Theoretical studies suggest 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 we have developed general-purpose software tools that substantially reduce the time required for development, visualization and simulation of morphologically complex neurons containing stochastic ion channels throughout their axonal and dendritic membranes.
The new software accurately and efficiently simulates stochastic ion channel activity in neurons with complex dendritic and axonal arborizations. Efficiency gains of more than an order of magnitude have been achieved through implementation of a computational core that uses a new version of the tau leap algorithm for simulation of ion channel gating. We have demonstrated further efficiency gains by enabling the core to run simulations in parallel on multiple processors. We have also developed software for visualization and modification of models that contain stochastically gating ion channels. To maximize compatibility with existing and future software, the new software builds on standard formalisms for representation of neuronal models and can import models from online databases or as files exported from modeling packages currently used for deterministic simulations. Each piece of software has been thoroughly evaluated for accuracy, performance, compatibility and standards compliance.
The software is fully documented and following completion of peer review will be made freely available for download from a dedicated website. Simulations that we have carried out with the new software demonstrate previously unappreciated differences between neurons in the impact that stochastic channel gating has on dendritic integration. We are now using the new software to investigate the functional implications of these differences and also to evaluate the functional consequences of stochastic channel gating in the dendrites of stellate cells from the entorhinal cortex.
1. We overcame substantial technical challenges to develop new software tools that solve the problem of simulating stochastic activity of all ion channels in a neuron with complex morphology. We tested this software to demonstrates its accuracy and efficiency.
2. We developed and tested new software for visualisation of ion channels in neurons with complex morphology.
3. We demonstrated for the first time that the functional impact of stochastic ion channel gating depends on neuronal morphology.
4. We introduced the first evidence that when ion channels in a neuron's dendrites gate stochastically, as they do in real neurons, then neuronal computation is probabilistic. This is in contrast to the commonly held deterministic view of computation that arises in part from use of simulators that do not account for experimentally observed stochastic properties of ion channel gating