Efficient enhancement of information in the prefrontal cortex during the presence of reward predicting stimuli

Abstract

The prefrontal cortex (PFC) is a key brain structure for decision making, behavioural flexibility and working memory. Neurons in PFC encode relevant stimuli through changes in their firing rate, although the metabolic cost of spiking activity puts strong constrains to neural codes based on firing rate modulation. Thus, how PFC neural populations code relevant information in an efficient way is not clearly understood. To address this issue we made single unit recordings in the PFC of rats performing a GO/NOGO discrimination task and analysed how entropy between pairs of neurons changes during cue presentation. We found that entropy rises only during reward-predicting cues. Moreover, this change in entropy occurred along an increase in the efficiency of the whole process. We studied possible mechanisms behind the efficient gain in entropy by means of a two neuron leaky integrate-and-fire model, and found that a precise relationship between synaptic efficacy and firing rate is required to explain the experimentally observed results.

Putative dopamine neurons in the ventral tegmental area enhance information coding in the prefrontal cortex

“…In a recent study (Mininni et al . 20 ), we found that the coding capacity in PFC increases efficiently during stimuli presentation in a Go/NoGO discrimination task. Further theoretical considerations suggest that changes in PFC signal-to-noise correlation ratio induced by VTA dopamine neurons could explain our results.…”

“…Given that PFC neurons may code information by either increasing or decreasing their firing rate, we employed mutual information (MI) as a measure of information content in PFC to estimate the amount of information conveyed by neural activity regardless of the direction of firing rate changes. To this end, we first built a two-state neuron model that allowed a reliable estimation of MI 20 . In the model, we set the output of every neuron to ‘0’ or ‘1’ depending on whether the number of spikes within a given time window was lower/higher than the average computed in the same window across all correct GO and NoGO trials.…”

“…To study how much information is contained in the neuron population we built a binary neuron model that allows reliable estimation of pairwise Shannon entropy and mutual information 20 . The state of each neuron can be ‘1’ or ‘0’, depending on whether the number of spikes in a given time window was higher or lower than its average across all correct (GO and NoGO) trials.…”

Information capacity and robustness of encoding in the medial prefrontal cortex are modulated by the bioavailability of serotonin and the time elapsed from the cue during a reward-driven task

“…Surgical procedures were performed as previously described 28 . Rats were deeply anesthetized with a single I.P.…”