\This research introduces the Network Similarity Index (NSI), an objective tool designed to verify the quality and sufficiency of precision functional mapping (PFM) data. By quantifying how well individual brain scans align with canonical network templates, the NSI replaces subjective visual inspections with a reproducible, algorithmic framework. High NSI values indicate a well-resolved low-spatial-frequency scaffold, which is essential for distinguishing true individual-specific brain organization from fragmented noise. The framework effectively identifies usable datasets, estimates the reliability of current data, and predicts the benefits of collecting additional scan time. Ultimately, this open-source resource enhances the accuracy of individualized brain mapping in both healthy populations and clinical subjects with neuropsychiatric disorders.
References:
Lynch C J, Chang M, Elbau I, et al. Objective quality assessment for precision functional MRI data[J]. Neuron, 2026.
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