Neurocomputational mechanisms underlying fear-biased adaptation learning in changing environments.

Humans are able to adapt to the fast-changing world by estimating statistical regularities of the environment. Although fear can profoundly impact adaptive behaviors, the computational and neural mechanisms underlying this phenomenon remain elusive. Here, we conducted a behavioral experiment (n = 21) and a functional magnetic resonance imaging experiment (n = 37) with a novel cue-biased adaptation learning task, during which we simultaneously manipulated emotional valence (fearful/neutral expressions of the cue) and environmental volatility (frequent/infrequent reversals of reward probabilities). Across 2 experiments, computational modeling consistently revealed a higher learning rate for the environment with frequent versus infrequent reversals following neutral cues. In contrast, this flexible adjustment was absent in the environment with fearful cues, suggesting a suppressive role of fear in adaptation to environmental volatility. This suppressive effect was underpinned by activity of the ventral striatum, hippocampus, and dorsal anterior cingulate cortex (dACC) as well as increased functional connectivity between the dACC and temporal-parietal junction (TPJ) for fear with environmental volatility. Dynamic causal modeling identified that the driving effect was located in the TPJ and was associated with dACC activation, suggesting that the suppression of fear on adaptive behaviors occurs at the early stage of bottom-up processing. These findings provide a neuro-computational account of how fear interferes with adaptation to volatility during dynamic environments.

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.

Oscillatory mechanisms of intrinsic human brain networks.

Non-invasive neuroimaging has revealed specific network-based resting-state dynamics in the human brain, yet the underlying neurophysiological mechanism remains unclear. We employed intracranial electroencephalography to characterize local field potentials within the default mode network (DMN), frontoparietal network (FPN), and salience network (SN) in 42 participants. We identified stronger within-network phase coherence at low frequencies (θ and α band) within the DMN, and at high frequencies (γ band) within the FPN. Hidden Markov modeling indicated that the DMN exhibited preferential low frequency phase coupling. Phase-amplitude coupling (PAC) analysis revealed that the low-frequency phase in the DMN modulated the high-frequency amplitude envelopes of the FPN, suggesting frequency-dependent characterizations of intrinsic brain networks at rest. These findings provide intracranial electrophysiological evidence in support of the network model for intrinsic organization of human brain and shed light on the way brain networks communicate at rest.

Molecular basis underlying default mode network functional abnormalities in postpartum depression with and without anxiety.

Although Postpartum depression (PPD) and PPD with anxiety (PPD-A) have been well characterized as functional disruptions within or between multiple brain systems, however, how to quantitatively delineate brain functional system irregularity and the molecular basis of functional abnormalities in PPD and PPD-A remains unclear. Here, brain sample entropy (SampEn), resting-state functional connectivity (RSFC), transcriptomic and neurotransmitter density data were used to investigate brain functional system irregularity, functional connectivity abnormalities and associated molecular basis for PPD and PPD-A. PPD-A exhibited higher SampEn in medial prefrontal cortex (MPFC) and posterior cingulate cortex (PPC) than healthy postnatal women (HPW) and PPD while PPD showed lower SampEn in PPC compared to HPW and PPD-A. The functional connectivity analysis with MPFC and PPC as seed areas revealed decreased functional couplings between PCC and paracentral lobule and between MPFC and angular gyrus in PPD compared to both PPD-A and HPW. Moreover, abnormal SampEn and functional connectivity were associated with estrogenic level and clinical symptoms load. Importantly, spatial association analyses between functional changes and transcriptome and neurotransmitter density maps revealed that these functional changes were primarily associated with synaptic signaling, neuron projection, neurotransmitter level regulation, amino acid metabolism, cyclic adenosine monophosphate (cAMP) signaling pathways, and neurotransmitters of 5-hydroxytryptamine (5-HT), norepinephrine, glutamate, dopamine and so on. These results reveal abnormal brain entropy and functional connectivities primarily in default mode network (DMN) and link these changes to transcriptome and neurotransmitters to establish the molecular basis for PPD and PPD-A for the first time. Our findings highlight the important role of DMN in neuropathology of PPD and PPD-A.

Connectome-based individualized prediction of reciprocity propensity and sensitivity to framing: a resting-state functional magnetic resonance imaging study.

BACKGROUND: The social representation theory states that individual differences in reciprocity decisions are composed of a stable central core (i.e., reciprocity propensity, RP) and a contextual-dependent periphery (i.e., sensitivity to the framing effect; SFE, the effect by how the decision is presented). However, the neural underpinnings that explain RP and SFE are still unknown. METHOD: Here, we employed prediction and lesion models to decode resting-state functional connectivity (RSFC) of RP and SFE for reciprocity decisions of healthy volunteers who underwent RS functional magnetic resonance imaging and completed one-shot trust (give frame) and distrust (take frame) games as trustees. RESULTS: Regarding the central core, reciprocity rates were positively associated between the give and take frame. Neuroimaging results showed that inter-network RSFC between the default-mode network (DMN; associated with mentalizing) and cingulo-opercular network (associated with cognitive control) contributed to the prediction of reciprocity under both frames. Regarding the periphery, behavioral results demonstrated a significant framing effect-people reciprocated more in the give than in the take frame. Our neuroimaging results revealed that intra-network RSFC of DMN (associated with mentalizing) contributed dominantly to the prediction of SFE. CONCLUSION: Our findings provide evidence for distinct neural mechanisms of RP and SFE in reciprocity decisions.

Role of the amygdala in disrupted integration and effective connectivity of cortico-subcortical networks in apathy.

BACKGROUND: Apathy is a quantitative reduction in motivation and goal-directed behaviors, not only observed in neuropsychiatric disorders, but also present in healthy populations. Although brain abnormalities associated with apathy in clinical disorders have been studied, the organization of brain networks in healthy individuals has yet to be identified. METHOD: We examined properties of intrinsic brain networks in healthy individuals with varied levels of apathy. By using functional magnetic resonance imaging in combination with graph theory analysis and dynamic causal modeling analysis, we tested communications among nodes and modules as well as effective connectivity among brain networks. RESULTS: We found that the average participation coefficient of the subcortical network, especially the amygdala, was lower in individuals with high than low apathy. Importantly, we observed weaker effective connectivity fromthe hippocampus and parahippocampal gyrus to the amygdala, and from the amygdala to the parahippocampal gyrus and medial frontal cortex in individuals with apathy. CONCLUSION: These findings suggest that individuals with high apathy exhibit aberrant communication within the cortical-to-subcortical network, characterized by differences in amygdala-related effective connectivity. Our work sheds light on the neural basis of apathy in subclinical populations and may have implications for understanding the development of clinical conditions that feature apathy.

Midfrontal theta phase underlies evidence accumulation and response thresholding in cognitive control.

Cognitive control involves evidence accumulation and response thresholding, but the neural underpinnings of these 2 processes are poorly understood. Based on recent findings that midfrontal theta phase coordinates the correlation between theta power and reaction time during cognitive control, this study investigated whether and how theta phase would modulate the relationships between theta power and evidence accumulation and response thresholding in human participants when they performed a flanker task. Our results confirmed the modulation of theta phase on the correlations between ongoing midfrontal theta power and reaction time under both conditions. Using hierarchical drift-diffusion regression modeling, we found that in both conditions, theta power was positively associated with boundary separation in phase bins with optimal power-reaction time correlations, whereas the power-boundary correlation decreased to nonsignificance in phase bins with reduced power-reaction time correlations. In contrast, the power-drift rate correlation was not modulated by theta phase, but by cognitive conflict. Drift rate was positively correlated with theta power for the bottom-up processing in the non-conflict condition, whereas it was negatively correlated with theta power for the top-down control to address conflict. These findings suggest that evidence accumulation is likely to be a phase-coordinated continuous process, whereas thresholding may be a phase-specific transient process.

Altered functional coupling between the cerebellum and cerebrum in patients with amnestic mild cognitive impairment.

Cognitive processing relies on the functional coupling between the cerebrum and cerebellum. However, it remains unclear how the 2 collaborate in amnestic mild cognitive impairment (aMCI) patients. With functional magnetic resonance imaging techniques, we compared cerebrocerebellar functional connectivity during the resting state (rsFC) between the aMCI and healthy control (HC) groups. Additionally, we distinguished coupling between functionally corresponding and noncorresponding areas across the cerebrum and cerebellum. The results demonstrated decreased rsFC between both functionally corresponding and noncorresponding areas, suggesting distributed deficits of cerebrocerebellar connections in aMCI patients. Increased rsFC was also observed, which were between functionally noncorresponding areas. Moreover, the increased rsFC was positively correlated with attentional scores in the aMCI group, and this effect was absent in the HC group, supporting that there exists a compensatory mechanism in patients. The current study contributes to illustrating how the cerebellum adjusts its coupling with the cerebrum in individuals with cognitive impairment.

Threat-induced anxiety and selfishness in resource sharing: Behavioral and neural evidence.

In real life, it is not unusual that we face potential threats (i.e., physical stimuli and environments that may cause harm or danger) with other individuals together, yet it remains largely unknown how threat-induced anxious feelings influence prosocial behaviors such as resource sharing. In this study, we investigated this question by combining functional magnetic resonance imaging and a novel paradigm. Together with an anonymous partner, each participant faced the possibility of receiving a 10-s noise administration, which had a low or high probability to be a threat (i.e., the intensity of noise can induce a high level of unpleasantness). Each participant first reported her/his immediate feeling of anxiety about the current situation (being threatened by the unpleasant noise), then decided how to split a number of resources (which could relieve the noise) between her/him and the partner. Behavioral results revealed that the participants showed a selfish bias in the threat conditions than in the safe conditions, and that self-reported anxiety feeling significantly predicted this bias. Functional magnetic resonance imaging results revealed that: (1) the activation level of the anterior insula was correlated with self-reported anxiety and (2) the connectivity between the anterior insula and the temporoparietal junction was sensitive to the modulating effect of anxiety on the selfish bias. These findings indicate the neural correlates of the association between threat-induced anxiety and prosocial tendencies in social interactions.

Gene transcriptional expression of cortical thinning during childhood and adolescence.

The cognitive and behavioral development of children and adolescents is closely related to the maturation of brain morphology. Although the trajectory of brain development has been depicted in detail, the underlying biological mechanism of normal cortical morphological development in childhood and adolescence remains unclear. By combining the Allen Human Brain Atlas dataset with two single-site magnetic resonance imaging data including 427 and 733 subjects from China and the United States, respectively, we performed partial least squares regression and enrichment analysis to explore the relationship between the gene transcriptional expression and the development of cortical thickness in childhood and adolescence. We found that the spatial model of normal cortical thinning during childhood and adolescence is associated with genes expressed predominantly in astrocytes, microglia, excitatory and inhibitory neurons. Top cortical development-related genes are enriched for energy-related and DNA-related terms and are associated with psychological and cognitive disorders. Interestingly, there is a great deal of similarity between the findings derived from the two single-site datasets. This fills the gap between early cortical development and transcriptomes, which promotes an integrative understanding of the potential biological neural mechanisms.

How resource sharing resists scarcity: the role of cognitive empathy and its neurobiological mechanisms.

Resource scarcity challenges individuals' willingness to share limited resources with other people. Still, lots of field studies and laboratory experiments have shown that sharing behaviors do not disappear under scarcity. Rather, some individuals are willing to share their scarce resources with others in a similar way as when the resource is abundant, which is crucial for the maintenance and development of human society. Here, we designed a novel paradigm in which subjects decided whether (and how much) to share an amount of "relieving resources" for counteracting unpleasant noises, which mimics real-life situations that people cost their own resources to help others escape from adversity. Overall, the robustness of resource sharing under scarcity was positively correlated with individual level of the cognitive component of empathy across two independent experiments. Resource insufficiency modulated the activations of several brain regions (including the TPJ, mPFC, and PCC) as well as the functional connection (from the rTPJ to the mPFC) within the mentalizing brain network, but the modulatory effect decreased as a function of cognitive empathy. We also applied the administration of oxytocin and found significant effects on sharing behavior among individuals with a higher level of cognitive empathy, but not their low-level counterparts. These findings highlight the importance of empathy to resource sharing under scarcity and explain the underlying neurobiological mechanisms.

Long-Term Stress and Trait Anxiety Affect Brain Network Balance in Dynamic Cognitive Computations.

Long-term stress has a profound impact on executive functions. Trait anxiety is recognized as a vulnerable factor accounting for stress-induced adaptive or maladaptive effects. However, the neurocognitive mechanisms underlying long-term stress and trait anxiety interactions remain elusive. Here we investigated how long-term stress and trait anxiety interact to affect dynamic decisions during n-back task performance by altering functional brain network balance. In comparison to controls, participants under long-term stress experienced higher psychological distress and exhibited faster evidence accumulation but had a lower decision-threshold when performing n-back tasks in general. This corresponded with hyper-activation in the anterior insula, less deactivation in the default-mode network, and stronger default-mode network decoupling with the frontoparietal network. Critically, high trait anxiety under long-term stress led to slower evidence accumulation through higher frontoparietal activity during cognitively demanding task, and increased decoupling between the default-mode and frontoparietal networks. Our findings suggest a neurocognitive model of how long-term stress and trait anxiety interplay to affect latent dynamic computations in executive functioning with adaptive and maladaptive changes, and inform personalized assessments and preventions for stress vulnerability.

Neural dynamics and coupling underlying uncertain anticipatory conflicts in anxious individuals.

Anticipation plays an important role in cognitive control and related psychiatric disorders such as anxiety. However, anticipation processing of conflicts in anxious individuals and the underlying brain mechanisms remain unknown. Using a newly designed cue-flanker task, we observed faster responses to congruent flankers with certain cues in individuals with high trait anxiety (HTA) than those with low trait anxiety (LTA). Microstate analyses revealed less occurrence of cue-evoked microstates in HTA than LTA. Importantly, the less occurrence of specific state was correlated to the larger flanker effect in HTA, suggesting that deficient conflict control in anxiety is associated with abnormal vigilance-related dynamic processing during anticipation. Delta-beta coupling at anticipation stage mediated the association between the level of anxiety and reaction time in conflict processing with uncertain cues in HTA, suggesting the mediatory role of delta-beta coupling in anticipatory conflict processing of anxious individuals. These results suggest hyperactive anticipatory processing of goal-relevant information for the upcoming conflict in anxious individuals. Our findings provide neurocognitive evidence for altered anticipatory cognitive control in anxious individuals and have important implications for diagnosis and treatment of anxiety-related disorders.

Functional mapping and cooperation between the cerebellum and cerebrum during word reading.

Multiple areas in the cerebellum have been reported to be engaged in reading. However, how these regions cooperate with the reading-related areas in the cerebrum remains unclear. Here, brain images of fifty-two adults were acquired via functional magnetic resonance imaging. By comparing the cerebellar activation across three localization tasks targeting orthographic, phonological, and semantic processing, we first identified three different reading-related areas in the cerebellum, biased toward orthography, phonology, and semantics, respectively. Then, functional connectivity (FC) analyses demonstrated that the mean FC between functionally corresponding areas across the cerebrum and cerebellum was greater than that between noncorresponding areas during silent word reading. FC patterns of functionally corresponding areas could significantly predict reading speed, with the FC driven from orthographic and semantic areas contributing the most. Effective FC analyses further showed that orthographic and semantic areas in the cerebellum had selective and direct connectivity to areas in the cerebrum with similar functional specificity. These results suggest that reading-related areas vary in their functions to reading, and cooperation between areas with corresponding functions was greater than that between noncorresponding areas. These findings emphasize the importance of functional cooperation between the cerebrum and cerebellum during reading from a new perspective.

Emotional autobiographical memory retrieval in time domain.

Autobiographical memory (AM) is an important psychological phenomenon that has significance for self-development and mental health. The psychological mechanisms of emotional AM retrieval and their association with individual emotional symptoms remain largely unclear in the literature. For this purpose, the current study provided cue words to elicit emotional AMs. Event-related potentials (ERPs) associated with the retrieval process of AMs were recorded and analyzed. We found that the ERP component N400 was sensitive to both emotional valence and retrieval state, such that its amplitude was larger for negative compared to positive AMs, and larger responses for unrecalled compared to recalled AMs. Further, the N400 amplitude in the positive recalled condition was correlated with individual difference in depression (measured by the Beck Depression Inventory). Another ERP component, the late positive potential (LPP), was also sensitive to emotional valence, such that its amplitude was larger (i.e., more positive-going) for positive compared to negative cues. No significant effect was observed on the early ERP components P1, N1, or P2. The current findings bring new understanding on the difference between positive and negative AMs retrieval in the time domain. Also, the importance of this difference to the individual level of depression is worth noting.

Prefrontal control of social influence in risk decision making.

To optimize our decisions, we may change our mind by utilizing social information. Here, we examined how changes of mind were modulated by Social Misalignment Sensitivity (SMS), egocentric tendency, and decision preferences in a decision-making paradigm including both risk and social information. Combining functional magnetic resonance imaging with computational modeling, we showed that both SMS and egocentric tendency modulated changes of mind under the influence of social information. While SMS was represented in the dorsal anterior cingulate cortex (dACC) and superior parietal gyrus (SPG) in the socially aligned situation, a distributed brain network was activated in the misaligned condition, including not only the dACC and SPG but also superior frontal gyrus and precuneus. These results suggest that SMS is related to a monitoring brain system, the scope of which varies according to the level of misalignment with social majority. The dorsolateral prefrontal cortex selectively interacted with SMS among the participants with a low switching threshold, indicating that its regulation on SMS may be sensitive to inter-individual variation. Our findings highlight the predominant roles of SMS and the prefrontal control system towards changes of mind under social influence.

Resting-state functional connectivity of social brain regions predicts motivated dishonesty.

Motivated dishonesty is a typical social behavior varying from person to person. Resting-state fMRI (rsfMRI) is capable of identifying unique patterns from functional connectivity (FC) between brain regions. Recent work has built a link between brain networks in resting state to dishonesty in Western participants. To determine and reproduce the relevant neural patterns and build an interpretable model to predict dishonesty, we analyzed two conceptually similar datasets containing rsfMRI data with different dishonesty tasks. Both tasks implemented the information-passing paradigm, in which monetary rewards were employed to induce dishonesty. We applied connectome-based predictive modeling (CPM) to build a model among FC within and between four social brain networks (reward, self-referential, moral, and cognitive control). The CPM analysis indicated that FCs of social brain networks are predictive of dishonesty rate, especially FCs within reward network, and between self-referential and cognitive control networks. Our study offers an conceptual replication with integrated model to predict dishonesty with rsfMRI, and the results suggest that frequent motivated dishonest decisions may require the higher engagement of social brain regions.

Individualized prediction of consummatory anhedonia from functional connectome in major depressive disorder.

BACKGROUND: Anhedonia is a key symptom of major depressive disorder (MDD) and other psychiatric diseases. The neural basis of anhedonia has been widely examined, yet the interindividual variability in neuroimaging biomarkers underlying individual-specific symptom severity is not well understood. METHODS: To establish an individualized prediction model of anhedonia, we applied connectome-based predictive modeling (CPM) to whole-brain resting-state functional connectivity profiles of MDD patients. RESULTS: The CPM can successfully and reliably predict individual consummatory but not anticipatory anhedonia. The predictive model mainly included salience network (SN), frontoparietal network (FPN), default mode network (DMN), and motor network. Importantly, subsequent computational lesion prediction and consummatory-specific model prediction revealed that connectivity of the SN with DMN and FPN is essential and specific for the prediction of consummatory anhedonia. CONCLUSIONS: This study shows that brain functional connectivity, especially the connectivity of SN-FPN and SN-DMN, can specifically predict individualized consummatory anhedonia in MDD. These findings suggest the potential of functional connectomes for the diagnosis and prognosis of anhedonia in MDD and other disorders.

Moral Conflict in Economic Decision Making: The Role of the Anterior Cingulate Cortex-Striatum Pathway.

The present study combined a novel hypothetical investment game with functional magnetic resonance imaging to examine how moral conflict biases our real decision preference when it is not obvious or explicitly presented. Investment projects were chosen based on their prior subjective morality ratings to fit into 2 categories: a high level of moral conflict (HMC) or a low level of moral conflict (LMC). Participants were instructed to invest high or low amounts of capital into different projects. Behavioral and neural responses during decision making were recorded and compared. Behaviorally, we observed a significant decision bias such that investments were lower for HMC projects than for LMC projects. At the neural level, we found that moral conflict-related activity in the anterior cingulate cortex (ACC) was higher in the HMC condition than in the LMC condition and that reward-related activity in bilateral striatum was lower. Dynamic causal modeling further suggested that the moral conflict detected in the ACC influenced final decisions by modulating the representation of subjective value through the ACC's connection to the reward system.

Connectome-Based Predictive Modeling of Individual Anxiety.

Anxiety-related illnesses are highly prevalent in human society. Being able to identify neurobiological markers signaling high trait anxiety could aid the assessment of individuals with high risk for mental illness. Here, we applied connectome-based predictive modeling (CPM) to whole-brain resting-state functional connectivity (rsFC) data to predict the degree of trait anxiety in 76 healthy participants. Using a computational "lesion" approach in CPM, we then examined the weights of the identified main brain areas as well as their connectivity. Results showed that the CPM successfully predicted individual anxiety based on whole-brain rsFC, especially the rsFC between limbic areas and prefrontal cortex. The prediction power of the model significantly decreased from simulated lesions of limbic areas, lesions of the connectivity within limbic areas, and lesions of the connectivity between limbic areas and prefrontal cortex. Importantly, this neural model generalized to an independent large sample (n = 501). These findings highlight important roles of the limbic system and prefrontal cortex in anxiety prediction. Our work provides evidence for the usefulness of connectome-based modeling in predicting individual personality differences and indicates its potential for identifying personality factors at risk for psychopathology.