This study investigates the disruption of intrinsic functional brain connectivity in Alzheimer's disease (AD) using network analysis. Functional brain networks, detected in resting-state functional magnetic resonance imaging (fMRI), exhibit a small-world architecture, characterized by high clustering coefficients and low characteristic path lengths. The study compared these metrics in 21 AD patients and 18 age-matched controls. Wavelet analysis was used to compute frequency-dependent correlation matrices, which were thresholded to create 90-node undirected graphs of functional brain networks. Small-world metrics, including clustering coefficient and characteristic path length, were calculated. In controls, these metrics showed small-world organization, while in AD patients, they were significantly lower, indicating disrupted local connectivity. The clustering coefficient was significantly lower in the left and right hippocampus in AD patients compared to controls. The clustering coefficient distinguished AD patients from controls with 72% sensitivity and 78% specificity. The study provides evidence that AD disrupts functional brain network organization, and small-world metrics may serve as imaging-based biomarkers for AD. The findings suggest that AD patients show reduced global functional organization, with disrupted connectivity in the hippocampus and other brain regions. The study also highlights the importance of small-world metrics in characterizing functional brain organization and their potential as biomarkers for AD. The results indicate that AD patients have lower clustering coefficients and higher characteristic path lengths compared to controls, suggesting a loss of small-world properties. The study's findings support the use of small-world metrics as a tool for distinguishing AD from healthy aging. The study's limitations include the potential influence of medication on results and the need for further validation. Overall, the study demonstrates that AD disrupts intrinsic functional brain connectivity, with implications for the development of imaging-based biomarkers for early detection and monitoring of AD.This study investigates the disruption of intrinsic functional brain connectivity in Alzheimer's disease (AD) using network analysis. Functional brain networks, detected in resting-state functional magnetic resonance imaging (fMRI), exhibit a small-world architecture, characterized by high clustering coefficients and low characteristic path lengths. The study compared these metrics in 21 AD patients and 18 age-matched controls. Wavelet analysis was used to compute frequency-dependent correlation matrices, which were thresholded to create 90-node undirected graphs of functional brain networks. Small-world metrics, including clustering coefficient and characteristic path length, were calculated. In controls, these metrics showed small-world organization, while in AD patients, they were significantly lower, indicating disrupted local connectivity. The clustering coefficient was significantly lower in the left and right hippocampus in AD patients compared to controls. The clustering coefficient distinguished AD patients from controls with 72% sensitivity and 78% specificity. The study provides evidence that AD disrupts functional brain network organization, and small-world metrics may serve as imaging-based biomarkers for AD. The findings suggest that AD patients show reduced global functional organization, with disrupted connectivity in the hippocampus and other brain regions. The study also highlights the importance of small-world metrics in characterizing functional brain organization and their potential as biomarkers for AD. The results indicate that AD patients have lower clustering coefficients and higher characteristic path lengths compared to controls, suggesting a loss of small-world properties. The study's findings support the use of small-world metrics as a tool for distinguishing AD from healthy aging. The study's limitations include the potential influence of medication on results and the need for further validation. Overall, the study demonstrates that AD disrupts intrinsic functional brain connectivity, with implications for the development of imaging-based biomarkers for early detection and monitoring of AD.