AI RESEARCH
Implicit Behavioral Decoding from Next-Step Spike Forecasts at Population Scale
arXiv CS.LG
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ArXi:2605.12999v1 Announce Type: cross Closed-loop brain-computer interfaces often require both a forecast of upcoming neural population activity and a readout of the animal's behavioral state. A single Mamba forecaster, trained only on next-step spike counts at Neuropixels scale, can deliver both in one forward pass. A lightweight per-session linear head reading the model's predicted rates decodes behavior better than the same linear classifier reading the raw spike counts, under matched temporal context.