Miyatsu, T.; Mahyari, A.; Rogala, J.; Broderick, T.; Pirolli, P.

Brain activity at a resting state and functional connectivity represent individuals\' neural configurations that can be used to predict various performance and trait measures. Yet, most of the previous empirical demonstrations of this phenomena are limited to using resting-state neuroimaging to predict a single task performance/trait measure, and a few studies that predicted multiple task performance/traits measures employed conceptually similar tasks to produce converging evidence for their topic of investigation. In the current paper, we applied RID-Rihazcek phase synchrony, a nonlinear time-frequency-based method for neural computation, to resting-state EEG data and simultaneously predicted a wide variety of measures: standard shooting task performance and novel verbal communication-based team shooting task performance in a simulator, visuo-spatial tracking task performance (Neurotracker), executive function (verbal fluency task), fluid and crystalized Intelligence (Multidimensional Aptitude Battery II: MAB-II), and neurocognitive functioning (Automated Neuropsychological Assessment Metrics-4: ANAM-4) with the average R2 = .60. Our findings show great promise for RID-Rihazcek phase synchrony and resting-state EEG in general to be used in aptitude assessment.