The influence of vertical disparity gradient and cue conflict on EEG omega complexity in Panum’s limiting case

Abstract

Using behavioral measures and ERP technique, researchers discovered at least two factors could influence the final perception of depth in Panum’s limiting case, which are the vertical disparity gradient and the degree of cue conflict between two-and three-dimensional shapes. Although certain event-related potential components have been proved to be sensitive to the different levels of these two factors, some methodological limitations existed in this technique. In this study, we proposed that the omega complexity of EEG signal may serve as an important supplement of the traditional event-related potential technique. We found that the trials with lower vertical gradient disparity have lower omega complexity (i.e., higher global functional connectivity) of the occipital region, especially that of the right-occipital hemisphere. Moreover, for occipital omega complexity, the trials with low-cue conflict have significantly larger omega complexity than those with medium-and high-cue conflict. It is also found that the electrodes located in the middle line of the occipital region (i.e., POz and Oz) are more crucial to the impact of different levels of cue conflict on omega complexity than the other electrodes located in the left-and right-occipital hemispheres. These evidences demonstrated that the EEG omega complexity could reflect distinct neural activities evoked by Panum’s limiting case configurations, with different levels of vertical disparity gradient and cue conflict. Besides, the influence of vertical disparity gradient and cue conflict on omega complexity may be regional dependent. NEW & NOTEWORTHY The EEG omega complexity could reflect distinct neural activities evoked by Panum’s limiting case configurations with different levels of vertical disparity gradient and cue conflict. The influence of vertical disparity gradient and cue conflict on omega complexity is regional dependent. The omega complexity of EEG signal can serve as an important supplement of the traditional ERP technique.