An fNIRS Dataset for Cognitive Decoding during a Multi-day Block-design Stroop Task
Lingwei Zeng, Kewei Sun, Yimeng Yuan, Yuntao Gao, Xiuchao Wang, Zhihong Wen, Di Wu
Air Force Medical University
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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 hemoglobin responses from 55 young adults. Each participant completed three sessions of color-word Stroop task within approximately 2 weeks, to collect more than 30 trials per condition while avoiding mental fatigue caused by a single session. 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.
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