Brain representations of motion and position in the double-drift illusion.
Noah J SteinbergZvi N RothJ Anthony MovshonElisha P MerriamPublished in: eLife (2024)
In the 'double-drift' illusion, local motion within a window moving in the periphery of the visual field alters the window's perceived path. The illusion is strong even when the eyes track a target whose motion matches the window so that the stimulus remains stable on the retina. This implies that the illusion involves the integration of retinal signals with non-retinal eye-movement signals. To identify where in the brain this integration occurs, we measured BOLD fMRI responses in visual cortex while subjects experienced the double-drift illusion. We then used a combination of univariate and multivariate decoding analyses to identify (1) which brain areas were sensitive to the illusion and (2) whether these brain areas contained information about the illusory stimulus trajectory. We identified a number of cortical areas that responded more strongly during the illusion than a control condition that was matched for low-level stimulus properties. Only in area hMT+ was it possible to decode the illusory trajectory. We additionally performed a number of important controls that rule out possible low-level confounds. Concurrent eye tracking confirmed that subjects accurately tracked the moving target; we were unable to decode the illusion trajectory using eye position measurements recorded during fMRI scanning, ruling out explanations based on differences in oculomotor behavior. Our results provide evidence for a perceptual representation in human visual cortex that incorporates extraretinal information.
Keyphrases
- resting state
- functional connectivity
- white matter
- optical coherence tomography
- diabetic retinopathy
- cerebral ischemia
- working memory
- endothelial cells
- physical activity
- squamous cell carcinoma
- high resolution
- optic nerve
- multiple sclerosis
- radiation therapy
- depressive symptoms
- mental health
- locally advanced
- rectal cancer
- electron microscopy