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Updated: Oct 13, 2025

Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
Published on: April 11, 2025
Cross-fixation interactions of orientations suggest high-to-low-level decoding in visual working memory
Long Luu1, Mingsha Zhang2, Misha Tsodyks3
1Department of Neuroscience, Zuckerman Institute, Department of Physiology & Cellular Biophysics, Columbia University, New York, NY 10027, USA.
Visual perception decoding may follow a high-to-low hierarchy, not low-to-high. This study found cross-fixation interactions between orientations in working memory, challenging traditional models.
Area of Science:
- Neuroscience
- Cognitive Science
- Visual Perception
Background:
- Sensory encoding progresses from low- to high-level features.
- Visual decoding is assumed to follow a similar low-to-high hierarchy.
- Traditional models posit orientation decoding occurs in low-level visual areas (e.g., V1) without cross-fixation interactions.
Purpose of the Study:
- To investigate the hierarchy of visual decoding in working memory.
- To determine if task-relevant orientations interact across visual fields.
- To challenge the assumption of a strict low-to-high-level decoding hierarchy.
Main Methods:
- Experimental manipulation of visual stimuli presented across fixation points.
- Behavioral measurements of orientation perception.
- Control experiments to rule out alternative explanations (e.g., reporting bias, adaptation).
- Development and application of a Bayesian decoding framework.
Main Results:
- Observed cross-fixation interactions (repulsion and correlation) between orientations.
- Demonstrated that task-relevant orientations interact even when spatially separated.
- Ruled out alternative explanations for the observed interactions.
- Successfully explained data using a high-to-low-level Bayesian decoding model.
Conclusions:
- Visual decoding in working memory may often follow a high-to-low-level hierarchy.
- Interactions between lower-level features are constrained by higher-level representations.
- Findings challenge traditional models of visual processing and perception.
- A retrospective Bayesian decoding framework can explain these complex interactions.
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