SOURCE-LINKED INTELLIGENCE
iBrain: A Unified Foundation Model Reading the Brain from Surface to Spikes
Invasive neural recordings provide high-fidelity measurements of brain activity, with signals such as intracranial EEG (iEEG) and intracortical spiking activity capturing neural dynamics at different spatial and temporal scales. Yet existing neural foundation models have largely been developed independently for different invasive recording paradigms, leaving joint pretraining across heterogeneous invasive signals underexplored. In this work, we introduce iBrain, a unified foundation model that jointly learns from iEEG and spiking activity. iBrain employs signal-specific encoders to accommodate
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-07T02:56:42.000Z
First collected: 2026-09-20T20:52:10.320Z. This is not the publication date.