In contrast to neurons, the role of astro-cytes has been matter of debate since their discovery, and mostly because of misconceptions about their role. As a consequence, technologies to study brain physiology have be...In contrast to neurons, the role of astro-cytes has been matter of debate since their discovery, and mostly because of misconceptions about their role. As a consequence, technologies to study brain physiology have been designed around neurons, to answer one specifc question, leaving glia experts with the only possibility to “hack” these techniques to describe astrocytes. As questions to answer about astrocytic functioning are based on factual observations, conclusions are often vague and cryptic, no matter how technically sound the work is. For instance, compelling evidence on calcium elevations has been provided, their dynamics have been studied in detail, but their role is still open for interpretation. Another as-trocytic feature that carries a lot of mysteries is their com-plex morphology. The use of three-dimensional electron microscopy （3DEM） would most certainly be the best approach to unveil hidden features of such complex cells, nevertheless so far 3DEM hasn’t been fully exploited in that sense, nor techniques has been adapted for astrocytic observations in particular. One of the most ambitious neuroscience projects, the connectome, is pushing to their limits electron microscopy, image segmentation and 3D reconstruction and analysis, making it a very good candi-date to adapt pipelines and methodologies to the study of astrocytic morphology. Here, we briefy review our current knowledge and technical state of art on 3D glia morphology, and speculate about its future directions.展开更多
近日,《临床心身疾病杂志》主编、河南省生物精神病学重点实验室吕路线教授团队在国际知名期刊《Translational Psychiatry》上发表题为《Prediction of Antipsychotic Drug Efficacy for Schizophrenia Treatment Based on Neural Feat...近日,《临床心身疾病杂志》主编、河南省生物精神病学重点实验室吕路线教授团队在国际知名期刊《Translational Psychiatry》上发表题为《Prediction of Antipsychotic Drug Efficacy for Schizophrenia Treatment Based on Neural Features of the Resting-State Functional Connectome》的研究论文。展开更多
Alzheimer＇s disease （AD） is the most common type of dementia, comprising an estimated 60-80% of all dementia cases. It is clinically characterized by impairments of memory and other cognitive functions. Previous st...Alzheimer＇s disease （AD） is the most common type of dementia, comprising an estimated 60-80% of all dementia cases. It is clinically characterized by impairments of memory and other cognitive functions. Previous studies have demonstrated that these impairments are associated with abnormal structural and functional connections among brain regions, leading to a disconnection concept of AD. With the advent of a combination of non-invasive neuroimaging （structural magnetic resonance imaging （MRI）, diffusion MRI, and functional MRI） and neurophysiological techniques （electroencephalography and magnetoencephaJography） with graph theoretical analysis, recent studies have shown that patients with AD and mild cognitive impairment （MCI）, the prodromal stage of AD, exhibit disrupted topological organization in large-scale brain networks （i.e., connectomics） and that this disruption is significantly correlated with the decline of cognitive functions. In this review, we summarize the recent progress of brain connectomics in AD and MCI, focusing on the changes in the topological organization of large-scale structural and functional brain networks using graph theoretical approaches. Based on the two different perspectives of information segregation and integration, the literature reviewed here suggests that AD and MCI are associated with disrupted segregation and integration in brain networks. Thus, these connectomics studies open up a new window for understanding the pathophysiological mechanisms of AD and demonstrate the potential to uncover imaging biomarkers for clinical diagnosis and treatment evaluation for this disease.展开更多
The zona incerta(ZI)is involved in various functions and may serve as an integrative node of the circuits for global behavioral modulation.However,the long-range connectivity of different sectors in the mouse ZI has n...The zona incerta(ZI)is involved in various functions and may serve as an integrative node of the circuits for global behavioral modulation.However,the long-range connectivity of different sectors in the mouse ZI has not been comprehensively mapped.Here,we obtained whole-brain images of the input and output connections via fluorescence micro-optical sectioning tomography and viral tracing.The principal regions in the input-output circuits of ZI GABAergic neurons were topologically organized.The 3D distribution of cortical inputs showed rostro-caudal correspondence with different ZI sectors,while the projection fibers from ZI sectors were longitudinally organized in the superior colliculus.Clustering results show that the medial and lateral ZI are two different major functional compartments,and they can be further divided into more subdomains based on projection and input connectivity.This study provides a comprehensive anatomical foundation for understanding how the ZI is involved in integrating different information,conveying motivational states,and modulating global behaviors.展开更多
OBJECTIVE Major depressive disorder(MDD) is a highly heterogeneous mental illness.Further classification may help characterize its heterogeneity.The purpose of this study was to examine metabolomic and brain connectom...OBJECTIVE Major depressive disorder(MDD) is a highly heterogeneous mental illness.Further classification may help characterize its heterogeneity.The purpose of this study was to examine metabolomic and brain connectomic associations with traditional Chinese medicine(TCM) diagnostic classification of MDD.METHODS Fifty unmedicated depressed patients were classified into Liver Qi Stagnation(LQS,n=30) and Heart and Spleen Deficiency(HSD,n=20) subtypes according to TCM diagnosis.Healthy volunteers(n=28) were included as controls.Gas chromatography-mass spectrometry(GC-MS) and diffusion tensor imaging were used to detect serum and urinary metabolomic profiles and whole-brain white matter connectivity,respectively.RESULTS In metabolomic analysis,28 metabolites were identified for good separations between TCM subtypes and healthy controls in serum and urine samples.While both TCM subtypes had similar profiles in proteinogenic branched-chain amino acids and energy metabolism-related metabolites that were differentiated from healthy controls,the LQS subtype additionally differed from healthy controls in multiple amino acid metabolites that are involved in the biosynthesis of monoamine and amino acid neurotransmitters.Several metabolites are differentially associated with the two subtypes.In connectomic analysis,The LQS subtype showed significant differences in multiple network metrics of the angular gyrus,middle occipital gyrus,calcarine sulcus,and Heschl′ s gyrus when compared to the other two groups.The HSD subtype had markedly greater regional connectivity of the insula,parahippocampal gyrus,and posterior cingulate gyrus than the other two groups,and microstructural abnormalities of the frontal medial orbital gyrus and middle temporal pole.The insular betweenness centrality was strongly inversely correlated with the severity of depression and dichotomized the two subtypes at the optimal cutoff value with acceptable sensitivity and specificity.CONCLUSION The LQS subtype may represent an MDD subpopulation mainly characterized by abnormalities in the biosynthesis of monoamine and amino acid neurotransmitters,closer associations with stress-related pathophysiology,and aberrant connectivity of the audiovisual perception-related temporal-occipital network,whereas the HSD subtype is more closely associated with hyperconnectivity and microstructural abnormalities of the limbicparalimbic network.Certain metabolomic and connectomic variables are potential biomarkers for TCM diagnostic subtypes which is perhaps an alternative classification for depressive disorders.展开更多
Chinese,as a logographic language,fundamentally differs from alphabetic languages like English.Previous neuroimaging studies have mainly focused on alphabetic languages,while the exploration of Chinese reading is stil...Chinese,as a logographic language,fundamentally differs from alphabetic languages like English.Previous neuroimaging studies have mainly focused on alphabetic languages,while the exploration of Chinese reading is still an emerging and fast-growing research field.Recently,a growing number of neuroimaging studies have explored the neural circuit of Chinese reading.Here,we summarize previous research on Chinese reading from a connectomic perspective.Converging evidence indicates that the left middle frontal gyrus is a specialized hub region that connects the ventral with dorsal pathways for Chinese reading.Notably,the orthography-to-phonology and orthography-to-semantics mapping,mainly processed in the ventral pathway,are more specific during Chinese reading.Besides,in addition to the left-lateralized language-related regions,reading pathways in the right hemisphere also play an important role in Chinese reading.Throughout,we comprehensively review prior findings and emphasize several challenging issues to be explored in future work.展开更多
Traumatic brain injury survivors often experience cognitive deficits and neuropsychiatric symptoms.However,the neurobiological mechanisms underlying specific impairments are not fully understood.Advances in neuroimagi...Traumatic brain injury survivors often experience cognitive deficits and neuropsychiatric symptoms.However,the neurobiological mechanisms underlying specific impairments are not fully understood.Advances in neuroimaging techniques（such as diffusion tensor imaging and functional MRI）have given us new insights on structural and functional connectivity patterns of the human brain in both health and disease.The connectome derived from connectivity maps reflects the entire constellation of distributed brain networks.Using these powerful neuroimaging approaches,changes at the microstructural level can be detected through regional and global properties of neuronal networks.Here we will review recent developments in the study of brain network abnormalities in traumatic brain injury,mainly focusing on structural and functional connectivity.Some connectomic studies have provided interesting insights into the neurological dysfunction that occurs following traumatic brain injury.These techniques could eventually be helpful in developing imaging biomarkers of cognitive and neurobehavioral sequelae,as well as predicting outcome and prognosis.展开更多
Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer＇s disease, and brain network-connection strength, networ...Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer＇s disease, and brain network-connection strength, network efficiency, and nodal attributes are abnormal. However, existing research has only analyzed the differences between these patients and normal controls. In this study, we constructed brain networks using resting-state functional MRI data that was extracted from four populations （nor- mal controls, patients with early mild cognitive impairment, patients with late mild cognitive impairment, and patients with Alzheimer＇s disease） using the Alzheimer＇s Disease Neuroimaging Initiative data set. The aim was to analyze the characteristics of resting-state functional neural networks, and to observe mild cognitive impairment at different stages before the transformation to Alzheimer＇s disease. Results showed that as cognitive deficits increased across the four groups, the shortest path in the rest- ing-state functional network gradually increased, while clustering coefficients gradually decreased. This evidence indicates that dementia is associated with a decline of brain network efficiency. In addi- tion, the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and AIz- heimer＇s disease. The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions, and we speculate that early impairments in memory, hearing, and language function can eventually lead to diffuse brain injury and other cognitive impairments.展开更多
The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons.Precise dissection of neural circuits at the mesoscopic level can provide important structural in...The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons.Precise dissection of neural circuits at the mesoscopic level can provide important structural information for understanding the brain.Optical approaches can achieve submicron lateral resolution and achieve“optical sectioning”by a variety of means,which has the natural advantage of allowing the observation of neural circuits at the mesoscopic level.Automated whole-brain optical imaging methods based on tissue clearing or histological sectioning surpass the limitation of optical imaging depth in biological tissues and can provide delicate structural information in a large volume of tissues.Combined with various fluorescent labeling techniques,whole-brain optical imaging methods have shown great potential in the brain-wide quantitative profiling of cells,circuits,and blood vessels.In this review,we summarize the principles and implementations of various whole-brain optical imaging methods and provide some concepts regarding their future development.展开更多
Functional hubs with disproportionately extensive connectivities play a crucial role in global information integration in human brain networks.However,most resting-state functional magnetic resonance imaging(R-fMRI)st...Functional hubs with disproportionately extensive connectivities play a crucial role in global information integration in human brain networks.However,most resting-state functional magnetic resonance imaging(R-fMRI)studies have identified functional hubs by examining spontaneous fluctuations of the blood oxygen level-dependent signal within a typical low-frequency band(e.g.,0.01–0.08 Hz or 0.01–0.1 Hz).Little is known about how the spatial distributions of functional hubs depend on frequency bands of interest.Here,we used repeatedly measured R-fMRI data from 53 healthy young adults and a degree centrality analysis to identify voxelwise frequency-resolved functional hubs and further examined their test-retest reliability across two sessions.We showed that a wide-range frequency band(0.01–0.24 Hz)accessible with a typical sampling rate(fsample=0.5 Hz)could be classified into three frequency bands with distinct patterns,namely,low-frequency(LF,0.01–0.06 Hz),middle-frequency(MF,0.06–0.16 Hz),and high-frequency(HF,0.16–0.24 Hz)bands.The functional hubs were mainly located in the medial and lateral frontal and parietal cortices in the LF band,and in the medial prefrontal cortex,superior temporal gyrus,parahippocampal gyrus,amygdala,and several cerebellar regions in the MF and HF bands.These hub regions exhibited fair to good test-retest reliability,regardless of the frequency band.The presence of the three frequency bands was well replicated using an independent R-fMRI dataset from 45 healthy young adults.Our findings demonstrate reliable frequency-resolved functional connectivity hubs in three categories,thus providing insights into the frequency-specific connectome organization in healthy and disordered brains.展开更多
The increasing number of long-term survivors of pediatric brain tumors requires us to incorporate the most recent knowledge derived from cognitive neuroscience into their oncological treatment.As the lesion itself,as ...The increasing number of long-term survivors of pediatric brain tumors requires us to incorporate the most recent knowledge derived from cognitive neuroscience into their oncological treatment.As the lesion itself,as well as each treatment,can cause specific neural damage,the long-term neurocognitive outcomes are highly complex and challenging to assess.The number of neurocognitive studies in this population grows exponentially worldwide,motivating modern neuroscience to provide guidance in follow-up before,during and after treatment.In this review,we provide an overview of structural and functional brain connectomes and their role in the neuropsychological outcomes of specific brain tumor types.Based on this information,we propose a theoretical neuroscientific framework to apply appropriate neuropsychological and imaging follow-up for future clinical care and rehabilitation trials.展开更多
Conscious agency is considered to be founded upon a quantum state of mind . An original synthesis, called “Lithium Quantum Consciousness” (LQC), proposes that this quantum state utilises lithium-6 (spin-1) qutrit nu...Conscious agency is considered to be founded upon a quantum state of mind . An original synthesis, called “Lithium Quantum Consciousness” (LQC), proposes that this quantum state utilises lithium-6 (spin-1) qutrit nuclear magnetic resonance (NMR) quantum information processing (QIP) in the connectome (brain-graph). In parallel to the connectome’s processing of physiological controls, perception, cognition and intelligence via quantum electrodynamics (QED), the connectome also functions via its dynamic algebraic topology as a unitary transceiver antenna laced with lithium-6 nuclei which are spin-entangled with each other and with the environmental vortical gluon field via quantum chromodynamics (QCD). This unitary antenna (connectome) bestows the self its unity of consciousness within an intertwined-history multi-agent environment. An equivalence is proposed between Whitehead’s occasions of experience and topological spacetime instantons in the vortical gluon field. Topological spacetime instantons pervade the vortical gluon field in a quantum information network of vortex interactions, herein termed the “instanton-net”, or “Instanet” [sic]. The fermionic isotope lithium-6 has a very low nuclear binding energy and the smallest non-zero nuclear electric quadrupole moment of any stable nucleus making it susceptible to quantum chromodynamic (QCD) interaction with the vortical gluon field and ideal for spin-1 qutrit NMR-QIP. The compact spherical atomic orbital of lithium provides ideal rotational freedom inside tetrahedral water cages in organo6Li+(H2O)4 within which the lithium nucleus rapidly tumbles for NMR motional narrowing and long decoherence times. Nuclear spin-entanglement, among water-caged lithium-6 nuclei in the connectome, is a spin-1 qutrit NMR-QIP resource for conscious agency. By contrast, similar tetrahedral xenon cages in organo6Li+Xe4 excimers are postulated to decohere the connectome’s NMR-QIP due to xenon’s NMR signal being extremely sensitive to its molecular environment. By way of this quantum neurochemistry, lithium is an effective psychiatric medication for enhancing mood and xenon is an effective anaesthetic.展开更多
The structural and functional connectomes interact and depend on each other to jointly maintain the functioning of the brain and further support cognitive processing.Elucidating the complex interplay between the struc...The structural and functional connectomes interact and depend on each other to jointly maintain the functioning of the brain and further support cognitive processing.Elucidating the complex interplay between the structural connectome(SC)and functional connectome(FC)is one of the central challenges in network neuroscience.While previous studies have consistently reported SC-FC coupling or SC constraints on FC[1],[2],[3],they typically analyzed these networks in isolation.展开更多
Alzheimer’s disease(AD)is a common neurodegenerative disorder nowadays.Amyloid-beta(Aβ)and tau proteins are among the main contributors to the AD progression.In AD,Aβproteins clump together to form plaques and disr...Alzheimer’s disease(AD)is a common neurodegenerative disorder nowadays.Amyloid-beta(Aβ)and tau proteins are among the main contributors to the AD progression.In AD,Aβproteins clump together to form plaques and disrupt cell functions.On the other hand,the abnormal chemical change in the brain helps to build sticky tau tangles that block the neuron’s transport system.Astrocytes generally maintain a healthy balance in the brain by clearing the Aβplaques(toxic Aβ).However,overactivated astrocytes release chemokines and cytokines in the presence of Aβand react to pro-inflammatory cytokines,further increasing the production of Aβ.In this study,we construct a mathematical model that can capture astrocytes’dual behavior.Furthermore,we reveal that the disease progression depends on the current time instance and the disease’s earlier status,called theamemory effect,omaking non-Markovian processes an appropriate approach.We consider a fractional order network mathematical model to capture the influence of such memory effects on AD progression.We have integrated brain connectome data into the model and studied the memory effect,the dual role of astrocytes,and the brain’s neuronal damage.Based on the pathology,primary,secondary,and mixed tauopathies parameters are considered in the model.Due to the mixed tauopathy,different brain nodes or regions in the brain connectome accumulate different toxic concentrations of Aβand tau proteins.Finally,we explain how the memory effect can slow down the propagation of such toxic proteins in the brain,decreasing the rate of neuronal damage.展开更多
Objective:There is increasing evidence that amyotrophic lateral sclerosis(ALS)is a progressive neurodegenerative disease impacting large-scale brain networks.However,it is still unclear which structural networks are a...Objective:There is increasing evidence that amyotrophic lateral sclerosis(ALS)is a progressive neurodegenerative disease impacting large-scale brain networks.However,it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression.This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate.Methods:Magnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire difusion-weighted magnetic resonance images and construct white matter(WM)networks using tractography methods.The global and regional network properties were compared between ALS and healthy subjects.The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms.Results:Compared with the healthy participants,the patients with ALS showed signifcantly decreased clustering coefcient C_(p)(P=0.0034,t=2.98),normalized clustering coefcientγ(P=0.039,t=2.08),and small‐worldnessσ(P=0.038,t=2.10)at the global network level.The patients also showed decreased regional centralities in motor and non-motor systems including the frontal,temporal and subcortical regions.Using the single-subject structural connection matrix,our classifcation model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%.Conclusion:Disruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems,extending the classical pathophysiological understanding of ALS as a motor disorder.The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.展开更多
Background:Amyotrophic lateral sclerosis(ALS)is a disease characterized by a progressive degeneration of motor neurons leading to paralysis.Our previous MRI diffusion tensor imaging studies detected early white matter...Background:Amyotrophic lateral sclerosis(ALS)is a disease characterized by a progressive degeneration of motor neurons leading to paralysis.Our previous MRI diffusion tensor imaging studies detected early white matter changes in the spinal cords of mice carrying the G93A-SOD1 mutation.Here,we extend those studies using ultra-high field MRI(17.6 T)and fluorescent microscopy to investigate the appearance of early structural and connectivity changes in the spinal cords of ALS mice.Methods:The spinal cords from presymptomatic and symptomatic mice(80 to 120 days of age)were scanned(ex-vivo)using diffusion-weighted MRI.The fractional anisotropy(FA),axial(AD)and radial(RD)diffusivities were calculated for axial slices from the thoracic,cervical and lumbar regions of the spinal cords.The diffusion parameters were compared with fluorescence microscopy and membrane cellular markers from the same tissue regions.Results:At early stages of the disease(day 80)in the lumbar region,we found,a 19% decrease in FA,a 9% decrease in AD and a 35% increase in RD.Similar changes were observed in cervical and thoracic spinal cord regions.Differences between control and ALS mice groups at the symptomatic stages(day 120)were larger.Quantitative fluorescence microscopy at 80 days,demonstrated a 22% reduction in axonal area and a 22% increase in axonal density.Tractography and quantitative connectome analyses measured by edge weights showed a 52%decrease in the lumbar regions of the spinal cords of this ALS mice group.A significant increase in ADC(23.3%)in the ALS mice group was related to an increase in aquaporin markers.Conclusions:These findings suggest that the combination of ultra-high field diffusion MRI with fluorescent ALS mice reporters is a useful approach to detect and characterize presymptomatic white matter micro-ultrastructural changes and axonal connectivity anomalies in ALS.展开更多
Attention-deficit/hyperactivity disorder(ADHD)has been conceptualized as a brain dysconnectivity disorder.In the past decade,noninvasive diffusion magnetic resonance imaging(dMRI)studies have demonstrated that individ...Attention-deficit/hyperactivity disorder(ADHD)has been conceptualized as a brain dysconnectivity disorder.In the past decade,noninvasive diffusion magnetic resonance imaging(dMRI)studies have demonstrated that individuals with ADHD have alterations in the white matter structural connectome,and that these alterations are associated with core symptoms and cognitive deficits in patients.This review aims to summarize recent dMRI-based structural connectome studies in ADHD from voxel-,tractography-,and network-based perspectives.Voxel-and tractography-based studies have demonstrated disrupted microstructural properties predominantly located in the frontostriatal tracts,the corpus callosum,the corticospinal tracts,and the cingulum bundle in patients with ADHD.Network-based studies have suggested abnormal global and local efficiency as well as nodal properties in the prefrontal and parietal regions in the ADHD structural connectomes.The altered structural connectomes in those with ADHD provide significant signatures for prediction of symptoms and diagnostic classification.These studies suggest that abnormalities in the structural connectome may be one of the neural underpinnings of ADHD psychopathology and show potential for establishing imaging biomarkers in clinical evaluation.However,given that there are inconsistent findings across studies due to sample heterogeneity and analysis method variations,these ADHD-related white matter alterations are still far from informing clinical practice.Future studies with larger and more homogeneous samples are needed to validate the consistency of current results;advanced dMRI techniques can help to generatemuchmore precise estimation of whitematter pathways and assure specific fiber configurations;and finally,dimensional analysis frameworks can deepen our understanding of the neurobiology underlying ADHD.展开更多
Psychiatric disorders are a pressing public health challenge,posing a significant threat to the well-being of millions of people worldwide.Their elusive etiology,rooted in the complex interplay of genetic,environmenta...Psychiatric disorders are a pressing public health challenge,posing a significant threat to the well-being of millions of people worldwide.Their elusive etiology,rooted in the complex interplay of genetic,environmental,and neural factors,requires innovative research approaches.The advent of advanced neuroimaging techniques and connectomics marks a transformative era,enabling researchers to delve into the structural and functional networks of the human brain.This transformation is underscored by the establishment of large brain datasets and a growing body of published findings,heralding a new era in neuroscience research that is poised to reshape our understanding of psychiatric disorders.Here,we review recent advances in connectome and neuroimaging big data in psychiatric disorders.First,we highlight several multisite neuroimaging datasets that hold immense potential for groundbreaking discoveries in understanding the intricate structural and functional network architecture of various psychiatric disorders.We then present innovative methods for multicenter and multidimensional data analysis,particularly connectome-based meta-analytic and multivariate analysis methods.Furthermore,we demonstrate the critical value of these methods in synthesizing findings from diverse published works or multisite data,and in exploring connectomics associations with demographics,symptomatology,behavioral and cognitive metrics,and genetic data in psychiatric disorders.Finally,we discuss the emerging issues and challenges that urgently need to be addressed in the field and that will shape the future trajectory of psychiatric research.展开更多
Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network,capturing a functional spectrum that ranges from perception and action to abstract cognition.However,how...Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network,capturing a functional spectrum that ranges from perception and action to abstract cognition.However,how this gradient pattern develops and whether its development is linked to cognitive growth,topological reorganization,and gene expression profiles remain largely unknown.Using longitudinal resting-state functional magnetic resonance imaging data from 305 children(aged 6-14 years),we describe substantial changes in the primary-to-transmodal gradient between childhood and adolescence,including emergence as the principal gradient,expansion of global topography,and focal tuning in primary and default-mode regions.These gradient changes are mediated by developmental changes in network integration and segregation,and are associated with abstract processing functions such as working memory and expression levels of calcium ion regulated exocytosis and synaptic transmission-related genes.Our findings have implications for understanding connectome maturation principles in normal development and developmental disorders.展开更多
Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an effi...Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an efficient, robust, reliable and easy-to-use pipeline to mine such large neuroscience datasets. Here, we introduce a computational pipeline--namely the Connectome Compu- tation System （CCS）-for discovery science of human brain connectomes at the macroscale with multimodal magnetic resonance imaging technologies. The CCS is designed with a three-level hierarchical structure that includes data cleaning and preprocessing, individual connectome mapping andconnectome mining, and knowledge discovery. Several functional modules are embedded into this hierarchy to implement quality control procedures, reliability analysis and connectome visualization. We demonstrate the utility of the CCS based upon a publicly available dataset, the NKI- Rockland Sample, to delineate the normative trajectories of well-known large-scale neural networks across the natural life span （6-85 years of age）. The CCS has been made freely available to the public via GitHub （https：//github.com/ zuoxinian/CCS） and our laboratory＇s Web site （http：//lfcd. psych.ac.cn/ccs.html） to facilitate progress in discovery science in the field of human brain connectomics.展开更多
文摘In contrast to neurons, the role of astro-cytes has been matter of debate since their discovery, and mostly because of misconceptions about their role. As a consequence, technologies to study brain physiology have been designed around neurons, to answer one specifc question, leaving glia experts with the only possibility to “hack” these techniques to describe astrocytes. As questions to answer about astrocytic functioning are based on factual observations, conclusions are often vague and cryptic, no matter how technically sound the work is. For instance, compelling evidence on calcium elevations has been provided, their dynamics have been studied in detail, but their role is still open for interpretation. Another as-trocytic feature that carries a lot of mysteries is their com-plex morphology. The use of three-dimensional electron microscopy （3DEM） would most certainly be the best approach to unveil hidden features of such complex cells, nevertheless so far 3DEM hasn’t been fully exploited in that sense, nor techniques has been adapted for astrocytic observations in particular. One of the most ambitious neuroscience projects, the connectome, is pushing to their limits electron microscopy, image segmentation and 3D reconstruction and analysis, making it a very good candi-date to adapt pipelines and methodologies to the study of astrocytic morphology. Here, we briefy review our current knowledge and technical state of art on 3D glia morphology, and speculate about its future directions.
文摘近日,《临床心身疾病杂志》主编、河南省生物精神病学重点实验室吕路线教授团队在国际知名期刊《Translational Psychiatry》上发表题为《Prediction of Antipsychotic Drug Efficacy for Schizophrenia Treatment Based on Neural Features of the Resting-State Functional Connectome》的研究论文。
基金supported by National Key Basic Research Program of China(2014CB846102)Natural Science Foundation of China(81030028 and 31221003)+1 种基金Beijing Natural Science Foundation(Z111107067311036)National Science Fund for Distinguished Young Scholars(81225012)
文摘Alzheimer＇s disease （AD） is the most common type of dementia, comprising an estimated 60-80% of all dementia cases. It is clinically characterized by impairments of memory and other cognitive functions. Previous studies have demonstrated that these impairments are associated with abnormal structural and functional connections among brain regions, leading to a disconnection concept of AD. With the advent of a combination of non-invasive neuroimaging （structural magnetic resonance imaging （MRI）, diffusion MRI, and functional MRI） and neurophysiological techniques （electroencephalography and magnetoencephaJography） with graph theoretical analysis, recent studies have shown that patients with AD and mild cognitive impairment （MCI）, the prodromal stage of AD, exhibit disrupted topological organization in large-scale brain networks （i.e., connectomics） and that this disruption is significantly correlated with the decline of cognitive functions. In this review, we summarize the recent progress of brain connectomics in AD and MCI, focusing on the changes in the topological organization of large-scale structural and functional brain networks using graph theoretical approaches. Based on the two different perspectives of information segregation and integration, the literature reviewed here suggests that AD and MCI are associated with disrupted segregation and integration in brain networks. Thus, these connectomics studies open up a new window for understanding the pathophysiological mechanisms of AD and demonstrate the potential to uncover imaging biomarkers for clinical diagnosis and treatment evaluation for this disease.
基金National Natural ScienceFoundation of China(61890953 and 31871088)the Chinese Academy of Medical Sciences Innovation Fund forMedical Sciences(2019-12M-5-014)the Director Fund of Wuhan National Laboratory for Optoelectronics.
文摘The zona incerta(ZI)is involved in various functions and may serve as an integrative node of the circuits for global behavioral modulation.However,the long-range connectivity of different sectors in the mouse ZI has not been comprehensively mapped.Here,we obtained whole-brain images of the input and output connections via fluorescence micro-optical sectioning tomography and viral tracing.The principal regions in the input-output circuits of ZI GABAergic neurons were topologically organized.The 3D distribution of cortical inputs showed rostro-caudal correspondence with different ZI sectors,while the projection fibers from ZI sectors were longitudinally organized in the superior colliculus.Clustering results show that the medial and lateral ZI are two different major functional compartments,and they can be further divided into more subdomains based on projection and input connectivity.This study provides a comprehensive anatomical foundation for understanding how the ZI is involved in integrating different information,conveying motivational states,and modulating global behaviors.
基金National Natural Science Foundation of China(81403502)General Research Fund ofResearch Grants Council of Hong Kong (17124418).
文摘OBJECTIVE Major depressive disorder(MDD) is a highly heterogeneous mental illness.Further classification may help characterize its heterogeneity.The purpose of this study was to examine metabolomic and brain connectomic associations with traditional Chinese medicine(TCM) diagnostic classification of MDD.METHODS Fifty unmedicated depressed patients were classified into Liver Qi Stagnation(LQS,n=30) and Heart and Spleen Deficiency(HSD,n=20) subtypes according to TCM diagnosis.Healthy volunteers(n=28) were included as controls.Gas chromatography-mass spectrometry(GC-MS) and diffusion tensor imaging were used to detect serum and urinary metabolomic profiles and whole-brain white matter connectivity,respectively.RESULTS In metabolomic analysis,28 metabolites were identified for good separations between TCM subtypes and healthy controls in serum and urine samples.While both TCM subtypes had similar profiles in proteinogenic branched-chain amino acids and energy metabolism-related metabolites that were differentiated from healthy controls,the LQS subtype additionally differed from healthy controls in multiple amino acid metabolites that are involved in the biosynthesis of monoamine and amino acid neurotransmitters.Several metabolites are differentially associated with the two subtypes.In connectomic analysis,The LQS subtype showed significant differences in multiple network metrics of the angular gyrus,middle occipital gyrus,calcarine sulcus,and Heschl′ s gyrus when compared to the other two groups.The HSD subtype had markedly greater regional connectivity of the insula,parahippocampal gyrus,and posterior cingulate gyrus than the other two groups,and microstructural abnormalities of the frontal medial orbital gyrus and middle temporal pole.The insular betweenness centrality was strongly inversely correlated with the severity of depression and dichotomized the two subtypes at the optimal cutoff value with acceptable sensitivity and specificity.CONCLUSION The LQS subtype may represent an MDD subpopulation mainly characterized by abnormalities in the biosynthesis of monoamine and amino acid neurotransmitters,closer associations with stress-related pathophysiology,and aberrant connectivity of the audiovisual perception-related temporal-occipital network,whereas the HSD subtype is more closely associated with hyperconnectivity and microstructural abnormalities of the limbicparalimbic network.Certain metabolomic and connectomic variables are potential biomarkers for TCM diagnostic subtypes which is perhaps an alternative classification for depressive disorders.
基金supported by the Natural Science Foundation of China(81901826 and 61932008)the Natural Science Foundation of Shanghai(19ZR1405600 and 20ZR1404900)the Shanghai Municipal Science and Technology Major Project(2018SHZDZX01)。
文摘Chinese,as a logographic language,fundamentally differs from alphabetic languages like English.Previous neuroimaging studies have mainly focused on alphabetic languages,while the exploration of Chinese reading is still an emerging and fast-growing research field.Recently,a growing number of neuroimaging studies have explored the neural circuit of Chinese reading.Here,we summarize previous research on Chinese reading from a connectomic perspective.Converging evidence indicates that the left middle frontal gyrus is a specialized hub region that connects the ventral with dorsal pathways for Chinese reading.Notably,the orthography-to-phonology and orthography-to-semantics mapping,mainly processed in the ventral pathway,are more specific during Chinese reading.Besides,in addition to the left-lateralized language-related regions,reading pathways in the right hemisphere also play an important role in Chinese reading.Throughout,we comprehensively review prior findings and emphasize several challenging issues to be explored in future work.
基金supported by a grant from the Medical Scientific Research Programs of Nanjing Military Command,No.14MS122
文摘Traumatic brain injury survivors often experience cognitive deficits and neuropsychiatric symptoms.However,the neurobiological mechanisms underlying specific impairments are not fully understood.Advances in neuroimaging techniques（such as diffusion tensor imaging and functional MRI）have given us new insights on structural and functional connectivity patterns of the human brain in both health and disease.The connectome derived from connectivity maps reflects the entire constellation of distributed brain networks.Using these powerful neuroimaging approaches,changes at the microstructural level can be detected through regional and global properties of neuronal networks.Here we will review recent developments in the study of brain network abnormalities in traumatic brain injury,mainly focusing on structural and functional connectivity.Some connectomic studies have provided interesting insights into the neurological dysfunction that occurs following traumatic brain injury.These techniques could eventually be helpful in developing imaging biomarkers of cognitive and neurobehavioral sequelae,as well as predicting outcome and prognosis.
基金sponsored by the National Natural Science Foundation of China,No.61070077,61170136,61373101the Natural Science Foundation of Shanxi Province,No.2011011015-4Beijing Postdoctoral Science Foundation,No.Q6002020201201
文摘Brain structure and cognitive function change in the temporal lobe, hippocampus, and prefrontal cortex of patients with mild cognitive impairment and Alzheimer＇s disease, and brain network-connection strength, network efficiency, and nodal attributes are abnormal. However, existing research has only analyzed the differences between these patients and normal controls. In this study, we constructed brain networks using resting-state functional MRI data that was extracted from four populations （nor- mal controls, patients with early mild cognitive impairment, patients with late mild cognitive impairment, and patients with Alzheimer＇s disease） using the Alzheimer＇s Disease Neuroimaging Initiative data set. The aim was to analyze the characteristics of resting-state functional neural networks, and to observe mild cognitive impairment at different stages before the transformation to Alzheimer＇s disease. Results showed that as cognitive deficits increased across the four groups, the shortest path in the rest- ing-state functional network gradually increased, while clustering coefficients gradually decreased. This evidence indicates that dementia is associated with a decline of brain network efficiency. In addi- tion, the changes in functional networks revealed the progressive deterioration of network function across brain regions from healthy elderly adults to those with mild cognitive impairment and AIz- heimer＇s disease. The alterations of node attributes in brain regions may reflect the cognitive functions in brain regions, and we speculate that early impairments in memory, hearing, and language function can eventually lead to diffuse brain injury and other cognitive impairments.
基金supported by the STI2030-Major Projects(2021ZD0201001 and 2021ZD0201000)the National Natural Science Foundation of China(81827901 and 32192412).
文摘The mammalian brain is a highly complex network that consists of millions to billions of densely-interconnected neurons.Precise dissection of neural circuits at the mesoscopic level can provide important structural information for understanding the brain.Optical approaches can achieve submicron lateral resolution and achieve“optical sectioning”by a variety of means,which has the natural advantage of allowing the observation of neural circuits at the mesoscopic level.Automated whole-brain optical imaging methods based on tissue clearing or histological sectioning surpass the limitation of optical imaging depth in biological tissues and can provide delicate structural information in a large volume of tissues.Combined with various fluorescent labeling techniques,whole-brain optical imaging methods have shown great potential in the brain-wide quantitative profiling of cells,circuits,and blood vessels.In this review,we summarize the principles and implementations of various whole-brain optical imaging methods and provide some concepts regarding their future development.
基金The study was supported by the National Key R&D Program of China(2018YFA0701402)the National Natural Science Foundation of China(82021004,81971690,81620108016,and 11835003)the Fundamental Research Funds for the Central Universities of China(2019NTST24).
文摘Functional hubs with disproportionately extensive connectivities play a crucial role in global information integration in human brain networks.However,most resting-state functional magnetic resonance imaging(R-fMRI)studies have identified functional hubs by examining spontaneous fluctuations of the blood oxygen level-dependent signal within a typical low-frequency band(e.g.,0.01–0.08 Hz or 0.01–0.1 Hz).Little is known about how the spatial distributions of functional hubs depend on frequency bands of interest.Here,we used repeatedly measured R-fMRI data from 53 healthy young adults and a degree centrality analysis to identify voxelwise frequency-resolved functional hubs and further examined their test-retest reliability across two sessions.We showed that a wide-range frequency band(0.01–0.24 Hz)accessible with a typical sampling rate(fsample=0.5 Hz)could be classified into three frequency bands with distinct patterns,namely,low-frequency(LF,0.01–0.06 Hz),middle-frequency(MF,0.06–0.16 Hz),and high-frequency(HF,0.16–0.24 Hz)bands.The functional hubs were mainly located in the medial and lateral frontal and parietal cortices in the LF band,and in the medial prefrontal cortex,superior temporal gyrus,parahippocampal gyrus,amygdala,and several cerebellar regions in the MF and HF bands.These hub regions exhibited fair to good test-retest reliability,regardless of the frequency band.The presence of the three frequency bands was well replicated using an independent R-fMRI dataset from 45 healthy young adults.Our findings demonstrate reliable frequency-resolved functional connectivity hubs in three categories,thus providing insights into the frequency-specific connectome organization in healthy and disordered brains.
基金funded by the Fonds voor Wetenschappelijk Onderzoek for a senior post-doctoral fellowship.PCF is supported by funding from the Bernard Wolfe Health Neuroscience Fund(206368/Z/17/Z)His research is also supported by the NIHR Cambridge Biomedical Research Centre(BRC-1215-20014).
文摘The increasing number of long-term survivors of pediatric brain tumors requires us to incorporate the most recent knowledge derived from cognitive neuroscience into their oncological treatment.As the lesion itself,as well as each treatment,can cause specific neural damage,the long-term neurocognitive outcomes are highly complex and challenging to assess.The number of neurocognitive studies in this population grows exponentially worldwide,motivating modern neuroscience to provide guidance in follow-up before,during and after treatment.In this review,we provide an overview of structural and functional brain connectomes and their role in the neuropsychological outcomes of specific brain tumor types.Based on this information,we propose a theoretical neuroscientific framework to apply appropriate neuropsychological and imaging follow-up for future clinical care and rehabilitation trials.
文摘Conscious agency is considered to be founded upon a quantum state of mind . An original synthesis, called “Lithium Quantum Consciousness” (LQC), proposes that this quantum state utilises lithium-6 (spin-1) qutrit nuclear magnetic resonance (NMR) quantum information processing (QIP) in the connectome (brain-graph). In parallel to the connectome’s processing of physiological controls, perception, cognition and intelligence via quantum electrodynamics (QED), the connectome also functions via its dynamic algebraic topology as a unitary transceiver antenna laced with lithium-6 nuclei which are spin-entangled with each other and with the environmental vortical gluon field via quantum chromodynamics (QCD). This unitary antenna (connectome) bestows the self its unity of consciousness within an intertwined-history multi-agent environment. An equivalence is proposed between Whitehead’s occasions of experience and topological spacetime instantons in the vortical gluon field. Topological spacetime instantons pervade the vortical gluon field in a quantum information network of vortex interactions, herein termed the “instanton-net”, or “Instanet” [sic]. The fermionic isotope lithium-6 has a very low nuclear binding energy and the smallest non-zero nuclear electric quadrupole moment of any stable nucleus making it susceptible to quantum chromodynamic (QCD) interaction with the vortical gluon field and ideal for spin-1 qutrit NMR-QIP. The compact spherical atomic orbital of lithium provides ideal rotational freedom inside tetrahedral water cages in organo6Li+(H2O)4 within which the lithium nucleus rapidly tumbles for NMR motional narrowing and long decoherence times. Nuclear spin-entanglement, among water-caged lithium-6 nuclei in the connectome, is a spin-1 qutrit NMR-QIP resource for conscious agency. By contrast, similar tetrahedral xenon cages in organo6Li+Xe4 excimers are postulated to decohere the connectome’s NMR-QIP due to xenon’s NMR signal being extremely sensitive to its molecular environment. By way of this quantum neurochemistry, lithium is an effective psychiatric medication for enhancing mood and xenon is an effective anaesthetic.
基金supported by the National Natural Science Foundation of China(82021004,82327807,and T24B2012)the Beijing Natural Science Foundation(JQ23033)the Fundamental Research Funds for the Central Universities(2233100018 and 2233300002).
文摘The structural and functional connectomes interact and depend on each other to jointly maintain the functioning of the brain and further support cognitive processing.Elucidating the complex interplay between the structural connectome(SC)and functional connectome(FC)is one of the central challenges in network neuroscience.While previous studies have consistently reported SC-FC coupling or SC constraints on FC[1],[2],[3],they typically analyzed these networks in isolation.
基金BERC 2022-2025Natural Sciences and Engineering Research Council of Canada+4 种基金Alliance de recherche numérique du CanadaCanada Research ChairsBasque Government fund AIShared Hierarchical Academic Research Computer NetworkSpanish Ministry of Science,Innovation and Universities。
文摘Alzheimer’s disease(AD)is a common neurodegenerative disorder nowadays.Amyloid-beta(Aβ)and tau proteins are among the main contributors to the AD progression.In AD,Aβproteins clump together to form plaques and disrupt cell functions.On the other hand,the abnormal chemical change in the brain helps to build sticky tau tangles that block the neuron’s transport system.Astrocytes generally maintain a healthy balance in the brain by clearing the Aβplaques(toxic Aβ).However,overactivated astrocytes release chemokines and cytokines in the presence of Aβand react to pro-inflammatory cytokines,further increasing the production of Aβ.In this study,we construct a mathematical model that can capture astrocytes’dual behavior.Furthermore,we reveal that the disease progression depends on the current time instance and the disease’s earlier status,called theamemory effect,omaking non-Markovian processes an appropriate approach.We consider a fractional order network mathematical model to capture the influence of such memory effects on AD progression.We have integrated brain connectome data into the model and studied the memory effect,the dual role of astrocytes,and the brain’s neuronal damage.Based on the pathology,primary,secondary,and mixed tauopathies parameters are considered in the model.Due to the mixed tauopathy,different brain nodes or regions in the brain connectome accumulate different toxic concentrations of Aβand tau proteins.Finally,we explain how the memory effect can slow down the propagation of such toxic proteins in the brain,decreasing the rate of neuronal damage.
基金This study was supported by the funding of 1.3.5 project for disciplines of excellence,West China Hospital,Sichuan University(ZYJC18038)the National Natural Science Foundation of China(81621003,81820108018,81871000,81761128023)+5 种基金the Program for Changjiang Scholars and Innovative Research Team in University(PCSIRT,IRT16R52)of Chinathe Changjiang Scholar Professorship Award(T2014190)of Chinathe CMB Distinguished Professorship Award(F510000/G16916411)administered by the Institute of International Educationthe China Postdoctoral Science Foundation(2019M653427),Sichuan Science and Technology Program(2020YFS0220)Post-Doctor Research Project,West China Hospital,Sichuan University(2019HXBH029)D.L.was supported by the Newton International Fellowship from the Royal Society。
文摘Objective:There is increasing evidence that amyotrophic lateral sclerosis(ALS)is a progressive neurodegenerative disease impacting large-scale brain networks.However,it is still unclear which structural networks are associated with the disease and whether the network connectomics are associated with disease progression.This study was aimed to characterize the network abnormalities in ALS and to identify the network-based biomarkers that predict the ALS baseline progression rate.Methods:Magnetic resonance imaging was performed on 73 patients with sporadic ALS and 100 healthy participants to acquire difusion-weighted magnetic resonance images and construct white matter(WM)networks using tractography methods.The global and regional network properties were compared between ALS and healthy subjects.The single-subject WM network matrices of patients were used to predict the ALS baseline progression rate using machine learning algorithms.Results:Compared with the healthy participants,the patients with ALS showed signifcantly decreased clustering coefcient C_(p)(P=0.0034,t=2.98),normalized clustering coefcientγ(P=0.039,t=2.08),and small‐worldnessσ(P=0.038,t=2.10)at the global network level.The patients also showed decreased regional centralities in motor and non-motor systems including the frontal,temporal and subcortical regions.Using the single-subject structural connection matrix,our classifcation model could distinguish patients with fast versus slow progression rate with an average accuracy of 85%.Conclusion:Disruption of the WM structural networks in ALS is indicated by weaker small-worldness and disturbances in regions outside of the motor systems,extending the classical pathophysiological understanding of ALS as a motor disorder.The individual WM structural network matrices of ALS patients are potential neuroimaging biomarkers for the baseline disease progression in clinical practice.
基金This study was supported in part by a Chicago Biomedical Consortium(CBC)postdoctoral fellowship grant(Award#085740)to RG at the University of Illinois in Chicago.
文摘Background:Amyotrophic lateral sclerosis(ALS)is a disease characterized by a progressive degeneration of motor neurons leading to paralysis.Our previous MRI diffusion tensor imaging studies detected early white matter changes in the spinal cords of mice carrying the G93A-SOD1 mutation.Here,we extend those studies using ultra-high field MRI(17.6 T)and fluorescent microscopy to investigate the appearance of early structural and connectivity changes in the spinal cords of ALS mice.Methods:The spinal cords from presymptomatic and symptomatic mice(80 to 120 days of age)were scanned(ex-vivo)using diffusion-weighted MRI.The fractional anisotropy(FA),axial(AD)and radial(RD)diffusivities were calculated for axial slices from the thoracic,cervical and lumbar regions of the spinal cords.The diffusion parameters were compared with fluorescence microscopy and membrane cellular markers from the same tissue regions.Results:At early stages of the disease(day 80)in the lumbar region,we found,a 19% decrease in FA,a 9% decrease in AD and a 35% increase in RD.Similar changes were observed in cervical and thoracic spinal cord regions.Differences between control and ALS mice groups at the symptomatic stages(day 120)were larger.Quantitative fluorescence microscopy at 80 days,demonstrated a 22% reduction in axonal area and a 22% increase in axonal density.Tractography and quantitative connectome analyses measured by edge weights showed a 52%decrease in the lumbar regions of the spinal cords of this ALS mice group.A significant increase in ADC(23.3%)in the ALS mice group was related to an increase in aquaporin markers.Conclusions:These findings suggest that the combination of ultra-high field diffusion MRI with fluorescent ALS mice reporters is a useful approach to detect and characterize presymptomatic white matter micro-ultrastructural changes and axonal connectivity anomalies in ALS.
基金supported by the National Natural Science Foundation of China(Nos.82021004,81620108016,31221003)Changjiang Scholar Professorship Award(No.T2015027).
文摘Attention-deficit/hyperactivity disorder(ADHD)has been conceptualized as a brain dysconnectivity disorder.In the past decade,noninvasive diffusion magnetic resonance imaging(dMRI)studies have demonstrated that individuals with ADHD have alterations in the white matter structural connectome,and that these alterations are associated with core symptoms and cognitive deficits in patients.This review aims to summarize recent dMRI-based structural connectome studies in ADHD from voxel-,tractography-,and network-based perspectives.Voxel-and tractography-based studies have demonstrated disrupted microstructural properties predominantly located in the frontostriatal tracts,the corpus callosum,the corticospinal tracts,and the cingulum bundle in patients with ADHD.Network-based studies have suggested abnormal global and local efficiency as well as nodal properties in the prefrontal and parietal regions in the ADHD structural connectomes.The altered structural connectomes in those with ADHD provide significant signatures for prediction of symptoms and diagnostic classification.These studies suggest that abnormalities in the structural connectome may be one of the neural underpinnings of ADHD psychopathology and show potential for establishing imaging biomarkers in clinical evaluation.However,given that there are inconsistent findings across studies due to sample heterogeneity and analysis method variations,these ADHD-related white matter alterations are still far from informing clinical practice.Future studies with larger and more homogeneous samples are needed to validate the consistency of current results;advanced dMRI techniques can help to generatemuchmore precise estimation of whitematter pathways and assure specific fiber configurations;and finally,dimensional analysis frameworks can deepen our understanding of the neurobiology underlying ADHD.
基金supported by STI 2030-Major Projects(2022ZD0211500)the National Natural Science Foundation of China(82071998,82021004,and 62206024)+1 种基金Beijing Natural Science Foundation(JQ23033)Beijing United Imaging Research Institute of Intelligent Imaging Foundation(CRIBJZD202102).
文摘Psychiatric disorders are a pressing public health challenge,posing a significant threat to the well-being of millions of people worldwide.Their elusive etiology,rooted in the complex interplay of genetic,environmental,and neural factors,requires innovative research approaches.The advent of advanced neuroimaging techniques and connectomics marks a transformative era,enabling researchers to delve into the structural and functional networks of the human brain.This transformation is underscored by the establishment of large brain datasets and a growing body of published findings,heralding a new era in neuroscience research that is poised to reshape our understanding of psychiatric disorders.Here,we review recent advances in connectome and neuroimaging big data in psychiatric disorders.First,we highlight several multisite neuroimaging datasets that hold immense potential for groundbreaking discoveries in understanding the intricate structural and functional network architecture of various psychiatric disorders.We then present innovative methods for multicenter and multidimensional data analysis,particularly connectome-based meta-analytic and multivariate analysis methods.Furthermore,we demonstrate the critical value of these methods in synthesizing findings from diverse published works or multisite data,and in exploring connectomics associations with demographics,symptomatology,behavioral and cognitive metrics,and genetic data in psychiatric disorders.Finally,we discuss the emerging issues and challenges that urgently need to be addressed in the field and that will shape the future trajectory of psychiatric research.
基金supported by the National Natural Science Foundation of China(31830034,82021004,81620108016,31221003,31521063,81671767,82071998,81971690,32130045,and 61761166004)Changjiang Scholar Professorship Award(T2015027)+3 种基金the National Key Research and Development Project of China(2018YFA0701402)Beijing Nova Program(Z191100001119023)the Beijing Brain Initiative of Beijing Municipal Science&Technology Commission(Z181100001518003)the Fundamental Research Funds for the Central Universities(2020NTST29)。
文摘Connectome mapping studies have documented a principal primary-to-transmodal gradient in the adult brain network,capturing a functional spectrum that ranges from perception and action to abstract cognition.However,how this gradient pattern develops and whether its development is linked to cognitive growth,topological reorganization,and gene expression profiles remain largely unknown.Using longitudinal resting-state functional magnetic resonance imaging data from 305 children(aged 6-14 years),we describe substantial changes in the primary-to-transmodal gradient between childhood and adolescence,including emergence as the principal gradient,expansion of global topography,and focal tuning in primary and default-mode regions.These gradient changes are mediated by developmental changes in network integration and segregation,and are associated with abstract processing functions such as working memory and expression levels of calcium ion regulated exocytosis and synaptic transmission-related genes.Our findings have implications for understanding connectome maturation principles in normal development and developmental disorders.
基金partially supported by the National Basic Research Program (973) of China (2015CB351702)the National Natural Science Foundation of China (81220108014, 81471740, 81201153, 81171409, and 81270023)+4 种基金the Key Research Program (KSZD-EW-TZ-002)the Hundred Talents Program of the Chinese Academy of SciencesDr. Xiu-Xia Xing acknowledges the Beijing Higher Education Young Elite Teacher Project (No. YETP1593)Dr. Zhi Yang acknowledges the Foundation of Beijing Key Laboratory of Mental Disorders (2014JSJB03)the Outstanding Young Researcher Award from Institute of Psychology, Chinese Academy of Sciences (Y4CX062008)
文摘Much like genomics, brain connectomics has rapidly become a core component of most national brain projects around the world. Beyond the ambitious aims of these projects, a fundamental challenge is the need for an efficient, robust, reliable and easy-to-use pipeline to mine such large neuroscience datasets. Here, we introduce a computational pipeline--namely the Connectome Compu- tation System （CCS）-for discovery science of human brain connectomes at the macroscale with multimodal magnetic resonance imaging technologies. The CCS is designed with a three-level hierarchical structure that includes data cleaning and preprocessing, individual connectome mapping andconnectome mining, and knowledge discovery. Several functional modules are embedded into this hierarchy to implement quality control procedures, reliability analysis and connectome visualization. We demonstrate the utility of the CCS based upon a publicly available dataset, the NKI- Rockland Sample, to delineate the normative trajectories of well-known large-scale neural networks across the natural life span （6-85 years of age）. The CCS has been made freely available to the public via GitHub （https：//github.com/ zuoxinian/CCS） and our laboratory＇s Web site （http：//lfcd. psych.ac.cn/ccs.html） to facilitate progress in discovery science in the field of human brain connectomics.
