Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature Brain of Honeybees

Mark Roper; Chrisantha Fernando; Lars Chittka

doi:10.1371/journal.pcbi.1005333

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Open Access

Peer-reviewed

Research Article

Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature Brain of Honeybees

Mark Roper ,

* E-mail: mark.roper@qmul.ac.uk

Affiliation Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom

http://orcid.org/0000-0003-1135-6187

⨯
Chrisantha Fernando,

Affiliations Google DeepMind, London, United Kingdom, School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom
⨯
Lars Chittka

Affiliation Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom

http://orcid.org/0000-0001-8153-1732

⨯

Insect Bio-inspired Neural Network Provides New Evidence on How Simple Feature Detectors Can Enable Complex Visual Generalization and Stimulus Location Invariance in the Miniature Brain of Honeybees

Mark Roper,
Chrisantha Fernando,
Lars Chittka

Published: February 3, 2017
https://doi.org/10.1371/journal.pcbi.1005333

About the Authors

Mark Roper

* E-mail: mark.roper@qmul.ac.uk

Affiliation Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom

http://orcid.org/0000-0003-1135-6187

Chrisantha Fernando

Affiliations Google DeepMind, London, United Kingdom, School of Electronic Engineering and Computer Science, Queen Mary University of London, London, United Kingdom

Lars Chittka

Affiliation Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, United Kingdom

http://orcid.org/0000-0001-8153-1732

Competing Interests

The authors have declared that no competing interests exist. Chrisantha Fernando is a paid employee of Google DeepMind.

Author Contributions

Conceptualization: MR CF LC. Formal analysis: MR. Funding acquisition: LC. Investigation: MR. Methodology: MR CF. Project administration: LC. Software: MR. Supervision: CF LC. Visualization: MR. Writing – original draft: MR CF LC. Writing – review & editing: MR CF LC.

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Honey bees
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Neurons
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Eyes
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Bees
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Behavior
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Synapses
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