Special Session: Brain Machine Intelligence — Models, Systems, and Translational Applications

Scope and Motivation

Brain Machine Intelligence aims to unify neural sensing, cognitive computation, and interactive learning into coherent artificial intelligence systems that work with the human brain. The field integrates neural and physiological signals with perception, language, action, and memory modules, and closes the loop through adaptive feedback and stimulation. Recent progress in foundation models, self‑supervised learning, neuromorphic computing, and large‑scale multimodal datasets has created an opportunity to move beyond conventional brain–computer interfaces toward intelligent agents that understand, predict, and collaborate with human cognition.

Real‑world Brain Machine Intelligence demands methods that learn robust representations from noisy and heterogeneous signals, align neural activity with semantic and motor spaces, and support safe and efficient closed‑loop control. It further requires principled approaches to interpretability, uncertainty, personalization, continual learning, and privacy‑preserving computation. Meeting these challenges calls for collaboration across neuroscience, biomedical engineering, artificial intelligence, cognitive science, clinical research, and industry.

Objectives

• Showcase algorithmic advances in neural representation learning, alignment with perception and language models, and co‑adaptive decoding and control.
• Introduce system architectures for closed‑loop interaction that connect sensing, inference, decision making, and feedback in real‑time settings.
• Establish evaluation protocols, benchmarks, and reproducible toolkits for Brain Machine Intelligence across laboratory and clinical environments.
• Foster collaboration among researchers and practitioners from neuroscience, engineering, cognitive AI, healthcare, and industry.
• Highlight translational applications in assistive communication, neurorehabilitation, mental health, surgical guidance, and human–machine collaboration.

Topics of Interest

We welcome original research and innovative contributions that include but are not limited to the following topics:

• Foundation models for neural and behavioral data, including pretraining on large‑scale electrophysiology and neuroimaging.
• Alignment between neural activity and language, vision, and action spaces, including brain‑to‑text and brain‑to‑intent decoding.
• Closed‑loop Brain Machine Intelligence, co‑adaptive learning, and online personalization with safety and stability guarantees.
• Multimodal neural signal processing that integrates EEG, fNIRS, ECoG, fMRI, eye tracking, kinematics, and peripheral physiology.
• Interpretable and causal inference methods for neural decoding, uncertainty estimation, and trust in clinical decision support.
• Real‑time systems, efficient inference on embedded devices, and neuromorphic or event‑driven sensing and computing.
• Synthetic data generation, simulation, and digital twin modeling for data augmentation and evaluation.
• Benchmarks, datasets, and metrics for Brain Machine Intelligence in communication, mobility, affect, and cognition.
• Privacy‑preserving learning, secure data governance, and responsible deployment in healthcare and everyday environments.
• Human‑in‑the‑loop evaluation, usability, and long‑term robustness in field studies and clinical trials.

Importance and Significance

This special session will articulate a coherent agenda for Brain Machine Intelligence by connecting representation learning, interactive control, and translational practice. The discussion will identify principles that enable reliable and interpretable systems, propose shared resources for benchmarking and reproducibility, and accelerate progress toward practical solutions in assistive technology, neurorehabilitation, mental health assessment, and collaborative robotics. By bringing together diverse communities, the session will help transform neural data and intelligent algorithms into systems that advance human ability and well‑being.

Organizers