README for the cerebellar nucleus (CN) neuron model described in the paper: Volker Steuber, Nathan Schultheiss, R. Angus Silver, Erik De Schutter & Dieter Jaeger (2010). Determinants of synaptic integration and heterogeneity in rebound firing explored with data-driven models of deep cerebellar nucleus cells. Journal of Computational Neuroscience, epub ahead of print. GENESIS files included: cn0106c_z15_l01_ax.p CN neuron morphology cn_chan.g functions that create ion channel prototypes cn_comp.g functions that create compartments cn_fileout.g functions that provide output to files cn_syn.g functions that create synapse prototypes cn_vclamp.g functions that create a voltage clamp circuit cn_AMPAcomps.txt list of compartments containing AMPA and NMDA receptors cn_cip_main.g main simulation script for current injection cn_const.g simulation parameters cn_GABAcomps.txt list of compartments containing GABAA receptors cn_syn_main.g main simulation script for synaptic input cn_vclamp_main.g main simulation script for voltage clamp simulations Note: As most biologically detailed neuron models, this model is under continuous development, and modifications of it (both in GENESIS and NEURON) have already been used for follow-up publications by Dieter Jaeger's and Volker Steuber's teams (Rin et al. and Luthman et al., submitted). Please contact us (djaeger@emory.edu and v.steuber@herts.ac.uk) for information about the latest updates. Moreover, we hope that future updates by others will be made available on ModelDB and we would appreciate hearing about them. We would also like to hear about any new experimental data that could be used to improve the model. Usage: Download and extract the archive, and create a subdirectory called data in the directory that contains all simulation files. There are three separate main scripts to simulate current injection, voltage clamp and synaptic input. These three types of simulations are run with: genesis cn_cip_main.g genesis cn_vclamp_main.g genesis cn_syn_main.g How to reproduce the figures in Steuber et al. (2010): Figure 1 (b) run with: genesis cn_cip_main.g in cn_const.g, set GNaPs = 0 Ghs = 1.0 GCaLVAs = 0 spontaneous activity: cipamp = 0 current injection: cipamp = 50.0e-12 // 50 pA ciponset = 3.0 cipdur = 1.5 Figure 1 (c) run with: genesis cn_cip_main.g in cn_const.g, set GNaPs = 8.0 Ghs = 1.0 GCaLVAs = 2.0 cipamp = 0.0 - 400.0e-12 Figure 2 run with: genesis cn_cip_main.g in cn_const.g, set GNaPs = 0 Ghs = 0 GCaLVAs = 0 cipamp = 50.0e-12 ciponset = 3.0 cipdur = 1.5 Figures 3 and 4 run with: genesis cn_cip_main.g in cn_const.g, set cipamp = -150.0e-12 ciponset = 3.0 cipdur = 1.5 Neuron 1 model: GNaPs = 2 Ghs = 0.5 GCaLVAs = 3.5 Neuron 2 model: GNaPs = 6 Ghs = 0.5 GCaLVAs = 4.5 Neuron 3 model: GNaPs = 8 Ghs = 2 GCaLVAs = 1.5 Figure 5 run with: genesis cn_vclamp_main.g in cn_const.g, set vcstep = -90e-3 vconset = 3.0 vcdur = 0.5 Figures 6, 7, 8 run with: genesis cn_cip_main.g in cn_const.g, set cipamp and cipdur as specified in the Figure Legends Figures 9 and 10 run with: genesis cn_syn_main.g in cn_const.g, set E_GABA = -80e-3 ex_rate_d, inhib_rate_d, GNaPs, Ghs, GCaLVAs as specified in the Figure Legends and panels low Gsyn: G_AMPAd = 5.0e-11 G_GABAd = 5.0e-11 intermediate Gsyn: G_AMPAd = 1.0e-10 G_GABAd = 1.0e-10 high Gysn: G_AMPAd = 2.0e-10 G_GABAd = 2.0e-10 Figure 11 run with: genesis cn_syn_main.g in cn_const.g, set E_GABA as specified in the panels ex_rate_d = 20 inhib_rate_d = 30 G_AMPAd = 1.0e-10 G_GABAd = 1.0e-10 inb1onset = 3.0 inb1dur = 0.25 inb1rate = 300 Neuron 2 model: GNaPs = 6 Ghs = 0.5 GCaLVAs = 4.5 Neuron 3 model: GNaPs = 8 Ghs = 2 GCaLVAs = 1.5 Figures 12 and 13 run with: genesis cn_syn_main.g in cn_const.g, set E_GABA = -90e-3 ex_rate_d and inhib_rate_d as specified in the panels inb1onset = 3.0 inb1dur = 0.25 inb1rate = 300 low Gsyn: G_AMPAd = 5.0e-11 G_GABAd = 5.0e-11 high Gysn: G_AMPAd = 2.0e-10 G_GABAd = 2.0e-10 Neuron 1 model: GNaPs = 2 Ghs = 0.5 GCaLVAs = 3.5 Neuron 3 model: GNaPs = 8 Ghs = 2 GCaLVAs = 1.5