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Functional Connectivity Assessment on Aging Brain using Functional Near Infrared Spectroscopy (fNIRS)

Chan, Yee Ling (2017) Functional Connectivity Assessment on Aging Brain using Functional Near Infrared Spectroscopy (fNIRS). UNSPECIFIED.

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Abstract

To date, conventional diagnosis of Alzheimer’s disease (AD) using questionnaire are still widely implemented due to constraints of safety and costs in biochemical and neuroimaging approaches. Hence this research aims to derive a low-cost, non-invasive and stable biomarker to differentiate normal aging (NA), mild cognitive impairment (MCI) and AD using functional near infrared spectroscopy (fNIRS). Sixty-one participants (31,12,18 for NA, MCI, AD groups respectively) completed Clinical Dementia Rating (CDR) and Mini-Mental State Examination (MMSE). They performed three categories of semantic verbal fluency test while neuronal activity in prefrontal cortex (PFC) measured using fNIRS. A new software algorithm has been developed to derive functional connectivity parameters. The synchronization of oxygenated haemoglobin (oxy-Hb) signals from pair channels were evaluated using temporal correlation. Findings showed that functional connectivity and laterality of brain declined with cognitive severity. Connectivity decreased from 307 to 170 (NA to AD). Meanwhile the laterality between left and right PFC became insignificant (p>0.01) during AD stage. Moreover, NA groups demonstrated significantly higher small-worldness than AD (p<0.05), suggesting more effective neuronal activity and hence leading to higher PFC performance. Furthermore, neuronal connectivity of MCI correlated positively with MMSE and with average VFT score regardless of hemispheres which might indicated compensation mechanism. The findings supported fNIRS as a promising alternative measuring instrument to differentiate NA group from MCI and AD.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: UNSPECIFIED
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 20 Jun 2019 11:06
Last Modified: 20 Jun 2019 11:06
URI: http://utpedia.utp.edu.my/id/eprint/19141

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