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

Olga Dyakova,Valerij G Kiselev,Yu-Jen Lee,Kit D Longden,Karin Nordström

doi:10.1038/ncomms9522

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.

Highlights

Animal sensory systems are optimally adapted to those features typically encountered in natural surrounds, allowing neurons with limited bandwidth to encode challengingly large input ranges
Fourier domain analyses of photographs of natural scenes show that the amplitude has a characteristic fall-off with spatial frequency, with slope constants close to 1
Our data here show that the slope constant influences the level of inhibition generated in cSIFE, with peak inhibition at slope constants that are most similar to those of natural scenes (Figs 2, 3)

Summary

Introduction

Animal sensory systems are optimally adapted to those features typically encountered in natural surrounds, 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 tuned to natural spatial statistics, but less is known about coding in higher order neurons in insects. Photographs of natural scenes can be statistically analysed using the Fourier transform[3,4,5,6] that describes the image as a set of spatial frequencies of given amplitudes and phases, and different orientations. Low temporal and spatial frequencies predominate naturalistic visual input[12,16] In both mammals and insects low-frequency redundancy is suppressed via lateral inhibition and temporal antagonism[17,18,19,20] in photoreceptors and associated peripheral neurons. Retinal filters in fly lamina monopolar cells (LMCs, the first interneurons in the insect visual pathway) and ganglion cells of the vertebrate retina ‘whiten’ the signal[2,16,19,20]

Methods

Results

Conclusion