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Year 2020, Volume: 24 Issue: 1, 178 - 182, 01.02.2020
https://doi.org/10.16984/saufenbilder.521545

Abstract

References

  • [1] H. Wilson and J. Cowan, “A Mathematical theory of the functional dynamics of cortical and thalamic nervous tissue”, Biological Cybernetics. vol. 13, no. 2, pp. 55-80, 1973.
  • [2] S. I. Amari, “Dynamics of pattern formation in lateral-inhibition type neural fields,” Biological Cybernetics. vol. 27, no. 2, pp. 77-87, 1977.
  • [3] S. Coombes, “Waves, bumps, and patterns in neural field theories,” Biological Cybernetics, vol. 93, no. 2, pp 91-108, 2005.
  • [4] S. Coombes, N.A. Venkov, L. Shiau, L. Bojak, D.T.J. Liley, C.R. Laing, “Modeling electrocortical activity through improved local approximations of integral neural field equations,” Phys. Rev. E 76, 051901, 2007.
  • [5] C. Huang and S. Vandewalle, “An analysis of delay dependent stability for ordinary and partial differential equations with fixed and distributed delays,” SIAM Journal on Scientific Computing, vol. 25, no. 5, pp.1608-1632, 2004.
  • [6] S. A. Van Gils, S. G. Janssens, Yu. A. Kuznetsov and S. Visser, “On local bifurcations in neural field models with transmission delays,” Journal of Mathematical Biology, vol. 66, no. 4, pp 837-887, 2013.
  • [7] R. Veltz, “Interplay between synaptic delays and propagation delays in neural field equations,” Siam Journal of Applied Dynamical Systems, vol. 12, no. 3, pp. 1566-1612, 2013.
  • [8] R. Veltz and O. Faugeras, “Stability of the stationary solutions of neural field equations with propagation delay,” Journal of Mathematical Neuroscience, 1,1 ,2011.
  • [9] R. Veltz and O. Faugeras, “A center manifold result for delayed neural fields equations,” Siam Journal on Mathematical Analysis, vol. 45, no. 3, pp. 1527-1562, 2013.
  • [10] G. Faye and O. Faugeras, “Some theoretical and numerical results for delayed neural field equations,” Physica D: Nonlinear Phenomena, vol. 239, no. 9, pp. 561-578, 2010.
  • [11] B. Özgür and A. Demir, “Some stability charts of a neural field model of two neural populations,” Communications in Mathematics and Applications, vol. 7, no. 2, 2016.
  • [12] B. Özgür, A. Demir and S. Erman, “A note on the stability of a neural field model,” Hacettepe Journal of Mathematics and Statistics, vol. 47, no. 6, 2018.
  • [13] B. Özgür and A. Demir, “On the stability of two neuron populations interacting with each other,” Rocky Mountain Journal of Mathematics, vol. 48, no. 7, 2018.
  • [14] F. M. Atay and A. Hutt, “Stability and bifurcations in neural fields with finite propagation speed and general connectivity,” Siam Journal on Mathematical Analysis, vol. 5, no. 4, pp. 670-698, 2006.
  • [15] J. Forde and P. Nelson, “Applications of Sturm sequences to bifurcation analysis of delay differential equation models,” Journal of Mathematical Analysis and Applications, 300, pp. 273-284, 2004.

Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters

Year 2020, Volume: 24 Issue: 1, 178 - 182, 01.02.2020
https://doi.org/10.16984/saufenbilder.521545

Abstract

In this
paper, a special case for a delayed neural field model is considered. After
constructing its characteristic equation a stability analysis is made. Using
Routh-Hurwitz criterion, some conditions for characteristic equation are given
for the stability of the system.

References

  • [1] H. Wilson and J. Cowan, “A Mathematical theory of the functional dynamics of cortical and thalamic nervous tissue”, Biological Cybernetics. vol. 13, no. 2, pp. 55-80, 1973.
  • [2] S. I. Amari, “Dynamics of pattern formation in lateral-inhibition type neural fields,” Biological Cybernetics. vol. 27, no. 2, pp. 77-87, 1977.
  • [3] S. Coombes, “Waves, bumps, and patterns in neural field theories,” Biological Cybernetics, vol. 93, no. 2, pp 91-108, 2005.
  • [4] S. Coombes, N.A. Venkov, L. Shiau, L. Bojak, D.T.J. Liley, C.R. Laing, “Modeling electrocortical activity through improved local approximations of integral neural field equations,” Phys. Rev. E 76, 051901, 2007.
  • [5] C. Huang and S. Vandewalle, “An analysis of delay dependent stability for ordinary and partial differential equations with fixed and distributed delays,” SIAM Journal on Scientific Computing, vol. 25, no. 5, pp.1608-1632, 2004.
  • [6] S. A. Van Gils, S. G. Janssens, Yu. A. Kuznetsov and S. Visser, “On local bifurcations in neural field models with transmission delays,” Journal of Mathematical Biology, vol. 66, no. 4, pp 837-887, 2013.
  • [7] R. Veltz, “Interplay between synaptic delays and propagation delays in neural field equations,” Siam Journal of Applied Dynamical Systems, vol. 12, no. 3, pp. 1566-1612, 2013.
  • [8] R. Veltz and O. Faugeras, “Stability of the stationary solutions of neural field equations with propagation delay,” Journal of Mathematical Neuroscience, 1,1 ,2011.
  • [9] R. Veltz and O. Faugeras, “A center manifold result for delayed neural fields equations,” Siam Journal on Mathematical Analysis, vol. 45, no. 3, pp. 1527-1562, 2013.
  • [10] G. Faye and O. Faugeras, “Some theoretical and numerical results for delayed neural field equations,” Physica D: Nonlinear Phenomena, vol. 239, no. 9, pp. 561-578, 2010.
  • [11] B. Özgür and A. Demir, “Some stability charts of a neural field model of two neural populations,” Communications in Mathematics and Applications, vol. 7, no. 2, 2016.
  • [12] B. Özgür, A. Demir and S. Erman, “A note on the stability of a neural field model,” Hacettepe Journal of Mathematics and Statistics, vol. 47, no. 6, 2018.
  • [13] B. Özgür and A. Demir, “On the stability of two neuron populations interacting with each other,” Rocky Mountain Journal of Mathematics, vol. 48, no. 7, 2018.
  • [14] F. M. Atay and A. Hutt, “Stability and bifurcations in neural fields with finite propagation speed and general connectivity,” Siam Journal on Mathematical Analysis, vol. 5, no. 4, pp. 670-698, 2006.
  • [15] J. Forde and P. Nelson, “Applications of Sturm sequences to bifurcation analysis of delay differential equation models,” Journal of Mathematical Analysis and Applications, 300, pp. 273-284, 2004.
There are 15 citations in total.

Details

Primary Language English
Subjects Mathematical Sciences
Journal Section Research Articles
Authors

Berrak Özgür 0000-0002-9709-7376

Publication Date February 1, 2020
Submission Date February 3, 2019
Acceptance Date December 1, 2019
Published in Issue Year 2020 Volume: 24 Issue: 1

Cite

APA Özgür, B. (2020). Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters. Sakarya University Journal of Science, 24(1), 178-182. https://doi.org/10.16984/saufenbilder.521545
AMA Özgür B. Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters. SAUJS. February 2020;24(1):178-182. doi:10.16984/saufenbilder.521545
Chicago Özgür, Berrak. “Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters”. Sakarya University Journal of Science 24, no. 1 (February 2020): 178-82. https://doi.org/10.16984/saufenbilder.521545.
EndNote Özgür B (February 1, 2020) Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters. Sakarya University Journal of Science 24 1 178–182.
IEEE B. Özgür, “Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters”, SAUJS, vol. 24, no. 1, pp. 178–182, 2020, doi: 10.16984/saufenbilder.521545.
ISNAD Özgür, Berrak. “Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters”. Sakarya University Journal of Science 24/1 (February 2020), 178-182. https://doi.org/10.16984/saufenbilder.521545.
JAMA Özgür B. Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters. SAUJS. 2020;24:178–182.
MLA Özgür, Berrak. “Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters”. Sakarya University Journal of Science, vol. 24, no. 1, 2020, pp. 178-82, doi:10.16984/saufenbilder.521545.
Vancouver Özgür B. Stability Switches of A Neural Field Model: An Algebraic Study On The Parameters. SAUJS. 2020;24(1):178-82.

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