Open AccessEfficient enhancement of information in the prefrontal cortex during the presence of reward predicting stimuli
Author(s) -
Camilo J. Mininni,
César F. Caiafa,
Bonifacio Silvano Zanutto,
Kuei Y. Tseng,
Sergio E. Lew
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0188579
Subject(s) - prefrontal cortex , neuroscience , computer science , encode , entropy (arrow of time) , neural coding , transfer entropy , working memory , psychology , artificial intelligence , cognition , biology , principle of maximum entropy , physics , quantum mechanics , biochemistry , gene
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.