Approximations for Semi-Markov Single Ion Channel Models

1999 ◽  
pp. 103-115 ◽  
Author(s):  
Susan M. Pitts
Keyword(s):  
Ion Channel ◽  
Channel Models

On the exact distribution of observed open times in single ion channel models

1993 ◽  
Vol 30 (03) ◽  
pp. 529-537 ◽  
Author(s):  
Frank Ball ◽  
Robin K. Milne ◽  
Geoffrey F. Yeo
Keyword(s):  
Ion Channel ◽  
Continuous Time ◽  
Exact Distribution ◽  
Continuous Time Markov Chain ◽  
Channel Models ◽  
Direct Derivation ◽  
Markov Chain Models ◽  
Closed Class ◽  
Open Time ◽  
Semi Markov Processes

Continuous-time Markov chain models have been widely considered for the gating behaviour of a single ion channel. In such models the state space is usually partitioned into two classes, designated ‘open' and ‘closed', and there is ‘aggregation' in that it is possible to observe only which class the process is in at any given time. Hawkes et al. (1990) have derived an expression for the density function of the exact distribution of an observed open time in such an aggregated Markov model, where brief sojourns in either the open or the closed class are unobservable. This paper extends their result to single ion channel models based on aggregated semi-Markov processes, giving a more direct derivation which is probabilistic and exhibits clearly the combinatorial content.

scholarly journals Single ion channel models incorporating aggregation and time interval omission

1993 ◽  
Vol 64 (2) ◽  
pp. 357-374 ◽  
Author(s):  
F.G. Ball ◽  
G.F. Yeo ◽  
R.K. Milne ◽  
R.O. Edeson ◽  
B.W. Madsen ◽  
...  
Keyword(s):  
Ion Channel ◽  
Time Interval ◽  
Channel Models

scholarly journals ICGenealogy: Mapping the Function of Neuronal Ion Channels in Model and Experiment

2016 ◽  
Author(s):  
William F Podlaski ◽  
Alexander Seeholzer ◽  
Lukas N Groschner ◽  
Gero Miesenböck ◽  
Rajnish Ranjan ◽  
...  
Keyword(s):  
Ion Channels ◽  
Ion Channel ◽  
Large Scale ◽  
Building Blocks ◽  
Web Interface ◽  
Neuron Models ◽  
Channel Models ◽  
Ion Channel Kinetics ◽  
Scale Classification

SummaryIon channel models are the building blocks of computational neuron models. Their biological fidelity is therefore crucial for the interpretability of simulations. However, the number of published models, and the lack of standardization, make the comparison of models with one another and with experimental data difficult. Here, we present a framework for the automated large-scale classification of ion channel models. Using annotated metadata and model responses to a set of voltage-clamp protocols, we assigned 2378 models of voltage- and calcium-gated ion channels coded in NEURON to 211 clusters. The IonChannelGenealogy web interface provides an interactive resource for the categorization of new and existing models and experimental recordings. It enables quantitative comparisons of simulated and/or measured ion channel kinetics, and facilitates field-wide standardization of experimentally-constrained modeling.

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