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Neuroscience Bulletin 2024年第7期40卷 905-920页

作者： Xingyu He Vince D.Calhoun Yuhui Du School of Computer and Information Technology Shanxi UniversityTaiyuan 030006China Tri-Institutional center for Translational Research in neuroimaging and Data Science Georgia State UniversityGeorgia Institute of TechnologyEmory UniversityAtlanta 30303USA

functional networks(FNs)hold significant promise in understanding brain *** component analysis(ICA)has been applied in estimating FNs from functional magnetic resonance imaging(fMRI).However,determining an optimal model order for ICA remains challenging,leading to criticism about the reliability of FN ***,we propose a SMART(splitting-merging assisted reliable)ICA method that automatically extracts reliable FNs by clustering independent components(ICs)obtained from multi-model-order ICA using a simplified graph while providing linkages among FNs deduced from different-model *** extend SMART ICA to multi-subject fMRI analysis,validating its effectiveness using simulated and real fMRI *** on simulated data,the method accurately estimates both group-common and group-unique components and demonstrates robustness to *** two age-matched cohorts of resting fMRI data comprising 1,950 healthy subjects,the resulting reliable group-level FNs are greatly similar between the two cohorts,and interestingly the subject-specific FNs show progressive changes while age ***,both small-scale and large-scale brain FN templates are provided as benchmarks for future *** together,SMART ICA can automatically obtain reliable FNs in analyzing multi-subject fMRI data,while also providing linkages between different FNs.

关键词： Independent component analysis functional magnetic resonance imaging-Brain functional networks Clustering Multi-model-order

PLAU plays a functional role in driving lung squamous cell carcinoma metastasis

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Genes & Diseases 2024年第2期11卷 554-557页

作者： Pengbo Ning Fuyu Du Xiaocheng Gong Jingtong Yuan Caixia Ding Xilian Zhao Wei Li School of Life Science and Technology Xidian UniversityXi'anShaanxi 710071China Engineering Research center of Molecular & neuroimaging Ministry of EducationXi'anShaanxi 710071China Department of Medical Oncology Zhongshan HospitalFudan UniversityShanghai 200032China Department of Pathology Shaanxi Provincial Tumor HospitalXi'an Jiaotong UniversityXi'anShaanxi 710061China

The high mortality of patients with lung squamous cell carcinoma(LUSC)results from metastasis rather than primary tumors,1 whereas the molecular pathogenesis of cancer metastasis remains poorly *** encodes urokinase-type plasminogen activator(uPA)which is closely related to tumor diagnosis,treatment target,and prognosis of patients.2.3 We previously predicted that PLAU is a key gene negatively associated with overall survival by integrated multidimensional analyses of The Cancer Genome Atlas(TCGA)datasets from 504 samples of LUSC tumor tissues and 46 samples of adjacent non-tumorous lung tissues.4 However,whether the role of PLAU contributes to the metastasis of LUC remains ***,we analyzed the association between uPA levels and LUSC and found that uPA levels were associated with pathological variations in LUSC patients.

关键词： metastasis lung squamous

Dynamic Organization of Large-scale functional Brain Networks Supports Interactions Between Emotion and Executive Control

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Neuroscience Bulletin 2024年第7期40卷 981-991页

作者： Haiyang Geng Pengfei Xu Andre Aleman Shaozheng Qin Yue-Jia Luo State Key Laboratory of Cognitive Neuroscience and Learning Beijing Normal UniversityBeijing 100875China Tianqiao and Chrissy Chen Institute for Translational ResearchShanghai 200040China Beijing Key Laboratory of Applied Experimental Psychology National Demonstration Center for Experimental Psychology Education(BNU)Faculty of PsychologyBeijing Normal UniversityBeijing 100875China center for neuroimaging Shenzhen Institute of NeuroscienceShenzhen 518107China University of Groningen Department of Biomedical Sciences of Cells and SystemsSection Cognitive NeuroscienceUniversity Medical Center GroningenGroningenThe Netherlands Institute for Neuropsychological Rehabilitation University of Health and Rehabilitation SciencesQingdao 266113China Shenzhen Key Laboratory of Affective and Social Neuroscience Magnetic Resonance ImagingCenter for Brain Disorders and Cognitive SciencesShenzhen UniversityShenzhen 518060China Chinese Institute for Brain Research Beijing 102206China

Emotion and executive control are often conceptualized as two distinct modes of human brain ***,however,is known about how the dynamic organization of large-scale functional brain networks that support flexible emotion processing and executive control,especially their *** amygdala and prefrontal systems have long been thought to play crucial roles in these *** advances in human neuroimaging studies have begun to delineate functional organization principles among the large-scale brain networks underlying emotion,executive control,and their ***,we propose a dynamic brain network model to account for interactive competition between emotion and executive control by reviewing recent resting-state and task-related neuroimaging studies using network-based *** this model,dynamic interactions among the executive control network,the salience network,the default mode network,and sensorimotor networks enable dynamic processes of emotion and support flexible executive control of multiple processes;neural oscillations across multiple frequency bands and the locus coeruleus−norepinephrine pathway serve as communicational mechanisms underlying dynamic synergy among large-scale functional brain *** model has important implications for understanding how the dynamic organization of complex brain systems and networks empowers flexible cognitive and affective functions.

关键词： Dynamic brain network Emotion Executive control Salience network Executive control network Default mode network

functional near-infrared spectroscopy in non-invasive neuromodulation

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Neural Regeneration Research 2024年第7期19卷 1517-1522页

作者： Congcong Huo Gongcheng Xu Hui Xie Tiandi Chen Guangjian Shao Jue Wang Wenhao Li Daifa Wang Zengyong Li Beijing Advanced Innovation center for Biomedical Engineering Key Laboratory for Biomechanics and Mechanobiology of Ministry of EducationSchool of Biological Science and Medical EngineeringBeihang UniversityBeijingChina Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability National Research Center for Rehabilitation Technical AidsBeijingChina School of Mechatronic Engineering and Automation Foshan UniversityFoshanGuangdong ProvinceChina School of Rehabilitation Engineering Beijing College of Social AdministrationBeijingChina Key Laboratory of Neuro-functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs BeijingChina

Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks,which have been widely applied in the field of central neurological diseases,such as stroke,Parkinson’s disease,and mental *** significant advances have been made in neuromodulation technologies,the identification of optimal neurostimulation paramete rs including the co rtical target,duration,and inhibition or excitation pattern is still limited due to the lack of guidance for neural *** r,the neural mechanism unde rlying neuromodulation for improved behavioral performance remains poorly ***,advancements in neuroimaging have provided insight into neuromodulation *** near-infrared spectroscopy,as a novel non-invasive optical brain imaging method,can detect brain activity by measuring cerebral hemodynamics with the advantages of portability,high motion tole rance,and anti-electromagnetic *** functional near-infra red spectroscopy with neuromodulation technologies offe rs an opportunity to monitor the cortical response,provide realtime feedbac k,and establish a closed-loop strategy integrating evaluation,feedbac k,and intervention for neurostimulation,which provides a theoretical basis for development of individualized precise neuro *** aimed to summarize the advantages of functional near-infra red spectroscopy and provide an ove rview of the current research on functional near-infrared spectroscopy in transcranial magnetic stimulation,transcranial electrical stimulation,neurofeedback,and braincomputer ***,the future perspectives and directions for the application of functional near-infrared spectroscopy in neuromodulation are *** conclusion,functional near-infrared spectroscopy combined with neuromodulation may promote the optimization of central pellral reorganization to achieve better functional recovery form central nervous system

关键词： brain-computer interface cerebral neural networks functional near-infrared spectroscopy neural circuit neurofeedback neurological diseases neuromodulation non-invasive brain stimulation transcranial electrical stimulation transcranial electrical stimulation

Research progresses of resting-state functional MRI in mild cognitive impairment and Alzheimer's disease

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中国医学影像技术 2024年第8期40卷 1254-1257页

作者： DUAN Huanqin LI Linqin QIU Lihua Department of Radiology the Affiliated Hospital of North Sichuan Medical CollegeNanchong 637000China Department of Medical Imaging center Second People's Hospital of YibinYibin 644000China School of Medical and Life Sciences Chengdu University of Traditional Chinese MedicineChengdu 611137China neuroimaging Big Data Research center Clinical Medical Research and Transformation CenterSecond People's Hospital of YibinYibin 644000China

Alzheimer's disease(AD)is a prevalent neurodegenerative disease characterized by cognitive decline in the early *** cognitive impairment(MCI)is considered as an intermediate stage between normal aging and *** recent years,studies related to resting-state functional MRI(rs-fMRI)indicated that the occurrence and development process of MCI and AD might be closely linked to spontaneous brain activity and alterations in functional connectivity among brain regions,and rs-fMRI could provide important reference for specific diagnosis and early treatment of MCI and *** research progresses of rs-fMRI for MCI and AD were reviewed in this article.

关键词： Alzheimer disease cognition disorders magnetic resonance imaging

Multimodal Fusion of Brain Imaging Data: Methods and Applications

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Machine Intelligence Research 2024年第1期21卷 136-152页

作者： Na Luo Weiyang Shi Zhengyi Yang Ming Song Tianzi Jiang Brainnetome center and National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Research center for Augmented Intelligence Zhejiang LaboratoryHangzhou 311100China

neuroimaging data typically include multiple modalities,such as structural or functional magnetic resonance imaging,dif-fusion tensor imaging,and positron emission tomography,which provide multiple views for observing and analyzing the *** lever-age the complementary representations of different modalities,multimodal fusion is consequently needed to dig out both inter-modality and intra-modality *** the exploited rich information,it is becoming popular to combine multiple modality data to ex-plore the structural and functional characteristics of the brain in both health and disease *** this paper,we first review a wide spectrum of advanced machine learning methodologies for fusing multimodal brain imaging data,broadly categorized into unsupervised and supervised learning *** by this,some representative applications are discussed,including how they help to under-stand the brain arealization,how they improve the prediction of behavioral phenotypes and brain aging,and how they accelerate the biomarker exploration of brain ***,we discuss some exciting emerging trends and important future ***,we intend to offer a comprehensive overview of brain imaging fusion methods and their successful applications,along with the chal-lenges imposed by multi-scale and big data,which arises an urgent demand on developing new models and platforms.

关键词： Multimodal fusion supervised learning unsupervised learning brain atlas cognition brain disorders

众脑之力:通过开放神经影像数据和大规模协作催化神经精神疾病的创新发现

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Science Bulletin 2024年第10期69卷 1536-1555页

作者：鲁彬陈骁 Francisco Xavier Castellanos Paul M.Thompson 左西年臧玉峰严超赣 CAS Key Laboratory of Behavioral Science Institute of PsychologyBeijing 100101China Department of Psychology University of Chinese Academy of SciencesBeijing 100101China Department of Child and Adolescent Psychiatry NYU Grossman School of MedicineNew York 10016USA d Nathan Kline Institute for Psychiatric Research Orangeburg 10962USA Imaging Genetics center Mark&Mary Stevens Institute for Neuroimaging&InformaticsKeck School of MedicineUniversity of Southern CaliforniaLos Angeles 90033USA Developmental Population Neuroscience Research center IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijing 100875China National Basic Science Data center Beijing 100190China Centre for Cognition and Brain Disorders The Affiliated Hospital of Hangzhou Normal UniversityHangzhou 310004China Institute of Psychological Science Hangzhou Normal UniversityHangzhou 310030China Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairment Hangzhou 311121China International Big-Data center for Depression Research Institute of PsychologyChinese Academy of SciencesBeijing 100101China Magnetic Resonance Imaging Research center Institute of PsychologyChinese Academy of SciencesBeijing 100101China

Recent advances in open neuroimaging data are enhancing our comprehension of neuropsychiatric *** pooling images from various cohorts,statistical power has increased,enabling the detection of subtle abnormalities and robust associations,and fostering new research *** collaborations in imaging have furthered our knowledge of the neurobiological foundations of brain disorders and aided in imaging-based prediction for more targeted ***-scale magnetic resonance imaging initiatives are driving innovation in analytics and supporting generalizable psychiatric *** also emphasize the significant role of big data in understanding neural mechanisms and in the early identification and precise treatment of neuropsychiatric ***,challenges such as data harmonization across different sites,privacy protection,and effective data sharing must be *** 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.

关键词： Magnetic resonance imaging Neuropsychiatric disorders Big data Open science Artificial intelligence

Using multimodal MRI to investigate alterations in brain structure and function in the BBZDR/Wor rat model of type 2 diabetes

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Animal Models and Experimental Medicine 2020年第4期3卷 285-294页

作者： Christopher M.Lawson Kilian F.G.Rentrup Xuezhu Cai Praveen P.Kulkarni Craig F.Ferris center for Translational neuroimaging Northeastern UniversityBostonMAUSA

Background:This is an exploratory study using multimodal magnetic resonance imaging(MRI)to interrogate the brain of rats with type 2 diabetes(T2DM)as compared to *** was hypothesized there would be changes in brain structure and function that reflected the human disorder,thus providing a model system by which to follow disease progression with noninvasive ***:The transgenic BBZDR/Wor rat,an animal model of T2MD,and agematched controls were studied for changes in brain structure using voxel-based morphometry,alteration in white and gray matter microarchitecture using diffusion weighted imaging with indices of anisotropy,and functional coupling using restingstate BOLD functional *** from each modality were registered to,and analyzed,using a 3D MRI rat atlas providing site-specific data on over 168 different brain ***:There was an overall reduction in brain volume focused primarily on the somatosensory cortex,cerebellum,and white matter *** putative changes in white and gray matter microarchitecture were pervasive affecting much of the brain and not localized to any *** was a general increase in connectivity in T2DM rats as compared to *** cerebellum presented with strong functional coupling to pons and brainstem in T2DM rats but negative connectivity to ***:The neuroradiological measures collected in BBBKZ/Wor rats using multimodal imaging methods did not reflect those reported for T2DB patients in the *** data would suggest the BBBKZ/Wor rat is not an appropriate imaging model for T2DM.

关键词： BBZDR/Wor rat diffusion weighted imaging magnetic resonance imaging resting-state BOLD functional imaging small vessel disease voxel-based morphometry

Imaging Brain Activity during Natural Vision Using CASL Perfusion fMRI

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Imaging Brain Activity during Natural Vision Using CASL Perf...

Individualized brain mapping for navigated neuromodulation

第一届全国脑与认知科学学术研讨会

作者： Kathy Tang John A.Detre Dept of Neurology ＆ center for functional neuroimaging Univ.of Pennsylvania USA Dept of Neurology ＆ center for functional neuroimaging Univ.of Pennsylvania USA

＜正＞Introduction The neural substrates underlying the processes of natural scenes in everyday vision remains poorly understood, which may due to the much longer time-scales of natural vision than the duration of strictly controlled conditions in optimal BOLD fMRI studies, and the complex scenes of multiple objects moving in spatial and temporal dimensions. Recently, Arterial spin labeling （ASL） perfusion fMRI has emerged as an appealing alternative to BOLD fMRI for imaging the longitudinal processes like natural conditions because of its noninvasive quantification of absolute cerebral blood flow （CBF） and long term temporal stability. The

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Chinese Medical Journal 2024年第5期137卷 508-523页

作者： Chaohong Gao Xia Wu Xinle Cheng Kristoffer Hougaard Madsen Congying Chu Zhengyi Yang Lingzhong Fan Sino–Danish College University of Chinese Academy of SciencesBeijing 100190China Brainnetome center National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100190China Department of Applied Mathematics and Computer Science Technical University of DenmarkKongens Lyngby 2800Denmark Danish Research Centre for Magnetic Resonance Centre for Functional and Diagnostic Imaging and ResearchCopenhagen University Hospital Amager and HvidovreHvidovre 2650Denmark CAS center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Health and Life Sciences University of Health and Rehabilitation SciencesQingdaoShandong 266000China

The brain is a complex organ that requires precise mapping to understand its structure and *** atlases provide a powerful tool for studying brain circuits,discovering biological markers for early diagnosis,and developing personalized treatments for neuropsychiatric *** techniques,such as transcranial magnetic stimulation and deep brain stimulation,have revolutionized clinical therapies for neuropsychiatric ***,the lack of fine-scale brain atlases limits the precision and effectiveness of these *** in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation ***,the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized *** article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles,advantages,disadvantages,and future trends of these *** article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

关键词： Brain atlas Individualization Navigated neuromodulation Multimodal magnetic resonance imaging Transcranial magnetic stimulation Deep brain stimulation