Realistic Models of Cerebellar Stellate Neurons Predicts Intrinsic Excitability and the Impact of Synaptic Inputs.

The cerebellar stellate cells (SC) are inhibitory interneurons located in the molecular layer (ML) of the cerebellum. These cells receive excitatory inputs from parallel fibers (pf) and their branched axons make inhibitory synapses with Purkinje cells and other SCs. We reconstructed a multi-compartmental biophysically realistic SC model in Python-NEURON (Python 2.7; NEURON 7.5) to investigate the SC electrophysiological properties. 3D morphologies of mouse neurons were reconstructed from fluorescent images obtained with a confocal microscope and analyzed with Neurolucida. Ionic channels were located on the morphology compartments according to immunohistochemistry data. The maximum ionic conductances (Gi-max) were tuned to match the firing pattern revealed by electrophysiological recordings in mice cerebellar slices using patch-clamp techniques. SC discharges elicited by step current injections were used as templates to extract the features needed to assess the fitness function for the optimization procedure. Gi-max tuning was performed by automatic parameter estimation algorithms, using the multi-objective genetic algorithm in Blue Brain Python Optimisation Library (BluePyOpt). Optimized models reproduced the experimental results, showing spontaneous firing, an almost linear I/O relationship following positive somatic current injections, sag in hyperpolarizing direction following negative current injections, synaptic responses and PSTH following pf inputs and synchronization through gap-junctions. The optimization technique gave satisfactory results, reproducing SC electrophysiological behaviors. The model provided a valuable tool to further investigate the SC function in cerebellar network activity