Dynamics of Information Storage and Recall in the Hippocampus
Cortical circuitry consists of a large population of excitatory neurons, typically pyramidal cells, which are contacted by smaller numbers of heterogeneous populations of inhibitory interneurons. Assuming the excitatory pyramidal cells (PCs) are the “information processors”, then the largely inhibitory microcircuit surrounding each PC forms a control system to modulate information throughput, involving PC spiking activity and synaptic plasticity. To explore this concept we have built a computational model based on the circuitry of the CA1 area of the mammalian hippocampus. With this model we demonstrate possible roles for four classes on inhibitory interneurons (IN) in controlling the storage and recall of patterns of information coded as PC spiking activity. The model is based on published experimental data showing that the PC and different IN populations show phasic activity profiles during the 5 Hz theta rhythm that is prominent in CA1 in rats that are actively exploring an environment. The phasic relationships between cell types can result in PC activity representing recalled information during one half of a theta cycle, while new information is stored by synaptic plasticity of excitatory inputs onto PCs during the opposite half cycle. Dr Bruce Graham is a Reader in Computing Science and Leader of the Cognitive Computation research group at the University of Stirling, Scotland U.K. He has been a researcher in Computational Neuroscience for 24 years, starting as a postdoc in the Centre for Information Technology Research at the Australian National University (1990-1993), followed by 7 years as a research fellow in the Centre for Cognitive Science and Institute for Adaptive and Neural Computation at the University of Edinburgh. He established his own research group at Stirling in 2000. He has an Honours degree in Mathematics (Flinders University of South Australia, 1981; University Medal), specialising in control theory. His PhD is in Chemical Engineering (University of Queensland, 1988) in which he applied fuzzy logic techniques to the control of chemical plants. He was given a Distinguished Alumni Award for contributions to Computational Neuroscience by Flinders University in 2008. He is coauthor of the book, “Principles of Computational Modelling in Neuroscience” (CUP, July 2011).