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Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis

This paper presents an alternative method, called as parallel factor analysis (PARAFAC) with a continuous wavelet transform, to analyze of brain activity in patients with chronic pain in the time-frequency-channel domain and quantifies differences between chronic pain patients and controls in these...

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Autores principales: Wang, Juan, Li, Xiaoli, Lu, Chengbiao, Voss, Logan J., Barnard, John P. M., Sleigh, Jamie W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287053/
https://www.ncbi.nlm.nih.gov/pubmed/22400048
http://dx.doi.org/10.1155/2012/279560
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author Wang, Juan
Li, Xiaoli
Lu, Chengbiao
Voss, Logan J.
Barnard, John P. M.
Sleigh, Jamie W.
author_facet Wang, Juan
Li, Xiaoli
Lu, Chengbiao
Voss, Logan J.
Barnard, John P. M.
Sleigh, Jamie W.
author_sort Wang, Juan
collection PubMed
description This paper presents an alternative method, called as parallel factor analysis (PARAFAC) with a continuous wavelet transform, to analyze of brain activity in patients with chronic pain in the time-frequency-channel domain and quantifies differences between chronic pain patients and controls in these domains. The event related multiple EEG recordings of the chronic pain patients and non-pain controls with somatosensory stimuli (pain, random pain, touch, random touch) are analyzed. Multiple linear regression (MLR) is applied to describe the effects of aging on the frequency response differences between patients and controls. The results show that the somatosensory cortical responses occurred around 250 ms in both groups. In the frequency domain, the neural response frequency in the pain group (around 4 Hz) was less than that in the control group (around 5.5 Hz) under the somatosensory stimuli. In the channel domain, cortical activation was predominant in the frontal region for the chronic pain group and in the central region for controls. The indices of active ratios were statistical significant between the two groups in the frontal and central regions. These findings demonstrate that the PARAFAC is an interesting method to understanding the pathophysiological characteristics of chronic pain.
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spelling pubmed-32870532012-03-07 Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis Wang, Juan Li, Xiaoli Lu, Chengbiao Voss, Logan J. Barnard, John P. M. Sleigh, Jamie W. Comput Math Methods Med Research Article This paper presents an alternative method, called as parallel factor analysis (PARAFAC) with a continuous wavelet transform, to analyze of brain activity in patients with chronic pain in the time-frequency-channel domain and quantifies differences between chronic pain patients and controls in these domains. The event related multiple EEG recordings of the chronic pain patients and non-pain controls with somatosensory stimuli (pain, random pain, touch, random touch) are analyzed. Multiple linear regression (MLR) is applied to describe the effects of aging on the frequency response differences between patients and controls. The results show that the somatosensory cortical responses occurred around 250 ms in both groups. In the frequency domain, the neural response frequency in the pain group (around 4 Hz) was less than that in the control group (around 5.5 Hz) under the somatosensory stimuli. In the channel domain, cortical activation was predominant in the frontal region for the chronic pain group and in the central region for controls. The indices of active ratios were statistical significant between the two groups in the frontal and central regions. These findings demonstrate that the PARAFAC is an interesting method to understanding the pathophysiological characteristics of chronic pain. Hindawi Publishing Corporation 2012 2012-02-02 /pmc/articles/PMC3287053/ /pubmed/22400048 http://dx.doi.org/10.1155/2012/279560 Text en Copyright © 2012 Juan Wang 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
Wang, Juan
Li, Xiaoli
Lu, Chengbiao
Voss, Logan J.
Barnard, John P. M.
Sleigh, Jamie W.
Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis
title Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis
title_full Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis
title_fullStr Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis
title_full_unstemmed Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis
title_short Characteristics of Evoked Potential Multiple EEG Recordings in Patients with Chronic Pain by Means of Parallel Factor Analysis
title_sort characteristics of evoked potential multiple eeg recordings in patients with chronic pain by means of parallel factor analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3287053/
https://www.ncbi.nlm.nih.gov/pubmed/22400048
http://dx.doi.org/10.1155/2012/279560
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