Definition
In 1948, Hodgkin distinguished between three classes of excitability on the basis of spiking patterns observed in crustacean axons. This classification scheme is still applied today because it captures fundamental differences in excitability that stem from how action potentials, or spikes, are generated. The nonlinear dynamical mechanism responsible for spike initiation in each cell class has been worked out, and the biophysical implementation of those dynamical mechanisms is reasonably well understood. Moreover, the differences in spike initiation that define each class confer differences in metrics like the phase-response curve (PRC) and spike-triggered average (STA), meaning that this simple classification scheme is predictive of important differences in neural coding.
Detailed Description
Historical Background
Based on single fiber recordings from the crab Carcinus maenas, Hodgkin (1948) identified three different classes of excitability. Class 1 axons were capable of...
Keywords
- SNIC Bifurcation
- Saddle-node On Invariant Circle (SNIC)
- Spike Initiation
- Stable Fixed Point
- Repetitive Spiking
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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References
Ermentrout GB, Galan RF, Urban NN (2007) Relating neural dynamics to neural coding. Phys Rev Lett 99:248103
Hodgkin AL (1948) The local electric changes associated with repetitive action in a non-medullated axon. J Physiol 107:165–181
Izhikevich EM (2007) Dynamical systems in neuroscience. MIT Press, Cambridge, MA
Prescott SA, De Koninck Y, Sejnowski TJ (2008) Biophysical basis for three distinct dynamical mechanisms of action potential initiation. PLoS Comput Biol 4:e1000198
Ratté S, Hong S, De Schutter E, Prescott SA (2013) Impact of neuronal properties on network coding: roles of spike initiation dynamics and robust synchrony transfer. Neuron 78:758–772
Rinzel J, Ermentrout B (1989) Analysis of neural excitability and oscillations. In: Koch C, Segev I (eds) Methods in neuronal modeling. MIT Press, Cambridge, MA
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Prescott, S.A. (2014). Excitability: Types I, II, and III. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_151-1
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DOI: https://doi.org/10.1007/978-1-4614-7320-6_151-1
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Publisher Name: Springer, New York, NY
Online ISBN: 978-1-4614-7320-6
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