Faculty Opinions recommendation of Dopamine and performance in a reinforcement learning task: evidence from Parkinson's disease.

Author(s):  
Kent Berridge
Brain ◽  
2012 ◽  
Vol 135 (6) ◽  
pp. 1871-1883 ◽  
Author(s):  
Tamara Shiner ◽  
Ben Seymour ◽  
Klaus Wunderlich ◽  
Ciaran Hill ◽  
Kailash P. Bhatia ◽  
...  

2020 ◽  
Author(s):  
Brónagh McCoy ◽  
Rebecca P. Lawson ◽  
Jan Theeuwes

ABSTRACTDopamine is known to be involved in several important cognitive processes, most notably in learning from rewards and in the ability to attend to task-relevant aspects of the environment. Both of these features of dopaminergic signalling have been studied separately in research involving Parkinson’s disease (PD) patients, who exhibit diminished levels of dopamine. Here, we tie together some of the commonalities in the effects of dopamine on these aspects of cognition by having PD patients (ON and OFF dopaminergic medication) and healthy controls (HCs) perform two tasks that probe these processes. Within-patient behavioural measures of distractibility, from an attentional capture task, and learning performance, from a probabilistic classification reinforcement learning task, were included in one model to assess the role of distractibility during learning. Dopamine medication state and distractibility level were found to have an interactive effect on learning performance; less distractibility in PD ON was associated with higher accuracy during learning, and this was altered in PD OFF. Functional magnetic resonance imaging (fMRI) data acquired during the learning task furthermore allowed us to assess multivariate patterns of positive and negative outcomes in fronto-striatal and visual brain regions involved in both learning processes and the executive control of attention. Here, we demonstrate that while PD ON show a clearer distinction between outcomes than OFF in dorsolateral prefrontal cortex (DLPFC) and putamen, PD OFF show better distinction of activation patterns in visual regions that respond to the stimuli presented during the task. These results demonstrate that dopamine plays a key role in modulating the interaction between attention and learning at the level of both behaviour and activation patterns in the brain.


Brain ◽  
2020 ◽  
Vol 143 (11) ◽  
pp. 3422-3434
Author(s):  
Annelies J van Nuland ◽  
Rick C Helmich ◽  
Michiel F Dirkx ◽  
Heidemarie Zach ◽  
Ivan Toni ◽  
...  

Abstract Parkinson’s disease is clinically defined by bradykinesia, along with rigidity and tremor. However, the severity of these motor signs is greatly variable between individuals, particularly the presence or absence of tremor. This variability in tremor relates to variation in cognitive/motivational impairment, as well as the spatial distribution of neurodegeneration in the midbrain and dopamine depletion in the striatum. Here we ask whether interindividual heterogeneity in tremor symptoms could account for the puzzlingly large variability in the effects of dopaminergic medication on reinforcement learning, a fundamental cognitive function known to rely on dopamine. Given that tremor-dominant and non-tremor Parkinson’s disease patients have different dopaminergic phenotypes, we hypothesized that effects of dopaminergic medication on reinforcement learning differ between tremor-dominant and non-tremor patients. Forty-three tremor-dominant and 20 non-tremor patients with Parkinson’s disease were recruited to be tested both OFF and ON dopaminergic medication (200/50 mg levodopa-benserazide), while 22 age-matched control subjects were recruited to be tested twice OFF medication. Participants performed a reinforcement learning task designed to dissociate effects on learning rate from effects on motivational choice (i.e. the tendency to ‘Go/NoGo’ in the face of reward/threat of punishment). In non-tremor patients, dopaminergic medication improved reward-based choice, replicating previous studies. In contrast, in tremor-dominant patients, dopaminergic medication improved learning from punishment. Formal modelling showed divergent computational effects of dopaminergic medication as a function of Parkinson’s disease motor phenotype, with a modulation of motivational choice bias and learning rate in non-tremor and tremor patients, respectively. This finding establishes a novel cognitive/motivational difference between tremor and non-tremor Parkinson’s disease patients, and highlights the importance of considering motor phenotype in future work.


Ergonomics ◽  
2022 ◽  
pp. 1-30
Author(s):  
Gisele C. Gotardi ◽  
Fabio A. Barbieri ◽  
Rafael O. Simão ◽  
Vinicius A. Pereira ◽  
André M. Baptista ◽  
...  

2020 ◽  
Vol 127 (10) ◽  
pp. 1369-1376
Author(s):  
Thomas Müller ◽  
Ali Harati

Abstract Motor symptoms in patients with Parkinson’s disease may be determined with instrumental tests and rating procedures. Their outcomes reflect the functioning and the impairment of the individual patient when patients are tested off and on dopamine substituting drugs. Objectives were to investigate whether the execution speed of a handwriting task, instrumentally assessed fine motor behavior, and rating scores improve after soluble levodopa application. 38 right-handed patients were taken off their regular drug therapy for at least 12 h before scoring, handwriting, and performance of instrumental devices before and 1 h after 100 mg levodopa intake. The outcomes of all performed procedures improved. The easy-to-perform handwriting task and the instrumental tests demand for fast and precise execution of movement sequences with considerable cognitive load in the domains' attention and concentration. These investigations may serve as additional tools for the testing of the dopaminergic response.


2020 ◽  
Author(s):  
Walter Maetzler ◽  
Lynn Rochester ◽  
Roongroj Bhidayasiri ◽  
Alberto J. Espay ◽  
Alvaro Sánchez‐Ferro ◽  
...  

Brain ◽  
2020 ◽  
Vol 143 (11) ◽  
pp. 3178-3180
Author(s):  
Sanjay G Manohar

This scientific commentary refers to ‘Effects of dopamine on reinforcement learning in Parkinson’s disease depend on motor phenotype’ by van Nuland et al. (doi:10.1093/brain/awaa335).


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