Evidence map›Paper›PMID 39095445›Full record

ArticleScientific reports2024

Task-dependent contribution to edge-based versus region-based texture perception.

Elena Gheorghiu, Cassandra Diggiss, Frederick A A Kingdom

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Elena GheorghiuDepartment of Psychology, University of Stirling, Stirling, FK9 4LA, Scotland, UK. elena.gheorghiu@stir.ac.uk.
Cassandra DiggissMcGill Vision Research, Department of Ophthalmology and Visual Sciences, McGill University, Montreal, Canada.
Frederick A A KingdomMcGill Vision Research, Department of Ophthalmology and Visual Sciences, McGill University, Montreal, Canada.

Funding

Leverhulme Trust RPG-2016-056Natural Sciences and Engineering Research Council of Canada OGP01217130
6 · The paper itself

Abstract

Texture segregation studies indicate that some types of textures are processed by edge-based and others by region-based mechanisms. However, studies employing nominally edge-based textures have found evidence for region-based processing mechanisms when the task was to detect rather than segregate the textures. Here we investigate directly whether the nature of the task determines if region-based or edge-based mechanisms are involved in texture perception. Stimuli consisted of randomly positioned Gabor micropattern texture arrays with five types of modulation: orientation modulation, orientation variance modulation, luminance modulation, contrast modulation and contrast variance modulation (CVM). There were four modulation frequencies: 0.1, 0.2, 0.4 and 0.8 cpd. Each modulation type was defined by three types of waveforms: sinewave (SN) with its smooth variations, square-wave (SQ) and cusp-wave (CS) with its sharp texture edges. The CS waveform was constructed by removing a sinewave from an equal amplitude square-wave. Participants performed two tasks: detection in which participants selected which of two stimuli contained the modulation and discrimination in which participants indicated which of two textures had a different modulation orientation. Our results indicate that threshold amplitudes in the detection task followed the ordering SQ < SN < CS across all spatial frequencies, consistent with detection being mediated by the overall energy in the stimulus and hence region based. With the discrimination task at low texture spatial frequencies and with CVM textures at all spatial frequencies the order was CS ≤ SQ with both < SN, consistent with being edge-based. We modeled the data by estimating the spatial frequency of a Difference of Gaussian filter that gave the largest peak amplitude response to the data. We found that the peak amplitude was lower for detection than discrimination across all texture types except for the CVM texture. We conclude that task requirements are critical to whether edges or regions underpin texture processing.

Indexed as

ContrastEdgeLuminanceOrientationRegionSegmentationTexture

Identifiers

PMID39095445
PMCPMC11297202

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