Computational tools for simulation of stochastic ion channel activity in neurons

A fundamental goal of modern biology is to understand how the physical and behavioural characteristics of living organisms arise from components, such as cells and molecules, which are often too small to be seen with the naked eye. Considerable progress has been made towards determining how the physical properties of living organisms are specified by their genetic code, which is contained in individual molecules of DNA. By contrast, we understand much less about the physical principles that govern human or animal behaviour. For example, although it is clear that communication between nerve cells is a key component of brain function, the appropriate level of physical detail at which nerve cells must be understood to fully account for human or animal behaviour is far from clear. Most nerve cells have ornate branching structures, called axons and dendrites, which play fundamental roles in processing of information in the brain. In a single nerve cell these structures may contain well over a million ion channels, small molecules that determine how the cell processes information. While in the past neuroscientists have generally only considered how the average activity of this large umber of ion channels influences the function of nerve cells, recent evidence suggests that fluctuations in the activity of individual ion channels may be a critical determinant of nervous system function. Yet, we have few clear insights into how this basic property of ion channel function affects information processing in the brain. One promising approach to this problem is to develop computer models to simulate ion channel activity. However, at present accurately simulating the activity of each ion channel in complex neuronal structures is a formidable task, and it has therefore been difficult to explore how fluctuations in the activity of individual ion channels influences brain function. The goal of the proposed study is to develop new tools to efficiently simulate models of neurons or neuronal circuits that explicitly simulate the activity and location of individual ion channels. These tools will take advantage of recently developed computational algorithms, together with advances in computer science and methods for parallel computing, to reduce the time required for simulation of these models by greater than 100 fold. To facilitate compatibility with other widely used software, the tools will build on current community standards for specification of neuronal models and will be made freely available for download by other researchers or interested parties. Development of these new computational tools will enable new and fundamental questions to be addressed. For example, what particular aspects of neural information processing are most sensitive to fluctuations in the activity of individual ion channels? Do these fluctuations impair neural function, for example by introducing noise, or do they increase the computational power of neural circuits, for example though stochastic resonance effects? If they impair neural function then what mechanisms have evolved to counteract this effect? Conversely, if they confer benefits, then how are these advantages optimized in biological systems? The proposed project will prime new areas of research in the principal investigators laboratory that will aim to address these questions. More generally it will provide a new set of tools, of general use to the wider research community, that may lead to a better understanding of the relationship between the properties of single ion channel molecules, computations carried out by neural circuits and the behaviour of living organisms.

Recent work suggests that stochastic gating of individual ion channels profoundly affects the computational properties of neurons, but with presently available modeling tools it is difficult to explore the implications of these insights for computations carried out by neurons with complex axonal or dendritic architectures. To overcome these obstacles I propose to develop general-purpose software tools that will substantially reduce the time required for development and simulation of morphologically complex neurons containing stochastic ion channels throughout their axonal and dendritic membranes. To achieve efficiency gains of > 20 fold compared with the current best available solutions we will develop a computational core that uses new versions of the tau leap algorithm for simulation of ion channels. Further efficiency gains will be obtained by enabling the core to run simulations in parallel on multiple processors. To maximize compatibility with existing and future software, the tools to be developed will build on standard formalisms for representation of neuronal models and will also include a version of the software core compatible with the Genesis simulation environment. The time critical components of the core will be developed in Fortran 95 for optimal performance, whereas the outer components of the core and associated software will be developed in Java to maximize their portability. Each piece of software will be evaluated for accuracy, performance, compatibility and standards compliance. The software will be documented and released for download from the principal investigators website. A pilot project using the new software will build on the principal investigators study of stochastic gating in stellate cells of the entorhinal cortex, by evaluating the how the dendrites of stellate cells influence the functional consequences of stochastic channel gating in these neurons.