Biophysical basis for three distinct dynamical mechanisms of action potential initiation.
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Hodgkin identified three classes of neurons with qualitatively different analog-to-digital transduction properties.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.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.
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PubMed Central - PubMed
Affiliation: Computational Neurobiology Laboratory, Salk Institute, La Jolla, California, United States of America. prescott@neurobio.pitt.edu
ABSTRACT
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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 analog-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. With 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. Related in: MedlinePlus |
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Mentions: Interpretation of the phase plane geometry can be formalized by doing localstability analysis near the fixed points ([27], see also chapter11 in [28]). In class 3 neurons, at the stable fixed point. This means, at steadystate, that positive feedback is slower than the rate of negativefeedback,φw/τw.Subthreshold activation of Islow produces a steadystate I–V curve that is monotonic and sufficientlysteep near the apex of the instantaneous I–V curvethat V is prohibited from rising high enough to stronglyactivate Ifast (Figure 9A, left). However, because the twofeedback processes have different kinetics, a spike can be initiated if thesystem is perturbed from steady state: if V escapes high enoughto activate Ifast (e.g., at the onset of an abruptstep in Istim), fast-activating inward current canoverpower slow-activating outward current—the latter is stronger whenfully activated, but can only partially activate (because of its slow kinetics)before a spike is inevitable. Through this mechanism, a single spike can beinitiated before negative feedback forces the system back to its stable fixedpoint, hence class 3 excitability. Speeding up the kinetics ofIslow predictably allowsIslow to compete more effectively withIfast (see below). |
View Article: PubMed Central - PubMed
Affiliation: Computational Neurobiology Laboratory, Salk Institute, La Jolla, California, United States of America. prescott@neurobio.pitt.edu