Network-motif delay differential analysis of brain activity during seizures
© 2023 Author(s). Published under an exclusive license by AIP Publishing..
Delay Differential Analysis (DDA) is a nonlinear method for analyzing time series based on principles from nonlinear dynamical systems. DDA is extended here to incorporate network aspects to improve the dynamical characterization of complex systems. To demonstrate its effectiveness, DDA with network capabilities was first applied to the well-known Rössler system under different parameter regimes and noise conditions. Network-motif DDA, based on cortical regions, was then applied to invasive intracranial electroencephalographic data from drug-resistant epilepsy patients undergoing presurgical monitoring. The directional network motifs between brain areas that emerge from this analysis change dramatically before, during, and after seizures. Neural systems provide a rich source of complex data, arising from varying internal states generated by network interactions.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:33 |
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| Enthalten in: |
Chaos (Woodbury, N.Y.) - 33(2023), 12 vom: 01. Dez. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Lainscsek, Claudia [VerfasserIn] |
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| Links: |
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| Themen: |
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| Anmerkungen: |
Date Completed 03.01.2024 Date Revised 10.02.2024 published: Print Citation Status MEDLINE |
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| doi: |
10.1063/5.0165904 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM366476335 |
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| 520 | |a © 2023 Author(s). Published under an exclusive license by AIP Publishing. | ||
| 520 | |a Delay Differential Analysis (DDA) is a nonlinear method for analyzing time series based on principles from nonlinear dynamical systems. DDA is extended here to incorporate network aspects to improve the dynamical characterization of complex systems. To demonstrate its effectiveness, DDA with network capabilities was first applied to the well-known Rössler system under different parameter regimes and noise conditions. Network-motif DDA, based on cortical regions, was then applied to invasive intracranial electroencephalographic data from drug-resistant epilepsy patients undergoing presurgical monitoring. The directional network motifs between brain areas that emerge from this analysis change dramatically before, during, and after seizures. Neural systems provide a rich source of complex data, arising from varying internal states generated by network interactions | ||
| 650 | 4 | |a Journal Article | |
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| 700 | 1 | |a Mendes, Eduardo M A M |e verfasserin |4 aut | |
| 700 | 1 | |a Fan, Miaolin |e verfasserin |4 aut | |
| 700 | 1 | |a Cash, Sydney S |e verfasserin |4 aut | |
| 700 | 1 | |a Sejnowski, Terrence J |e verfasserin |4 aut | |
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