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Modulation of neural activity in frontopolar cortex drives reward-based motor learning

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Sammler,  Daniela
Research Group Neurocognition of Music and Language, Max Planck Institute for Empirical Aesthetics, Max Planck Society;

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Citation

Ruiz, M. H., Maudrich, T., Kalloch, B., Sammler, D., Kenville, R., Villringer, A., et al. (2021). Modulation of neural activity in frontopolar cortex drives reward-based motor learning. Scientific Reports, 11: 20303. doi:10.1038/s41598-021-98571-y.


Cite as: https://hdl.handle.net/21.11116/0000-0009-82D7-1
Abstract
The frontopolar cortex (FPC) contributes to tracking the reward of alternative choices during decision making, as well as their reliability. Whether this FPC function extends to reward gradients associated with continuous movements during motor learning remains unknown. We used anodal transcranial direct current stimulation (tDCS) over the right FPC to investigate its role in reward-based motor learning. Nineteen healthy human participants practiced novel sequences of finger movements on a digital piano with corresponding auditory feedback. Their aim was to use trialwise reward feedback to discover a hidden performance goal along a continuous dimension: timing. We additionally modulated the contralateral motor cortex (left M1) activity, and included a control sham stimulation. Right FPC-tDCS led to faster learning compared to lM1-tDCS and sham through regulation of motor variability. Bayesian computational modelling revealed that in all stimulation protocols, an increase in the trialwise expectation of reward was followed by greater exploitation, as shown previously. Yet, this association was weaker in lM1-tDCS suggesting a less efficient learning strategy. The effects of frontopolar stimulation were dissociated from those induced by lM1-tDCS and sham, as motor exploration was more sensitive to inferred changes in the reward tendency (volatility). The findings suggest that rFPC-tDCS increases the sensitivity of motor exploration to updates in reward volatility, accelerating reward-based motor learning.