Biophysical basis for three distinct dynamical mechanisms of action potential initiation.
PLoS Comput Biol 2008;
4:e1000198. [PMID:
18846205 PMCID:
PMC2551735 DOI:
10.1371/journal.pcbi.1000198]
[Citation(s) in RCA: 190] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2008] [Accepted: 09/03/2008] [Indexed: 11/19/2022] Open
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 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.
Information is transmitted through the nervous system in the form of action
potentials or spikes. Contrary to popular belief, a spike is not generated
instantaneously when membrane potential crosses some preordained threshold. In
fact, different neurons employ different rules to determine when and why they
spike. These different rules translate into diverse spiking patterns that have
been observed experimentally and replicated time and again in computational
models. In this study, our aim was not simply to replicate different spiking
patterns; instead, we sought to provide deeper insight into the connection
between biophysics and neural coding by relating each to the process of spike
initiation. We show that Hodgkin's three classes of excitability result
from a nonlinear competition between oppositely directed, kinetically mismatched
currents; the outcome of that competition is manifested as dynamically distinct
spike-initiating mechanisms. Our results highlight the benefits of forward
engineering minimal models capable of reproducing phenomena of interest and then
dissecting those models in order to identify general explanations of how those
phenomena arise. Furthermore, understanding nonlinear dynamical processes such
as spike initiation is crucial for definitively explaining how biophysical
properties impact neural coding.
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