Developing and validating an isotrigon texture discrimination task using Amazon Mechanical Turk
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KeywordsSpatial Frequency Discrimination Task Human Visual System Natural Image Comparable Quality
The human visual system must employ mechanisms to minimize informational redundancy whilst maintaining that which is behaviorally relevant [1, 2]. Previous research has concentrated on two-point correlations via spatial frequency and orientation tuning. Higher-order correlations are less studied, but they may inform us about cortical functioning . Isotrigon textures can be used to probe the sensitivity of the human visual system as their structure is exclusively due to 4th and higher-order spatial correlations . Although artificially generated, the same features that give isotrigons salience also create salience in natural images . We implemented an isotrigon discrimination task using the crowdsourcing platform Amazon Mechanical Turk (mTurk) . An important secondary aim was to evaluate the suitability of mTurk for visual psychometric studies as very few exist .
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