Glass pattern studies of contrast effects in feature integration and segmentation

We investigated the role of disparity information in the detection of global form. Glass patterns, which allow insight into processing at both local and global stages of form analysis, were used as stimuli. We determined how detection of concentric Glass patterns is affected by a disparity difference introduced between partner dots forming local dipoles (Experiment 1), and how detection is affected by the addition of randomly oriented dot-pairs (noise dots) at crossed and uncrossed disparities (Experiment 2). The first experiment showed that detection thresholds increased when partner dots were separated in depth at disparities greater than approximately 17 min arc; the second experiment showed that noise dots disrupted the detection of form if they were presented at disparities of between approximately +/-20 min arc from the Glass pattern's presentation depth plane. Our findings suggest that disparity information plays a role in the recovery of the image structure and, importantly, local and global form mechanisms were found to be selective for a small range of stereo-depths. We discuss the findings of our study in the light of current evidence indicating that a common neural substrate is responsible for the analysis of form and binocular disparity.

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Glass-pattern detection is tuned for stereo-depth

Khuu

Hayes

2005

Vision Research

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Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

Greene

Hansen

2020

J. Neurosci.

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Human scene categorization is characterized by its remarkable speed. While many visual and conceptual features have been linked to this ability, significant correlations exist between feature spaces, impeding our ability to determine their relative contributions to scene categorization. Here, we used a whitening transformation to decorrelate a variety of visual and conceptual features and assess the time course of their unique contributions to scene categorization. Participants (both sexes) viewed 2250 full-color scene images drawn from 30 different scene categories while having their brain activity measured through 256-channel EEG. We examined the variance explained at each electrode and time point of visual event-related potential (vERP) data from nine different whitened encoding models. These ranged from low-level features obtained from filter outputs to high-level conceptual features requiring human annotation. The amount of category information in the vERPs was assessed through multivariate decoding methods. Behavioral similarity measures were obtained in separate crowdsourced experiments. We found that all nine models together contributed 78% of the variance of human scene similarity assessments and were within the noise ceiling of the vERP data. Low-level models explained earlier vERP variability (88 ms after image onset), whereas high-level models explained later variance (169 ms). Critically, only high-level models shared vERP variability with behavior. Together, these results suggest that scene categorization is primarily a high-level process, but reliant on previously extracted low-level features.

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Glass pattern studies of contrast effects in feature integration and segmentation

Cited by 2 publications

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Glass-pattern detection is tuned for stereo-depth

Glass-pattern detection is tuned for stereo-depth

Disentangling the Independent Contributions of Visual and Conceptual Features to the Spatiotemporal Dynamics of Scene Categorization

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