Adaptation to implied tilt: extensive spatial extrapolation of orientation gradients

Abstract

To extract the global structure of an image, the visual system must integrate local orientation estimates across space. Progress is being made toward understanding this integration process, but very little is known about whether the presence of structure exerts a reciprocal influence on local orientation coding. We have previously shown that adaptation to patterns containing circular or radial structure induces tilt-aftereffects (TAEs), even in locations where the adapting pattern was occluded. These spatially "remote" TAEs have novel tuning properties and behave in a manner consistent with adaptation to the local orientation implied by the circular structure (but not physically present) at a given test location. Here, by manipulating the spatial distribution of local elements in noisy circular textures, we demonstrate that remote TAEs are driven by the extrapolation of orientation structure over remarkably large regions of visual space (more than 20°). We further show that these effects are not specific to adapting stimuli with polar orientation structure, but require a gradient of orientation change across space. Our results suggest that mechanisms of visual adaptation exploit orientation gradients to predict the local pattern content of unfilled regions of space.

Keywords: adaptation; cortical plasticity; orientation; psychological; texture analysis; tilt aftereffect.

Figure 1

Measuring the spatial specificity of the remote TAE. (A) Example of a test stimulus, oriented clockwise of vertical and positioned above and to the right of the fixation dot. (B) Noisy concentric adapting stimulus comprising signal and noise elements randomly distributed throughout the texture pattern (“intermixed” condition). (C) Concentric adapting stimulus with all noise elements restricted to the space surrounding the test location (“proximal noise” condition). (D) Concentric adapting stimulus with all signal elements surrounding the test location (“distal noise” condition).

Figure 2

Spatially remote TAEs-induced by adaptation to noisy concentric texture patterns with different spatial configurations. Points of subjective equality are plotted as a function of signal to noise ratio for three individual observers. Black filled symbols represent performance where randomly oriented noise elements were distributed across the texture pattern (see Figure 1B). Red and blue symbols represent performance when noise elements were positioned inside (Figure 1C) or outside (Figure 1D) an annular region surrounding the test site, respectively. Unadapted (baseline) performance is shown by the unfilled black symbol. Error bars indicate ± 1 standard error.

Figure 3

Inducing spatially remote TAEs with orientation gradients. (A) Smoothly varying orientation textures are shown, where structure is defined by a linear change in orientation as a function of either the horizontal (x) or vertical position (y). In each stimulus, the underlying orientation gradient is anchored about the test location (center of noisy annulus), ensuring that the implied orientation at that position is constant (15° counter-clockwise of vertical). (B) Orientation textures containing reflectional symmetry. Textures with linear orientation gradients along the x and y axes contain symmetry about the horizontal and vertical meridians, respectively.

Figure 4

Orientation gradient tuning of spatially remote TAEs. PSEs for each observer are plotted as a function of the rate of change of orientation in the adapting texture across space, applied either in the horizontal (green symbols) or vertical (purple symbols) dimension. Unfilled and filled symbols indicate conditions with and without reflective symmetry applied around the horizontal or vertical meridian (see General Methods for details). Error bars indicate ± 1 standard error.

Figure 5

Manipulating the smoothness of an orientation gradient via quantization of orientation within discrete spatial bands. Each of the textures shown contain an constant linear change in orientation as a function of horizontal position, but have been quantized within bands measuring (A) 4° (B) 8°, or (C) 12°. Within each band all texture elements have a constant orientation, determined by space-averaging the underlying orientation gradient.

Figure 6

Effect of quantizing the orientation gradient within the adapting texture. PSEs are plotted as a function of the width of each spatial bin, within which all texture elements were assigned a fixed orientation (filled symbols). The upper scale shows the corresponding orientation resolution, defined as the change in orientation between successive spatial bands. For comparison, unfilled symbols indicate performance in the absence of adaptation. Error bars indicate ± 1 standard error.