Noise in Neurons and Other Constraints

Abstract

How do the properties of signalling molecules constrain the structure and function biological networks such as those of our brain? Here we focus on the action potential, the fundamental electrical signal of the brain, because malfunction of the action potential causes many neurological conditions. The action potential is mediated by the concerted action of voltagegated ion channels and relating the properties of these signalling molecules to the properties of neurons at the systems level is essential for biomedical brain research, as minor variations in properties of a neurons individual component, can have large, pathological effects on the physiology of the whole nervous system and the behaviour it generates. This approach is very complex and requires us to discuss computational methods that can span across many levels of biological organization, from single signalling proteins to the organization of the entire nervous system, and encompassing time scales from milliseconds to hours.Within this methodical framework, we will focus on how the properties of voltagegated ion channels relate to the functional and structural requirements of axonal signalling and the engineering design principles of neurons and their axons (nerve fibres). This is important, not only because axons are the essential wires that allow information transmission between neurons, but also because they play a crucial in neural computation itself.

Many properties at the molecular level of the nervous system display noise and variability, which in turn makes it difficult to understand neuronal design and behaviour at the systems level without incorporating the sources of this probabilistic behaviour. To this end we have developed computationalmethods, which will enable us to conduct stochastic simulations of neurons that account for the probabilistic behaviour of ion channels. This allows us to explore the relationship between individual ion channel properties, derived from high-resolution patch clamp data,and the properties of axons. The computational techniques we introduce here will allow us to tackle problems that are (1) beyond the reach of experimental methods, because we can disambiguate the effects of variability and reliability of individual molecular components to whole cell behaviour, and (2) allow us to consider the many finer fibers in the central and peripheral system, which are experimentally difficulty to access and record from. We start with the well-established data that Ion channels behave with an element of randomness resulting in “channel noise”. The impact of channel noise in determining axonal structure and function became apparent only very recently, because in the past findings were extrapolated from very large unmyelinated axons (squid giant axon), where channel noise had little impact due to the law of large numbers. However, the many axons in the central and peripheral nervous system are over 1,000 times thinner and the small number of ion channels involved in sustaining the action potential, imply that channel noise can affect signalling and constraint both the reliability of neural circuit function, but also sets limits to the anatomy of the brain as a whole.