About hc-19

Summary

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.

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.

Referenced papers are:

Real-time classification of experience-related ensemble spiking patterns for closed-loop applications. Davide Ciliberti, Frédéric Michon and Fabian Kloosterman eLife 2018 (in press)

Falcon: a highly flexible open-source software for closed-loop neuroscience. Davide Ciliberti and Fabian Kloosterman. J. Neural Eng. 2017 14(4):045004. doi: 10.1088/1741-2552/aa7526

Bayesian decoding using unsorted spikes in the rat hippocampus Fabian Kloosterman, Stuart P. Layton, Zhe Chen and Matthew Wilson. J. Neurophysiol. 2014 111(1):217-27. doi: 10.1152/jn.01046.2012

Format of the data