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Dynamical Systems in Neuroscience:

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208 Bifurcationswith fast and slow nullcl<strong>in</strong>es as <strong>in</strong> Fig. 6.41a and µ ≪ 1. Suppose that there is a stableequilibrium, as <strong>in</strong> Fig. 6.41a, for some values of the bifurcation parameter b < 0, anda stable limit cycle, as <strong>in</strong> Fig. 6.41h, for some other values b > 0. What k<strong>in</strong>d of abifurcation of the equilibrium occurs when b <strong>in</strong>creases from negative to positive, andthe slow nullcl<strong>in</strong>e passes the left knee of the fast N-shaped nullcl<strong>in</strong>e?The Jacobian matrix at the equilibrium has the form( )fx fL =yµg x µg yS<strong>in</strong>ce f x = 0 at the knee (prove this), but f y is typically not, the Jacobian matrixresembles the one for the Bogdanov-Takens bifurcation (6.10) <strong>in</strong> the limit µ = 0.However, the resemblance is only superficial, s<strong>in</strong>ce the relaxation oscillator does notsatisfy the non-degeneracy conditions. In particular, second-order partial derivativesof µg(x, y, b) vanish <strong>in</strong> the limit µ → 0, result<strong>in</strong>g <strong>in</strong> σ = 0 and <strong>in</strong> the disappearance ofthe term u 2 <strong>in</strong> the topological normal form (6.11).A purely geometrical consideration confirms that the transition from Fig. 6.41a toFig. 6.41h cannot be of the Bogdanov-Takens type, s<strong>in</strong>ce there is a unique equilibriumand no possibility for a saddle-node bifurcation, which always accompanies theBogdanov-Takens bifurcation. Actually, the equilibrium loses stability via Andronov-Hopf bifurcation that occurs whentr L = f x + µg y = 0 and det L = µ(f x g y − f y g x ) > 0 .The loss of stability typically happens not at the left knee, where f x = 0, but a littlebit to the right of the knee, where f x = −µg y > 0 (because g y < 0 <strong>in</strong> neuronal models).We already saw this phenomenon <strong>in</strong> Sect. 4.2.6 when we considered FitzHugh-Nagumomodel.An <strong>in</strong>terest<strong>in</strong>g observation is that the period of damped or susta<strong>in</strong>ed oscillationsnear the Andronov-Hopf bifurcation po<strong>in</strong>t <strong>in</strong> Fig. 6.41b is of the order 1/ √ µ, becausethe frequency ω = √ det L ≈ √ µ, whereas the period of large-amplitude relaxationoscillation is of the order 1/µ, because it takes 1/µ units of time to slide up anddown along the branches of the fast nullcl<strong>in</strong>e <strong>in</strong> Fig. 6.41h. Thus, the period of smallsubthreshold oscillations of a neural model may have no relation to the period ofspik<strong>in</strong>g, if the model is a relaxation oscillator.The Andronov-Hopf bifurcation could be supercritical or subcritical, depend<strong>in</strong>g onthe functions f and g; see Ex. 14 and Ex. 18. Figure 6.41 depicts the supercriticalcase. In the subcritical case, stable and unstable limit cycles are typically born viafold limit cycle bifurcation, then the unstable limit cycle goes through the shapes as<strong>in</strong> Fig. 6.41g,f,e,d,c, and b, and then shr<strong>in</strong>ks to a po<strong>in</strong>t.CanardsThe dist<strong>in</strong>ctive feature of limit cycles <strong>in</strong> Fig. 6.41c-g is that they follow the unstablebranch (dashed curve) of the fast nullcl<strong>in</strong>e before jump<strong>in</strong>g to the left or to the right

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