This study investigates the functional brain organization in Alzheimer's Disease (AD) using task-free functional magnetic resonance imaging (fMRI). The authors applied wavelet analysis to fMRI data from 21 AD patients and 18 age-matched controls to compute frequency-dependent correlation matrices, which were thresholded to create 90-node undirected graphs of functional brain networks. Small-world metrics, including characteristic path length and clustering coefficient, were used to analyze the global functional organization of these networks. The results showed that AD patients exhibited a loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01) compared to controls, indicating disrupted local connectivity. Specifically, the left and right hippocampus showed significantly lower clustering coefficients (p<0.01) in AD patients compared to controls. The clustering coefficient also distinguished AD participants from controls with a sensitivity of 72% and specificity of 78%. These findings suggest that small-world network characteristics may serve as useful imaging biomarkers for distinguishing AD from healthy aging. The study highlights the importance of disrupted global functional organization in AD and provides evidence for the potential of small-world measures as biomarkers.This study investigates the functional brain organization in Alzheimer's Disease (AD) using task-free functional magnetic resonance imaging (fMRI). The authors applied wavelet analysis to fMRI data from 21 AD patients and 18 age-matched controls to compute frequency-dependent correlation matrices, which were thresholded to create 90-node undirected graphs of functional brain networks. Small-world metrics, including characteristic path length and clustering coefficient, were used to analyze the global functional organization of these networks. The results showed that AD patients exhibited a loss of small-world properties, characterized by a significantly lower clustering coefficient (p<0.01) compared to controls, indicating disrupted local connectivity. Specifically, the left and right hippocampus showed significantly lower clustering coefficients (p<0.01) in AD patients compared to controls. The clustering coefficient also distinguished AD participants from controls with a sensitivity of 72% and specificity of 78%. These findings suggest that small-world network characteristics may serve as useful imaging biomarkers for distinguishing AD from healthy aging. The study highlights the importance of disrupted global functional organization in AD and provides evidence for the potential of small-world measures as biomarkers.