No abstract

Face recognition ability varies tremendously among neurologically typical individuals. What causes these differences is still largely unknown. Here, we first used a data-driven experimental techniquebubbles-to measure the use of local facial information in 140 neurotypical individuals during a face-sex categorization task. We discovered that the use of the eye and eyebrow area located on the right side of the face image from the observer's viewpoint correlates positively with performance, whereas the use of the left-eye and eyebrow area correlates negatively with performance. We then tested if performance could be altered by inducing participants to use either the right-or the left-eye area. One hundred of these participants thus underwent a 1-hr session of a novel implicit training procedure aimed at inducing the use of specific facial information. Afterward, participants repeated the bubbles face-sex categorization task to assess the changes in use of information and its effect on performance. Participants that underwent right-eye induction used this facial region more than they initially did and, as expected, improved their performance more than the participants who underwent the left-eye induction. This is the first clear evidence of a causal link between the use of specific face information and face recognition ability: Use of right-eye region not only predicts but causes better face-sex categorization.

SummaryWe recorded a large dataset of high-density electroencephalographic signals and used a combination of behavioural tests and machine learning to characterise the brain computations covarying with face recognition in individuals with extraordinary abilities. We show that individual face recognition ability can be accurately decoded from brain activity in an extended temporal interval for face and non-face objects. We demonstrate that this decoding is supported by perceptual and semantic brain computations.

Deficits in social functioning are especially severe amongst schizophrenia individuals with the prevalent comorbidity of social anxiety disorder (SZ&SAD). Yet, the mechanisms underlying the recognition of facial expression of emotions—a hallmark of social cognition—are practically unexplored in SZ&SAD. Here, we aim to reveal the visual representations SZ&SAD (n = 16) and controls (n = 14) rely on for facial expression recognition. We ran a total of 30,000 trials of a facial expression categorization task with Bubbles, a data-driven technique. Results showed that SZ&SAD’s ability to categorize facial expression was impared compared to controls. More severe negative symptoms (flat affect, apathy, reduced social drive) was associated with more impaired emotion recognition ability, and with more biases in attributing neutral affect to faces. Higher social anxiety symptoms, on the other hand, was found to enhance the reaction speed to neutral and angry faces. Most importantly, Bubbles showed that these abnormalities could be explained by inefficient visual representations of emotions: compared to controls, SZ&SAD subjects relied less on fine facial cues (high spatial frequencies) and more on coarse facial cues (low spatial frequencies). SZ&SAD participants also never relied on the eye regions (only on the mouth) to categorize facial expressions. We discuss how possible interactions between early (low sensitivity to coarse information) and late stages of the visual system (overreliance on these coarse features) might disrupt SZ&SAD’s recognition of facial expressions. Our findings offer perceptual mechanisms through which comorbid SZ&SAD impairs crucial aspects of social cognition, as well as functional psychopathology.