Copertina

Large Connectome Model: An fMRI Foundation Model of Brain Connectomes Empowered by Brain-Environment Interaction in Multitask Learning Landscape

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Wei, Ziquan, Dan, Tingting, Wu, Guorong
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

NeuroPath: A Neural Pathway Transformer for Joining the Dots of Human Connectomes
di: Wei, Ziquan, et al.
Pubblicazione: (2024)

Message Detouring: A Simple Yet Effective Cycle Representation for Expressive Graph Learning
di: Wei, Ziquan, et al.
Pubblicazione: (2024)

Brain-OF: An Omnifunctional Foundation Model for fMRI, EEG and MEG
di: Guo, Hanning, et al.
Pubblicazione: (2026)

NeuroGraph: Benchmarks for Graph Machine Learning in Brain Connectomics
di: Said, Anwar, et al.
Pubblicazione: (2023)

Brain Effective Connectome based on fMRI and DTI Data: Bayesian Causal Learning and Assessment
di: Bagheri, Abdolmahdi, et al.
Pubblicazione: (2023)

GeoDynamics: A Geometric State-Space Neural Network for Understanding Brain Dynamics on Riemannian Manifolds
di: Dan, Tingting, et al.
Pubblicazione: (2026)

Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help
di: Han, Keqi, et al.
Pubblicazione: (2025)

fMRI2GES: Co-speech Gesture Reconstruction from fMRI Signal with Dual Brain Decoding Alignment
di: Zhu, Chunzheng, et al.
Pubblicazione: (2025)

Explore Brain-Inspired Machine Intelligence for Connecting Dots on Graphs Through Holographic Blueprint of Oscillatory Synchronization
di: Dan, Tingting, et al.
Pubblicazione: (2026)

VIBE: Video-Input Brain Encoder for fMRI Response Modeling
di: Schad, Daniel Carlström, et al.
Pubblicazione: (2025)

BrainCSD: A Hierarchical Consistency-Driven MoE Foundation Model for Unified Connectome Synthesis and Multitask Brain Trait Prediction
di: Shen, Xiongri, et al.
Pubblicazione: (2025)

ConnectomeBench: Can LLMs Proofread the Connectome?
di: Brown, Jeff, et al.
Pubblicazione: (2025)

Model Connectomes: A Generational Approach to Data-Efficient Language Models
di: Kotar, Klemen, et al.
Pubblicazione: (2025)

BrainCast: A Spatio-Temporal Forecasting Model for Whole-Brain fMRI Time Series Prediction
di: Gao, Yunlong, et al.
Pubblicazione: (2026)

Spectral Graph Neural Networks for Cognitive Task Classification in fMRI Connectomes
di: Maji, Debasis, et al.
Pubblicazione: (2025)

Marrying Generative Model of Healthcare Events with Digital Twin of Social Determinants of Health for Disease Reasoning
di: Wei, Ziquan, et al.
Pubblicazione: (2026)

BrainDINO: A Brain MRI Foundation Model for Generalizable Clinical Representation Learning
di: Wu, Yizhou, et al.
Pubblicazione: (2026)

Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis
di: Wei, Yuxiang, et al.
Pubblicazione: (2024)

EmoMind: Decoding Affective Captions from Human Brain fMRI
di: Mohammed, Bilal A., et al.
Pubblicazione: (2026)

MindFormer: Semantic Alignment of Multi-Subject fMRI for Brain Decoding
di: Han, Inhwa, et al.
Pubblicazione: (2024)

Prompt Your Brain: Scaffold Prompt Tuning for Efficient Adaptation of fMRI Pre-trained Model
di: Dong, Zijian, et al.
Pubblicazione: (2024)

SDE-Driven Spatio-Temporal Hypergraph Neural Networks for Irregular Longitudinal fMRI Connectome Modeling in Alzheimer's Disease
di: Chen, Ruiying, et al.
Pubblicazione: (2026)

From Cortical Synchronous Rhythm to Brain Inspired Learning Mechanism: An Oscillatory Spiking Neural Network with Time-Delayed Coordination
di: Dan, Tingting, et al.
Pubblicazione: (2026)

Personalized Federated Dictionary Learning for Modeling Heterogeneity in Multi-site fMRI Data
di: Zhang, Yipu, et al.
Pubblicazione: (2025)

Region-Aware Reconstruction Strategy for Pre-training fMRI Foundation Model
di: Doodipala, Ruthwik Reddy, et al.
Pubblicazione: (2025)

Brain Networks and Intelligence: A Graph Neural Network Based Approach to Resting State fMRI Data
di: Thapaliya, Bishal, et al.
Pubblicazione: (2023)

Ada-FCN: Adaptive Frequency-Coupled Network for fMRI-Based Brain Disorder Classification
di: Xun, Yue, et al.
Pubblicazione: (2025)

MLC-GCN: Multi-Level Generated Connectome Based GCN for AD Analysis
di: Zhu, Wenqi, et al.
Pubblicazione: (2024)

Characterizing Continuous and Discrete Hybrid Latent Spaces for Structural Connectomes
di: Rudravaram, Gaurav, et al.
Pubblicazione: (2025)

Diffusion-Guided Pretraining for Brain Graph Foundation Models
di: Wei, Xinxu, et al.
Pubblicazione: (2026)

On the Limits of Applying Graph Transformers for Brain Connectome Classification
di: Lara-Rangel, Jose, et al.
Pubblicazione: (2025)

Nonlocal operator learning for fMRI encoding and decoding tasks
di: Kramer, Andreas, et al.
Pubblicazione: (2026)

Explainable AI for Autism Diagnosis: Identifying Critical Brain Regions Using fMRI Data
di: Vidya, Suryansh, et al.
Pubblicazione: (2024)

Foundation-Model-Boosted Multimodal Learning for fMRI-based Neuropathic Pain Drug Response Prediction
di: Fan, Wenrui, et al.
Pubblicazione: (2025)

MoRE-Brain: Routed Mixture of Experts for Interpretable and Generalizable Cross-Subject fMRI Visual Decoding
di: Wei, Yuxiang, et al.
Pubblicazione: (2025)

A Dual-Attention Graph Network for fMRI Data Classification
di: Arbab, Amirali, et al.
Pubblicazione: (2025)

SpikingBrain: Spiking Brain-inspired Large Models
di: Pan, Yuqi, et al.
Pubblicazione: (2025)

Discovering Dynamic Effective Connectome of Brain with Bayesian Dynamic DAG Learning
di: Bagheri, Abdolmahdi, et al.
Pubblicazione: (2023)

A Confounding Factors-Inhibition Adversarial Learning Framework for Multi-site fMRI Mental Disorder Identification
di: Wen, Xin, et al.
Pubblicazione: (2025)

Inverting Foundation Models of Brain Function with Simulation-Based Inference
di: Bracher, Niels, et al.
Pubblicazione: (2026)