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An insect-inspired model for visual binding I: learning objects and their characteristics

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Abstract

Visual binding is the process of associating the responses of visual interneurons in different visual submodalities all of which are responding to the same object in the visual field. Recently identified neuropils in the insect brain termed optic glomeruli reside just downstream of the optic lobes and have an internal organization that could support visual binding. Working from anatomical similarities between optic and olfactory glomeruli, we have developed a model of visual binding based on common temporal fluctuations among signals of independent visual submodalities. Here we describe and demonstrate a neural network model capable both of refining selectivity of visual information in a given visual submodality, and of associating visual signals produced by different objects in the visual field by developing inhibitory neural synaptic weights representing the visual scene. We also show that this model is consistent with initial physiological data from optic glomeruli. Further, we discuss how this neural network model may be implemented in optic glomeruli at a neuronal level.

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Acknowledgements

The authors would like to thank the Air Force Office of Scientific Research for early support of this project with Grant Number FA9550-07-1-0165, and the Air Force Research Laboratories for supporting this research to maturity with STTR Phase I Award Number FA8651-13-M-0085 and Phase II Award Number FA8651-14-C-0108, both in collaboration with Spectral Imaging Laboratory (Pasadena, CA). We would also like to thank the reviewers, whose input greatly enhanced this manuscript.

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Authors and Affiliations

  1. Department of Electrical and Computer Engineering, University of Arizona, 1230 E. Speedway Blvd., Tucson, AZ, 85721, USA

    Brandon D. Northcutt

  2. Department of Biology, Northwest University, 5520 108th Ave. N.E., Kirkland, WA, 98033, USA

    Jonathan P. Dyhr

  3. Departments of Neuroscience and Electrical/Computer Engineering, University of Arizona, 1040 E. 4th St., Tucson, AZ, 85721, USA

    Charles M. Higgins

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  1. Brandon D. Northcutt
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Correspondence to Brandon D. Northcutt.

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Northcutt, B.D., Dyhr, J.P. & Higgins, C.M. An insect-inspired model for visual binding I: learning objects and their characteristics. Biol Cybern 111, 185–206 (2017). https://doi.org/10.1007/s00422-017-0715-0

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