Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models

Biol Cybern. 2023 Apr 8. doi: 10.1007/s00422-023-00961-0. Online ahead of print.ABSTRACTThe processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Specifically, in goldfish, the [Formula: see text] model has been proposed to describe the Mauthner cell, an identified neuron involved in startle escape responses. In the vinegar fly, a third model was developed for the giant fiber neuron, which triggers last resort escapes immediately before an impending collision. One key property of these models is their prediction that peak neuronal responses occur at a fixed delay after the simulated approaching object reaches a threshold angular size on the retina. This prediction is valid for simulated objects approaching at a constant speed. We tested whether it remains valid when approaching objects accelerate. After characterizing and comparing the models' responses to accelerating and constant speed stimuli, we find that the prediction holds true for the [Formula: see text] and the giant fiber model, but not for th...

Source: Biological Cybernetics - April 8, 2023 Category: Science Authors: Fabrizio Gabbiani Thomas Preuss Richard B Dewell Source Type: research