Abstract

Seeing the direction of motion is essential for survival of all sighted animals. Consequently, nerve cells that respond to visual stimuli moving in one but not in the opposite direction, so-called ‘direction-selective’ neurons, are found abundantly. In general, direction selectivity can arise by either signal amplification for stimuli moving in the cell’s preferred direction (‘preferred direction enhancement’), signal suppression for stimuli moving along the opposite direction (‘null direction suppression’), or a combination of both. While signal suppression can be readily implemented in biophysical terms by a hyperpolarization followed by a rectification corresponding to the nonlinear voltage-dependence of the Calcium channel, the biophysical mechanism for signal amplification has remained unclear so far. Taking inspiration from the fly, I analyze a neural circuit where a direction-selective ON-cell receives inhibitory input from an OFF cell on the preferred side of the dendrite, while excitatory ON-cells contact the dendrite centrally. This way, an ON edge moving along the cell’s preferred direction suppresses the inhibitory input, leading to a release from inhibition in the postsynaptic cell. The benefit of such a two-fold signal inversion lies in the resulting increase of the postsynaptic cell’s input resistance, amplifying its response to a subsequent excitatory input signal even with a passive dendrite, i.e. without voltage-gated ion channels. A motion detector implementing this mechanism together with null direction suppression shows a high degree of direction selectivity over a large range of temporal frequency, narrow directional tuning, and a large signal-to-noise ratio.

Highlights

  • Motion represents an essential visual cue, used for predator avoidance, prey capture and visual navigation throughout the animal kingdom

  • Nerve cells that respond preferentially to visual stimuli moving in a certain direction are found abundantly

  • Algorithmic models have been proposed in the past that calculate the direction of motion by multiplying and/or dividing the input signals from neighboring photoreceptors after asymmetric temporal filtering

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Summary

Introduction

Motion represents an essential visual cue, used for predator avoidance, prey capture and visual navigation throughout the animal kingdom. Motion-sensitive neurons are found in various brain areas of vertebrates and invertebrates alike. To describe the response properties of these neurons, a number of partially equivalent models [17] have been developed, e.g. the Hassenstein-Reichardt detector [18], the Barlow-Levick detector [2], the F-model [19], the elaborated Reichardt model [20] and the energy model [21]. These models compute the local direction of motion by correlating the luminance values of adjacent image pixels after asymmetric temporal filtering. With one exception [22], the biophysical implementation of such a correlative, multiplicative-like interaction has so far not been elucidated

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