The use of automated parameter searches to improve ion channel kinetics for neural modeling
- PMID: 21243419
- DOI: 10.1007/s10827-010-0312-x
The use of automated parameter searches to improve ion channel kinetics for neural modeling
Abstract
The voltage and time dependence of ion channels can be regulated, notably by phosphorylation, interaction with phospholipids, and binding to auxiliary subunits. Many parameter variation studies have set conductance densities free while leaving kinetic channel properties fixed as the experimental constraints on the latter are usually better than on the former. Because individual cells can tightly regulate their ion channel properties, we suggest that kinetic parameters may be profitably set free during model optimization in order to both improve matches to data and refine kinetic parameters. To this end, we analyzed the parameter optimization of reduced models of three electrophysiologically characterized and morphologically reconstructed globus pallidus neurons. We performed two automated searches with different types of free parameters. First, conductance density parameters were set free. Even the best resulting models exhibited unavoidable problems which were due to limitations in our channel kinetics. We next set channel kinetics free for the optimized density matches and obtained significantly improved model performance. Some kinetic parameters consistently shifted to similar new values in multiple runs across three models, suggesting the possibility for tailored improvements to channel models. These results suggest that optimized channel kinetics can improve model matches to experimental voltage traces, particularly for channels characterized under different experimental conditions than recorded data to be matched by a model. The resulting shifts in channel kinetics from the original template provide valuable guidance for future experimental efforts to determine the detailed kinetics of channel isoforms and possible modulated states in particular types of neurons.
Similar articles
-
A numerical approach to ion channel modelling using whole-cell voltage-clamp recordings and a genetic algorithm.PLoS Comput Biol. 2007 Aug;3(8):e169. doi: 10.1371/journal.pcbi.0030169. Epub 2007 Jul 18. PLoS Comput Biol. 2007. PMID: 17784781 Free PMC article.
-
Channel density distributions explain spiking variability in the globus pallidus: a combined physiology and computer simulation database approach.J Neurosci. 2008 Jul 23;28(30):7476-91. doi: 10.1523/JNEUROSCI.4198-07.2008. J Neurosci. 2008. PMID: 18650326 Free PMC article.
-
Calcium-activated SK channels influence voltage-gated ion channels to determine the precision of firing in globus pallidus neurons.J Neurosci. 2009 Jul 1;29(26):8452-61. doi: 10.1523/JNEUROSCI.0576-09.2009. J Neurosci. 2009. PMID: 19571136 Free PMC article.
-
Channel noise in neurons.Trends Neurosci. 2000 Mar;23(3):131-7. doi: 10.1016/s0166-2236(99)01521-0. Trends Neurosci. 2000. PMID: 10675918 Review.
-
How voltage-gated ion channels alter the functional properties of ganglion and amacrine cell dendrites.Arch Ital Biol. 2002 Oct;140(4):347-59. Arch Ital Biol. 2002. PMID: 12228988 Review.
Cited by
-
Automated evolutionary optimization of ion channel conductances and kinetics in models of young and aged rhesus monkey pyramidal neurons.J Comput Neurosci. 2016 Aug;41(1):65-90. doi: 10.1007/s10827-016-0605-9. Epub 2016 Apr 22. J Comput Neurosci. 2016. PMID: 27106692
-
A flexible, interactive software tool for fitting the parameters of neuronal models.Front Neuroinform. 2014 Jul 10;8:63. doi: 10.3389/fninf.2014.00063. eCollection 2014. Front Neuroinform. 2014. PMID: 25071540 Free PMC article.
-
Patterns of presynaptic activity and synaptic strength interact to produce motor output.J Neurosci. 2011 Nov 30;31(48):17555-71. doi: 10.1523/JNEUROSCI.4723-11.2011. J Neurosci. 2011. PMID: 22131417 Free PMC article.
-
Rapid genetic algorithm optimization of a mouse computational model: benefits for anthropomorphization of neonatal mouse cardiomyocytes.Front Physiol. 2012 Nov 5;3:421. doi: 10.3389/fphys.2012.00421. eCollection 2012. Front Physiol. 2012. PMID: 23133423 Free PMC article.
-
Automatic Construction of Predictive Neuron Models through Large Scale Assimilation of Electrophysiological Data.Sci Rep. 2016 Sep 8;6:32749. doi: 10.1038/srep32749. Sci Rep. 2016. PMID: 27605157 Free PMC article.
References
Publication types
MeSH terms
Substances
Grants and funding
LinkOut - more resources
Full Text Sources