The relationship between viewer individual differences and gaze control has been largely neglected in the scene perception literature. The present study used Successor Representation Scanpath Analysis (SRSA) to quantify the strength of the association between individual differences in scan patterns during real-world scene viewing and individual differences in viewer attention-deficit disorder, autism spectrum disorder, and dyslexia scores.
Real-world scenes comprise a blooming, buzzing confusion of information. To manage this complexity, visual attention is guided to important scene regions in real time. What factors guide attention within scenes? A leading theoretical position suggests that visual salience based on semantically uninterpreted image features plays the critical causal role in attentional guidance, with knowledge and meaning playing a secondary or modulatory role. Here we propose instead that meaning plays the dominant role in guiding human attention through scenes.
The relationship between scan patterns and viewer individual differences during scene viewing remains poorly understood because scan patterns are difficult to analyze. The present study uses a powerful technique called Successor Representation Scanpath Analysis (SRSA, Hayes, Petrov, & Sederberg, 2011, 2015) to quantify the strength of the association between individual differences in scan patterns during real-world scene viewing and individual differences in viewer intelligence, working memory capacity, and speed of processing.
Pupil size is correlated with a wide variety of important cognitive variables and is increasingly being used by cognitive scientists. One serious confound that is often not properly controlled is pupil foreshortening error (PFE)—the foreshortening of the pupil image as the eye rotates away from the camera. Here we systematically map PFE using an artificial eye model and then apply a geometric model correction.
Recent reports of training-induced gains on fluid intelligence tests have fueled an explosion of interest in cognitive training-now a billion-dollar industry. The interpretation of these results is questionable because score gains can be dominated by factors that play marginal roles in the scores themselves, and because intelligence gain is not the only possible explanation for the observed control-adjusted far transfer across tasks. Here we present novel evidence that the test score gains used to measure the efficacy of cognitive training may reflect strategy refinement instead of intelligence gains.