Network change point detection in resting-state functional connectivity dynamics of mild cognitive impairment patients.

Autor:	Mancho-Fora N; Facultat de Psicologia, Universitat de Barcelona, Spain., Montalà-Flaquer M; Facultat de Psicologia, Universitat de Barcelona, Spain.; UB Institute of Complex Systems, Universitat de Barcelona, Spain., Farràs-Permanyer L; Facultat de Psicologia, Universitat de Barcelona, Spain., Zarabozo-Hurtado D; Grupo Radiológico Rio. Guadalajara, Mexico., Gallardo-Moreno GB; Instituto de Neurociencias, Universidad de Guadalajara, Mexico., Gudayol-Farré E; Facultad de Psicología, Universidad Miochoacana San Nicolás de Hidalgo, Morelia, Mexico., Peró-Cebollero M; Facultat de Psicologia, Universitat de Barcelona, Spain.; UB Institute of Complex Systems, Universitat de Barcelona, Spain.; Institute of Neuroscience, Universitat de Barcelona, Spain., Guàrdia-Olmos J; Facultat de Psicologia, Universitat de Barcelona, Spain.; UB Institute of Complex Systems, Universitat de Barcelona, Spain.; Institute of Neuroscience, Universitat de Barcelona, Spain.
Jazyk:	angličtina
Zdroj:	International journal of clinical and health psychology : IJCHP [Int J Clin Health Psychol] 2020 Sep-Dec; Vol. 20 (3), pp. 200-212. Date of Electronic Publication: 2020 Aug 16.
DOI:	10.1016/j.ijchp.2020.07.005
Abstrakt:	Background/Objective : This study aims to characterize the differences on the short-term temporal network dynamics of the undirected and weighted whole-brain functional connectivity between healthy aging individuals and people with mild cognitive impairment (MCI). The Network Change Point Detection algorithm was applied to identify the significant change points in the resting-state fMRI register, and we analyzed the fluctuations in the topological properties of the sub-networks between significant change points. Method : Ten MCI patients matched by gender and age in 1:1 ratio to healthy controls screened during patient recruitment. A neuropsychological evaluation was done to both groups as well as functional magnetic images were obtained with a Philips 3.0T. All the images were preprocessed and statistically analyzed through dynamic point estimation tools. Results : No statistically significant differences were found between groups in the number of significant change points in the functional connectivity networks. However, an interaction effect of age and state was detected on the intra-participant variability of the network strength. Conclusions : The progression of states was associated to higher variability in the patient's group. Additionally, higher performance in the prospective and retrospective memory scale was associated with higher median network strength. (© 2020 Asociación Española de Psicología Conductual. Published by Elsevier España, S.L.U.)
Databáze:	MEDLINE
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