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A higher order visual neuron tuned to the spatial amplitude spectra of natural scenes

Author

Listed:
  • Olga Dyakova

    (Uppsala University)

  • Yu-Jen Lee

    (Uppsala University)

  • Kit D. Longden

    (HHMI Janelia Research Campus)

  • Valerij G. Kiselev

    (Medical Physics, University Medical Center Freiburg)

  • Karin Nordström

    (Uppsala University
    Anatomy and Histology, Centre for Neuroscience, Flinders University)

Abstract

Animal sensory systems are optimally adapted to those features typically encountered in natural surrounds, thus allowing neurons with limited bandwidth to encode challengingly large input ranges. Natural scenes are not random, and peripheral visual systems in vertebrates and insects have evolved to respond efficiently to their typical spatial statistics. The mammalian visual cortex is also tuned to natural spatial statistics, but less is known about coding in higher order neurons in insects. To redress this we here record intracellularly from a higher order visual neuron in the hoverfly. We show that the cSIFE neuron, which is inhibited by stationary images, is maximally inhibited when the slope constant of the amplitude spectrum is close to the mean in natural scenes. The behavioural optomotor response is also strongest to images with naturalistic image statistics. Our results thus reveal a close coupling between the inherent statistics of natural scenes and higher order visual processing in insects.

Suggested Citation

  • Olga Dyakova & Yu-Jen Lee & Kit D. Longden & Valerij G. Kiselev & Karin Nordström, 2015. "A higher order visual neuron tuned to the spatial amplitude spectra of natural scenes," Nature Communications, Nature, vol. 6(1), pages 1-10, December.
    • Handle: RePEc:nat:natcom:v:6:y:2015:i:1:d:10.1038_ncomms9522
    DOI: 10.1038/ncomms9522
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    Cited by:

    1. Yao, Zhao & Wang, Chunni, 2021. "Control the collective behaviors in a functional neural network," Chaos, Solitons & Fractals, Elsevier, vol. 152(C).

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