Control of persistent spiking activity by background correlations.

Abstract

Event Abstract Back to Event Control of persistent spiking activity by background correlations. Mario Dipoppa1* and Boris Gutkin1 1 DEC, ENS, Group for Neural Theory, France A telltale feature of working memory (WM) is the sustained neural activity associated with holding necessary information on-line (e.g., Romo et al. 1999 Nature: 399, 470-473). A key unresolved question is how the cortical machinery manipulates this sustained activity in order to perform WM tasks. Specifically, a unified spike-based process that can "gate-in" the information at the task initiation, control the activity dynamics during the memory period and "gate-out" the memory trace at task completion remains to be specified. Here we show that it is possible to control multiple aspects of the persistent activity at once via variable correlations in the background noise and suggest that this control depends on transient synchronization of the spiking. As a paradigmatic model of sustained activity we consider a network of QIF neurons coupled with all-to-all recurrent synaptic excitation and background noise in which we can modify the global amount of correlations among neurons. In accordance with previous studies, above a critical synaptic strength and time-scale the network exhibits multi-stable behavior with sustained activity states and quiescence. We find that in the absence of noise, the sustained activity state with the lowest rate shows a specific spike-time structure referred to as "splay-state". This spike-time structure is characterized by maximum anti-synchrony among the active neurons (the spikes of N-1 neurons constituent in a network sized N are equally splayed out within an interspike interval of the Nth neuron). We show this splay-state spike arrangement to be robust to variations in PSP shape. We develop analytic conditions for the stability of the splay-state using event-driven spike-time maps. Furthermore the network responses and the robustness of the sustained splay-state are examined under noisy conditions. For a given noise strength, we find that noise correlations robustly promote transitions from the splay-state to the quiescent state while suppressing spurious reactivation of the sustained activity. We find that these transitions are due to noise induced increases in spike-time coherence among the active neurons. This effect of noise-induced synchronization becomes dominant as the network size grows. We thus find a stochastic analogue of synchrony-induced turn-off of sustained activity as proposed by Gutkin et al., (2001 J Comp Neurosci: 11, 121-134). We further find that for strongly correlated noise no splay-state activation is possible. Hence by tuning correlations in the background memory-unrelated activity we can control 1. the ability of an incoming stimulus to initiate sustained activity, 2. spurious activations of sustained activity, 3. the mean life-time of the persistent state, 4. the ability of excitatory transients to read-out and turn-off the activity rapidly. This mechanism could be used to conceive a new model of working memory where the basin of attraction of the persistent state is controlled by a correlation parameter. In conclusion, correlated stochastic input can gate persistent activity during a working memory task and slow variations of the background correlations may embed task-timing information directly into the working-memory trace. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Poster Presentation Topic: Poster session III Citation: Dipoppa M and Gutkin B (2010). Control of persistent spiking activity by background correlations.. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00158 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: 02 Mar 2010; Published Online: 02 Mar 2010. * Correspondence: Mario Dipoppa, DEC, ENS, Group for Neural Theory, Paris, France, mario.dipoppa@ens.fr 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 Mario Dipoppa Boris Gutkin Google Mario Dipoppa Boris Gutkin Google Scholar Mario Dipoppa Boris Gutkin PubMed Mario Dipoppa Boris Gutkin 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.