Real neurons, and their networks, are far too complex to be described exactly by simple
deterministic equations. Any description of their dynamics must therefore incorporate noise
to some degree. It is my thesis that the nervous system is organized in such a way that its
performance is optimal, subject to this constraint. I further contend that neuronal dynamics
may even be enhanced by noise, when compared with their deterministic counter-parts.
To support my thesis I will present and analyze three case studies. I will show how noise
might (i) extend the dynamic range of mammalian cold-receptors and other cells that
exhibit a temperature-dependent discharge; (ii) feature in the perception of ambiguous
figures such as the Necker cube; (iii) alter the discharge pattern of single cells.
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.