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Convis: A Toolbox to Fit and Simulate Filter-Based Models of Early Visual Processing.

Jacob Huth1, Timothée Masquelier2, Angelo Arleo1

  • 1Centre National de la Recherche Scientifique, INSERM, Sorbonne Universités, UPMC Univ Paris 06, Paris, France.

Frontiers in Neuroinformatics
|March 23, 2018
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Summary

Convis is a new Python simulation toolbox for large-scale neural populations, using 3D convolutions for flexible and optimized neural modeling. It enables gradient-based optimization and can simulate various neural systems, including retina and V1 cells.

Keywords:
GPUPyTorchPythonTheanoprimary visual cortex modelretina modelvision model toolbox

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Area of Science:

  • Computational Neuroscience
  • Machine Learning
  • Software Development

Background:

  • Simulating large-scale neural populations is computationally intensive.
  • Existing tools may lack flexibility in modeling receptive fields and optimization methods.

Purpose of the Study:

  • To introduce Convis, a novel Python toolbox for simulating large-scale neural populations.
  • To leverage 3D convolutions and GPU acceleration for efficient and flexible neural modeling.
  • To enable gradient-based optimization of model parameters and inputs.

Main Methods:

  • Developed Convis using Python and PyTorch for GPU-accelerated 3D convolutions.
  • Implemented arbitrary receptive fields and complex non-linearities.
  • Utilized automatic differentiation for parameter and input optimization.

Main Results:

  • Convis successfully recreated simulation results from VirtualRetina with enhanced flexibility.
  • Demonstrated the utility of 3D convolution filters for direction-selective responses.
  • Showcased the ability to optimize inputs for specific goals, aiding experimental design.

Conclusions:

  • Convis offers a flexible, extensible, and efficient platform for neural population simulations.
  • The toolbox supports gradient-based optimization, surpassing traditional methods.
  • Convis extends beyond retina simulations, applicable to other neural systems like V1 cells.