NDLI: Molecular neural model recreates electrophysiology: Transcriptome-To-Physiome™ NeurobioSimulations using $COPASI^{®}$ software

Content Provider	IEEE Xplore Digital Library
Author	Phelix, C.F. Villareal, G. LeBaron, R.G. Roberson, D.J.
Copyright Year	2013
Description	Author affiliation: Univ. of Texas at San Antonio, San Antonio, TX, USA (Phelix, C.F.; LeBaron, R.G.) \|\| AL Phahelix Biometrics, Inc., San Antonio, TX, USA (Villareal, G.; Roberson, D.J.)
Abstract	A multi-compartmental molecular model has been developed for rodent basal forebrain cholinergic neurons with established gene expression levels. Reconstruction of neurons and network function were acquired using the Transcriptome-To-Physiome™ (TTP™) NeurobioSimulation. Gene expression values [NCBI GEO GSE 13379] were used to derive protein level and kinetic parameters for ligand and voltage gated ion channels in the TTP™ NeurobioSimulator Model using $COPASI^{®}$ software. Global parameters for membrane potential used permeability and ion concentrations inside and outside of the membrane in the Goldman-Hodgkin-Katz equation. Four compartments of the model neuron are included: glutamate synapse, distal dendrite, proximal dendrite, and axon hillock. The simulation of a voltage-gated sodium channel activation, and inactivated states of distal dendrites of cholinergic modeled neurons depends on the excitatory postsynaptic potential (EPSP) event. This distally activated event yielded temporally relevant proximal dendritic activation and inactivation of voltage-gated sodium and potassium channels in the reconstructed neuron. Graded potentials showed temporal summation and a classic action potential occurs at the axon hillock with sodium and potassium fluxes as expected. In future studies, we will reconstruct the electrophysiology of vulnerable neuronal populations in the diseased brain and compare them to controls thus lending substantial insight into molecular and network function corollary to neuropathogenesis.
Starting Page	178
Ending Page	181
File Size	724815
Page Count	4
File Format	PDF
ISBN	9781467319690
ISSN	19483554
DOI	10.1109/NER.2013.6695901
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-06
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Electric potential Nerve fibers Biological system modeling Computational modeling Biomembranes Mathematical model
Content Type	Text
Resource Type	Article

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