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Research Article Open access CC BY 4.0

Regions and Sub-regions Dysfunctions in Alzheimer’s during Rest

K. C. Usha Usha, Dr. H. N. Suma

Asian Journal of Medicine and Health · pp. 43–54 · Published 16 Jun 2020

10.9734/ajmah/2020/v18i530205

Abstract

Aims: Alterations in the cerebrum structurally and functionally are triggered largely due to an increase in neuro depressive brain disorders like Alzheimer’s. This study aims is to determine these alterations in the regions of the cerebrum which are significant and distinguishing in Alzheimer’s disease subjects compared to healthy. We employ the most potential resting-state functional Magnetic Resonance Imaging (rs-fMRI) modality for this analysis. Methodology: 24 Alzheimer’s disease (AD) and 25 Healthy Controlled (HC) subjects were evaluated with rs-fMRI which is more efficient in anticipating neuronal activity changes. Thus, obtained data of all subjects were preprocessed and components of larger networks to smaller regions were extracted by independent component analysis (ICA) method. Differences in resting-state connectivity were examined for 6 networks of interest viz., Auditory network, Central Executive network, Default mode network, Silence mode network, Sensory-motor network and Visual network and their regions, which are affected due to the common symptoms of Alzheimer’s disease-like memory, thinking and behavioral changes. Statistical analysis was done with one sample t-test to check the functional connectivity activations in Resting-State Networks (RSNs) and regions of both AD & HC groups at a threshold of T>2. Finally, to obtain the abnormal sub-regions in each of the RSNs of AD a two-sample t-test was carried out at a threshold of P < .03. Results: Our method potentially identifies the functional connectivity alterations and core regions dysfunction amongst the major 6 RSNs in AD compared to HC subjects. The results also showed decreased connectivity in regions of sensory-motor and default mode networks increased connectivity in regions of central executive and silence mode network along with some of the sub-regions dysfunctions in AD. Conclusion: Modifications in functional connectivity within the major RSNs and regions have been detected which serves as a capability to determine an early biomarker and examining the disease progression.

Functional Magnetic Resonance Imaging (fMRI) resting-state fMRI functional connectivity Alzheimer’s disease independent component analysis resting state networks auditory network central executive network default mode network salience network; sensory-motor network visual network.

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