Active sensing explains cortical variability and improves visual information
- 1University of Washington
Abstract
Active vision is often considered at the scale of saccades, with each fixation treated as a static visual sample. Yet the eyes continue to move during fixation, continually transforming the retinal input. Here we measured these movements at high precision while recording neuronal populations in the foveal primary visual cortex of awake marmosets viewing repeated flashed natural images. Fixational eye movements accounted for most conditional firing-rate variability and nearly all shared variability not explained by the trial-averaged response. An image-computable model captured this modulation largely from gaze-dependent retinal input; explicit eye-position and eye-velocity signals added little predictive power. Under natural viewing, retinal motion redistributed image power across temporal frequencies, and motion effects grew when this power engaged spatiotemporal tuning. In model-derived populations, fixational motion increased the spatial information carried per spike relative to stabilized input, with sharpening growing across successive nonlinear stages. Thus, activity commonly assigned to cortical noise is not just structured visual reafference generated by the movement of the observer, but is beneficial signal which sharpens spatial representations.
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BibTeX
@misc{ressmeyer2026active,
title = {{Active sensing explains cortical variability and improves visual information}},
author = {R. A. Ressmeyer and D. P. Rowley and T. Kothapalli and D. Galor and R.-J. Wu and M. Rucci and J. F. Mitchell and D. A. Butts and A. C. Huk and J. L. Yates},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.12.758571},
url = {https://www.biorxiv.org/content/10.64898/2026.10.12.758571v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Active sensing explains cortical variability and improves visual information
AU - R. A. Ressmeyer
AU - D. P. Rowley
AU - T. Kothapalli
AU - D. Galor
AU - R.-J. Wu
AU - M. Rucci
AU - J. F. Mitchell
AU - D. A. Butts
AU - A. C. Huk
AU - J. L. Yates
PY - 2026
DA - 2026/10/12
PB - bioRxiv
DO - 10.64898/2026.10.12.758571
UR - https://www.biorxiv.org/content/10.64898/2026.10.12.758571v1
AB - Active vision is often considered at the scale of saccades, with each fixation treated as a static visual sample. Yet the eyes continue to move during fixation, continually transforming the retinal input. Here we measured these movements at high precision while recording neuronal populations in the foveal primary visual cortex of awake marmosets viewing repeated flashed natural images. Fixational eye movements accounted for most conditional firing-rate variability and nearly all shared variability not explained by the trial-averaged response. An image-computable model captured this modulation largely from gaze-dependent retinal input; explicit eye-position and eye-velocity signals added little predictive power. Under natural viewing, retinal motion redistributed image power across temporal frequencies, and motion effects grew when this power engaged spatiotemporal tuning. In model-derived populations, fixational motion increased the spatial information carried per spike relative to stabilized input, with sharpening growing across successive nonlinear stages. Thus, activity commonly assigned to cortical noise is not just structured visual reafference generated by the movement of the observer, but is beneficial signal which sharpens spatial representations.
ER -