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doi: 10.3934/dcdsb.2022117
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## Stability and dynamics of spike-type solutions to delayed Gierer-Meinhardt equations

 1 Department of Mathematics, Simon Fraser University, British Columbia, Canada 2 Current affiliation: Department of Mathematics, Columbia College, British Columbia, Canada 3 Department of Mathematics, Dalhousie University, Nova Scotia, Canada

* Corresponding author: David Iron

Received  May 2021 Revised  May 2022 Early access June 2022

For a specific set of parameters, we analyze the stability of a one-spike equilibrium solution to the one-dimensional Gierer-Meinhardt reaction-diffusion model with delay in the components of the reaction-kinetics terms. Assuming slow activator diffusivity, we consider instabilities due to Hopf bifurcation in both the spike position and the spike profile for increasing values of the time-delay parameter $T$. Using method of matched asymptotic expansions it is shown that the model can be reduced to a system of ordinary differential equations representing the position of the slowly evolving spike solution. The reduced evolution equations for the one-spike solution undergoes a Hopf bifurcation in the spike position in two cases: when the negative feedback of the activator equation is delayed, and when delay is in both the negative feedback of the activator equation and the non-linear production term of the inhibitor equation. Instabilities in the spike profile are also considered, and it is shown that the spike solution is unstable as $T$ is increased beyond a critical Hopf bifurcation value $T_H$, and this occurs for the same cases as in the spike position analysis. In all cases, the instability in the profile is triggered before the positional instability. If however the degradation of activator is delayed, we find stable positional oscillations can occur in this system.

Citation: Nancy Khalil, David Iron, Theodore Kolokolnikov. Stability and dynamics of spike-type solutions to delayed Gierer-Meinhardt equations. Discrete and Continuous Dynamical Systems - B, doi: 10.3934/dcdsb.2022117
##### References:
 [1] U. M. Ascher, S. J. Ruuth and R. J. Spiteri, Implicit-explicit Runge-Kutta methods for time-dependent partial differential equations, Appl. Numer. Math., 25 (1997), 151-167.  doi: 10.1016/S0168-9274(97)00056-1. [2] S. Chen and J. Shi, Global attractivity of equlibrium in Gierer-Meinhardt system with activator production saturation and gene expression time delays, Nonlinear Anal. Real World Appl., 14 (2013), 1871-1886.  doi: 10.1016/j.nonrwa.2012.12.004. [3] X. Chen and M. Kowalcyzk, Dynamics of an interior spike in the Gierer-Meinhardt system, SIAM J. Math. Anal., 33 (2001), 172-193.  doi: 10.1137/S0036141099364954. [4] N. Fadai, M. J. Ward and J. Wei, The stability of spikes in the Gierer-Meinhardt model with delayed reaction-kinetics, to be submitted, SIAM J. Appl. Math., (2015), 23 pp. [5] N. Fadai, M. J. Ward and J. Wei, A time-delay in the activator kinetics enhances the stability of a spike solution to the Gierer-Meinhardt model, Discrete Contin. Dyn. Syst. Ser. B, 23 (2018), 1431-1458.  doi: 10.3934/dcdsb.2018158. [6] A. Gierer and H. Meinhardt, A theory of biological pattern formation, Kybernetik, 12 (1972), 30-39.  doi: 10.1007/BF00289234. [7] D. Iron and M. J. Ward, A metastable spike solution for a non-local reaction-diffusion model, SIAM J. Appl. Math., 60 (2000), 778-802.  doi: 10.1137/S0036139998338340. [8] D. Iron and M. J. Ward, The dynamics of multispike solutions to the one-dimensional Gierer-Meinhardt model, SIAM J. Appl. Math., 62 (2002), 1924-1951.  doi: 10.1137/S0036139901393676. [9] D. Iron, M. J. Ward and J. Wei, The stability of spike solutions to the one-dimensional Gierer-Meinhardt model, Physica D, 150 (2001), 25-62.  doi: 10.1016/S0167-2789(00)00206-2. [10] T. Kolokolnikov and J. Wei, Stability of spike solutions in a competition model with cross-diffusion, SIAM J. Appl. Math., 71 (2011), 1428-1457.  doi: 10.1137/100808381. [11] C. Levy and D. Iron, Dynamics and stability of a three-dimensional model of cell signal transduction with delay, Nonlinearity, 28 (2015), 2515-2553.  doi: 10.1088/0951-7715/28/7/2515. [12] Y. Nec and M. J. Ward, An explicitly solvable nonlocal eigenvalue problem and the stability of a spike for a sub-diffusive reaction-diffusion system, Math. Model. of Nat. Phenom., 8 (2013), 55-87.  doi: 10.1051/mmnp/20138205. [13] S. Seirin Lee, E. A. Gaffney and N. A. M. Monk, The influence of gene expression time delays on Gierer-Meinhardt pattern formation systems, Bull. Math. Biol., 72 (2010), 2139-2160.  doi: 10.1007/s11538-010-9532-5. [14] S. Seirin Lee, E. A. Gaffney and N. A. M. Monk, The influence of gene expression time delays on Gierer-Meinhardt pattern formation systems, Bull. Math. Bio., 72 (2010), 2139-2160.  doi: 10.1007/s11538-010-9532-5. [15] A. M. Turing, The chemical basis of morphogenesis, Philos. Trans. Roy. Soc. London Ser. B, 327 (1952), 37-72.  doi: 10.1098/rstb.1952.0012. [16] M. Van Dyke, Perturbation Methods in Fluid Mechanics, Applied Mathematics and Mechanics, 8, 1964. [17] M. J. Ward and J. Wei, Hopf bifurcation of spike solutions for the shadow Gierer-Meinhardt model, Europ. J. Appl. Math., 14 (2003), 677-711.  doi: 10.1017/S0956792503005278. [18] M. J. Ward and J. Wei, Hopf bifurcation and oscillatory instabilities of spike solutions for the one-dimensional Gierer-Meinhardt model, J. Nonlinear Science, 13 (2003), 209-264.  doi: 10.1007/s00332-002-0531-z. [19] J. Wei, On single interior spike solutions for the Gierer-Meinhardt system: Uniqueness and stability estimates, Europ. J. Appl. Math., 10 (1999), 353-378.  doi: 10.1017/S0956792599003770. [20] J. Wei, Existence and stability of spikes for the Gierer-Meinhardt system, book chapter in Handbook of Differential Equations, Stationary Partial Differential Equations, Vol. 5 (M. Chipot ed.), Elsevier, (2008), 489–585. doi: 10.1016/S1874-5733(08)80013-7. [21] J. Wei and M. Winter, Spikes for the two-dimensional Gierer-Meinhardt system: The weak coupling case, J. Nonlinear Sci., 11 (2001), 415-458.  doi: 10.1007/s00332-001-0380-1.

show all references

##### References:
 [1] U. M. Ascher, S. J. Ruuth and R. J. Spiteri, Implicit-explicit Runge-Kutta methods for time-dependent partial differential equations, Appl. Numer. Math., 25 (1997), 151-167.  doi: 10.1016/S0168-9274(97)00056-1. [2] S. Chen and J. Shi, Global attractivity of equlibrium in Gierer-Meinhardt system with activator production saturation and gene expression time delays, Nonlinear Anal. Real World Appl., 14 (2013), 1871-1886.  doi: 10.1016/j.nonrwa.2012.12.004. [3] X. Chen and M. Kowalcyzk, Dynamics of an interior spike in the Gierer-Meinhardt system, SIAM J. Math. Anal., 33 (2001), 172-193.  doi: 10.1137/S0036141099364954. [4] N. Fadai, M. J. Ward and J. Wei, The stability of spikes in the Gierer-Meinhardt model with delayed reaction-kinetics, to be submitted, SIAM J. Appl. Math., (2015), 23 pp. [5] N. Fadai, M. J. Ward and J. Wei, A time-delay in the activator kinetics enhances the stability of a spike solution to the Gierer-Meinhardt model, Discrete Contin. Dyn. Syst. Ser. B, 23 (2018), 1431-1458.  doi: 10.3934/dcdsb.2018158. [6] A. Gierer and H. Meinhardt, A theory of biological pattern formation, Kybernetik, 12 (1972), 30-39.  doi: 10.1007/BF00289234. [7] D. Iron and M. J. Ward, A metastable spike solution for a non-local reaction-diffusion model, SIAM J. Appl. Math., 60 (2000), 778-802.  doi: 10.1137/S0036139998338340. [8] D. Iron and M. J. Ward, The dynamics of multispike solutions to the one-dimensional Gierer-Meinhardt model, SIAM J. Appl. Math., 62 (2002), 1924-1951.  doi: 10.1137/S0036139901393676. [9] D. Iron, M. J. Ward and J. Wei, The stability of spike solutions to the one-dimensional Gierer-Meinhardt model, Physica D, 150 (2001), 25-62.  doi: 10.1016/S0167-2789(00)00206-2. [10] T. Kolokolnikov and J. Wei, Stability of spike solutions in a competition model with cross-diffusion, SIAM J. Appl. Math., 71 (2011), 1428-1457.  doi: 10.1137/100808381. [11] C. Levy and D. Iron, Dynamics and stability of a three-dimensional model of cell signal transduction with delay, Nonlinearity, 28 (2015), 2515-2553.  doi: 10.1088/0951-7715/28/7/2515. [12] Y. Nec and M. J. Ward, An explicitly solvable nonlocal eigenvalue problem and the stability of a spike for a sub-diffusive reaction-diffusion system, Math. Model. of Nat. Phenom., 8 (2013), 55-87.  doi: 10.1051/mmnp/20138205. [13] S. Seirin Lee, E. A. Gaffney and N. A. M. Monk, The influence of gene expression time delays on Gierer-Meinhardt pattern formation systems, Bull. Math. Biol., 72 (2010), 2139-2160.  doi: 10.1007/s11538-010-9532-5. [14] S. Seirin Lee, E. A. Gaffney and N. A. M. Monk, The influence of gene expression time delays on Gierer-Meinhardt pattern formation systems, Bull. Math. Bio., 72 (2010), 2139-2160.  doi: 10.1007/s11538-010-9532-5. [15] A. M. Turing, The chemical basis of morphogenesis, Philos. Trans. Roy. Soc. London Ser. B, 327 (1952), 37-72.  doi: 10.1098/rstb.1952.0012. [16] M. Van Dyke, Perturbation Methods in Fluid Mechanics, Applied Mathematics and Mechanics, 8, 1964. [17] M. J. Ward and J. Wei, Hopf bifurcation of spike solutions for the shadow Gierer-Meinhardt model, Europ. J. Appl. Math., 14 (2003), 677-711.  doi: 10.1017/S0956792503005278. [18] M. J. Ward and J. Wei, Hopf bifurcation and oscillatory instabilities of spike solutions for the one-dimensional Gierer-Meinhardt model, J. Nonlinear Science, 13 (2003), 209-264.  doi: 10.1007/s00332-002-0531-z. [19] J. Wei, On single interior spike solutions for the Gierer-Meinhardt system: Uniqueness and stability estimates, Europ. J. Appl. Math., 10 (1999), 353-378.  doi: 10.1017/S0956792599003770. [20] J. Wei, Existence and stability of spikes for the Gierer-Meinhardt system, book chapter in Handbook of Differential Equations, Stationary Partial Differential Equations, Vol. 5 (M. Chipot ed.), Elsevier, (2008), 489–585. doi: 10.1016/S1874-5733(08)80013-7. [21] J. Wei and M. Winter, Spikes for the two-dimensional Gierer-Meinhardt system: The weak coupling case, J. Nonlinear Sci., 11 (2001), 415-458.  doi: 10.1007/s00332-001-0380-1.
Left: Plot of the one-spike stable equilibrium solution $a$ (blue curve) and $h$ (red curve) for the model in (2) with delay in the inhibitor equation. Right: Plot of the trajectory $x_0(\tau)$ for the center of the spike. The dotted curve is the full numerical simulation obtained from (2), and the solid curve is the asymptotic result as obtained from (21), with delay in the non-linear term of the inhibitor equation. Parameter values used are $T = 0.1$, $\epsilon = 0.06$, $\mu = 1$, $L = 1$ and $D = 1$
Left: Plot of the one-spike stable equilibrium solution $a$ (solid curve) and $h$ (dotted curve) for the model in (22), with delay in the $h$ term of the activator equation. Right: Plot of the trajectory $x_0(\tau)$ for the center of the spike. The dotted curve is the full numerical simulation obtained from (22), and the solid curve is the asymptotic result as obtained from (30), with delay in the $h$ term of the activator equation. Parameter values used are $T = 0.1$, $\epsilon = 0.06$, $\mu = 1$, $L = 1$ and $D = 1$
Left: Plot of the one-spike stable equilibrium solution $a$ (solid curve) and $h$ (dotted curve) for the model in (31), with delay in both the activator regulation and inhibitor production. Right: Plot of the trajectory $x_0(\tau)$ for the center of the spike. The dotted curve is the full numerical simulation obtained from (31), and the solid curve is the asymptotic result as obtained from (35), with delay in the $h$ term of the activator equation. Parameter values used are $T = 0.1$, $\epsilon = 0.06$, $\mu = 1$, and $D = 1$
Left: Plot of the one-spike stable equilibrium solution $a$ (solid curve) and $h$ (dotted curve) for the model in (36), where the nonlinear term of the activator equation is delayed. Right: Plot of the trajectory $x_0(\tau)$ for the center of the spike. The dotted curve is the full numerical simulation obtained from (36), and the solid curve is the asymptotic result as obtained from (49). Parameter values used are $T = 0.1$, $\epsilon = 0.06$, $\mu = 1$, $L = 1$ and $D = 1$
Left: Plot of the one-spike stable equilibrium solution $a$ (solid curve) and $h$ (dotted curve) for the model in (50), where all the nonlinear terms are delayed. Right: Plot of the trajectory $x_0(\tau)$ for the center of the spike. The dotted curve is the full numerical simulation obtained from (50), and the solid curve is the asymptotic result as obtained from (51). Parameter values used are $T = 0.1$, $\epsilon = 0.06$, $\mu = 1$, $L = 1$ and $D = 1$
Plot of the motion of the center of the spike as obtained from the asymptotic ODE (21), with delay in the inhibitor equation. Increasing values of the delay $T$ were used, and initial points as indicated. There are no oscillations in this case, and the equilibrium position $x_0 = 0.5$ is always stable. Parameters used are $\epsilon = 0.06$, $\mu = 1$, and $D = 1$
Solutions of (64) for various values of $L$
Plot of the asymptotic result $x_0(t)$ as obtained from (30), with delay in the $h$ term of the activator equation, for delay $T = 1.7<T_H$ (left figure) and $T = 1.9>T_H$ (right figure). Parameters used are $\epsilon = 0.06$, $\mu = 1$, $L = 2$ and $D = 1$
Solutions of (68) for a range of $L$
Plot of the asymptotic result $x_0(t)$ as obtained from (35), where delay is in both the activator and inhibitor equations, for delay values $T_1 = 1.3$ (feft figure) and $T_1 = 1.45$ (right figure). Parameters used are $\epsilon = 0.06$, $\mu = 1$, $L = 2$ and $D = 1$
Plot of trajectories corresponding to motion of the spike as obtained from the asymptotic ODE (49), with increasing values of delay in the non-linear term of the activator equation, and using various initial points as indicated. No oscillations are observed and all trajectories approach the stable equilibrium position $x_0 = 0.5$. Parameters used are $\epsilon = 0.06$, $\mu = 1$, and $D = 1$
Solution to (85) for various values of $L$
Amplitude of spike solution to (2) for delay below and above the critical value of $T_H = 0.519$. Here $D = 1$, $\mu = 1$, $L = 1$ and $\varepsilon = 0.06$
Amplitude of spike solution to (31) for delay below and above the critical value of $T_H\sim0.25$. Here $D = 1$, $\mu = 1$, $L = 1$ and $\varepsilon = 0.06$
Plot of $Re(\lambda_0)$ versus $Im(\lambda_0)$ for the eigenvalue of matrix $\mathcal{M}$. In figure (a), the red curve follows $T = 0$ to 0.6. Black from 0.6 to 1.4, blue form 1.4 to 1.6 and green 1.6 to 2.2
Simulations of (99) with $D = 1$, $\mu = 1$, $L = 1$. In 16(a), $T = .9$ and in 16(b), $T = 1.04$. Time is plotted on the horizontal axis and $x_0$ is plotted on the vertical axis
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