Persistent homology based topological analysis on the gestalt patterns during human brain cognition process - Zaisheng LIU; Fei NI; Rongpeng LI; Honggang ZHANG; Chang LIU; Jiefang ZHANG; Songyun XIE (Dianxin kexue)
The integrated development of information communication technology and neuroscience heralds the possibility and great potential of brain-to-brain wireless communication(B2BC).The physiologically meaningful features of brain responses were extracted to different contour and shape in images in Gestalt cognitive tests by combining persistent homology analysis with electroencephalogram (EEG).The experimental results show that more brain regions in the frontal lobe were involved when the subject perceives the random and disordered combination of images compared to the ordered Gestalt images.Meanwhile, the persistence entropy of EEG data evoked by random sequence diagram (RSD) was observed to be significantly different from that by the ordered Gestalt images(GST) in several frequency bands, which indicated that human cognition of shapes and contours, such as a preliminary advanced cognition process, could be separated to some extent through topological analysis.This method can digitize the neural signals while preserving the whole and local features of the original signals.In general, the cognitively related neural correlates by persistent homology features of EEG signal are revaluated and quantified, which provides an approach to realize the digitization of neural signals in brain-to-brain wireless communication.