Scibelli, F., Troncone, A., Likforman-Sulem, L., Vinciarelli, A. and Esposito, A. (2016) How major depressive disorder affects the ability to decode multimodal dynamic emotional stimuli. Frontiers in ICT, 3, 16. (doi: 10.3389/fict.2016.00016)
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Abstract
Most studies investigating the processing of emotions in depressed patients reported impairments in the decoding of negative emotions. However, these studies adopted static stimuli (mostly stereotypical facial expressions corresponding to basic emotions) which do not reflect the way people experience emotions in everyday life. For this reason, this work proposes to investigate the decoding of emotional expressions in patients affected by Recurrent Major Depressive Disorder (RMDDs) using dynamic audio/video stimuli. RMDDs’ performance is compared with the performance of patients with Adjustment Disorder with Depressed Mood (ADs) and healthy (HCs) subjects. The experiments involve 27 RMDDs (16 with acute depression - RMDD-A, and 11 in a compensation phase - RMDD-C), 16 ADs and 16 HCs. The ability to decode emotional expressions is assessed through an emotion recognition task based on short audio (without video), video (without audio) and audio/video clips. The results show that AD patients are significantly less accurate than HCs in decoding fear, anger, happiness, surprise and sadness. RMDD-As with acute depression are significantly less accurate than HCs in decoding happiness, sadness and surprise. Finally, no significant differences were found between HCs and RMDD-Cs in a compensation phase. The different communication channels and the types of emotion play a significant role in limiting the decoding accuracy.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Vinciarelli, Professor Alessandro |
| Authors: | Scibelli, F., Troncone, A., Likforman-Sulem, L., Vinciarelli, A., and Esposito, A. |
| College/School: | College of Science and Engineering > School of Computing Science |
| Journal Name: | Frontiers in ICT |
| Publisher: | Frontiers Media |
| ISSN: | 2297-198X |
| ISSN (Online): | 2297-198X |
| Published Online: | 08 August 2016 |
| Copyright Holders: | Copyright © 2016 Scibelli, Troncone, Likforman-sulem, Vinciarelli and Esposito |
| First Published: | First published in Frontiers in ICT 3:16 |
| Publisher Policy: | Reproduced under a Creative Commons License |
| Related URLs: |
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