Abstract
A novel approach for simulating potential propagation in neuronal branches with high accuracy is developed. The method relies on high-order accurate difference schemes using the Summation-By-Parts operators with weak boundary and interface conditions applied to the Hodgkin-Huxley equations. This work is the first demonstrating high accuracy for that equation. Several boundary conditions are considered including the non-standard one accounting for the soma presence, which is characterized by its own partial differential equation. Well-posedness for the continuous problem as well as stability of the discrete approximation is proved for all the boundary conditions. Gains in terms of CPU times are observed when high-order operators are used, demonstrating the advantage of the high-order schemes for simulating potential propagation in large neuronal trees.
Original language | English |
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Pages (from-to) | 573-590 |
Number of pages | 18 |
Journal | Journal of Computational Physics |
Volume | 252 |
DOIs | |
Publication status | Published - 1 Nov 2013 |
Externally published | Yes |
Keywords
- High-order accuracy
- Hodgkin-Huxley
- Neuronal networks
- Stability
- Summation-by-parts
- Well-posedness
ASJC Scopus subject areas
- Numerical Analysis
- Modeling and Simulation
- Physics and Astronomy (miscellaneous)
- General Physics and Astronomy
- Computer Science Applications
- Computational Mathematics
- Applied Mathematics