Closed-loop neuromodulation,especially using the phase of the electroencephalography(EEG)rhythm to assess the real-time brain state and optimize the brain stimulation process,is becoming a hot research topic.Because t...Closed-loop neuromodulation,especially using the phase of the electroencephalography(EEG)rhythm to assess the real-time brain state and optimize the brain stimulation process,is becoming a hot research topic.Because the EEG signal is non-stationary,the commonly used EEG phase-based prediction methods have large variances,which may reduce the accuracy of the phase prediction.In this study,we proposed a machine learning-based EEG phase prediction network,which we call EEG phase prediction network(EPN),to capture the overall rhythm distribution pattern of subjects and map the instantaneous phase directly from the narrow-band EEG data.We verified the performance of EPN on pre-recorded data,simulated EEG data,and a real-time experiment.Compared with widely used state-of-the-art models(optimized multi-layer filter architecture,auto-regress,and educated temporal prediction),EPN achieved the lowest variance and the greatest accuracy.Thus,the EPN model will provide broader applications for EEG phase-based closed-loop neuromodulation.展开更多
Dear Editor,Transcranial Magnetic Stimulation(TMS)has emerged as a promising therapeutic tool for various neurological and psychiatric conditions[1-3].However,despite its potential benefits,TMS is not without its disc...Dear Editor,Transcranial Magnetic Stimulation(TMS)has emerged as a promising therapeutic tool for various neurological and psychiatric conditions[1-3].However,despite its potential benefits,TMS is not without its discomfort issues[4,5],which are mainly related to target location,stimulus intensity,and treatment duration.The discomfort associated with TMS arises from several factors,including the physical sensations experienced during the procedure and potential adverse effects on the scalp and surrounding tissues.展开更多
Attention deficit hyperactivity disorder(ADHD),a prevalent neurodevelopmental disorder influenced by both genetic and environmental factors,remains poorly understood regarding how its polygenic risk score(PRS)impacts ...Attention deficit hyperactivity disorder(ADHD),a prevalent neurodevelopmental disorder influenced by both genetic and environmental factors,remains poorly understood regarding how its polygenic risk score(PRS)impacts functional networks and symptomology.This study capitalized on data from 11,430 children in the Adolescent Brain Cognitive Development study to explore the interplay between PRSADHD,brain function,and behavioral problems,along with their interactive effects.The results showed that children with a higher PRSADHD exhibited more severe attention deficits and rule-breaking problems,and experienced sleep disturbances,particularly in initiating and maintaining sleep.We also identified the central executive network,default mode network,and sensory-motor network as the functional networks most associated with PRS and symptoms in ADHD cases,with potential mediating roles.Particularly,the impact of PRSADHD was enhanced in children experiencing heightened sleep disturbances,emphasizing the need for early intervention in sleep issues to potentially mitigate subsequent ADHD symptoms.展开更多
The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiologi...The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiological measurements,including electroencephalograph(EEG)and functional magnetic resonance imaging(fMRI),and are crucial for insights into physiological phenomena.This study introduces a novel method,the baseline perspective visibility graph(BPVG),which can analyze time series by accurately capturing connectivity across data points both above and below the baseline.We present the BPVG construction process and validate its performance using simulated signals.Results demonstrate that BPVG accurately translates periodic,random,and fractal signals into regular,random,and scale-free networks respectively,exhibiting diverse degree distribution traits.Furthermore,we apply BPVG to classify Alzheimer’s disease(AD)patients from healthy controls using EEG data and identify non-demented adults at varying dementia risk using resting-state fMRI(rs-fMRI)data.Utilizing degree distribution entropy derived from BPVG networks,our results exceed the best accuracy benchmark(77.01%)in EEG analysis,especially at channels F4(78.46%)and O1(81.54%).Additionally,our rs-fMRI analysis achieves a statistically significant classification accuracy of 76.74%.These findings highlight the effectiveness of BPVG in distinguishing various time series types and its practical utility in EEG and rs-fMRI analysis for early AD detection and dementia risk assessment.In conclusion,BPVG’s validation across both simulated and real data confirms its capability to capture comprehensive information from time series,irrespective of baseline constraints,providing a novel method for studying neural physiological signals.展开更多
The rich club,as a community of highly interconnected nodes,serves as the topological center of the network.However,the similarities and differences in how the rich club supports functional integration and segregation...The rich club,as a community of highly interconnected nodes,serves as the topological center of the network.However,the similarities and differences in how the rich club supports functional integration and segregation in the brain across different species remain unknown.In this study,we first detected and validated the rich club in the structural networks of mouse,monkey,and human brains using neuronal tracing or diffusion magnetic resonance imaging data.Further,we assessed the role of rich clubs in functional integration,segregation,and balance using quantitative metrics.Our results indicate that the presence of a rich club facilitates whole-brain functional integration in all three species,with the functional networks of higher species exhibiting greater integration.These findings are expected to help to understand the relationship between brain structure and function from the perspective of brain evolution.展开更多
Dear Editor,Growing clinical evidence shows that brain disorders are heterogeneous in phenotype,genetics,and neuropathology[1].Diagnosis and treatment tend to be affected by symptom presentation and the heterogeneity ...Dear Editor,Growing clinical evidence shows that brain disorders are heterogeneous in phenotype,genetics,and neuropathology[1].Diagnosis and treatment tend to be affected by symptom presentation and the heterogeneity of pathology,potentially hindering clinical trials in the development of medical treatment.Brain-based subtyping studies utilize magnetic resonance imaging(MRI)and data-driven methods to discover the subtypes of diseases,providing a new perspective on disease heterogeneity.展开更多
Schizophrenia(SZ)stands as a severe psychiatric disorder.This study applied diffusion tensor imaging(DTI)data in conjunction with graph neural networks to distinguish SZ patients from normal controls(NCs)and showcases...Schizophrenia(SZ)stands as a severe psychiatric disorder.This study applied diffusion tensor imaging(DTI)data in conjunction with graph neural networks to distinguish SZ patients from normal controls(NCs)and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features,achieving an accuracy of 73.79%in distinguishing SZ patients from NCs.Beyond mere discrimination,our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis.These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers,providing novel insights into the neuropathological basis of SZ.In summary,our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.展开更多
Neuroimaging made it possible to quantify brain structure and function.However,there are few neuroimaging biomarkers for the early diagnosis,prognosis,and evaluation of therapy for brain diseases.The development of ne...Neuroimaging made it possible to quantify brain structure and function.However,there are few neuroimaging biomarkers for the early diagnosis,prognosis,and evaluation of therapy for brain diseases.The development of neuroimaging biomarkers for brain diseases faces two major bottleneck problems.First,the neuroimaging datasets of brain diseases are always characterized by small sample size,high dimension,and large heterogeneity.Second,a fine-grained individualized human brain atlas for effective dimensionality reduction has always been lacking.展开更多
When presented with visual stimuli of face images,the ventral stream visual cortex of the human brain exhibits face-specific activity that is modulated by the physical properties of the input images.However,it is stil...When presented with visual stimuli of face images,the ventral stream visual cortex of the human brain exhibits face-specific activity that is modulated by the physical properties of the input images.However,it is still unclear whether this activity relates to conscious face perception.We explored this issue by using the human intracranial electroencephalography technique.Our results showed that face-specific activity in the ventral stream visual cortex was significantly higher when the subjects subjectively saw faces than when they did not,even when face stimuli were presented in both conditions.In addition,the face-specific neural activity exhibited a more reliable neural response and increased posterior-anterior direction information transfer in the“seen”condition than the“unseen”condition.Furthermore,the face-specific neural activity was significantly correlated with performance.These findings support the view that face-specific activity in the ventral stream visual cortex is linked to conscious face perception.展开更多
When new information enters the brain,a human's prior knowledge of the world can change rapidly through a process referred to as"knowledge assembly".Recently,Nelli et al.investigated the neural correlate...When new information enters the brain,a human's prior knowledge of the world can change rapidly through a process referred to as"knowledge assembly".Recently,Nelli et al.investigated the neural correlates of knowledge assembly in the human brain using functional MRI.Further,inspired by the neural mechanism,the authors developed an artificial neural network algorithm to permit rapid knowledge assembly,improving the flexibility of the system[1].Once again,this research demonstrates that studying how the brain works can lead to better computational algorithms.展开更多
The current study aimed to evaluate the susceptibility to regional brain atrophy and its biological mechanism in Alzheimer’s disease(AD).We conducted data-driven meta-analyses to combine 3,118 structural magnetic res...The current study aimed to evaluate the susceptibility to regional brain atrophy and its biological mechanism in Alzheimer’s disease(AD).We conducted data-driven meta-analyses to combine 3,118 structural magnetic resonance images from three datasets to obtain robust atrophy patterns.Then we introduced a set of radiogenomic analyses to investigate the biological basis of the atrophy patterns in AD.Our results showed that the hippocampus and amygdala exhibit the most severe atrophy,followed by the temporal,frontal,and occipital lobes in mild cognitive impairment(MCI)and AD.The extent of atrophy in MCI was less severe than that in AD.A series of biological processes related to the glutamate signaling pathway,cellular stress response,and synapse structure and function were investigated through gene set enrichment analysis.Our study contributes to understanding the manifestations of atrophy and a deeper understanding of the pathophysiological processes that contribute to atrophy,providing new insight for further clinical research on AD.展开更多
Chimpanzees(Pan troglodytes)are one of humans'closest living relatives,making them the most directly relevant comparison point for understanding human brain evolution.Zeroing in on the differences in brain connect...Chimpanzees(Pan troglodytes)are one of humans'closest living relatives,making them the most directly relevant comparison point for understanding human brain evolution.Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occurred along the human lineage.However,such comparisons are hindered by the absence of cross-species brain atlases established within the same framework.To address this gap,we developed the Chimpanzee Brainnetome Atlas(ChimpBNA)using a connectivity-based parcellation framework.Leveraging this new resource,we found substantial divergence in connectivity patterns between the two species across most association cortices,notably in the lateral temporal and dorsolateral prefrontal cortex.These differences deviate sharply from the pattern of cortical expansion observed when comparing humans to chimpanzees,highlighting more complex and nuanced connectivity changes in brain evolution than previously recognized.Additionally,we identified regions displaying connectional asymmetries that differed between species,likely resulting from evolutionary divergence.Genes highly expressed in regions of divergent connectivities were enriched in cell types crucial for cortical projection circuits and synapse formation,whose pronounced differences in expression patterns hint at genetic influences on neural circuit development,function,and evolution.Our study provides a fine-scale chimpanzee brain atlas and highlights the chimpanzee-human connectivity divergence in a rigorous and comparative manner.In addition,these results suggest potential gene expression correlates for species-specific differences by linking neuroimaging and genetic data,offering insights into the evolution of human-unique cognitive capabilities.展开更多
Transcranial magnetic stimulation(TMS)is a popular modulatory technique for the noninvasive diagnosis and therapy of neurological and psychiatric diseases.Unfortunately,current modulation strategies are only modestly ...Transcranial magnetic stimulation(TMS)is a popular modulatory technique for the noninvasive diagnosis and therapy of neurological and psychiatric diseases.Unfortunately,current modulation strategies are only modestly effective.The literature provides strong evidence that the modulatory effects of TMS vary depending on device components and stimulation protocols.These differential effects are important when designing precise modulatory strategies for clinical or research applications.Developments in TMS have been accompanied by advances in combining TMS with neuroimaging techniques,including electroencephalography,functional nearinfrared spectroscopy,functional magnetic resonance imaging,and positron emission tomography.Such studies appear particularly promising as they may not only allow us to probe affected brain areas during TMS but also seem to predict underlying research directions that may enable us to precisely target and remodel impaired cortices or circuits.However,few precise modulation strategies are available,and the long-term safety and efficacy of these strategies need to be confirmed.Here,we review the literature on possible technologies for precise modulation to highlight progress along with limitations with the goal of suggesting future directions for this field.展开更多
Schizophrenia is hypothesized to arise from disrupted brain connectivity. This ＂dysconnectivity hypothesis＂ has generated interest in discovering whether there is anatomical and functional dysconnectivity between th...Schizophrenia is hypothesized to arise from disrupted brain connectivity. This ＂dysconnectivity hypothesis＂ has generated interest in discovering whether there is anatomical and functional dysconnectivity between the prefrontal cortex （PFC） and other brain regions, and how this dysconnectivity is linked to the impaired cognitive functions and aberrant behaviors of schizophrenia. Critical advances in neuroimaging technologies, including diffusion tensor imaging （DTI） and functional magnetic resonance imaging （fMRI）, make it possible to explore these issues. DTI affords the possibility to explore anatomical connectivity in the human brain in vivo and fMRI can be used to make inferences about functional connections between brain regions. In this review, we present major advances in the understanding of PFC anatomical and functional dysconnectivity and their implications in schizophrenia. We then briefly discuss future prospects that need to be explored in order to move beyond simple mapping of connectivity changes to elucidate the neuronal mechanisms underlying schizophrenia.展开更多
Specific patterns of brain atrophy may be helpful in the diagnosis of Alzheimer＇s disease （AD）. In the present study, we set out to evaluate the utility of grey-matter volume in the classification of AD and amnesti...Specific patterns of brain atrophy may be helpful in the diagnosis of Alzheimer＇s disease （AD）. In the present study, we set out to evaluate the utility of grey-matter volume in the classification of AD and amnestic mild cognitive impairment （aMCI） compared to normal control （NC）individuals. Voxel-based morphometric analyses were performed on structural MRIs from 35 AD patients, 27 aMCI patients, and 27 NC participants. A two-sample two-tailed t-test was computed between the NC and AD groups to create a map of abnormal grey matter in AD. The brain areas with significant differences were extracted as regions of interest （ROIs）, and the grey-matter volumes in the ROIs of the aMCI patients were included to evaluate the patterns of change across different disease severities. Next, correlation analyses between the grey-matter volumes in the ROIs and all clinical variables were performed in aMCI and AD patients to determine whether they varied with disease progression. The results revealed significantly decreased grey matter in the bilateral hippocampus/ parahippocampus, the bilateral superior/middle temporal gyri, and the right precuneus in AD patients.The grey-matter volumes with clinical variables were positively correlated Finally, we performed exploratory linear discriminative analyses to assess the classifying capacity of grey-matter volumes in the bilateral hippocampus and parahippocampus among AD, aMCI, and NC. Leave-one-out cross- validation analyses demonstrated that grey-matter volumes in hippocampus and parahippocampus accurately distinguished AD from NC. These findings indicate that grey-matter volumes are useful in the classification of AD.展开更多
At present,predicting the severity of brain injury caused by global cerebral ischemia/reperfusion injury(GCI/RI)is a clinical problem.After such an injury,clinical indicators that can directly reflect neurological dys...At present,predicting the severity of brain injury caused by global cerebral ischemia/reperfusion injury(GCI/RI)is a clinical problem.After such an injury,clinical indicators that can directly reflect neurological dysfunction are lacking.The change in hippocampal microstructure is the key to memory formation and consolidation.Diffusion tensor imaging is a highly sensitive tool for visualizing injury to hippocampal microstructure.Although hippocampal microstructure,brain-derived neurotrophic factor(BDNF),and tropomyosin-related kinase B(Trk B)levels are closely related to nerve injury and the repair process after GCI/RI,whether these indicators can reflect the severity of such hippocampal injury remains unknown.To address this issue,we established rat models of GCI/RI using the four-vessel occlusion method.Diffusion tensor imaging parameters,BDNF,and Trk B levels were correlated with modified neurological severity scores.The results revealed that after GCI/RI,while neurological function was not related to BDNF and Trk B levels,it was related to hippocampal fractional anisotropy.These findings suggest that hippocampal fractional anisotropy can reflect the severity of hippocampal injury after global GCI/RI.The study was approved by the Institutional Animal Care and Use Committee of Capital Medical University,China(approval No.AEEI-2015-139)on November 9,2015.展开更多
Spinal cord stimulation （SCS） is a promising technique for treating disorders of consciousness （DOCs）. However, differences in the spatio-temporal responsiveness of the brain under varied SCS parameters remain unc...Spinal cord stimulation （SCS） is a promising technique for treating disorders of consciousness （DOCs）. However, differences in the spatio-temporal responsiveness of the brain under varied SCS parameters remain unclear. In this pilot study, functional near-infrared spectroscopy was used to measure the hemodynamic responses of 10 DOC patients to different SCS frequencies （5 Hz, 10 Hz, 50 Hz, 70 Hz, and 100 Hz）. In the prefrontal cortex, a key area in consciousness circuits, we found significantly increased hemodynamic responses at 70 Hz and 100 Hz, and significantly different hemodynamic responses between 50 Hz and 70 Hz/100 Hz. In addition, the functional connectivity between prefrontal and occipital areas was significantly improved with SCS at 70 Hz. These results demonstrated that SCS modulates the hemodynamic responses and long-range connectivity in a frequency-specific manner （with 70 Hz apparently better）, perhaps by improving the cerebral blood volume and information transmission through the reticular formation-thalamus-cortex pathway.展开更多
Severe brain injury can lead to disorders of consciousness （DOCs）. Since DOC patients cannot communicate functionally or behave purposefully, most remain bedridden and require laborious care. The medical community i...Severe brain injury can lead to disorders of consciousness （DOCs）. Since DOC patients cannot communicate functionally or behave purposefully, most remain bedridden and require laborious care. The medical community is often confronted with the expectations of the families of chronic DOC patients, and the social, economic, and ethical consequences are tremendous. Research on DOCs is attracting increasing attention from scientists and physicians in various fields. With the development of modern neuroimaging and neuromodulation techniques, much progress has been made in the diagnosis, prognosis, treatment, and rehabilitation of DOCs in the last decade.展开更多
An important and unresolved question is how human brain regions process information and interact with each other in intertemporal choice related to gains and losses. Using psychophysiological interaction and dynamic c...An important and unresolved question is how human brain regions process information and interact with each other in intertemporal choice related to gains and losses. Using psychophysiological interaction and dynamic causal modeling analyses, we investigated the functional interactions between regions involved in the decision- making process while participants performed temporal discounting tasks in both the gains and losses domains. We found two distinct intrinsic valuation systems underlying temporal discounting in the gains and losses domains： gains were specifically evaluated in the medial regions, including the medial prefrontal and orbitofrontal cortices, and losses were evaluated in the lateral dorsolateral prefrontal cortex. In addition, immediate reward or pun- ishment was found to modulate the functional interactions between the dorsolateral prefrontal cortex and distinct regions in both the gains and losses domains： in the gains domain, the mesolimbic regions; in the losses domain, the medial prefrontal cortex, anterior cingulate cortex, and insula. These findings suggest that intertemporal choice of gains and losses might involve distinct valuation systems, and more importantly, separate neural interactions may implement the intertemporal choices of gains and losses. These findings may provide a new biological perspective for understanding the neural mechanisms underlying intertemporal choice of gains and losses.展开更多
Neuroimaging has opened new opportunities to study the neural correlates of consciousness, and provided additional information concerning diagnosis, prognosis, and therapeutic interventions in patients with disorders ...Neuroimaging has opened new opportunities to study the neural correlates of consciousness, and provided additional information concerning diagnosis, prognosis, and therapeutic interventions in patients with disorders of consciousness. Here, we aim to review neuroimaging studies in chronic disorders of consciousness from the viewpoint of the brain network, focusing on positron emission tomogra- phy, functional MRI, functional near-infrared spectroscopy, electrophysiology, and diffusion MRI. To accelerate basic research on disorders of consciousness and provide a panoramic view of unconsciousness, we propose that it is urgent to integrate different techniques at various spatiotemporal scales, and to merge fragmented findings into a uniform ＂Brainnetome＂ （Brain-net-ome） research framework.展开更多
基金supported by the Key Collaborative Research Program of the Alliance of International Science Organizations(ANSO-CR-KP-2022-10)Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence Project(2021ZD0200200)+2 种基金Natural Science Foundation of China(82151307,82202253,and 31620103905)Strategic Priority Research Program of the Chinese Academy of Sciences(XDB32030207)Science Frontier Program of the Chinese Academy of Sciences(QYZDJ-SSW-SMCO19).
文摘Closed-loop neuromodulation,especially using the phase of the electroencephalography(EEG)rhythm to assess the real-time brain state and optimize the brain stimulation process,is becoming a hot research topic.Because the EEG signal is non-stationary,the commonly used EEG phase-based prediction methods have large variances,which may reduce the accuracy of the phase prediction.In this study,we proposed a machine learning-based EEG phase prediction network,which we call EEG phase prediction network(EPN),to capture the overall rhythm distribution pattern of subjects and map the instantaneous phase directly from the narrow-band EEG data.We verified the performance of EPN on pre-recorded data,simulated EEG data,and a real-time experiment.Compared with widely used state-of-the-art models(optimized multi-layer filter architecture,auto-regress,and educated temporal prediction),EPN achieved the lowest variance and the greatest accuracy.Thus,the EPN model will provide broader applications for EEG phase-based closed-loop neuromodulation.
基金supported by STI2030-Major Projects(2021ZD0200200)the Key Collaborative Research Program of the Alliance of International Science Organizations(ANSO-CR-KP-2022-10)+1 种基金the Natural Science Foundation of China(82151307,82202253,and 31620103905)the Science Frontier Program of the Chinese Academy of Sciences(QYZDJ-SSW-SMC019).
文摘Dear Editor,Transcranial Magnetic Stimulation(TMS)has emerged as a promising therapeutic tool for various neurological and psychiatric conditions[1-3].However,despite its potential benefits,TMS is not without its discomfort issues[4,5],which are mainly related to target location,stimulus intensity,and treatment duration.The discomfort associated with TMS arises from several factors,including the physical sensations experienced during the procedure and potential adverse effects on the scalp and surrounding tissues.
基金supported by the National Natural Science Foundation of China(62373062,82022035,and 82001450)the Scientific and Technological Innovation 2030-The Major Project of the Brain Science and Brain-Inspired Intelligence Technology(2021ZD0200500)the Startup Funds for Talents at Beijing Normal University,and the China Postdoctoral Science Foundation(2022M710434).
文摘Attention deficit hyperactivity disorder(ADHD),a prevalent neurodevelopmental disorder influenced by both genetic and environmental factors,remains poorly understood regarding how its polygenic risk score(PRS)impacts functional networks and symptomology.This study capitalized on data from 11,430 children in the Adolescent Brain Cognitive Development study to explore the interplay between PRSADHD,brain function,and behavioral problems,along with their interactive effects.The results showed that children with a higher PRSADHD exhibited more severe attention deficits and rule-breaking problems,and experienced sleep disturbances,particularly in initiating and maintaining sleep.We also identified the central executive network,default mode network,and sensory-motor network as the functional networks most associated with PRS and symptoms in ADHD cases,with potential mediating roles.Particularly,the impact of PRSADHD was enhanced in children experiencing heightened sleep disturbances,emphasizing the need for early intervention in sleep issues to potentially mitigate subsequent ADHD symptoms.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFF1204803)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20190736)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.NJ2024029)the National Natural Science Foundation of China(Grant Nos.81701346 and 62201265).
文摘The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiological measurements,including electroencephalograph(EEG)and functional magnetic resonance imaging(fMRI),and are crucial for insights into physiological phenomena.This study introduces a novel method,the baseline perspective visibility graph(BPVG),which can analyze time series by accurately capturing connectivity across data points both above and below the baseline.We present the BPVG construction process and validate its performance using simulated signals.Results demonstrate that BPVG accurately translates periodic,random,and fractal signals into regular,random,and scale-free networks respectively,exhibiting diverse degree distribution traits.Furthermore,we apply BPVG to classify Alzheimer’s disease(AD)patients from healthy controls using EEG data and identify non-demented adults at varying dementia risk using resting-state fMRI(rs-fMRI)data.Utilizing degree distribution entropy derived from BPVG networks,our results exceed the best accuracy benchmark(77.01%)in EEG analysis,especially at channels F4(78.46%)and O1(81.54%).Additionally,our rs-fMRI analysis achieves a statistically significant classification accuracy of 76.74%.These findings highlight the effectiveness of BPVG in distinguishing various time series types and its practical utility in EEG and rs-fMRI analysis for early AD detection and dementia risk assessment.In conclusion,BPVG’s validation across both simulated and real data confirms its capability to capture comprehensive information from time series,irrespective of baseline constraints,providing a novel method for studying neural physiological signals.
基金supported by STI2030-Major Projects(2021ZD0200200)the National Natural Science Foundation of China(62327805 and 82151307)+1 种基金the Equipment Development Project of the Chinese Academy of Sciences(YJKYYQ20190040)the Science and Technology Innovation Program of Hunan Province(2024RC4028).
文摘The rich club,as a community of highly interconnected nodes,serves as the topological center of the network.However,the similarities and differences in how the rich club supports functional integration and segregation in the brain across different species remain unknown.In this study,we first detected and validated the rich club in the structural networks of mouse,monkey,and human brains using neuronal tracing or diffusion magnetic resonance imaging data.Further,we assessed the role of rich clubs in functional integration,segregation,and balance using quantitative metrics.Our results indicate that the presence of a rich club facilitates whole-brain functional integration in all three species,with the functional networks of higher species exhibiting greater integration.These findings are expected to help to understand the relationship between brain structure and function from the perspective of brain evolution.
基金supported by the National Natural Science Foundation of China(82102018,62333002,T2425027,and 82327809)Data collection and sharing for this project were supported by the National Natural Science Foundation of China(61633018,81571062,81471120,and 81901101)+30 种基金Data collection and sharing for this project were funded by the ADNI(National Institutes of Health Grant U01 AG024904)the Department of Defense ADNI(award number W81XWH-12-2-0012).The ADNI is funded by the National Institute on Aging,the National Institute of Biomedical Imaging and Bioengineering,and through generous contributions from the following:AbbVie,Alzheimer’s AssociationAlzheimer’s Drug Discovery FoundationAraclon BiotechBioClinica,Inc.BiogenBristol-Myers Squibb Co.CereSpir,Inc.CogstateEisai Inc.Elan Pharmaceuticals,Inc.Eli Lilly and Co.EuroImmunF.Hoffmann-La Roche Ltd and its affiliated company Genentech,Inc.FujirebioG.E.HealthcareIXICO Ltd.Janssen Alzheimer Immunotherapy Research&Development,LLC.Johnson&Johnson Pharmaceutical Research&Development LLC.LumosityLundbeckMerck&Co.,Inc.Meso Scale Diagnostics,LLC.NeuroRx ResearchNeurotrack TechnologiesNovartis Pharmaceuticals Corp.Pfizer Inc.Piramal ImagingServierTakeda Pharmaceutical Co.and Transition Therapeutics.The Canadian Institutes of Health Research provides funds to support ADNI clinical sites in Canada.Private sector contributions are facilitated by the Foundation for the National Institutes of Health(www.fnih.org).The grantee organization was the Northern California Institute for Research and Education,and the study was coordinated by the Alzheimer’s Therapeutic Research Institute at the University of Southern California.ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.
文摘Dear Editor,Growing clinical evidence shows that brain disorders are heterogeneous in phenotype,genetics,and neuropathology[1].Diagnosis and treatment tend to be affected by symptom presentation and the heterogeneity of pathology,potentially hindering clinical trials in the development of medical treatment.Brain-based subtyping studies utilize magnetic resonance imaging(MRI)and data-driven methods to discover the subtypes of diseases,providing a new perspective on disease heterogeneity.
基金supported by the National Natural Science Foundation of China(62276049,61701078,61872068,and 62006038)the Natural Science Foundation of Sichuan Province(2025ZNSFSC0487)+3 种基金the Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence Project(2021ZD0200200)the National Key R&D Program of China(2023YFE0118600)Sichuan Province Science and Technology Support Program(2019YJ0193,2021YFG0126,2021YFG0366,and 2022YFS0180)Medico-Engineering Cooperation Funds from the University of Electronic Science and Technology of China(ZYGX2021YGLH014).
文摘Schizophrenia(SZ)stands as a severe psychiatric disorder.This study applied diffusion tensor imaging(DTI)data in conjunction with graph neural networks to distinguish SZ patients from normal controls(NCs)and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features,achieving an accuracy of 73.79%in distinguishing SZ patients from NCs.Beyond mere discrimination,our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis.These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers,providing novel insights into the neuropathological basis of SZ.In summary,our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
文摘Neuroimaging made it possible to quantify brain structure and function.However,there are few neuroimaging biomarkers for the early diagnosis,prognosis,and evaluation of therapy for brain diseases.The development of neuroimaging biomarkers for brain diseases faces two major bottleneck problems.First,the neuroimaging datasets of brain diseases are always characterized by small sample size,high dimension,and large heterogeneity.Second,a fine-grained individualized human brain atlas for effective dimensionality reduction has always been lacking.
基金supported by the Science and Technology Innovation 2030-Brain Science and Brain-Inspired Intelligence Project (2021ZD0200200)the National Natural Science Foundation of China (62327805,82151307,and 32271085)the Beijing Natural Science Foundation (5244049).
文摘When presented with visual stimuli of face images,the ventral stream visual cortex of the human brain exhibits face-specific activity that is modulated by the physical properties of the input images.However,it is still unclear whether this activity relates to conscious face perception.We explored this issue by using the human intracranial electroencephalography technique.Our results showed that face-specific activity in the ventral stream visual cortex was significantly higher when the subjects subjectively saw faces than when they did not,even when face stimuli were presented in both conditions.In addition,the face-specific neural activity exhibited a more reliable neural response and increased posterior-anterior direction information transfer in the“seen”condition than the“unseen”condition.Furthermore,the face-specific neural activity was significantly correlated with performance.These findings support the view that face-specific activity in the ventral stream visual cortex is linked to conscious face perception.
基金supported by STI2030-Major Projects 2021ZD0200201the Scientific Research and Equipment Development Project of the Chinese Academy of Sciences(YJKYYQ20190040)。
文摘When new information enters the brain,a human's prior knowledge of the world can change rapidly through a process referred to as"knowledge assembly".Recently,Nelli et al.investigated the neural correlates of knowledge assembly in the human brain using functional MRI.Further,inspired by the neural mechanism,the authors developed an artificial neural network algorithm to permit rapid knowledge assembly,improving the flexibility of the system[1].Once again,this research demonstrates that studying how the brain works can lead to better computational algorithms.
基金Science and Technology Innovation 2030 Major Projects(2022ZD0211600)Fundamental Research Funds for the Central Universities(2021XD-A03)+3 种基金National Natural Science Foundation of China(81871438 and 82102018)Data collection and sharing for this project were supported by the National Natural Science Foundation of China(61633018,81571062,81400890,81471120,81701781,and 81901101)Data collection and sharing for this project were funded by the Alzheimer’s Disease Neuroimaging Initiative(ADNI)(National Institutes of Health Grant U01 AG024904)DOD ADNI(Department of Defense award number W81XWH-12-2-0012)。
文摘The current study aimed to evaluate the susceptibility to regional brain atrophy and its biological mechanism in Alzheimer’s disease(AD).We conducted data-driven meta-analyses to combine 3,118 structural magnetic resonance images from three datasets to obtain robust atrophy patterns.Then we introduced a set of radiogenomic analyses to investigate the biological basis of the atrophy patterns in AD.Our results showed that the hippocampus and amygdala exhibit the most severe atrophy,followed by the temporal,frontal,and occipital lobes in mild cognitive impairment(MCI)and AD.The extent of atrophy in MCI was less severe than that in AD.A series of biological processes related to the glutamate signaling pathway,cellular stress response,and synapse structure and function were investigated through gene set enrichment analysis.Our study contributes to understanding the manifestations of atrophy and a deeper understanding of the pathophysiological processes that contribute to atrophy,providing new insight for further clinical research on AD.
基金supported by ST12030-Major Projects(grant na 2021ZD0200203)the Natural Science Foundation of China(grant nos.82072099,82202253,and 62250058)the China Postdoctoral Science Foundation(2022M722915)+1 种基金the Guangxi Science and Technology Base and Talent Special Project(grant no AD22035125)Chongqing Science and Health Joint Medical Research Key Project(2025GGXM005).
文摘Chimpanzees(Pan troglodytes)are one of humans'closest living relatives,making them the most directly relevant comparison point for understanding human brain evolution.Zeroing in on the differences in brain connectivity between humans and chimpanzees can provide key insights into the specific evolutionary changes that might have occurred along the human lineage.However,such comparisons are hindered by the absence of cross-species brain atlases established within the same framework.To address this gap,we developed the Chimpanzee Brainnetome Atlas(ChimpBNA)using a connectivity-based parcellation framework.Leveraging this new resource,we found substantial divergence in connectivity patterns between the two species across most association cortices,notably in the lateral temporal and dorsolateral prefrontal cortex.These differences deviate sharply from the pattern of cortical expansion observed when comparing humans to chimpanzees,highlighting more complex and nuanced connectivity changes in brain evolution than previously recognized.Additionally,we identified regions displaying connectional asymmetries that differed between species,likely resulting from evolutionary divergence.Genes highly expressed in regions of divergent connectivities were enriched in cell types crucial for cortical projection circuits and synapse formation,whose pronounced differences in expression patterns hint at genetic influences on neural circuit development,function,and evolution.Our study provides a fine-scale chimpanzee brain atlas and highlights the chimpanzee-human connectivity divergence in a rigorous and comparative manner.In addition,these results suggest potential gene expression correlates for species-specific differences by linking neuroimaging and genetic data,offering insights into the evolution of human-unique cognitive capabilities.
基金the Chinese Academy of Sciences,Science and Technology Service Network Initiative(KFJ-STS-ZDTP-078)the National Natural Science Foun-dation of China(31620103905)+1 种基金the Science Frontier Program of the Chinese Academy of Sciences(QYZDJ SSW-SMC019)the National Key R&D Program of China(2017YFA0105203)。
文摘Transcranial magnetic stimulation(TMS)is a popular modulatory technique for the noninvasive diagnosis and therapy of neurological and psychiatric diseases.Unfortunately,current modulation strategies are only modestly effective.The literature provides strong evidence that the modulatory effects of TMS vary depending on device components and stimulation protocols.These differential effects are important when designing precise modulatory strategies for clinical or research applications.Developments in TMS have been accompanied by advances in combining TMS with neuroimaging techniques,including electroencephalography,functional nearinfrared spectroscopy,functional magnetic resonance imaging,and positron emission tomography.Such studies appear particularly promising as they may not only allow us to probe affected brain areas during TMS but also seem to predict underlying research directions that may enable us to precisely target and remodel impaired cortices or circuits.However,few precise modulation strategies are available,and the long-term safety and efficacy of these strategies need to be confirmed.Here,we review the literature on possible technologies for precise modulation to highlight progress along with limitations with the goal of suggesting future directions for this field.
基金supported by the National Basic Research Development Program (973 Program) of China (2011CB707800)the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB02030300)the National Natural Science Foundation of China (91132301 and 81371476)
文摘Schizophrenia is hypothesized to arise from disrupted brain connectivity. This ＂dysconnectivity hypothesis＂ has generated interest in discovering whether there is anatomical and functional dysconnectivity between the prefrontal cortex （PFC） and other brain regions, and how this dysconnectivity is linked to the impaired cognitive functions and aberrant behaviors of schizophrenia. Critical advances in neuroimaging technologies, including diffusion tensor imaging （DTI） and functional magnetic resonance imaging （fMRI）, make it possible to explore these issues. DTI affords the possibility to explore anatomical connectivity in the human brain in vivo and fMRI can be used to make inferences about functional connections between brain regions. In this review, we present major advances in the understanding of PFC anatomical and functional dysconnectivity and their implications in schizophrenia. We then briefly discuss future prospects that need to be explored in order to move beyond simple mapping of connectivity changes to elucidate the neuronal mechanisms underlying schizophrenia.
基金supported by the National Natural Science Foundation of China (60831004 and 81270020)the CASIA Fund for Young Scientists with Lu-Jia-Xi award+2 种基金the Specific Healthcare Research Projects (13BJZ50)the Clinical Sciences Fund of the Chinese PLA General Hospital (2013FC-TSYS-1006)the Science Technological Innovation Nursery Fund of the Chinese PLA General Hospital (13KMM19), China
文摘Specific patterns of brain atrophy may be helpful in the diagnosis of Alzheimer＇s disease （AD）. In the present study, we set out to evaluate the utility of grey-matter volume in the classification of AD and amnestic mild cognitive impairment （aMCI） compared to normal control （NC）individuals. Voxel-based morphometric analyses were performed on structural MRIs from 35 AD patients, 27 aMCI patients, and 27 NC participants. A two-sample two-tailed t-test was computed between the NC and AD groups to create a map of abnormal grey matter in AD. The brain areas with significant differences were extracted as regions of interest （ROIs）, and the grey-matter volumes in the ROIs of the aMCI patients were included to evaluate the patterns of change across different disease severities. Next, correlation analyses between the grey-matter volumes in the ROIs and all clinical variables were performed in aMCI and AD patients to determine whether they varied with disease progression. The results revealed significantly decreased grey matter in the bilateral hippocampus/ parahippocampus, the bilateral superior/middle temporal gyri, and the right precuneus in AD patients.The grey-matter volumes with clinical variables were positively correlated Finally, we performed exploratory linear discriminative analyses to assess the classifying capacity of grey-matter volumes in the bilateral hippocampus and parahippocampus among AD, aMCI, and NC. Leave-one-out cross- validation analyses demonstrated that grey-matter volumes in hippocampus and parahippocampus accurately distinguished AD from NC. These findings indicate that grey-matter volumes are useful in the classification of AD.
基金supported by the Fundamental Research Funds for Central Public Welfare Research Institute of China,Nos.2015CZ-36(to HTL)and 2019CZ-7(to WZW)。
文摘At present,predicting the severity of brain injury caused by global cerebral ischemia/reperfusion injury(GCI/RI)is a clinical problem.After such an injury,clinical indicators that can directly reflect neurological dysfunction are lacking.The change in hippocampal microstructure is the key to memory formation and consolidation.Diffusion tensor imaging is a highly sensitive tool for visualizing injury to hippocampal microstructure.Although hippocampal microstructure,brain-derived neurotrophic factor(BDNF),and tropomyosin-related kinase B(Trk B)levels are closely related to nerve injury and the repair process after GCI/RI,whether these indicators can reflect the severity of such hippocampal injury remains unknown.To address this issue,we established rat models of GCI/RI using the four-vessel occlusion method.Diffusion tensor imaging parameters,BDNF,and Trk B levels were correlated with modified neurological severity scores.The results revealed that after GCI/RI,while neurological function was not related to BDNF and Trk B levels,it was related to hippocampal fractional anisotropy.These findings suggest that hippocampal fractional anisotropy can reflect the severity of hippocampal injury after global GCI/RI.The study was approved by the Institutional Animal Care and Use Committee of Capital Medical University,China(approval No.AEEI-2015-139)on November 9,2015.
基金supported by the National Key Research and Development Program of China (2017YFB1002502)the National Natural Science Foundation of China (81501550, 81600919, and 31771076)+5 种基金the Cross Training (Shipei) Project of High-Caliber Talents in Beijing Municipal Institutions (2017–2018)the Supplementary and Supportive Project for Teachers at Beijing Information Science and Technology University (2018–2020, 5029011103)the School Scientific Research Project at Beijing Information Science and Technology University (1825010) the Beijing Municipal Science and Technology Commission (Z161100000516165) the Shenzhen Peacock Plan (KQTD2015033016104926)the Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team grant (2016ZT06S220)
文摘Spinal cord stimulation （SCS） is a promising technique for treating disorders of consciousness （DOCs）. However, differences in the spatio-temporal responsiveness of the brain under varied SCS parameters remain unclear. In this pilot study, functional near-infrared spectroscopy was used to measure the hemodynamic responses of 10 DOC patients to different SCS frequencies （5 Hz, 10 Hz, 50 Hz, 70 Hz, and 100 Hz）. In the prefrontal cortex, a key area in consciousness circuits, we found significantly increased hemodynamic responses at 70 Hz and 100 Hz, and significantly different hemodynamic responses between 50 Hz and 70 Hz/100 Hz. In addition, the functional connectivity between prefrontal and occipital areas was significantly improved with SCS at 70 Hz. These results demonstrated that SCS modulates the hemodynamic responses and long-range connectivity in a frequency-specific manner （with 70 Hz apparently better）, perhaps by improving the cerebral blood volume and information transmission through the reticular formation-thalamus-cortex pathway.
文摘Severe brain injury can lead to disorders of consciousness （DOCs）. Since DOC patients cannot communicate functionally or behave purposefully, most remain bedridden and require laborious care. The medical community is often confronted with the expectations of the families of chronic DOC patients, and the social, economic, and ethical consequences are tremendous. Research on DOCs is attracting increasing attention from scientists and physicians in various fields. With the development of modern neuroimaging and neuromodulation techniques, much progress has been made in the diagnosis, prognosis, treatment, and rehabilitation of DOCs in the last decade.
基金supported by the National Natural Science Foundation of China(71471171,71071150,91432302,31620103905,31471005,and 71761167001)the Science Frontier Program of the Chinese Academy of Sciences(QYZDJSSW-SMC019)+2 种基金the Shenzhen Peacock Plan(KQTD2015033016104926)the Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team(2016ZT06S220)the CAS Key Laboratory of Behavioral Science,Institute of Psychology(Y5CX052003)
文摘An important and unresolved question is how human brain regions process information and interact with each other in intertemporal choice related to gains and losses. Using psychophysiological interaction and dynamic causal modeling analyses, we investigated the functional interactions between regions involved in the decision- making process while participants performed temporal discounting tasks in both the gains and losses domains. We found two distinct intrinsic valuation systems underlying temporal discounting in the gains and losses domains： gains were specifically evaluated in the medial regions, including the medial prefrontal and orbitofrontal cortices, and losses were evaluated in the lateral dorsolateral prefrontal cortex. In addition, immediate reward or pun- ishment was found to modulate the functional interactions between the dorsolateral prefrontal cortex and distinct regions in both the gains and losses domains： in the gains domain, the mesolimbic regions; in the losses domain, the medial prefrontal cortex, anterior cingulate cortex, and insula. These findings suggest that intertemporal choice of gains and losses might involve distinct valuation systems, and more importantly, separate neural interactions may implement the intertemporal choices of gains and losses. These findings may provide a new biological perspective for understanding the neural mechanisms underlying intertemporal choice of gains and losses.
基金supported by the National Natural Science Foundation of China(81471380,31771076,81501550,91432302,31620103905,and 81501179)the Science Frontier Program of the Chinese Academy of Sciences(QYZDJSSW-SMC019)+4 种基金National Key R&D Program of China(2017YFA0105203,2017YFB1002502)Beijing Municipal Science and Technology Commission(Z161100000216152,Z161100000216139,Z171100000117002,and Z161100000516165)the Shenzhen Peacock Plan(KQTD2015033016104926)the Guangdong Pearl River Talents Plan(2016ZT06S220)Youth Innovation Promotion Association,CAS,China
文摘Neuroimaging has opened new opportunities to study the neural correlates of consciousness, and provided additional information concerning diagnosis, prognosis, and therapeutic interventions in patients with disorders of consciousness. Here, we aim to review neuroimaging studies in chronic disorders of consciousness from the viewpoint of the brain network, focusing on positron emission tomogra- phy, functional MRI, functional near-infrared spectroscopy, electrophysiology, and diffusion MRI. To accelerate basic research on disorders of consciousness and provide a panoramic view of unconsciousness, we propose that it is urgent to integrate different techniques at various spatiotemporal scales, and to merge fragmented findings into a uniform ＂Brainnetome＂ （Brain-net-ome） research framework.
