Extracellular recordings from rat hippocampal area CA1 during rest and exploration of a 3-arm maze along with results of real-time and offline detection of hippocampal replay content.

This data set was used in Ciliberti et al. (2018) to demonstrate and characterize the real-time detection of hippocampal memory replay events. The data set contains three daily sessions with tetrode recordings from hippocampal area CA1 in a single rat. In each session, the rat twice explored a 3-arm maze (RUN1 and RUN2), both before and after a short rest period (REST). Included in the data set are the raw data, the results of live detection of hippocampal replay events, and the results of offline analysis. Referenced paper is:
Real-time classification of experience-related ensemble spiking patterns for closed-loop applications.
Davide Ciliberti, Frédéric Michon and Fabian Kloosterman
eLife 2018 (in press)

No spike sorting was performed on the data, as we used a no-sort neural decoding approach (Kloosterman et al. 2014)
for decoding the rat’s location on the maze and for analyzing hippocampal replay events. All analyses were performed
in Python and code is available at: https://bitbucket.org/kloostermannerflab/ciliberti_elife2018_realtimereplay/.
The software for real-time replay identification is part of the Falcon real-time neural processing
framework (Ciliberti & Kloosterman, 2017) and can be found here: https://bitbucket.org/kloostermannerflab/falcon-server.