Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders.
Sleep architecture and microstructures alter with aging and sleep disorder-led accelerated aging. We proposed a sleep EEG based brain age prediction model using convolutional neural networks. We then associated the estimated brain age index with brain structural aging features, sleep disorders and v...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-12-01
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| Series: | NeuroImage |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1053811922008746 |
| _version_ | 1811295538123898880 |
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| author | Soonhyun Yook Hea Ree Park Claire Park Gilsoon Park Diane C. Lim Jinyoung Kim Eun Yeon Joo Hosung Kim |
| author_facet | Soonhyun Yook Hea Ree Park Claire Park Gilsoon Park Diane C. Lim Jinyoung Kim Eun Yeon Joo Hosung Kim |
| author_sort | Soonhyun Yook |
| collection | DOAJ |
| description | Sleep architecture and microstructures alter with aging and sleep disorder-led accelerated aging. We proposed a sleep EEG based brain age prediction model using convolutional neural networks. We then associated the estimated brain age index with brain structural aging features, sleep disorders and various sleep parameters. Our model also showed a higher BAI (predicted brain age minus chronological age) is associated with cortical thinning in various functional areas. We found a higher BAI for sleep disorder groups compared to healthy sleepers, as well as significant differences in the spectral pattern of EEG among different sleep disorders (lower power in slow and ϑ waves for sleep apnea vs. higher power in β and σ for insomnia), suggesting sleep disorder-dependent pathomechanisms of aging. Our results demonstrate that the new EEG-BAI can be a biomarker reflecting brain health in normal and various sleep disorder subjects, and may be used to assess treatment efficacy. |
| first_indexed | 2024-04-13T05:35:02Z |
| format | Article |
| id | doaj.art-97b4b4f209774b528f552bcb55f731ba |
| institution | Directory Open Access Journal |
| issn | 1095-9572 |
| language | English |
| last_indexed | 2024-04-13T05:35:02Z |
| publishDate | 2022-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj.art-97b4b4f209774b528f552bcb55f731ba2022-12-22T03:00:19ZengElsevierNeuroImage1095-95722022-12-01264119753Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders.Soonhyun Yook0Hea Ree Park1Claire Park2Gilsoon Park3Diane C. Lim4Jinyoung Kim5Eun Yeon Joo6Hosung Kim7USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal Ave., Los Angeles, CA 90033, USADepartment of Neurology, Inje University College of Medicine, Ilsan Paik Hospital, Goyang 10380, KoreaUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal Ave., Los Angeles, CA 90033, USA; School of Medicine, California University of Science and Medicine, Colton, CA 92324, USAUSC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal Ave., Los Angeles, CA 90033, USADivision of Pulmonary, Critical Care, Sleep, University of Miami, Miami, FL 33125, USASchool of Nursing, University of Nevada, Las Vegas, NV 89154, USADepartment of Neurology, Neuroscience Center, Samsung Medical Center, Samsung Biomedical Research Institute, School of Medicine, Sungkyunkwan University, Seoul 06351, Korea; Corresponding authors.USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, 2025 Zonal Ave., Los Angeles, CA 90033, USA; Corresponding authors.Sleep architecture and microstructures alter with aging and sleep disorder-led accelerated aging. We proposed a sleep EEG based brain age prediction model using convolutional neural networks. We then associated the estimated brain age index with brain structural aging features, sleep disorders and various sleep parameters. Our model also showed a higher BAI (predicted brain age minus chronological age) is associated with cortical thinning in various functional areas. We found a higher BAI for sleep disorder groups compared to healthy sleepers, as well as significant differences in the spectral pattern of EEG among different sleep disorders (lower power in slow and ϑ waves for sleep apnea vs. higher power in β and σ for insomnia), suggesting sleep disorder-dependent pathomechanisms of aging. Our results demonstrate that the new EEG-BAI can be a biomarker reflecting brain health in normal and various sleep disorder subjects, and may be used to assess treatment efficacy.http://www.sciencedirect.com/science/article/pii/S1053811922008746Sleep EEGBrain ageNeuroelectrophysiologySleep disorderBiomarkerDeep learning |
| spellingShingle | Soonhyun Yook Hea Ree Park Claire Park Gilsoon Park Diane C. Lim Jinyoung Kim Eun Yeon Joo Hosung Kim Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders. NeuroImage Sleep EEG Brain age Neuroelectrophysiology Sleep disorder Biomarker Deep learning |
| title | Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders. |
| title_full | Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders. |
| title_fullStr | Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders. |
| title_full_unstemmed | Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders. |
| title_short | Novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders. |
| title_sort | novel neuroelectrophysiological age index associated with imaging features of brain aging and sleep disorders |
| topic | Sleep EEG Brain age Neuroelectrophysiology Sleep disorder Biomarker Deep learning |
| url | http://www.sciencedirect.com/science/article/pii/S1053811922008746 |
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