Neuromorphic models of the visual system for multichannel, spike based encoding and processing.

Abstract

The mammalian retina is a complex neural tissue composed by millions of specialized neurons. Even though its architecture is simpler than the brain cortex, it already process a variety of visual signals by optimally filtering and extracting relevant environmental information through complex computing. Visual signals processed by the retina are then transmitted to the brain in the form of spikes through several parallel channels forming the optic nerve, where they are further processed in a parallel an hierarchical way, at increasing levels of complexity. We will conduct research on the spike based representation of visual images, with emphasis on its multichannel nature. By measuring the response of each encoder to different images, we will characterize quantitatively and qualitatively how much and what information can be extracted from each of these information channels. We expect that our work will help to further the functional characterization of each of these retinal circuits, and that it will enable work on their relation with cortical responses of primary visual cortex and, subsequently, higher visual cortical areas.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 14, 2022
Source ID
FA95501910368

Entities

People

  • Tomas Perez Acle

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force

Tags

Readers

  • Image Processing and Computer Vision.
  • Neural Network Machine Learning.
  • Vision Science/Vision Psychology/Cognitive Neuroscience.