Deep Convolutional Neural Networks for mental load classification based on EEG data.

•Both single-channel and multi-channel CNN models are developed to obtain representation from spatial and temporal information of EEG data.•A point-wise gated Boltzmann machines component is introduced to our models to improve performance of our CNN models.•Both our independent and fused models achieve better performance on mental load classification task, and our models contain much less parameters which result in higher efficiency.