We present a universal building block for cognitive machines, called NeuroNavigator, inspired by theories of the hippocampus. The module is designed to fit both biological plausibility and constraints of forthcoming neuromorphic hardware. Its functions may range from spatial navigation to episodic memory retrieval. The goal of the present study of NeuroNavigator is to show the scalability of the model. The core of the architecture is based on our previously described model of hippocampal function and includes 3 layers (DG, CA3, CA1) of spiking neurons with noisy STDP synaptic connections among neighboring layers. The model is applied to a spatial navigation paradigm in a hierarchical virtual environment, the metrics of which need to be learned by exploration. The goal in each trial is set arbitrarily as any one of the previously seen objects or features. In order to navigate toward the goal, the agent needs to “imagine” previously performed available moves at the current location and select one of them, using the acquired spatial knowledge. This process controlled by NeuroNavigator is repeated until the goal is reached. Overall, the simulation results show robustness and scalability of the solution based on a biologically-inspired network of spiking neurons and STDP synapses.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 firstname.lastname@example.org
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 email@example.com