Journal of Vision Cover Image for Volume 25, Issue 5
April 2025
Volume 25, Issue 5
Open Access
Optica Fall Vision Meeting Abstract  |   April 2025
Contributed Talks I: Fixational eye movements and retinal adaptation: optimizing drift to maximize information acquisition
Author Affiliations
  • Daniel J. Read
    School of Mathematics, University of Leeds
  • Alexander J. H. Houston
    School of Mathematics & Statistics, University of Glasgow
  • Hannah E. Smithson
    Department of Experimental Psychology, University of Oxford
  • David H. Brainard
    Department of Psychology, University of Pennsylvania
  • Allie C. Hexley
    Department of Experimental Psychology, University of Oxford
  • Mengxin Wang
    Department of Experimental Psychology, University of Oxford
Journal of Vision April 2025, Vol.25, 9. doi:https://doi.org/10.1167/jov.25.5.9
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      Daniel J. Read, Alexander J. H. Houston, Hannah E. Smithson, David H. Brainard, Allie C. Hexley, Mengxin Wang; Contributed Talks I: Fixational eye movements and retinal adaptation: optimizing drift to maximize information acquisition. Journal of Vision 2025;25(5):9. https://doi.org/10.1167/jov.25.5.9.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Fixational eye movements (FEMs) are small, fluctuating eye motions when fixating on a target. Given our visual system is evolved, we may ask why FEMs are beneficial and whether they are optimal. A possible reason for FEMs is overcoming retinal adaptation (fading perception of a fixed image). We present a simple model system allowing theoretical investigation of FEM influence on information about an external stimulus. The model incorporates temporal stimulus modulation, retinal image motion due to the drift component of FEMs, blurring due to optics and receptor size, uniform sampling by the receptor array, adaptation via a bandpass temporal filter, and added noise. We investigate how elements of the model mediate the information transmitted, via: i) mutual information between visual system response and external stimulus, ii) direct estimation of stimulus from the system response, and iii) contrast threshold for signal detection. For all these we find a common quantity that must be maximized. For each spatial frequency this quantity is a summed power transmitted due to stimulus temporal modulation and phase shifts from FEMs, when passed through the temporal filter. We demonstrate that the information transmitted can be increased by adding local persistence to an underlying diffusive process. We also quantify the contribution of FEMs to signal detection for targets of different size and duration; such predictions provide a qualitative account of human psychophysical performance.

Footnotes
 Funding: This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/W023873/1].
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