Evidence map›Paper›PMID 34548517›Full record

ArticleScientific reports2021

Exploring reward-related attention selectivity deficits in Parkinson's disease.

Matthew J D Pilgrim, Zhen-Yi Andy Ou, Madeleine Sharp

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Matthew J D PilgrimDepartment of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, H3A 2B4, Canada.
Zhen-Yi Andy OuDepartment of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, H3A 2B4, Canada.
Madeleine SharpDepartment of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montréal, QC, H3A 2B4, Canada. madeleine.sharp@mcgill.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An important aspect of managing a limited cognitive resource like attention is to use the reward value of stimuli to prioritize the allocation of attention to higher-value over lower-value stimuli. Recent evidence suggests this depends on dopaminergic signaling of reward. In Parkinson's disease, both reward sensitivity and attention are impaired, but whether these deficits are directly related to one another is unknown. We tested whether Parkinson's patients use reward information when automatically allocating their attention and whether this is modulated by dopamine replacement. We compared patients, tested both ON and OFF dopamine replacement medication, to older controls using a standard attention capture task. First, participants learned the different reward values of stimuli. Then, these reward-associated stimuli were used as distractors in a visual search task. We found that patients were generally distracted by the presence of the distractors but that the degree of distraction caused by the high-value and low-value distractors was similar. Furthermore, we found no evidence to support the possibility that dopamine replacement modulates the effect of reward on automatic attention allocation. Our results suggest a possible inability in Parkinson's patients to use the reward value of stimuli when automatically allocating their attention, and raise the possibility that reward-driven allocation of resources may affect the adaptive modulation of other cognitive processes.

Indexed as

AttentionRewardAgedCase-Control StudiesFemaleHumansMaleMiddle AgedNeuropsychological TestsParkinson DiseaseTask Performance and Analysis

Identifiers

PMID34548517
PMCPMC8455525

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.