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Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study
Power changes in specific frequency bands are typical brain responses during motor planning or preparation. Many studies have demonstrated that, in addition to the premotor, supplementary motor, and primary sensorimotor areas, the prefrontal area contributes to generating such responses. However, mo...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4122137/ https://www.ncbi.nlm.nih.gov/pubmed/25126578 http://dx.doi.org/10.1155/2014/783203 |
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author | Ryun, Seokyun Kim, June Sic Lee, Sang Hun Jeong, Sehyoon Kim, Sung-Phil Chung, Chun Kee |
author_facet | Ryun, Seokyun Kim, June Sic Lee, Sang Hun Jeong, Sehyoon Kim, Sung-Phil Chung, Chun Kee |
author_sort | Ryun, Seokyun |
collection | PubMed |
description | Power changes in specific frequency bands are typical brain responses during motor planning or preparation. Many studies have demonstrated that, in addition to the premotor, supplementary motor, and primary sensorimotor areas, the prefrontal area contributes to generating such responses. However, most brain-computer interface (BCI) studies have focused on the primary sensorimotor area and have estimated movements using postonset period brain signals. Our aim was to determine whether the prefrontal area could contribute to the prediction of voluntary movement types before movement onset. In our study, electrocorticography (ECoG) was recorded from six epilepsy patients while performing two self-paced tasks: hand grasping and elbow flexion. The prefrontal area was sufficient to allow classification of different movements through the area's premovement signals (−2.0 s to 0 s) in four subjects. The most pronounced power difference frequency band was the beta band (13–30 Hz). The movement prediction rate during single trial estimation averaged 74% across the six subjects. Our results suggest that premovement signals in the prefrontal area are useful in distinguishing different movement tasks and that the beta band is the most informative for prediction of movement type before movement onset. |
format | Online Article Text |
id | pubmed-4122137 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41221372014-08-14 Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study Ryun, Seokyun Kim, June Sic Lee, Sang Hun Jeong, Sehyoon Kim, Sung-Phil Chung, Chun Kee Biomed Res Int Research Article Power changes in specific frequency bands are typical brain responses during motor planning or preparation. Many studies have demonstrated that, in addition to the premotor, supplementary motor, and primary sensorimotor areas, the prefrontal area contributes to generating such responses. However, most brain-computer interface (BCI) studies have focused on the primary sensorimotor area and have estimated movements using postonset period brain signals. Our aim was to determine whether the prefrontal area could contribute to the prediction of voluntary movement types before movement onset. In our study, electrocorticography (ECoG) was recorded from six epilepsy patients while performing two self-paced tasks: hand grasping and elbow flexion. The prefrontal area was sufficient to allow classification of different movements through the area's premovement signals (−2.0 s to 0 s) in four subjects. The most pronounced power difference frequency band was the beta band (13–30 Hz). The movement prediction rate during single trial estimation averaged 74% across the six subjects. Our results suggest that premovement signals in the prefrontal area are useful in distinguishing different movement tasks and that the beta band is the most informative for prediction of movement type before movement onset. Hindawi Publishing Corporation 2014 2014-07-14 /pmc/articles/PMC4122137/ /pubmed/25126578 http://dx.doi.org/10.1155/2014/783203 Text en Copyright © 2014 Seokyun Ryun et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ryun, Seokyun Kim, June Sic Lee, Sang Hun Jeong, Sehyoon Kim, Sung-Phil Chung, Chun Kee Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study |
title | Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study |
title_full | Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study |
title_fullStr | Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study |
title_full_unstemmed | Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study |
title_short | Movement Type Prediction before Its Onset Using Signals from Prefrontal Area: An Electrocorticography Study |
title_sort | movement type prediction before its onset using signals from prefrontal area: an electrocorticography study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4122137/ https://www.ncbi.nlm.nih.gov/pubmed/25126578 http://dx.doi.org/10.1155/2014/783203 |
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