1. MRI meets economics: Balancing sample size and scan duration

COEX 

Resting-state functional connectivity is widely used to predict behavioral traits in individuals. A pervasive dilemma in neuroimaging is whether to prioritize sample size or scan duration given fixed resources. Here, we systematically investigate the trade-off between sample size and scan time in the context of the accuracy and reliability of brain-behavior relationships using resting-state fMRI. For prediction accuracy of individual-level behavioral measures, we find that the contributions of increasing sample size and scan duration are similar up to approximately 20-30 minutes of scan-time per participant. In particular, total scan duration (sample size × scan time per participant) robustly explains prediction accuracy via a logarithmic function. On the other hand, when considering the reliability of brain-behavior associations, sample size dominates individual participant scan durations beyond 6 to 10 minutes.These results replicate across a wide range of behavioral measures from two large-scale datasets. Overall, our findings establish an empirically informed reference for calibrating scan duration and sample size to maximize prediction of behavioral performance and reliability of brain-behavior association.