Dysfunctional Default Mode and Visual Networks Underlie Cognitive Deficits in Dementia With Lewy Bodies: A Resting-State fMRI Study

Zhou Su^1*Jun Kuai²Tingting Yi¹Yuechang Zheng¹Xinran Bao³Jiyu Ji¹

• ¹Department of Neurology, The First Affiliated Hospital of Xinxiang Medical University, Xin xiang, China
• ²department of gastroenterology，the first affiliated of xinxiang mecical university, xinxiang, China
• ³department of neurology, first Hospital of Qinhuangda, Qinhuangda, 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 (R² = 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.