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.

Initial eye gaze to faces and its functional consequence on face identification abilities in autism spectrum disorder.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder defined and diagnosed by core deficits in social communication and the presence of restricted and repetitive behaviors. Research on face processing suggests deficits in this domain in ASD but includes many mixed findings regarding the nature and extent of these differences. The first eye movement to a face has been shown to be highly informative and sufficient to achieve high performance in face identification in neurotypical adults. The current study focused on this critical moment shown to be essential in the process of face identification. METHODS: We applied an established eye-tracking and face identification paradigm to comprehensively characterize the initial eye movement to a face and test its functional consequence on face identification performance in adolescents with and without ASD (n = 21 per group), and in neurotypical adults. Specifically, we presented a series of faces and measured the landing location of the first saccade to each face, while simultaneously measuring their face identification abilities. Then, individuals were guided to look at specific locations on the face, and we measured how face identification performance varied as a function of that location. Adolescent participants also completed a more traditional measure of face identification which allowed us to more fully characterize face identification abilities in ASD. RESULTS: Our results indicate that the location of the initial look to faces and face identification performance for briefly presented faces are intact in ASD, ruling out the possibility that deficits in face perception, at least in adolescents with ASD, begin with the initial eye movement to the face. However, individuals with ASD showed impairments on the more traditional measure of face identification. CONCLUSION: Together, the observed dissociation between initial, rapid face perception processes, and other measures of face perception offers new insights and hypotheses related to the timing and perceptual complexity of face processing and how these specific aspects of face identification may be disrupted in ASD.

Domain Specificity of Oculomotor Learning after Changes in Sensory Processing.

Humans visually process the world with varying spatial resolution and can program their eye movements optimally to maximize information acquisition for a variety of everyday tasks. Diseases such as macular degeneration can change visual sensory processing, introducing central vision loss (a scotoma). However, humans can learn to direct a new preferred retinal location to regions of interest for simple visual tasks. Whether such learned compensatory saccades are optimal and generalize to more complex tasks, which require integrating information across a large area of the visual field, is not well understood. Here, we explore the possible effects of central vision loss on the optimal saccades during a face identification task, using a gaze-contingent simulated scotoma. We show that a new foveated ideal observer with a central scotoma correctly predicts that the human optimal point of fixation to identify faces shifts from just below the eyes to one that is at the tip of the nose and another at the top of the forehead. However, even after 5000 trials, humans of both sexes surprisingly do not change their initial fixations to adapt to the new optimal fixation points to faces. In contrast, saccades do change for tasks such as object following and to a lesser extent during search. Our findings argue against a central brain motor-compensatory mechanism that generalizes across tasks. They instead suggest task specificity in the learning of oculomotor plans in response to changes in front-end sensory processing and the possibility of separate domain-specific representations of learned oculomotor plans in the brain.SIGNIFICANCE STATEMENT The mechanism by which humans adapt eye movements in response to central vision loss is still not well understood and carries importance for gaining a fundamental understanding of brain plasticity. We show that although humans adapt their eye movements for simpler tasks such as object following and search, these adaptations do not generalize to more complex tasks such as face identification. We provide the first computational model to predict where humans with central vision loss should direct their eye movements in face identification tasks, which could become a critical tool in making patient-specific recommendations. Based on these results, we suggest a novel theory for oculomotor learning: a distributed representation of learned eye-movement plans represented in domain-specific areas of the brain.