Skvortsova, V;
Palminteri, S;
Buot, A;
Karachi, C;
Welter, M-L;
Grabli, D;
Pessiglione, M;
(2021)
A Causal Role for the Pedunculopontine Nucleus in Human Instrumental Learning.
Current Biology
, 31
(5)
943-954.e5.
10.1016/j.cub.2020.11.042.
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Abstract
A critical mechanism for maximizing reward is instrumental learning. In standard instrumental learning models, action values are updated on the basis of reward prediction errors (RPEs), defined as the discrepancy between expectations and outcomes. A wealth of evidence across species and experimental techniques has established that RPEs are signaled by midbrain dopamine neurons. However, the way dopamine neurons receive information about reward outcomes remains poorly understood. Recent animal studies suggest that the pedunculopontine nucleus (PPN), a small brainstem structure considered as a locomotor center, is sensitive to reward and sends excitatory projection to dopaminergic nuclei. Here, we examined the hypothesis that the PPN could contribute to reward learning in humans. To this aim, we leveraged a clinical protocol that assessed the therapeutic impact of PPN deep-brain stimulation (DBS) in three patients with Parkinson disease. PPN local field potentials (LFPs), recorded while patients performed an instrumental learning task, showed a specific response to reward outcomes in a low-frequency (alpha-beta) band. Moreover, PPN DBS selectively improved learning from rewards but not from punishments, a pattern that is typically observed following dopaminergic treatment. Computational analyses indicated that the effect of PPN DBS on instrumental learning was best captured by an increase in subjective reward sensitivity. Taken together, these results support a causal role for PPN-mediated reward signals in human instrumental learning.
| Type: | Article |
|---|---|
| Title: | A Causal Role for the Pedunculopontine Nucleus in Human Instrumental Learning |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.cub.2020.11.042 |
| Publisher version: | https://doi.org/10.1016/j.cub.2020.11.042 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Parkinson disease, computational modeling, decision making, deep-brain stimulation, dopamine, local field potentials, low-frequency oscillations, pedunculopontine nucleus, reinforcement learning, reward prediction error |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10120326 |
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