Dynamics of task-related electrophysiological networks: a benchmarking study
Motor, sensory and cognitive functions rely on dynamic reshaping of functional brain networks. Tracking these rapid changes is crucial to understand information processing in the brain, but challenging due to the great variety of dimensionality reduction methods used at the network-level and the lim...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2021-05-01
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| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811921001063 |
| _version_ | 1818437829300060160 |
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| author | Judie Tabbal Aya Kabbara Mohamad Khalil Pascal Benquet Mahmoud Hassan |
| author_facet | Judie Tabbal Aya Kabbara Mohamad Khalil Pascal Benquet Mahmoud Hassan |
| author_sort | Judie Tabbal |
| collection | DOAJ |
| description | Motor, sensory and cognitive functions rely on dynamic reshaping of functional brain networks. Tracking these rapid changes is crucial to understand information processing in the brain, but challenging due to the great variety of dimensionality reduction methods used at the network-level and the limited evaluation studies. Using Magnetoencephalography (MEG) combined with Source Separation (SS) methods, we present an integrated framework to track fast dynamics of electrophysiological brain networks. We evaluate nine SS methods applied to three independent MEG databases (N=95) during motor and memory tasks. We report differences between these methods at the group and subject level. We seek to help researchers in choosing objectively the appropriate SS method when tracking fast reconfiguration of functional brain networks, due to its enormous benefits in cognitive and clinical neuroscience. |
| first_indexed | 2024-12-14T17:30:53Z |
| format | Article |
| id | doaj.art-ec990cbbb4ad456ca0b609dd743f2fe5 |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-12-14T17:30:53Z |
| publishDate | 2021-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-ec990cbbb4ad456ca0b609dd743f2fe52022-12-21T22:53:06ZengElsevierNeuroImage1095-95722021-05-01231117829Dynamics of task-related electrophysiological networks: a benchmarking studyJudie Tabbal0Aya Kabbara1Mohamad Khalil2Pascal Benquet3Mahmoud Hassan4Univ Rennes, LTSI - U1099, F-35000 Rennes, France; Azm Center for Research in Biotechnology and Its Applications, EDST, Lebanese University, Beirut, Lebanon; Corresponding author.Univ Rennes, LTSI - U1099, F-35000 Rennes, FranceAzm Center for Research in Biotechnology and Its Applications, EDST, Lebanese University, Beirut, Lebanon; CRSI Lab, Engineering Faculty, Lebanese University, Beirut, LebanonUniv Rennes, LTSI - U1099, F-35000 Rennes, FranceNeuroKyma, F-35000 Rennes, FranceMotor, sensory and cognitive functions rely on dynamic reshaping of functional brain networks. Tracking these rapid changes is crucial to understand information processing in the brain, but challenging due to the great variety of dimensionality reduction methods used at the network-level and the limited evaluation studies. Using Magnetoencephalography (MEG) combined with Source Separation (SS) methods, we present an integrated framework to track fast dynamics of electrophysiological brain networks. We evaluate nine SS methods applied to three independent MEG databases (N=95) during motor and memory tasks. We report differences between these methods at the group and subject level. We seek to help researchers in choosing objectively the appropriate SS method when tracking fast reconfiguration of functional brain networks, due to its enormous benefits in cognitive and clinical neuroscience.http://www.sciencedirect.com/science/article/pii/S1053811921001063Magneto-encephalography (MEG)Electrophysiological brain networksDynamic functional connectivityDimensionality reductionSource separation |
| spellingShingle | Judie Tabbal Aya Kabbara Mohamad Khalil Pascal Benquet Mahmoud Hassan Dynamics of task-related electrophysiological networks: a benchmarking study NeuroImage Magneto-encephalography (MEG) Electrophysiological brain networks Dynamic functional connectivity Dimensionality reduction Source separation |
| title | Dynamics of task-related electrophysiological networks: a benchmarking study |
| title_full | Dynamics of task-related electrophysiological networks: a benchmarking study |
| title_fullStr | Dynamics of task-related electrophysiological networks: a benchmarking study |
| title_full_unstemmed | Dynamics of task-related electrophysiological networks: a benchmarking study |
| title_short | Dynamics of task-related electrophysiological networks: a benchmarking study |
| title_sort | dynamics of task related electrophysiological networks a benchmarking study |
| topic | Magneto-encephalography (MEG) Electrophysiological brain networks Dynamic functional connectivity Dimensionality reduction Source separation |
| url | http://www.sciencedirect.com/science/article/pii/S1053811921001063 |
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