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Network dynamics in the healthy and epileptic developing brain
Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarized along different dimensions using network-level quantitative measures, such as channel-to-channel correlation, or band power distributions across channels. These reveal net...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MIT Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5989999/ https://www.ncbi.nlm.nih.gov/pubmed/29911676 http://dx.doi.org/10.1162/NETN_a_00026 |
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author | Rosch, Richard Baldeweg, Torsten Moeller, Friederike Baier, Gerold |
author_facet | Rosch, Richard Baldeweg, Torsten Moeller, Friederike Baier, Gerold |
author_sort | Rosch, Richard |
collection | PubMed |
description | Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarized along different dimensions using network-level quantitative measures, such as channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different timescales and can be tracked dynamically. Here we describe the dynamics of network state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n = 8, age: 1–8 months). We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity. We further show that EEGs from different patient groups and controls may be distinguishable on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups. These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in the future inform the clinical use of quantitative EEG for diagnosis. |
format | Online Article Text |
id | pubmed-5989999 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MIT Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-59899992018-06-15 Network dynamics in the healthy and epileptic developing brain Rosch, Richard Baldeweg, Torsten Moeller, Friederike Baier, Gerold Netw Neurosci Methods Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. EEG recordings can be summarized along different dimensions using network-level quantitative measures, such as channel-to-channel correlation, or band power distributions across channels. These reveal network patterns that unfold over a range of different timescales and can be tracked dynamically. Here we describe the dynamics of network state transitions in EEG recordings of spontaneous brain activity in normally developing infants and infants with severe early infantile epileptic encephalopathies (n = 8, age: 1–8 months). We describe differences in measures of EEG dynamics derived from band power, and correlation-based summaries of network-wide brain activity. We further show that EEGs from different patient groups and controls may be distinguishable on a small set of the novel quantitative measures introduced here, which describe dynamic network state switching. Quantitative measures related to the sharpness of switching from one correlation pattern to another show the largest differences between groups. These findings reveal that the early epileptic encephalopathies are associated with characteristic dynamic features at the network level. Quantitative network-based analyses like the one presented here may in the future inform the clinical use of quantitative EEG for diagnosis. MIT Press 2018-03-01 /pmc/articles/PMC5989999/ /pubmed/29911676 http://dx.doi.org/10.1162/NETN_a_00026 Text en © 2017 Massachusetts Institute of Technology http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Rosch, Richard Baldeweg, Torsten Moeller, Friederike Baier, Gerold Network dynamics in the healthy and epileptic developing brain |
title | Network dynamics in the healthy and epileptic developing brain |
title_full | Network dynamics in the healthy and epileptic developing brain |
title_fullStr | Network dynamics in the healthy and epileptic developing brain |
title_full_unstemmed | Network dynamics in the healthy and epileptic developing brain |
title_short | Network dynamics in the healthy and epileptic developing brain |
title_sort | network dynamics in the healthy and epileptic developing brain |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5989999/ https://www.ncbi.nlm.nih.gov/pubmed/29911676 http://dx.doi.org/10.1162/NETN_a_00026 |
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