Integrating local and prospective features improved decoding performance, reaching 74.4% accuracy for future choice prediction in Test trials and 78.2% for upcoming trajectory decoding in Sample trials; the authors say incorporating spatiotemporal hippocampal features improves behavioral decoding and provides a framework for hippocampus-based BCIs to predict future decisions. PMID 42546762, DOI 10.1088/1741-2552/ae93f5
Integrated Decoding of Local and Prospective Spatial Representations for Future Decision Prediction
Summary
The study recorded hippocampal CA1 population activity in rats performing a sequential spatial decision task in a modified T-maze, dividing the decision into initiation, running and approach phases. Local theta sequences consistently over-represented the actual choice, while prospective representations driven by choice-arm place cells shifted from predicting the actual choice during running to representing potential paths more evenly at the choice point. Integrating local and prospective features improved decoding, reaching 74.4% accuracy for future choice prediction and 78.2% for upcoming trajectory decoding.
Why it matters
Decoding what an animal will choose — not just what it is doing — from hippocampal ensembles is the basis for cognitive BCIs that anticipate decisions rather than merely track them.
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pubmed.ncbi.nlm.nih.gov 2026-08-04