Event Abstract Back to Event A spike timing computational model of hippocampal-frontal dynamics underlying navigation and memory Laurence Jayet1*, Philip H. Goodman2 and Mathias Quoy3 1 University of Nevada Reno , Brain Computation Lab, United States 2 University of Nevada Reno , United States 3 University of Cergy, France Understanding and intervening in central nervous system disorders such as dementia, epilepsy, and stroke requires a deeper understanding of mechanisms between hippocampal and neocortical regions that produce meaningful action. A basic behavior shared by all mammals is the task of navigating in a novel environment, which requires reliable short-term episodic memory. The most well-established electrophysiological findings in the hippocampal-neocortical system are the phenomenon of place fields and hippocampal "place cells", modulated by 6-10 Hz "theta" inhibition, first described by O’Keefe and Dostrovsky in 1971 (Brain Res 1971; 34:171). More recently, Hafting et. al reported entorhinal "grid cells" (Nature 2005; 436:801), which further studies showed are likely responsible for stabilizing place fields (Eur J Neurosc 2008; 27:1933). In 2009, Harvey et al. (Nature 2009; 461:941) reported the first in vivo patch recordings of hippocampal CA1 cells in an awake behaving mouse navigating a virtual maze. Despite this series of discoveries, we are aware only of high level spatial-temporal theories that attempt to explain the role of grid cells (Moser et al. Annu Rev Neurosci 2008; 31:69). Here, we present what we believe is he first comprehensive spike-timing, conduction-based synaptic model of the hippocampal formation (HF)-neocortical system that includes a role of grid cells in stabilizing rather than establishing place cell activity. Our model attempts to explain the mechanisms of both place field formation and stabilization during a computer-simulated rodent maze navigation, exhibiting subthreshold dynamics consistent with the recent in vivo recordings by Harvey et al. This model utilizes recent theoretical microcircuitry dynamics being developed at UNR, called "Recurrent Asynchronous Irregular Nonlinear" (RAIN) networks, that are self-sustaining once activated, and silenced under certain perturbations. This RAIN-HF model has been implemented in segments, that to date successfully reproduce (1) spontaneously activating and de-activating RAIN networks corresponding to place cell activity, (2) interacting RAIN networks that incorporates Kahp channels resulting in intracellular and field potential theta inhibitory oscillation with biological irregularity. This model also includes (3) a feedback loop between the hippocampus (place cells) and the entorhinal cortex (grid cells) to stabilize place field formation, and (4) bidirectional monosynaptic connections from prefrontal cortex to represent a role for executive functions and planning. The RAIN-HF model is framed so that predictions can be biologically represented and tested experimentally in vitro and in vivo. Further implications for physiology and pathophysiology of memory are addressed. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Poster Presentation Topic: Poster session I Citation: Jayet L, Goodman PH and Quoy M (2010). A spike timing computational model of hippocampal-frontal dynamics underlying navigation and memory. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00074 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: 19 Feb 2010; Published Online: 19 Feb 2010. * Correspondence: Laurence Jayet, University of Nevada Reno, Brain Computation Lab, Reno, United States, ljayet@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 Laurence Jayet Philip H Goodman Mathias Quoy Google Laurence Jayet Philip H Goodman Mathias Quoy Google Scholar Laurence Jayet Philip H Goodman Mathias Quoy PubMed Laurence Jayet Philip H Goodman Mathias Quoy 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.