Movement Related Statistics of Grid Cell Firing

Abstract

Event Abstract Back to Event Movement Related Statistics of Grid Cell Firing Carleen Kluger1, 2*, Alexander Mathis1, 3, Martin Stemmler1, 3 and Andreas V. Herz1, 3 1 Ludwig-Maximilians-Universität München, Bernstein Center for Computational Neuroscience Munich, Germany 2 Ludwig-Maximilians-Universität München, Department of Physics, Germany 3 Ludwig-Maximilians-Universität München, Division of Neurobiology, Germany The spatially modulated firing of grid cells in the entorhinal cortex (EC) [Hafting et al, 2005] has revolutionized our understanding of how the rodent brain represents space. Whether or how grid cells manage to disambiguate spatial location, velocity, and path and movement history by their spike code remains an open question, however. Here we study the correlation between the statistics of grid cell spiking and movement, based on linear track data recorded in the lab of E. I. Moser. Every passage through a firing field yields a spike train. We clustered spike trains resulting from similar runs through space, ordering them according to parameters such as mean velocity or the net deviation from a straight-line path. Using a cost-based spike train metric, we computed the relative similarity of the spike trains and found strong correlations of the spike trains with the order parameters derived from the movement statistics. Extending the spike-train metric to include information about the local field potential (LFP) in the theta band (7-12 Hz), we map the spike trains onto the cylinder of time and phase (Fig. 1) before computing distances between spike trains. This transformation reveals the role of the LFP in shaping the temporal sequence of spikes, highlighting the importance of the theta rhythm in the EC. While spikes exhibit position-dependent locking to the LFP, the spike count for a run through the grid field is generally Poisson-distributed. In contrast, place cells in hippocampus have been shown to exhibit spike counts with even higher variance. In addition, the spatial tuning of grid fields is nearly Gaussian, as evidenced by comparing kernel density estimates of firing probability with Gaussian fits. The statistical properties of grid cell firing are thus well captured by a doubly stochastic process modulated by both position and LFP; such a statistical model can then be used to estimate the coding properties of grid cells, based either on the spike count or the spike timing. Fig 1: A new metric for the parallel analysis of LFP phase and spike timing for Grid Cells recorded on the linear track Figure 1 Keywords: computational neuroscience Conference: Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010. Presentation Type: Presentation Topic: Bernstein Conference on Computational Neuroscience Citation: Kluger C, Mathis A, Stemmler M and Herz AV (2010). Movement Related Statistics of Grid Cell Firing. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience. doi: 10.3389/conf.fncom.2010.51.00134 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 24 Sep 2010; Published Online: 24 Sep 2010. * Correspondence: Ms. Carleen Kluger, Ludwig-Maximilians-Universität München, Bernstein Center for Computational Neuroscience Munich, Martinsried, Germany, carleen.kluger@physik.uni-muenchen.de Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Carleen Kluger Alexander Mathis Martin Stemmler Andreas V Herz Google Carleen Kluger Alexander Mathis Martin Stemmler Andreas V Herz Google Scholar Carleen Kluger Alexander Mathis Martin Stemmler Andreas V Herz PubMed Carleen Kluger Alexander Mathis Martin Stemmler Andreas V Herz Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.