The impact of paediatric epilepsy and co-occurring neurodevelopmental disorders on functional brain networks in wake and sleep
Epilepsy is one of the most common neurological disorders in children. Diagnosing epilepsy in children can be very challenging, especially as it often coexists with neurodevelopmental conditions like autism and ADHD. Functional brain networks obtained from neuroimaging and electrophysiological data...
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| Veröffentlicht in: | PloS one 2024-08, Vol.19 (8), p.e0309243 |
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| creator | Junges, Leandro Galvis, Daniel Winsor, Alice Treadwell, Grace Richards, Caroline Seri, Stefano Johnson, Samuel Terry, John R Bagshaw, Andrew P |
| description | Epilepsy is one of the most common neurological disorders in children. Diagnosing epilepsy in children can be very challenging, especially as it often coexists with neurodevelopmental conditions like autism and ADHD. Functional brain networks obtained from neuroimaging and electrophysiological data in wakefulness and sleep have been shown to contain signatures of neurological disorders, and can potentially support the diagnosis and management of co-occurring neurodevelopmental conditions. In this work, we use electroencephalography (EEG) recordings from children, in restful wakefulness and sleep, to extract functional connectivity networks in different frequency bands. We explore the relationship of these networks with epilepsy diagnosis and with measures of neurodevelopmental traits, obtained from questionnaires used as screening tools for autism and ADHD. We explore differences in network markers between children with and without epilepsy in wake and sleep, and quantify the correlation between such markers and measures of neurodevelopmental traits. Our findings highlight the importance of considering the interplay between epilepsy and neurodevelopmental traits when exploring network markers of epilepsy. |
| doi_str_mv | 10.1371/journal.pone.0309243 |
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Diagnosing epilepsy in children can be very challenging, especially as it often coexists with neurodevelopmental conditions like autism and ADHD. Functional brain networks obtained from neuroimaging and electrophysiological data in wakefulness and sleep have been shown to contain signatures of neurological disorders, and can potentially support the diagnosis and management of co-occurring neurodevelopmental conditions. In this work, we use electroencephalography (EEG) recordings from children, in restful wakefulness and sleep, to extract functional connectivity networks in different frequency bands. We explore the relationship of these networks with epilepsy diagnosis and with measures of neurodevelopmental traits, obtained from questionnaires used as screening tools for autism and ADHD. We explore differences in network markers between children with and without epilepsy in wake and sleep, and quantify the correlation between such markers and measures of neurodevelopmental traits. Our findings highlight the importance of considering the interplay between epilepsy and neurodevelopmental traits when exploring network markers of epilepsy.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0309243</identifier><identifier>PMID: 39186749</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adolescent ; Analysis ; Attention Deficit Disorder with Hyperactivity - physiopathology ; Attention deficit hyperactivity disorder ; Autism ; Biology and Life Sciences ; Brain ; Brain - diagnostic imaging ; Brain - physiopathology ; Care and treatment ; Child ; Child development deviations ; Child, Preschool ; Children ; Complications and side effects ; Computer and Information Sciences ; Convulsions & seizures ; Developmental disabilities ; Diagnosis ; EEG ; Electroencephalography ; Epilepsy ; Epilepsy - physiopathology ; Epilepsy in children ; Families & family life ; Female ; Fourier transforms ; Frequencies ; Humans ; Male ; Medical imaging ; Medicine and Health Sciences ; Metadata ; Nerve Net - physiopathology ; Networks ; Neural networks ; Neurodevelopmental disorders ; Neurodevelopmental Disorders - physiopathology ; Neuroimaging ; Neurological diseases ; Pediatrics ; Quality of life ; Questionnaires ; Research and Analysis Methods ; Risk factors ; Sleep ; Sleep - physiology ; Sleep and wakefulness ; Sleep deprivation ; Social Sciences ; Wakefulness ; Wakefulness - physiology</subject><ispartof>PloS one, 2024-08, Vol.19 (8), p.e0309243</ispartof><rights>Copyright: © 2024 Junges et al. 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 author and source are credited.</rights><rights>COPYRIGHT 2024 Public Library of Science</rights><rights>2024 Junges et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2024 Junges et al 2024 Junges et al</rights><rights>2024 Junges et al. 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Diagnosing epilepsy in children can be very challenging, especially as it often coexists with neurodevelopmental conditions like autism and ADHD. Functional brain networks obtained from neuroimaging and electrophysiological data in wakefulness and sleep have been shown to contain signatures of neurological disorders, and can potentially support the diagnosis and management of co-occurring neurodevelopmental conditions. In this work, we use electroencephalography (EEG) recordings from children, in restful wakefulness and sleep, to extract functional connectivity networks in different frequency bands. We explore the relationship of these networks with epilepsy diagnosis and with measures of neurodevelopmental traits, obtained from questionnaires used as screening tools for autism and ADHD. We explore differences in network markers between children with and without epilepsy in wake and sleep, and quantify the correlation between such markers and measures of neurodevelopmental traits. 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| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2024-08, Vol.19 (8), p.e0309243 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_3097454792 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Public Library of Science (PLoS); PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adolescent Analysis Attention Deficit Disorder with Hyperactivity - physiopathology Attention deficit hyperactivity disorder Autism Biology and Life Sciences Brain Brain - diagnostic imaging Brain - physiopathology Care and treatment Child Child development deviations Child, Preschool Children Complications and side effects Computer and Information Sciences Convulsions & seizures Developmental disabilities Diagnosis EEG Electroencephalography Epilepsy Epilepsy - physiopathology Epilepsy in children Families & family life Female Fourier transforms Frequencies Humans Male Medical imaging Medicine and Health Sciences Metadata Nerve Net - physiopathology Networks Neural networks Neurodevelopmental disorders Neurodevelopmental Disorders - physiopathology Neuroimaging Neurological diseases Pediatrics Quality of life Questionnaires Research and Analysis Methods Risk factors Sleep Sleep - physiology Sleep and wakefulness Sleep deprivation Social Sciences Wakefulness Wakefulness - physiology |
| title | The impact of paediatric epilepsy and co-occurring neurodevelopmental disorders on functional brain networks in wake and sleep |
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