Analysis of matrix and striosomal cell activity to explore and predict mouse behavior in 'T' maze

Abstract

Animals have evolved to allow for decision-making based on rewarding and aversive features of the environment. This ability has been studied in mice and other species as well as the different neuropsychiatric and neurological disorders that undermine this ability. Previous work has shown that some of this decision-making is linked to the striatum, a part of the basal ganglia. There is also previous research that suggests this behavior is partly controlled by a set of distributed striatal microzones known as striosomes. We aim to study the neural activity of striosome and matrix cells in wild type and Huntington disease modeling mice and how they are linked to cost-benefit decision-making. This paper will analyze and model the neural data and train a classifier that can predict the mouse's behavior as it runs a T-maze. The paper finds some support for the claim that striosomes are correlated to the decision-making process.