Minimal Models of Sensory Perception

Abstract

Although many neuroscientists seem to believe that the brain predicts sensory input, such assertions still lack conclusive evidence and associated understanding of the neural code and neural mechanisms. Using a recent technical advance in the benchmarking of predictive performance, we aim to: test the ability of humans and networks of cultured neurons to predict sensory input; unravel the neural code of prediction in the network of neurons; and explore the effects of synaptic dysfunction on prediction capability of the neurons. The results of this research will rigorously demonstrate when and how humans and neurons are good at predicting input, and may lead to new learning rules for recurrent neural networks trying to predict.

Document Details

Document Type
DoD Grant Award
Publication Date
Jan 14, 2022
Source ID
FA95501910411

Entities

People

  • Sarah Marzen

Organizations

  • Air Force Office of Scientific Research
  • Claremont McKenna College
  • United States Air Force

Tags

Fields of Study

  • Biology

Readers

  • Neural Network Machine Learning.
  • Neuroscience
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks