发展人口神经科学:拥抱多样性

在“人类大科学计划”的时代背景下,脑科学成为21世纪生命科学制高点[1].人类面向解析自身科学认知的这一最后疆域,对多学科交叉融合创新提出了重大需求,清晰地认识到学科发展挑战和机遇[2].人脑科学研究聚焦解读“人脑如何产生心理行为?”这一核心科学问题,面临“管中窥豹”的“现象科学”困境,需要深入研究影响人类脑智改变的多样性因素[3].

众脑之力:通过开放神经影像数据和大规模协作催化神经精神疾病的创新发现

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders.By pooling images from various cohorts,statistical power has increased,enabling the detection of subtle abnormalities and robust associations,and fostering new research methods.Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment.Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies.We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders.However,challenges such as data harmonization across different sites,privacy protection,and effective data sharing must be addressed.With proper governance and open science practices,we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis,treatment selection,and outcome prediction,contributing to optimal brain health.

Paradigm shift in psychiatric neuroscience:Multidimensional integrative theory

Abnormal structure and function of the human brain cause various mental and neurological disorders.The search for neurobiological mechanisms and biomarkers associated with psychiatric disorders has always been a focal point and a challenging issue in neuroscience.Functional magnetic resonance imaging(fMRI)allows the noninvasive re-cording of high spatial-temporal resolution brain activity in patients,making it one of the primary research methods in integrative neuroscience.

Reshaping the Cortical Connectivity Gradient by Long-Term Cognitive Training During Development

The organization of the brain follows a topologi-cal hierarchy that changes dynamically during development.However,it remains unknown whether and how cognitive training administered over multiple years during develop-ment can modify this hierarchical topology.By measuring the brain and behavior of school children who had carried out abacus-based mental calculation(AMC)training for five years(starting from 7 years to 12 years old)in pre-training and post-training,we revealed the reshaping effect of long-term AMC intervention during development on the brain hierarchical topology.We observed the development-induced emergence of the default network,AMC training-promoted shifting,and regional changes in cortical gradi-ents.Moreover,the training-induced gradient changes were located in visual and somatomotor areas in association with the visuospatial/motor-imagery strategy.We found that gradient-based features can predict the math ability within groups.Our findings provide novel insights into the dynamic nature of network recruitment impacted by long-term cognitive training during development.

Erratum to“The power of many brains:Catalyzing neuropsychiatric discovery through open neuroimaging data and large-scale collaboration”[Sci Bull 2024;69:1536-1555]

The publisher regrets to note that reference citation errors have occurred in panels b,c,e-l in Fig 2 and the sentence“However,the literature reports both decreased and increased intra-network functional connections among patients with depression[115,116].”The publisher would like to apologise for any inconvenience caused.Fig.2.Principal neuroimaging findings in major depressive disorder.(a)Decreased intra-DMN FC is observed in recurrent MDD patients[35].(b)Eight-week antidepressant treatment reduce extensive large-scale functional networks[107].(c)Reduced global and local efficiency(Eglob/Eloc)are revealed in MDD patients[108].(d)Structural variations of the cortex and subcortical nuclei are found in ENIGMA-MDD studies[82].(e)Accelerated brain aging based on functional MRI is observed in MDD patients[114].(f)Accelerated brain aging based on structural MRI is observed in MDD patients[115].(g)Two subtypes of MDD can be identified through DMN FC[127].(h)A significant schizophrenia PRS by MDD interaction for rostral anterior cingulate cortex thickness is found in the UK Biobank dataset[215].(i)Stability of the four MDD subtypes based on FC[126].(j)The two subtypes of MDD exhibit distinct patterns of FC within and between SMS,DMN,and subcortical structures[130].(k)Performance of the functional connectivity-based classifiers across two multicenter datasets[135].(l)Salient brain regions that serve as important classification features for the graph convolutional network-based classifier[136].Brain-PAD:brain-predicted age difference;DAN:dorsal attention network;DMN:default mode network;FC:functional connectivity;FEDN:first-episode and drug-naïve;FPN:frontoparietal network;GCN:graph convolutional neural network;HC:healthy control;linear-SVM:linear support vector machine;MDD:major depressive disorder;mddrest:REST-meta-MDD dataset;NC:normal control;RACC:rostral anterior cingulate cortex;PRS:polygenic risk score;psymri:PsyMRI dataset;rbf-SVM:radial basis function support vector machine;SCN:subcortical network;SCZ:schizophrenia;SMN:sensorimotor network;SMS:sensory and motor systems;SubC:subcortical network;VAN:ventral attention network;VN:visual network.

Altered relationship between thickness and intrinsic activity amplitude in generalized tonic–clonic seizures

A thinner cortex has higher potential for binding GABA receptor A which is associated with larger amplitudes of intrinsic brain activity(i BA). However, the relationship between cortical thickness and i BA is unknown in intact and epileptic brains. To this end, we investigated the relationship between cortical thickness measured by highresolution MRI and surface-based i BA derived from resting-state functional MRI in normal controls(n = 82) andpatients with generalized tonic–clonic seizures(GTCS)only(n = 82). We demonstrated that the spatial distribution of cortical thickness negatively correlated with surface-based i BA amplitude at both whole-brain and within independent brain functional networks. In GTCS patients,spatial coupling between thickness and i BA amplitude decreased in the default mode, dorsal attention, and somatomotor networks. In addition, the vertex-wise acrosssubject thickness–i BA amplitude correspondence altered in the frontal and temporal lobes as well as in the precuneus in GTCS patients. The relationship between these two modalities can serve as a brain-based marker for detecting epileptogenic changes.

Concordance among indices of intrinsic brain function： Insights from inter-individual variation and temporal dynamics

Various resting-state fMRI(R-fMRI) measures have been developed to characterize intrinsic brain activity. While each of these measures has gained a growing presence in the literature, questions remain regarding the common and unique aspects these indices capture. The present work provided a comprehensive examination of inter-individual variation and intra-individual temporal variation for commonly used measures, including fractional amplitude of low frequency fluctuations, regional homogeneity,voxel-mirrored homotopic connectivity, network centrality and global signal correlation. Regardless of whether examining intra-individual or inter-individual variation, we found that these definitionally distinct R-fMRI indices tend to exhibit a relatively high degree of covariation, which doesn't exist in phase randomized surrogate data. As a measure of intrinsic brain function, concordance for R-fMRI indices was negatively correlated with age across individuals(i.e., concordance among functional indices decreased with age). To understand the functional significance of concordance, we noted that higher concordance was generally associated with higher strengths of R-fMRI indices, regardless of whether looking through the lens of inter-individual(i.e., high vs. low concordance participants) or intra-individual(i.e., high vs.low concordance states identified via temporal dynamic analyses) differences. We also noted a linear increase in functional concordance together with the R-fMRI indices through the scan, which may suggest a decrease in arousal. The current study demonstrated an enriched picture regarding the relationship among the R-fMRI indices, as well as provided new insights in examining dynamic states within and between individuals.

Ventral medial prefrontal functional connectivity and emotion regulation in chronic schizophrenia: A pilot study

People with schizophrenia exhibit impaired social cognitive functions, particularly emotion regulation. Abnormal activations of the ventral medial prefrontal cortex （vMPFC） during emotional tasks have been demonstrated in schizophrenia, suggesting its important role in emotion processing in patients. We used the resting-state functional connectivity approach, setting a functionally relevant region, the vMPFC, as a seed region to examine the intrinsic functional interactions and communication between the vMPFC and other brain regions in schizophrenic patients. We found hypo-connectivity between the vMPFC and the medial frontal cortex, right middle temporal lobe （MTL）, right hippocampus, parahippocampal cortex （PHC） and amygdala. Further, there was a decreased strength of the negative connectivity （or anticorrelation） between the vMPFC and the bilateral dorsal lateral prefrontal cortex （DLPFC） and pre-supplementary motor areas. Among these connectivity alterations, reduced vMPFC-DLPFC connectivity was positively correlated with positive symptoms on the Positive and Negative Syndrome Scale, while vMPFC-right MTL/PHC/amygdala functional connectivity was positively correlated with the performance of emotional regulation in patients. These findings imply that communication and coordination throughout the brain networks are disrupted in schizophrenia. The emotional correlates of vMPFC connectivity suggest a role of the hypo-connectivity between these regions in the neuropathology of abnormal social cognition in chronic schizophrenia.

Developmental population neuroscience: emerging from ICHBD

The 3rd International Conference on Human Brain Development(ICHBD)was held during October 10–15,2017 in Nanning,Guangxi,China.ICHBD was initiated in 2014 by Drs.Xi-Nian Zuo,Olaf Sporns and Michael P.Milham(co-chairs),and has been consistently supported by a major international collaboration grant from Natural Science Foundation of China(81220108014).The goal of ICHBD is to bring together international scientists from a

转化人类脑图表的6E压舱石

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[1].

The anatomy of reliability: a must read for future human brain mapping

Human brain mapping (HBM)is increasingly becoming a multidisciplinary field where some scientific issues are fundamental for all scientists and applications of using the technology to investigate individual differences.Reliability represents a significant issue for all scientific fields and has particularly been overlooked for decades by the HBM field [1].Meanwhile,recent advances in open science have offered the field big data for developing novel methodological frameworks as well as performing largescale investigations of the brain-mind associations based upon the individual differences assessed with HBM [2].A systematic investigation of reliability seems still far behind these HBM developments. It is critical that reliability is evaluated ahead of these applications, motivating the current commentary on delineation of the anatomy of reliability for future HBM.

Segregation between the parietal memory network and the default mode network： effects of spatial smoothing and model order in ICA

Abstract A brain network consisting of two key parietal nodes, the precuneus and the posterior cingulate cortex, has emerged from recent fMRI studies. Though it is anatomically adjacent to and spatially overlaps with the default mode network （DMN）, its function has been associated with memory processing, and it has been referred to as the parietal memory network （PMN）. Independent component analysis （ICA） is the most common data-driven method used to extract PMN and DMN simultaneously. However, the effects of data preprocessing and parameter determi- nation in ICA on PMN-DMN segregation are completely unknown. Here, we employ three typical algorithms of group ICA to assess how spatial smoothing and model order influence the degree of PMN-DMN segregation. Our findings indicate that PMN and DMN can only be stably separated using a combination of low-level spatial smoothing and high model order across the three ICA algorithms. We thus argue for more considerations on parametric settings for interpreting DMN data.

Small P values may not yield robust findings:an example using REST-meta-PD

Thousands of resting state functional magnetic resonance imaging(RS-f MRI)articles have been published on brain disorders.For precise localization of abnormal brain activity,a voxel-level comparison is needed.Because of the large number of voxels in the brain,multiple comparison correction(MCC)must be performed to reduce false positive rates,and a smaller P value(usually including either liberal or stringent MCC)is widely recommended[1].

Charting brain growth in tandem with brain templates at school age

Brain growth charts and age-normed brain templates are essential resources for researchers to eventually contribute to the care of individuals with atypical developmental trajectories.The present work generates age-normed brain templates for children and adolescents at one-year intervals and the corresponding growth charts to investigate the influences of age and ethnicity using a common pediatric neuroimaging protocol.Two accelerated longitudinal cohorts with the identical experimental design were implemented in the United States and China.Anatomical magnetic resonance imaging(MRI)of typically developing school-age children(TDC)was obtained up to three times at nominal intervals of1.25 years.The protocol generated and compared population-and age-specific brain templates and growth charts,respectively.A total of 674 Chinese pediatric MRI scans were obtained from 457 Chinese TDC and 190 American pediatric MRI scans were obtained from 133 American TDC.Population-and age-specific brain templates were used to quantify warp cost,the differences between individual brains and brain templates.Volumetric growth charts for labeled brain network areas were generated.Shape analyses of cost functions supported the necessity of age-specific and ethnicitymatched brain templates,which was confirmed by growth chart analyses.These analyses revealed volumetric growth differences between the two ethnicities primarily in lateral frontal and parietal areas,regions which are most variable across individuals in regard to their structure and function.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.These templates and growth charts as well as related codes have been made freely available to the public for open neuroscience(https://github.com/zuoxinian/CCS/tree/master/H3/Growth Charts).

Mapping the human brain function in vivo

Mapping of the human brain function in vivo is among the most promising means of uncovering the relationship between brain and behavior. Both the 1000 Functional Connectome Project1 and Human Connectome Project2 have made advancements in the collection, management, and sharing of massive neuroimaging datasets. In China, the government plans to announce the China Brain Project （CBP）, a national brain project aimed at understanding neural mechanisms underlying human cognition with applications of brain disease and brain-inspired computa- tion [1]. Methods for in vivo human brain mapping must be included in the CBP, as they make possible direct assess- ment of brain structure and activity and contribute directly to translational research.

Connectome Computation System:2015–2021 updates

The Connectome Computation System(CCS)was previously reported in the Science Bulletin[1].Here,we describe a summary of the 6-year CCS updates(2015–2021),which are accessible at https://github.com/zuoxinian/CCS.These updates contain many utilities of mining developmental neuroimaging data.Specifically,H1 module covers the data cleaning and preprocessing and refines the implementations of face-masking,brain extraction,denoising,and frequency banding.

Open science as a better gatekeeper for science and society: a perspective from neurolaw

In 2011,a court near Milan,Italy,reduced the sentence of a convicted murderer from life to 20years in jail,after considering results from neuroimaging and genetic tests.These tests had been used to convince the judge that the trial's female defendant,Stefania Albertani,was suffering from partial mental illness (http:// blogs.nature.com/news/2011/09]italian_court_reduces_murde_s. html).The structural MRI images showed that Albertani's grey matter volume was different from the average volume of a randomly-selected group -10healthy women with no history of mental or neurological disorders -in brain areas including the anterior cingulate gyrus (ACC)and insula.The expert testimony concluded that "these alterations (of brain structures)have to be considered in causal relation to the psychiatric symptomatology of the murderer."

The DIRECT consortium and the REST-meta-MDD project:towards neuroimaging biomarkers of major depressive disorder

Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder(MDD),repro-ducible findings are lacking,probably reflecting mostly small sample sizes and heterogeneity in analytic approaches.To address these issues,the Depression Imaging REsearch ConsorTium(DIRECT)was launched.The REST-meta-MDD project,pooling 2428 functional brain images processed with a standardized pipeline across all participating sites,has been the first effort from DIRECT.In this review,we present an overview of the moti-vations,rationale,and principal findings of the studies so far from the REST-meta-MDD project.Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network,in whole-brain topological properties,in dynamic features,and in functional lat-eralization.These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research.Following these fruitful explorations,DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations.A state-of-the-art,surface-based preprocessing pipeline has also been introduced to improve sensitivity.Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diag-nosis boundaries.In addition,large-scale longitudinal studies targeting brain network alterations following antidepressant treatment,aggregation of diffusion tensor images,and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway.Through these endeavours,we hope to accelerate the translation of functional neuroimaging findings to clinical use,such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets,while building an open repository for the scientific community.

Neuroimaging brain growth charts:A road to mental health

Mental disorders are common health concerns and contribute to a heavy global burden on our modern society.It is challenging to identify and treat them timely.Neuroimaging evidence suggests the incidence of various psychiatric and behavioral disorders is closely related to the atypical development of brain structure and function.The identification and understanding of atypical brain development provide chances for clinicians to detect mental disorders earlier,perhaps even prior to onset,and treat them more precisely.An invaluable and necessary method in identifying and monitoring atypical brain development are growth charts of typically developing individuals in the population.The brain growth charts can offer a series of standard references on typical neurodevelopment,representing an important resource for the scientific and medical communities.In the present paper,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.

Functional brain network mapping with dual regression

Functional magnetic resonance imaging（fMRI）is an in-vivo non-invasive technique for measuring brain activity with excellent spatial and good temporal resolution.Without performing explicit tasks,resting-state fMRI（rfMRI）is widely used to map the functional connectivity network（FCN）,which refers to a large-scale network of interdependent or functionally connected brain regions and it could be detected by using different algorithms（Zuo and Xing, 2014）.ciation CAS （2016084）, Guangxi Bagui Scholarship, the Natural Science Foundation of China （81471740, 81220108014）, the Major Project of National Social Science Foundation of China （14ZDB161）, Beijing Municipal Science and Tech Commission （Z161100002616023, Z161100000216152） and the National R＆D Infrastructure and Facility Development Program ＂Fundamental Science Data Sharing Platform＂ （DKA2017-12-02-21）.