Biophysical Models of Neural Computation: Max and Tuning Circuits

Abstract

Pooling under a softmax operation and Gaussian-like tuning in the form of a normalized dotproduct were proposed as the key operations in a recent model of object recognition in the ventral stream of visual cortex. We investigate how these two operations might be implemented by plausible circuits of a few hundred neurons in cortex. We consider two di erent sets of circuits whose di erent properties may correspond to the conditions in visual and barrel cortices, respectively. They constitute a plausibility proof that stringent timing and accuracy constraints imposed by the neuroscience of object recognition can be satisfied with standard spiking and synaptic mechanisms. We provide simulations illustrating the performance of the circuits, and discuss the relevance of our work to neurophysiology as well as what bearing it may have on the search for maximum and tuning circuits in cortex.

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Document Details

Document Type
Technical Report
Publication Date
Apr 20, 2007
Accession Number
ADA466426

Entities

People

  • Jake Bouvrie
  • Tomaso Poggio
  • Ulf Knoblich

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Accuracy
  • Artificial Intelligence
  • Brain
  • Cognitive Science
  • Computational Science
  • Computations
  • Computer Programming
  • Computer Vision
  • Dynamic Range
  • Firing Rate
  • Membrane Potentials
  • Neurons
  • Object Recognition
  • Recognition
  • Simulations
  • Transfer Functions
  • Visual Cortex

Readers

  • Computer Vision.
  • Electronics Engineering
  • Neuroscience

Technology Areas

  • Biotechnology