Simultaneous EEG-fNIRS Data on Learning Capability via Implicit Learning Induced by Cognitive Tasks

The development of real-time learning assessment tools is hindered by an incomplete understanding of the underlying neural mechanisms. To address this gap, this study aimed to identify the specific neural correlates of implicit learning, a foundational process crucial for skill acquisition. We collected simultaneous electroencephalography and functional near-infrared spectroscopy data from thirty healthy adults (ages 21–29) performing a serial reaction time task designed to induce implicit learning. By capturing both electrophysiological and hemodynamic responses concurrently at shared locations, this dataset offers a unique opportunity to investigate neurovascular coupling during implicit learning and gain deeper insights into the neural mechanisms of learning. The dataset is categorized into two groups: participants who demonstrated implicit learning (based on post-experiment interviews) and those who did not. This dataset enables the identification of prominent brain regions, features, and temporal patterns associated with successful implicit learning. This identification will form the basis for future real-time learning assessment tools.