Electrophysiological signatures of resting state networks in the human brain.
Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographical...
| Main Authors: | , , , , |
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| Format: | Journal article |
| Language: | English |
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2007
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| _version_ | 1797095448485298176 |
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| author | Mantini, D Perrucci, MG Del Gratta, C Romani, G Corbetta, M |
| author_facet | Mantini, D Perrucci, MG Del Gratta, C Romani, G Corbetta, M |
| author_sort | Mantini, D |
| collection | OXFORD |
| description | Functional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1-80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies. |
| first_indexed | 2024-03-07T04:27:56Z |
| format | Journal article |
| id | oxford-uuid:cd4ddbf9-6be8-4aae-a81c-750c7ca3dbcc |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:27:56Z |
| publishDate | 2007 |
| record_format | dspace |
| spelling | oxford-uuid:cd4ddbf9-6be8-4aae-a81c-750c7ca3dbcc2022-03-27T07:27:45ZElectrophysiological signatures of resting state networks in the human brain.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:cd4ddbf9-6be8-4aae-a81c-750c7ca3dbccEnglishSymplectic Elements at Oxford2007Mantini, DPerrucci, MGDel Gratta, CRomani, GCorbetta, MFunctional neuroimaging and electrophysiological studies have documented a dynamic baseline of intrinsic (not stimulus- or task-evoked) brain activity during resting wakefulness. This baseline is characterized by slow (<0.1 Hz) fluctuations of functional imaging signals that are topographically organized in discrete brain networks, and by much faster (1-80 Hz) electrical oscillations. To investigate the relationship between hemodynamic and electrical oscillations, we have adopted a completely data-driven approach that combines information from simultaneous electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Using independent component analysis on the fMRI data, we identified six widely distributed resting state networks. The blood oxygenation level-dependent signal fluctuations associated with each network were correlated with the EEG power variations of delta, theta, alpha, beta, and gamma rhythms. Each functional network was characterized by a specific electrophysiological signature that involved the combination of different brain rhythms. Moreover, the joint EEG/fMRI analysis afforded a finer physiological fractionation of brain networks in the resting human brain. This result supports for the first time in humans the coalescence of several brain rhythms within large-scale brain networks as suggested by biophysical studies. |
| spellingShingle | Mantini, D Perrucci, MG Del Gratta, C Romani, G Corbetta, M Electrophysiological signatures of resting state networks in the human brain. |
| title | Electrophysiological signatures of resting state networks in the human brain. |
| title_full | Electrophysiological signatures of resting state networks in the human brain. |
| title_fullStr | Electrophysiological signatures of resting state networks in the human brain. |
| title_full_unstemmed | Electrophysiological signatures of resting state networks in the human brain. |
| title_short | Electrophysiological signatures of resting state networks in the human brain. |
| title_sort | electrophysiological signatures of resting state networks in the human brain |
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