Complex network analysis of resting state EEG in amnestic mild cognitive impairment patients with type 2 diabetes

Purpose: Diabetes is a great risk factor for dementia and mild cognitive impairment (MCI). This study investigates whether complex network-derived features in resting state EEG (rsEEG) could be applied as a biomarker to distinguish amnestic mild cognitive impairment (aMCI) from normal cognitive func...

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Detalles Bibliográficos
Autores principales: Zeng, Ke, Wang, Yinghua, Ouyang, Gaoxiang, Bian, Zhijie, Wang, Lei, Li, Xiaoli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4624867/
https://www.ncbi.nlm.nih.gov/pubmed/26578946
http://dx.doi.org/10.3389/fncom.2015.00133

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4624867/
https://www.ncbi.nlm.nih.gov/pubmed/26578946
http://dx.doi.org/10.3389/fncom.2015.00133

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