The University of Southampton
Engineering and the Environment

Research project: Modelling of the neuronal responses of identified motor neurons across animals

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As presented at the Signal Processing and Control Group Away Day, June 2012.

Project Overview

Artificial Neural Network (ANN) models have been designed through a metaheuristic algorithm to predict the response on an identified neuron in the locust hind leg. Identified neurons are neurons with similar or identical dynamical properties. Neurons have been identified so far in small species, including insects, but not all of them have been discovered yet. Chordotonal organs in insects monitor leg angle and position, velocity and acceleration of leg movements. The Femoro-tibial Chordotonal Organ (FeCO) monitors the femur and tibia joint in the locust hind leg. The reflex control system of this leg corrects the position of the leg when movement is imposed. When a displacement is detected, the FeCO apodeme and flexor strand transmit the movement to the sensory neurons in the FeCO, which, through a series of interneurons, excite the motor neurons. The tibia is innervated by two extensor motor neurons, the Fast Extensor Tibiae (FETi) and the Slow Extensor Tibiae (SETi). The ANN models estimate the response of the FETi motor neuron when a mechanical stimulus is applied in the FeCO apodeme. The results show that the models are able to predict the response of the FETi motor neuron across animals with some accuracy, implying that there is a common underlying function to all animals. However, the errors in the predictions show that there are high levels of spontaneous neuronal activity, inherent to each individual, which increase the errors in the predictions.

Related research groups

Signal Processing and Control Group

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