I was trained in cognitive neuroscience and computer science. My current research interests involve using multimodal neuroimaging and advanced computational methods to characterize brain network organization underlying affective and cognitive processing in children with and without neurodevelopmental disorders.
Honors & Awards
Sammy Kuo Award (Paper of the Year), Stanford Neurosciences Institute, Stanford University School of Medicine (2019)
Graduated with distinction, Beijing, China (2015)
Graduated with distinction, Peking University (2015)
The Fifty-Four Scholarship, Peking University (2012-2013)
Excellent Study Award, Peking University (2011-2012)
Scholarship for Studying Abroad, the Chinese Scholarship Council (2011-2012)
Third Prize, The ACM Programming Contest, Peking University (2011)
Second Prize, The ACM Programming Contest, Peking University (2010)
The Fifty-Four Scholarship, Peking University (2009-2010)
Graduated with Distinction, Beijing University with Technology (2008)
Bronze Medal, The Asia ACM Programming Contest, Xian Site (2006)
Honorable Mention, The Asia ACM Programming Contest, Beijing Site (2006)
Bachelor of Engineering, Beijing University of Technology (2008)
Doctor of Philosophy, Peking University (2015)
Anxiety and Stress Alter Decision-Making Dynamics and Causal Amygdala-Dorsolateral Prefrontal Cortex Circuits During Emotion Regulation in Children.
Anxiety and stress reactivity are risk factors for the development of affective disorders. However, the behavioral and neurocircuit mechanisms that potentiate maladaptive emotion regulation are poorly understood. Neuroimaging studies have implicated the amygdala and dorsolateral prefrontal cortex (DLPFC) in emotion regulation, but how anxiety and stress alter their context-specific causal circuit interactions is not known. Here, we use computational modeling to inform affective pathophysiology, etiology, and neurocircuit targets for early intervention.Forty-five children (10-11 years of age; 25 boys) reappraised aversive stimuli during functional magnetic resonance imaging scanning. Clinical measures of anxiety and stress were acquired for each child. Drift-diffusion modeling of behavioral data and causal circuit analysis of functional magnetic resonance imaging data, with a National Institute of Mental Health Research Domain Criteria approach, were used to characterize latent behavioral and neurocircuit decision-making dynamics driving emotion regulation.Children successfully reappraised negative responses to aversive stimuli. Drift-diffusion modeling revealed that emotion regulation was characterized by increased initial bias toward positive reactivity during viewing of aversive stimuli and increased drift rate, which captured evidence accumulation during emotion evaluation. Crucially, anxiety and stress reactivity impaired latent behavioral dynamics associated with reappraisal and decision making. Anxiety and stress increased dynamic casual influences from the right amygdala to DLPFC. In contrast, DLPFC, but not amygdala, reactivity was correlated with evidence accumulation and decision making during emotion reappraisal.Our findings provide new insights into how anxiety and stress in children impact decision making and amygdala-DLPFC signaling during emotion regulation, and uncover latent behavioral and neurocircuit mechanisms of early risk for psychopathology.
View details for DOI 10.1016/j.biopsych.2020.02.011
View details for PubMedID 32331823
Development of human emotion circuits investigated using a Big-Data analytic approach: Stability, reliability, and robustness.
The Journal of neuroscience : the official journal of the Society for Neuroscience
Emotion perception is fundamental to affective and cognitive development and is thought to involve distributed brain circuits. Efforts to chart neurodevelopmental changes in emotion have been severely hampered by narrowly focused approaches centered on activation of individual brain regions and small sample sizes. Here we investigate the maturation of human functional brain circuits associated with identification of fear, anger, sadness, happiness, and neutral faces using a large sample of 759 children, adolescents, and adults (ages 8-23; female/male = 419/340). Network analysis of emotion-related brain circuits revealed three functional modules, encompassing lateral frontoparietal, medial prefrontal-posterior cingulate, and subcortical-posterior insular cortices, with hubs in medial prefrontal, but not posterior cingulate, cortex. This overall network architecture was stable by age eight, and it anchored maturation of circuits important for salience detection and cognitive control, as well as dissociable circuit patterns across distinct emotion categories. Our findings point to similarities and differences in functional circuits associated with identification of fearful, angry, sad, happy, and neutral faces, and reveal aspects of brain circuit organization underlying emotion perception that are stable over development as well as features that change with age. Reliability analyses demonstrated the robustness of our findings and highlighted the importance of large samples for probing functional brain circuit development. Our study emphasizes a need to focus beyond amygdala circuits and provides a robust neurodevelopmental template for investigating emotion perception and identification in psychopathology.SIGNIFICANCE STATEMENTEmotion perception is fundamental to cognitive and affective development. However, efforts to chart neurodevelopmental changes in emotion perception have been hampered by narrowly focused approaches centered on the amygdala and prefrontal cortex and small sample sizes. Using a large sample of 759 children, adolescents, and adults and a multipronged analytical strategy, we investigated the development of brain network organization underlying identification and categorization of fearful, happy, angry, sad, and neutral facial expressions. Results revealed a developmentally-stable modular architecture that anchored robust age-related and emotion category-related changes in brain connectivity across multiple brain systems that extend far beyond amygdala circuits and provide a new template for investigation of emotion processing in the developing brain.
View details for DOI 10.1523/JNEUROSCI.0220-19.2019
View details for PubMedID 31332001
Mental workload drives different reorganizations of functional cortical connectivity between 2D and 3D simulated flight experiments.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Despite the apparent usefulness of efficient mental workload assessment in various real-world situations, the underlying neural mechanism remains largely unknown and studies of mental workload are limited to well-controlled cognitive tasks using 2D computer screen. In this work, we investigated functional brain network alterations in a simulated flight experiment with three mental workload levels and compared the reorganization pattern between computer screen (2D) and virtual reality (3D) interfaces. We constructed multiband functional networks in EEG source space, which were further assessed in terms of network efficiency and workload classification performances. We found that increased alpha band efficiencies and beta band local efficiency were associated with elevated mental workload levels, while beta band global efficiency exhibited distinct development trends between 2D and 3D interfaces. Furthermore, using a small subset of connectivity features, we achieved a satisfactory multilevel workload classification accuracy in both interfaces (82% for both 2D and 3D). Further inspection of these discriminative connectivity subsets, we found predominant alpha band connectivity features followed by beta and theta band features with different topological patterns between 2D and 3D interfaces. These findings allow for a more comprehensive interpretation of the neural mechanisms of mental workload in relation to realworld assessment.
View details for DOI 10.1109/TNSRE.2019.2930082
View details for PubMedID 31329123
Dynamic Temporal Inflexibility of the Frontoparietal Network Predicts Depression Severity and Treatment Response in Internalizing Psychopathologies
ELSEVIER SCIENCE INC. 2018: S196–S197
View details for Web of Science ID 000432466300491
Altered intra- and inter-hemispheric functional dysconnectivity in schizophrenia.
Brain imaging and behavior
Despite convergent evidence suggesting that schizophrenia is a disorder of brain dysconnectivity, it remains unclear whether intra- or inter-hemispheric deficits or their combination underlie the dysconnection. This study examined the source of the functional dysconnection in schizophrenia. Resting-state fMRI was performed in 66 patients with schizophrenia and 73 matched healthy controls. Functional brain networks were constructed for each participant and further partitioned into intra- and inter-hemispheric connections. We examined how schizophrenia altered the intra-hemispheric topological properties and the inter-hemispheric nodal strength. Although several subcortical and cingulate regions exhibited hemispheric-independent aberrations of regional efficiency, the optimal small-world properties in the hemispheric networks and their lateralization were preserved in patients. A significant deficit in the inter-hemispheric connectivity was revealed in most of the hub regions, leading to an inter-hemispheric hypo-connectivity pattern in patients. These abnormal intra- and inter-hemispheric network organizations were associated with the clinical features of schizophrenia. The patients in the present study received different medications. These findings provide new insights into the nature of dysconnectivity in schizophrenia, highlighting the dissociable processes between the preserved intra-hemispheric network topology and altered inter-hemispheric functional connectivity.
View details for PubMedID 30094555
Lateral prefrontal/orbitofrontal cortex has different roles in norm compliance in gain and loss domains: a transcranial current stimulation (tDCS) study.
The European journal of neuroscience
Sanction is used by almost all known human societies to enforce fairness norm in resource distribution. Previous studies have consistently shown that the lateral prefrontal cortex (lPFC) and the adjacent orbitofrontal cortex (lOFC) play a causal role in mediating the effect of sanction threat on norm compliance. However, most of these studies were conducted in the gain domain in which resources are distributed among members. Little is known about the mechanisms underlying norm compliance in the loss domain in which individual sacrifices are needed. Here we employed a modified version of Dictator Game (DG) and high-definition transcranial direct current stimulation (HD-tDCS) to investigate to what extent lPFC/lOFC is involved in norm compliance (with and without sanction-threat) in both gain and loss sharing contexts. Participants allocated a fixed total amount of monetary gain or loss between themselves and an anonymous partner in multiple rounds of the game. A computer program randomly decided whether a given round involved sanction threat for the participants. Results showed that disruption of the right lPFC/lOFC by tDCS increased the voluntary norm compliance in the gain domain, but not in the loss domain; tDCS on lPFC/lOFC had no effect on compliance under sanction-threat in either the gain or loss domain. Our findings reveal a complex context-dependent nature of norm compliance and differential roles of lPFC/lOFC in norm compliance in the gain and loss domains. This article is protected by copyright. All rights reserved.
View details for PubMedID 28715119
Intention Modulates the Effect of Punishment Threat in Norm Enforcement via the Lateral Orbitofrontal Cortex
JOURNAL OF NEUROSCIENCE
2016; 36 (35): 9217-9226
Although economic theories suggest that punishment threat is crucial for maintaining social norms, counterexamples are noted in which punishment threat hinders norm compliance. Such discrepancy may arise from the intention behind the threat: unintentionally introduced punishment threat facilitates, whereas intentionally introduced punishment threat hinders, norm compliance. Here, we combined a dictator game and fMRI to investigate how intention modulates the effect of punishment threat on norm compliance and the neural substrates of this modulation. We also investigated whether this modulation can be influenced by brain stimulation. Human participants divided an amount of money between themselves and a partner. The partner (intentionally) or a computer program (unintentionally) decided to retain or waive the right to punish the participant upon selfish distribution. Compared with the unintentional condition, participants allocated more when the partner intentionally waived the power of punishment, but less when the partner retained such power. The right lateral orbitofrontal cortex (rLOFC) showed higher activation when the partner waived compared with when the computer waived or when the partner retained the power. The functional connectivity between the rLOFC and the brain network associated with intention/mentalizing processing was predictive of the allocation difference induced by intention. Moreover, inhibition or activation of the rLOFC by brain stimulation decreased or increased, respectively, the participants' reliance on the partner's intention during monetary allocation. These findings demonstrate that the perceived intention of punishment threat plays a crucial role in norm compliance and that the LOFC is casually involved in the implementation of intention-based cooperative decisions.Does punishment threat facilitate or hinder norm enforcement? So far, cognitive neuroscience research offers equivocal evidence. By directly manipulating the intention behind punishment threat, we demonstrate that intention modulates the effectiveness of punishment threat. Moreover, we show that inhibition or activation of the right lateral orbitofrontal cortex (rLOFC) decreased or increased the effect of punishment threat in the intentional context, but not in the unintentional context, suggesting the casual involvement of the rLOFC in intention-based cooperative decisions.
View details for DOI 10.1523/JNEUROSCI.0595-16.2016
View details for Web of Science ID 000384005600018
View details for PubMedID 27581461
Synchronized network activity as the origin of a P300 component in a facial attractiveness judgment task
2014; 51 (3): 285-289
Many studies have used the P300 as an index for cognitive processing and neurological/psychiatric disorders. Here, we combined the source separation and source localization methods to investigate the cortical origins of the P300 elicited in a facial attractiveness judgment task. For each participant, we applied second-order blind identification (SOBI) to continuous EEG data to decompose the mixture of brain signals and noise. We then used the equivalent current dipole (ECD) models to estimate the centrality of the SOBI-recovered P300. We found that the ECD models, consisting of dipoles in the frontal and posterior association cortices, account for 96.5 ± 0.5% of variance in the scalp projection of the component. Given that the recovered dipole activities in different brain regions share the same time course with different weights, we conclude that the P300 originates from synchronized activity between anterior and posterior parts of the brain.
View details for Web of Science ID 000331356100008
View details for PubMedID 24506464
Brain responses in evaluating feedback stimuli with a social dimension
FRONTIERS IN HUMAN NEUROSCIENCE
Previous studies on outcome evaluation and performance monitoring using gambling or simple cognitive tasks have identified two event-related potential (ERP) components that are particularly relevant to the neural responses to decision outcome. The feedback-related negativity (FRN), typically occurring 200-300 ms post-onset of feedback stimuli, encodes mainly the valence of outcome while the P300, which is the most positive peak between 200-600 ms, is related to various aspects of outcome evaluation. This study investigated the extent to which neural correlates of outcome evaluation involving perceptually complex feedback stimuli (i.e., female faces) are similar to those elicited by simple feedback. We asked participants to judge the attractiveness of blurred faces and then showed them unblurred faces as implicit feedback. The FRN effect can be identified in the ERP waveforms, albeit in a delayed 300-380 ms time window, with faces inconsistent with the initial judgment eliciting more negative-going responses than faces consistent with the judgment. However, the ERP waveforms did not show the typical pattern of P300 responses. With the principal component analysis (PCA), a clear pattern of P300 effects were revealed, with the P300 being more positive to faces consistent with the initial judgment than to faces inconsistent with the judgment, and more positive to attractive faces than to unattractive ones. The effect of feedback consistency did not interact with the effect of attractiveness in either the FRN or P300 component. These findings suggest that brain responses involved in processing complex feedback stimuli with a social dimension are generally similar to those involved in processing simple feedback stimuli in gambling or cognitive tasks, although appropriate means of data analysis are needed to reveal the typical ERP effects that may have been masked by sophisticated cognitive (and emotional) processes for complex stimuli.
View details for DOI 10.3389/fnhum.2012.00029
View details for Web of Science ID 000301120000002
View details for PubMedID 22371701
ELECTROENCEPHALOGRAM OSCILLATIONS DIFFERENTIATE SEMANTIC AND PROSODIC PROCESSES DURING SENTENCE READING
2010; 169 (2): 654-664
How prosodic information is processed at the neural level during silent sentence reading is an unsolved issue. In this study, we investigate whether and how the processing of prosodic constraints can be distinguished from the processing of semantic constraints by measuring changes in event-related electroencephalogram (EEG) power. We visually presented Chinese sentences containing verb-noun combinations that were semantically congruent or incongruent and that had normal or abnormal rhythmic patterns and asked participants to judge whether the sentences were semantically and rhythmically acceptable. In Chinese, the rhythmic pattern refers to the combination of words with different syllable lengths. While the [1+1] pattern is normal for a verb-noun combination, the [2+1] pattern is abnormal. With the critical nouns, we found that the violation of semantic constraints was associated with the low beta (16-20 Hz) decrease in the early window (0-200 ms post onset) and the alpha (10-15 Hz) and low beta decrease in the later window (400-657 ms) while the processing of the abnormal rhythmic pattern was associated with the theta (4-6 Hz) and the alpha increase in the early window and the alpha and upper beta (20-24 Hz) decrease in the later window. These findings suggest that although the processing of semantic constraints and the processing of rhythmic pattern may partially share neuro-cognitive processes, as reflected by the similar decreases in alpha band power, they can nevertheless be differentiated in EEG responses during sentence reading.
View details for DOI 10.1016/j.neuroscience.2010.05.032
View details for Web of Science ID 000280386900010
View details for PubMedID 20580785