Proceedings of the National Academy of SciencesNeurosciencePeer-reviewed journal article
Biased competition in the absence of input bias: predictions from corticostriatal computation
Salva ArdidiD, Jason S. SherfeyiD, Michelle M. McCarthyiD, Joachim HaßiD, Benjamin Pittman-PollettaiD, Nancy KopelliD
Abstract
Classical accounts of biased competition (BC) require an input bias to resolve the competition between neuronal ensembles driving downstream processing. However, flexible and reliable selection of behaviorally-relevant ensembles can occur with unbiased stimulation: striatal D1 and D2 spiny projecting neurons (SPNs) receive balanced cortical input, yet their activity determines the choice between GO and NO-GO pathways in the basal ganglia. We present a corticostriatal model identifying three mechanisms that rely on physiological asymmetries to effect rate- and time-coded BC in the presence of balanced inputs. First, tonic input strength determines which SPN phenotype exhibit higher mean firing rate (FR). Second, low strength oscillatory inputs induce higher FR in D2 SPNs but higher coherence between D1 SPNs. Third, high strength inputs oscillating at distinct frequencies preferentially activate D1 or D2 SPN populations. Of these mechanisms, the latter accommodates observed rhythmic activity supporting rule-based decision making in prefrontal cortex.
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