State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses

BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Eva M. M. Strijbis [verfasserIn] Yannick S. S. Timar [verfasserIn] Deborah N. Schoonhoven [verfasserIn] Ilse M. Nauta [verfasserIn] Shanna D. Kulik [verfasserIn] Lodewijk R. J. de Ruiter [verfasserIn] Menno M. Schoonheim [verfasserIn] Arjan Hillebrand [verfasserIn] Cornelis J. Stam [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	magnetoencephalography (MEG) EEG graph connectivity analysis spectral power analysis drowsiness

Übergeordnetes Werk:	In: Frontiers in Neuroscience - Frontiers Media S.A., 2008, 16(2022)
Übergeordnetes Werk:	volume:16 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fnins.2022.782474

Katalog-ID:	DOAJ043466567

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520			\|a BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance.
650		4	\|a magnetoencephalography (MEG)
650		4	\|a EEG
650		4	\|a graph connectivity analysis
650		4	\|a spectral power analysis
650		4	\|a drowsiness
653		0	\|a Neurosciences. Biological psychiatry. Neuropsychiatry
700	0		\|a Eva M. M. Strijbis \|e verfasserin \|4 aut
700	0		\|a Yannick S. S. Timar \|e verfasserin \|4 aut
700	0		\|a Deborah N. Schoonhoven \|e verfasserin \|4 aut
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allfields	10.3389/fnins.2022.782474 doi (DE-627)DOAJ043466567 (DE-599)DOAJc54bb9b4b35b4fa9b6e3cf3843883ccf DE-627 ger DE-627 rakwb eng RC321-571 Eva M. M. Strijbis verfasserin aut State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance. magnetoencephalography (MEG) EEG graph connectivity analysis spectral power analysis drowsiness Neurosciences. Biological psychiatry. Neuropsychiatry Eva M. M. Strijbis verfasserin aut Yannick S. S. Timar verfasserin aut Deborah N. Schoonhoven verfasserin aut Deborah N. Schoonhoven verfasserin aut Ilse M. Nauta verfasserin aut Shanna D. Kulik verfasserin aut Lodewijk R. J. de Ruiter verfasserin aut Menno M. Schoonheim verfasserin aut Arjan Hillebrand verfasserin aut Arjan Hillebrand verfasserin aut Cornelis J. Stam verfasserin aut Cornelis J. Stam verfasserin aut In Frontiers in Neuroscience Frontiers Media S.A., 2008 16(2022) (DE-627)55908109X (DE-600)2411902-7 1662453X nnns volume:16 year:2022 https://doi.org/10.3389/fnins.2022.782474 kostenfrei https://doaj.org/article/c54bb9b4b35b4fa9b6e3cf3843883ccf kostenfrei https://www.frontiersin.org/articles/10.3389/fnins.2022.782474/full kostenfrei https://doaj.org/toc/1662-453X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022
spelling	10.3389/fnins.2022.782474 doi (DE-627)DOAJ043466567 (DE-599)DOAJc54bb9b4b35b4fa9b6e3cf3843883ccf DE-627 ger DE-627 rakwb eng RC321-571 Eva M. M. Strijbis verfasserin aut State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance. magnetoencephalography (MEG) EEG graph connectivity analysis spectral power analysis drowsiness Neurosciences. Biological psychiatry. Neuropsychiatry Eva M. M. Strijbis verfasserin aut Yannick S. S. Timar verfasserin aut Deborah N. Schoonhoven verfasserin aut Deborah N. Schoonhoven verfasserin aut Ilse M. Nauta verfasserin aut Shanna D. Kulik verfasserin aut Lodewijk R. J. de Ruiter verfasserin aut Menno M. Schoonheim verfasserin aut Arjan Hillebrand verfasserin aut Arjan Hillebrand verfasserin aut Cornelis J. Stam verfasserin aut Cornelis J. Stam verfasserin aut In Frontiers in Neuroscience Frontiers Media S.A., 2008 16(2022) (DE-627)55908109X (DE-600)2411902-7 1662453X nnns volume:16 year:2022 https://doi.org/10.3389/fnins.2022.782474 kostenfrei https://doaj.org/article/c54bb9b4b35b4fa9b6e3cf3843883ccf kostenfrei https://www.frontiersin.org/articles/10.3389/fnins.2022.782474/full kostenfrei https://doaj.org/toc/1662-453X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022
allfields_unstemmed	10.3389/fnins.2022.782474 doi (DE-627)DOAJ043466567 (DE-599)DOAJc54bb9b4b35b4fa9b6e3cf3843883ccf DE-627 ger DE-627 rakwb eng RC321-571 Eva M. M. Strijbis verfasserin aut State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance. magnetoencephalography (MEG) EEG graph connectivity analysis spectral power analysis drowsiness Neurosciences. Biological psychiatry. Neuropsychiatry Eva M. M. Strijbis verfasserin aut Yannick S. S. Timar verfasserin aut Deborah N. Schoonhoven verfasserin aut Deborah N. Schoonhoven verfasserin aut Ilse M. Nauta verfasserin aut Shanna D. Kulik verfasserin aut Lodewijk R. J. de Ruiter verfasserin aut Menno M. Schoonheim verfasserin aut Arjan Hillebrand verfasserin aut Arjan Hillebrand verfasserin aut Cornelis J. Stam verfasserin aut Cornelis J. Stam verfasserin aut In Frontiers in Neuroscience Frontiers Media S.A., 2008 16(2022) (DE-627)55908109X (DE-600)2411902-7 1662453X nnns volume:16 year:2022 https://doi.org/10.3389/fnins.2022.782474 kostenfrei https://doaj.org/article/c54bb9b4b35b4fa9b6e3cf3843883ccf kostenfrei https://www.frontiersin.org/articles/10.3389/fnins.2022.782474/full kostenfrei https://doaj.org/toc/1662-453X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022
allfieldsGer	10.3389/fnins.2022.782474 doi (DE-627)DOAJ043466567 (DE-599)DOAJc54bb9b4b35b4fa9b6e3cf3843883ccf DE-627 ger DE-627 rakwb eng RC321-571 Eva M. M. Strijbis verfasserin aut State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance. magnetoencephalography (MEG) EEG graph connectivity analysis spectral power analysis drowsiness Neurosciences. Biological psychiatry. Neuropsychiatry Eva M. M. Strijbis verfasserin aut Yannick S. S. Timar verfasserin aut Deborah N. Schoonhoven verfasserin aut Deborah N. Schoonhoven verfasserin aut Ilse M. Nauta verfasserin aut Shanna D. Kulik verfasserin aut Lodewijk R. J. de Ruiter verfasserin aut Menno M. Schoonheim verfasserin aut Arjan Hillebrand verfasserin aut Arjan Hillebrand verfasserin aut Cornelis J. Stam verfasserin aut Cornelis J. Stam verfasserin aut In Frontiers in Neuroscience Frontiers Media S.A., 2008 16(2022) (DE-627)55908109X (DE-600)2411902-7 1662453X nnns volume:16 year:2022 https://doi.org/10.3389/fnins.2022.782474 kostenfrei https://doaj.org/article/c54bb9b4b35b4fa9b6e3cf3843883ccf kostenfrei https://www.frontiersin.org/articles/10.3389/fnins.2022.782474/full kostenfrei https://doaj.org/toc/1662-453X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022
allfieldsSound	10.3389/fnins.2022.782474 doi (DE-627)DOAJ043466567 (DE-599)DOAJc54bb9b4b35b4fa9b6e3cf3843883ccf DE-627 ger DE-627 rakwb eng RC321-571 Eva M. M. Strijbis verfasserin aut State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance. magnetoencephalography (MEG) EEG graph connectivity analysis spectral power analysis drowsiness Neurosciences. Biological psychiatry. Neuropsychiatry Eva M. M. Strijbis verfasserin aut Yannick S. S. Timar verfasserin aut Deborah N. Schoonhoven verfasserin aut Deborah N. Schoonhoven verfasserin aut Ilse M. Nauta verfasserin aut Shanna D. Kulik verfasserin aut Lodewijk R. J. de Ruiter verfasserin aut Menno M. Schoonheim verfasserin aut Arjan Hillebrand verfasserin aut Arjan Hillebrand verfasserin aut Cornelis J. Stam verfasserin aut Cornelis J. Stam verfasserin aut In Frontiers in Neuroscience Frontiers Media S.A., 2008 16(2022) (DE-627)55908109X (DE-600)2411902-7 1662453X nnns volume:16 year:2022 https://doi.org/10.3389/fnins.2022.782474 kostenfrei https://doaj.org/article/c54bb9b4b35b4fa9b6e3cf3843883ccf kostenfrei https://www.frontiersin.org/articles/10.3389/fnins.2022.782474/full kostenfrei https://doaj.org/toc/1662-453X Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022
language	English
source	In Frontiers in Neuroscience 16(2022) volume:16 year:2022
sourceStr	In Frontiers in Neuroscience 16(2022) volume:16 year:2022
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	magnetoencephalography (MEG) EEG graph connectivity analysis spectral power analysis drowsiness Neurosciences. Biological psychiatry. Neuropsychiatry
isfreeaccess_bool	true
container_title	Frontiers in Neuroscience
authorswithroles_txt_mv	Eva M. M. Strijbis @@aut@@ Yannick S. S. Timar @@aut@@ Deborah N. Schoonhoven @@aut@@ Ilse M. Nauta @@aut@@ Shanna D. Kulik @@aut@@ Lodewijk R. J. de Ruiter @@aut@@ Menno M. Schoonheim @@aut@@ Arjan Hillebrand @@aut@@ Cornelis J. Stam @@aut@@
publishDateDaySort_date	2022-01-01T00:00:00Z
hierarchy_top_id	55908109X
id	DOAJ043466567
language_de	englisch
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Strijbis</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2022</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">Computermedien</subfield><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Online-Ressource</subfield><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in &gt;55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetoencephalography (MEG)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">EEG</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">graph connectivity analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">spectral power analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">drowsiness</subfield></datafield><datafield tag="653" ind1=" " ind2="0"><subfield code="a">Neurosciences. Biological psychiatry. 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callnumber-first	R - Medicine
author	Eva M. M. Strijbis
spellingShingle	Eva M. M. Strijbis misc RC321-571 misc magnetoencephalography (MEG) misc EEG misc graph connectivity analysis misc spectral power analysis misc drowsiness misc Neurosciences. Biological psychiatry. Neuropsychiatry State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses
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topic_title	RC321-571 State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses magnetoencephalography (MEG) EEG graph connectivity analysis spectral power analysis drowsiness
topic	misc RC321-571 misc magnetoencephalography (MEG) misc EEG misc graph connectivity analysis misc spectral power analysis misc drowsiness misc Neurosciences. Biological psychiatry. Neuropsychiatry
topic_unstemmed	misc RC321-571 misc magnetoencephalography (MEG) misc EEG misc graph connectivity analysis misc spectral power analysis misc drowsiness misc Neurosciences. Biological psychiatry. Neuropsychiatry
topic_browse	misc RC321-571 misc magnetoencephalography (MEG) misc EEG misc graph connectivity analysis misc spectral power analysis misc drowsiness misc Neurosciences. Biological psychiatry. Neuropsychiatry
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title	State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses
ctrlnum	(DE-627)DOAJ043466567 (DE-599)DOAJc54bb9b4b35b4fa9b6e3cf3843883ccf
title_full	State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses
author_sort	Eva M. M. Strijbis
journal	Frontiers in Neuroscience
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author_browse	Eva M. M. Strijbis Yannick S. S. Timar Deborah N. Schoonhoven Ilse M. Nauta Shanna D. Kulik Lodewijk R. J. de Ruiter Menno M. Schoonheim Arjan Hillebrand Cornelis J. Stam
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author-letter	Eva M. M. Strijbis
doi_str_mv	10.3389/fnins.2022.782474
author2-role	verfasserin
title_sort	state changes during resting-state (magneto)encephalographic studies: the effect of drowsiness on spectral, connectivity, and network analyses
callnumber	RC321-571
title_auth	State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses
abstract	BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance.
abstractGer	BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance.
abstract_unstemmed	BackgroundA common problem in resting-state neuroimaging studies is that subjects become drowsy or fall asleep. Although this could drastically affect neurophysiological measurements, such as magnetoencephalography (MEG), its specific impact remains understudied. We aimed to systematically investigate how often drowsiness is present during resting-state MEG recordings, and how the state changes alter quantitative estimates of oscillatory activity, functional connectivity, and network topology.MethodsAbout 8-min MEG recordings of 19 healthy subjects, split into ~13-s epochs, were scored for the presence of eyes-open (EO), alert eyes-closed (A-EC), or drowsy eyes-closed (D-EC) states. After projection to source-space, results of spectral, functional connectivity, and network analyses in 6 canonical frequency bands were compared between these states on a global and regional levels. Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in >55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. These findings are important for interpreting the results of EEG/MEG studies using spectral analyses in neurological disease, where recordings should be evaluated for the presence of drowsiness. For connectivity analyses or studies on network topology, this seems of far less importance.
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title_short	State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses
url	https://doi.org/10.3389/fnins.2022.782474 https://doaj.org/article/c54bb9b4b35b4fa9b6e3cf3843883ccf https://www.frontiersin.org/articles/10.3389/fnins.2022.782474/full https://doaj.org/toc/1662-453X
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author2	Eva M. M. Strijbis Yannick S. S. Timar Deborah N. Schoonhoven Ilse M. Nauta Shanna D. Kulik Lodewijk R. J. de Ruiter Menno M. Schoonheim Arjan Hillebrand Cornelis J. Stam
author2Str	Eva M. M. Strijbis Yannick S. S. Timar Deborah N. Schoonhoven Ilse M. Nauta Shanna D. Kulik Lodewijk R. J. de Ruiter Menno M. Schoonheim Arjan Hillebrand Cornelis J. Stam
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up_date	2024-07-03T17:43:20.299Z
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Functional connectivity was analyzed using the phase lag index (PLI) and corrected amplitude envelope correlation (AECc), and network topology was analyzed using the minimum spanning tree (MST).ResultsDrowsiness was present in &gt;55% of all epochs that did not fulfill the AASM criteria for sleep. There were clear differences in spectral results between the states (A-EC vs. D-EC) and conditions (EO vs. A-EC). The influence of state and condition was far less pronounced for connectivity analyses, with only minimal differences between D-EC and EO in the AECc in the delta band. There were no effects of drowsiness on any of the MST measures.ConclusionsDrowsiness during eyes-closed resting-state MEG recordings is present in the majority of epochs, despite the instructions to stay awake. This has considerable influence on spectral properties, but much less so on functional connectivity and network topology. 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State Changes During Resting-State (Magneto)encephalographic Studies: The Effect of Drowsiness on Spectral, Connectivity, and Network Analyses

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