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Computational modeling of activity dependent velocity changes in peripheral C-fibers
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0003-0281-9450
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
Dept. of Anaesthesiology Mannheim, Heidelberg University, Mannheim, German.
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2011 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Initiation and propagation of action potentials along unmyelinated C-fibers are the first steps of the pain pathway. Propagation velocity and its fiber class-specific activity-dependent slowing (ADS) is intimately linked to fibre excitability. In chronic pain patients, ADS alterations have been suggested to reflect increased excitability, possibly underlying clinical pain. Due to their small diameter, peripheral axons of nociceptors in patients are not accessible for intraaxonal recordings of their ion channel properties. We have therefore constructed a model of a C-fibre to study the relationship between ion channel composition and velocity changes as well as excitability. Ion channels are modeled from data of DRG somata using a Hodgkin-Huxley formalism (Na currents: TTX-sensitive, Nav1.8, Nav1.9, K currents: Kdr, A-type, Kv7.3, non-specific cationic: HCN). Moreover, ion pumps (Na/K-ATPase) and concentrations of intra and extraaxonal sodium and potassium are also included. The geometry and temperature of the fibre represents a section of the superficial branch and the deeper parent and is represented by a multicompartmental structure where each compartment contains passive as well as ion channel and pump elements. Using parameter estimation techniques, we optimized ion channel and pump expression pattern such that basic electrophysiological characteristics of the action potential and its velocity matched the experimental data. Moreover, we have also replicated activity dependent slowing. In ongoing work, we extend optimization to also include recovery cycles. The model will be used to study hypothesis of the relationship between individual ion channel subtypes and axonal excitability related to pain, generating independent information on impact of selective neuronal targets.

Place, publisher, year, edition, pages
2011. 162.05- p.
National Category
Neurosciences
Identifiers
URN: urn:nbn:se:kth:diva-138913OAI: oai:DiVA.org:kth-138913DiVA: diva2:681925
Conference
Neuroscience 2011, Annual Meeting of the Society for Neuroscience, Nov. 12-16, 2011, Washington, DC
Note

QC 20150330

Available from: 2013-12-20 Created: 2013-12-20 Last updated: 2015-03-30Bibliographically approved

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Fransén, Erik

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