Purchase this article with an account.
Greg Appelbaum, Vladimir Vildavski, Mark W. Pettet, Alex R. Wade, Anthony M. Norcia; Cortical networks underlying scene segmentation. Journal of Vision 2006;6(6):475. https://doi.org/10.1167/6.6.475.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
The segmentation of visual scenes into objects and their surrounds is a fundamental task that can be accomplished by the detection of spatial gradients in local cues such as luminance, texture, color, or temporal structure. To assess the cortical mechanisms underlying figure and background processing and to evaluate the role of boundary cues in segmentation, we constructed displays in which figure and background regions were separately ‘tagged’ with periodic modulations of their local texture elements. Textures were defined on orientation, phase (co-linearity), and temporal structure. Using these synthetic texture-defined objects and an electrophysiological paradigm that allows us to monitor figure-region, background-region, and border-specific activity separately in fMRI defined visual areas, we have found distinct neuronal networks for the processing of each surface and the formation of region boundaries. Figure activity was distributed over a network of ventral stream visual areas including the lateral occipital cortex. A separate network, extending from primary visual cortex through the dorsal visual pathway is observed in response to the background region. The activated sites and temporal sequence of these networks was largely invariant with respect to the cues used to define the figure. In contrast, responses related to non-linear figure-ground interaction (measured at the sum of the two tag frequencies) depended strongly on the cue type and, involved both first-tier (V1/V2/V3) and extra-striate areas. Cue-specific activity in several visual areas converges on the both dorsal and lateral occipital cortex where cue-invariant surface representations are formed.
This PDF is available to Subscribers Only