NeurIPS 2025 Past Large language modelsNeuroscience
NeurIPS 2025 Workshop on Foundation Models for the Brain and Body
NeurIPS 2025 Workshop BrainBodyFM
- Submission deadline
- Aug 30, 2025, 12:00 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (57)
Fetched from OpenReview (v2) on 2026-06-10.
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‘EEGReXferNet’ – A Lightweight Gen-AI Framework for EEG Subspace Reconstruction via Cross-Subject Transfer Learning and Channel-Aware Embedding.
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∆ DELTA: Language Diffusion-based EEG-to-Text Architecture
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A foundation model with multi-variate parallel attention to generate neuronal activity
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A scalable self-supervised method for modeling human intracranial recordings during natural behavior
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A Sensing Whole Brain Zebrafish Foundation Model for Neuron Dynamics and Behavior
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A VQ-VAE framework for modeling physiological information in fMRI
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Adapting Neural Audio Codecs to EEG
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Advancing Brainwave Modelling with a Codebook-Based Foundation Model
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Are foundation models useful feature extractors for electroencephalography analysis?
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Brain2Model Learning: Training sensory and decision models with human neural activity as a teacher
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CONFORM: A Project to Create Crowd-Sourced Open Neuroscience fMRI Foundation Models
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CPEP: Contrastive Pose-EMG Pre-training Enhances Gesture Generalization on EMG signals
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Decoder-as-Policy: Head-Only PPO Fine-Tuning of a Spike-Transformer for Low-Error Kinematic Decoding
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Decoding Predictive Inference in Visual Language Processing via Spatiotemporal Neural Coherence
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EEG Foundation Models: A Critical Review of Current Progress and Future Directions
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EEG-Bench: A Benchmark for EEG Foundation Models in Clinical Applications
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Efficient Calibration in Motor Imagery BCIs Under Data Constraints via Subject Transfer
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ENIGMA: A Unified Lightweight EEG-to-Image Model for Multi-Subject Visual Decoding
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Evaluating Foundation Models for the Brain: A Dynamical Systems Perspective
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Exploring RAG-driven Multimodal LLMs for Explainable ECG Interpretation
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FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification
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GAN-Guided Diffusion Models for Generating Clinically Meaningful Multimodal Neuroimaging Data
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Handwriting decoding as a challenging Motor Imagery task for EEG Foundation Models
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HuiduRep: A Self-Supervised Learning Framework for More Robust Neural Representations from Extracellular Recordings
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Human Sensory-Musculoskeletal Modeling and Control of Whole-Body Movements
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Imitation learning of dexterous hand control uncovers muscle-level representations in primate sensorimotor cortex
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Interpretable-MTLNet: A Kolmogorov–Arnold Network for Multitask Mental Health Prediction
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Latent Graph Learning in Generative Models of Neural Signals
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Learning Structured Sleep Transitions with Sequential EEG Foundation Models
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Learning the relative composition of EEG signals using pairwise relative shift pretraining
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Learning Time-Scale Invariant Population-Level Neural Representations
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Leveraging Foundational Models and Simple Fusion for Multi-modal Physiological Signal Analysis
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MIRAGE: Robust multi-modal architectures translate fMRI-to-image models from vision to mental imagery
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Mitigating Subject Dependency in EEG Decoding with Subject-Specific Low-Rank Adapters
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Mouse-Guided Gaze: Semi-Supervised Learning of Intention-Aware Representations for Reading Detection
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Multi-modal, multi-species, and multi-task latent-space model for decoding level of consciousness
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MultiDiffNet: A Multi-Objective Diffusion Framework for Generalizable Brain Decoding
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NeuroMamba: A State-Space Foundation Model for Functional MRI
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Not All Sessions Are Equal: Data Selection for Multi-Session Pretraining in Neural Data Transformers
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Optimizing fMRI Data Acquisition for Decoding Natural Speech with Limited Participants
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PhysioJEPA: Joint Embedding Representations of Physiological Signals for Real Time Risk Estimation in the Intensive Care Unit
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Predictive Modeling of Brain-Body Association
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PrimateFace: A Resource for Generalizable Cross-Species Facial Analysis
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Processing fMRI Brain Signals Using Latents from Natural Image Autoencoders
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Region-Aware Reconstruction Strategy for Pre-training fMRI Foundation Model
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Representation-First Emotion Decoding from 7T fMRI
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Resource-Efficient ECG Foundation Networks via Layer-wise Adaptive Compression
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Scalable Diffusion Transformer for Conditional 4D fMRI Synthesis
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Scaling Vision Transformers for Functional MRI with Flat Maps
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Simple Temporal Attention Beats Complex Decoders for Neural-to-Visual Mapping from Primate Spiking Data
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The Neural Pile: 476 billion tokens of broad-coverage spiking neural activity data
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The One Where They Brain-Tune for Social Cognition: Multi-Modal Brain-Tuning on Friends
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Towards a generalizable, unified framework for multimodal neural decoding
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Towards Clinically Faithful ECG Reports via Quantization-Based Tokenization
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Towards foundation models of naturalistic collective social‑neural dynamics
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Towards Interpretable Visual Decoding with Attention to Brain Representations
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Unified Pretraining on Mixed Optophysiology and Electrophysiology Data Across Brain Regions