Likelihood-based identification of hippocampal replay from spike sequences

• Researchers introduce a likelihood-based method to identify neural replay directly from spike sequences.¹
• The framework is designed to detect hippocampal replay events in spike-train data.¹
• Replay identification is cast as a likelihood inference problem over sequential spike activity.¹
• The paper appears in Nature Communications (DOI s41467-026-74822-2) and is methods-focused.¹
• The approach is intended to support offline calibration of neural decoders using replay-linked spike structure and state identification in spike/iEEG BCIs.^{1 1}

Footnotes

1. https://www.nature.com/articles/s41467-026-74822-2 ↩ ↩² ↩³ ↩⁴ ↩⁵ ↩⁶