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Updated: Jan 9, 2026

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
Dysfunctional default mode and visual networks underlie cognitive deficits in dementia with Lewy bodies: a
Zhou Su1, Mengran Liu2, Jun Kuai3
1Department of Neurology, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, China.
Objective:
To characterize abnormal functional connectivity in dementia with Lewy bodies (DLB) and its association with cognitive impairment using resting-state functional magnetic resonance imaging (rs-fMRI).
Methods:
Sixty-eight DLB patients and 38 age-, sex-, and education-matched healthy controls underwent neuropsychological assessments (MoCA, MMSE) and rs-fMRI. Imaging analyses included seed-based functional connectivity (sFC), independent component analysis (ICA), regional homogeneity (ReHo), fractional amplitude of low-frequency fluctuations (fALFF), and graph-theoretical network metrics (small-worldness, global/local efficiency).
Results:
DLB patients exhibited significantly reduced FC in the default mode network (DMN) and visual network, including PCC-AG (P < 0.001) and PCC-mPFC (P < 0.001). ReHo and fALFF indicated decreased local neural synchronization and low-frequency activity in the posterior occipital lobe (fALFF: P = 0.004), angular gyrus (fALFF: P = 0.001), left temporal pole (fALFF: P < 0.001), left parietal (ReHo: P < 0.001), and posterior cerebellar lobe (ReHo: P < 0.001). Graph theory revealed impaired global network topology in DLB, with decreased small-worldness (P < 0.001) and global efficiency (P < 0.001). PCC-AG connectivity positively correlated with the MoCA total score (r = 0.53, P < 0.001), attention (r = 0.46, P < 0.001), executive (r = 0.41, P < 0.001), and language function (r = 0.34, P < 0.001). Posterior occipital fALFF and left parietal ReHo showed significant positive correlations with multiple cognitive domains, including visuospatial ability (r = 0.34, P < 0.001 for fALFF; r = 0.42, P < 0.001 for ReHo) and memory (r = 0.45, P < 0.001 for fALFF; r = 0.27, P = 0.006 for ReHo). A combined model of PCC-AG connectivity, fALFF, and small-worldness predicted 42% of MoCA variance (R 2 = 0.42, P < 0.001).
Conclusion:
DLB is characterized by DMN and visual network dysfunction, disrupted local neural activity, and impaired global network integration. These rs-fMRI metrics may serve as potential biomarkers for cognitive deficits in DLB.
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