Modulate the impact of the drowsiness on the resting state functional connectivity
Abstract This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and m...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2024-04-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-59476-8 |
| _version_ | 1797199521888862208 |
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| author | Marc Joliot Sandrine Cremona Christophe Tzourio Olivier Etard |
| author_facet | Marc Joliot Sandrine Cremona Christophe Tzourio Olivier Etard |
| author_sort | Marc Joliot |
| collection | DOAJ |
| description | Abstract This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution. According to the reference method, drowsy individuals exhibit higher cortico-cortical FC than alert individuals. First, we demonstrated that each method reduced the differences between drowsy and alert states. The second result is that the global signal regression was quantitively the most effective, minimizing significant FC differences to only 3.3% of the total FCs. However, one should consider the risks of overcorrection often associated with this methodology. Therefore, choosing a less aggressive form of regression, such as the physiological method or Gaussian-based approaches, might be a more cautious approach. Third and last, using the Gaussian-based methods, cortico-subcortical and intra-default mode network (DMN) FCs were significantly greater in alert than drowsy subjects. These findings bear resemblance to the anticipated patterns during the onset of sleep, where the cortex isolates itself to assist in transitioning into deeper slow wave sleep phases, simultaneously disconnecting the DMN. |
| first_indexed | 2024-04-24T07:17:05Z |
| format | Article |
| id | doaj.art-17087a53a7694c37af854a9a5ead2c44 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-24T07:17:05Z |
| publishDate | 2024-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-17087a53a7694c37af854a9a5ead2c442024-04-21T11:14:31ZengNature PortfolioScientific Reports2045-23222024-04-0114111510.1038/s41598-024-59476-8Modulate the impact of the drowsiness on the resting state functional connectivityMarc Joliot0Sandrine Cremona1Christophe Tzourio2Olivier Etard3GIN, IMN UMR5293, CEA, CNRS, Université de BordeauxGIN, IMN UMR5293, CEA, CNRS, Université de BordeauxBPH, U1219, INSERM, Université de BordeauxNormandie Université, UNICAEN, INSERM, COMETE U1075, CYCERON, CHU CaenAbstract This research explores different methodologies to modulate the effects of drowsiness on functional connectivity (FC) during resting-state functional magnetic resonance imaging (RS-fMRI). The study utilized a cohort of students (MRi-Share) and classified individuals into drowsy, alert, and mixed/undetermined states based on observed respiratory oscillations. We analyzed the FC group difference between drowsy and alert individuals after five different processing methods: the reference method, two based on physiological and a global signal regression of the BOLD time series signal, and two based on Gaussian standardizations of the FC distribution. According to the reference method, drowsy individuals exhibit higher cortico-cortical FC than alert individuals. First, we demonstrated that each method reduced the differences between drowsy and alert states. The second result is that the global signal regression was quantitively the most effective, minimizing significant FC differences to only 3.3% of the total FCs. However, one should consider the risks of overcorrection often associated with this methodology. Therefore, choosing a less aggressive form of regression, such as the physiological method or Gaussian-based approaches, might be a more cautious approach. Third and last, using the Gaussian-based methods, cortico-subcortical and intra-default mode network (DMN) FCs were significantly greater in alert than drowsy subjects. These findings bear resemblance to the anticipated patterns during the onset of sleep, where the cortex isolates itself to assist in transitioning into deeper slow wave sleep phases, simultaneously disconnecting the DMN.https://doi.org/10.1038/s41598-024-59476-8Resting-statefMRIDrowsinessFunctional connectivity |
| spellingShingle | Marc Joliot Sandrine Cremona Christophe Tzourio Olivier Etard Modulate the impact of the drowsiness on the resting state functional connectivity Scientific Reports Resting-state fMRI Drowsiness Functional connectivity |
| title | Modulate the impact of the drowsiness on the resting state functional connectivity |
| title_full | Modulate the impact of the drowsiness on the resting state functional connectivity |
| title_fullStr | Modulate the impact of the drowsiness on the resting state functional connectivity |
| title_full_unstemmed | Modulate the impact of the drowsiness on the resting state functional connectivity |
| title_short | Modulate the impact of the drowsiness on the resting state functional connectivity |
| title_sort | modulate the impact of the drowsiness on the resting state functional connectivity |
| topic | Resting-state fMRI Drowsiness Functional connectivity |
| url | https://doi.org/10.1038/s41598-024-59476-8 |
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