4.4 Article

CROSS-DIFFUSION EFFECTS ON STATIONARY PATTERN FORMATION IN THE FITZHUGH-NAGUMO MODEL

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AMER INST MATHEMATICAL SCIENCES-AIMS
DOI: 10.3934/dcdsb.2022063

关键词

Cross-diffusion; FitzHugh-Nagumo; Turing instability; out-of-phase patterns; amplitude equations

资金

  1. PRIN grant [2017YBKNCE]
  2. GNFM-INdAM

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We investigate the formation of stationary patterns in the Fitz-Hugh-Nagumo reaction-diffusion system with linear cross-diffusion terms. The study focuses on the effects of cross-diffusion on the Turing mechanism. Results show that positive values of the inhibitor cross-diffusion enlarge the parameter space region where a Turing instability is excited. Furthermore, a sufficiently large cross-diffusion coefficient of the inhibitor removes the requirement that the inhibitor must diffuse faster than the activator. In an extended parameter space region, a double bifurcation threshold of the inhibitor/activator diffusivity ratio is observed, leading to the formation of classical Turing patterns or out-of-phase spatial structures known as cross-Turing patterns, depending on the diffusion ratio.
We investigate the formation of stationary patterns in the Fitz-Hugh-Nagumo reaction-diffusion system with linear cross-diffusion terms. We focus our analysis on the effects of cross-diffusion on the Turing mechanism. Linear stability analysis indicates that positive values of the inhibitor cross-diffusion enlarge the region in the parameter space where a Turing instability is excited. A sufficiently large cross-diffusion coefficient of the inhibitor removes the requirement imposed by the classical Turing mechanism that the inhibitor must diffuse faster than the activator. In an extended region of the parameter space a new phenomenon occurs, namely the existence of a double bifurcation threshold of the inhibitor/activator diffusivity ratio for the onset of patterning instabilities: for large values of inhibitor/activator diffusivity ratio, classical Turing patterns emerge where the two species are in-phase, while, for small values of the diffusion ratio, the analysis predicts the formation of out-of-phase spatial structures (named cross-Turing patterns). In addition, for increasingly large values of the inhibitor cross-diffusion, the upper and lower bifurcation thresholds merge, so that the instability develops independently on the value of the diffusion ratio, whose magnitude selects Turing or cross-Turing patterns. Finally, the pattern selection problem is addressed through a weakly nonlinear analysis.

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