| Title |
Node Accessibility in Cortical Networks During Motor Tasks
|
|---|---|
| Published in |
Neuroinformatics, May 2013
|
| DOI | 10.1007/s12021-013-9185-2 |
| Pubmed ID | |
| Authors |
Mario Chavez, Fabrizio De Vico Fallani, Miguel Valencia, Julio Artieda, Donatella Mattia, Vito Latora, Fabio Babiloni |
| Abstract |
Recent findings suggest that the preparation and execution of voluntary self-paced movements are accompanied by the coordination of the oscillatory activities of distributed brain regions. Here, we use electroencephalographic source imaging methods to estimate the cortical movement-related oscillatory activity during finger extension movements. Then, we apply network theory to investigate changes (expressed as differences from the baseline) in the connectivity structure of cortical networks related to the preparation and execution of the movement. We compute the topological accessibility of different cortical areas, measuring how well an area can be reached by the rest of the network. Analysis of cortical networks reveals specific agglomerates of cortical sources that become less accessible during the preparation and the execution of the finger movements. The observed changes neither could be explained by other measures based on geodesics or on multiple paths, nor by power changes in the cortical oscillations. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Austria | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 4% |
| Colombia | 1 | 4% |
| Unknown | 22 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 21% |
| Professor > Associate Professor | 4 | 17% |
| Researcher | 4 | 17% |
| Student > Ph. D. Student | 3 | 13% |
| Professor | 3 | 13% |
| Other | 2 | 8% |
| Unknown | 3 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 5 | 21% |
| Neuroscience | 4 | 17% |
| Psychology | 3 | 13% |
| Medicine and Dentistry | 2 | 8% |
| Physics and Astronomy | 2 | 8% |
| Other | 3 | 13% |
| Unknown | 5 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 01 June 2013.
All research outputs
#15,272,611
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Outputs from Neuroinformatics
#250
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Outputs of similar age
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Outputs of similar age from Neuroinformatics
#6
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