Estimation and assessment of non-Poisson neural encoding models

Abstract

Event Abstract Back to Event Estimation and assessment of non-Poisson neural encoding models Jonathan W. Pillow1* 1 University of Texas at Austin, United States Recent work on the statistical modeling of neural responses has focused on modulated renewal processes in which the spike rate is a function of the stimulus and recent spiking history. Typically, these models incorporate spike-history dependencies via either: (1) a conditionally-Poisson process with rate dependent on a linear projection of the spike train history (e.g., generalized linear model); or (2) a modulated non-Poisson renewal process (e.g., inhomogeneous gamma process). Here we show that the two approaches can be combined, resulting in a conditional renewal (CR) model for neural spike trains. This model captures both real-time and rescaled-time history effects, and can be fit by maximum likelihood using a simple application of the time-rescaling theorem. We show that for any modulated renewal process model, the log-likelihood is concave in the linear filter parameters only under certain restrictive conditions on the renewal density, which rules out many popular choices (e.g. gamma with shape k ≠1). This result suggests that real-time history effects are easier to incorporate than non-Poisson renewal properties. Finally, we show that goodness-of-fit tests based on the time-rescaling theorem quantify relative-time effects, but do not reliably assess accuracy in spike prediction or stimulus-response modeling. We illustrate the CR model with applications to both real and simulated neural data. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Poster Presentation Topic: Poster session II Citation: Pillow JW (2010). Estimation and assessment of non-Poisson neural encoding models. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00207 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: 03 Mar 2010; Published Online: 03 Mar 2010. * Correspondence: Jonathan W Pillow, University of Texas at Austin, Austin, United States, pillow@princeton.edu 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 Jonathan W Pillow Google Jonathan W Pillow Google Scholar Jonathan W Pillow PubMed Jonathan W Pillow 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.