Neuroimaging

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Overview

Neuroimaging studies the brain using modalities such as MRI, functional MRI, diffusion imaging, PET, EEG, and MEG, to understand brain organization and support diagnosis and treatment. Methods range from image registration, segmentation, and signal modeling to machine learning that predicts clinical outcomes or decodes responses to stimuli; newer work also combines modalities and models brain changes over time. Self-supervised and foundation models, generative methods, and graph-based analyses are being explored to make better use of large, heterogeneous datasets and capture brain structure and dynamics. A central challenge is whether gains on familiar datasets generalize across scanners, sites, and populations while producing reliable, interpretable results that can be validated in clinical settings.

Latest papers

CardsList

235 papers30 papers in the last four weeks, up 15% on the four weeks before. 0.2% of all new papers.

  1. BrainSTR: Spatio-Temporal Contrastive Learning for Interpretable Dynamic Brain Network Modeling

    Mar 10, 2026Guiliang Guo, Guangqi Wen, Lingwen Liu +6Dynamic Functional ConnectivityBrain Network Analysis

    Computer Science and Engineering, Northeastern University, Shenyang, China · School of Computer Science and Artificial Intelligence, Shandong Normal University, Jinan, China · Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Fukuoka, Japan +3

  2. Multimodal Deep Learning for Dynamic and Static Neuroimaging: Integrating MRI and fMRI for Alzheimer Disease Analysis

    Mar 9, 2026Anima Kujur, Zahra MonfaredAlzheimer's Disease ClassificationNeuroimaging

    Interdisciplinary Centre for Scientific Computing (IWR), Department of Mathematics and Computer Science, Heidelberg University, Germany

  3. BrainCast: A Spatio-Temporal Forecasting Model for Whole-Brain fMRI Time Series Prediction

    Mar 9, 2026Yunlong Gao, Jinbo Yang, Li Xiao +5Time Series ForecastingSpatiotemporal Forecasting

    Institute of Advanced Technology, University of Science and Technology of China, Hefei 230052, China. · MoE Key Laboratory of Brain-Inspired Intelligence Perception and Cognition, University of Science and Technology of China, Hefei 230052, China. · School of Mathematics and Computer Sciences, Nanchang University, Nanchang 330031, China. +3

  4. Neural Dynamics-Informed Pre-trained Framework for Personalized Brain Functional Network Construction

    Mar 8, 2026Hongjie Jiang, Yifei Tang, Shuqiang WangBrain Network AnalysisFunctional Connectivity

    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.

  5. An Approach to Simultaneous Acquisition of Real-Time MRI Video, EEG, and Surface EMG for Articulatory, Brain, and Muscle Activity During Speech Production

    Mar 5, 2026Jihwan Lee, Parsa Razmara, Kevin Huang +16NeuroimagingSpeech Production

    Signal Analysis and Interpretation Laboratory, University of Southern California · Ming Hsieh Dept. of Electrical and Computer Engineering, University of Southern California · Dept. of Linguistics, University of Southern California

  6. LUMINA: Laplacian-Unifying Mechanism for Interpretable Neurodevelopmental Analysis via Quad-Stream GCN

    Mar 5, 2026Minkyung Cha, Jooyoung Bae, Jaewon Jung +3GNN OversmoothingGraph Neural Networks

    Seoul National University, Seoul, Republic of Korea · NVIDIA AI Technology Center HK, Hong Kong

  7. A Unified Framework for Joint Detection of Lacunes and Enlarged Perivascular Spaces

    Mar 4, 2026Lucas He, Krinos Li, Hanyuan Zhang +7NeuroimagingBrain MRI

    Hawkes Institute, University College London, UK · Unit for Lifelong Health and Aging, University College London, UK · Bioengineering Department and Imperial-X, Imperial College London, UK +6

  8. Beyond Anatomy: Explainable ASD Classification from rs-fMRI via Functional Parcellation and Graph Attention Networks

    Mar 3, 2026Syeda Hareem Madani, Noureen Bibi, Adam Rafiq Jeraj +3Autism Spectrum DisorderNeuroimaging

    Salim Habib University · VentureDive · National University of Computer and Emerging Sciences

  9. Multiple Inputs and Mixwd data for Alzheimer's Disease Classification Based on 3D Vision Transformer

    Feb 28, 2026Juan A. Castro-Silva, Maria N. Moreno Garcia, Diego H. Peluffo-OrdoñezAlzheimer's Disease ClassificationMultimodal Classification

    Faculty of Engineering, Universidad Surcolombiana, Neiva 410002, Colombia · College of Computing, Mohammed VI Polytechnic University, Lot 660, Hay Moulay Rachid, Ben Guerir 43150, Morocco

  10. SHINE: Sequential Hierarchical Integration Network for EEG and MEG

    Feb 27, 2026Xiran Xu, Yujie Yan, Songyi Li +4ElectroencephalographyNeural Processes

    Speech and Hearing Research Center, School of Intelligence Science and Technology, Peking University, China · National Key Laboratory of General Artificial Intelligence, China · Center for BioMed-X Research, Academy for Advanced Interdisciplinary Studies, Peking University, China

  11. 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

  12. Token-UNet: A New Case for Transformers Integration in Efficient and Interpretable 3D UNets for Brain Imaging Segmentation

    Feb 23, 2026Louis Fabrice Tshimanga, Andrea Zanola, Federico Del Pup +13D Medical Image SegmentationHybrid CNN-Transformer Architectures

  13. A Data-Driven Method to Map the Functional Organisation of Human Brain White Matter

    Feb 21, 2026Yifei Sun, James M. Shine, Robert D. Sanders +4Functional ConnectivityNeuroimaging

    School of Biomedical Engineering, The University of Sydney, Sydney, 2050, Australia. · Brain and Mind Centre, The University of Sydney, Sydney, 2050, Australia. · School of Medical Science, The University of Sydney, Sydney, 2050, Australia. +5

  14. Machine Learning-Based Classification of Jhana Advanced Concentrative Absorption Meditation Using 7 Tesla Functional Magnetic Resonance Imaging

    Feb 13, 2026Puneet Kumar, Winson F. Z. Yang, Alakhsimar Singh +2Functional Magnetic Resonance ImagingNeural Decoding

    School of AI and Data Engineering, Indian Institute of Technology Ropar 140001, India · Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA · Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02129, USA +2

  15. Data-Driven Registration and Modeling of Brain Deformation for Image-Guided Neurosurgery: A Systematic Review

    Feb 9, 2026Tiago Assis, Colin P. Galvin, Joshua P. Castillo +12NeuroimagingDeformable Image Registration

    LASIGE, Faculty of Sciences, University of Lisbon, 1749-016 Lisbon, Portugal · Department of Neurosurgery and Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA · Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, QC H3G 2W1, Canada +5

  16. BrainNormalizer: Anatomy-Informed Pseudo-Healthy Brain Reconstruction from Tumor MRI via Edge-Guided ControlNet

    Nov 17, 2025Min Gu Kwak, Yeonju Lee, Hairong Wang +2Diffusion Models for Image RestorationMedical Image Synthesis

    Department of Health and Rehabilitation Sciences, University of Pittsburgh, Pittsburgh, PA, USA · H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA,2026 USA · Operations Research and Industrial Engineering, Cockrell School of Engineering, University of Texas at Austin, Austin, TX, USAJul +2

  17. Hi-DREAM: Brain-Inspired Hierarchical Diffusion for fMRI-to-Image Reconstruction via ROI Encoder and VisuAl Mapping

    Nov 14, 2025Guowei Zhang, Yun Zhao, Kai Sun +4Visual NeuroscienceConditional Image Generation

    Dept of Data Science and AI, Monash University, Melbourne, Australia · Brain and Mind Centre, University of Sydney, Sydney, Australia · School of Psychological Sciences, Monash University, Melbourne, Australia

  18. Scaling Vision Transformers for Functional MRI with Flat Maps

    Oct 15, 2025Connor Lane, Mihir Tripathy, Leema Krishna Murali +15fMRI Foundation ModelsMasked Autoencoders

    MedARC · Sophont · Baylor College of Medicine +3

  19. On a Geometry of Interbrain Networks

    Sep 12, 2025Nicolás Hinrichs, Noah Guzmán, Melanie WeberNeuroimaging

    Neural Data Science and Statistical Computing Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany · Embodied Cognitive Science Unit, Okinawa Institute of Science and Technology, Okinawa, Japan · Independent Scholar +1

  20. Reduced NEXI protocol for the quantification of human gray matter microstructure on the Connectome 2.0 scanner

    Sep 11, 2025Quentin Uhl, Tommaso Pavan, Julianna Gerold +10Magnetic Resonance ImagingNeuroimaging

    Department of Radiology, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland · Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Boston, MA, USA

  21. Uncertain but Useful: Leveraging CNN Training Variability into Data Augmentation

    Sep 5, 2025Inés Gonzalez-Pepe, Vinuyan Sivakolunthu, Yohan Chatelain +1Image SegmentationData Augmentation

    Department of Computer Science Concordia University Montreal, QC H3G 1M8, Canada · Department of Computer Science Concordia University2026 Montreal, QC H3G 1M8, Canada · Krembil Centre for Neuroinformatics Centre for Addiction and Mental Health Toronto, ON M5T 0S8, Canada +1

  22. Achieving detailed medial temporal lobe segmentation with upsampled isotropic training from implicit neural representation

    Aug 24, 2025Yue Li, Pulkit Khandelwal, Rohit Jena +8Alzheimer's DiseaseImage Segmentation

    University of Pennsylvania, Philadelphia, United States · Siemens Healthineers, Princeton, United States · Lund University, Lund, Sweden

  23. A Multimodal Sequence-to-Sequence Model for Cross-Subject Prediction of Brain Responses to Naturalistic Stimuli

    Jul 24, 2025Qianyi He, Monica D. Rosenberg, Yuan Chang LeongNeural DecodingNeuroimaging

    Data Science Institute University of Chicago, USA · Department of Psychology, Neuroscience Institute University of Chicago, USA

  24. Explainable Graph-theoretical Machine Learning with Application to Alzheimer's Disease Prediction

    Mar 20, 2025Narmina Baghirova, Duy-Thanh Vũ, Duy-Cat Can +6Clinical Outcome PredictionNeuroimaging

    Department of Informatics, University of Fribourg, Fribourg, Switzerland · Platform of Bioinformatics, Lausanne University Hospital (CHUV), Lausanne, Switzerland · Faculty of Biology and Medicine, University of Lausanne, Lausanne, Switzerland

  25. Enhancing Cognitive Workload Classification Using Integrated LSTM Layers and CNNs for fNIRS Data Analysis

    Jul 22, 2024Mehshan Ahmed Khan, Houshyar Asadi, Mohammad Reza Chalak Qazani +6Recurrent Neural NetworksConvolutional Neural Networks

    Institute for Intelligent Systems Research and Innovation, Deakin University, 75 Pigdons Rd, Waurn Ponds, VIC, 3216, Geelong, Australia