Year: 2025
Type: article
Abstract: Neural and synaptic models that are relatively biologically accurate are easy to use to run efficient and distributed programs. The mechanism described in this paper uses these models to develop cell assemblies with a small number of neurons that persist indefinitely unless stopped. These in turn can be used to implement finite state automata and many other useful components, including cognitive maps and natural language parsers. These components support the development of, among other things, agents in virtual environments. Two spiking neuron agents are described, both able to run using either a standard neural simulator or using neuromorphic hardware. Examples of their behavior are described touching the individual spike level. The component model supports step-wise development, and the example of extending the cognitive mapping mechanism from the simple agent to the full agent is described. Spiking nets support parallelism, use on neuromorphic platforms, and engineering and exploration of multiple subsystems, which in turn can help explore the neural basis of cognitive phenomena. Relationships between these spiking nets and biology are discussed. The code is available to ease reuse by other researchers.
Source: Electronics
Authors: Christian Huyck, Fayokunmi Obisesan
Institution: Middlesex University London
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: European Commission
OpenAlex ID: W4416131132