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Unveiling convergent and divergent intrinsic brain network alternations in depressed adolescents engaged in non-suicidal self-injurious behaviors with and without suicide attempts.

Li, L ; Liang, Z ; et al.
In: CNS neuroscience & therapeutics, Jg. 30 (2024-05-01), Heft 5, S. e14684
Online academicJournal

Titel:
Unveiling convergent and divergent intrinsic brain network alternations in depressed adolescents engaged in non-suicidal self-injurious behaviors with and without suicide attempts.
Autor/in / Beteiligte Person: Li, L ; Liang, Z ; Li, G ; Xu, H ; Yang, X ; Liu, X ; Zhang, X ; Wang, J ; Zhang, Z ; Zhou, Y
Link:
Zeitschrift: CNS neuroscience & therapeutics, Jg. 30 (2024-05-01), Heft 5, S. e14684
Veröffentlichung: Oxford, UK : Wiley-Blackwell, c2008-, 2024
Medientyp: academicJournal
ISSN: 1755-5949 (electronic)
DOI: 10.1111/cns.14684
Schlagwort:
  • Humans
  • Adolescent
  • Male
  • Female
  • Nerve Net diagnostic imaging
  • Nerve Net physiopathology
  • Depression psychology
  • Depression physiopathology
  • Depression diagnostic imaging
  • Neural Pathways physiopathology
  • Neural Pathways diagnostic imaging
  • Child
  • Self-Injurious Behavior psychology
  • Suicide, Attempted psychology
  • Magnetic Resonance Imaging
  • Brain diagnostic imaging
  • Brain physiopathology
Sonstiges:
  • Nachgewiesen in: MEDLINE
  • Sprachen: English
  • Publication Type: Journal Article; Research Support, Non-U.S. Gov't
  • Language: English
  • [CNS Neurosci Ther] 2024 May; Vol. 30 (5), pp. e14684.
  • MeSH Terms: Self-Injurious Behavior* / psychology ; Suicide, Attempted* / psychology ; Magnetic Resonance Imaging* ; Brain* / diagnostic imaging ; Brain* / physiopathology ; Humans ; Adolescent ; Male ; Female ; Nerve Net / diagnostic imaging ; Nerve Net / physiopathology ; Depression / psychology ; Depression / physiopathology ; Depression / diagnostic imaging ; Neural Pathways / physiopathology ; Neural Pathways / diagnostic imaging ; Child
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  • Grant Information: 2023A1515010840 Natural Science Foundation of Guangdong Province; 62276169 National Natural Science Foundation of China; 82272114 National Natural Science Foundation of China; 2022SHIBS0003 Shenzhen Science and Technology Program; RKX20220705152815035 Shenzhen Science and Technology Program; KCXFZ20201221173613036 Shenzhen Science and Technology Program; SZSM202011014 Shenzhen Science and Technology Program; SZGSP013 Shenzhen Science and Technology Program; the Medical-Engineering Interdisciplinary Research Foundation of Shenzhen University; the Shenzhen University-Lingnan University Joint Research Programme
  • Contributed Indexing: Keywords: adolescence; depression; machine learning; non‐suicidal self‐injury; resting‐state functional connectivity; suicidal attempt
  • Entry Date(s): Date Created: 20240513 Date Completed: 20240513 Latest Revision: 20240515
  • Update Code: 20240515
  • PubMed Central ID: PMC11090151

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