Computational Dissociation of Dopaminergic and Cholinergic Effects on Action Selection and Inhibitory Control

Abstract

Background: Patients with schizophrenia make more errors than healthy subjects in the antisaccade task. In this paradigm, participants are required to inhibit a reflexive saccade to a target and to select the correct action (a saccade in the opposite direction). While the precise origin of this deficit is not clear, it has been connected to aberrant dopaminergic and cholinergic neuromodulation.

Methods: To study the impact of dopamine and acetylcholine on inhibitory control and action selection, we administered two selective drugs (levodopa 200 mg/galantamine 8 mg) to healthy volunteers (N = 100) performing the antisaccade task. The computational model SERIA (stochastic early reaction, inhibition, and late action) was employed to separate the contribution of inhibitory control and action selection to empirical reaction times and error rates.

Results: Modeling suggested that levodopa improved action selection (at the cost of increased reaction times) but did not have a significant effect on inhibitory control. By contrast, according to our model, galantamine affected inhibitory control in a dose-dependent fashion, reducing inhibition failures at low doses and increasing them at higher levels. These effects were sufficiently specific that the computational analysis allowed for identifying the drug administered to an individual with 70% accuracy.

Conclusions: Our results do not support the hypothesis that elevated tonic dopamine strongly impairs inhibitory control. Rather, levodopa improved the ability to select correct actions. However, inhibitory control was modulated by cholinergic drugs. This approach may provide a starting point for future computational assays that differentiate neuromodulatory abnormalities in heterogeneous diseases like schizophrenia.

Keywords: Action selection; Antisaccades; Computational psychiatry; Galantamine; Inhibitory control; Levodopa; Schizophrenia.