Current Role at Stanford
Basic Life Research Scientist
Education & Certifications
PhD, Peking University, Psychology
BEng, Beijing University of Technology, Computer Science
Deep learning models reveal replicable, generalizable, and behaviorally relevant sex differences in human functional brain organization.
Proceedings of the National Academy of Sciences of the United States of America
2024; 121 (9): e2310012121
Sex plays a crucial role in human brain development, aging, and the manifestation of psychiatric and neurological disorders. However, our understanding of sex differences in human functional brain organization and their behavioral consequences has been hindered by inconsistent findings and a lack of replication. Here, we address these challenges using a spatiotemporal deep neural network (stDNN) model to uncover latent functional brain dynamics that distinguish male and female brains. Our stDNN model accurately differentiated male and female brains, demonstrating consistently high cross-validation accuracy (>90%), replicability, and generalizability across multisession data from the same individuals and three independent cohorts (N ~ 1,500 young adults aged 20 to 35). Explainable AI (XAI) analysis revealed that brain features associated with the default mode network, striatum, and limbic network consistently exhibited significant sex differences (effect sizes > 1.5) across sessions and independent cohorts. Furthermore, XAI-derived brain features accurately predicted sex-specific cognitive profiles, a finding that was also independently replicated. Our results demonstrate that sex differences in functional brain dynamics are not only highly replicable and generalizable but also behaviorally relevant, challenging the notion of a continuum in male-female brain organization. Our findings underscore the crucial role of sex as a biological determinant in human brain organization, have significant implications for developing personalized sex-specific biomarkers in psychiatric and neurological disorders, and provide innovative AI-based computational tools for future research.
View details for DOI 10.1073/pnas.2310012121
View details for PubMedID 38377194
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
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
Cognitive training enhances growth mindset in children through plasticity of cortico-striatal circuits.
NPJ science of learning
2022; 7 (1): 30
Growth mindset, the belief that one's abilities can improve through cognitive effort, is an important psychological construct with broad implications for enabling children to reach their highest potential. However, surprisingly little is known about malleability of growth mindset in response to cognitive interventions in children and its neurobiological underpinnings. Here we address critical gaps in our knowledge by investigating behavioral and brain changes in growth mindset associated with a four-week training program designed to enhance foundational, academically relevant, cognitive skills in 7-10-year-old children. Cognitive training significantly enhanced children's growth mindset. Cross-lagged panel analysis of longitudinal pre- and post-training data revealed that growth mindset prior to training predicted cognitive abilities after training, providing support for the positive role of growth mindset in fostering academic achievement. We then examined training-induced changes in brain response and connectivity associated with problem solving in relation to changes in growth mindset. Children's gains in growth mindset were associated with increased neural response and functional connectivity of the dorsal anterior cingulate cortex, striatum, and hippocampus, brain regions crucial for cognitive control, motivation, and memory. Plasticity of cortico-striatal circuitry emerged as the strongest predictor of growth mindset gains. Taken together, our study demonstrates that children's growth mindset can be enhanced by cognitive training, and elucidates the potential neurobiological mechanisms underlying its malleability. Findings provide important insights into effective interventions that simultaneously promote growth mindset and learning during the early stages of cognitive development.
View details for DOI 10.1038/s41539-022-00146-7
View details for PubMedID 36371438
Foundational number sense training gains are predicted by hippocampal-parietal circuits.
The Journal of neuroscience : the official journal of the Society for Neuroscience
The development of mathematical skills in early childhood relies on number sense, the foundational ability to discriminate between quantities. Number sense in early childhood is predictive of academic and professional success, and deficits in number sense are thought to underlie lifelong impairments in mathematical abilities. Despite its importance, the brain circuit mechanisms that support number sense learning remain poorly understood. Here, we designed a theoretically motivated training program to determine brain circuit mechanisms underlying foundational number sense learning in female and male elementary school-aged children (ages 7-10). Our four-week integrative number sense training program gradually strengthened the understanding of the relations between symbolic (Arabic numerals) and non-symbolic (sets of items) representations of quantity. We found that our number sense training program improved symbolic quantity discrimination ability in children across a wide a range of math abilities including those with learning difficulties. Crucially, the strength of pre-training functional connectivity between the hippocampus and intraparietal sulcus, brain regions implicated in associative learning and quantity discrimination, respectively, predicted individual differences in number sense learning across typically developing children and children with learning difficulties. Reverse meta-analysis of inter-regional co-activations across 14,371 fMRI studies and 89 cognitive functions confirmed a reliable role for hippocampal-intraparietal-sulcus circuits in learning. Our study identifies a canonical hippocampal-parietal circuit for learning which plays a foundational role in children's cognitive skill acquisition. Findings provide important insights into neurobiological circuit markers of individual differences in children's learning and delineate a robust target for effective cognitive interventions.Significance StatementMathematical skill development relies on number sense, the ability to discriminate between quantities. Here, we develop a theoretically motivated training program and investigate brain circuits that predict number sense learning in children during a period important for acquisition of foundational cognitive skills. Our integrated number sense training program was effective in children across a wide a range of math abilities, including children with learning difficulties. We identify hippocampal-parietal circuits that predict individual differences in learning gains. Our study identifies a novel brain circuit predictive of the acquistion of foundational number sense skills and delineates a robust target for effective interventions and monitoring response to cognitive training.
View details for DOI 10.1523/JNEUROSCI.1005-21.2022
View details for PubMedID 35410879
Developmental Maturation of Causal Signaling Hubs in Voluntary Control of Saccades and Their Functional Controllability.
Cerebral cortex (New York, N.Y. : 1991)
The ability to adaptively respond to behaviorally relevant cues in the environment, including voluntary control of automatic but inappropriate responses and deployment of a goal-relevant alternative response, undergoes significant maturation from childhood to adulthood. Importantly, the maturation of voluntary control processes influences the developmental trajectories of several key cognitive domains, including executive function and emotion regulation. Understanding the maturation of voluntary control is therefore of fundamental importance, but little is known about the underlying causal functional circuit mechanisms. Here, we use state-space and control-theoretic modeling to investigate the maturation of causal signaling mechanisms underlying voluntary control over saccades. We demonstrate that directed causal interactions in a canonical saccade network undergo significant maturation between childhood and adulthood. Crucially, we show that the frontal eye field (FEF) is an immature causal signaling hub in children during control over saccades. Using control-theoretic analysis, we then demonstrate that the saccade network is less controllable in children and that greater energy is required to drive FEF dynamics in children compared to adults. Our findings provide novel evidence that strengthening of causal signaling hubs and controllability of FEF are key mechanisms underlying age-related improvements in the ability to plan and execute voluntary control over saccades.
View details for DOI 10.1093/cercor/bhab514
View details for PubMedID 35094063
Linear and nonlinear profiles of weak behavioral and neural differentiation of numerical operations in children with math learning difficulties.
Mathematical knowledge is constructed hierarchically during development from a basic understanding of addition and subtraction, two foundational and inter-related, but semantically distinct, numerical operations. Early in development, children show remarkable variability in their numerical problem-solving skills and difficulties in solving even simple addition and subtraction problems are a hallmark of math learning difficulties. Here, we use novel quantitative analyses to investigate whether less distinct representations are associated with poor problem-solving abilities in children during the early stages of math-skill acquisition. Crucially, we leverage dimensional and categorical analyses to identify linear and nonlinear neurobehavioral profiles of individual differences in math skills. Behaviorally, performance on the two different numerical operations was less differentiated in children with low math abilities, and lower problem-solving efficiency stemmed from weak evidence-accumulation during problem-solving. Children with low numerical abilities also showed less differentiated neural representations between addition and subtraction operations in multiple cortical areas, including the fusiform gyrus, intraparietal sulcus, anterior temporal cortex and insula. Furthermore, analysis of multi-regional neural representation patterns revealed significantly higher network similarity and aberrant integration of representations within a fusiform gyrus-intraparietal sulcus pathway important for manipulation of numerical quantity. These findings identify the lack of distinct neural representations as a novel neurobiological feature of individual differences in children's numerical problem-solving abilities, and an early developmental biomarker of low math skills. More generally, our approach combining dimensional and categorical analyses overcomes pitfalls associated with the use of arbitrary cutoffs for probing neurobehavioral profiles of individual differences in math abilities.
View details for DOI 10.1016/j.neuropsychologia.2021.107977
View details for PubMedID 34329664
Neural representational similarity between symbolic and non-symbolic quantities predicts arithmetic skills in childhood but not adolescence
Mathematical knowledge is constructed hierarchically from basic understanding of quantities and the symbols that denote them. Discrimination of numerical quantity in both symbolic and non-symbolic formats has been linked to mathematical problem-solving abilities. However, little is known of the extent to which overlap in quantity representations between symbolic and non-symbolic formats is related to individual differences in numerical problem solving and whether this relation changes with different stages of development and skill acquisition. Here we investigate the association between neural representational similarity (NRS) across symbolic and non-symbolic quantity discrimination and arithmetic problem-solving skills in early and late developmental stages: elementary school children (ages 7-10 years) and adolescents and young adults (AYA, ages 14-21 years). In children, cross-format NRS in distributed brain regions, including parietal and frontal cortices and the hippocampus, was positively correlated with arithmetic skills. In contrast, no brain region showed a significant association between cross-format NRS and arithmetic skills in the AYA group. Our findings suggest that the relationship between symbolic-non-symbolic NRS and arithmetic skills depends on developmental stage. Taken together, our study provides evidence for both mapping and estrangement hypotheses in the context of numerical problem solving, albeit over different cognitive developmental stages.
View details for DOI 10.1111/desc.13123
View details for Web of Science ID 000656424000001
View details for PubMedID 34060183
Stress-induced changes in modular organizations of human brain functional networks.
Neurobiology of stress
2020; 13: 100231
Humans inevitably go through various stressful events, which initiates a chain of neuroendocrine reactions that may affect brain functions and lead to psychopathological symptoms. Previous studies have shown stress-induced changes in activation of individual brain regions or pairwise inter-regional connectivity. However, it remains unclear how large-scale brain network is reconfigured in response to stress. Using a within-subjects design, we combined the Trier Social Stress Test and graph theoretical method to characterize stress-induced topological alterations of brain functional network. Modularity analysis revealed that the brain network can be divided into frontoparietal, default mode, occipital, subcortical, and central-opercular modules under control and stress conditions, corresponding to several well-known functional systems underpinning cognitive control, self-referential mental processing, visual, salience processing, sensory and motor functions. While the frontoparietal module functioned as a connector module under stress, its within-module connectivity was weakened. The default mode module lost its connector function and its within-module connectivity was enhanced under stress. Moreover, stress altered the capacity to control over information flow in a few regions important for salience processing and self-referential metal processing. Furthermore, there was a trend of negative correlation between modularity and stress response magnitude. These findings demonstrate that acute stress prompts large-scale brain-wide reconfiguration involving multiple functional modules.
View details for DOI 10.1016/j.ynstr.2020.100231
View details for PubMedID 32490057
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 DOI 10.1111/ejn.13653
View details for PubMedID 28715119
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