Abstract
The mammalian hippocampus plays a crucial role in producing a cognitive map of space—an internalized representation of the animal’s environment. We have previously shown that it is possible to model this map formation using a topological framework, in which information about the environment is transmitted through the temporal organization of neuronal spiking activity, particularly those occasions in which the firing of different place cells overlaps. In this paper, we discuss how gamma rhythm, one of the main components of the extracellular electrical field potential affects the efficiency of place cell map formation. Using methods of algebraic topology and the maximal entropy principle, we demonstrate that gamma modulation synchronizes the spiking of dynamical cell assemblies, which enables learning a spatial map at faster timescales.
Highlights
The mammalian hippocampus plays a key role in spatial cognition
We have previously shown that it is possible to model this map formation using a topological framework, in which information about the environment is transmitted through the temporal organization of neuronal spiking activity, those occasions in which the firing of different place cells overlaps
Using methods of algebraic topology and the maximal entropy principle, we demonstrate that gamma modulation synchronizes the spiking of dynamical cell assemblies, which enables learning a spatial map at faster timescales
Summary
Hippocampal place cells manifest remarkable spatial specificity of spiking activity: they fire only in select locations in the environment, known as place fields [1]. Place cell spike trains contain information about the animal’s current location [2], as well as its future [3] and past [4] navigation routes, both in the wakeful state and even in sleep [5]. Damage to the hippocampal network impairs spatial learning and navigation planning [6, 7]. It is believed that the population of place cells encodes a cognitive map of the environment that serves as the basis of animal’s spatial awareness [8, 9]
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