Atypical neural encoding of faces in individuals with autism spectrum disorder.

Individuals with autism spectrum disorder (ASD) experience pervasive difficulties in processing social information from faces. However, the behavioral and neural mechanisms underlying social trait judgments of faces in ASD remain largely unclear. Here, we comprehensively addressed this question by employing functional neuroimaging and parametrically generated faces that vary in facial trustworthiness and dominance. Behaviorally, participants with ASD exhibited reduced specificity but increased inter-rater variability in social trait judgments. Neurally, participants with ASD showed hypo-activation across broad face-processing areas. Multivariate analysis based on trial-by-trial face responses could discriminate participant groups in the majority of the face-processing areas. Encoding social traits in ASD engaged vastly different face-processing areas compared to controls, and encoding different social traits engaged different brain areas. Interestingly, the idiosyncratic brain areas encoding social traits in ASD were still flexible and context-dependent, similar to neurotypicals. Additionally, participants with ASD also showed an altered encoding of facial saliency features in the eyes and mouth. Together, our results provide a comprehensive understanding of the neural mechanisms underlying social trait judgments in ASD.

A critical period for developing face recognition.

Face learning has important critical periods during development. However, the computational mechanisms of critical periods remain unknown. Here, we conducted a series of in silico experiments and showed that, similar to humans, deep artificial neural networks exhibited critical periods during which a stimulus deficit could impair the development of face learning. Face learning could only be restored when providing information within the critical period, whereas, outside of the critical period, the model could not incorporate new information anymore. We further provided a full computational account by learning rate and demonstrated an alternative approach by knowledge distillation and attention transfer to partially recover the model outside of the critical period. We finally showed that model performance and recovery were associated with identity-selective units and the correspondence with the primate visual systems. Our present study not only reveals computational mechanisms underlying face learning but also points to strategies to restore impaired face learning.

A preference to look closer to the eyes is associated with a position-invariant face neural code.

When looking at faces, humans invariably move their eyes to a consistent preferred first fixation location on the face. While most people have the preferred fixation location just below the eyes, a minority have it between the nose-tip and mouth. Not much is known about whether these long-term differences in the preferred fixation location are associated with distinct neural representations of faces. To study this, we used a gaze-contingent face adaptation aftereffect paradigm to test in two groups of observers, one with their mean preferred fixation location closer to the eyes (upper lookers) and the other closer to the mouth (lower lookers). In this task, participants were required to maintain their gaze at either their own group's mean preferred fixation location or that of the other group during adaptation and testing. The two possible fixation locations were 3.6° apart on the face. We measured the face adaptation aftereffects when the adaptation and testing happened while participants maintained fixation at either the same or different locations on the face. Both groups showed equally strong adaptation effects when the adaptation and testing happened at the same fixation location. Crucially, only the upper lookers showed a partial transfer of the FAE across the two fixation locations, when adaptation occurred at the eyes. Lower lookers showed no spatial transfer of the FAE irrespective of the adaptation position. Given the classic finding that neural tuning is increasingly position invariant as one moves higher in the visual hierarchy, this result suggests that differences in the preferred fixation location are associated with distinct neural representations of faces.

Peripheral facial features guiding eye movements and reducing fixational variability.

Face processing is a fast and efficient process due to its evolutionary and social importance. A majority of people direct their first eye movement to a featureless point just below the eyes that maximizes accuracy in recognizing a person's identity and gender. Yet, the exact properties or features of the face that guide the first eye movements and reduce fixational variability are unknown. Here, we manipulated the presence of the facial features and the spatial configuration of features to investigate their effect on the location and variability of first and second fixations to peripherally presented faces. Our results showed that observers can utilize the face outline, individual facial features, and feature spatial configuration to guide the first eye movements to their preferred point of fixation. The eyes have a preferential role in guiding the first eye movements and reducing fixation variability. Eliminating the eyes or altering their position had the greatest influence on the location and variability of fixations and resulted in the largest detriment to face identification performance. The other internal features (nose and mouth) also contribute to reducing fixation variability. A subsequent experiment measuring detection of single features showed that the eyes have the highest detectability (relative to other features) in the visual periphery providing a strong sensory signal to guide the oculomotor system. Together, the results suggest a flexible multiple-cue approach that might be a robust solution to cope with how the varying eccentricities in the real world influence the ability to resolve individual feature properties and the preferential role of the eyes.

Eye movement strategies in face ethnicity categorization vs. face identification tasks.

A quick look at a face allows us to identify the person, their gender, and emotion. Humans direct their first eye movement towards points on the face that vary moderately across these common tasks and maximize performance. However, not known is the extent to which humans alter their oculomotor strategies to maximize accuracy in more specialized face categorization tasks. We studied the eye movements of Indian observers during a North vs. South Indian face categorization task and compared them to those in a person-identification task. We found that observers did not alter their first eye movement strategy for the ethnic categorization task, i.e., they directed their first fixations to a similar preferred point as in the person-identification task. To assess whether using a similar preferred point of fixation for both tasks resulted in a performance cost for the categorization task, we measured performance as a function of fixation position along the face. Fixating away from the preferred point of fixation reduced observer performance in the person identification task, but not in the ethnicity categorization task. We used computational modeling to assess whether the results could be explained by an interaction between the distribution of task information across the face and the foveated properties of the visual system. A foveated ideal observer analysis revealed a spatially more distributed task information and lower dependence of performance on the point of fixation for the ethnicity categorization task relative to the person identification. We conclude that, unlike the person identification task, humans can access the information for the ethnicity categorization task from various points of fixation. Thus, the observer strategy to utilize the typical person identification first eye movement for the ethnicity categorization task is a simple solution that incurs little or no performance cost.