This is the readme for the model associated with the paper: Prescott SA, De Koninck Y, Sejnowski TJ (2008) Biophysical Basis for Three Distinct Dynamical Mechanisms of Action Potential Initiation. PLoS Comput. Biol. 4(10): e1000198 Abstract: Transduction of graded synaptic input into trains of all-or-none action potentials (spikes) is a crucial step in neural coding. Hodgkin identified three classes of neurons with qualitatively different analogue-to-digital transduction properties. Despite widespread use of this classification scheme, a generalizable explanation of its biophysical basis has not been described. We recorded from spinal sensory neurons representing each class and reproduced their transduction properties in a minimal model. Using phase plane and bifurcation analysis, each class of excitability was shown to derive from distinct spike initiating dynamics. Excitability could be converted between all three classes by varying single parameters; moreover, several parameters, when varied one at a time, had functionally equivalent effects on excitability. From this, we conclude that the spike initiating dynamics associated with each of Hodgkin's classes represent different outcomes in a nonlinear competition between oppositely directed, kinetically mismatched currents. Class 1 excitability occurs through a saddle-node on invariant circle bifurcation when net current at perithreshold potentials is inward (depolarizing) at steady state. Class 2 excitability occurs through a Hopf bifurcation when, despite net current being outward (hyperpolarizing) at steady state, spike initiation occurs because inward current activates faster than outward current. Class 3 excitability occurs through a quasi-separatrix-crossing when fast-activating inward current overpowers slow-activating outward current during a stimulus transient, although slow-activating outward current dominates during constant stimulation. Experiments confirmed that different classes of spinal lamina I neurons express the subthreshold currents predicted by our simulations and, further, that those currents are necessary for the excitability in each cell class. Thus, our results demonstrate that all three classes of excitability arise from a continuum in the direction and magnitude of subthreshold currents. Through detailed analysis of the spike initiating process, we have explained a fundamental link between biophysical properties and qualitative differences in how neurons encode sensory input. Model Notes: Models demonstrate how action potentials can be generated through different dynamical mechanisms depending on the direction and magnitude of subthreshold current. We start with a two-dimensional Morris-Lecar-type model. Varying parameter Beta_w causes this model to exhibit class 1, 2, or 3 excitability according to Hodgkin's 1948 classification (see Figure 1 in paper). In this, the simplest model, dynamical systems analysis shows that each class is associated with a different spike initiating mechanism (see Figure 2 in paper). Try varying Beta_w to see how it affects dynamics visualized on the V-w plane. To increase the biological realism of the model, we split the recovery variable (w) into two parts (y and z) which each control slightly different currents (see Figure 4 in paper). Try varying gsub and Vsub. Noise is not included in these models but can be added by following the notes included in the code. The code contains numerous other comments that will help explain the model. For more information about XPP, visit http://www.scholarpedia.org/article/XPPAUT or http://www.math.pitt.edu/~bard/xpp/xpp.html Novemeber 14th, 2008: smaller sigma instead of sigma_inoise in comments update