electroencephalography
Electroencephalography (EEG) is a technique for recording electrical activity in the brain. In AI, EEG data can be used for brain-computer interfaces and cognitive state monitoring, where understanding neural activity patterns can inform model development.
- BrainOmni: A Brain Foundation Model for Unified EEG and MEG Signals
- CSBrain: A Cross-scale Spatiotemporal Brain Foundation Model for EEG Decoding
- EvoBrain: Dynamic Multi-Channel EEG Graph Modeling for Time-Evolving Brain Networks
- Is Limited Participant Diversity Impeding EEG-based Machine Learning?
- LUNA: Efficient and Topology-Agnostic Foundation Model for EEG Signal Analysis
- NeurIPT: Foundation Model for Neural Interfaces
- Neural-Driven Image Editing
- REFED: A Subject Real-time Dynamic Labeled EEG-fNIRS Synchronized Recorded Emotion Dataset
- S$^2$M-Former: Spiking Symmetric Mixing Branchformer for Brain Auditory Attention Detection
- Towards a General Attention Framework on Gyrovector Spaces for Matrix Manifolds