7-Tesla evidence for columnar and rostral-caudal organization of the human periaqueductal gray response in the absence of threat: a working memory study.

The periaqueductal gray (PAG) is a small midbrain structure that surrounds the cerebral aqueduct, regulates brain-body communication, and is often studied for its role in "fight-or-flight" and "freezing" responses to threat. We used ultra-high field 7-Tesla fMRI to resolve the PAG in humans and distinguish it from the cerebral aqueduct, examining its in vivo function in humans during a working memory task (N = 87). Both mild and moderate cognitive demand elicited spatially similar patterns of whole brain BOLD response, and moderate cognitive demand elicited widespread BOLD increases above baseline in the brainstem. Notably, these brainstem increases were not significantly greater than those in the mild demand condition, suggesting that a subthreshold brainstem BOLD increase occurred for mild cognitive demand as well. PAG response was group-aligned and examined with subject-specific masks. In PAG, both mild and moderate demand elicited a well-defined response in ventrolateral PAG (vlPAG), a region thought to be functionally related to anticipated painful threat in humans and non-human animals-yet, the present task posed only the most minimal (if any) "threat", with the cognitive tasks used being approximately equivalent to remembering a phone number. These findings suggest that the PAG may play a more general role in visceromotor regulation, even in the absence of threat.Significance statement The periaqueductal gray (PAG) is thought to control survival-related behavior, and is typically studied using experiments that manipulate threat. Others have proposed that the PAG plays a more general role in bodily regulation, but studies examining PAG function outside of threat-based experimental contexts are rare. We used high-resolution fMRI to examine PAG response in humans during a working memory task, which involves minimal threat. Moderate cognitive demands elicited a well-defined response in ventrolateral PAG, a functional subregion thought to coordinate a "freezing" response to threat. A task where threat is minimal elicited a clear fMRI response in one of the most well-known survival circuits in the brain, which suggests the PAG supports a more general function in brain--body coordination.

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).

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.

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).

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.

A Computational Neural Model for Mapping Degenerate Neural Architectures.

Degeneracy in biological systems refers to a many-to-one mapping between physical structures and their functional (including psychological) outcomes. Despite the ubiquity of the phenomenon, traditional analytical tools for modeling degeneracy in neuroscience are extremely limited. In this study, we generated synthetic datasets to describe three situations of degeneracy in fMRI data to demonstrate the limitations of the current univariate approach. We describe a novel computational approach for the analysis referred to as neural topographic factor analysis (NTFA). NTFA is designed to capture variations in neural activity across task conditions and participants. The advantage of this discovery-oriented approach is to reveal whether and how experimental trials and participants cluster into task conditions and participant groups. We applied NTFA on simulated data, revealing the appropriate degeneracy assumption in all three situations and demonstrating NTFA's utility in uncovering degeneracy. Lastly, we discussed the importance of testing degeneracy in fMRI data and the implications of applying NTFA to do so.

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.

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.

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.

At the Neural Intersection Between Language and Emotion.

What role does language play in emotion? Behavioral research shows that emotion words such as "anger" and "fear" alter emotion experience, but questions still remain about mechanism. Here, we review the neuroscience literature to examine whether neural processes associated with semantics are also involved in emotion. Our review suggests that brain regions involved in the semantic processing of words: (i) are engaged during experiences of emotion, (ii) coordinate with brain regions involved in affect to create emotions, (iii) hold representational content for emotion, and (iv) may be necessary for constructing emotional experience. We relate these findings with respect to four theoretical relationships between language and emotion, which we refer to as "non-interactive," "interactive," "constitutive," and "deterministic." We conclude that findings are most consistent with the interactive and constitutive views with initial evidence suggestive of a constitutive view, in particular. We close with several future directions that may help test hypotheses of the constitutive view.

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.

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.

Ultra High Field fMRI of Human Superior Colliculi Activity during Affective Visual Processing.

Research on rodents and non-human primates has established the involvement of the superior colliculus in defensive behaviours and visual threat detection. The superior colliculus has been well-studied in humans for its functional roles in saccade and visual processing, but less is known about its involvement in affect. In standard functional MRI studies of the human superior colliculus, it is challenging to discern activity in the superior colliculus from activity in surrounding nuclei such as the periaqueductal gray due to technological and methodological limitations. Employing high-field strength (7 Tesla) fMRI techniques, this study imaged the superior colliculus at high (0.75 mm isotropic) resolution, which enabled isolation of the superior colliculus from other brainstem nuclei. Superior colliculus activation during emotionally aversive image viewing blocks was greater than that during neutral image viewing blocks. These findings suggest that the superior colliculus may play a role in shaping subjective emotional experiences in addition to its visuomotor functions, bridging the gap between affective research on humans and non-human animals.

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 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.