2026-10-12T17:04:38Z https://www.scidb.cn/oai

10.57760/sciencedb.42036 2026-07-06T09:06:11Z

2026-07-06 MS-STAMNet-FDL Dataset: An EEG dataset for the evaluation of auditory frequency difference limen doi:10.57760/sciencedb.42036 en This dataset is an electroencephalogram (EEG) dataset constructed for MS-STAMNet, a deep learning framework designed for the single-trial decoding of weak auditory evoked responses. It integrates personalized auditory stimulus configurations and their corresponding multi-dimensional neural representations evoked at the perceptual threshold state. The data were collected from 11 healthy participants utilizing a customized rapid serial auditory presentation paradigm based on each individual's frequency difference limen. The dataset contains EEG recordings and model code. Frequency difference discrimination; Deep learning; EEG Li Shengye EMBARGO https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.3724/j.pibb.2026.0252 Science Data Bank