Separating spiking input correlation structures: an inhibitory STDP approach

Abstract

Event Abstract Back to Event Separating spiking input correlation structures: an inhibitory STDP approach Florence Kleberg1*, Matthieu Gilson1 and Tomoki Fukai1 1 RIKEN Brain Science Institute, Japan Correlations of activities in networks of neurons are believed to take part in representations of sensory or cognitive processes [1]. Detecting correlation patterns in the input is therefore of functional importance in neural computations. Synaptic plasticity enables neurons to “learn” structure in input signals and/or to become selective to specific input pathways. In neural network models, Spike-Timing Dependent Plasticity (STDP) can capture correlations at a short temporal scale [2]. Though this issue has been addressed in networks of excitatory neurons, it is not well known whether STDP can support detection of correlation that is shared between excitatory and inhibitory inputs. Recent investigations have just begun to address the issue [3-4]. In particular, a recent investigation indicated that combined excitatory and inhibitory (Hebbian) STDP can lead to globally balanced inputs, while correlation structure in excitatory inputs remains detectable [4]. Moreover, the study revealed that the presence of inhibition increases competition between subgroups of correlated excitatory inputs. With numerical and analytical methods, we extend on their findings by addressing the interplay between the postsynaptic response to correlated input structure and different STDP learning curves for inhibitory synapses. Using a single neuron model (Fig. 1), we examine conditions with differently correlated subgroups under which nontrivial structure in excitatory and inhibitory synapses is developed. For instance, cases where subgroups in excitatory and inhibitory inputs share correlation (Fig. 1 A) or are independently correlated (Fig. 1 B) are addressed. A preliminary result is shown (Fig. 2). We can quantify the structure development in the synaptic weights by the ratio between correlated and uncorrelated weights. If the ratio is >1, structure in synaptic weights is developed. The top left figure shows that for shared correlation between excitatory and inhibitory inputs, structure is developed for both excitatory and inhibitory synapses, if correlation is weak (c = 0.1). However, if correlation is increased, or if correlation is independent between excitatory and inhibitory inputs, no structure is developed for inhibitory synapses. We ask how excitatory and inhibitory STDP can cooperatively isolate multiple correlation sources to elucidate the importance of inhibitory plasticity in detecting correlation patterns in neural activities. Figure 1 Figure 2 References [1] Riehle A, Grün S, Diesmann M, Aertsen A (1997). Science 278(5345): 1950–1953 [2] Gilson M, Fukai T (2011). PLoS ONE 6(10): e25339 [3] Vogels TP, Sprekeler H, Zenke F, Clopath C, Gerstner W (2011) Science 334(6062): 1569-73 [4] Luz Y, Shamir M (2012) PLoS Comput. Biol. 8(1): e1002334 Keywords: Correlation, inhibitory, single neuron, STDP Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012. Presentation Type: Poster Topic: Learning, plasticity, memory Citation: Kleberg F, Gilson M and Fukai T (2012). Separating spiking input correlation structures: an inhibitory STDP approach. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00086 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: 11 May 2012; Published Online: 12 Sep 2012. * Correspondence: Dr. Florence Kleberg, RIKEN Brain Science Institute, Wakoshi, Saitama, Japan, klebergfi@gmail.com 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 Florence Kleberg Matthieu Gilson Tomoki Fukai Google Florence Kleberg Matthieu Gilson Tomoki Fukai Google Scholar Florence Kleberg Matthieu Gilson Tomoki Fukai PubMed Florence Kleberg Matthieu Gilson Tomoki Fukai 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.