 This study investigated the complementary nature of electroencephalogram, EEG, and functional near-infrared spectroscopy, FNIRS, data by employing an optimization-based feature selection algorithm. The results indicated that the proposed hybrid classification framework outperformed both the individual modalities and traditional feature selection classification. This suggests that the proposed framework could be useful for various neuroclinical applications. This article was authored by Mohamed Umer Ali, Kuang Soo Kim, Karam Dadkalu, and others.