A spiking neuron model of head-direction cells for robot orientation.
T. Degris, L. Lachèze, C. Boucheny, and A. Arleo.
In S. Schaal, A. Ijspeert, A. Billard, S. Vijayakumar, J. Hallam, and J.-A. Meyer, editors,
Proceedings of the 8th Int. Conf. on Simulation of Adaptive Behavior, from Animals to Animats, pp.255-263, MIT Press.
This paper proposes a bio-mimetic model of head- direction (HD) cells implemented on a real robot. The model is based on spiking neurons to study the tem- poral aspects of state transitions of the HD cell ac- tivity following reorienting visual stimuli. The short transient latencies observed experimentally are repro- duced by the model. We focus on the integration of angular velocity inertial signals provided by ac- celerometers. This integration is realized by a con- tinuous attractor network modeling the interaction be- tween the lateral mammillary nucleus (LMN) and the dorsal tegmental nucleus (DTN), two structures be- longing to the HD cell anatomical circuit. Relevant parameters defining the connections between LMN and DTN are determined by a genetic algorithm.