eprintid: 17262
rev_number: 2
eprint_status: archive
userid: 1
dir: disk0/00/01/72/62
datestamp: 2023-12-19 03:23:41
lastmod: 2023-12-19 03:23:41
status_changed: 2023-12-19 03:07:45
type: conference_item
metadata_visibility: show
creators_name: Sadiq, A.
creators_name: Yahya, N.
creators_name: Tang, T.B.
creators_name: Hashim, H.
creators_name: Saad, M.N.M.
title: Variance Analysis on Functional Connectivity of Resting-state fMRI Signals in Alzheimer's Disease Patients
ispublished: pub
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
note: 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
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.
date: 2022
publisher: Institute of Electrical and Electronics Engineers Inc.
official_url: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85149108259&doi=10.1109%2fICFTSC57269.2022.10040043&partnerID=40&md5=b30dc9e17a93785ba32307251f379fd5
id_number: 10.1109/ICFTSC57269.2022.10040043
full_text_status: none
publication: 2022 International Conference on Future Trends in Smart Communities, ICFTSC 2022
pagerange: 223-228
refereed: TRUE
isbn: 9798350334548
citation:   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.