fNIRS Dataset for Stroop Decoding

Cognitive state decoding is key to brain-computer interface technology, serves as a promising tool for psychiatric diagnosis and rehabilitation, and offers a novel perspective for neuroscientific study. Datasets for decoding cognitive states using optical neuroimaging modalities remain scarce. To address this, we provide an fNIRS dataset acquired during a Stroop task, consisting of frontal hemodynamic responses from 55 young adults. Each participant completed three sessions, with a seven-day gap between sessions, to minimize biases associated with task familiarity or practice effects. This dataset supports a range of applications, from studying conflict inhibition to building decoders for neurofeedback training and large-scale cross-subject fNIRS models, while also facilitating the development of signal processing algorithms for hemodynamic signals.