The goal of this paper is to investigate whether motor imagery tasks, performed under pain-
free versus pain conditions, can be discriminated from electroencephalography (EEG)
recordings. Four motor imagery classes of right hand, left hand, foot, and tongue are
considered. A functional connectivity-based feature extraction approach along with a long
short-term memory (LSTM) classifier are employed for classifying pain-free versus under-
pain classes. Moreover, classification is performed in different frequency bands to study the …