EEG Representations of Spatial and Temporal Features in Imagined Speech and Overt Speech

Imagined speech is an emerging paradigm for intuitive control of the brain-computer interface based communication system. Although the decoding performance of the imagined speech is improving with actively proposed architectures, the fundamental question about ‘what component are they decoding?’ is still remaining as a question mark. Considering that the imagined speech refers to an internal mechanism of producing speech, it may naturally resemble the distinct features of the overt speech. In this paper, we investigate the close relation of the spatial and temporal features between imagined speech and overt speech using electroencephalography signals. Based on the common spatial pattern feature, we acquired 16.2% and 59.9% of averaged thirteen-class classification accuracy (chance rate = 7.7%) for imagined speech and overt speech, respectively. Although the overt speech showed significantly higher classification performance compared to the imagined speech, we found potentially similar common spatial pattern of the identical classes of imagined speech and overt speech. Furthermore, in the temporal feature, we examined the analogous grand averaged potentials of the highly distinguished classes in the two speech paradigms. Specifically, the correlation of the amplitude between the imagined speech and the overt speech was 0.71 in the class with the highest true positive rate. The similar spatial and temporal features of the two paradigms may provide a key to the bottom-up decoding of imagined speech, implying the possibility of robust classification of multiclass imagined speech. It could be a milestone to comprehensive decoding of the speech-related paradigms, considering their underlying patterns.