Variance Analysis on Functional Connectivity of Resting-state fMRI Signals in Alzheimer's Disease Patients

Sadiq, A. and Yahya, N. and Tang, T.B. and Hashim, H. and Saad, M.N.M. (2022) Variance Analysis on Functional Connectivity of Resting-state fMRI Signals in Alzheimer's Disease Patients. In: UNSPECIFIED.

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Official URL: https://www.scopus.com/inward/record.uri?eid=2-s2....

Abstract

The assessment of the brain network is a powerful tool for determining brain topological organisation, and it is been employed extensively in the study of mental disorders. Observing the brain's connectivity patterns is one of the most effective approaches for analysing brain functionality. According to recent research, Alzheimer's disease is significantly linked to the changes in network connection among distinct brain regions. In this work, five brain regions are chosen to be analyzed in showing the variation in functional connectivity. These regions are hippocampus, parahippocampus, olfactory, superior parietal gyrus and anterior cingulate gyrus. Pearson's Correlation is used for determining the functional connection between the five brain regions. When comparing Alzheimer's disease (AD) patients to Normal Controls, the findings indicate that there are higher variations of functional connectivity in AD patients. © 2022 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: cited By 0; Conference of 2022 International Conference on Future Trends in Smart Communities, ICFTSC 2022 ; Conference Date: 1 December 2022 Through 2 December 2022; Conference Code:186671
Uncontrolled Keywords: Correlation methods; Functional neuroimaging; Neurodegenerative diseases, Alzheimers disease; Brain lobe; Brain networks; Brain regions; Disruption; Functional connectivity; Mental disorders; Resting state; Variance; Variance analysis, Brain
Depositing User: Mr Ahmad Suhairi UTP
Date Deposited: 19 Dec 2023 03:23
Last Modified: 19 Dec 2023 03:23
URI: https://khub.utp.edu.my/scholars/id/eprint/17262

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