Abstract

Sand scorpions and many other arachnids locate their prey through highly sensitive slit sensilla at the tips (tarsi) of their eight legs. This sensor array responds to vibrations with stimulus-locked action potentials encoding the target direction. We present a neuronal model to account for stimulus angle determination using a population of second-order neurons, each receiving excitatory input from one tarsus and inhibition from a triad opposite to it. The input opens a time window whose width determines a neuron's firing probability. Stochastic optimization is realized through tuning the balance between excitation and inhibition. The agreement with experiments on the sand scorpion is excellent.

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