Using fingerprinting as a testbed for strategies to improve reproducibility of functional connectivity

Reproducible functional connectivity-based biomarkers have remained elusive despite the promise of deeply phenotyped consortia. Developing methods for assessing and optimizing the reproducibility of functional connectivity pipelines and metrics is crucial to advancing biomarker identification. Here, we demonstrate functional connectome fingerprinting can serve as a robust, easily computed, intuitive, and sensitive index for assessing, comparing or benchmarking pipeline parameters. Using five datasets from the Consortium for Replicability and Reproducibility, we found that higher identification accuracies were achieved when using: (I) global signal regression; (II) finer brain parcellations; (III) cortical regions compared to subcortical and cerebellar structures; (IV) medial frontal and frontoparietal networks relative to the whole-brain; (V) discriminative edges; (VI) longer scan duration; and (VII) lower sample size. Such fingerprint-informed pipelines may enable assessment and adjudication of functional connectivity-based analysis pipelines or novel analytic approaches, as a means to enhance their reproducibility in heterogeneous populations, and to advance biomarker discovery.