Rejecting probability summation for radial frequency patterns, not so Quick!

Baldwin, Alex S.; Schmidtmann, Gunnar; Kingdom, Frederick A. A.; Hess, Robert F.

doi:10.1016/j.visres.2016.03.003

Cited by 17 publications

(67 citation statements)

References 59 publications

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“…Although there is variation in the data, our results are consistent with Baldwin et al (2016) and with other work from our lab, which suggests no change in psychometric slopes with an increase in the number of cycles of modulation.…”

Section: Resultssupporting

confidence: 91%

“…Previous studies have used high threshold theory (HTT) to provide an estimate of probability summation; however, evidence from Baldwin et al (2016) has suggested this is an inappropriate method for RF patterns. We have included it here to provide a comparison with previous works.…”

Section: Methodsmentioning

confidence: 99%

“…The number of channels included (Q) in estimates of probability summation under SDT have a large effect on the resulting predicted strength of integration. Previous research by Cribb, Badcock, Maybery, and Badcock (2016) has used both a ''low'' and ''high'' number of channels to provide an ultra-conservative estimate (low number of channels; Q ¼ 3; and consistent with Baldwin et al, 2016) and a more theoretically appropriate estimate (high number of channels; Q ¼ 120). The same method will be employed by the current study.…”

Section: Methodsmentioning

confidence: 99%

“…Detection and discrimination of objects are important functions of the visual system, but not all objects within a scene are freely visible. Previous research has suggested that spatial disruption of contour information of a simple shape increases that shape's thresholds for detection (Hess, Wang, & Dakin, 1999;Loffler, Wilson, & Wilkinson, 2003) and that information cannot be integrated across discrete shapes (Baldwin, Schmidtmann, Kingdom, & Hess, 2016). It has been suggested that spatiotemporally tuned cells enable us to combine form information when an object moves behind a stationary slit (Burr & Ross, 2004) and indeed object recognition is easy under these circumstances (Yin, Shimojo, Moore, & Engel, 2002).…”

Section: Introductionmentioning

confidence: 99%

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The effect of spatiotemporal displacement on the integration of shape information

2018

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Within a natural scene it is not uncommon for an object's shape to be revealed over time. We investigated whether the same integration of shape information that happens around a fully visible contour also happens when that information is distributed over time. In a two-interval forced-choice task, observers discriminated between a radial frequency (RF) pattern and a circle that were revealed either using an implicit slit or traced out by a dot's motion; and a line and a modulated line that were either contour-defined or motion-defined. First, with presentation times of approximately 1 s, we found no difference in the strength of integration when comparing a freely visible contour to one that (a) moved behind a slit; (b) was revealed by a moving slit; or (c) revealed piecemeal by a slit appearing at random locations (Experiment 1). Changing the duration of presentation (250-4,000 ms) had no effect on strength of integration or threshold for detection within the moving slit condition (Experiment 2). Considering these results, Experiment 3 revisited integration for a dot tracing out an RF path (Or, Thabet, Wilkinson, & Wilson, 2011), finding removal of a change in speed cue increased the strength of integration to that found in Experiments 1 and 2 of the current study. The pattern of results for modulated lines was different from RF patterns; however, within these conditions, there was no difference in strength of integration between contour-defined and motion-defined stimuli. Our results suggest motion-defined patterns are processed as form from motion.

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Section: Resultssupporting

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The effect of spatiotemporal displacement on the integration of shape information

2018

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confidence: 99%

Convergent evidence for global processing of shape

2018

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There is an ongoing debate over whether there is convincing evidence in support of global contour integration in shape discrimination tasks, particularly when using radial frequency (RF) patterns as stimuli (Baldwin, Schmidtmann, Kingdom, & Hess, 2016). The objection lies in the previous use of high-threshold theory (HTT), rather than signal detection theory (SDT) to model the probability summation estimates of observer thresholds to determine whether integration of information is occurring around the contour. Here we used a discrimination at threshold method to establish evidence of global processing of two frequently used RF patterns (RF3 and RF5) that does not require mathematical modeling. To provide a bridge between current and past research we examined the two proposed methods, finding that HTT produced probability summation estimates that were more conservative than SDT (when an appropriate number of channels was used to generate estimates). We found no difference in observer thresholds when an RF pattern was presented as the only test stimulus in a block of trials or when two RF patterns were interleaved, and no evidence for a decrease in psychometric slopes with increasing numbers of stimulus elements. These findings are contrary to what is predicted by SDT for a stimulus whose detection conforms to probability summation. Therefore, our results find no evidence that supports probability summation, further demonstrating the importance of using random phase RF patterns while measuring integration around a contour and providing strong evidence for global shape processing around low frequency RF patterns.

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Nothing more than a pair of curvatures: A common mechanism for the detection of both radial and non-radial frequency patterns

Schmidtmann

Kingdom

2017

Vision Research

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Radial frequency (RF) patterns, which are sinusoidal modulations of a radius in polar coordinates, are commonly used to study shape perception. Previous studies have argued that the detection of RF patterns is either achieved globally by a specialized global shape mechanism, or locally using as cue the maximum tangent orientation difference between the RF pattern and the circle. Here we challenge both ideas and suggest instead a model that accounts not only for the detection of RF patterns but also for line frequency patterns (LF), i.e. contours sinusoidally modulated around a straight line. The model has two features. The first is that the detection of both RF and LF patterns is based on curvature differences along the contour. The second is that this curvature metric is subject to what we term the Curve Frequency Sensitivity Function, or CFSF, which is characterized by a flat followed by declining response to curvature as a function of modulation frequency, analogous to the modulation transfer function of the eye. The evidence that curvature forms the basis for detection is that at very low modulation frequencies (1-3 cycles for the RF pattern) there is a dramatic difference in thresholds between the RF and LF patterns, a difference however that disappears at medium and high modulation frequencies. The CFSF feature on the other hand explains why thresholds, rather than continuously declining with modulation frequency, asymptote at medium and high modulation frequencies. In summary, our analysis suggests that the detection of shape modulations is processed by a common curvature-sensitive mechanism that is subject to a shape-frequency-dependent transfer function. This mechanism is independent of whether the modulation is applied to a circle or a straight line.

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Rejecting probability summation for radial frequency patterns, not so Quick!

Cited by 17 publications

References 59 publications

The effect of spatiotemporal displacement on the integration of shape information

The effect of spatiotemporal displacement on the integration of shape information

Convergent evidence for global processing of shape

Nothing more than a pair of curvatures: A common mechanism for the detection of both radial and non-radial frequency patterns

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