Neurocomputational Substrates Underlying the Effect of Identifiability on Third-Party Punishment.

The identifiable target effect refers to the preference for helping identified victims and punishing identifiable perpetrators compared with equivalent but unidentifiable counterparts. The identifiable target effect is often attributed to the heightened moral emotions evoked by identified targets. However, the specific neurocognitive processes that mediate and/or modulate this effect remain largely unknown. Here, we combined a third-party punishment game with brain imaging and computational modeling to unravel the neurocomputational underpinnings of the identifiable transgressor effect. Human participants (males and females) acted as bystanders and punished identified or anonymous wrongdoers. Participants were more punitive toward identified wrongdoers than anonymous wrongdoers because they took a vicarious perspective of victims and adopted lower reference points of inequity (i.e., more stringent norms) in the identified context than in the unidentified context. Accordingly, there were larger activity of the ventral anterior insula, more distinct multivariate neural patterns in the dorsal anterior insula and dorsal anterior cingulate cortex, and lower strength between ventral anterior insula and dorsolateral PFC and between dorsal anterior insula and ventral striatum connectivity in response to identified transgressors than anonymous transgressors. These findings implicate the interplay of expectancy violations, emotions, and self-interest in the identifiability effect. Last, individual differences in the identifiability effect were associated with empathic concern/social dominance orientation, activity in the precuneus/cuneus and temporo-parietal junction, and intrinsic functional connectivity of the dorsolateral PFC. Together, our work is the first to uncover the neurocomputational processes mediating identifiable transgressor effect and to characterize psychophysiological profiles modulating the effect.SIGNIFICANCE STATEMENT The identifiable target effect, more help to identified victims or stronger punishment to identifiable perpetrators, is common in daily life. We examined the neurocomputational mechanisms mediating/modulating the identifiability effect on third-party punishment by bridging literature from economics and cognitive neuroscience. Our findings reveal that identifiable transgressor effect is mediated by lower reference points of inequity (i.e., more stringent norms), which might be associated with a stronger involvement of the emotion processes and a weaker engagement of the analytic/deliberate processes. Furthermore, personality traits, altered brain activity, and intrinsic functional connectivity contribute to the individual variance in the identifiability effect. Overall, our study advances the understanding of the identifiability effect by shedding light on its component processes and modulating factors.

Uncovering individual variations in bystander intervention of injustice through intrinsic brain connectivity patterns.

When confronted with injustice, individuals often intervene as third parties to restore justice by either punishing the perpetrator or helping the victim, even at their own expense. However, little is known about how individual differences in third-party intervention propensity are related to inter-individual variability in intrinsic brain connectivity patterns and how these associations vary between help and punishment intervention. To address these questions, we employed a novel behavioral paradigm in combination with resting-state fMRI and inter-subject representational similarity analysis (IS-RSA). Participants acted as third-party bystanders and needed to decide whether to maintain the status quo or intervene by either helping the disadvantaged recipient (Help condition) or punishing the proposer (Punish condition) at a specific cost. Our analyses focused on three brain networks proposed in the third-party punishment (TPP) model: the salience (e.g., dorsal anterior cingulate cortex, dACC), central executive (e.g., dorsolateral prefrontal cortex, dlPFC), and default mode (e.g., dorsomedial prefrontal cortex, dmPFC; temporoparietal junction, TPJ) networks. IS-RSA showed that individual differences in resting-state functional connectivity (rs-FC) patterns within these networks were associated with the general third-party intervention propensity. Moreover, rs-FC patterns of the right dlPFC and right TPJ were more strongly associated with individual differences in the helping propensity rather than the punishment propensity, whereas the opposite pattern was observed for the dmPFC. Post-hoc predictive modeling confirmed the predictive power of rs-FC in these regions for intervention propensity across individuals. Collectively, these findings shed light on the shared and distinct roles of key regions in TPP brain networks at rest in accounting for individual variations in justice-restoring intervention behaviors.

Common neural dysfunction of economic decision-making across psychiatric conditions.

Adaptive decision-making, which is often impaired in various psychiatric conditions, is essential for well-being. Recent evidence has indicated that decision-making capacity in multiple tasks could be accounted for by latent dimensions, enlightening the question of whether there is a common disruption of brain networks in economic decision-making across psychiatric conditions. Here, we addressed the issue by combining activation/lesion network mapping analyses with a transdiagnostic brain imaging meta-analysis. Our findings indicate that there were transdiagnostic alterations in the thalamus and ventral striatum during the decision or outcome stage of decision-making. The identified regions represent key nodes in a large-scale network, which is composed of multiple heterogeneous brain regions and plays a causal role in motivational functioning. The findings suggest that disturbances in the network associated with emotion- and reward-related processing play a key role in dysfunctions of decision-making observed in various psychiatric conditions. This study provides the first meta-analytic evidence of common neural alterations linked to deficits in economic decision-making.

Brain responses to self- and other- unfairness under resource distribution context: meta-analysis of fMRI studies.

Under resource distribution context, individuals have a strong aversion to unfair treatment not only toward themselves but also toward others. However, there is no clear consensus regarding the commonality and distinction between these two types of unfairness. Moreover, many neuroimaging studies have investigated how people evaluate and respond to unfairness in the abovementioned two contexts, but the consistency of the results remains to be investigated. To resolve these two issues, we sought to summarize existing findings regarding unfairness to self and others and to further elucidate the neural underpinnings related to distinguishing evaluation and response processes through meta-analyses of previous neuroimaging studies. Our results indicated that both types of unfairness consistently activate the affective and conflict-related anterior insula (AI) and dorsal anterior cingulate cortex/supplementary motor area (dACC/SMA), but the activations related to unfairness to self appeared stronger than those related to others, suggesting that individuals had negative reactions to both unfairness and a greater aversive response toward unfairness to self. During the evaluation process, unfairness to self activated the bilateral AI, dACC, and right dorsolateral prefrontal cortex (DLPFC), regions associated with unfairness aversion, conflict, and cognitive control, indicating reactive, emotional and automatic responses. In contrast, unfairness to others activated areas associated with theory of mind, the inferior parietal lobule and temporoparietal junction (IPL-TPJ), suggesting that making rational judgments from the perspective of others was needed. During the response, unfairness to self activated the affective-related left AI and striatum, whereas unfairness to others activated cognitive control areas, the left DLPFC and the thalamus. This indicated that the former maintained the traits of automaticity and emotionality, whereas the latter necessitated cognitive control. These findings provide a fine-grained description of the common and distinct neurocognitive mechanisms underlying unfairness to self and unfairness to others. Overall, this study not only validates the inequity aversion model but also provides direct evidence of neural mechanisms for neurobiological models of fairness.

Dissociated modulations of intranasal vasopressin on prosocial learning between reward-seeking and punishment-avoidance.

BACKGROUND: As an integral ingredient of human sociality, prosocial behavior requires learning what acts can benefit or harm others. However, it remains unknown how individuals adjust prosocial learning to avoid punishment or to pursue reward. Given that arginine vasopressin (AVP) is a neuropeptide that has been involved in modulating various social behaviors in mammals, it could be a crucial neurochemical facilitator that supports prosocial learning. METHODS: In 50 placebo controls and 54 participants with AVP administration, we examined the modulation of AVP on the prosocial learning characterized by reward and punishment framework, as well as its underlying neurocomputational mechanisms combining computational modeling, event-related potentials and oscillations. RESULTS: We found a self-bias that individuals learn to avoid punishment asymmetrically more severely than reward-seeking. Importantly, AVP increased behavioral performances and learning rates when making decisions to avoid losses for others and to obtain gains for self. These behavioral effects were underpinned by larger responses of stimulus-preceding negativity (SPN) to anticipation, as well as higher punishment-related feedback-related negativity (FRN) for prosocial learning and reward-related P300 for proself benefits, while FRN and P300 neural processes were integrated into theta (4-7 Hz) oscillation at the outcome evaluation stage. CONCLUSIONS: These results suggest that AVP context-dependently up-regulates altruism for concerning others' losses and reward-seeking for self-oriented benefits. Our findings provide insight into the selectively modulatory roles of AVP in prosocial behaviors depending on learning contexts between proself reward-seeking and prosocial punishment-avoidance.

Static and dynamic topological organizations of the costly punishment network predict individual differences in punishment propensity.

Human costly punishment plays a vital role in maintaining social norms. Recently, a brain network model is conceptually proposed indicating that the implement of costly punishment depends on a subset of nodes in three high-level networks. This model, however, has not yet been empirically examined from an integrated perspective of large-scale brain networks. Here, we conducted comprehensive graph-based network analyses of resting-state functional magnetic resonance imaging data to explore system-level characteristics of intrinsic functional connectivity among 18 regions related to costly punishment. Nontrivial organizations (small-worldness, connector hubs, and high flexibility) were found that were qualitatively stable across participants and over time but quantitatively exhibited low test-retest reliability. The organizations were predictive of individual costly punishment propensities, which was reproducible on independent samples and robust against different analytical strategies and parameter settings. Moreover, the prediction was specific to system-level network organizations (rather than interregional functional connectivity) derived from positive (rather than negative or combined) connections among the specific (rather than randomly chosen) subset of regions from the three high-order (rather than primary) networks. Collectively, these findings suggest that human costly punishment emerges from integrative behaviors among specific regions in certain functional networks, lending support to the brain network model for costly punishment.

Separate neural subsystems support goal-directed speech listening.

How do humans excel at tracking the narrative of a particular speaker with a distracting noisy background? This feat places great demands on the collaboration between speech processing and goal-related regulatory functions. Here, we propose that separate subsystems with different cross-task dynamic activity properties and distinct functional purposes support goal-directed speech listening. We adopted a naturalistic dichotic speech listening paradigm in which listeners were instructed to attend to only one narrative from two competing inputs. Using functional magnetic resonance imaging with inter- and intra-subject correlation techniques, we discovered a dissociation in response consistency in temporal, parietal and frontal brain areas as the task demand varied. Specifically, some areas in the bilateral temporal cortex (SomMotB_Aud and TempPar) and lateral prefrontal cortex (DefaultB_PFCl and ContA_PFCl) always showed consistent activation across subjects and across scan runs, regardless of the task demand. In contrast, some areas in the parietal cortex (DefaultA_pCunPCC and ContC_pCun) responded reliably only when the task goal remained the same. These results suggested two dissociated functional neural networks that were independently validated by performing a data-driven clustering analysis of voxelwise functional connectivity patterns. A subsequent meta-analysis revealed distinct functional profiles for these two brain correlation maps. The different-task correlation map was strongly associated with language-related processes (e.g., listening, speech and sentences), whereas the same-task versus different-task correlation map was linked to self-referencing functions (e.g., default mode, theory of mind and autobiographical topics). Altogether, the three-pronged findings revealed two anatomically and functionally dissociated subsystems supporting goal-directed speech listening.

Intrinsic brain activity patterns across large-scale networks predict reciprocity propensity.

Reciprocity is prevalent across human societies, but individuals are heterogeneous regarding their reciprocity propensity. Although a large body of task-based brain imaging measures has shed light on the neural underpinnings of reciprocity at group level, the neural basis underlying the individual differences in reciprocity propensity remains largely unclear. Here, we combined brain imaging and machine learning techniques to individually predict reciprocity propensity from resting-state brain activity measured by fractional amplitude of low-frequency fluctuation. The brain regions contributing to the prediction were then analyzed for functional connectivity and decoding analyses, allowing for a data-driven quantitative inference on psychophysiological functions. Our results indicated that patterns of resting-state brain activity across multiple brain systems were capable of predicting individual reciprocity propensity, with the contributing regions distributed across the salience (e.g., ventrolateral prefrontal cortex), fronto-parietal (e.g., dorsolateral prefrontal cortex), default mode (e.g., ventromedial prefrontal cortex), and sensorimotor (e.g., supplementary motor area) networks. Those contributing brain networks are implicated in emotion and cognitive control, mentalizing, and motor-based processes, respectively. Collectively, these findings provide novel evidence on the neural signatures underlying the individual differences in reciprocity, and lend support the assertion that reciprocity emerges from interactions among regions embodied in multiple large-scale brain networks.

Differentiating the abnormalities of social and monetary reward processing associated with depressive symptoms.

BACKGROUND: Reward dysfunction is a major dimension of depressive symptomatology, but it remains obscure if that dysfunction varies across different reward types. In this study, we focus on the abnormalities in anticipatory/consummatory processing of monetary and social reward associated with depressive symptoms. METHODS: Forty participants with depressive symptoms and forty normal controls completed the monetary incentive delay (MID) and social incentive delay (SID) tasks with event-related potential (ERP) recording. RESULTS: In the SID but not the MID task, both the behavioral hit rate and the ERP component contingent negative variation (CNV; indicating reward anticipation) were sensitive to the interaction between the grouping factor and reward magnitude; that is, the depressive group showed a lower hit rate and a smaller CNV to large-magnitude (but not small-magnitude) social reward cues compared to the control group. Further, these two indexes were correlated with each other. Meanwhile, the ERP components feedback-related negativity and P3 (indicating reward consumption) were sensitive to the main effect of depression across the MID and SID tasks, though this effect was more prominent in the SID task. CONCLUSIONS: Overall, we suggest that depressive symptoms are associated with deficits in both the reward anticipation and reward consumption stages, particularly for social rewards. These findings have a potential to characterize the profile of functional impairment that comprises and maintains depression.

Effect sizes of associations between neuroimaging measures and affective symptoms: A meta-analysis.

BACKGROUND: The utility of brain-based biomarkers for psychiatric disorders hinges among other factors on their ability to explain a significant portion of the phenotypic variance. In particular, many small scale studies have been unable to arbitrate whether structural or functional magnetic resonance imaging has potential to be a biological marker for these disorders. METHODS: This study conducted a meta-analysis to examine the relationship between study power and published effect sizes for the relationship between affective symptoms and structural or functional magnetic resonance imaging measures. The current analyses are based on 821 brain-affective symptom association effect sizes derived from 120 publications, which employed a univariate region-of-interest approach. RESULTS: For self-assessed affective symptoms published brain imaging measures accounted for on average 8% (confidence interval: 1.6%-23%) of between-subject variation. This average effect size was based mostly on studies with small sample sizes, which have likely led to inflation of these effect size estimates. CONCLUSIONS: These findings support the conclusion that brain imaging measures currently account for a smaller proportion of the interindividual variance in affective symptoms than has been previously reported. The current findings support the need for both large-sample clinical studies and new statistical and theoretical models to more robustly capture systematic variance of brain-affective symptom relationships.

From gratitude to injustice: Neurocomputational mechanisms of gratitude-induced injustice.

Gratitude shapes individuals' behaviours and impacts the harmony of society. Many previous studies focused on its association with prosocial behaviours. A possibility that gratitude can lead to moral violation has been overlooked until recently. Nevertheless, the neurocognitive mechanisms of gratitude-induced moral violation are still unclear. On the other hand, though neural correlates of the gratitude's formation have been examined, the neural underpinnings of gratitude-induced behaviour remain unknown. For addressing these two overlapped research gaps, we developed novel tasks to investigate how participants who had received voluntary (Gratitude group) or involuntary help (Control group) punished their benefactors' unfairness with functional magnetic resonance imaging (fMRI). The Gratitude group punished their benefactors less than the Control group. The self-report and computational modelling results demonstrated a crucial role of the boosted protection tendency on behalf of benefactors in the gratitude-induced injustice. The fMRI results showed that activities in the regions associated with mentalizing (temporoparietal junction) and reward processing (ventral medial prefrontal cortex) differed between the groups and were related to the gratitude-induced injustice. They suggest that grateful individuals concern for benefactors' benefits, value chances to interact with benefactors, and refrain from action that perturbs relationship-building (i.e., exert less punishment on benefactors' unfairness), which reveal a dark side of gratitude and enrich the gratitude theory (i.e., the find-bind-remind theory). Our findings provide psychological, computational, and neural accounts of the gratitude-induced behaviour and further the understanding of the nature of gratitude.

Prediction of trust propensity from intrinsic brain morphology and functional connectome.

Trust forms the basis of virtually all interpersonal relationships. Although significant individual differences characterize trust, the driving neuropsychological signatures behind its heterogeneity remain obscure. Here, we applied a prediction framework in two independent samples of healthy participants to examine the relationship between trust propensity and multimodal brain measures. Our multivariate prediction analyses revealed that trust propensity was predicted by gray matter volume and node strength across multiple regions. The gray matter volume of identified regions further enabled the classification of individuals from an independent sample with the propensity to trust or distrust. Our modular and functional decoding analyses showed that the contributing regions were part of three large-scale networks implicated in calculus-based trust strategy, cost-benefit calculation, and trustworthiness inference. These findings do not only deepen our neuropsychological understanding of individual differences in trust propensity, but also provide potential biomarkers in predicting trust impairment in neuropsychiatric disorders.

Intranasal vasopressin expedites dishonesty in women.

As an integral ingredient of human sociality, dishonesty can be both egocentric and altruistic, as well as gradually escalate. Here, we examined the influence of arginine vasopressin (AVP), a neuropeptide associated with human prosocial behaviors, on dishonest behaviors in men and women. In this double-blind and placebo-controlled study, 101 participants were randomized to administration of either 20 IU intranasal AVP or placebo. We used a two-party task to manipulate the incentive structure of dishonesty in the way of self-/other-serving repeatedly. For lies that benefit both themselves and others, women receiving intranasal AVP lied more than women receiving intranasal placebo and men receiving intranasal AVP. The dishonest behavior of women treated with AVP gradually escalated with repetition over time. These results suggest that AVP selectively regulates the escalation of dishonesty in women, contingent on the motivation of dishonesty. Our findings provide insight into gender-specific modulations of AVP on human dishonest behavior.

The Dynamics of Belief Updating in Human Cooperation: Findings from inter-brain ERP hyperscanning.

Generally, successful cooperation can only be established when the interacting persons believe that they would not be betrayed; this belief can be updated by observing the other persons' actual choices. Thus, the process of belief updating plays an important role in conditional cooperation. Using the Prisoner's Dilemma Game (PDG) with event-related potential (ERP) hyperscanning, this study investigated the dynamics of belief updating in a dyad. During the task, participants were asked if they believed that their opponent would cooperate in the next trial, and their answers functioned as a self-reported index of reciprocal belief. The results suggested that this index shows strong associations with participants' behavioral choices (cooperate/betray). At the individual level, the amplitudes of the ERP components frontal P3a and parietal P3b elicited by the decision outcome were sensitive to belief updating. At the interpersonal level, the between-subject synchronization in P3b was higher than those in the other conditions when the paired participants confirmed each other's reciprocal beliefs. Since previous studies have linked the P3b with memory updating, we suggest that a cooperative relationship is built up when the memory systems (which support belief updating) of two interacting persons reach a high level of coordination. These findings may help explain how conditional cooperation develops between strangers.

Differentiating guilt and shame in an interpersonal context with univariate activation and multivariate pattern analyses.

Guilt and shame are usually evoked during interpersonal interactions. However, no study has compared guilt and shame processing under such circumstances. In the present study, we investigated guilt and shame in an interpersonal context using functional magnetic resonance imaging (fMRI). Behaviorally, participants reported more "guilt" when their wrong advice caused a confederate's economic loss, whereas they reported more "shame" when their wrong advice were correctly refused by the confederate. The fMRI results showed that both guilt and shame activated regions related to the integration of theory of mind and self-referential information (dorsal medial prefrontal cortex, dmPFC) and to the emotional processing (anterior insula). Guilt relative to shame activated regions linked with theory of mind (supramarginal gyrus and temporo-parietal junction) and cognitive control (orbitofrontal cortex/ventrolateral prefrontal cortex and dorsolateral prefrontal cortex). Shame relative to guilt revealed no significant results. Using multivariate pattern analysis, we demonstrated that in addition to the regions found in the univariate activation analysis, the ventral anterior cingulate cortex and dmPFC could also distinguish guilt and shame. These results do not only echo previous studies of guilt and shame using recall and imagination paradigms but also provide new insights into the psychological and neural mechanisms of guilt and shame.

Connectome-based model predicts individual differences in propensity to trust.

Trust constitutes a fundamental basis of human society and plays a pivotal role in almost every aspect of human relationships. Although enormous interest exists in determining the neuropsychological underpinnings of a person's propensity to trust utilizing task-based fMRI; however, little progress has been made in predicting its variations by task-free fMRI based on whole-brain resting-state functional connectivity (RSFC). Here, we combined a one-shot trust game with a connectome-based predictive modeling approach to predict propensity to trust from whole-brain RSFC. We demonstrated that individual variations in the propensity to trust were primarily predicted by RSFC rooted in the functional integration of distributed key nodes-caudate, amygdala, lateral prefrontal cortex, temporal-parietal junction, and the temporal pole-which are part of domain-general large-scale networks essential for the motivational, affective, and cognitive aspects of trust. We showed, further, that the identified brain-behavior associations were only evident for trust but not altruistic preferences and that propensity to trust (and its underlying neural underpinnings) were modulated according to the extent to which a person emphasizes general social preferences (i.e., horizontal collectivism) rather than general risk preferences (i.e., trait impulsiveness). In conclusion, the employed data-driven approach enables to predict propensity to trust from RSFC and highlights its potential use as an objective neuromarker of trust impairment in mental disorders.

Individualized prediction of dispositional worry using white matter connectivity.

BACKGROUND: Excessive worry is a defining feature of generalized anxiety disorder and is present in a wide range of other psychiatric conditions. Therefore, individualized predictions of worry propensity could be highly relevant in clinical practice, with respect to the assessment of worry symptom severity at the individual level. METHODS: We applied a multivariate machine learning approach to predict dispositional worry based on microstructural integrity of white matter (WM) tracts. RESULTS: We demonstrated that the machine learning model was able to decode individual dispositional worry scores from microstructural properties in widely distributed WM tracts (mean absolute error = 10.46, p < 0.001; root mean squared error = 12.82, p < 0.001; prediction R2 = 0.17, p < 0.001). WM tracts that contributed to worry prediction included the posterior limb of internal capsule, anterior corona radiate, and cerebral peduncle, as well as the corticolimbic pathways (e.g. uncinate fasciculus, cingulum, and fornix) already known to be critical for emotion processing and regulation. CONCLUSIONS: The current work thus elucidates potential neuromarkers for clinical assessment of worry symptoms across a wide range of psychiatric disorders. In addition, the identification of widely distributed pathways underlying worry propensity serves to better improve the understanding of the neurobiological mechanisms associated with worry.

Gender-specific effects of vasopressin on human social communication: An ERP study.

The quick and efficient perception of facial expressions represents a special and fundamental capacity of humans to engage in social communication. Here, we examined the effects of vasopressin (AVP, a neuropeptide) on the processing of same- and other-gender facial expressions among males and females. After receiving either AVP or placebo (PBO) intranasally in a randomized and double-blind manner, participants were asked to rate their approachability to facial expressions while event-related potentials (ERPs) were recorded. Males rated lower approachability scores to neutral and positive male faces relative to the scores to emotion-matched female faces after AVP but not following PBO administration. These behavioral effects were correlated with the AVP-induced increased P1 and decreased N170 responses to male faces among male participants. Females rated higher approachability scores to negative female faces than the scores to negative male faces after AVP but not following PBO treatment. These results suggest that AVP decreases friendly responses to neutral/positive male faces in males and increases friendly responses to negative female faces in females. Overall, these results demonstrate the gender-specific effects of AVP in response to same- and other-gender facial expressions, indicating there are sex- and context-dependent effects of AVP on socioemotional processes.

Neural representations of the multidimensional self in the cortical midline structures.

Self-concept consists of self-identity that distinguishes self from other people and knowledge that describes one's own attributes in different dimensions. Because self-concept plays a fundamental role in individuals' social functioning and mental health, behavioral studies have examined cognitive processes of self-identity and self-knowledge extensively. Nevertheless, how different dimensions of the self-concept are organized in multi-voxel neural patterns remains elusive. Here, we address this issue by employing representational similarity analyses of behavioral/theoretical models of multidimensional self-representation and blood oxygen level dependent responses, recorded using functional MRI, to judgments of personality traits, physical attributes and social roles of oneself, a close (one's mother) other, and a distant (celebrity) other. The multivoxel patterns of neural activities in the medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC) distinguished representations of the self from both close and distant others, suggesting a specific neural representation of the self-identity; and distinguished different dimensions of person knowledge of oneself, indicating dimension-sensitive neural representation of the self. Moreover, the pattern of PCC activity is more strongly coupled with dimensions of self-knowledge than self-identity. Our findings suggest that multivoxel neural patterns of the cortical midline structures distinguish not only self from others but also discriminate different dimensions of the self.

Neural substrates of the emotion-word and emotional counting Stroop tasks in healthy and clinical populations: A meta-analysis of functional brain imaging studies.

The emotional Stroop task (EST) is among the most influential paradigms used to probe attention-related or cognitive control-related emotional processing in healthy subjects and clinical populations. The neuropsychological mechanism underlying the emotional Stroop effect has attracted extensive and long-lasting attention in both cognitive and clinical psychology and neuroscience; however, a precise characterization of the neural substrates underlying the EST in healthy and clinical populations remains elusive. Here, we implemented a coordinate-based meta-analysis covering functional imaging studies that employed the emotion-word or emotional counting Stroop paradigms to determine the underlying neural networks in healthy subjects and the trans-diagnostic alterations across clinical populations. Forty-six publications were identified that reported relevant contrasts (negative > neutral; positive > neutral) for healthy or clinical populations as well as for hyper- or hypo-activation of patients compared to controls. We demonstrate consistent involvement of the vlPFC and dmPFC in healthy subjects and consistent involvement of the vlPFC in patients. We further identify a trans-diagnostic pattern of hyper-activation in the prefrontal and parietal regions. These findings underscore the critical roles of cognitive control processes in the EST and implicate trans-diagnostic cognitive control deficits. Unlike the current models that emphasize the roles of the amygdala and rACC, our findings implicate novel mechanisms underlying the EST for both healthy and clinical populations.