Functional magnetic resonance imaging(fMRI)is a prevalent technology in brain research of cognition,emotion,development,and brain disorders.The traditional fMRI analysis is based on volume-based preprocessing pipeline...Functional magnetic resonance imaging(fMRI)is a prevalent technology in brain research of cognition,emotion,development,and brain disorders.The traditional fMRI analysis is based on volume-based preprocessing pipelines and algorithms,which means that the brain MRI data is to be registered to a 3-dimensional(3D)coordinate[1].However,the relatively low spatial resolution of fMRI may lead to partial-volume-effect(e.g.,a 3D region may contain signals from grey matter,white matter and even cerebrospinal fluid).Given the human brain function is organized in a brain surface mesh manner,therefore,a growing number of studies conducted surface-based preprocessing pipelines and algorithms.Surface-based methods reconstructed the brain grey matter into 2-dimensional cortical surface which better represent the curving structure of the brain.Surface-based method is superior to volume-based method on brain registration,signal–noise ratio and reproducibility of algorithms[2].Specifically,the traditional volume-based approach was reported with a spatial localization that is only 35%of the best surface-based method[2].展开更多
Background:As one of the leading causes of global disability,major depressive disorder(MDD)places a noticeable burden on individuals and society.Despite the great expectation on finding accurate biomarkers and effecti...Background:As one of the leading causes of global disability,major depressive disorder(MDD)places a noticeable burden on individuals and society.Despite the great expectation on finding accurate biomarkers and effective treatment targets of MDD,studies in applying functional magnetic resonance imaging(fMRI)are still faced with challenges,including the representational ambiguity,small sample size,low statistical power,relatively high false positive rates,etc.Thus,reviewing studies with solid methodology may help achieve a consensus on the pathology of MDD.Methods:In this systematic review,we screened fMRI studies on MDD through strict criteria to focus on reliable studies with sufficient sample size,adequate control of head motion,and a proper multiple comparison control strategy.Results:We found consistent evidence regarding the dysfunction within and among the default mode network(DMN),the frontoparietal network(FPN),and other brain regions.However,controversy remains,probably due to the heterogeneity of participants and data processing strategies.Conclusion:Future studies are recommended to apply a comprehensive set of neuro-behavioral measurements,consider the heterogeneity of MDD patients and other potentially confounding factors,apply surface-based neuroscientific network fMRI approaches,and advance research transparency and open science by applying state-ofthe-art pipelines along with open data sharing.展开更多
The human brain, a marvel of intricate connections, functions as a complex network comprising structurally and functionally integrated regions. This network orchestrates a multitude of complex patterns through high-le...The human brain, a marvel of intricate connections, functions as a complex network comprising structurally and functionally integrated regions. This network orchestrates a multitude of complex patterns through high-level integration and continuous cooperation, essential for overall brain functionality [1].展开更多
The publisher regrets to note that reference citation errors have occurred in panels b,c,e-l in Fig 2 and the sentence“However,the literature reports both decreased and increased intra-network functional connections ...The publisher regrets to note that reference citation errors have occurred in panels b,c,e-l in Fig 2 and the sentence“However,the literature reports both decreased and increased intra-network functional connections among patients with depression[115,116].”The publisher would like to apologise for any inconvenience caused.Fig.2.Principal neuroimaging findings in major depressive disorder.(a)Decreased intra-DMN FC is observed in recurrent MDD patients[35].(b)Eight-week antidepressant treatment reduce extensive large-scale functional networks[107].(c)Reduced global and local efficiency(Eglob/Eloc)are revealed in MDD patients[108].(d)Structural variations of the cortex and subcortical nuclei are found in ENIGMA-MDD studies[82].(e)Accelerated brain aging based on functional MRI is observed in MDD patients[114].(f)Accelerated brain aging based on structural MRI is observed in MDD patients[115].(g)Two subtypes of MDD can be identified through DMN FC[127].(h)A significant schizophrenia PRS by MDD interaction for rostral anterior cingulate cortex thickness is found in the UK Biobank dataset[215].(i)Stability of the four MDD subtypes based on FC[126].(j)The two subtypes of MDD exhibit distinct patterns of FC within and between SMS,DMN,and subcortical structures[130].(k)Performance of the functional connectivity-based classifiers across two multicenter datasets[135].(l)Salient brain regions that serve as important classification features for the graph convolutional network-based classifier[136].Brain-PAD:brain-predicted age difference;DAN:dorsal attention network;DMN:default mode network;FC:functional connectivity;FEDN:first-episode and drug-naïve;FPN:frontoparietal network;GCN:graph convolutional neural network;HC:healthy control;linear-SVM:linear support vector machine;MDD:major depressive disorder;mddrest:REST-meta-MDD dataset;NC:normal control;RACC:rostral anterior cingulate cortex;PRS:polygenic risk score;psymri:PsyMRI dataset;rbf-SVM:radial basis function support vector machine;SCN:subcortical network;SCZ:schizophrenia;SMN:sensorimotor network;SMS:sensory and motor systems;SubC:subcortical network;VAN:ventral attention network;VN:visual network.展开更多
Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders.By pooling images from various cohorts,statistical power has increased,enabling the detection of subtle abnormali...Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders.By pooling images from various cohorts,statistical power has increased,enabling the detection of subtle abnormalities and robust associations,and fostering new research methods.Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment.Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies.We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders.However,challenges such as data harmonization across different sites,privacy protection,and effective data sharing must be addressed.With proper governance and open science practices,we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis,treatment selection,and outcome prediction,contributing to optimal brain health.展开更多
Background:Early-onset schizophrenia(EOS)and autism spectrum disorder(ASD)are two mental disorders with abnormal neurodevelopment and overlapping clinical symptoms.However,few prospective multi-center imaging studies ...Background:Early-onset schizophrenia(EOS)and autism spectrum disorder(ASD)are two mental disorders with abnormal neurodevelopment and overlapping clinical symptoms.However,few prospective multi-center imaging studies explored their pathophysiological differences and similarities comprehensively.Methods:We utilized a large cohort of functional magnetic resonance imaging data with standardized scanning protocols from 594 participants(276 participants with high-functioning ASD,187 participants with EOS,and 131 normal controls(NCs))recruited at five centers.A comprehensive evaluation of anatomical and connectomic features,in-cluding cortical thickness,subcortical nuclei volume,functional connectivity,functional gradients,and network efficiency,was conducted,culminating in the construction of imaging-based neuro-profiles for individuals with EOS and ASD.Results:The derived neuro-profiles revealed that EOS is characterized by more pro-nounced reductions in cortical thickness and subcortical nuclei volumes.In contrast,ASD exhibited more pronounced abnormalities in connectomic attributes.The de-creased network functional connectivity and compressed functional gradients in ASD are likely to contribute to reduced network efficiency.Classifiers based on imaging profiles successfully distinguished individuals with EOS,ASD,and NCs with com-mendable performance in leave-site-out cross-validation(area under the operating characteristic curve(AUC)for ASD vs.NC:0.769,AUC for ASD vs.EOS:0.792,AUC for EOS vs.NC:0.854).Conclusion:The neuro-profiles revealed that EOS and ASD exhibit overlapping as well as unique imaging characteristics;however,EOS exhibits greater structural variation,while ASD presents with more subtle connectomic abnormalities.These findings offer valuable insights into the distinct neurobiological mechanisms of EOS and ASD and enhance the prospect of early diagnosis through objective imaging-based biomarkers.展开更多
Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder(MDD),repro-ducible findings are lacking,probably reflecting mostly small sample sizes and heterogeneity in analytic approac...Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder(MDD),repro-ducible findings are lacking,probably reflecting mostly small sample sizes and heterogeneity in analytic approaches.To address these issues,the Depression Imaging REsearch ConsorTium(DIRECT)was launched.The REST-meta-MDD project,pooling 2428 functional brain images processed with a standardized pipeline across all participating sites,has been the first effort from DIRECT.In this review,we present an overview of the moti-vations,rationale,and principal findings of the studies so far from the REST-meta-MDD project.Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network,in whole-brain topological properties,in dynamic features,and in functional lat-eralization.These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research.Following these fruitful explorations,DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations.A state-of-the-art,surface-based preprocessing pipeline has also been introduced to improve sensitivity.Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diag-nosis boundaries.In addition,large-scale longitudinal studies targeting brain network alterations following antidepressant treatment,aggregation of diffusion tensor images,and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway.Through these endeavours,we hope to accelerate the translation of functional neuroimaging findings to clinical use,such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets,while building an open repository for the scientific community.展开更多
Background:Abnormalities of cortical thickness(CTh)in patients with their first episode psychosis(FEP)have been frequently reported,but findings are inconsistent.Objective:To define the most consistent CTh changes in ...Background:Abnormalities of cortical thickness(CTh)in patients with their first episode psychosis(FEP)have been frequently reported,but findings are inconsistent.Objective:To define the most consistent CTh changes in patients with FEP by meta-analysis of publishedwholebrain studies.Methods:The meta-analysis used seed-based dmapping(SDM)software to obtain the most prominent regional CTh changes in FEP,and meta-regression analyses to explore the effects of demographics and clinical characteristics.The meta-analysis results were verified in an independent sample of 142 FEP patients and 142 age-and sex-matched healthy controls(HCs),using both a vertex-wise and a region of interest analysis,with multiple comparisons correction.Results:The meta-analysis identified lower CTh in the rightmiddle temporal cortex(MTC)extending to superior temporal cortex(STC),insula,and anterior cingulate cortex(ACC)in FEP compared with HCs.No significant correlations were identified between CTh alterations and demographic or clinical variables.These results were replicated in the independent dataset analysis.Conclusion:This study identifies a robust pattern of cortical abnormalities in FEP and extends understanding of gray matter abnormalities and pathological mechanisms in FEP.展开更多
Background:Rumination is a transdiagnostic psychological process that plays a prominent role in many common psychiatric disorders,albeit its neurophysiological basis remains elusive.Existing neuroimaging studies have ...Background:Rumination is a transdiagnostic psychological process that plays a prominent role in many common psychiatric disorders,albeit its neurophysiological basis remains elusive.Existing neuroimaging studies have highlighted the precuneus and hippocampus as two pivotal brain regions in rumination’s neural underpinnings.Methods:Here,we examined the intracranial electroencephalogram(iEEG)recordings from 21 patients with epilepsy during a naturalistic,continuous,active rumination state and measured the low frequency(1-8 Hz)and high gamma(70-150 Hz)band oscillation powers.Results:We observed enhanced low-frequency power in the precuneus and reduced high gamma power in the hippocampus during the rumination condition compared to the control condition.The hippocampal high gamma power reduction was associated with the self-reported reflection tendency.Conclusions:Our findings provided empirical evidence of the neurophysiological underpinnings of rumination and implicated a precuneus-hippocampus coupling across neural oscillation bands during an active rumination state.展开更多
基金supported by the National Natural Science Foundation of China(82122035,81671774,and 81630031)the 13th Five-year Informatization Plan of Chinese Academy of Sciences(XXH13505)+1 种基金the Key Research Program of the Chinese Academy of Sciences(ZDBS-SSW-JSC006)the Beijing Nova Program of Science and Technology(Z191100001119104)。
文摘Functional magnetic resonance imaging(fMRI)is a prevalent technology in brain research of cognition,emotion,development,and brain disorders.The traditional fMRI analysis is based on volume-based preprocessing pipelines and algorithms,which means that the brain MRI data is to be registered to a 3-dimensional(3D)coordinate[1].However,the relatively low spatial resolution of fMRI may lead to partial-volume-effect(e.g.,a 3D region may contain signals from grey matter,white matter and even cerebrospinal fluid).Given the human brain function is organized in a brain surface mesh manner,therefore,a growing number of studies conducted surface-based preprocessing pipelines and algorithms.Surface-based methods reconstructed the brain grey matter into 2-dimensional cortical surface which better represent the curving structure of the brain.Surface-based method is superior to volume-based method on brain registration,signal–noise ratio and reproducibility of algorithms[2].Specifically,the traditional volume-based approach was reported with a spatial localization that is only 35%of the best surface-based method[2].
基金This work was supported by the National Key R&D Program of China(2017YFC1309902 to CY)the National Natural Science Foundation of China(81671774,81630031 to CY)+4 种基金the 13th Five-year Informatization Plan of Chinese Academy of Sciences(XXH13505 to CY)the Key Research Program of the Chinese Academy of Sciences(ZDBS-SSWJSC006 to CY)Beijing Nova Program of Science and Technology(Z191100001119104 to CY)Scientific Foundation of Institute of Psychology,Chinese Academy of Sciences(Y9CX422005 to XC),China Postdoctoral Science Foundation(2019M660847 to XC)China National Postdoctoral Program for Innovative Talents(BX20200360 to XC)。
文摘Background:As one of the leading causes of global disability,major depressive disorder(MDD)places a noticeable burden on individuals and society.Despite the great expectation on finding accurate biomarkers and effective treatment targets of MDD,studies in applying functional magnetic resonance imaging(fMRI)are still faced with challenges,including the representational ambiguity,small sample size,low statistical power,relatively high false positive rates,etc.Thus,reviewing studies with solid methodology may help achieve a consensus on the pathology of MDD.Methods:In this systematic review,we screened fMRI studies on MDD through strict criteria to focus on reliable studies with sufficient sample size,adequate control of head motion,and a proper multiple comparison control strategy.Results:We found consistent evidence regarding the dysfunction within and among the default mode network(DMN),the frontoparietal network(FPN),and other brain regions.However,controversy remains,probably due to the heterogeneity of participants and data processing strategies.Conclusion:Future studies are recommended to apply a comprehensive set of neuro-behavioral measurements,consider the heterogeneity of MDD patients and other potentially confounding factors,apply surface-based neuroscientific network fMRI approaches,and advance research transparency and open science by applying state-ofthe-art pipelines along with open data sharing.
基金supported by the Sci-Tech Innovation 2030-Major Project of Brain Science and Brain-inspired Intelligence Technology (2021ZD0200600)the National Natural Science Foundation of China (82122035,81671774,81630031)+3 种基金the Key Research Program of the Chinese Academy of Sciences (ZDBSSSW-JSC006)Beijing Nova Program of Science and Technology (Z191100001119104 and 20230484465)Beijing Natural Science Foundation (J230040)the Scientific Foundation of Institute of Psychology,Chinese Academy of Sciences (E2CX4425YZ)。
文摘The human brain, a marvel of intricate connections, functions as a complex network comprising structurally and functionally integrated regions. This network orchestrates a multitude of complex patterns through high-level integration and continuous cooperation, essential for overall brain functionality [1].
文摘The publisher regrets to note that reference citation errors have occurred in panels b,c,e-l in Fig 2 and the sentence“However,the literature reports both decreased and increased intra-network functional connections among patients with depression[115,116].”The publisher would like to apologise for any inconvenience caused.Fig.2.Principal neuroimaging findings in major depressive disorder.(a)Decreased intra-DMN FC is observed in recurrent MDD patients[35].(b)Eight-week antidepressant treatment reduce extensive large-scale functional networks[107].(c)Reduced global and local efficiency(Eglob/Eloc)are revealed in MDD patients[108].(d)Structural variations of the cortex and subcortical nuclei are found in ENIGMA-MDD studies[82].(e)Accelerated brain aging based on functional MRI is observed in MDD patients[114].(f)Accelerated brain aging based on structural MRI is observed in MDD patients[115].(g)Two subtypes of MDD can be identified through DMN FC[127].(h)A significant schizophrenia PRS by MDD interaction for rostral anterior cingulate cortex thickness is found in the UK Biobank dataset[215].(i)Stability of the four MDD subtypes based on FC[126].(j)The two subtypes of MDD exhibit distinct patterns of FC within and between SMS,DMN,and subcortical structures[130].(k)Performance of the functional connectivity-based classifiers across two multicenter datasets[135].(l)Salient brain regions that serve as important classification features for the graph convolutional network-based classifier[136].Brain-PAD:brain-predicted age difference;DAN:dorsal attention network;DMN:default mode network;FC:functional connectivity;FEDN:first-episode and drug-naïve;FPN:frontoparietal network;GCN:graph convolutional neural network;HC:healthy control;linear-SVM:linear support vector machine;MDD:major depressive disorder;mddrest:REST-meta-MDD dataset;NC:normal control;RACC:rostral anterior cingulate cortex;PRS:polygenic risk score;psymri:PsyMRI dataset;rbf-SVM:radial basis function support vector machine;SCN:subcortical network;SCZ:schizophrenia;SMN:sensorimotor network;SMS:sensory and motor systems;SubC:subcortical network;VAN:ventral attention network;VN:visual network.
基金supported by the Sci-Tech Innovation 2030-Major Projects of Brain Science and Brain-inspired Intelligence Technology(2021ZD0200600)the National Natural Science Foundation of China(82122035,81671774,81630031,32300933)+3 种基金the Key Research Program of the Chinese Academy of Sciences(ZDBS-SSW-JSC006)Beijing Nova Program of Science and Technology(Z191100001119104 and 20230484465)Beijing Natural Science Foundation(J230040)the Scientific Foundation of Institute of Psychology,Chinese Academy of Sciences(E3CX1425,E2CX4425YZ).
文摘Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric disorders.By pooling images from various cohorts,statistical power has increased,enabling the detection of subtle abnormalities and robust associations,and fostering new research methods.Global collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted treatment.Large-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric studies.We also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric disorders.However,challenges such as data harmonization across different sites,privacy protection,and effective data sharing must be addressed.With proper governance and open science practices,we conclude with a projection of how large-scale imaging resources and collaborations could revolutionize diagnosis,treatment selection,and outcome prediction,contributing to optimal brain health.
基金supported by the National Key R&D Program of China(2017YFC1309900)the National Natural Science Foundation of China(82122035,81671774,81630031,and 81571339)+3 种基金the Key Research Program of the Chinese Academy of Sciences(ZDBS-SSW-JSC006)the Beijing Nova Program of Science and Technology(Z191010001119104)the Key-Area Research and Development Program of Guangdong Province(2019B030335001)the Scientific Foundation of Institute of Psychology,Chinese Academy of Sciences(E3CX1425 and E2CX4425YZ).
文摘Background:Early-onset schizophrenia(EOS)and autism spectrum disorder(ASD)are two mental disorders with abnormal neurodevelopment and overlapping clinical symptoms.However,few prospective multi-center imaging studies explored their pathophysiological differences and similarities comprehensively.Methods:We utilized a large cohort of functional magnetic resonance imaging data with standardized scanning protocols from 594 participants(276 participants with high-functioning ASD,187 participants with EOS,and 131 normal controls(NCs))recruited at five centers.A comprehensive evaluation of anatomical and connectomic features,in-cluding cortical thickness,subcortical nuclei volume,functional connectivity,functional gradients,and network efficiency,was conducted,culminating in the construction of imaging-based neuro-profiles for individuals with EOS and ASD.Results:The derived neuro-profiles revealed that EOS is characterized by more pro-nounced reductions in cortical thickness and subcortical nuclei volumes.In contrast,ASD exhibited more pronounced abnormalities in connectomic attributes.The de-creased network functional connectivity and compressed functional gradients in ASD are likely to contribute to reduced network efficiency.Classifiers based on imaging profiles successfully distinguished individuals with EOS,ASD,and NCs with com-mendable performance in leave-site-out cross-validation(area under the operating characteristic curve(AUC)for ASD vs.NC:0.769,AUC for ASD vs.EOS:0.792,AUC for EOS vs.NC:0.854).Conclusion:The neuro-profiles revealed that EOS and ASD exhibit overlapping as well as unique imaging characteristics;however,EOS exhibits greater structural variation,while ASD presents with more subtle connectomic abnormalities.These findings offer valuable insights into the distinct neurobiological mechanisms of EOS and ASD and enhance the prospect of early diagnosis through objective imaging-based biomarkers.
基金funded by the National Key R&D Program of China no.2017YFC1309902the National Natural Science Foundation of China grant numbers 82122035,81671774,and 81630031+3 种基金the 13th Five-year Informatization Plan of Chinese Academy of Sciences grant no.XXH13505the Key Research Program of the Chinese Academy of Sciences no.ZDBS-SSW-JSC006Beijing Nova Program of Science and Technology no.Z191100001119104the China National Postdoctoral Program for Innovative Talents no.BX20200360.
文摘Despite a growing neuroimaging literature on the pathophysiology of major depressive disorder(MDD),repro-ducible findings are lacking,probably reflecting mostly small sample sizes and heterogeneity in analytic approaches.To address these issues,the Depression Imaging REsearch ConsorTium(DIRECT)was launched.The REST-meta-MDD project,pooling 2428 functional brain images processed with a standardized pipeline across all participating sites,has been the first effort from DIRECT.In this review,we present an overview of the moti-vations,rationale,and principal findings of the studies so far from the REST-meta-MDD project.Findings from the first round of analyses of the pooled repository have included alterations in functional connectivity within the default mode network,in whole-brain topological properties,in dynamic features,and in functional lat-eralization.These well-powered exploratory observations have also provided the basis for future longitudinal hypothesis-driven research.Following these fruitful explorations,DIRECT has proceeded to its second stage of data sharing that seeks to examine ethnicity in brain alterations in MDD by extending the exclusive Chinese original sample to other ethnic groups through international collaborations.A state-of-the-art,surface-based preprocessing pipeline has also been introduced to improve sensitivity.Functional images from patients with bipolar disorder and schizophrenia will be included to identify shared and unique abnormalities across diag-nosis boundaries.In addition,large-scale longitudinal studies targeting brain network alterations following antidepressant treatment,aggregation of diffusion tensor images,and the development of functional magnetic resonance imaging-guided neuromodulation approaches are underway.Through these endeavours,we hope to accelerate the translation of functional neuroimaging findings to clinical use,such as evaluating longitudinal effects of antidepressant medications and developing individualized neuromodulation targets,while building an open repository for the scientific community.
基金supported by the National Natural Science Foundation of China(grant nos 81621003,81761128023,81820108018,82027808,and 82001795)NIH/NIMH R01MH112189-01,China Postdoctoral Science Foundation(2020M673245)+3 种基金Post-Doctor Research Project of West China Hospital of Sichuan University(2021HXBH025)US-China joint grant(grant nos NSFC81761128023)Instituto de Salud Carlos III/European Union(ERDF/ESF,‘Investing in your future’:CPII19/00009 and PI19/00394)the project SLT006/17/00357,from PERIS 2016-2020(Departament de Salut),CERCA Programme/Generalitat de Catalunya.
文摘Background:Abnormalities of cortical thickness(CTh)in patients with their first episode psychosis(FEP)have been frequently reported,but findings are inconsistent.Objective:To define the most consistent CTh changes in patients with FEP by meta-analysis of publishedwholebrain studies.Methods:The meta-analysis used seed-based dmapping(SDM)software to obtain the most prominent regional CTh changes in FEP,and meta-regression analyses to explore the effects of demographics and clinical characteristics.The meta-analysis results were verified in an independent sample of 142 FEP patients and 142 age-and sex-matched healthy controls(HCs),using both a vertex-wise and a region of interest analysis,with multiple comparisons correction.Results:The meta-analysis identified lower CTh in the rightmiddle temporal cortex(MTC)extending to superior temporal cortex(STC),insula,and anterior cingulate cortex(ACC)in FEP compared with HCs.No significant correlations were identified between CTh alterations and demographic or clinical variables.These results were replicated in the independent dataset analysis.Conclusion:This study identifies a robust pattern of cortical abnormalities in FEP and extends understanding of gray matter abnormalities and pathological mechanisms in FEP.
基金supported by the National Natural Science Foundation of China(32300933,82122035,81671774,and 81630031)the China Scholarship Council(202104910248)+6 种基金the Sci-Tech Innovation 2030-Major Project of Brain Science and Brain-inspired Intelligence Technology(2021ZD0200600)the National Key R&D Program of China(2017YFC1309902)the 13th Five-year Informatization Plan of Chinese Academy of Sciences(XXH13505)the Key Research Program of the Chinese Academy of Sciences(ZDBS-SSW-JSC006)the Beijing Nova Program of Science and Technology(Z191100001119104 and 20230484465)the Beijing Natural Science Foundation(J230040)the Scientific Foundation of Institute of Psychology,Chinese Academy of Sciences(E2CX4425YZ).
文摘Background:Rumination is a transdiagnostic psychological process that plays a prominent role in many common psychiatric disorders,albeit its neurophysiological basis remains elusive.Existing neuroimaging studies have highlighted the precuneus and hippocampus as two pivotal brain regions in rumination’s neural underpinnings.Methods:Here,we examined the intracranial electroencephalogram(iEEG)recordings from 21 patients with epilepsy during a naturalistic,continuous,active rumination state and measured the low frequency(1-8 Hz)and high gamma(70-150 Hz)band oscillation powers.Results:We observed enhanced low-frequency power in the precuneus and reduced high gamma power in the hippocampus during the rumination condition compared to the control condition.The hippocampal high gamma power reduction was associated with the self-reported reflection tendency.Conclusions:Our findings provided empirical evidence of the neurophysiological underpinnings of rumination and implicated a precuneus-hippocampus coupling across neural oscillation bands during an active rumination state.
