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Implicit task switching in Parkinson's disease is preserved when on medication.

ABSTRACT: People with Parkinson's disease have been shown to have difficulty switching between movement plans. In the great majority of studies, the need to switch between tasks was made explicitly. Here, we tested whether people with Parkinson's disease, taking their normal medication, have difficulty switching between implicitly specified tasks. We further examined whether this switch is performed predictively or reactively. Twenty five people with Parkinson's disease continuously increased or decreased the frequency of their arm movements, inducing an abrupt-but unaware-switch between rhythmic movements (at high frequencies) and discrete movements (at low frequencies). We tested whether that precipitous change was performed reactively or predictively. We found that 56% of participants predictively switched between the two movement types. The ability of people with Parkinson's disease, taking their regular medication, to predictively control their movements on implicit tasks is thus preserved.

SUBMITTER: Yaffe JA

PROVIDER: S-EPMC6959575 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Implicit task switching in Parkinson's disease is preserved when on medication.

Yaffe Jacob A JA Zlotnik Yair Y Ifergane Gal G Levy-Tzedek Shelly S

PloS one 20200114 1

People with Parkinson's disease have been shown to have difficulty switching between movement plans. In the great majority of studies, the need to switch between tasks was made explicitly. Here, we tested whether people with Parkinson's disease, taking their normal medication, have difficulty switching between implicitly specified tasks. We further examined whether this switch is performed predictively or reactively. Twenty five people with Parkinson's disease continuously increased or decreased ...[more]

PMID: 31935247

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Project description:Malfunctions in the neural circuitry of the basal ganglia (BG), induced by alterations in the dopaminergic system, are responsible for an array of motor disorders and milder cognitive issues in Parkinson's disease (PD). Recently Baston and Ursino (2015a) presented a new neuroscience mathematical model aimed at exploring the role of basal ganglia in action selection. The model is biologically inspired and reproduces the main BG structures and pathways, modeling explicitly both the dopaminergic and the cholinergic system. The present work aims at interfacing this neurocomputational model with a compartmental model of levodopa, to propose a general model of medicated Parkinson's disease. Levodopa effect on the striatum was simulated with a two-compartment model of pharmacokinetics in plasma joined with a motor effect compartment. The latter is characterized by the levodopa removal rate and by a sigmoidal relationship (Hill law) between concentration and effect. The main parameters of this relationship are saturation, steepness, and the half-maximum concentration. The effect of levodopa is then summed to a term representing the endogenous dopamine effect, and is used as an external input for the neurocomputation model; this allows both the temporal aspects of medication and the individual patient characteristics to be simulated. The frequency of alternate tapping is then used as the outcome of the whole model, to simulate effective clinical scores. Pharmacokinetic-pharmacodynamic modeling was preliminary performed on data of six patients with Parkinson's disease (both "stable" and "wearing-off" responders) after levodopa standardized oral dosing over 4 h. Results show that the model is able to reproduce the temporal profiles of levodopa in plasma and the finger tapping frequency in all patients, discriminating between different patterns of levodopa motor response. The more influential parameters are the Hill coefficient, related with the slope of the effect sigmoidal relationship, the drug concentration at half-maximum effect, and the drug removal rate from the effect compartment. The model can be of value to gain a deeper understanding on the pharmacokinetics and pharmacodynamics of the medication, and on the way dopamine is exploited in the neural circuitry of the basal ganglia in patients at different stages of the disease progression.

Project description:Empirical evidence suggests that levodopa medication used to treat the motor symptoms of Parkinson's disease (PD) may either improve, impair or not affect specific cognitive processes. This evidence led to the 'dopamine overdose' hypothesis that levodopa medication impairs performance on cognitive tasks if they recruit fronto-striatal circuits which are not yet dopamine-depleted in early PD and as a result the medication leads to an excess of dopamine. This hypothesis has been supported for various learning tasks including conditional associative learning, reversal learning, classification learning and intentional deterministic sequence learning, on all of which PD patients demonstrated significantly worse performance when tested on relative to off dopamine medication. Incidental sequence learning is impaired in PD, but how such learning is affected by dopaminergic therapy remains undetermined. The aim of the current study was to investigate the effect of dopaminergic medication on incidental sequence learning in PD. We used a probabilistic serial reaction time task (SRTT), a sequence learning paradigm considered to make the sequence less apparent and more likely to be learned incidentally rather than intentionally. We compared learning by the same group of PD patients (n=15) on two separate occasions following oral administration of levodopa medication (on state) and after overnight withdrawal of medication (off state). Our results demonstrate for the first time that levodopa medication enhances incidental learning of a probabilistic sequence on the serial reaction time task in PD. However, neither group significantly differed from performance of a control group without a neurological disease, which indicates the importance of within group comparisons for identifying deficits. Levodopa medication enhanced incidental learning by patients with PD on a probabilistic sequence learning paradigm even though the patients were not aware of the existence of the sequence or their acquired knowledge. The results suggest a role in acquiring incidental motor sequence learning for dorsal striatal areas strongly affected by dopamine depletion in early PD.

Dataset Information

Implicit task switching in Parkinson's disease is preserved when on medication.

Publications

Implicit task switching in Parkinson's disease is preserved when on medication.

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