Neuronal computations underlying the firing of place cells and their role in navigation

Abstract

Our model of the spatial and temporal aspects of place cell firing and their role in rat navigation is reviewed. The model provides a candidate mechanism, at the level of individual cells, by which place cell information concerning self-localization could be used to guide navigation to previously visited reward sites. The model embodies specific predictions regarding the formation of place fields, the phase coding of place cell firing with respect to the hippocampal theta rhythm, and the formation of neuronal population vectors downstream from the place cells that code for the directions of goals during navigation. Recent experiments regarding the spatial distribution of place cell firing have confirmed our initial modeling hypothesis, that place fields are formed from Gaussian tuning curve inputs coding for the distances from environmental features, and enabled us to further specify the functional form of these inputs. Other recent experiments regarding the temporal distribution of place cell firing in two-dimensional environments have confirmed our predictions based on the temporal aspects of place cell firing on linear tracks. Directions for further experiments and refinements to the model are outlined for the future.

Conjoint Control of Hippocampal Place Cell Firing by Two Visual Stimuli

“…In the standard cylinder, there is an exact match between the current view of the environment and information stored in the autoassociator. Consequently, only those place cells whose fields contain the rat's current position discharge; the discharge rate of each cell is a function of the distance between the rat's position and the centroid of the cell's field (Zipser 1985; Sharp 1991; Wan et al 1993; Burgess and O'Keefe 1996; O'Keefe and Burgess 1996). When the rat moves to another position, the sensory input pattern changes and the distribution of activity across the output of the autoassociator (the place cells) changes in parallel.…”

Modeling hippocampal and neocortical contributions to recognition memory: A complementary-learning-systems approach.

“…The hippocampal component of the CLS model is part of a long tradition of hippocampal modeling (e.g., Marr, 1971;McNaughton & Morris, 1987;Rolls, 1989;Levy, 1989;Touretzky & Redish, 1996;Burgess & O'Keefe, 1996;Wu, Baxter, & Levy, 1996;Treves & Rolls, 1994;Moll & Miikkulainen, 1997;Hasselmo & Wyble, 1997). Although different hippocampal models may differ slightly in the functions they ascribe to particular hippocampal subcomponents, a remarkable consensus has emerged regarding how the hippocampus supports episodic memory (i.e., by assigning minimally overlapping CA3 representations to different episodes, with recurrent connectivity serving to bind together the constituent features of those episodes).…”

The CA3 network as a memory store for spatial representations

“…Place fields per se arise in networks of different architecture and plasticity, which are made to process spatial information (Zipser 1985;Burgess and O'Keefe 1996), so their mere appearance does not usefully constrain hypothetical hippocampal operations. Their relative quality, however, can give important insight into these operations, particularly as concerns exact localization within a context.…”