For that aim, we recorded EEG data of 27 participants engaged in the Flanker task and receiving either positive or negative feedback following each trial. We then utilized the recently developed ...

The ERPENet incorporates convolutional neural networks (CNNs) and long short-term memory (LSTM), in an autoencoder setup, which tries to simultaneously compress the input EEG signal and extract ...

The model transformed EEG data into 2D images using a short-time Fourier transform, applied transfer learning to extract discriminative features, and consequently integrated them with fNIRS-derived ...