December 2017
Volume 17, Issue 15
Open Access
OSA Fall Vision Meeting Abstract  |   December 2017
Image systems engineering tools for biology: ISETBIO
Author Affiliations
  • Brian Wandell
    Stanford Center for Image Systems Engineering
Journal of Vision December 2017, Vol.17, 10-11. doi:
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      Brian Wandell; Image systems engineering tools for biology: ISETBIO. Journal of Vision 2017;17(15):10-11. doi:

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

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For more than two centuries scientists have developed theories and made measurements that characterize how the visual system converts light into neural signals. This knowledge is contained in a distributed set of textbooks and research papers. We are developing an open-source Matlab toolbox, ISETBIO, that integrates this knowledge into a set of computations that convert 3D scene spectral radiance into retinal irradiance and neural responses. At this time, ISETBIO models the physiological optics, inert ocular pigments, eye movements, photoreceptor sampling and photopigment absorptions, cone photocurrent, bipolar cell responses, and retinal ganglion cell responses. One benefit of the project is that it clarifies which parts of our understanding are secure and which need further definition; a second benefit is that assembling the diverse sources of information into a single integrated package clarifies the contributions from different visual system components. We hope our colleagues will check and extend our work - we are particularly eager to develop models that characterize responses deeper in the nervous system and models that can be applied to animal visual systems. I will explain how the current computations, which characterize the initial stages of visual encoding, can be helpful to research scientists and engineers who aim to understand how information available in the nervous system limits fundamental perceptual judgments, such as Vernier acuity, contrast sensitivity, and color and motion sensitivity.


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