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Updated: May 13, 2026

In Vivo Wireless Optogenetic Control of Skilled Motor Behavior
Published on: November 22, 2021
Punishment-induced behavioral and neurophysiological variability reveals dopamine-dependent selection of kinematic
Joseph M Galea1, Diane Ruge, Arthur Buijink
1Behavioural Brain Sciences, School of Psychology, University of Birmingham, B15 2TT United Kingdom. joe.galea.01@gmail.com
Abstract:
Action selection describes the high-level process that selects between competing movements. In animals, behavioral variability is critical for the motor exploration required to select the action that optimizes reward and minimizes cost/punishment and is guided by dopamine (DA). The aim of this study was to test in humans whether low-level movement parameters are affected by punishment and reward in ways similar to high-level action selection. Moreover, we addressed the proposed dependence of behavioral and neurophysiological variability on DA and whether this may underpin the exploration of kinematic parameters. Participants performed an out-and-back index finger movement and were instructed that monetary reward and punishment were based on its maximal acceleration (MA). In fact, the feedback was not contingent on the participant's behavior but predetermined. Blocks highly biased toward punishment were associated with increased MA variability relative to blocks either with reward or without feedback. This increase in behavioral variability was positively correlated with neurophysiological variability, as measured by changes in corticospinal excitability with transcranial magnetic stimulation over the primary motor cortex. Following the administration of a DA antagonist, the variability associated with punishment diminished and the correlation between behavioral and neurophysiological variability no longer existed. Similar changes in variability were not observed when participants executed a predetermined MA, nor did DA influence resting neurophysiological variability. Thus, under conditions of punishment, DA-dependent processes influence the selection of low-level movement parameters. We propose that the enhanced behavioral variability reflects the exploration of kinematic parameters for less punishing, or conversely more rewarding, outcomes.
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