video clips of ordinary human actions, we manipulated the extent to which participants identified the unobservable mental states of the actor (mentalizing) or the observable mechanics of their behavior (mechanizing). Although areas of the mirror neuron system did show an enhanced response during action identification, its activity was not significantly modulated by the extent to which the observers identified mental states. Instead, several regions of the mentalizing system, including dorsal and ventral aspects of medial pFC, posterior cingulate cortex, and temporal poles, were associated with mentalizing actions, whereas a single region in left lateral occipito-temporal cortex was associated with mechanizing actions. These data suggest that embodied simulation is insufficient to account for the sophisticated mentalizing that human beings are capable of while observing another and that a different system along the cortical midline and in anterior temporal cortex is involved in mentalizing an observed action.

The sunny side of fairness: preference for fairness activates reward circuitry (and disregarding unfairness activates self-control circuitry)

Little is known about the positive emotional impact of fairness or the process of resolving conflict between fairness and financial interests. In past research, fairness has covaried with monetary payoff, such that the mental processes underlying preference for fairness and those underlying preference for greater monetary outcome could not be distinguished. We examined self-reported happiness and neural responses to fair and unfair offers while controlling for monetary payoff. Compared with unfair offers of equal monetary value, fair offers led to higher happiness ratings and activation in several reward regions of the brain. Furthermore, the tendency to accept unfair proposals was associated with increased activity in right ventrolateral prefrontal cortex, a region involved in emotion regulation, and with decreased activity in the anterior insula, which has been implicated in negative affect. This work provides evidence that fairness is hedonically valued and that tolerating unfair treatment for material gain involves a pattern of activation resembling suppression of negative affect.

Integrating automatic and controlled processes into neurocognitive models of social cognition

Interest in the neural systems underlying social perception has expanded tremendously over the past few decades. However, gaps between behavioral literatures in social perception and neuroscience are still abundant. In this article, we apply the concept of dual-process models to neural systems in an effort to bridge the gap between many of these behavioral studies and neural systems underlying social perception. We describe and provide support for a neural division between reflexive and reflective systems. Reflexive systems correspond to automatic processes and include the amygdala, basal ganglia, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, and lateral temporal cortex. Reflective systems correspond to controlled processes and include lateral prefrontal cortex, posterior parietal cortex, medial prefrontal cortex, rostral anterior cingulate cortex, and the hippocampus and surrounding medial temporal lobe region. This framework is considered to be a working model rather than a finished product. Finally, the utility of this model and its application to other social cognitive domains such as Theory of Mind are discussed.

An fMRI study of causal judgments

The capacity to evaluate causal relations is fundamental to human cognition, and yet little is known of its neurocognitive underpinnings. A functional magnetic resonance imaging study was performed to investigate an hypothesized dissociation between the use of semantic knowledge to evaluate specifically causal relations in contrast to general associative relations. Identical pairs of words were judged for causal or associative relations in different blocks of trials. Causal judgments, beyond associative judgments, generated distinct activation in left dorsolateral prefrontal cortex and right pre-cuneus. These findings indicate that the evaluation of causal relations in semantic memory involves additional neural mechanisms relative to those required to evaluate associative relations.

Personality from a controlled processing perspective: An fMRI study of neuroticism, extraversion, and self-consciousness

Although neuroticism has been central to most theories of personality, self-reported neuroticism has had limited success in predicting expected behavioral outcomes. The reason for this may be due, in part, to the imprecision of self-reports. The purpose of this study was to examine the relationship between neural correlates of control systems and neuroticism, extraversion, and self-consciousness. In response to an oddball task, neuroticism was associated with increased dorsal anterior cingulate cortex (dACC) reactivity, typically associated with discrepancy detection, whereas extraversion and self-consciousness were associated with lateral and medial frontoparietal networks, respectively, typically associated with task-focused (lateral) or self-focused (medial) controlled processes. We also examined whether the neural measure of neuroticism would predict a relevant behavioral outcome better than self-reports would. Interoceptive accuracy, an outcome associated with neuroticism, was better accounted for by dACC reactivity (r2 = .74) than by self-reported neuroticism (r2 = .16), suggesting that neural reactivities may provide a more direct measure of personality than self-reports do.

Context Processing and Context Maintenance in Healthy Aging and Early Stage Dementia of the Alzheimer's Type

Declines in the ability to process context information may represent a fundamental mechanism of age-related cognitive changes. Two components of context processing--activation/updating and maintenance--were examined in a sample of healthy younger and older adults, along with individuals suffering from early stage dementia of the Alzheimer's type (DAT). All older adult groups showed context activation/updating impairments, whereas context maintenance was only impaired in the oldest adults (age>75 years) and was further exacerbated in DAT individuals. The results suggest that context processing may be composed of functionally dissociable components and point to the utility of this construct in understanding the timecourse of cognitive decline in healthy and pathological aging.

Evidence-Based and Intuition-Based Self-Knowledge: An fMRI Study

Behavioral and neuropsychological studies have suggested multiple self-knowledge systems may exist (i.e., evidence-based and intuition-based self-knowledge); however, little is known about the nature of intuition-based self-knowledge. In a functional magnetic resonance imaging study, the neural correlates of intuition-based and evidence-based self-knowledge were investigated. Participants with high and low experience in different domains (soccer and acting) made self-descriptiveness judgments about words from each domain while being scanned. High-experience domain judgments produced activation in a network of neural structures called the X-system, involved in automatic social cognition, whereas low-experience domain judgments produced activations in a network called the C-system, involved in effortful social cognition and propositional thought. The affective and slow-changing nature of intuition-based self-knowledge is discussed.