부산대학교 도서관

Although others have reported and characterised different patterns of Purkinje firing (Womack and Khodakhah, 2002, 2003, 2004; McKay and Turner, 2005) this thesis is the first study that moves beyond their description and investigates the actual basis of their generation. Purkinje cells can intrinsically fire action potentials in a repeating trimodal or bimodal pattern. The trimodal pattern consists of tonic spiking, bursting and quiescence. The bimodal pattern consists of tonic spiking and quiescence. How these firing patterns are generated, and what ascertains which firing pattern is selected, has not been determined to date. We have constructed a detailed biophysical Purkinje cell model that can replicate these patterns and which shows that Na+/K+ pump activity sets the model’s operating mode. We propose that Na+/K+ pump modulation switches the Purkinje cell between different firing modes in a physiological setting and so innovatively hypothesise the Na+/K+ pump to be a computational element in Purkinje information coding. We present supporting in vitro Purkinje cell recordings in the presence of ouabain, which irreversibly blocks the Na+/K+ pump. Climbing fiber (CF) input has been shown experimentally to toggle a Purkinje cell between an up (firing) and down (quiescent) state and set the gain of its response to parallel fiber (PF) input (Mckay et al., 2007). Our Purkinje cell model captures these toggle and gain computations with a novel intracellular calcium computation that we hypothesise to be applicable in real Purkinje cells. So notably, our Purkinje cell model can compute, and importantly, relates biophysics to biological information processing. Our Purkinje cell model is biophysically detailed and as a result is very computationally intensive. This means that, whilst it is appropriate for studying properties of the 8 individual Purkinje cell (e.g. relating channel densities to firing properties), it is unsuitable for incorporation into network simulations. We have overcome this by deploying mathematical transforms to produce a simpler, surrogate version of our model that has the same electrical properties, but a lower computational overhead. Our hope is that this model, of intermediate biological fidelity and medium computational complexity, will be used in the future to bridge cellular and network studies and identify how distinctive Purkinje behaviours are important to network and system function.