Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography
Magnetoencephalography has gained an increasing importance in systems neuroscience thanks to the possibility it offers of unraveling brain networks at time-scales relevant to behavior, i.e., frequencies in the 1–100 Hz range, with sufficient spatial resolution. In the first part of this review, we d...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2019-09-01
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| Series: | Frontiers in Neuroscience |
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| Online Access: | https://www.frontiersin.org/article/10.3389/fnins.2019.00964/full |
| _version_ | 1818356077083754496 |
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| author | Laura Marzetti Laura Marzetti Alessio Basti Alessio Basti Federico Chella Federico Chella Antea D'Andrea Antea D'Andrea Jaakko Syrjälä Jaakko Syrjälä Vittorio Pizzella Vittorio Pizzella |
| author_facet | Laura Marzetti Laura Marzetti Alessio Basti Alessio Basti Federico Chella Federico Chella Antea D'Andrea Antea D'Andrea Jaakko Syrjälä Jaakko Syrjälä Vittorio Pizzella Vittorio Pizzella |
| author_sort | Laura Marzetti |
| collection | DOAJ |
| description | Magnetoencephalography has gained an increasing importance in systems neuroscience thanks to the possibility it offers of unraveling brain networks at time-scales relevant to behavior, i.e., frequencies in the 1–100 Hz range, with sufficient spatial resolution. In the first part of this review, we describe, in a unified mathematical framework, a large set of metrics used to estimate MEG functional connectivity at the same or at different frequencies. The different metrics are presented according to their characteristics: same-frequency or cross-frequency, univariate or multivariate, directed or undirected. We focus on phase coupling metrics given that phase coupling of neuronal oscillations is a putative mechanism for inter-areal communication, and that MEG is an ideal tool to non-invasively detect such coupling. In the second part of this review, we present examples of the use of specific phase methods on real MEG data in the context of resting state, visuospatial attention and working memory. Overall, the results of the studies provide evidence for frequency specific and/or cross-frequency brain circuits which partially overlap with brain networks as identified by hemodynamic-based imaging techniques, such as functional Magnetic Resonance (fMRI). Additionally, the relation of these functional brain circuits to anatomy and to behavior highlights the usefulness of MEG phase coupling in systems neuroscience studies. In conclusion, we believe that the field of MEG functional connectivity has made substantial steps forward in the recent years and is now ready for bringing the study of brain networks to a more mechanistic understanding. |
| first_indexed | 2024-12-13T19:51:28Z |
| format | Article |
| id | doaj.art-34e9b2e6b15644e1ac082bb69a30c0c8 |
| institution | Directory Open Access Journal |
| issn | 1662-453X |
| language | English |
| last_indexed | 2024-12-13T19:51:28Z |
| publishDate | 2019-09-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Neuroscience |
| spelling | doaj.art-34e9b2e6b15644e1ac082bb69a30c0c82022-12-21T23:33:25ZengFrontiers Media S.A.Frontiers in Neuroscience1662-453X2019-09-011310.3389/fnins.2019.00964469179Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From MagnetoencephalographyLaura Marzetti0Laura Marzetti1Alessio Basti2Alessio Basti3Federico Chella4Federico Chella5Antea D'Andrea6Antea D'Andrea7Jaakko Syrjälä8Jaakko Syrjälä9Vittorio Pizzella10Vittorio Pizzella11Imaging and Clinical Sciences, Department of Neuroscience, University of Chieti-Pescara, Chieti, ItalyInstitute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, ItalyImaging and Clinical Sciences, Department of Neuroscience, University of Chieti-Pescara, Chieti, ItalyInstitute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, ItalyImaging and Clinical Sciences, Department of Neuroscience, University of Chieti-Pescara, Chieti, ItalyInstitute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, ItalyImaging and Clinical Sciences, Department of Neuroscience, University of Chieti-Pescara, Chieti, ItalyInstitute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, ItalyImaging and Clinical Sciences, Department of Neuroscience, University of Chieti-Pescara, Chieti, ItalyInstitute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, ItalyImaging and Clinical Sciences, Department of Neuroscience, University of Chieti-Pescara, Chieti, ItalyInstitute for Advanced Biomedical Technologies, University of Chieti-Pescara, Chieti, ItalyMagnetoencephalography has gained an increasing importance in systems neuroscience thanks to the possibility it offers of unraveling brain networks at time-scales relevant to behavior, i.e., frequencies in the 1–100 Hz range, with sufficient spatial resolution. In the first part of this review, we describe, in a unified mathematical framework, a large set of metrics used to estimate MEG functional connectivity at the same or at different frequencies. The different metrics are presented according to their characteristics: same-frequency or cross-frequency, univariate or multivariate, directed or undirected. We focus on phase coupling metrics given that phase coupling of neuronal oscillations is a putative mechanism for inter-areal communication, and that MEG is an ideal tool to non-invasively detect such coupling. In the second part of this review, we present examples of the use of specific phase methods on real MEG data in the context of resting state, visuospatial attention and working memory. Overall, the results of the studies provide evidence for frequency specific and/or cross-frequency brain circuits which partially overlap with brain networks as identified by hemodynamic-based imaging techniques, such as functional Magnetic Resonance (fMRI). Additionally, the relation of these functional brain circuits to anatomy and to behavior highlights the usefulness of MEG phase coupling in systems neuroscience studies. In conclusion, we believe that the field of MEG functional connectivity has made substantial steps forward in the recent years and is now ready for bringing the study of brain networks to a more mechanistic understanding.https://www.frontiersin.org/article/10.3389/fnins.2019.00964/fullmagnetoencephalographyfunctional connectivitybrain networksphase couplingbrain rhythms |
| spellingShingle | Laura Marzetti Laura Marzetti Alessio Basti Alessio Basti Federico Chella Federico Chella Antea D'Andrea Antea D'Andrea Jaakko Syrjälä Jaakko Syrjälä Vittorio Pizzella Vittorio Pizzella Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography Frontiers in Neuroscience magnetoencephalography functional connectivity brain networks phase coupling brain rhythms |
| title | Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography |
| title_full | Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography |
| title_fullStr | Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography |
| title_full_unstemmed | Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography |
| title_short | Brain Functional Connectivity Through Phase Coupling of Neuronal Oscillations: A Perspective From Magnetoencephalography |
| title_sort | brain functional connectivity through phase coupling of neuronal oscillations a perspective from magnetoencephalography |
| topic | magnetoencephalography functional connectivity brain networks phase coupling brain rhythms |
| url | https://www.frontiersin.org/article/10.3389/fnins.2019.00964/full |
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