Several recent studies have used radial frequency patterns to investigate intermediate-level shape perception, a critical precursor to object recognition. Here, we developed the first neural model of RF perception based on known V4 properties that exhibits many of the characteristics of human RF perception. The model is composed of two main parts: (1) recovery of object position using large-scale non-Fourier V4-like concentric units that respond at the center of concentric contour segments across orientations, and (2) curvature detectors that encode local shape information. Each curvature mechanism combines multiplicatively the responses of three oriented filters, the positions and orientation preferences of which determine the curvature mechanism's tuning properties for position, orientation, and degree of curvature. When responding to RF patterns, peak responses occur at points of maximum curvature. Shape is represented as curvature responses as a function of orientation around the object center, and the cross-correlation of that function with a sine wave peaks when the frequency of the sine wave matches the number of peaks in the stimulus. Cross-correlation strength can be used to model human performance. Model and human performance are comparable for detection, identification, and lateral masking tasks. Moreover, the model also shows size invariance of detection performance due to scaling of the curvature mechanisms. The model is then used to make novel predictions.

Davis and Driver presented evidence suggesting that Kanizsa-type subjective contours could be detected in a visual search task in a time that is independent of the number of nonsubjective contour distractors. A linking connection was made between these psychophysical data and the physiological data of Peterhans and von der Heydt which showed that cells in primate area V2 respond to subjective contours in the same way that they respond to luminance-defined contours. Here in three experiments it is shown that there was sufficient information in the displays used by Davis and Driver to support parallel search independently of whether subjective contours were present or not. When confounding properties of the stimuli were eliminated search became slow whether or not subjective contours were present in the display. One of the slowest search conditions involved stimuli that were virtually identical to those used in the physiological studies of Peterhans and von der Heydt to which Davis and Driver wish to link their data. It is concluded that while subjective contours may be represented in the responses of very early visual mechanisms (eg in V2) access to these representations is impaired by high-contrast contours used to induce the subjective contours and nonsubjective figure distractors. This persistent control problem continues to confound attempts to show that Kanizsa-type subjective contours can be detected in parallel.

Symmetry is usually computationally expensive to encode reliably, and yet it is relatively effortless to perceive. Here, we extend F. J. A. M. Poirier and H. R. Wilson's (2006) model for shape perception to account for H. R. Wilson and F. Wilkinson's (2002) data on shape symmetry. Because the model already accounts for shape perception, only minimal neural circuitry is required to enable it to encode shape symmetry as well. The model is composed of three main parts: (1) recovery of object position using large-scale non-Fourier V4-like concentric units that respond at the center of concentric contour segments across orientations, (2) around that recovered object center, curvature mechanisms combine multiplicatively the responses of oriented filters to encode object-centric local shape information, with a preference for convexities, and (3) object-centric symmetry mechanisms. Model and human performances are comparable for symmetry perception of shapes. Moreover, with some improvement of edge recovery, the model can encode symmetry axes in natural images such as faces.

Background Lack of awareness of cognitive decline (ACD) is common in late-stage Alzheimer’s disease (AD). Recent studies showed that ACD can also be reduced in the early stages. Methods We described different trends of evolution of ACD over 3 years in a cohort of memory-complainers and their association to amyloid burden and brain metabolism. We studied the impact of ACD at baseline on cognitive scores’ evolution and the association between longitudinal changes in ACD and in cognitive score. Results 76.8% of subjects constantly had an accurate ACD (reference class). 18.95% showed a steadily heightened ACD and were comparable to those with accurate ACD in terms of demographic characteristics and AD biomarkers. 4.25% constantly showed low ACD, had significantly higher amyloid burden than the reference class, and were mostly men. We found no overall effect of baseline ACD on cognitive scores’ evolution and no association between longitudinal changes in ACD and in cognitive scores. Conclusions ACD begins to decrease during the preclinical phase in a group of individuals, who are of great interest and need to be further characterized. Trial registration The present study was conducted as part of the INSIGHT-PreAD study. The identification number of INSIGHT-PreAD study (ID-RCB) is 2012-A01731-42.

Object perception uses a variety of visual cues, including shape cues derived from sides and convexities. Two recent masking studies using radial frequency patterns have argued, respectively, for a predominant role of convexity [Habak, C., Wilkinson, F., Zakher, B., & Wilson, H. R. (2004). Curvature population coding for complex shapes in human vision. Vision Research, 44 (24), 2815-2823] or side information [Hess, R. F., Wang, Y. -Z., & Dakin, S. C. (1999). Are judgements of circularity local or global? Vision Research, 39, 4354-4360]. Here we resolve the controversy by separating the masks into their parts (e.g., convexities and sides), and measuring the relative masking influences of the different mask components. We found that both side and convexity information contribute to masking. However, masking due to side information was much less dependent on alignment compared to masking due to convexities. This supports a theory where convexities constitute a prime source of information for shape processing, and sides do also contribute but to a smaller extent.