Brain Network Analysis

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Overview

Brain network analysis represents brain regions or recording channels as nodes and their structural or functional connections as edges, using data such as MRI, fMRI, EEG, and intracranial recordings. Researchers use graph theory, dynamic network models, graph neural networks, hypergraphs, and multimodal learning to characterize connectivity and predict outcomes such as diagnosis, cognition, and disease progression. Current work increasingly explores individualized and higher-order networks, self-supervised and foundation models, and transfer across sites, atlases, and populations. A central challenge is ensuring that predictive features are reproducible and biologically meaningful despite confounds, dataset shifts, uncertain connectivity estimates, and limitations in model explanations.

Latest papers

CardsList

65 papers11 papers in the last four weeks, up 120% on the four weeks before. 0.1% of all new papers.

  1. ODEBrain: Continuous-Time EEG Graph for Modeling Dynamic Brain Networks

    Feb 26, 2026Haohui Jia, Zheng Chen, Lingwei Zhu +6Latent Dynamics ModelingElectroencephalography

    Information Science and Techinology, Hokkaido University, Japan · SANKEN, The University of Osaka, Japan · Great Bay University, China +1

  2. PIME: Prototype-based Interpretable MCTS-Enhanced Brain Network Analysis for Disorder Diagnosis

    Feb 24, 2026Kunyu Zhang, Yanwu Yang, Jing Zhang +2Brain Network AnalysisInterpretable ML

    Zhengzhou University, Zhengzhou, China · University Hospital Tübingen, Tübingen, Germany · China University of Geosciences, Wuhan, China +3

  3. LERD: Latent Event-Relational Dynamics for Neurodegenerative Classification

    Feb 20, 2026Yicheng Feng, Hairong Chen, Ziyu Jia +2Alzheimer's Disease ClassificationLatent Dynamics Modeling

    Section of Health Data Science & AI, Department of Public Health, University of Copenhagen, Copenhagen, Denmark · Institute of Information Science, Beijing Jiaotong University, Beijing, China · College of Computing and Data Science, Nanyang Technological University, Singapore +3

  4. Probability-Invariant Random Walk Learning on Gyral Folding-Based Cortical Similarity Networks for Alzheimer's and Lewy Body Dementia Diagnosis

    Feb 19, 2026Minheng Chen, Tong Chen, Chao Cao +4Alzheimer's Disease ClassificationBrain Network Analysis

    Department of Computer Science and Engineering, University of Texas at Arlington, United States · School of Computing, University of Georgia, United States · Department of Psychiatry, University of Cambridge, United Kingdom +1

  5. A Unified Geometric Space for Topological Alignment Between Transformer-Based Models and Human Brain Networks

    Oct 28, 2025Silin Chen, Yuzhong Chen, Caiwei Wang +9Neural Representation GeometryTransformer Attention

    The Clinical Hospital of Chengdu Brain Science Institute, MOE-K Lab for NeuroInformation, Brain-Apparatus Communication Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu. 611731, China. · School of Automation, Northwestern Polytechnical University, Xi’an 710072, China. · Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA. +1