Dissecting Inhibitory Control of Striatal Projection Neurons

Abstract

Event Abstract Back to Event Dissecting Inhibitory Control of Striatal Projection Neurons Damodaran Sriraman1* and Kim Blackwell1 1 George Mason University, United States The striatum is the main input nucleus of the basal ganglia and is involved in processing inputs from the cortex and thalamus. This processing is carried out by GABAergic medium spiny projection neurons (MSPN) that comprise 90-95% of the neuronal population in the rodent striatum (Bolam and Bennett, 1993). These neurons project to the basal ganglia output structures, the globus pallidus and substantia nigra; therefore understanding striatal processing will help elucidate further the factors affecting basal ganglia function. GABAergic inhibition plays a very important role in the modulation of the MSPN network (Tepper et al., 2008). Among the different GABAergic interneurons in the striatum, the fast-spiking interneurons (FSIs) provide strong feedforward inhibition of the MSPNs (Koos & Tepper, 1999; Tepper et al., 2008), whereas MSPNs provide widespsread but weak feedback inhibition of each other. The FSIs are interconnected through electrical synapses/gap junctions (Galarreta and Hestrin, 2001) and GABAergic synapses (Gittis et al., 2010). It has been hypothesized that gap junctions are involved in coordinating synchronous activity in populations of the MSPN network (Berke et al., 2004, Galarreta and Hestrin, 2002). However, recent experiments (Berke, 2008) suggest that FSIs do not fire synchronously, and recent simulations (Hjorth et al., 2009) have shown that gap junctions alone are not sufficient to synchronize FSI network activity in the striatum, except transiently in response to synchronous cortical activity. The function of the widespread but weak feedback loop of the MSPNs is also not clear (Plenz, 2002). The present study constructs a network of the realistic multi-compartmental model MSPNs receiving both realistic synaptic input from a model FSI network and simulated input trains from the cortex. The FSI network, which also receives cortical input trains, is connected by both gap junctions (Hjorth et al., 2009) and chemical synapses (Gittis et al., 2010). The simulations address the role of chemical synapses and gap junctions in the FSI network in controlling activity in the MSPN network of the striatum. The simulations also parse out the contributions of the feedforward and feedback connections on the MSN output thus addressing the functional contribution of each type of connection to the network activity. Keywords: computational neuroscience Conference: 4th INCF Congress of Neuroinformatics, Boston, United States, 4 Sep - 6 Sep, 2011. Presentation Type: Poster Presentation Topic: Computational neuroscience Citation: Sriraman D and Blackwell K (2011). Dissecting Inhibitory Control of Striatal Projection Neurons. Front. Neuroinform. Conference Abstract: 4th INCF Congress of Neuroinformatics. doi: 10.3389/conf.fninf.2011.08.00031 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: 17 Oct 2011; Published Online: 19 Oct 2011. * Correspondence: Dr. Damodaran Sriraman, George Mason University, Fairfax, United States, dsriraman@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 Damodaran Sriraman Kim Blackwell Google Damodaran Sriraman Kim Blackwell Google Scholar Damodaran Sriraman Kim Blackwell PubMed Damodaran Sriraman Kim Blackwell 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.