Comparing Functional Connectivity Metrics from Resting-State fMRI: Applications to Alzheimer's Disease

Resting-state functional connectivity, derived from resting-state functional Magnetic Resonance Imaging, maps neural patterns representing spontaneous brain activity. The choice of connectivity metrics could significantly impact the results and interpretations of the analysis. This study compares 10 commonly used metrics to the gold-standard Pearson Correlation measure using the Mantel test. This analysis was conducted using data from two popular public repositories, ADNI3*∗Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wpcontent/uploads/howtoapply/ADNIAcknowledgementList.pdf and OASIS3. Our findings showed that the Mantel test discriminates between metrics and reveals possible influences in connectivity patterns related to the datasets and cognitive groups. This comparative approach could identify measures that most diverge from Pearson Correlation. Based on these results, we propose a multi-feature framework for selecting relevant functional connectivity metrics in a data-driven manner, facilitating subsequent processing and analysis.