A Study of Visual Recognition of Facial Emotional Expressions in a Normal Aging Population in the Absence of Cognitive Disorders

Objective: To examine and measure the decision-making processes involved in Visual Recognition of Facial Emotional Expressions (VRFEE) and to study the effects of demographic factors on this process. Method: We evaluated a newly designed software application (M.A.R.I.E.) that permits computerized metric measurement of VRFEE. We administered it to 204 cognitively normal participants ranging in age from 20 to 70 years. Results: We established normative values for the recognition of anger, disgust, joy, fear, surprise and sadness expressed on the faces of three individuals. There was a significant difference in the: 1) measurement (F (8.189) = 3896, p = 0.0001); 2) education level (x2(12) = 28.4, p = 0.005); 3) face (F(2.195) = 10, p = 0.0001); 4)series (F (8.189)=28, p = 0.0001); 5) interaction between the identity and recognition of emotions (F (16, 181 =11, p = 0.0001). However, performance did not differ according to: 1) age (F (6.19669) = 1.35, p = 0.2) or 2) level of education (F (1, 1587) = 0.6, p = 0.4). Conclusions: In healthy participants, the VRFEE remains stable throughout the lifespan when cognitive functions remain optimal. Disgust, sadness, fear, and joy seem to be the four most easily recognized facial emotions, while anger and surprise are not easily recognized. Visual recognition of disgust and fear is independent of aging. The characteristics of a face have a significant influence on the ease with which people recognize expressed emotions (idiosyncrasy). Perception and recognition of emotions is categorical, even when the facial images are integrated in a spectrum of morphs reflecting two different emotions on either side.