Project description DEENESFRITPL Understanding emotion recognition using statistical learning Some emotions are harder to recognise than others and some individuals, such as those with autism spectrum disorder (ASD), simply find it more difficult to recognise emotions generally. The EU-funded LearningEmotions project will explore whether the two phenomena may arise from a common source, that is, difficulties with learning patterns and their associations (i.e. statistical learning). The project will quantify the variability of cues used to signal emotions from an audio-visual emotion database to compare whether difficult-to-recognise emotions have less consistent patterns than emotions that are easier to recognise. The project will also compare individuals with and without ASD on their ability to recognise emotions and learn patterns to see if the two abilities are related using behavioural and neural methods. Show the project objective Hide the project objective Objective Statistical learning refers to the ability to learn through the discovery of patterns and structures. I propose to investigate emotion recognition using a statistical learning perspective in order to understand (i) why some emotions are harder to recognise than others; and (ii) why individuals with autism spectrum disorder (ASD individuals) have more difficulty recognising emotions than neurotypicals (i.e. individuals without autism).I argue that part of the difficulty in recognising certain emotions lies in how reliable or consistent the auditory and visual cues are in signalling the emotion. That is, if particular cues consistently signal or have a high probability of signalling an emotion (e.g. 'happy' is consistently signaled by squinty eyes and grin/smile), then that emotion would be easier to recognise than emotions that are signalled by inconsistent cues (e.g. sarcasm may have varied expressions depending on the individual, context, etc. and so sarcasm would be more difficult to recognise). To investigate this, I will use an audio-visual emotion database that is currently under development to quantify the variability of cues across speakers in signalling the intended emotion.I propose that the difficulty ASD individuals have with recognising emotions lies in a general difficulty with consolidating probabilistic information. In terms of emotion recognition, this would manifest as a difficulty with making a correct inference of the intended emotion given particular cues, which vary in their probabilities in signalling the emotion. To investigate this hypothesis, I will conduct a behavioural and a neural experiment comparing ASD individuals with neurotypicals on probabilistic learning to determine whether group differences exist and whether probabilistic learning is related to emotion recognition.Outcomes of this project may inform intervention practices for ASD individuals and provide a general framework of understanding other ASD characteristics. Fields of science natural sciencescomputer and information sciencesdatabases Keywords autism statistical learning probabilistic learning emotion Programme(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Topic(s) MSCA-IF-2019 - Individual Fellowships Call for proposal H2020-MSCA-IF-2019 See other projects for this call Funding Scheme MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinator THE UNIVERSITY OF READING Net EU contribution € 212 933,76 Address WHITEKNIGHTS CAMPUS WHITEKNIGHTS HOUSE RG6 6AH Reading United Kingdom See on map Region South East (England) Berkshire, Buckinghamshire and Oxfordshire Berkshire Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 212 933,76
