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. 2018 Jun 5;7:e34467. doi: 10.7554/eLife.34467

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© 2018, Maboudi et al

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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Figure 7. — Examples of remote replay events identified with HMM-congruence. We trained and evaluated HMMs on the events that were not Bayesian significant (residual events) to identify potential extra-spatial structure. (a) The normalized session quality drops as local-replay events above the Bayesian significance threshold are removed from the data. Each trace corresponds to one of the 18 linear track sessions, with the stroke width and the stroke intensity proportional to the baseline (all-events) session quality. The blue line identifies a session in which model quality drops more slowly, indicating the potential presence of extra-spatial information. The reduction in session quality for a W maze experiment with known extra-spatial information is even slower (green). When, instead, Bayesian-significant remote events are removed, rapid reduction in session quality is again revealed (red). (b) The lsPF-based median decoding errors are shown as a function of baseline session quality for all 18 linear track sessions. The blue dot indicates the outlier session from panel (a) with potential extra-spatial information: this session shows high decoding error combined with high session quality. Session quality of the W maze session is also indicated on the x-axis (decoding error is not directly comparable). (c–n) Two example HMM-congruent but not Bayesian-significant events from the W maze session are depicted to highlight the fact that congruence can correspond to remote replay. (c) Spikes during ripple with local place cells highlighted (top panel) and the corresponding latent state probabilities (bottom panel) decoded using the HMM show sequential structure (grayscale intensity corresponds to probability). (d) In this event, the Bayesian score relative to the shuffle distribution (top panel) indicates that the event is not-significant, whereas the HMM score relative to shuffles indicates (bottom panel) the ripple event is HMM-congruent. (e) Estimates of position using local place fields show jumpy, multi-modal a posteriori distributions over space in 1D (top left panel) and 2D (top right panel; distribution modes and time is denoted in color). Bayesian decoding using the remote environment place fields (bottom panel) indicates that the sample event is a remote replay. Note that in a typical experiment, only the local place fields would be available. (f–h) Same as (c–e), but for a different ripple event.