Erik De Schutter is well known for the detailed model of the Purkinje cell he developed in the past (9). This model replicates the complete morphology and electrophysiology of the neuron and has demonstrated strong predictive power (10). We have now developed a new Purkinje cell model that incorporates recent data about voltage-gated channels and use it to investigate the complex spike (11). This model replicates the firing-rate dependence of the Purkinje cell Phase Response Curve, enabling firing-rate dependent oscillations (12) and parallel fiber evoked dendritic calcium spikes support multiplexed coding by the Purkinje cell (13).
We have extended our stochastic modeling to the cellular level and using the STEPS simulator (1) we demonstrated that the variability of dendritic calcium spikes, which has been observed experimentally, is caused by stochastic calcium mechanisms (14). This work links stochasticity at the molecular level with cellular properties. We are now extending this model to simulating a full Purkinje cell at the nanoscale level (15). The importance of morphological properties of astrocyte branches on calcium signaling was simulated (16).
More in general we are interested in the importance of neuronal morphology and excitability for function. We showed that the type of excitability a neuron expresses determines its type of network correlation (17,18), an important correction of the literature on the subject.
We are extending analysis of morphology to the network level: what are the properties of the forest of dendritic trees? This is a step towards modeling the development of neuronal morphology using environmental clues. To support such modeling we have developed the NeuroDevSim software (19), a more perfomant successor to NeuroMac (20). We are used NeuroDevSim to model the early development of cerebellar cortex (21).