Dopamine encodes reward and its prediction in reinforcement learning. Catechol-O-methyltransferase (COMT) activity in the medial prefrontal cortex (mPFC) has been shown to influence cognitive abilities by modifying dopamine clearance. Nevertheless, it is unknown how COMT in the mPFC influences operant learning. Systemic entacapone (50mg/kg), as well as local entacapone (3 pg) and recombinant COMT (17 μg) in the mPFC were administered to male Long Evans rats prior to training in an operant conditioning task. We found that systemic and local administration of the COMT inhibitor entacapone significantly improves learning performance. Conversely, recombinant COMT administration totally impaired learning. These data have been interpreted through a computational model where the phasic firing of dopaminergic neurons was computed by means of a temporal difference algorithm and dopamine bioavailability in the mPFC was simulated with a gating window. The duration of this window was selected to simulate the effects of inhibited or enhanced COMT activity (by entacapone or recombinant COMT respectively). The model accounts for an improved performance reproducing the entacapone effects, and a detrimental impact on learning when the clearance is increased reproducing the recombinant COMT effects. The experimental and computational results show that learning performance can be deeply influenced by COMT manipulations in the mPFC.
Keywords: COMT; Computational model; Dopamine; Entacapone; Neural network; Prefrontal cortex.
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