Judith Bek1, Ellen Poliakoff2, Karen Lander3. 1. Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, UK. Electronic address: Judith.Bek@manchester.ac.uk. 2. Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, UK. Electronic address: Ellen.Poliakoff@manchester.ac.uk. 3. Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, UK. Electronic address: Karen.Lander@manchester.ac.uk.
Abstract
BACKGROUND: Motion is an important cue to emotion recognition, and it has been suggested that we recognize emotions via internal simulation of others' expressions. There is a reduction of facial expression in Parkinson's disease (PD), which may influence the ability to use motion to recognise emotions in others. However, the majority of previous work in PD has used only static expressions. Moreover, few studies have used eye-tracking to explore emotion processing in PD. NEW METHOD: We measured accuracy and eye movements in people with PD and healthy controls when identifying emotions from both static and dynamic facial expressions. RESULTS: The groups did not differ overall in emotion recognition accuracy, but motion significantly increased recognition only in the control group. Participants made fewer and longer fixations when viewing dynamic expressions, and interest area analysis revealed increased gaze to the mouth region and decreased gaze to the eyes for dynamic stimuli, although the latter was specific to the control group. COMPARISON WITH EXISTING METHODS: Ours is the first study to directly compare recognition of static and dynamic emotional expressions in PD using eye-tracking, revealing subtle differences between groups that may otherwise be undetected. CONCLUSIONS: It is feasible and informative to use eye-tracking with dynamic expressions to investigate emotion recognition in PD. Our findings suggest that people with PD may differ from healthy older adults in how they utilise motion during facial emotion recognition. Nonetheless, gaze patterns indicate some effects of motion on emotional processing, highlighting the need for further investigation in this area.
BACKGROUND: Motion is an important cue to emotion recognition, and it has been suggested that we recognize emotions via internal simulation of others' expressions. There is a reduction of facial expression in Parkinson's disease (PD), which may influence the ability to use motion to recognise emotions in others. However, the majority of previous work in PD has used only static expressions. Moreover, few studies have used eye-tracking to explore emotion processing in PD. NEW METHOD: We measured accuracy and eye movements in people with PD and healthy controls when identifying emotions from both static and dynamic facial expressions. RESULTS: The groups did not differ overall in emotion recognition accuracy, but motion significantly increased recognition only in the control group. Participants made fewer and longer fixations when viewing dynamic expressions, and interest area analysis revealed increased gaze to the mouth region and decreased gaze to the eyes for dynamic stimuli, although the latter was specific to the control group. COMPARISON WITH EXISTING METHODS: Ours is the first study to directly compare recognition of static and dynamic emotional expressions in PD using eye-tracking, revealing subtle differences between groups that may otherwise be undetected. CONCLUSIONS: It is feasible and informative to use eye-tracking with dynamic expressions to investigate emotion recognition in PD. Our findings suggest that people with PD may differ from healthy older adults in how they utilise motion during facial emotion recognition. Nonetheless, gaze patterns indicate some effects of motion on emotional processing, highlighting the need for further investigation in this area.
Authors: Murugappan Murugappan; Waleed Alshuaib; Ali K Bourisly; Smith K Khare; Sai Sruthi; Varun Bajaj Journal: PLoS One Date: 2020-11-19 Impact factor: 3.240