Biology subjects

Palidis, D. J.

Publications and source records attributed to Palidis, D. J..

3 recordsLinked to original sources

bioRxiv2020

The role of dopamine in reward-based motor adaptation, savings, and interference

Dopamine signaling is thought to mediate reward-based learning. We tested for a role of dopamine in motor adaptation by administering the dopamine precursor levodopa to healthy participants in two experiments involving reaching movements. Levodopa has been shown to impair reward-based learning in cognitive tasks. Thus, we hypothesized that levodopa would selectively impair aspects of motor adaptation that depend on reinforcement of rewarding actions. In the first experiment, participants performed two separate tasks in which adaptation was driven either by visual error-based feedback of the hand position or binary reward feedback. We used EEG to measure event-related potentials evoked by task feedback. We hypothesized that levodopa would specifically diminish adaptation and the neural responses to feedback in the reward learning task. However, levodopa did not affect motor adaptation in either task nor did it diminish event-related potentials elicited by reward outcomes. In the second experiment, participants learned to compensate for mechanical force field perturbations applied to the hand during reaching. Previous exposure to a particular force field can result in savings during subsequent adaptation to the same force field or interference during adaptation to an opposite force field. We hypothesized that levodopa would diminish savings and anterograde interference, as previous work suggests that these phenomena result from a reinforcement learning process. However, we found no reliable effects of levodopa. These results suggest that reward-based motor adaptation, savings, and interference may not depend on the same dopaminergic mechanisms that have been shown to be disrupted by levodopa during various cognitive tasks. New and NoteworthyMotor adaptation relies on multiple processes including reinforcement of successful actions. Cognitive reinforcement learning is impaired by levodopa-induced disruption of dopamine function. We administered levodopa to healthy adults who participated in multiple motor adaptation tasks. We found no effects of levodopa on any component of motor adaptation. This suggests that motor adaptation may not depend on the same dopaminergic mechanisms as cognitive forms or reinforcement learning that have been shown to be impaired by levodopa.

neuroscience↗

bioRxiv2020

EEG correlates of physical effort and reward processing during reinforcement learning

Effort-based decision making is often described by choices according to subjective value, a function of reward discounted by effort. We asked whether a neural reinforcement learning signal, the feedback related negativity (FRN), is modulated not only by reward outcomes but also physical effort. We recorded EEG from human participants while they performed a task in which they were required to accurately produce target levels of muscle activation to receive rewards. Participants performed isometric knee extensions while quadriceps muscle activation was recorded using EMG. Real-time feedback indicated muscle activation relative to a target. On a given trial, the target muscle activation required either low or high effort. The effort was determined probabilistically according to a binary choice, such that the responses were associated with 20% and 80% probability of high effort. This contingency could only be known by experience, and it reversed periodically. After each trial binary reinforcement feedback was provided to indicate whether participants were sufficiently accurate in producing the target muscle activity. Participants adaptively avoided effort by switching responses more frequently after choices that resulted in hard effort. Feedback after participants choices which revealed the resulting effort requirement for the subsequent knee extension did not elicit an FRN component. However, the neural response to reinforcement feedback after the knee extension was increased during and after the time period of the FRN by preceding physical effort. Thus, retrospective effort modulates reward processing which may underlie paradoxical behavioral findings whereby rewards requiring more effort to obtain can become more powerful reinforcers. Significance StatementWhen making decisions, we typically select more rewarding and less effortful options. Neural reinforcement learning signals reinforce rewarding actions and deter punishing actions. When participants received feedback that their choices would require easy or hard physical effort, we did not observe reinforcement learning signals that are typically observed in response to feedback predicting reward and punishment. Thus, the reinforcement learning system does not strictly treat effort as loss or punishment. However, when the effort was completed and participants received feedback indicating whether they successfully achieved a reward or not, reinforcement learning signals were amplified by preceding effort. Thus, retrospective effort can affect neural responses to reinforcement outcomes, which may explain how effort can enhance the motivational effect of reinforcers.

neuroscience↗

bioRxiv2018

Distinct Neural Signatures of Reward and Sensory Prediction Error in Motor Learning

At least two distinct processes have been identified by which motor commands are adapted according to movement-related feedback: reward based learning and sensory error based learning. In sensory error based learning, mappings between sensory targets and motor commands are recalibrated according to sensory error feedback. In reward based learning, motor commands are associated with subjective value, such that successful actions are reinforced. We designed two tasks to isolate reward and sensory error based motor adaptation, and recorded electroencephalography (EEG) from humans to identify and dissociate the neural correlates of reward and sensory error processing. We designed a visuomotor rotation task to isolate sensory error based learning which was induced by altered visual feedback of hand position. In a reward learning task, we isolated reward based learning induced by binary reward feedback that was decoupled from the visual target. We found that a fronto-central event related potential called the feedback related negativity (FRN) was elicited specifically by reward feedback but not sensory error feedback. A more posterior component called the P300 was evoked by feedback in both tasks. In the visuomotor rotation task, P300 amplitude was increased by sensory error induced by perturbed visual feedback, and was correlated with learning rate. In the reward learning task, P300 amplitude was increased by reward relative to non reward and by surprise regardless of feedback valence. We propose that during motor adaptation, the FRN might specifically mark reward prediction error while the P300 might reflect processing which is modulated more generally by prediction error.\n\nNew and NoteworthyWe studied the event related potentials evoked by feedback stimuli during motor adaptation tasks that isolate reward and sensory error learning mechanisms. We found that the feedback related negativity was specifically elicited by reward feedback, while the P300 was observed in both tasks. These results reveal neural processes associated with different learning mechanisms and elucidate which classes of errors, from a computational standpoint, elicit the FRN and P300.

neuroscience↗