Abstract
The cable equation is one useful description for modeling phenomena such as neuronal dynamics and electrophysiology. The time-fractional cable model (TFCM) generalizes the classical cable equation by considering the anomalous diffusion that occurs in the ionic motion present for example in the neuronal system. This paper proposes a novel meshless numerical procedure, the radial basis function-generated finite difference (RBF-FD), to approximate the TFCM involving two fractional temporal derivatives. The time discretization of the TFCM is performed based on the Grünwald–Letnikov expansion. The spatial derivatives are discretized using the RBF-FD. The pattern of data distribution in the support domain is assumed as having a fixed number of points. The RBF-FD is based on the local support domain that leads to a sparsity system and also tackles the ill-conditioning problem caused by global collocation method. The theoretical stability and the convergence analysis of the scheme are also discussed in detail. It is shown that the proposed method is efficient and that the numerical results confirm the theoretical formulation.
Similar content being viewed by others
References
Baleanu D, Güvenç ZB, Machado JT et al (2010) New trends in nanotechnology and fractional calculus applications. Springer, Berlin
Baleanu D, Machado JAT, Luo AC (2011) Fractional dynamics and control. Springer, Berlin
Barkai E, Metzler R, Klafter J (2000) From continuous time random walks to the fractional Fokker–Planck equation. Phys Rev E 61(1):132
Buhmann MD (2003) Radial basis functions: theory and implementations, vol 12. Cambridge University Press, Cambridge
Bulut F, Oruç Ö, Esen A (2015) Numerical solutions of fractional system of partial differential equations by Haar wavelets. Comput Model Eng Sci 108(4):263–284
Cavlak E, Bayram M et al (2014) An approximate solution of fractional cable equation by homotopy analysis method. Bound Value Probl 2014(1):58
Dehestani H, Ordokhani Y, Razzaghi M (2019) Application of the modified operational matrices in multiterm variable-order time-fractional partial differential equations. Math Methods Appl Sci 42(18):7296–7313
Dehghan M, Abbaszadeh M (2016) Analysis of the element free Galerkin (EFG) method for solving fractional cable equation with dirichlet boundary condition. Appl Numer Math 109:208–234
Dentz M, Cortis A, Scher H, Berkowitz B (2004) Time behavior of solute transport in heterogeneous media: transition from anomalous to normal transport. Adv Water Resour 27(2):155–173
Esen A, Bulut F, Oruç Ö (2016) A unified approach for the numerical solution of time fractional Burgers’ type equations. Eur Phys J Plus 131(4):116
Fasshauer GE (2007) Meshfree approximation methods with matlab: (with CD-ROM), vol 6. World Scientific Publishing Company, Singapore
Franke C, Schaback R (1998) Convergence order estimates of meshless collocation methods using radial basis functions. Adv Comput Math 8(4):381–399
Franke R (1982) Scattered data interpolation: tests of some methods. Math Comput 38(157):181–200
Hardy RL (1971) Multiquadric equations of topography and other irregular surfaces. J Geophys Res 76(8):1905–1915
Hardy RL (1990) Theory and applications of the multiquadric-biharmonic method 20 years of discovery 1968–1988. Comput Math Appl 19(8–9):163–208
Kansa EJ (1990) Multiquadrics—a scattered data approximation scheme with applications to computational fluid-dynamics—I surface approximations and partial derivative estimates. Comput Math Appl 19(8–9):127–145
Kansa EJ (1990) Multiquadrics—a scattered data approximation scheme with applications to computational fluid-dynamics—II solutions to parabolic, hyperbolic and elliptic partial differential equations. Comput Math Appl 19(8–9):147–161
Koch C (1999) Biophysics of computation: information processing in single neurons. Oxford University Press, Oxford
Langlands T, Henry B, Wearne S (2005) Solution of a fractional cable equation: finite case. Applied mathematics report AMR05/34, University of New South Wales
Langlands T, Henry B, Wearne S (2009) Fractional cable equation models for anomalous electrodiffusion in nerve cells: infinite domain solutions. J Math Biol 59(6):761
Lin Y, Li X, Xu C (2011) Finite difference/spectral approximations for the fractional cable equation. Math Comput 80(275):1369–1396
Liu F, Yang Q, Turner I (2011) Two new implicit numerical methods for the fractional cable equation. J Comput Nonlinear Dyn 6(1):011009
Liu F, Zhuang P, Anh V, Turner I, Burrage K (2007) Stability and convergence of the difference methods for the space-time fractional advection–diffusion equation. Appl Math Comput 191(1):12–20
Machado J (1998) Fractional-order derivative approximations in discrete-time control systems. SAMS, Carmel, pp 1–16
Madych W, Nelson S (1990) Multivariate interpolation and conditionally positive definite functions. II. Math Comput 54(189):211–230
Metzler R, Klafter J (2000) The random walk’s guide to anomalous diffusion: a fractional dynamics approach. Phys Rep 339(1):1–77
Metzler R, Klafter J, Sokolov IM (1998) Anomalous transport in external fields: continuous time random walks and fractional diffusion equations extended. Phys Rev E 58(2):1621
Micchelli CA (1984) Interpolation of scattered data: distance matrices and conditionally positive definite functions. In: Singh SP, Burry JWH, Watson B (eds) Approximation theory and spline functions. Springer, Dordrecht, pp 143–145
Milici C, Drăgănescu G, Machado JT (2019) Introduction to fractional differential equations, vol 25. Springer, Dordrecht
Nikan O, Golbabai A, Machado JT, Nikazad T (2020) Numerical solution of the fractional Rayleigh–Stokes model arising in a heated generalized second-grade fluid. Eng Comput., pp 1–14. https://doi.org/10.1007/s00366-019-00913-y
Nikan O, Machado JT, Golbabai A, Nikazad T (2019) Numerical investigation of the nonlinear modified anomalous diffusion process. Nonlinear Dyn 97(4):2757–2775
Nikan O, Machado JT, Golbabai A, Nikazad T (2020) Numerical approach for modeling fractal mobile/immobile transport model in porous and fractured media. Int Commun Heat Mass Transfer 111:104443
Oldham KB, Spanier J (1974) The fractional calculus, vol 111 of mathematics in science and engineering. Elsevier, Amsterdam
Oruç Ö, Esen A, Bulut F (2019) A haar wavelet approximation for two-dimensional time fractional reaction–subdiffusion equation. Eng Comput 35(1):75–86
Oruç Ö, Esen A, Bulut F (2019) A unified finite difference Chebyshev wavelet method for numerically solving time fractional Burgers’ equation. Discrete Contin Dyn Syst S 12(3):533
Podlubny I (1998) Fractional differential equations: an introduction to fractional derivatives, fractional differential equations, to methods of their solution and some of their applications, vol 198. Elsevier, Amsterdam
Qian N, Sejnowski T (1989) An electro-diffusion model for computing membrane potentials and ionic concentrations in branching dendrites, spines and axons. Biol Cybern 62(1):1–15
Quintana-Murillo J, Yuste SB (2011) An explicit numerical method for the fractional cable equation. Int J Differ Equ 2011:231920
Rahimkhani P, Ordokhani Y (2019) A numerical scheme based on Bernoulli wavelets and collocation method for solving fractional partial differential equations with dirichlet boundary conditions. Numer Methods Partial Differ Equ 35(1):34–59
Rahimkhani P, Ordokhani Y (2020) Approximate solution of nonlinear fractional integro-differential equations using fractional alternative Legendre functions. J Comput Appl Math 365:112365
Ritchie K, Shan XY, Kondo J, Iwasawa K, Fujiwara T, Kusumi A (2005) Detection of non-Brownian diffusion in the cell membrane in single molecule tracking. Biophys J 88(3):2266–2277
Sarra SA (2012) A local radial basis function method for advection–diffusion–reaction equations on complexly shaped domains. Appl Math Comput 218(19):9853–9865
Sarra SA, Kansa EJ (2009) Multiquadric radial basis function approximation methods for the numerical solution of partial differential equations. Adv Comput Mech 2(2):1–206
Saxton MJ (2001) Anomalous subdiffusion in fluorescence photobleaching recovery: a Monte Carlo study. Biophys J 81(4):2226–2240
Schaback R (1995) Error estimates and condition numbers for radial basis function interpolation. Adv Comput Math 3(3):251–264
Shivanian E, Jafarabadi A (2018) An improved meshless algorithm for a kind of fractional cable problem with error estimate. Chaos Solitons Fractals 110:138–151
Shu C, Ding H, Yeo K (2003) Local radial basis function-based differential quadrature method and its application to solve two-dimensional incompressible Navier–Stokes equations. Comput Methods Appl Mech Eng 192(7–8):941–954
Tolstykh A, Shirobokov D (2003) On using radial basis functions in a “finite difference mode” with applications to elasticity problems. Comput Mech 33(1):68–79
Uchaikin VV (2013) Fractional derivatives for physicists and engineers, vol 2. Springer, Berlin
Wendland H (2004) Scattered data approximation, vol 17. Cambridge University Press, Cambridge
Wright GB, Fornberg B (2006) Scattered node compact finite difference-type formulas generated from radial basis functions. J Comput Phys 212(1):99–123
Yuste SB (2006) Weighted average finite difference methods for fractional diffusion equations. J Comput Phys 216(1):264–274
Zhang H, Yang X, Han X (2014) Discrete-time orthogonal spline collocation method with application to two-dimensional fractional cable equation. Comput Math Appl 68(12):1710–1722
Zhuang P, Liu F, Turner I, Anh V (2016) Galerkin finite element method and error analysis for the fractional cable equation. Numer Algorithms 72(2):447–466
Acknowledgements
The authors express their gratitude to the Editor-in-Chief (Professor Mark Shephard), Associate Editor and both the reviewers for their valuable suggestions and useful comments to make this paper better.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Nikan, O., Golbabai, A., Machado, J.A.T. et al. Numerical approximation of the time fractional cable model arising in neuronal dynamics. Engineering with Computers 38, 155–173 (2022). https://doi.org/10.1007/s00366-020-01033-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00366-020-01033-8