Evidence map›Paper›PMID 40567292›Full record

ArticleNeuroimage. Reports2021

Basal ganglia activation localized in MEG using a reward task.

Linnea Sepe-Forrest, Frederick W Carver, Romain Quentin, Tom Holroyd, Allison C Nugent

Abstract read
In one paragraph

Article in Neuroimage. Reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Trial
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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

5 authors.

Linnea Sepe-ForrestMagnetoencephalography Core, National Institute of Mental Health, Bethesda, MD, USA.
Frederick W CarverMagnetoencephalography Core, National Institute of Mental Health, Bethesda, MD, USA.
Romain QuentinHuman Cortical Physiology and Neurorehabilitation Section, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA.
Tom HolroydMagnetoencephalography Core, National Institute of Mental Health, Bethesda, MD, USA.
Allison C NugentMagnetoencephalography Core, National Institute of Mental Health, Bethesda, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The basal ganglia are a crucial component of neural networks underlying reward response and many other behaviors. Magnetoencephalography (MEG) can be used to non-invasively study the spatiotemporal dynamics of activity in neural networks. However, challenges associated with detecting deep sources has caused many to doubt the ability of MEG to detect basal ganglia signals. In this study, we employed a gambling task to assess the feasibility of using MEG to investigate basal ganglia-cortical networks during reward processing. Participants gambled to win or lose 5 or 25 cents and received unexpected high-value rewards of 50 cents at random intervals. We contrasted activity between reward conditions in the beta (15-30 Hz), gamma (30-60 Hz), and high gamma (60-150 Hz) bands. We found differences in oscillatory power in the beta and high gamma bands while contrasting the large reward condition with both the small reward and large loss conditions. Basal ganglia activity was localized to the caudate, putamen, and globus pallidum, while cortical activity appeared primarily in parietal and temporal areas. Our results show robust basal ganglia power differences in response to reward and corroborate animal literature showing beta and high gamma activation in the striatum. This experiment demonstrates that it is possible to study basal ganglia activity using MEG and reveals specific characteristics of the normal reward response that will inform future research.

Indexed as

Basal gangliaCortico-striatalGamblingMagnetoencephalographyReward

Identifiers

PMID40567292
PMCPMC12172725

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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.