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Sci Rep. 2018 Jun 5;8(1):8621. doi: 10.1038/s41598-018-26887-3.

Reinforcement magnitudes modulate subthalamic beta band activity in patients with Parkinson's disease.

Author information

1
Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany. henning.schroll@charite.de.
2
Computer Science, Chemnitz University of Technology, Chemnitz, Germany. henning.schroll@charite.de.
3
Psychology, Humboldt University Berlin, Berlin, Germany. henning.schroll@charite.de.
4
Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany.
5
Neurosurgery, Medical University Hanover, Hanover, Germany.
6
Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany.
7
Computer Science, Chemnitz University of Technology, Chemnitz, Germany.
8
Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany. andrea.kuehn@charite.de.

Abstract

We set out to investigate whether beta oscillations in the human basal ganglia are modulated during reinforcement learning. Based on previous research, we assumed that beta activity might either reflect the magnitudes of individuals' received reinforcements (reinforcement hypothesis), their reinforcement prediction errors (dopamine hypothesis) or their tendencies to repeat versus adapt responses based upon reinforcements (status-quo hypothesis). We tested these hypotheses by recording local field potentials (LFPs) from the subthalamic nuclei of 19 Parkinson's disease patients engaged in a reinforcement-learning paradigm. We then correlated patients' reinforcement magnitudes, reinforcement prediction errors and response repetition tendencies with task-related power changes in their LFP oscillations. During feedback presentation, activity in the frequency range of 14 to 27 Hz (beta spectrum) correlated positively with reinforcement magnitudes. During responding, alpha and low beta activity (6 to 18 Hz) was negatively correlated with previous reinforcement magnitudes. Reinforcement prediction errors and response repetition tendencies did not correlate significantly with LFP oscillations. These results suggest that alpha and beta oscillations during reinforcement learning reflect patients' observed reinforcement magnitudes, rather than their reinforcement prediction errors or their tendencies to repeat versus adapt their responses, arguing both against an involvement of phasic dopamine and against applicability of the status-quo theory.

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