The 5th ICHBD

Focusing on Developmental Population Neuroscience

(Sept. 22-24, 2021, Beijing, China)

The 5th International Conference of Human Brain Development (ICHBD) will be held at Beijing in September 2021. The theme of the conference is – Harnessing big data for developmental cognitive neuroscience toward developmental population neuroscience (DPN). The conference brings together international scientists from multiple disciplines focusing on measurement theory, cohort and mechanism as well as educational and clinical applications of the human lifespan development of brain and mind. ICHBD will call highlights of the optimization strategy based on the existing research platforms and achievements to predict the future directions and progress of DPN. By devoting to the development of brain, behavior as well as neurological and neuropsychological disorders, this ICHDB is committed to reaching a deeper understanding of brain working mechanisms underlying mental health, and exploring the normal and abnormal development in brain structure and function. We sincerely hope that the success of this conference can contribute to the progress of brain sciences in China and their international collaborations!


The conference is co-organized by the State Key Laboratory of Cognitive Neuroscience and Learning at Beijing Normal UniversityChina Association for Science and Technology and Chinese Neuroscience Society.

Scientific Program Committee

Chair: Xi-Nian Zuo, Sha Tao, Qi Dong (Beijing Normal University, China)

Michael Peter Milham (Child Mind Institute, USA)

Yu-Feng Zang (Hangzhou Normal University, China)

Yan-jie Su (Peking University, China)

Invited Speakers

An-Tao Chen, Southwest University, China

——“Investigating human reasoning via the intervention on executive attention”

In this study, we adopted anit-saccade (AS) task as EA training task, while the experimental group (HEA) would finish the anti-saccade task of which the ratio of AS trials to pro-saccade (PS) trials was 5:1 while the counterpart was 1:1 in the active control group (LEA). The results showed that the HEA group after the AS task finished reacted more accurately and significantly faster than the LEA group and the blank control group in analogical reasoning (AR) but not in perception. Further, the ERP results showed that compared to the LEA group, the anti-saccade (AS) trials elicited smaller N2 than pro-saccade (PS) trials and the resting alpha power was significantly improved after EA task in the HEA group. We also found that LPC significantly mediating the relationship between the N2 of AS trials and reasoning RTs in the HEA group. The role of EA in Gf related higher-order cognition was discussed.

An-Qi Qiu, National University of Singapore, Singapore

——“Brain Development and Aging: implication from brain imaging and transcriptome”

Early brain development is shaped by gene and environment, which also mirrors brain aging later in life. This talk will demonstrate the heterogeneity of brain networks at birth and its implication on heterogeneous patterns of behaviors in childhood. We will then discuss potential genetic and environmental factors that could contribute to such brain and behavioral heterogeneity in early life. Finally, we will show possible cell types and biological mechanisms that associate with brain development and aging from both brain images and transcriptomic data.

Chao-Gan Yan, Institute of Psychology, Chinese Academy of Sciences, China

——“The REST-meta-MDD Project: towards a Neuroimaging Biomarker of Major Depressive Disorder”

Major Depressive Disorder (MDD) is common and disabling, but its neuropathophysiology remains unclear. Most studies of functional brain networks in MDD have had limited statistical power and data analysis approaches have varied widely. The REST-meta-MDD Project of resting-state fMRI (R-fMRI) addresses these issues. Twenty-five research groups in China established the REST-meta-MDD Consortium by contributing R-fMRI data from 1,300 patients with MDD and 1,128 normal controls (NCs). When we focused on functional connectivity (FC) within the default mode network (DMN), frequently reported to be increased in MDD, we found decreased DMN FC. We have also examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency and degree) using graph theory-based methods. We found decreased global and local efficiency in patients with MDD compared to NCs. In this highly powered multisite study, we confirmed the key role of DMN in MDD and observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Christian Beckmann, Donders Centre for Cognitive Neuroimaging, NL

——“Advances in Phenotype Discovery from Population Brain Imaging”

Neuroimaging allows for the non-invasive study of the brain in rich detail. Data-driven discovery of patterns of population variability in the brain has the potential to be extremely valuable for early disease diagnosis and understanding the brain. The resulting patterns can be used as imaging-derived phenotypes (IDPs), and may complement existing expert-curated IDPs. However, population datasets, comprising many different structural and functional imaging modalities from thousands of subjects, provide a computational challenge not previously addressed. Here, for the first time, a multimodal independent component analysis approach is presented that is scalable for data fusion of voxel-level neuroimaging data in the full UK Biobank (UKB) dataset, that will soon reach 100,000 imaged subjects. This new computational approach can estimate modes of population variability that enhance the ability to predict thousands of phenotypic and behavioural variables using data from UKB and the Human Connectome Project. A high-dimensional decomposition achieved improved predictive power compared with widely-used analysis strategies, single-modality decompositions and existing IDPs. In UKB data (14,503 subjects with 47 different data modalities), many interpretable associations with non-imaging phenotypes were identified, including multimodal spatial maps related to fluid intelligence, handedness and disease, in some cases where IDP-based approaches failed.

Chuan-Peng Hu, Nanjing Normal University, China

——“Meta-science can improve the robustness of developmental population neuroscience”

Meta-science, also known as meta-research, is the use of scientific methodology to study science itself. Meta-science has gained increased visibility after the replication crisis in science about a decade ago. Since then, it has examined many aspects of neuroscientific and cognitive studies, including methods (biases in research, abuse of statistics, etc.), reporting and communication, reproducibility, and the research culture and incentive system. In this sense, meta-science can help developmental population neuroscience, a burgeoning interdisciplinary field, ensuring its robustness and scientific rigor. First, meta-science provides insights into the reasons behind the generalizability crisis and potential solutions. Second, meta-science reveals the flexibility in psychological measurements (e.g., SES and other psychological constructs) and provide a new starting point for better measurements in large-scale projects. Third, meta-science provides consensus-based reporting standards for empirical research, which will increase the reproducibility and credibility of science.

Dan-Hua Lin, Beijing Normal University, China

——“Childhood adversity and healthy development: Proposed neural mechanisms and protective factors among disadvantaged children in China”

Childhood adversity enhances children’s vulnerability to psychopathology through changing their brain morphology and function. Prior theories and empirical research have suggested that alterations in brain structure, functional activity, and connectivity following childhood adversity vary by cumulative risk and types of adversity. However, limited studies have explored this issue in China, and it is less clear about cultural differences in the associations between childhood adversity and brain development. In this presentation, we will first present findings drawn upon a series of neuroimaging studies among disadvantaged children in China (including AIDS orphan, rural-to-urban migrant children, and rural left-behind children). Next, we will introduce an ongoing, 6-year longitudinal project conducted among a sample of socioeconomically disadvantaged children, which focuses specifically on the impact of childhood adversity on neuropsychological and developmental outcomes of children and adolescents in rural China. Finally, future directions in adversity research will be discussed.

Fei WangNanjing Brain Hospital at Nanjing Medical University, China

——“Comprehensive characterization and classification of major psychiatric disorders using deep learning”

Phenomenology is currently the sole means for diagnosing major psychiatric disorders (MPDs–schizophrenia, bipolar disorder, and major depressive disorder). However, significant heterogeneities exist across diagnoses and substantial overlaps subsist among the diagnoses, resulting in many patients untreated. We set forth to look for biomarkers for MPD diagnosis. Using neuroimaging and multi-omics data of a large cohort, we identified patterns of regional-homogeneity as a reliable biomarker. We exploited these patterns in a deep learning-based model to classify MPDs into three new subtypes: Neurodevelopmental, Neurosomatic, and Atypical MPDs. The subtypes had unique neuroimaging patterns and distinct polygenic risk scores, risk gene expressions, and metabolic profiles. We performed personalized intervention trials based on the new subtypes and achieved superior clinical outcomes. Our study highlights the importance of integrating multi-level data, and longitudinal sampling to identify novel biologically-based subtypes to support well-informed treatment decisions.

Fei-Yan Chen, Zhejiang University, China

——“The role of individual differences in cognitive training and its neural correlates”

People differ in their cognitive abilities. Various factors could underlie such individual differences, including genetics, brain anatomy and brain activity. Furthermore, cognitive training interventions have become increasingly popular as a potential means to efficiently stabilize or enhance cognitive functioning across the lifespan, and there are great individual differences in cognitive training outcomes. However, the relationships between individual differences and cognitive training gains remains unclear. This talk try to study such biological bases and model its correlation to inter-person cognitive variability to better understand development and cognitive training effects.

Feng-ji Geng, Zhejiang University , China

——“Neural correlates of proactive and reactive cognitive control in children and adults”

Cognitive control is heavily involved in our daily activities. The dual-mechanism framework proposes that cognitive control involves proactive and reactive components. Age-related changes in these two types of cognitive control have been observed from early childhood to adolescence to adulthood using behavioral and the event-related potentials (ERP) methods. As limited by these methods, it was unknown about the exact neural correlates underlying the development of proactive and reactive control. This study collected task fMRI data from 8-to-11-year-olds and adults in a cued task-switching paradigm. Behavioral results indicated that both children and adults were able to use proactive control. However, neuroimaging results showed that children invested more brain resource to process cues and targets in proactive vs. reactive condition; in contrast, adults invested more brain resource to process cues and targets in reactive vs. proactive condition. Therefore, the use of proactive vs. reactive control is more demanding for children than adults.

Gao-Lang Gong, Beijing Normal University, China

——“Callosal fiber length scales with brain size according to functional lateralization, evolution, and development”

Brain size significantly impacts the organization of white matter fibers. Fiber length scaling – the degree to which fiber length varies according to brain size – was overlooked. We investigated how fiber lengths within the corpus callosum, the most prominent white matter tract, vary according to brain size. The results showed substantial variation in length scaling among callosal fibers, replicated in two large healthy cohorts. The underscaled callosal fibers mainly connected the precentral gyrus and parietal cortices, whereas the overscaled callosal fibers mainly connected the prefrontal cortices. The variation in such length scaling was biologically meaningful: larger scaling corresponded to larger neurite density index but smaller fractional anisotropy values; cortical regions connected by the callosal fibers with larger scaling were more lateralized functionally as well as phylogenetically and ontogenetically more recent than their counterparts. These findings highlight an interaction between interhemispheric communication and organizational and adaptive principles underlying brain development and evolution.

Hong-Jian He, Zhejiang University, China

——“Multi-center MRI: its heterogeneity and data harmonization”

Magnetic resonance imaging (MRI) has accumulated and will continue to generate a large amount of scientific and clinical imaging data. These data not only have large capacity, but they also have obvious heterogeneity characteristic, which is mainly due to different devices and acquisition protocols. Unifying hardware and standardizing protocols are currently the most effective ways to improve homogeneity, but their effectiveness on existing data is limited. Furthermore, physical and software differences are unavoidable in practice, making the standardized concept difficult to implement. Therefore, the heterogeneity of multi-center MRI has become a key and urgent problem to be solved.

Our team had previously conducted traveling volunteers experiments to investigate the cause of cross-center imaging heterogeneity. We investigated the impact of basic imaging parameters, such as b-value and TE, on diffusion measures in more depth. On the other hand, we proposed deep learning methods to improve imaging quality and help with MR data harmonization.

Richard Bethlehem, University of Cambridge, UK

——“ Brain charts for the human lifespan”

Over the past 25 years, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, there are no reference standards against which to anchor measures of individual differences in brain morphology, in contrast to growth charts for traits such as height and weight. Here, we built an interactive online resource ( to quantify individual differences in brain structure from any current or future magnetic resonance imaging (MRI) study, against models of expected age-related trends. With the goal of basing these on the largest and most inclusive dataset, we aggregated MRI data spanning 115 days post-conception through 100 postnatal years, totaling 122,123 scans from 100,071 individuals in over 100 studies across 6 continents. When quantified as centile scores relative to the reference models, individual differences show high validity with non-MRI brain growth estimates and high stability across longitudinal assessment. Centile scores helped identify previously unreported brain developmental milestones and demonstrated increased genetic heritability compared to non-centiled MRI phenotypes. Crucially for the study of brain disorders, centile scores provide a standardised and interpretable measure of deviation that reveals new patterns of neuroanatomical differences across neurological and psychiatric disorders emerging during development and ageing. In sum, brain charts for the human lifespan are an essential first step towards robust, standardised quantification of individual variation and for characterizing deviation from age-related trends. Our global collaborative study provides such an anchorpoint for basic neuroimaging research and will facilitate implementation of research-based standards in clinical studies.

Jiang Qiu, Southwest University, China

——“The developmental trajectory of adolescents’ creativity and its brain mechanisms”

Creativity is a complex and high-order cognitive ability. The cultivation of creativity is the foundation of Innovative Country Construction. This talk will introduce three main aspects of our research. First, based on the previous literature and the multimodal database (gene-brain-behavior) of brain development and mental development of children and adolescents, we explored the developmental trajectory and brain mechanism of creative thinking among children and adolescents. Second, we discovered the core network characteristics that can evaluate and predict individual creativity, and build a model based on brain imaging data to evaluate individual creativity. Last, through cognitive intervention research, we explored the brain plasticity mechanism that underlying the improvements of creative thinking among adolescents.

Li Hu, Institute of Psychology, Chinese Academy of Sciences, China

——“Developmental cognitive neuroscience of pain: present and future”

Past several decades have witnessed a booming research field of cognitive neuroscience of pain, yet the majority of such studies include young adult participants only, largely ignoring the age differences. The field needs to fill the gap and provide more comprehensive understanding on how pain is processed in the brain of the young and the elderly, and how pain can be successfully managed for different age groups. Importantly, the developmental perspective gives the invaluable insight that psychological and physiological characteristics of different age groups influence the validity of pain assessment and the efficacy of pain treatment, thus necessitating different pain measures and treatments for children, adolescents, adults, and the elderly. Future studies will exploit emerging innovative and advanced technologies, fully appreciate the multidimensional nature of pain, develop age-specific nonaddictive pain treatment, and ensure transparency and openness in developmental pain research.

Michael Milham, Child Mind Institute, US

——“ Moving Beyond Processing and Analysis Pipeline-Related Variation in Neuroscience”

Recent years have witnessed a growing appreciation of the importance of measurement reliability in neuroscience. Theoretical and empirical studies have emphasized reliability as an upper bound for validity, and a determinant of sample size requirements. The functional connectomics literature is proving to be a particularly notable beneficiary of such a focus, with a multitude of studies pointing to the ability to dramatically improve measurement reliability by increasing the amount of fMRI data obtained per individual (i.e., 25+ minutes vs. the more traditional 5-10 minutes) and/or adopting alternative data acquisition (e.g., multiecho fMRI) or analytic strategies (e.g., bagging, multivariate modeling). A commonality among these efforts is the focus on test-retest reliability, which is a critical prerequisite for any measure to achieve utility for scientific investigations and biomarker discovery – though, not the only one.

The reliability across processing and analytic pipelines is another aspect of measurement reliability that is critical for moving the field forward, as it ensures the suitability of data for comparison and/or aggregation across studies. Akin to the widely recognized concept of inter-rater reliability, a growing body of studies in the neuroimaging literature is emphasizing that even when supplied the same exact data, independently constructed processing and analysis pipelines can yield notably different results. In part, this may reflect unresolved differences of opinion in the specific steps to employ for optimal data analysis. Though, even when intending to accomplish the same basic step, differences in the specific algorithms used, or the codebase in which it is implemented, can lead to differing results.

Here, using functional connectomics as an example, we report the findings of a collaborative effort that aimed to: i) extend the literature examining pipeline implementation-related variation in fMRI by comparing the results generated using minimal preprocessing in five distinct pipelines (i.e., ABCD-BIDS, CCS, C-PAC, DPARSF and fMRIPrep), ii) demonstrate the role that pipeline harmonization can play as a means of exploring analytic variation and assessing the robustness of findings, iii) put inter-pipeline reliability into context with test-retest reliability and, iv) analyze the origins of differences among pipelines and subsequently evaluated the downstream effects of observed variations on efforts to improve reliability.

Qi-Yong Gong, West China Hospital of Sichuan University, China

——“Recent Advances in Psychoradiology”

Psychoradiology is a subspecialty of radiology with the growing intersection between fields of radiological imaging and psychiatry/psychology. It applies radiological technologies, particularly the multimodal MR imaging along with the comprehensively designed image acquisition and analysis algorithm, to investigate and guide optimal treatment for mental illnesses. Because brain alterations of psychiatric patients are relatively subtle, quantitative, rapid and efficient image analysis tools that combine information from different imaging analyses are needed to obtain clinically meaningful information about patients’ brain anatomy and function. The present talk will therefore summarize the most recent findings of the psychoradiology in conjunction with the AI development, and their implications for clinical care of the psychiatric patients.

Sha Tao, Beijing Normal University, China

——“The progresses of Beijing Cohort Study of School Functions and Child Brain Development and Its Possible Contributions to the National Study of Child Brain and Mind Development”

How do children adjust to schooling and make progresses in their brain structural and functional development? And how do children’s brain and their school functions connect during the development? Prospective cohort studies of larger samples in more countries beyond the western countries are in great needs. I will share the major progresses of a cohort study on brain development and school function in school children in Beijing (2016- ), including the sample, measurements, data collected and some findings. In addition, I will also discuss the possible contributions that the Beijing Cohort Study may make to the coming Chinese national cohort study of school-age children brain and mind development.

Shao-Zheng Qin, Beijing Normal University, China

——“Stress-induced Neurocognitive Reorganization Linking to Vulnerability in Youths”

Exposure to long-term stress can lead to brain dysfunction, cognitive deficits and mental disorders. Yet, our understanding of the underlying neurocognitive mechanisms why some individuals are more vulnerable than others is still in its infancy. Conventional approaches with acute stress paradigm provide limited information about the profound effects of long-term stress on human brain, cognition and behaviour. I will present a series of four task-dependent and resting-state fMRI studies in combination with naturistic long-term stress paradigms such as prolonged exposure to low socioeconomic backgrounds, negative parenting, and competitive exam stress, to investigate how stress-induced neurocognitive reorganization predicts individual differences in stress vulnerability in school-aged children, adolescents and adults. By leveraging neuropsychological and endocrinal assessments, computational modeling, and advanced analytic approaches (i.e., K-means, network connectivity, dynamic causal modeling of functional circuits, we found that: (1) exposure to low socioeconomic backgrounds reduced children’s integrative cortisol secretion considering basal cortisol at bedtime, nocturnal cortisol activity during sleep and  accelerating cortisol activity after awakening in the morning, which further led to increased centromedial amygdala connectivity with ventromedial and dorsolateral prefrontal regions; (2) negative parenting at 13-year-old during early adolescence could predict adolescents’ depressive symptoms 3 years alter during later adolescence through increased intrinsic amygdala connectivity with the ventrolateral prefrontal cortex; (3) trait anxiety as a vulnerable phenotype of stress-related mental disorders works in concert with long-term stress to affect latent decision-making dynamics during working memory through increased functional recruitment of fronto-parietal network and its imbalanced coupling with the default mode network in young healthy adults (4) pharmacological manipulation provide preliminary evidence to suggest that stress-sensitive cortisol secretion plays a critical role in stress-induced brain functional reorganization at regional activation, functional and effective connectivity levels. Altogether, our findings point toward that stress-induced neurocognitive reorganization predicts individual differences in stress vulnerability.

Ting-Yong Feng, Southwest University, China

——“Developmental neural basis and neuromodulation of procrastination”

Procrastination, referred as an irrational delay of intended action, has caused harms in many life domains. Previous studies have indicated 15%-20% of adults reported chronic procrastination across cultures, and at least 75% of students admitted to procrastinate academically, and even some people suffered from problematic procrastination. Our behavioral research showed that primary school (8-12 years old) is an important stage for the development of procrastination. The imaging study ascertained the brain morphological dynamics involving in self-control (e.g. dlPFC, ACC), emotion (e.g. OFC, insula) and episodic prospection (e.g. vmPFC, PHC) brain network for procrastination. Furthermore, our findings demonstrated an effective way to reduce actual procrastination by using ms-tDCS neuromodulation.

Tracy Riggins, University of Maryland, US

——“Hippocampal-memory network development and episodic memory in early childhood: Age-related changes and individual variation”

Memories for events that happen early in life are fragile—they are forgotten more quickly than later memories. Although numerous factors contribute to this phenomenon, one major source of change is the protracted development of memory-related neural regions. This talk will present findings from empirical studies in early childhood revealing that the development of the hippocampus, cortex, and connections between these regions contribute to age-related improvements in memory early in life. Additionally, evidence will be provided suggesting that individual differences in experience of stressful events impact memory-related neural regions and may ultimately contribute to variations in memory ability during this period.

Xi-Nian Zuo, Beijing Normal University, China

——“Chinese Color Nest Project – An accelerated longitudinal brain-mind cohort”

The ongoing Chinese Color Nest Project (CCNP) was established to create normative growth charts for brain structure and function across the human lifespan, and link age related changes in brain imaging measures to psychological assessments at the behavioral, cognitive and emotional levels using an accelerated longitudinal design. At the pilot stage, CCNP aims to recruit 1520 healthy individuals (6-90 years). In this paper, we presented an overview of the developing phase of CCNP (devCCNP) including study design, participants, data collection and preliminary findings. The devCCNP has acquired CCNP-SWU data with three waves from 2013 to 2017 in Chongqing, and is accumulating CCNP-CAS baseline data since July 2018 and wave-22 data since September 2020 in Beijing. Each participant in devCCNP was followed up for 2.5 years at 1.25-year intervals. The devCCNP obtained longitudinal neuroimaging, biophysical, social, behavioral and cognitive data via MRI, parent reported and self-reported questionnaires, behavioral assessments, and E-Prime computer tasks.Data were also collected on children’s learning, daily life and emotional states during COVID-19 pandemic in 2020. We demonstrated the solution of data harmonization across the two sites, and its promise of characterizing the growth curves of overall brain morphometry using multi-center longitudinal data as well as the data sharing information.

Xiang-Zhen Kong, Zhejiang University, China

——“Population-level brain asymmetry in health and disease”

Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables and brain disorders. This talk will present results on the population-level asymmetry in health and disease from several large-scale neuroimaging and imaging genetics projects via e.g., the ENIGMA and UK Biobank.

Xin Li, Beijing Normal University, China

——“Early prevention of cognitive impairment in the community population: The Beijing Aging Brain Rejuvenation Initiative”

Facing considerable challenges associated with aging and dementia, China urgently needs an evidence-based health-care system for prevention and management of dementia. The Beijing Aging Brain Rejuvenation Initiative (BABRI) is a community- based cohort study initiated in 2008 that focuses on asymptomatic stages of dementia, aims to develop community-based prevention strategies for cognitive impairment, and provides a platform for scientific research and clinical trials. BABRI has recruited more than 10000 participants. This article presents aims and study design of BABRI; summarizes preliminary behavioral and neuroimaging findings on mild cognitive impairment (MCI) and results of clinical trials on MCI; and discusses issues concerning early prevention in community, MCI diagnosis methods, and applications of database of aging and dementia. BABRI is proposed to build a systematic framework on brain health in old age.

Xu-Hong Liao, Beijing Normal University, China

——“Development of brain network dynamics in childhood and adolescence”

The human brain is an efficient and dynamic information processing system with a complex spatiotemporal organization. Network science approaches have revealed that the human brain functional network contains a nontrivial modular structure, in which functional specialization and integration are well balanced at low wiring costs. Accumulating evidence suggests that the modular architecture of human brain functional networks shows temporally varying patterns over short time scales (e.g., seconds), contributing to the flexible cognitive function and the fast response to external task demands. Yet, as recent work has pointed out, cognitive growth is largely dependent on age-related adjustments in the brain’s temporal dynamics. This talk will present findings from fMRI studies on the gradual progressive stabilization of brain network dynamics during childhood and adolescence and its alterations in a typical neurodevelopmental disorder — autism spectrum disorder.

Ting Xu, Center for the Developing Brain Child Mind Institute, US

——“In vivo mapping of brain organization in human and nonhuman primate”

The nonhuman primate (NHP) brain is the closest animal model to humans, which provides a unique opportunity to advance translational research. However, the complex mosaic of changes in brain morphology and functional organization that has shaped the mammalian brain, which complicates attempts to chart cortical differences across species. This talk will introduce a recently developed cross-species alignment between NHPs and humans which overcomes commonly encountered barriers for cross-species comparison. The findings unmask the functional phylogenetic pattern that mirrors functional hierarchies established in humans. This talk will also present functional dynamics across species and highlight the changeling of state differences (awake vs anesthetized) in translational research.

Xun Liu, Institute of Psychology, Chinese Academy of Sciences, China

——“Developmental neuroscience of cognitive control”

Cognitive control is the top-down process by which individuals store, plan, and manipulate relevant information through the deployment of cognitive resources. Cognitive control is a core function involving different processes such as selective attention, conflict resolution, working memory, cognitive flexibility, and inhibitory control, each of which may has its own distinctive lifelong developmental characteristics. Therefore, it is of great significance to design a set of standard task paradigms in order to map out cognitive and neural development of cognitive control. The long-term goal is to establish the developmental trajectory curves of cognitive control with the task battery, so as to help identify deficits of cognitive control in mental disorders such as addiction and cognitive aging.

Yan-Jie Su, Peking University, China

——“Adolescent neurocognitive development of communicative reasoning: The regulating role of the central executive network underlying online mentalization”

Socialization in adolescence refers to a bunch of elements such as coordinating the relationship between self and others and inferring the unstated intents underlying social communication. Beyond these socio-cognitive processes, primary cognitive control may function as a regulator reconciling the conflicts in a goal-directed communicative context. By decomposing the communicative online mentalization into the egocentric processing of the context information and the mental simulation of others’ intents, we found that the egocentric processing burst at around early adolescence, while the mental simulation towards others continuously developed from middle childhood through adolescence to emerging adulthood. And consistent with these trajectories, the gradually maturing cognitive control system started to function as a regulator exactly in early adolescence. Our findings possess implications in both the neurocognitive developmental association between the domain-specific online mentalization and the domain-general cognitive control system especially in adolescence, and developing more appropriate interventions facilitating adolescent socialization.

Yi Du, Institute of Psychology, Chinese Academy of Sciences, China

——“Brain lateralization and speech perception: Effects of age and musical training experience”

Speech perception becomes more challenging in older adults, while musical training experience is found to counteract age-related decline in speech perception. Although speech processing is generally believed to be left lateralized in the brain, previous research has indicated both an age- and a musical experience-related compensation by the right hemisphere in speech perception tasks. However, it remains unclear whether intrinsic brain functional lateralization plays a role in the modulation effects of age and musical expertise in speech perception. This talk will present findings on functional connectivity-based lateralization of resting-state fMRI data from 4 groups of participants (young musicians/non-musicians, old musicians/non-musicians) and its relationship with speech perception. This talk will also present some preliminary results on the development of brain lateralization and speech perception using data from the Chinese Color Nest Project (CCNP).

Yu-Feng Zang, Hangzhou Normal University, China

——“RS-fMRI guided precise TMS”

Resting-state functional MRI (RS-fMRI) usually refers to the blood ogxygentaiton level dependent (BOLD) technique. It measures the spontaneous or on-going brain activity during a continuous state (a few minutes or longer) without specific cognitive tasks. With the advantages of fairly good spatial (~3mm) and temporal resolution (0.1-2s), no radioactivity, and easy implementation, RS-fMRI is a promising functional neuroimaging technique for the diagnosis and to guide TMS treatment of brain disorders. Of the analytic methods, metrics for local activity (e.g., ALFF) and metrics for point-to-point functional connectivity showed potentials to guide TMS treatment. Multicenter data analysis is necessary to validate the reproducibility of abnormal brain activity, and hence, guide precise focused brain stimulation.

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