Theory for Characterization of Hippocampal Long-Term Potentiation Induced by Time-Structured Stimuli

TL;DR

This paper presents a theoretical model for hippocampal long-term potentiation (LTP) induced by various time-structured stimuli, highlighting the significant impact of chaotic stimuli on LTP magnitude.

Contribution

It introduces a neuron model that incorporates NMDA and non-NMDA receptor dynamics to explain experimental LTP results under different stimulus patterns.

Findings

Chaotic stimuli induce the largest LTP in the model.

The model successfully explains experimental observations.

Nonstationary stimuli significantly affect LTP magnitude.

Abstract

We theoretically investigate long-term potentiation (LTP) in the hippocampus using a simple model of a neuron stimulated by three different time-structured input signals (regular, Markov, and chaotic). The synaptic efficacy change is described taking into account both N-methyl-D-aspartate (NMDA) and non-NMDA receptors. The experimental results are successfully explained by our neuron model, and the remarkable fact that the chaotic stimuli in the nonstationary regime produce the largest LTP is discussed.