Place Cell’s Computational Model

Abstract

Hippocampal Place Cells play a pivotal role in spatial navigation. These cells have the particular characteristic of firing at a low rate during navigation throughout most of the environment, except when the animal is within a restricted spatial region called place field. The biophysical mechanisms underlying their formation or remapping following external sensory inputs are poorly understood. Recent experimental evidence clearly showed that, in the CA1 hippocampal region, the interaction between a properly timed association of inputs from the entorhinal cortex and the CA3 region can induce a novel place field formation. On CA1 pyramidal neurons, these different inputs are spatially segregated: the input from entorhinal cortex targets the most distal apical dendritic regions, while the CA3 input arrives onto proximal dendrites. The conditions under which this interaction can explain the formation of a place field in a CA1 pyramidal neuron are not fully understood. In this work, we present a series of simulations using a morphologically and biophysically detailed model of a CA1 pyramidal neuron. We tested the model by simulating a mouse random spatial navigation in a small room with objects. Following a reward signal activated during the navigation in the distal dendrites, as a forward traveling depolarization envelope, the neuron was able to selectively potentiate only the synapses coding for the object present in the visual field. Subsequent navigation through the same environment resulted in the neuron firing as expected for a place cell.