Fixational eye movements enhance the precision of visual information transmitted by the primate retina

Eric G Wu; Nora Brackbill; Colleen Rhoades; Alexandra Kling; Alex R Gogliettino; Nishal P Shah; Alexander Sher; Alan M Litke; Eero P Simoncelli; E J Chichilnisky

doi:10.1038/s41467-024-52304-7

Fixational eye movements enhance the precision of visual information transmitted by the primate retina

Nat Commun. 2024 Sep 11;15(1):7964. doi: 10.1038/s41467-024-52304-7.

Authors

Eric G Wu¹, Nora Brackbill², Colleen Rhoades³, Alexandra Kling^{4

5

6}, Alex R Gogliettino^{6

7}, Nishal P Shah^{8

4}, Alexander Sher⁹, Alan M Litke⁹, Eero P Simoncelli^{10

11

12}, E J Chichilnisky^{13

14

15}

Affiliations

¹ Department of Electrical Engineering, Stanford University, Stanford, CA, USA. [email protected].
² Department of Physics, Stanford University, Stanford, CA, USA.
³ Department of Bioengineering, Stanford University, Stanford, CA, USA.
⁴ Department of Neurosurgery, Stanford University, Stanford, CA, USA.
⁵ Department of Ophthalmology, Stanford University, Stanford, CA, USA.
⁶ Hansen Experimental Physics Laboratory, Stanford University, 452 Lomita Mall, Stanford, 94305, CA, USA.
⁷ Neurosciences PhD Program, Stanford University, Stanford, CA, USA.
⁸ Department of Electrical Engineering, Stanford University, Stanford, CA, USA.
⁹ Santa Cruz Institute for Particle Physics, University of California, Santa Cruz, Santa Cruz, CA, USA.
¹⁰ Flatiron Institute, Simons Foundation, New York, NY, USA.
¹¹ Center for Neural Science, New York University, New York, NY, USA.
¹² Courant Institute of Mathematical Sciences, New York University, New York, NY, USA.
¹³ Department of Neurosurgery, Stanford University, Stanford, CA, USA. [email protected].
¹⁴ Department of Ophthalmology, Stanford University, Stanford, CA, USA. [email protected].
¹⁵ Hansen Experimental Physics Laboratory, Stanford University, 452 Lomita Mall, Stanford, 94305, CA, USA. [email protected].

Abstract

Fixational eye movements alter the number and timing of spikes transmitted from the retina to the brain, but whether these changes enhance or degrade the retinal signal is unclear. To quantify this, we developed a Bayesian method for reconstructing natural images from the recorded spikes of hundreds of retinal ganglion cells (RGCs) in the macaque retina (male), combining a likelihood model for RGC light responses with the natural image prior implicitly embedded in an artificial neural network optimized for denoising. The method matched or surpassed the performance of previous reconstruction algorithms, and provides an interpretable framework for characterizing the retinal signal. Reconstructions were improved with artificial stimulus jitter that emulated fixational eye movements, even when the eye movement trajectory was assumed to be unknown and had to be inferred from retinal spikes. Reconstructions were degraded by small artificial perturbations of spike times, revealing more precise temporal encoding than suggested by previous studies. Finally, reconstructions were substantially degraded when derived from a model that ignored cell-to-cell interactions, indicating the importance of stimulus-evoked correlations. Thus, fixational eye movements enhance the precision of the retinal representation.

MeSH terms

Action Potentials / physiology
Algorithms
Animals
Bayes Theorem
Eye Movements* / physiology
Fixation, Ocular* / physiology
Macaca mulatta
Male
Models, Neurological
Photic Stimulation
Retina* / physiology
Retinal Ganglion Cells* / physiology

Abstract

MeSH terms

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