Analysis of Dynamic Functional Connectivity of Default Mode Network in Alzheimer's Disease

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MALEKI BALAJOO SOMAYEH; ASEMANI DAVUD; SOLTANIAN ZADEH HAMID

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Journal: IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING Year:2018 | Volume:12 | Issue:2 Page(s): 111-124

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Title

Analysis of Dynamic Functional Connectivity of Default Mode Network in Alzheimer's Disease

Author(s)

MALEKI BALAJOO SOMAYEH | ASEMANI DAVUD | SOLTANIAN ZADEH HAMID | Issue Writer Certificate

Keywords

resting-state functional magnetic resonance imagingQ1

dynamic functional connectivityQ1

temporal variability of functional patternQ1

default mode networkQ1

Alzheimer?s diseaseQ2

Abstract

Early alterations of functional connectivity (FC) within the default mode network (DMN) have been reported in Alzheimer’ s disease (AD). Recently, the resting-state brain networks have been described with non-stationary profiles since inter-and intra-FC of the brain networks changes over time, even at rest. To fully understand the FC changes that characterize AD, the underlying change of its dynamic pattern needs to be captured. The purpose of this study was to evaluate dynamic FC (dFC) patterns within the DMN in patients with AD relative to healthy aging. Here, a sparse logistic regression (SLR) model was employed to estimate the dFC networks in patients with AD (n = 24) compared with healthy control group (n = 37) using resting-state functional magnetic resonance imaging (rs-fMRI) data. To analyze the dFC network, we introduced a temporal variability-functional pattern (TV-FP) score, which shows how the functional pattern of a given region changes over time. This score is able to quantify the temporal patterns of regions involved in a dFC network. We compared TV-FP score across groups. The results indicate that the main regions of DMN, such as the anterior medial prefrontal cortex (aMPFC) and lateral temporal cortex (LTC), are associated with a significantly increased TV-FP score in the AD group when compared to the HC group. The FC pattern of these regions is impaired in AD according to a conventional static functional connectivity (sFC) analysis. These findings may suggest that aMPFC and LTC may tend to reorganize their functional pattern to compensate for the related functional deficiency due to AD.

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APA: Copy

MALEKI BALAJOO, SOMAYEH, & ASEMANI, DAVUD. (2018). Analysis of Dynamic Functional Connectivity of Default Mode Network in Alzheimer's Disease. IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING, 12(2 ), 111-124. SID. https://sid.ir/paper/81626/en

Vancouver: Copy

MALEKI BALAJOO SOMAYEH, ASEMANI DAVUD. Analysis of Dynamic Functional Connectivity of Default Mode Network in Alzheimer's Disease. IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING[Internet]. 2018;12(2 ):111-124. Available from: https://sid.ir/paper/81626/en

IEEE: Copy

SOMAYEH MALEKI BALAJOO, and DAVUD ASEMANI, “Analysis of Dynamic Functional Connectivity of Default Mode Network in Alzheimer's Disease,” IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING, vol. 12, no. 2 , pp. 111–124, 2018, [Online]. Available: https://sid.ir/paper/81626/en

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