Title :
Autonomous Navigational Controller Inspired by the Hippocampus
Author :
Mokhtar, Maizura ; Halliday, David M. ; Tyrrell, Andy M.
Author_Institution :
Univ. of York, York
Abstract :
This study uses models of pyramidal neurons in the hippocampus to design a hardware spiking neural network neuro-controller model for the purpose of navigation. The neural network model consists of individual neurons modeled using the two-dimensional bio-inspired Izhikevich algorithm. The network is connected according to the connectivity within the hippocampus region, as this region is one of the regions in the brain that is responsible for path navigation. The information processed by the model helps provide navigation and creates memories. The neural network model is intended to be implemented onto a field programmable gate array (FPGA) device. This eliminates the need of an operating system to run the network, thus achieving autonomy.
Keywords :
brain models; field programmable gate arrays; navigation; neurocontrollers; position control; autonomous navigational controller; field programmable gate array; hardware spiking neural network; hippocampus region; neuro-controller model; operating system; path navigation; pyramidal neuron models; two-dimensional bio-inspired Izhikevich algorithm; Biological neural networks; Biological system modeling; Equations; Field programmable gate arrays; Hippocampus; Navigation; Neural network hardware; Neural networks; Neurons; Operating systems; Neural network architecture; neural network hardware;
Conference_Titel :
Neural Networks, 2007. IJCNN 2007. International Joint Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4244-1379-9
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2007.4371062