Modeling biological neurons with Josephson junctions
© Crotty et al; licensee BioMed Central Ltd. 2009
Published: 13 July 2009
It is exceedingly difficult to simulate large numbers of interconnected biologically realistic neurons, even when simplified neuronal models that substantially reduce the computational requirements per neuron are employed. Computer CPUs can only solve for the behavior of a single neuron at once, meaning the total computational time is to at least N, the number of neurons, and up to N2 for densely connected networks. Multi-core processors, cluster computing, and parallel programming techniques can alleviate this problem somewhat, but not enough to make it feasible to simulate more than a few tens of thousands of neurons in a reasonable period of time.
Josephson neurons are easy to design and fairly inexpensive to fabricate; a thousand could be placed on a single chip. They would operate fully in parallel, meaning a single Josephson neuron in isolation would run just as quickly as a thousand fully interconnected ones. And they would be vastly faster than either computer simulations of neurons or actual biological ones: a Josephson neuron action potential lasts on the order of a picosecond, roughly a billion times shorter than a biological action potential. Josephson neurons may therefore provide a way of overcoming the traditional time and scaling problems of computational neuroscience.
This article is published under license to BioMed Central Ltd.