Brain Network Analysis

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7 papers in the last four weeks, against 1 the four weeks before. 0.1% of all new papers.

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A Connectome Test of the Fly Hashing Algorithm
Oct 6, 2026Sebastian SengeDimensionality Reduction Randomized Sketching
Independent Researcher
Uncertainty Quantification Is Indispensable for Reliable Connectome-Based Graph Learning: A Narrative Review and Case Study
Oct 6, 2026Mansooreh PakravanUncertainty Quantification Uncertainty Calibration
Department of Electrical and Computer Engineering, Tarbiat Modares University, Al Ahmad Street, Tehran 111-14115, Iran
CoHyFuse: Condition-wise Hypergraph Fusion with Global Connectome in Task-fMRI
Oct 5, 2026Boseong Kim, Haejun Chung, Ikbeom JangFunctional Connectivity Neuroimaging
Hanyang University, Seoul, Republic of Korea · Hankuk University of Foreign Studies, Yongin, Republic of Korea
Null-model treatment of the sensory-motor boundary changes an evolutionary connectome comparison
Sep 30, 2026Gyujeong ParkBrain Network Analysis Neuroevolution
IonLabs
BrainNet Studio: A Unified Toolkit for Brain Network Construction, Intelligent Analysis, and Visualization
Sep 29, 2026Xiwei Zeng, Shengrong Li, Yiheng Liu +3Functional Connectivity Neuroimaging
College of Artificial Intelligence, Nanjing University of Aeronautics and Astronautics, Nanjing, China · School of Computer Science and Technology, Harbin Institute of Technology, Harbin, China
Information Bottleneck-Guided Adaptive Hypergraph Transformer for Brain Disease Diagnosis
Sep 29, 2026Jingxi Feng, Xudong Chen, Yifan Zhang +5Medical Diagnosis Information Bottleneck
Deep Learning Methods in Neuroscience: From Modeling Molecular Mechanisms to Classifying States of Consciousness
Sep 28, 2026Elena Benderskaya, Anastasiia Alifanova, Svetlana Batalova +2Functional Connectivity Brain Network Analysis
Peter the Great St. Petersburg Polytechnic University, Polytechnicheskaya, 29, 195251 St.Petersburg, Russia
Beyond Site Agreement: Re-estimation for Brain Network Generalization
Sep 28, 2026Yingxu Wang, Kunyu Zhang, Yanwu Yang3 +4Functional Connectivity OOD Generalization
Mohamed bin Zayed University of Artificial Intelligence · Zhengzhou University · University Hospital Tübingen +3
FAST-Brain: A Flow-Aligned Spatio-Temporal Surrogate Brain Model
Sep 28, 2026Shucheng Liu, Changchun Shi, Kai Zhang +1Neural Surrogate Modeling Functional Connectivity
University of North Carolina at Chapel Hill · London School of Economics and Political Science
Explainable Deep Learning of Resting-State Functional Connectomes Reveals Network Biomarkers of Adolescent Intelligence
Sep 27, 2026Md. Tanvir Rahman, Nabil Anan Orka, Asaduzzaman Khan +1Explainable Artificial Intelligence Functional Connectivity
School of Health and Rehabilitation Sciences, The University of Queensland, QLD 4072, Australia · Department of Information and Communication Technology, Mawlana Bhashani Science and Technology University, Tangail 1902, Bangladesh
Benchmarking External Generalization of SPD Matrix Learning for Resting-State fMRI Connectome Prediction
Aug 31, 2026Ce Ju, Antoine Collas, Florent Bouchard +1Functional Connectivity Brain Age Prediction
Inria, CEA, Universit´e Paris-Saclay, Palaiseau, France · Universit´e Paris-Saclay, CNRS, CentraleSup´elec, L2S, France
FedDOSE: Federated Learning Framework Decomposing Site Effects for Modeling Brain Dynamic Functional Connectivity
Aug 7, 2026Deepank Girish, Yi Hao Chan, Yubin Zheng +2Functional Connectivity Medical Diagnosis
Nanyang Technological University · Shanghai Jiao Tong University · Indian Institute of Technology Ropar
When Language Models Meet NeuroGraphs: Exploring Enhanced Agentic LLM Framework Towards Brain Network Analysis
Jul 24, 2026Jiaxing Li, Rui Dong, Muyao Tang +1LLM Interpretability LLM Agents
School of Computer Science and Engineering, Southeast University
Adaptive Multi-Expert Graph Transformer for Interpretable EEG-Based Diagnostics
Jul 20, 2026Maryam Rahimimovassagh, Md Elias Hossain, Ivan Garibay +1Electroencephalography Dynamic Graph Learning
Department of Industrial Engineering and Management Systems University of Central Florida, Orlando, FL, USA
Navigating Hierarchy: Hyperbolic Learning on Brain Graphs for Disorder Diagnosis
Jul 8, 2026Yapeng Li, Bo Jiang, Ziyan Zhang +2Medical Diagnosis Hierarchical Representation Learning
School of Computer Science and Technology, Anhui University, 111 Jiulong Road, Hefei, 230601, China
CLABTOOLKIT: An Open-Source Toolkit for Routine Processing, Manipulation, and Visualization of Neuroimaging Data
Jul 2, 2026Yasser Alemán-Gómez, Nino Hervé, Patric HagmannNeuroimaging Brain Network Analysis
Connectomics Lab, Department of Radiology, Lausanne University Hospital (CHUV), Lausanne, Switzerland · University of Lausanne (UNIL), Lausanne, Switzerland
SABER: A Semantic-Aligned Brain Network Analysis Framework via Multi-scale Hypergraphs
Jul 2, 2026Yidan Xu, Xiangmin Han, Rundong Xue +1Medical Diagnosis Hypergraph Neural Networks
Hangzhou Dianzi University, China · Tsinghua University, China · Xi’an Jiaotong University, China
Progressive Self-Supervised Learning with Individualized Community Assignment for Brain Network Analysis
Jun 29, 2026Hairui Chen, Yanwu Yang, Jianfeng Cao +3Self-Supervised Learning Graph SSL
Harbin Institute of Technology at Shenzhen, Shenzhen, China · Peng Cheng Laboratory, Shenzhen, China · University of Tübingen, Tübingen, Germany +1
Connectivity Estimation using Stochastic Graph Heat Modelling
Jun 27, 2026Stephan Goerttler, Min Wu, Fei HeGraph Structure Learning Neuroimaging
Centre for Computational Science and Mathematical Modelling, Coventry University, Coventry CV1 5FB, UK · Institute for Infocomm Research, A*STAR, Singapore
Sex-based Network-Specific Differences in Connectomes: A Krakencoder-Based Analysis
Jun 15, 2026Vibhashree S H, Debanjali Bhattacharya, Vamshi Krishna Kancharla +1Functional Connectivity Neuroimaging
Centre for Brain Research, Indian Institute of Science, Bengaluru 560012, India · Dept. of Artificial Intelligence, Amrita School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Bengaluru 560035, India
Artemis: Anatomy-Resolved inTervention for Eliminating Multimodal NeuroImage confounderS
Jun 10, 2026Siyuan Dai, Yang Du, Kun Zhao +6Graph Neural Networks Multimodal Graph Learning
Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA. · Department of Computer Science, University of Maryland, College Park, MD · Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA +2
Vector Space of Cycles
Jun 6, 2026Moo K. Chung, Anass B. El-Yaagoubi, Hernando OmbaoGraph Structure Learning Brain Network Analysis
Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA · Statistics Program, King Abdullah University of Science and Technology, Thuwal, Saudi Arabia
SC-TauPath: A Structural Connectivity Attribution Framework for Mapping Tau Propagation Pathways in Alzheimer's Disease
Jun 2, 2026Jing Zhang, Norman Scheel, Minheng Chen +5Alzheimer's Disease Neuroimaging
University of Texas at Arlington, Arlington, TX, USA · Michigan State University, East Lansing, MI, USA · University of Texas Southwestern Medical Center, Dallas, TX, USA
Learning Multi-Scale Hypergraph for High-Order Brain Connectivity Analysis
Jun 2, 2026Jaeyoon Sim, Soojin Hwang, Seunghun Baek +2Neuroimaging Hypergraph Learning
Pohang University of Science and Technology (POSTECH), Pohang, South Korea · University of North Carolina at Chapel Hill, Chapel Hill, USA
BrainDyn: A Sheaf Neural ODE for Generative Brain Dynamics
May 19, 2026Siddharth Viswanath, Panayiotis Ketonis, Chen Liu +3Graph Neural Networks Sheaf Neural Networks
1Yale University · 2Boise State University · University of Wisconsin–Madison
Network-Aware Bilinear Tokenization for Brain Functional Connectivity Representation Learning
May 13, 2026Leo Milecki, Qingyu Hu, Bahram Jafrasteh +2Representation Learning Masked Autoencoders
Department of Radiology, Weill Cornell Medicine, New York, NY, USA. · School of Electrical and Computer Engineering, Cornell University and Cornell Tech, New York, NY, USA.
Supervised Deep Multimodal Matrix Factorization for Interpretable Brain Network Analysis
May 13, 2026Amjad Seyedi, Lifang He, Songlin Zhao +2Neural Network Interpretability Multimodal Graph Learning
Dept. of Mathematics & Operational Research University of Mons, Mons, Belgium · Dept. of Computer Science & Engineering Lehigh University, Bethlehem, PA, USA · Dept. of Industrial & Systems Engineering Lehigh University, Bethlehem, PA, USA
Learning beyond Site Bias for OOD Generalization in Brain Networks
May 7, 2026Yingxu Wang, Kunyu Zhang, Yanwu Yang +5Functional Connectivity Domain Generalization
Zhengzhou University · City University of Hong Kong
Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity
Apr 23, 2026Deepank Girish, Yi Hao Chan, Sukrit Gupta +2Medical Imaging Foundation Models Functional Connectivity
College of Computing and Data Science, Nanyang Technological University, Singapore
Modeling Higher-Order Brain Interactions via a Multi-View Information Bottleneck Framework for fMRI-based Psychiatric Diagnosis
Apr 20, 2026Kunyu Zhang, Qiang Li, Vince D. Calhoun +1Functional Connectivity Multi-View Learning
Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands · Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA · Department of Physics and Technology, UiT - The Arctic University of Norway, Tromsø, 9019, Norway
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 Geometry Transformer 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

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A Connectome Test of the Fly Hashing Algorithm

Sebastian Senge

Independent Researcher

Dimensionality Reduction Randomized Sketching Brain Network Analysis

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Dasgupta, Stevens and Navlakha (2017) showed that the Drosophila olfactory circuit, modelled as a random sparse projection followed by winner-take-all, is a locality-sensitive hash that beats classical LSH. The projection was random because the wiring was unknown. We test it against four electron-microscopy connectomes (MaleCNS, hemibrain, FlyWire, BANC; four animals, seven hemispheres). First, the 2017 pattern holds in a reimplementation of its protocol on SIFT, MNIST and odour mixtures (GloVe is near chance at short codes for every method): the fly hash beats k Gaussian projections at short hash lengths (3.1x in AP@200 on MNIST at k = 4). Second, against the tested real-valued Gaussian baseline that advantage is per active cell, not per operation: Gaussian projections given the same projection arithmetic retrieve better on every dataset and input dimension tested. Third, across four connectomes the measured pairing of glomeruli gives no consistent retrieval advantage over degree-preserving rewiring: retrieval is slightly lower (median -1.6%), and the small odour deficits depend on how missing odour responses are treated. Separately, equalising glomerular fan-out at fixed connection count improves retrieval in the model in every hemisphere, while equalising inputs per cell lowers it on average. Yet the fan-out profile is similar across the four sampled animals (median between-animal Spearman rho = 0.86), structural synapse counts do not offset it, and its relation to odour tuning is weak. In the model that uneven allocation costs retrieval. For practice: measured wiring gives no consistent retrieval advantage over degree-preserving random wiring, so a fly hash needs no connectome data, and its advantage is per active unit, which may suit hardware where active units rather than arithmetic are the binding cost, a hypothesis we do not test.

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