Title: Decomposition of neuronal assembly activity via empirical de-Poissonization
Abstract: Event Abstract Back to Event Decomposition of neuronal assembly activity via empirical de-Poissonization Benjamin Ehm1*, Benjamin Staude2 and Stefan Rotter2 1 Institute for Frontier Areas of Psychology and Mental Health, Germany 2 BCCN Freiburg, Germany The cell assembly hypothesis [1] postulates dynamically interacting groups of neurons as building blocks of cortical information processing. Synchronized spiking across large neuronal groups was later suggested as a potential signature for active assemblies [2], and recent advances in multi-electrode recording and optical imaging techniques provide promising data sets to rigorously test the assembly hypothesis [3]. However, currently available analysis techniques aimed to detect synchronously spiking groups in massively parallel spike train recordings face severe limitations. On the one hand, estimated pairwise interactions [4] alone do not allow to infer on large synchronized neuronal pools, and are insensitive for sparse synchronous events [5]. Approaches that transcend pairwise interactions by estimating higher-order correlations, on the other hand, require vast sample sizes, as the parameter space grows exponentially with the number of recorded neurons [6]. Here, we present a novel analysis technique for massively parallel spike train data that transcends the estimation of pairwise interactions, yet avoids the need for extensive sample sizes. Instead of estimating interactions among individual neuron-pairs, triplets, quadruplets, etc., we base our inference on the population spike counts, i.e. the spike counts extracted from the superimposed spiking activity of all recorded neurons. This leads to a parsimoniously parametrized univariate estimation problem, circumventing the curse of dimensionality and greatly reducing the demands with respect to the size of empirical samples. Specifically, we assume correlated Poisson processes as a simple descriptive parametrization of higher-order effects, where interaction in a group of neurons is modeled by inserting precisely synchronized spikes into the corresponding spike trains [7]. Our inference procedure is based on the observation that the characteristic function of the population spike counts of correlated Poisson processes is essentially a Fourier series whose coefficients are the interaction parameters of the model. Corresponding estimates are thus defined via Fourier-inversion of the empirical characteristic function. Expressions for their asymptotic (co)-variances are then used to construct combined hypothesis tests, e.g., whether or not a data sets exhibits interactions above a certain order. The method is illustrated by extensive Monte-Carlo simulations, showing its surprising sensitivity for higher-order interactions present in the data, even in situations where average pairwise correlation coefficients c are very small (in the range of c .01, compare cf. [6]). Acknowledgments: Supported by the German Federal Ministry of Education and Research (BMBF grant 01GQ0420), and DFG SFB 780 References 1. Hebb. Organization of behavior. Wiley (1949)2. Abeles. Local cortical circuits. Springer (1982); Riehle et al. Science 278:1950-1953 (1997)3. Brown et al. Nat Neurosci 7:456-461 (2004)4. Perkel et al. Biophys. J. 7:419-440 (1967)5. Schneidman et al. Nature 440:1007-1012 (2006)6. Martignon et al. Biol Cyber 73:69-81 (1995); Nakahara & Amari. Neural Comput 14:2296-2316 (2002)7. Kuhn et al. Neural Comput 1:67-101 (2003) Conference: Bernstein Symposium 2008, Munich, Germany, 8 Oct - 10 Oct, 2008. Presentation Type: Poster Presentation Topic: All Abstracts Citation: Ehm B, Staude B and Rotter S (2008). Decomposition of neuronal assembly activity via empirical de-Poissonization. Front. Comput. Neurosci. Conference Abstract: Bernstein Symposium 2008. doi: 10.3389/conf.neuro.10.2008.01.042 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: 13 Nov 2008; Published Online: 13 Nov 2008. * Correspondence: Benjamin Ehm, Institute for Frontier Areas of Psychology and Mental Health, Freiburg, Germany, [email protected] 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 Benjamin Ehm Benjamin Staude Stefan Rotter Google Benjamin Ehm Benjamin Staude Stefan Rotter Google Scholar Benjamin Ehm Benjamin Staude Stefan Rotter PubMed Benjamin Ehm Benjamin Staude Stefan Rotter 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.