xinian

xinian

Applied Mathematician and Brain Scientist, Professor

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Posts

Get Back to Normal Life

less than 1 minute read

Published:

To be memorized, today is the first day we come back to the normal life. It means the situation of CoVID-19 off to the safe level in Beijing.

portfolio

publications

Network centrality in the human functional connectome

Published in Cerebral Cortex, 2012

This work assembles and visualizes the voxel-wise (4 mm) functional connectome as a functional network.

Recommended citation: Xi-Nian, Zuo; Ross, Ehmke; Maarten, Mennes; Davide, Imperati; F Xavier, Castellanos; Olaf, Sporns; Michael P, Milham. (2012). "Network centrality in the human functional connectome." Cerebral Cortex. 22(8):1862–1875. https://academic.oup.com/cercor/article-pdf/22/8/1862/17306507/bhr269.pdf

An open science resource for establishing reliability and reproducibility in functional connectomics

Published in Scientific Data, 2014

The Consortium for Reliability and Reproducibility (CoRR) is working to address this challenge and establish test-retest reliability as a minimum standard for methods development in functional connectomics.

Recommended citation: Xi-Nian, Zuo; Jeffrey S., Anderson; Pierre, Bellec; Rasmus M., Birn; Bharat B., Biswal; Janusch, Blautzik; et al. (2014). "An open science resource for establishing reliability and reproducibility in functional connectomics." Scientific Data. 1:140049. https://pubmed.ncbi.nlm.nih.gov/25977800

Genetic and environmental contributions to functional connectivity architecture of the human brain

Published in Cerebral Cortex, 2016

This work provides network-specific hypotheses for discovery of the specific genetic and environmental factors influencing functional specialization and integration of the human brain.

Recommended citation: Zhi, Yang; Xi-Nian, Zuo; Katie L, McMahon; R Cameron, Craddock; Clare, Kelly; Greig I, de Zubicaray; Ian, Hickie; Peter A, Bandettini; F Xavier, Castellanos; Michael P, Milham; Margaret J, Wright. (2016). "Genetic and environmental contributions to functional connectivity architecture of the human brain." Cerebral Cortex, 26(5):2341-2352. https://academic.oup.com/cercor/article/26/5/2341/1754303

Regional Homogeneity: A multimodal, multiscale neuroimaging marker of the human connectome

Published in The Neuroscientist, 2016

This review proposes local functional homogeneity as a network centrality to characterize multimodal local features of the brain connectome, and render a neurobiological perspective on local functional homogeneity by linking its temporal, spatial, and individual variability to information processing, anatomical morphology, and brain development.

Recommended citation: Lili, Jiang; Xi-Nian, Zuo. (2016). Regional Homogeneity: A multimodal, multiscale neuroimaging marker of the human connectome. The Neuroscientist, 22(5):486-505. https://journals.sagepub.com/doi/10.1177/1073858415595004

Developmental population neuroscience: emerging from ICHBD

Published in Science Bulletin, 2018

This paper proposes a new field, developmental population neuroscience (DPN), for identifying environmental and genetic factors that shape development of the human brain.

Recommended citation: Xi-Nian, Zuo; Ye, He; Xuequan, Su; Xiao-Hui, Hou; Xuchu, Weng; Qiang, Li. (2018). "Developmental population neuroscience: emerging from ICHBD." Science Bulletin, 63(6):331-332. https://www.sciencedirect.com/science/article/pii/S2095927318300082

Harnessing reliability for neuroscience research

Published in Nature Human Behaviour, 2019

This comment focuses on reliability in neuroimaging and provides examples of how the reliability can be increased.

Recommended citation: Xi-Nian, Zuo; Ting, Xu; Michael P., Milham. (2019). "Harnessing reliability for neuroscience research." Nature Human Behaviour, 3:768–771. https://rdcu.be/bH2iL

Charting brain growth in tandem with brain templates at school age

Published in Science Bulletin, 2020

In this work, the researchers analyzed a large neuroimaging dataset of Chinese and American pediatric brains, and demonstrated that age- and ethnicity-specific brain templates enable more reliable and accurate mapping of human brain growth charts.

Recommended citation: Hao-Ming, Dong; F. Xavier, Castellanos; Ning, Yang; Zhe, Zhang; Quan, Zhou; Ye, He; Lei, Zhang; Ting, Xu; Avram J., Holmes; B.T.Thomas, Yeo; Feiyan, Chen; Bin, Wang; Christian, Beckmann; Tonya, White; Olaf, Sporns; Jiang, Qiu; Tingyong; Feng; Antao, Chen; Xun, Liu; Xu, Chen; Xuchu, Weng; Michael P., Milham; Xi-Nian, Zuo. (2020). "Charting brain growth in tandem with brain templates at school age." Science Bulletin, 65(22):1824-1834. https://www.sciencedirect.com/science/article/pii/S2095927320304965

Shifting gradients of macroscale cortical organization mark the transition from childhood to adolescence

Published in PNAS, 2021

Here, we describe age-dependent shifts in the macroscale organization of cortex in childhood and adolescence. The characterization of functional connectivity patterns in children revealed an overarching organizational framework anchored within the unimodal cortex, between somatosensory/motor and visual regions. Conversely, in adolescents, we observed a transition into an adult-like gradient, situating the default network at the opposite end of a spectrum from primary somatosensory/motor regions.

Recommended citation: Hao-Ming, Dong; Daniel S., Margulies; Xi-Nian, Zuo; Avram J., Holmes. (2021). "Shifting gradients of macroscale cortical organization mark the transition from childhood to adolescence." Proceedings of the National Academy of Sciences USA, 118(28):e2024448118. https://www.pnas.org/content/118/28/e2024448118

Chinese Color Nest Project: An accelerated longitudinal brain-mind cohort

Published in DCN, 2021

The ongoing Chinese Color Nest Project (CCNP) was established to create normative charts for brain structure and function across the human lifespan, and link age-related changes in brain imaging measures to psychological assessments of behavior, cognition, and emotion using an accelerated longitudinal design. In the initial stage, CCNP aims to recruit 1520 healthy individuals (6–90 years), which comprises three phases: developing (devCCNP: 6–18 years, N = 480), maturing (matCCNP: 20–60 years, N = 560) and aging (ageCCNP: 60–84 years, N = 480). In this paper, we present an overview of the devCCNP, including study design, participants, data collection and preliminary findings.

Recommended citation: Siman, Liu; Yin-Shan, Wang; Qing, Zhang; Quan, Zhou; Li-Zhi, Cao; Chao, Jiang; Zhe, Zhang; Ning, Yang; Qi, Dong; Xi-Nian, Zuo; The Chinese Color Nest Consortium. (2021). "Chinese Color Nest Project: An accelerated longitudinal brain-mind cohort." Developmental Cognitive Neuroscience, 52:101020. https://www.sciencedirect.com/science/article/pii/S1878929321001109?via%3Dihub

Neuroimaging brain growth charts: A road to mental health

Published in PSYCHRAD, 2021

We review the relationship between mental disorders and atypical brain development from a perspective of normative brain development by surveying the recent progress in the development of brain growth charts, including four aspects on growth chart utility: 1) cohorts, 2) measures, 3) mechanisms, and 4) clinical translations. In doing so, we seek to clarify the challenges and opportunities in charting brain growth, and to promote the application of brain growth charts in clinical practice.

Recommended citation: Li-Zhen, Chen; Avram J, Holmes; Xi-Nian, Zuo; Qi, Dong. (2021). "Neuroimaging brain growth charts: A road to mental health." Psychoradiology, 1(4):272-286. https://academic.oup.com/psyrad/article/1/4/272/6490296

Brain charts for the human lifespan

Published in NATURE, 2022

With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age.

Recommended citation: R. A. I. Bethlehem; J. Seidlitz; S. R. White; et al. (2022). "Brain charts for the human lifespan." Nature, 604(7906):525-533. https://www.nature.com/articles/s41586-022-04554-y

A paradigm shift in neuroscience driven by big data

Published in ARXIV, 2022

A recent editorial in Nature noted that cognitive neuroscience is at a crossroads where it is a thorny issue to reliably reveal brain-behavior associations. This commentary sketches a big data science way out for cognitive neuroscience, namely population neuroscience. In terms of design, analysis, and interpretations, population neuroscience research takes the design control to an unprecedented level, greatly expands the dimensions of the data analysis space, and paves a paradigm shift for exploring mechanisms on brain-behavior associations.

Recommended citation: Z. X. Zhou & X. N. Zuo. (2022). "A paradigm shift in neuroscience driven by big data: State of art, challenges, and proof of concept." arXiv, arXiv:2212.04195. https://arxiv.org/abs/2212.04195

Six cornerstones for translational brain charts

Published in SCIBULL, 2023

It is of great scientific and translational promise to formulate a normative reference for the lifespan development of human brain to precisely quantify individual differences. By aggregating more than 120,000 brain imaging scans across the world, the Lifespan Brain Chart Consortium (LBCC) recently published brain charts for the human lifespan in Nature. These charts have revealed previously undocumented neurodevelopmental milestones, marking a research model on team working for the neuroimaging community towards population neuroscience. The LBCC team demonstrated that after decades of advancement and accumulation in technologies, methods, and resources, we now have a tangible opportunity to achieve translational science for brain health.

Recommended citation: Z. X. Zhou, L. Z. Chen, M. P. Milham, X. N. Zuo & Lifespan Brain Chart Consortium. (2023). "Six cornerstones for translational brain charts." Science Bulletin, 68:795-799. https://doi.org/10.1016/j.scib.2023.03.047

Optimizing network neuroscience computation of individual differences

Published in NETWORK NEUROSCI, 2023

It is an essential mission for neuroscience to understand the individual differences in brain function. Graph or network theory offer novel methods of network neuroscience to address such a challenge. This article documents optimal strategies on the test-retest reliability of measuring individual differences in intrinsic brain networks of spontaneous activity. The analytical pipelines are identified to optimize for highly reliable, individualized network measurements. These pipelines optimize network metrics for high interindividual variances and low inner-individual variances by defining network nodes with whole-brain parcellations, deriving the connectivity with spontaneous high-frequency slow-band oscillations, constructing brain graphs with topology-based methods for edge filtering, and favoring multilevel or multimodal metrics. These psychometric findings are critical for translating the functional network neuroscience into clinical or other personalized practices requiring neuroimaging markers.

Recommended citation: C. Jiang, Y. He, R. F. Betzel, Y. S. Wang, X. X. Xing & X. N. Zuo. (2023). "Optimizing network neuroscience computation of individual differences in human spontaneous brain activity for test-retest reliability." Network Neuroscience, 7:1080–1108. https://doi.org/10.1162/netn_a_00315

Ventral attention network connectivity is linked to cortical maturation and cognitive ability in childhood

Published in NATURE NEUROSCI, 2024

The human brain experiences functional changes through childhood and adolescence, shifting from an organizational framework anchored within sensorimotor and visual regions into one that is balanced through interactions with later-maturing aspects of association cortex. Here, we link this profile of functional reorganization to the development of ventral attention network connectivity across independent datasets. We demonstrate that maturational changes in cortical organization link preferentially to within-network connectivity and heightened degree centrality in the ventral attention network, whereas connectivity within network-linked vertices predicts cognitive ability. This connectivity is associated closely with maturational refinement of cortical organization. Children with low ventral attention network connectivity exhibit adolescent-like topographical profiles, suggesting that attentional systems may be relevant in understanding how brain functions are refined across development. These data suggest a role for attention networks in supporting age-dependent shifts in cortical organization and cognition across childhood and adolescence.

Recommended citation: H. M. Dong, X. H. Zhang, L. Labache, S. Zhang, L. Q. R. Ooi, B. T. T. Yeo, D. S. Margulies, A. J. Holmes & X. N. Zuo. (2024). "Ventral attention network connectivity is linked to cortical maturation and cognitive ability in childhood." Nature Neuroscience, 27:2009–2020. https://doi.org/10.1038/s41593-024-01736-x

Dark brain energy: Toward an integrative model of spontaneous slow oscillations

Published in PHYS LIFE REV, 2025

Neural oscillations facilitate the functioning of the human brain in spatial and temporal dimensions at various frequencies. These oscillations feature a universal frequency architecture that is governed by brain anatomy, ensuring frequency specificity remains invariant across different measurement techniques. Initial magnetic resonance imaging (MRI) methodology constrained functional MRI (fMRI) investigations to a singular frequency range, thereby neglecting the frequency characteristics inherent in blood oxygen level-dependent oscillations. With advancements in MRI technology, it has become feasible to decode intricate brain activities via multi-band frequency analysis (MBFA). During the past decade, the utilization of MBFA in fMRI studies has surged, unveiling frequency-dependent characteristics of spontaneous slow oscillations (SSOs) believed to base dark energy in the brain. There remains a dearth of conclusive insights and hypotheses pertaining to the properties and functionalities of SSOs in distinct bands. We surveyed the SSO MBFA studies during the past 15 years to delineate the attributes of SSOs and enlighten their correlated functions. We further proposed a model to elucidate the hierarchical organization of multi-band SSOs by integrating their function, aimed at bridging theoretical gaps and guiding future MBFA research endeavors.

Recommended citation: Z. Q. Gong & X. N. Zuo. (2025). "Dark brain energy: Toward an integrative model of spontaneous slow oscillations." Physics of Life Reviews, 52:578–597. https://doi.org/10.1016/j.plrev.2025.02.001

Intellectual ability and cortical homotopy development in children and adolescents

Published in DEV COGN NEUROSCI, 2025

Functional homotopy, defined as the similarity between the corresponding regions of the two hemispheres, is a critical feature of interhemispheric communication and cognitive integration. Throughout development, the brain transitions from broadly connected networks in early childhood to more specialized configurations in adolescence, accompanied by increased hemispheric differentiation and integration. Using longitudinal data and a novel metric of functional homotopy, Homotopic Functional Affinity (HFA), we investigated the developmental patterns of functional homotopy and its relationship with intelligence. Our findings indicate a significant decrease in HFA with age, particularly in higher-order association networks. In addition, adolescents demonstrate stronger, predominantly negative correlations between HFA and intelligence, in contrast to younger children. In particular, individuals with superior intellectual ability experience accelerated decreases in HFA, indicating greater neural efficiency based on higher hemispheric specialization and differentiation. These findings provide evidence of the neural mechanisms that underlie cognitive development, emphasizing the dynamic interaction between hemispheric organization and intelligence. Our work may inform customized educational and clinical interventions for individual development.

Recommended citation: L. Z. Chen & X. N. Zuo. (2025). "Intellectual ability and cortical homotopy development in children and adolescents." Developmental Cognitive Neuroscence, 75:101596. https://doi.org/10.1016/j.dcn.2025.101596

talks

Developmental Population Neuroscience

Published:

This gives birth of a new field, namely Developmental Population Neuroscience (DPN), which will be introduced by the present keynote. The speaker will survey and foresee DPN progresses by presenting the most established and recognized scientific findings during the past two decades as well as connecting it with the national brain project.

Large Sample Size Alone May Not Save The Day - Reliability Matters and Cohort Studies Care

Published:

Neuroscientists are working to rapidly amass the large-scale sample sizes needed to meaningfully study individual differences and support reproducible biomarker discovery (e.g., big cohorts). Although promising, the measurement reliability of individual samples is often suboptimal, thereby requiring unnecessarily large sample sizes to achieve the same goals. Functional neuroimaging provides an example, as recent works suggest that data acquisitions may need to be made longer to achieve desired levels of reliability. The implications of the present talk extend to the broader life sciences. Visit the seminar website for more details.

Toward Pediatric Standards – Brain Templates and Growth Charts

Published:

This talk will present the work generating age-normed brain templates for children and adolescents at one-year intervals and the corresponding growth charts. Age- and ethnicity-specific brain templates facilitate establishing unbiased pediatric brain growth charts, indicating the necessity of the brain charts and brain templates generated in tandem.

teaching

Developmental Population Neuroscience

Undergraduate course, Beijing Normal University, Faculty of Psychology, 2021

This is a description of a teaching experience on Developmental Population Neuroscience.