The oblique effect in orientation acuity

Abstract

We have examined the dependence of rotational acuity on the orientation bandwidth of a stimulus using two-dimensional, band-pass filtered, spatial noise. Stimuli had a bandwidth of 0.5 octave of spatial frequency, centred at 5.0 cyc/deg, and an orientation bandwidth that covered the range from 0.0 to 25.0 deg. Thresholds were obtained on one principal (vertical), and one oblique axis (45 deg). It was found that acuity declined on both axes as bandwidth increased, in a manner that was compatible with simple statistical principles with virtually perfect sampling of the image. There was some evidence that the intrinsic noise is greater on the oblique axis than on the vertical, and that oblique axes are less densely sampled than the principal axes. These differences are small and are insufficient, either on their own or taken together to explain the oblique effect.

An ecological approach to cognitive (im)penetrability

“…This anisotropy, which Appelle (1972) called the "oblique effect," has been found in a wide variety of perceptual tasks (Appelle 1972;Essock 1980;Howard 1982). The processes that generate the visual oblique effect seem to be multi-componential and occur at different levels of processing (for recent reviews, see Heeley et al 1997;Saarinen & Levi 1995). The visual oblique effect is consistent with the discontinuity thesis presented in Pylyshyn's target article.…”

The effects of sampling and internal noise on the representation of ensemble average size

“…1 (Beaudot & Mullen, 2005;Dakin, 2001;Dakin et al, 2009;Demanins et al, 1999;Heeley et al, 1997). This approach has been used successfully to estimate the internal noise and sample size for averageorientation processing (Beaudot & Mullen, 2005;Dakin, 2001;Heeley et al, 1997). In this model, the manner in which the average-size thresholds (σ obs ) increase as the external variability in sizes increases (σ ext ) can be determined by a summation of noise processes.…”

“…Our approach here was inspired by previous research in which variance summation modeling has been used to estimate the internal noise and efficiency (i.e., sample size) of texture discrimination mechanisms (Beaudot & Mullen, 2005;Dakin, 2001;Dakin, Bex, Cass, & Watt, 2009;Demanins, Hess, Williams, & Keeble, 1999;Heeley, Buchanan-Smith, Cromwell, & Wright, 1997). For the present case, a benefit of this approach is that, once generated, estimates of the internal noise affecting ensemble processing can be compared to behavioral estimates of the internal noise affecting individualobject processing to address the question of whether or not the internal noise for ensemble processing is lower than that for processing individual items.…”

Detection of shape orientation depends on salient axes of symmetry and elongation: Evidence from visual search

“…First, processing of line orientation in visual search or detection tasks is effortless, provided the orientations of the target and distractors are sufficiently different (e.g., Foster & Ward, 1991a, 1991bMarendaz, Stivalet, & Genon, 1991;Nothdurft, 1991). Second, orientation acuity is better for vertical or horizontal orientations than for oblique orientations, suggesting that horizontal and vertical are treated as reference orientations (Appelle, 1972;Heeley, Buchanan-Smith, Cromwell, & Wright, 1997;Orban, Vandenbussche,& Vogels, 1984;Vogels & Orban, 1985). Third, for orientations deviating by a small amount (about 20º) from the vertical, search for oriented lines shows an asymmetry: Search for a tilted target among vertical distractors is fast and accurate, whereas search for a vertical target among tilted distractors is slow and inefficient Cavanagh, Arguin, & Treisman, 1990;Foster & Ward, 1991a, 1991bMarendaz, 1998;Marendaz, Stivalet, Barraclough, & Walkowiac, 1993;Marendaz et al, 1991;Meigen, Lagreze, & Bach, 1994;Treisman, 1985;Treisman & Gormican, 1988).…”