Connectome-based model predicts episodic memory performance in individuals with subjective cognitive decline and amnestic mild cognitive impairment.


Journal

Behavioural brain research
ISSN: 1872-7549
Titre abrégé: Behav Brain Res
Pays: Netherlands
ID NLM: 8004872

Informations de publication

Date de publication:
06 08 2021
Historique:
received: 14 01 2021
revised: 19 04 2021
accepted: 22 05 2021
pubmed: 29 5 2021
medline: 10 2 2022
entrez: 28 5 2021
Statut: ppublish

Résumé

To explore whether the whole brain resting-state functional connectivity (rs-FC) could predict episodic memory performance in individuals with subjective cognitive decline and amnestic mild cognitive impairment. This study included 33 cognitive normal (CN), 26 subjective cognitive decline (SCD) and 27 amnestic mild cognitive impairment (aMCI) patients, and all the participants completed resting-state fMRI (rs-fMRI) scan and neuropsychological scale test data. Connectome-based predictive modeling (CPM) based on the rs-FC data was used to predict the auditory verbal learning test-delayed recall (AVLT-DR) scores, which measured episodic memory in individuals. Pearson correlation between each brain connection in the connectivity matrices and AVLT-DR scores was computed across the patients in predementia stages of Alzheimer's disease (AD). The Pearson correlation coefficient values separated into a positive network and a negative network. Predictive networks were then defined and employed by calculating positive and negative network strengths. CPM with leave-one-out cross-validation (LOOCV) was conducted to train linear models to respectively relate positive and negative network strengths to AVLT-DR scores in the training set. During the testing procedure, each left-out testing subject's strengths of positive and negative network was normalized using the parameters acquired during training procedure, and then the trained models were used to predict the testing participant's AVLT-DR score. The negative network predictive model tested LOOCV significantly predicted individual differences in episodic memory from rs-FC. Key nodes that brain regions contributed to the prediction model were mainly located in the prefrontal cortex, frontal cortex, parietal cortex and temporal lobe. Our findings demonstrated that rs-FC among multiple neural systems could predict episodic memory at the individual level.

Identifiants

pubmed: 34048872
pii: S0166-4328(21)00275-8
doi: 10.1016/j.bbr.2021.113387
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

113387

Informations de copyright

Copyright © 2021 Elsevier B.V. All rights reserved.

Auteurs

Yao Zhu (Y)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China.

Feifei Zang (F)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China.

Qing Wang (Q)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China.

Qianqian Zhang (Q)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China.

Chang Tan (C)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China.

Shaoke Zhang (S)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China.

Tianjian Hu (T)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China.

Lingyu Qi (L)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China.

Shouyong Xu (S)

Department of Radiology, Geriatric Hospital of Nanjing Medical University, Nanjing, Jiangsu, 210000, China. Electronic address: xushyong@163.com.

Qingguo Ren (Q)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China. Electronic address: 101011331@seu.edu.cn.

Chunming Xie (C)

Department of Neurology, Affiliated ZhongDa Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, 210000, China. Electronic address: 101011769@seu.edu.cn.

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