Coding of low-level position and orientation information in human naturalistic vision

Orientation and position of small image segments are considered to be two fundamental low-level attributes in early visual processing, yet their encoding in complex natural stimuli is underexplored. By measuring the just-noticeable differences in noise perturbation, we investigated how orientation and position information of a large number of local elements (Gabors) were encoded separately or jointly. Importantly, the Gabors composed various classes of naturalistic stimuli that were equated by all low-level attributes and differed only in their higher-order configural complexity and familiarity. Although unable to consciously tell apart the type of perturbation, observers detected orientation and position noise significantly differently. Furthermore, when the Gabors were perturbed by both types of noise simultaneously, performance adhered to a reliability-based optimal probabilistic combination of individual attribute noises. Our results suggest that orientation and position are independently coded and probabilistically combined for naturalistic stimuli at the earliest stage of visual processing.