| Title |
Developmental Trajectory of Beta Cortical Oscillatory Activity During a Knee Motor Task
|
|---|---|
| Published in |
Brain Topography, June 2016
|
| DOI | 10.1007/s10548-016-0500-8 |
| Pubmed ID | |
| Authors |
Max J. Kurz, Amy L. Proskovec, James E. Gehringer, Katherine M. Becker, David J. Arpin, Elizabeth Heinrichs-Graham, Tony W. Wilson |
| Abstract |
There is currently a void in the scientific literature on the cortical beta oscillatory activity that is associated with the production of leg motor actions. In addition, we have limited data on how these cortical oscillations may progressively change as a function of development. This study began to fill this vast knowledge gap by using high-density magnetoencephalography to quantify the beta cortical oscillatory activity over a cross-section of typically developing children as they performed an isometric knee target matching task. Advanced beamforming methods were used to identify the spatiotemporal changes in beta oscillatory activity during the motor planning and motor action time frames. Our results showed that a widespread beta event-related desynchronization (ERD) was present across the pre/postcentral gyri, supplementary motor area, and the parietal cortices during the motor planning stage. The strength of this beta ERD sharply diminished across this fronto-parietal network as the children initiated the isometric force needed to match the target. Rank order correlations indicated that the older children were more likely to initiate their force production sooner, took less time to match the targets, and tended to have a weaker beta ERD during the motor planning stage. Lastly, we determined that there was a relationship between the child's age and the strength of the beta ERD within the parietal cortices during isometric force production. Altogether our results suggest that there are notable maturational changes during childhood and adolescence in beta cortical oscillatory activity that are associated with the planning and execution of leg motor actions. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 26 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 19% |
| Other | 3 | 12% |
| Student > Ph. D. Student | 3 | 12% |
| Student > Bachelor | 2 | 8% |
| Student > Doctoral Student | 1 | 4% |
| Other | 6 | 23% |
| Unknown | 6 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 5 | 19% |
| Medicine and Dentistry | 2 | 8% |
| Agricultural and Biological Sciences | 2 | 8% |
| Veterinary Science and Veterinary Medicine | 1 | 4% |
| Nursing and Health Professions | 1 | 4% |
| Other | 6 | 23% |
| Unknown | 9 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 11 August 2016.
All research outputs
#14,856,117
of 22,879,161 outputs
Outputs from Brain Topography
#283
of 487 outputs
Outputs of similar age
#204,445
of 343,021 outputs
Outputs of similar age from Brain Topography
#4
of 9 outputs
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