How to measure functional connectivity (FC) in the brain? A comprehensive empirical exploration of connectivity metrics

Functional connectivity in the context of functional magnetic resonance imaging is typically quantified by Pearson´s or partial correlation between regional timeseries of the blood oxygenation level dependent signal. However, a recent interdisciplinary methodological work by Cliff et al. (2023) proposes more than 230 different metrics to measure similarity between different types of timeseries. Hence, we systematically evaluated how the results of typical research approaches in functional neuroimaging vary depending on the functional connectivity metric of choice. We further explored which metrics most accurately detect biologically plausible neural decline induced by age, malignant brain tumors, or chronic schizophrenia. 

We addressed both research questions using four independent neuroimaging datasets (HCP-Aging, Mind-Brain-Body, Clinical Deep Phenotyping, and Brain Tumor Connectomics), comprising multimodal data from a total of 1187 individuals. We analyzed resting-state functional sequences to calculate functional connectivity based on 20 representative metrics from four distinct mathematical categories. We further used T1- and T2-weighted images to compute regional brain volumes, diffusion-weighted imaging data to build structural connectomes, and pseudo-continuous arterial spin labeling to measure regional brain perfusion. 

First, our findings demonstrate that the results of typical functional neuroimaging approaches differ fundamentally depending on the functional connectivity metric of choice. Second, we show that correlational and distance metrics are most appropriate to cover biologically plausible neural decline induced by age. In this context, partial correlation performs worse than other correlational metrics. Third, our findings suggest that the FC metric of choice depends on the utilized scanning parameters, the regions of interest, and the individual subject investigated. Lastly, beyond the major objective of this study, we provide evidence in favor of brain perfusion measured via pseudo-continuous arterial spin labeling as a robust neural entity mirroring age-related neural and cognitive decline. 

Our empirical evaluation supports a recent theoretical functional connectivity framework introduced by Reid et al. (2019). Future functional imaging studies need to comprehensively define the study-specific theoretical property of interest, the methodological property to assess this theoretical property, and the confounding property that may bias the conclusions.