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Training Emotion Recognition Accuracy: Results for Multimodal Expressions and Facial Micro Expressions.

ABSTRACT: Nonverbal emotion recognition accuracy (ERA) is a central feature of successful communication and interaction, and is of importance for many professions. We developed and evaluated two ERA training programs-one focusing on dynamic multimodal expressions (audio, video, audio-video) and one focusing on facial micro expressions. Sixty-seven subjects were randomized to one of two experimental groups (multimodal, micro expression) or an active control group (emotional working memory task). Participants trained once weekly with a brief computerized training program for three consecutive weeks. Pre-post outcome measures consisted of a multimodal ERA task, a micro expression recognition task, and a task about patients' emotional cues. Post measurement took place approximately a week after the last training session. Non-parametric mixed analyses of variance using the Aligned Rank Transform were used to evaluate the effectiveness of the training programs. Results showed that multimodal training was significantly more effective in improving multimodal ERA compared to micro expression training or the control training; and the micro expression training was significantly more effective in improving micro expression ERA compared to the other two training conditions. Both pre-post effects can be interpreted as large. No group differences were found for the outcome measure about recognizing patients' emotion cues. There were no transfer effects of the training programs, meaning that participants only improved significantly for the specific facet of ERA that they had trained on. Further, low baseline ERA was associated with larger ERA improvements. Results are discussed with regard to methodological and conceptual aspects, and practical implications and future directions are explored.

SUBMITTER: Dollinger L

PROVIDER: S-EPMC8406528 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:During real-life interactions, facial expressions of emotion are perceived dynamically with multimodal sensory information. In the absence of auditory sensory channel inputs, it is unclear how facial expressions are recognised and internally represented by deaf individuals. Few studies have investigated facial expression recognition in deaf signers using dynamic stimuli, and none have included all six basic facial expressions of emotion (anger, disgust, fear, happiness, sadness, and surprise) with stimuli fully controlled for their low-level visual properties, leaving the question of whether or not a dynamic advantage for deaf observers exists unresolved. We hypothesised, in line with the enhancement hypothesis, that the absence of auditory sensory information might have forced the visual system to better process visual (unimodal) signals, and predicted that this greater sensitivity to visual stimuli would result in better recognition performance for dynamic compared to static stimuli, and for deaf-signers compared to hearing non-signers in the dynamic condition. To this end, we performed a series of psychophysical studies with deaf signers with early-onset severe-to-profound deafness (dB loss >70) and hearing controls to estimate their ability to recognize the six basic facial expressions of emotion. Using static, dynamic, and shuffled (randomly permuted video frames of an expression) stimuli, we found that deaf observers showed similar categorization profiles and confusions across expressions compared to hearing controls (e.g., confusing surprise with fear). In contrast to our hypothesis, we found no recognition advantage for dynamic compared to static facial expressions for deaf observers. This observation shows that the decoding of dynamic facial expression emotional signals is not superior even in the deaf expert visual system, suggesting the existence of optimal signals in static facial expressions of emotion at the apex. Deaf individuals match hearing individuals in the recognition of facial expressions of emotion.

Project description:BackgroundThe emotion recognition task (ERT) was developed to overcome shortcomings of static emotion recognition paradigms, by identifying more subtle deficits in emotion recognition across different intensity levels. In this study, we used the ERT to investigate emotion recognition deficits across the frontotemporal (FTD) and Alzheimer's Dementia (AD) spectrum.MethodsWith the ERT, we assessed the recognition of facial emotional expressions (anger-disgust-fear-happiness-sadness-surprise) across four intensities (40-60-80-100%) in patients with behavioural variant FTD (bvFTD; n = 32), and AD (n = 32), presymptomatic FTD mutation carriers (n = 47) and controls (n = 49). We examined group differences using multilevel linear regression with age, sex and education level as covariates, and performed post hoc analyses on presymptomatic (MAPT, GRN and C9orf72) mutation carriers. Classification abilities were investigated by means of logistic regression.ResultsLowest ERT total scores were found in patients with bvFTD and AD, whereas equal highest performance was found in presymptomatic mutation carriers and controls. For all emotions, significantly lower subscores were found in patients with bvFTD than in presymptomatic mutation carriers and in controls (highest p value = 0.025). Patients with bvFTD performed lower than patients with AD on anger (p = 0.005) and a trend towards significance was found for a lower performance on happiness (p = 0.065). Task performance increased with higher emotional intensity, and classification was better at the lowest than at the highest intensity. C9orf72 mutation carriers performed worse on recognizing anger at the lowest intensity than GRN mutation carriers (p = 0.047) and controls (p = 0.038). The ERT differentiated between patients with bvFTD and controls, and between patients with AD and controls (both p < 0.001).DiscussionOur results demonstrate emotion recognition deficits in both bvFTD and AD, and suggest the presence of subtle emotion recognition changes in presymptomatic C9orf72-FTD. This highlights the importance of incorporating emotion recognition paradigms into standard neuropsychological assessment for early differential diagnosis, and as clinical endpoints in upcoming therapeutic trials.

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Training Emotion Recognition Accuracy: Results for Multimodal Expressions and Facial Micro Expressions.

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