How natural system anticipates emotion recognition

In this research paper we hypothesize the human facial emotions recognition (FER) process is related to gaze “jumping” and to emotional level of observer itself. Evolutionary speaking it’s vitally important to recognize emotions quickly and precisely in order to evaluate the situation and react to it adequately. We suppose that facial emotion recognition is a process of convergence of induced neural zones into one of many local attractors, which represent mental models or behavioral schemes as a reaction to certain emotions. The convergence speed is growing if visual FER part (“data collection”) is leaded by gaze fluctuations between emotion’ representing segments (for example, facial parts). The higher uncertainty of visage is, the bigger gaze fluctuations there are. In the case of factitious emotional expressions, FER is more difficult if observer is better trained and gaze “jumping” is minimal. Gaze “jumping” in nonstandard situations of untrained person (like a child) grows independently if it leads or not to only attractor (i.e. the emotion is recognized or is not recognized). Consequently the gaze “drifting” is related to experience and training, but an increased gaze fluctuations means transition from one local attractor to another improving FER process. Therefore learned emotions serves to recognize better the other emotions, by increased gaze „drifting“ - emotions participate as catalyst of recognition process. Also asymmetry evokes gaze fluctuations and even a small one anticipates recognition process. During the experiment (unnatural facial emotions recognition) with children, gaze “jumping” is higher even if any decision follows from that. Meanwhile gaze oscillations of adults are smaller and lead to certain identification cluster (even misguided).