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Local Fields in Human Subthalamic Nucleus Track the Lead-up to Impulsive Choices

Overview of attention for article published in Frontiers in Neuroscience, November 2017
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (67th percentile)

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Title
Local Fields in Human Subthalamic Nucleus Track the Lead-up to Impulsive Choices
Published in
Frontiers in Neuroscience, November 2017
DOI 10.3389/fnins.2017.00646
Pubmed ID
Authors

John M. Pearson, Patrick T. Hickey, Shivanand P. Lad, Michael L. Platt, Dennis A. Turner

Abstract

The ability to adaptively minimize not only motor but cognitive symptoms of neurological diseases, such as Parkinson's Disease (PD) and obsessive-compulsive disorder (OCD), is a primary goal of next-generation deep brain stimulation (DBS) devices. On the basis of studies demonstrating a link between beta-band synchronization and severity of motor symptoms in PD, the minimization of beta band activity has been proposed as a potential training target for closed-loop DBS. At present, no comparable signal is known for the impulsive side effects of PD, though multiple studies have implicated theta band activity within the subthalamic nucleus (STN), the site of DBS treatment, in processes of conflict monitoring and countermanding. Here, we address this challenge by recording from multiple independent channels within the STN in a self-paced decision task to test whether these signals carry information sufficient to predict stopping behavior on a trial-by-trial basis. As in previous studies, we found that local field potentials (LFPs) exhibited modulations preceding self-initiated movements, with power ramping across multiple frequencies during the deliberation period. In addition, signals showed phasic changes in power around the time of decision. However, a prospective model that attempted to use these signals to predict decision times showed effects of risk level did not improve with the addition of LFPs as regressors. These findings suggest information tracking the lead-up to impulsive choices is distributed across multiple frequency scales in STN, though current techniques may not possess sufficient signal-to-noise ratios to predict-and thus curb-impulsive behavior on a moment-to-moment basis.

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The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 86 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 86 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 21%
Student > Master 11 13%
Student > Bachelor 10 12%
Researcher 9 10%
Student > Postgraduate 4 5%
Other 9 10%
Unknown 25 29%
Readers by discipline Count As %
Neuroscience 17 20%
Medicine and Dentistry 14 16%
Psychology 8 9%
Engineering 7 8%
Business, Management and Accounting 1 1%
Other 5 6%
Unknown 34 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 December 2017.
All research outputs
#7,208,166
of 25,382,440 outputs
Outputs from Frontiers in Neuroscience
#4,675
of 11,542 outputs
Outputs of similar age
#131,560
of 445,887 outputs
Outputs of similar age from Frontiers in Neuroscience
#59
of 189 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 11,542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.0. This one has gotten more attention than average, scoring higher than 59% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 445,887 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.