An LGN inspired detect/transmit framework for high fidelity relay of visual information with limited bandwidth

  • Authors:

  • Nicholas A. Lesica;Garrett B. Stanley

  • Affiliations:

  • Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA;Division of Engineering and Applied Sciences, Harvard University, Cambridge, MA

  • Venue:
  • BVAI'05 Proceedings of the First international conference on Brain, Vision, and Artificial Intelligence
  • Year:
  • 2005

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Abstract

The mammalian visual system has developed complex strategies to optimize the allocation of its limited attentional resources for the relay of behaviorally relevant visual information. Here, we describe a framework for the relay of visual information that is based on the tonic and burst properties of the LGN. The framework consists of a multi-sensor transmitter and receiver that are connected by a channel with limited total bandwidth. Each sensor in the transmitter has two states, tonic and burst, and the current state depends on the salience of the recent visual input. In burst mode, a sensor transmits only one bit of information corresponding to the absence or presence of a salient stimulus, while in tonic mode, a sensor attempts to faithfully relay the input with as many bits as are available. By comparing video reconstructed from the signals of detect/transmit sensors with that reconstructed from the signals of transmit only sensors, we demonstrate that the detect/transmit framework can significantly improve relay by dynamically allocating bandwidth to the most salient areas of the visual field.