Neural correlates of device-based sleep characteristics in adolescents
Summary: Understanding the brain mechanisms underlying adolescent sleep patterns and their impact on psychophysiological development is complex. We applied sparse canonical correlation analysis (sCCA) to data from 3,222 adolescents in the Adolescent Brain Cognitive Development (ABCD) study, integrat...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
|
| Series: | Cell Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211124725003365 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850149605135613952 |
|---|---|
| author | Qing Ma Barbara J. Sahakian Bei Zhang Zeyu Li Jin-Tai Yu Fei Li Jianfeng Feng Wei Cheng |
| author_facet | Qing Ma Barbara J. Sahakian Bei Zhang Zeyu Li Jin-Tai Yu Fei Li Jianfeng Feng Wei Cheng |
| author_sort | Qing Ma |
| collection | DOAJ |
| description | Summary: Understanding the brain mechanisms underlying adolescent sleep patterns and their impact on psychophysiological development is complex. We applied sparse canonical correlation analysis (sCCA) to data from 3,222 adolescents in the Adolescent Brain Cognitive Development (ABCD) study, integrating sleep characteristics with multimodal imaging. This reveals two key sleep-brain dimensions: one linking later sleep onset and shorter duration to decreased subcortical-cortical connectivity and another associating a higher heart rate and shorter light sleep with lower brain volumes and connectivity. Hierarchical clustering identifies three biotypes: biotype 1 has delayed, shorter sleep with a higher heart rate; biotype 3 has earlier, longer sleep with a lower heart rate; and biotype 2 is intermediate. These biotypes also differ in cognitive performance and brain structure and function. Longitudinal analysis confirms these differences from ages 9 to 14, with biotype 3 showing consistent cognitive advantages. Our findings offer insights into optimizing sleep routines for better cognitive development. |
| format | Article |
| id | doaj-art-56639617d6dc4c829905a9fc6c9ca46b |
| institution | OA Journals |
| issn | 2211-1247 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cell Reports |
| spelling | doaj-art-56639617d6dc4c829905a9fc6c9ca46b2025-08-20T02:26:51ZengElsevierCell Reports2211-12472025-05-0144511556510.1016/j.celrep.2025.115565Neural correlates of device-based sleep characteristics in adolescentsQing Ma0Barbara J. Sahakian1Bei Zhang2Zeyu Li3Jin-Tai Yu4Fei Li5Jianfeng Feng6Wei Cheng7Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Institute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, ChinaInstitute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Department of Psychiatry, University of Cambridge, Cambridge, UKInstitute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, ChinaInstitute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, ChinaKey Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, ChinaDepartment of Developmental and Behavioral Pediatric & Child Primary Care/MOE-Shanghai Key Laboratory of Children’s Environmental Health, Xin Hua Hospital Affiliated with Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaInstitute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China; Department of Computer Science, University of Warwick, Coventry, UK; Zhangjiang Fudan International Innovation Center, Shanghai, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Zhejiang, ChinaInstitute of Science and Technology for Brain-Inspired Intelligence, Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Zhejiang, China; Corresponding authorSummary: Understanding the brain mechanisms underlying adolescent sleep patterns and their impact on psychophysiological development is complex. We applied sparse canonical correlation analysis (sCCA) to data from 3,222 adolescents in the Adolescent Brain Cognitive Development (ABCD) study, integrating sleep characteristics with multimodal imaging. This reveals two key sleep-brain dimensions: one linking later sleep onset and shorter duration to decreased subcortical-cortical connectivity and another associating a higher heart rate and shorter light sleep with lower brain volumes and connectivity. Hierarchical clustering identifies three biotypes: biotype 1 has delayed, shorter sleep with a higher heart rate; biotype 3 has earlier, longer sleep with a lower heart rate; and biotype 2 is intermediate. These biotypes also differ in cognitive performance and brain structure and function. Longitudinal analysis confirms these differences from ages 9 to 14, with biotype 3 showing consistent cognitive advantages. Our findings offer insights into optimizing sleep routines for better cognitive development.http://www.sciencedirect.com/science/article/pii/S2211124725003365CP: Neuroscience |
| spellingShingle | Qing Ma Barbara J. Sahakian Bei Zhang Zeyu Li Jin-Tai Yu Fei Li Jianfeng Feng Wei Cheng Neural correlates of device-based sleep characteristics in adolescents Cell Reports CP: Neuroscience |
| title | Neural correlates of device-based sleep characteristics in adolescents |
| title_full | Neural correlates of device-based sleep characteristics in adolescents |
| title_fullStr | Neural correlates of device-based sleep characteristics in adolescents |
| title_full_unstemmed | Neural correlates of device-based sleep characteristics in adolescents |
| title_short | Neural correlates of device-based sleep characteristics in adolescents |
| title_sort | neural correlates of device based sleep characteristics in adolescents |
| topic | CP: Neuroscience |
| url | http://www.sciencedirect.com/science/article/pii/S2211124725003365 |
| work_keys_str_mv | AT qingma neuralcorrelatesofdevicebasedsleepcharacteristicsinadolescents AT barbarajsahakian neuralcorrelatesofdevicebasedsleepcharacteristicsinadolescents AT beizhang neuralcorrelatesofdevicebasedsleepcharacteristicsinadolescents AT zeyuli neuralcorrelatesofdevicebasedsleepcharacteristicsinadolescents AT jintaiyu neuralcorrelatesofdevicebasedsleepcharacteristicsinadolescents AT feili neuralcorrelatesofdevicebasedsleepcharacteristicsinadolescents AT jianfengfeng neuralcorrelatesofdevicebasedsleepcharacteristicsinadolescents AT weicheng neuralcorrelatesofdevicebasedsleepcharacteristicsinadolescents |