I compared various computational measures to quantify variability in audio-video recordings of emotion expression and found one measure in particular best fit human data. Essentially, this measure is computed by reducing the audio-visual clip of the expression into a matrix and determining its “center”. We do this for all the clips of the same emotion and obtain the center of the centers.
Across various tasks, we found that autistic individuals showed comparable statistical learning as non-autistic individuals when the cue-outcome associations are strong, but groups differences emerged when the associations are weak, with poorer performance among autistic individuals. Moreover, autistic individuals were more likely to incorporate feedback — even those that should be ignored because it is ‘noise’– to their subsequent decision, which may lead to differences in their performance on the weak cue-outcome associations.
In one emotion perception study conducted as part of the project, we found that autistic individuals who frequently encountered others wearing face coverings showed improvement in recognising emotions from just the eyes over a 10-month period during which there was a face covering mandate. This suggests that long-term passive exposure can modify our emotion perception ability. In another study, we found that autistic individuals did not differ from non-autistic individuals in recognising spoken and sung emotions, but autistic individuals were slower for some emotions, particularly those that involve the Theory of Mind or the ability to understand one’s mental states to infer their feelings or thoughts, which have been reported to be atypical among autistic individuals.
