Neural computations in prosopagnosia.

We report an investigation of the neural processes involved in the processing of faces and objects of brain-lesioned patient PS, a well-documented case of pure acquired prosopagnosia. We gathered a substantial dataset of high-density electrophysiological recordings from both PS and neurotypicals. Using representational similarity analysis, we produced time-resolved brain representations in a format that facilitates direct comparisons across time points, different individuals, and computational models. To understand how the lesions in PS's ventral stream affect the temporal evolution of her brain representations, we computed the temporal generalization of her brain representations. We uncovered that PS's early brain representations exhibit an unusual similarity to later representations, implying an excessive generalization of early visual patterns. To reveal the underlying computational deficits, we correlated PS' brain representations with those of deep neural networks (DNN). We found that the computations underlying PS' brain activity bore a closer resemblance to early layers of a visual DNN than those of controls. However, the brain representations in neurotypicals became more akin to those of the later layers of the model compared to PS. We confirmed PS's deficits in high-level brain representations by demonstrating that her brain representations exhibited less similarity with those of a DNN of semantics.

Decoding face recognition abilities in the human brain.

Why are some individuals better at recognizing faces? Uncovering the neural mechanisms supporting face recognition ability has proven elusive. To tackle this challenge, we used a multimodal data-driven approach combining neuroimaging, computational modeling, and behavioral tests. We recorded the high-density electroencephalographic brain activity of individuals with extraordinary face recognition abilities-super-recognizers-and typical recognizers in response to diverse visual stimuli. Using multivariate pattern analyses, we decoded face recognition abilities from 1 s of brain activity with up to 80% accuracy. To better understand the mechanisms subtending this decoding, we compared representations in the brains of our participants with those in artificial neural network models of vision and semantics, as well as with those involved in human judgments of shape and meaning similarity. Compared to typical recognizers, we found stronger associations between early brain representations of super-recognizers and midlevel representations of vision models as well as shape similarity judgments. Moreover, we found stronger associations between late brain representations of super-recognizers and representations of the artificial semantic model as well as meaning similarity judgments. Overall, these results indicate that important individual variations in brain processing, including neural computations extending beyond purely visual processes, support differences in face recognition abilities. They provide the first empirical evidence for an association between semantic computations and face recognition abilities. We believe that such multimodal data-driven approaches will likely play a critical role in further revealing the complex nature of idiosyncratic face recognition in the human brain.

Diagnostic Features for Human Categorisation of Adult and Child Faces.

Knowing how humans differentiate children from adults has useful implications in many areas of both forensic and cognitive psychology. Yet, how we extract age from faces has been surprisingly underexplored in both disciplines. Here, we used a novel data-driven experimental technique to objectively measure the facial features human observers use to categorise child and adult faces. Relying on more than 35,000 trials, we used a reverse correlation technique that enabled us to reveal how specific features which are known to be important in face-perception - position, spatial-frequency (SF), and orientation - are associated with accurate child and adult discrimination. This showed that human observers relied on evidence in the nasal bone and eyebrow area for accurate adult categorisation, while they relied on the eye and jawline area to accurately categorise child faces. For orientation structure, only facial information of vertical orientation was linked to face-adult categorisation, while features of horizontal and, to a lesser extent oblique orientations, were more diagnostic of a child face. Finally, we found that SF diagnosticity showed a U-shaped pattern for face-age categorisation, with information in low and high SFs being diagnostic of child faces, and mid SFs being diagnostic of adult faces. Through this first characterisation of the facial features of face-age categorisation, we show that important information found in psychophysical studies of face-perception in general (i.e., the eye area, horizontals, and mid-level SFs) is crucial to the practical context of face-age categorisation, and present data-driven procedures through which face-age classification training could be implemented for real-world challenges.

Abnormal visual representations associated with confusion of perceived facial expression in schizophrenia with social anxiety disorder.

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.

Inducing the use of right eye enhances face-sex categorization performance.

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 technique-bubbles-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. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Stationary Objects Flashed Periodically Appear to Move During Smooth Pursuit Eye Movement.

We discovered that a white disc flashed twice at the same location appears to move during smooth pursuit eye tracking in the direction opposite to that of the eye movement. We called this novel phenomenon movement-induced apparent motion (MIAM). Using the method of constant stimuli, we measured the required displacement of the second appearance of the disc in the pursuit direction to null the effect during the closed-loop stage of smooth pursuit eye tracking. We observed a strong linear relationship between the points of subjective stationarity and the inter-stimuli intervals for four smooth pursuit eye movement speeds. The slopes and y-intercepts of these linear fits were well predicted by the hypothesis according to which subjects saw illusory motion from the first to the second retinal projections of the flashed disc during smooth pursuit eye movement, with no extra-retinal signal compensation.