AUTHOR=Jahans-Price Thomas , Gorochowski Thomas E., Wilson Matthew A., Jones Matthew W., Bogacz Rafal 

TITLE=Computational modeling and analysis of hippocampal-prefrontal information coding during a spatial decision-making task

JOURNAL=Frontiers in Behavioral Neuroscience

VOLUME=Volume 8 - 2014

YEAR=2014

URL=https://www.frontiersin.org/journals/behavioral-neuroscience/articles/10.3389/fnbeh.2014.00062

DOI=10.3389/fnbeh.2014.00062

ISSN=1662-5153

ABSTRACT=We introduce a computational model describing rat behaviour and the interactions of neural populations processing spatial and mnemonic information during a maze-based, decision-making task. The model integrates sensory input and implements a working memory to inform decisions at a choice point, reproducing rat behavioural data and predicting the occurrence of turn- and memory-dependent activity in neuronal networks supporting task performance. We tested these model predictions using a new software toolbox (Maze Query Language, MQL) to analyse activity of medial prefrontal cortical (mPFC) and dorsal hippocampal (dCA1) neurons recorded from 6 adult rats during task performance. The firing rates of dCA1 neurons discriminated context (i.e. the direction of the previous turn), whilst a subset of mPFC neurons was selective for current turn direction or context, with some conjunctively encoding both. mPFC turn-selective neurons displayed a ramping of activity on approach to the decision turn and turn-selectivity in mPFC was significantly reduced during error trials. These analyses complement data from neurophysiological recordings in non-human primates indicating that firing rates of cortical neurons correlate with integration of sensory evidence used to inform decision-making.