Detection and recognition of angular frequency patterns

Abstract

Previous research has extensively explored visual encoding of smoothly curved, closed contours described by sinusoidal variation of pattern radius as a function of polar angle (RF patterns). Although the contours of many biologically significant objects are curved, we also confront shapes with a more jagged and angular appearance. To study these, we introduce here a novel class of visual stimuli that deform smoothly from a circle to an equilateral polygon with N sides (AF patterns). Threshold measurements reveal that both AF and RF patterns can be discriminated from circles at the same deformation amplitude, approximately 18.0arcsec, which is in the hyperacuity range. Thresholds were slightly higher for patterns with 3.0 cycles than for those with 5.0 cycles. Discrimination between AF and RF patterns was 75% correct at an amplitude that was approximately 3.0 times the threshold amplitude, which implies that AF and RF patterns activate different neural populations. Experiments with jittered patterns in which the contour was broken into several pieces and shifted inward or outward had much less effect on AF patterns than on RF patterns. Similarly, thresholds for single angles of AF patterns showed no significant difference from thresholds for the entire AF pattern. Taken together, these results imply that the visual system incorporates angles explicitly in the representation of closed object contours, but it suggests that angular contours are represented more locally than are curved contours.

A Dorsal Visual Route Necessary for Global Form Perception: Evidence from Neuropsychological fMRI

“…Although our study did not test other stimuli related to local-global pattern processing, previous psychophysical studies have shown similar effects on localglobal pattern processing using different stimuli (e.g., radial frequency patterns; Habak, Wilkinson, Zakher, & Wilson, 2004;Wilkinson, Wilson, & Habak, 1998). Brain imaging studies on local-global tasks using other types of stimuli (Navon figures (Navon, 1977), parametrically degraded objects, etc.)…”

Discriminating facial expressions of emotion and its link with perceiving visual form in Parkinson's disease

“…Perceiving visual form initially requires accurate encoding of local orientation information, and then integrating separate features into global forms and segregating them from their backgrounds [42,67,69]. RF pattern discrimination is thought to tap intermediate stages of visual form processing [41], where separate features are pooled into global forms.…”

“…To investigate perception of visual form, we measured the ability to discriminate radial frequency (RF) patterns of varying modulations in amplitude from a perfect circle. RF patterns, first created by Wilkinson et al [67], are a family of smooth closed shapes that differ from each other and each from a perfect circle in a well-defined way: different patterns can be created by modulating the amplitude (affecting the sharpness or depth of the lobe), radial frequency (the number of lobes) and the orientation (the direction of the lobe). To investigate the link between the abilities to perceive visual form and facial expressions of emotion in PD, we correlated measures of discriminating RF3 patterns from perfect circles with measures of discriminating graded intensities of angry from neutral expressions.…”

Enhanced global integration of closed contours in individuals with high levels of autistic-like traits

“…Almeida et al (2010a) constructed a new visual search task using radial frequency (RF) patterns (see Section 2). RF patterns are created by deforming a circle through varying its radius sinusoidally as a function of polar angle, with the number of modulation cycles required to complete one revolution corresponding to the RF number (Wilkinson, Wilson, & Habak, 1998). These patterns were chosen because, like the simple target shape in the EFT, they are also closed contours, but they can be adjusted to evoke welldefined global or local closed-contour processing mechanisms (Bell & Badcock, 2009;Hess, Wang, & Dakin, 1999;Loffler, Wilson, & Wilkinson, 2003).…”