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BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy

Epilepsy is marked by hypersynchronous bursts of neuronal activity, and seizures can propagate variably to any and all areas, leading to brain network dynamic organization. However, the relationship between the network characteristics of scalp EEG and blood oxygenation level-dependent (BOLD) respons...

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Autores principales: Qin, Yun, Jiang, Sisi, Zhang, Qiqi, Dong, Li, Jia, Xiaoyan, He, Hui, Yao, Yutong, Yang, Huanghao, Zhang, Tao, Luo, Cheng, Yao, Dezhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425117/
https://www.ncbi.nlm.nih.gov/pubmed/30897433
http://dx.doi.org/10.1016/j.nicl.2019.101759
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author Qin, Yun
Jiang, Sisi
Zhang, Qiqi
Dong, Li
Jia, Xiaoyan
He, Hui
Yao, Yutong
Yang, Huanghao
Zhang, Tao
Luo, Cheng
Yao, Dezhong
author_facet Qin, Yun
Jiang, Sisi
Zhang, Qiqi
Dong, Li
Jia, Xiaoyan
He, Hui
Yao, Yutong
Yang, Huanghao
Zhang, Tao
Luo, Cheng
Yao, Dezhong
author_sort Qin, Yun
collection PubMed
description Epilepsy is marked by hypersynchronous bursts of neuronal activity, and seizures can propagate variably to any and all areas, leading to brain network dynamic organization. However, the relationship between the network characteristics of scalp EEG and blood oxygenation level-dependent (BOLD) responses in epilepsy patients is still not well known. In this study, simultaneous EEG and fMRI data were acquired in 18 juvenile myoclonic epilepsy (JME) patients. Then, the adapted directed transfer function (ADTF) values between EEG electrodes were calculated to define the time-varying network. The variation of network information flow within sliding windows was used as a temporal regressor in fMRI analysis to predict the BOLD response. To investigate the EEG-dependent functional coupling among the responding regions, modulatory interactions were analyzed for network variation of scalp EEG and BOLD time courses. The results showed that BOLD activations associated with high network variation were mainly located in the thalamus, cerebellum, precuneus, inferior temporal lobe and sensorimotor-related areas, including the middle cingulate cortex (MCC), supplemental motor area (SMA), and paracentral lobule. BOLD deactivations associated with medium network variation were found in the frontal, parietal, and occipital areas. In addition, modulatory interaction analysis demonstrated predominantly directional negative modulation effects among the thalamus, cerebellum, frontal and sensorimotor-related areas. This study described a novel method to link BOLD response with simultaneous functional network organization of scalp EEG. These findings suggested the validity of predicting epileptic activity using functional connectivity variation between electrodes. The functional coupling among the thalamus, frontal regions, cerebellum and sensorimotor-related regions may be characteristically involved in epilepsy generation and propagation, which provides new insight into the pathophysiological mechanisms and intervene targets for JME.
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spelling pubmed-64251172019-03-29 BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy Qin, Yun Jiang, Sisi Zhang, Qiqi Dong, Li Jia, Xiaoyan He, Hui Yao, Yutong Yang, Huanghao Zhang, Tao Luo, Cheng Yao, Dezhong Neuroimage Clin Regular Article Epilepsy is marked by hypersynchronous bursts of neuronal activity, and seizures can propagate variably to any and all areas, leading to brain network dynamic organization. However, the relationship between the network characteristics of scalp EEG and blood oxygenation level-dependent (BOLD) responses in epilepsy patients is still not well known. In this study, simultaneous EEG and fMRI data were acquired in 18 juvenile myoclonic epilepsy (JME) patients. Then, the adapted directed transfer function (ADTF) values between EEG electrodes were calculated to define the time-varying network. The variation of network information flow within sliding windows was used as a temporal regressor in fMRI analysis to predict the BOLD response. To investigate the EEG-dependent functional coupling among the responding regions, modulatory interactions were analyzed for network variation of scalp EEG and BOLD time courses. The results showed that BOLD activations associated with high network variation were mainly located in the thalamus, cerebellum, precuneus, inferior temporal lobe and sensorimotor-related areas, including the middle cingulate cortex (MCC), supplemental motor area (SMA), and paracentral lobule. BOLD deactivations associated with medium network variation were found in the frontal, parietal, and occipital areas. In addition, modulatory interaction analysis demonstrated predominantly directional negative modulation effects among the thalamus, cerebellum, frontal and sensorimotor-related areas. This study described a novel method to link BOLD response with simultaneous functional network organization of scalp EEG. These findings suggested the validity of predicting epileptic activity using functional connectivity variation between electrodes. The functional coupling among the thalamus, frontal regions, cerebellum and sensorimotor-related regions may be characteristically involved in epilepsy generation and propagation, which provides new insight into the pathophysiological mechanisms and intervene targets for JME. Elsevier 2019-03-12 /pmc/articles/PMC6425117/ /pubmed/30897433 http://dx.doi.org/10.1016/j.nicl.2019.101759 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Qin, Yun
Jiang, Sisi
Zhang, Qiqi
Dong, Li
Jia, Xiaoyan
He, Hui
Yao, Yutong
Yang, Huanghao
Zhang, Tao
Luo, Cheng
Yao, Dezhong
BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy
title BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy
title_full BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy
title_fullStr BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy
title_full_unstemmed BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy
title_short BOLD-fMRI activity informed by network variation of scalp EEG in juvenile myoclonic epilepsy
title_sort bold-fmri activity informed by network variation of scalp eeg in juvenile myoclonic epilepsy
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6425117/
https://www.ncbi.nlm.nih.gov/pubmed/30897433
http://dx.doi.org/10.1016/j.nicl.2019.101759
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