4.7 Article

A Computational Framework for Realistic Retina Modeling

Journal

INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
Volume 26, Issue 7, Pages -

Publisher

WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0129065716500301

Keywords

Computational retina modeling; large-scale retina model; single-cell retina model; retina simulator; visual adaptation; contrast adaptation; adaptation to the mean light intensity; object motion sensitive cells; space-variant Gaussian filter; low-pass temporal filter; single-compartment model; static nonlinearity; short-term plasticity; spiking neural networks

Funding

  1. Human Brain Project (FET project) [604102]
  2. Junta of Andalucia (Spain) - European Regional Development Fund (ERDF) [P11-TIC-7983, P11-TIC-8120]
  3. Spanish Government [FPU13/01487]
  4. [TIN2013-47069-P]
  5. [TIN2015-67020-P]

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Computational simulations of the retina have led to valuable insights about the biophysics of its neuronal activity and processing principles. A great number of retina models have been proposed to reproduce the behavioral diversity of the different visual processing pathways. While many of these models share common computational stages, previous efforts have been more focused on fitting specific retina functions rather than generalizing them beyond a particular model. Here, we define a set of computational retinal microcircuits that can be used as basic building blocks for the modeling of different retina mechanisms. To validate the hypothesis that similar processing structures may be repeatedly found in different retina functions, we implemented a series of retina models simply by combining these computational retinal microcircuits. Accuracy of the retina models for capturing neural behavior was assessed by fitting published electrophysiological recordings that characterize some of the best-known phenomena observed in the retina: adaptation to the mean light intensity and temporal contrast, and differential motion sensitivity. The retinal microcircuits are part of a new software platform for efficient computational retina modeling from single-cell to large-scale levels. It includes an interface with spiking neural networks that allows simulation of the spiking response of ganglion cells and integration with models of higher visual areas.

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