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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 brain.To lever-age the complementary representations of different modalities,multimodal fusion is consequently needed to dig out both inter-modality and intra-modality information.With 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 status.In 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 strategies.Followed 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 diseases.Finally,we discuss some exciting emerging trends and important future directions.Collectively,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

Multimodal Brain Imaging Fusion for the White-Matter Fiber Architecture in the Human Brain

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Neuroscience Bulletin 2022年第5期38卷 561-564页

作者： Ming Song Zhengyi Yang tianzi jiang National Laboratory of Pattern Recognition Institute of AutomationThe Chinese Academy of SciencesBeijing 100190China Brainnetome Center Institute of AutomationThe Chinese Academy of SciencesBeijing 100190China University of the Chinese Academy of Sciences Beijing 100049China CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesBeijing 100190China Key Laboratory for Neuroinformation of the Ministry of Education School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengdu 625014China The Queensland Brain Institute University of QueenslandBrisbaneQLD 4072Australia

Uncovering white-matter fiber architecture,particularly that of the human brain,is one of the major and most recent interests in the neuroscience community[1].Recently,a novel analysis method for quantifying white-mat... 详细信息

关键词： fiber white resolution

EM-fMRI:A Promising Method for Mapping the Brain Functional Connectome

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Neuroscience Bulletin 2023年第4期39卷 707-709页

作者： Xiaoru Zhang Ming Song Jin Li tianzi jiang University of the Chinese Academy of Sciences Beijing100049China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of SciencesBeijing100190China Institute of Automation Chinese Academy of Sciences Brainnetome CenterBeijing100190China CAS Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of SciencesBeijing100190China School of Life and Environmental Sciences Guilin University of Electronic TechnologyGuilin541004China Research Center for Augmented Intelligence Zhejiang LabHangzhou311100China

Electrical microstimulation(EM)can be used to locally stimulate the cerebral cortex or subcortical nuclei.Meanwhile,functional magnetic resonance imaging(fMRI)can noninvasively visualize the activity of the whole brain.When EM is combined with fMRI(EM-fMRI),it is possible to measure the changes of the whole-brain neural activity using fMRI while applying electrical stimulation to a specific brain site,and accordingly infer the causal links between the stimulated site and the activated brain areas.

关键词： Mapping cerebral fMRI

Different Regional Patterns in Gray Matter-based Age Prediction

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Neuroscience Bulletin 2023年第6期39卷 984-988页

作者： Nianming Zuo Tianyu Hu Hao Liu Jing Sui Yong Liu tianzi jiang Brainnetome Center Institute of AutomationChinese Academy of SciencesBeijing100190China National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijing100190China University of Chinese Academy of Sciences Beijing100190China Chinese Institute for Brain Research Beijing102206China CAS Center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing100190China Key Laboratory for NeuroInformation of the Ministry of Education School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengdu625014China Queensland Brain Institute University of QueenslandBrisbaneQLD4072Australia

Dear Editor,The brain experiences ongoing changes across different ages to support brain development and functional reorganization.During the span of adulthood,although the brain has matured from a neurobiological per... 详细信息

关键词： shaped continuously Pattern

A review of functional magnetic resonance imaging for Brainnetome

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Neuroscience Bulletin 2012年第4期28卷 389-398页

作者： Ming Song tianzi jiang LIAMA Center for Computational Medicine National Laboratory of Pattern Recognition Institute of Automation ChineseAcademy of Sciences Beijing 100190 China Key Laboratory for NeuroInformation of Ministry of Education School of Life Science and Technology University ofElectronic Science and Technology of China Chengdu 610054 China The Queensland Brain Institute the University of Queensland Brisbane QLD 4072 Australia

The functional brain network using blood-oxygen-level-dependent（BOLD） functional magnetic resonance imaging（fMRI） has revealed the potentials for probing brain architecture,as well as for identifying clinical biomarkers for brain diseases.In the general context of Brainnetome,this review focuses on the development of approaches for modeling and analyzing functional brain networks with BOLD fMRI.The prospects for these approaches are also discussed.

关键词： functional magnetic resonance imaging brain network functional connectivity effective connectivity Brainnetome

Recent Progress in Basic and Clinical Research on Disorders of Consciousness

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Neuroscience Bulletin 2018年第4期34卷 589-591页

作者： tianzi jiang Brainnetome Center Institute of Automation Chinese Academy of Sciences National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences

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.

关键词： In Recent Progress in Basic and Clinical Research on Disorders of Consciousness

Mapping Underlying Maturational Changes in Human Brain

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Neuroscience Bulletin 2017年第4期33卷 478-480页

作者： Lingzhong Fan tianzi jiang Brainnetome Center Institute of AutomationChinese Academy of SciencesBeijing 100190China National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijing 100190China CAS Center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Key Laboratory for neuro information of the Ministry of Education School of Life Science and TechnologyUniversity of Electronic Science and Technology of ChinaChengdu 625014China The Queensland Brain Institute University of QueenslandBrisbaneQLD 4072Australia University of Chinese Academy of Sciences Beijing 100190China

Human brain development is a complex process that continues between birth and maturity, and monitoring the underlying maturational changes at these stages is crucial for our understanding of typical development as well as neurodevelopmental disorders. During the critical periods of brain development, on one hand, many human capacities originate, but on the other hand, a brain undergoing rapid plastic changes may also be vulnerable to neuropsychiatric disorders . Multi-modal magnetic resonance imaging （MRI） has been increasingly used for its ability to noninvasively reveal structural and functional changes in the brain. However, interpretation of the neurobiological processes underlying the findings obtained with MRI is very limited .

关键词： Mapping Underlying Maturational Changes in Human Brain is for it been of that from have

Diffusion magnetic resonance imaging for Brainnetome:A critical review

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Neuroscience Bulletin 2012年第4期28卷 375-388页

作者： Nianming Zuo Jian Cheng tianzi jiang LIAMM Center for Computational Medicine National Laboratory of Pattern RecognitionInstitute of AutomationTheChinese Academy of SciencesBeijing 100190China Key Laboratory for Neurolnformation of Ministry of Education School of Life Science and TechnologyUniversity ofElectronic Science and Technology of ChinaChengdu 610054China The Queensland Brain Institute The University of QueenslandBrisbaneQLD 4072Australia

Increasing evidence shows that the human brain is a highly self-organized system that shows attributes of smallworldness,hierarchy and modularity.The ＂connectome＂ was conceived several years ago to identify the underpinning physical connectivities of brain networks.The need for an integration of multi-spatial and-temporal approaches is becoming apparent.Therefore,the ＂Brainnetome＂（brain-net-ome） project was proposed.Diffusion magnetic resonance imaging（dMRI） is a non-invasive way to study the anatomy of brain networks.Here,we review the principles of dMRI,its methodologies,and some of its clinical applications for the Brainnetome.Future research in this field is discussed.

关键词： brain mapping neural networks magnetic resonance imaging imaging

Reconstruction of behavior-relevant individual brain activity:an individualized fMRI study

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Science China(Life Sciences) 2020年第3期63卷 410-418页

作者： Dongya Wu Xin Li tianzi jiang Brainnetome Center Institute of AutomationChinese Academy of SciencesBeijing 100190China National Laboratory of Pattern Recognition Institute of AutomationChinese Academy of SciencesBeijing 100190China CAS Center for Excellence in Brain Science and Intelligence Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China The Clinical Hospital of Chengdu Brain Science Institute MOE Key Lab for NeuroinformationUniversity of Electronic Science and Technology of ChinaChengdu 625014China The Queensland Brain Institute University of QueenslandBrisbane QLD 4072Australia University of Chinese Academy of Sciences Beijing 100049China School of Mathematical Sciences Zhejiang UniversityHangzhou 310027China

Different patterns of brain activity are observed in various subjects across a wide functional domain.However,these individual differences,which are often neglected through the group average,are not yet completely understood.Based on the fundamental assumption that human behavior is rooted in the underlying brain function,we speculated that the individual differences in brain activity are reflected in the individual differences in behavior.Adopting 98 behavioral measures and assessing the brain activity induced at seven task functional magnetic resonance imaging states,we demonstrated that the individual differences in brain activity can be used to predict behavioral measures of individual subjects with high accuracy using the partial least square regression model.In addition,we revealed that behavior-relevant individual differences in brain activity transferred between different task states and can be used to reconstruct individual brain activity.Reconstructed individual brain activity retained certain individual differences which were lost in the group average and could serve as an individual functional localizer.Therefore,our results suggest that the individual differences in brain activity contain behavior-relevant information and should be included in group averaging.Moreover,reconstructed individual brain activity shows a potential use in precise and personalized medicine.

关键词： individual difference brain function behavior prediction fMRI