Resting-State Network Transitions in Temporal Lobe Epilepsy: Insights From MEG-Based Dynamic Functional Connectivity
Temporal Lobe Epilepsy (TLE), a common form of focal epilepsy, is associated with recurrent seizures originating in the temporal lobe, often leading to cognitive and psychological impairments. This study explores dynamic functional connectivity (dFC) patterns in TLE patients compared to Healthy Cont...
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IEEE
2025-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
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| Online Access: | https://ieeexplore.ieee.org/document/11021573/ |
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| author | M. V. Suhas Sanjib Sinha Karunakar Kotegar M. Ravindranadh Chowdary K. Raghavendra Ajay Asranna L. G. Viswanathan N. Mariyappa H. Anitha |
| author_facet | M. V. Suhas Sanjib Sinha Karunakar Kotegar M. Ravindranadh Chowdary K. Raghavendra Ajay Asranna L. G. Viswanathan N. Mariyappa H. Anitha |
| author_sort | M. V. Suhas |
| collection | DOAJ |
| description | Temporal Lobe Epilepsy (TLE), a common form of focal epilepsy, is associated with recurrent seizures originating in the temporal lobe, often leading to cognitive and psychological impairments. This study explores dynamic functional connectivity (dFC) patterns in TLE patients compared to Healthy Controls (HC) using resting-state Magnetoencephalography (MEG) data. dFC, which captures the temporal variability of brain networks, was analyzed across eight frequency bands (delta, theta, alpha, beta, low gamma, mid gamma, high gamma, and broadband) in 21 TLE patients and 21 HC. Nine dFC metrics, including state transitions, connectivity strength, network stability, and overall network movement, were derived using amplitude envelope correlations between 68 brain regions mapped to resting-state networks. Results reveal heightened variability in beta band transitions and increased entropy in delta band transitions, indicating unstable and diverse network configurations. TLE patients showed reduced dwell time in visual networks and increased dwell time in the dorsal attention network, suggesting compensatory mechanisms. Reduced connectivity in alpha and beta bands, coupled with increased variability in theta and low gamma bands, highlights widespread network instability. These findings emphasize dFC metrics as potential biomarkers for TLE, offering insights for targeted therapeutic interventions to stabilize brain dynamics. |
| format | Article |
| id | doaj-art-90b8bce4bb68475d9af82d7abd892b11 |
| institution | OA Journals |
| issn | 1534-4320 1558-0210 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| spelling | doaj-art-90b8bce4bb68475d9af82d7abd892b112025-08-20T02:07:46ZengIEEEIEEE Transactions on Neural Systems and Rehabilitation Engineering1534-43201558-02102025-01-01332286229810.1109/TNSRE.2025.357610811021573Resting-State Network Transitions in Temporal Lobe Epilepsy: Insights From MEG-Based Dynamic Functional ConnectivityM. V. Suhas0https://orcid.org/0000-0002-5337-7157Sanjib Sinha1Karunakar Kotegar2https://orcid.org/0000-0002-2458-3891M. Ravindranadh Chowdary3https://orcid.org/0000-0002-5360-257XK. Raghavendra4Ajay Asranna5https://orcid.org/0000-0002-8242-7248L. G. Viswanathan6N. Mariyappa7H. Anitha8https://orcid.org/0000-0001-5898-4442Department of Electronics and Communication Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, IndiaDepartment of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, IndiaDepartment of Data Science and Computer Applications, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, IndiaDepartment of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, IndiaDepartment of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, IndiaDepartment of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, IndiaDepartment of Neurology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, Karnataka, IndiaDepartment of Neurology, MEG Research Centre, NIMHANS, Bengaluru, Karnataka, IndiaDepartment of Computer Science and Engineering, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, Karnataka, IndiaTemporal Lobe Epilepsy (TLE), a common form of focal epilepsy, is associated with recurrent seizures originating in the temporal lobe, often leading to cognitive and psychological impairments. This study explores dynamic functional connectivity (dFC) patterns in TLE patients compared to Healthy Controls (HC) using resting-state Magnetoencephalography (MEG) data. dFC, which captures the temporal variability of brain networks, was analyzed across eight frequency bands (delta, theta, alpha, beta, low gamma, mid gamma, high gamma, and broadband) in 21 TLE patients and 21 HC. Nine dFC metrics, including state transitions, connectivity strength, network stability, and overall network movement, were derived using amplitude envelope correlations between 68 brain regions mapped to resting-state networks. Results reveal heightened variability in beta band transitions and increased entropy in delta band transitions, indicating unstable and diverse network configurations. TLE patients showed reduced dwell time in visual networks and increased dwell time in the dorsal attention network, suggesting compensatory mechanisms. Reduced connectivity in alpha and beta bands, coupled with increased variability in theta and low gamma bands, highlights widespread network instability. These findings emphasize dFC metrics as potential biomarkers for TLE, offering insights for targeted therapeutic interventions to stabilize brain dynamics.https://ieeexplore.ieee.org/document/11021573/Dynamic functional connectivitymagnetoencephalographyresting state networktemporal lobe epilepsy |
| spellingShingle | M. V. Suhas Sanjib Sinha Karunakar Kotegar M. Ravindranadh Chowdary K. Raghavendra Ajay Asranna L. G. Viswanathan N. Mariyappa H. Anitha Resting-State Network Transitions in Temporal Lobe Epilepsy: Insights From MEG-Based Dynamic Functional Connectivity IEEE Transactions on Neural Systems and Rehabilitation Engineering Dynamic functional connectivity magnetoencephalography resting state network temporal lobe epilepsy |
| title | Resting-State Network Transitions in Temporal Lobe Epilepsy: Insights From MEG-Based Dynamic Functional Connectivity |
| title_full | Resting-State Network Transitions in Temporal Lobe Epilepsy: Insights From MEG-Based Dynamic Functional Connectivity |
| title_fullStr | Resting-State Network Transitions in Temporal Lobe Epilepsy: Insights From MEG-Based Dynamic Functional Connectivity |
| title_full_unstemmed | Resting-State Network Transitions in Temporal Lobe Epilepsy: Insights From MEG-Based Dynamic Functional Connectivity |
| title_short | Resting-State Network Transitions in Temporal Lobe Epilepsy: Insights From MEG-Based Dynamic Functional Connectivity |
| title_sort | resting state network transitions in temporal lobe epilepsy insights from meg based dynamic functional connectivity |
| topic | Dynamic functional connectivity magnetoencephalography resting state network temporal lobe epilepsy |
| url | https://ieeexplore.ieee.org/document/11021573/ |
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