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Dynamical Systems in Neuroscience:

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116 Two-Dimensional <strong>Systems</strong>heterocl<strong>in</strong>ic orbithomocl<strong>in</strong>icorbitFigure 4.25: A heterocl<strong>in</strong>ic orbit starts andends at different equilibria. A homocl<strong>in</strong>ic orbitstarts and ends at the same equilibrium.trajectory will converge to the rest attractor (left). If the <strong>in</strong>itial condition is preciselyon the stable manifold (po<strong>in</strong>t C), the trajectory converges neither to rest nor to spik<strong>in</strong>gstate, but to the saddle equilibrium. Of course, this case is highly unstable and smallperturbations will certa<strong>in</strong>ly push the trajectory to one or the other side. The importantmessage <strong>in</strong> Fig. 4.24 is that a threshold is not a po<strong>in</strong>t, i.e., a s<strong>in</strong>gle voltage value, buta trajectory on the phase plane. (F<strong>in</strong>d an exceptional case when the threshold lookslike a s<strong>in</strong>gle voltage value. H<strong>in</strong>t: see Fig. 4.17.)4.3.3 Homocl<strong>in</strong>ic/heterocl<strong>in</strong>ic trajectoriesFig. 4.24 shows that trajectories form<strong>in</strong>g the unstable manifold orig<strong>in</strong>ate from thesaddle. Where do they go? Similarly, the trajectories form<strong>in</strong>g the stable manifoldterm<strong>in</strong>ate at the saddle. Where do they come from? We say that a trajectory isheterocl<strong>in</strong>ic if it orig<strong>in</strong>ates at one equilibrium and term<strong>in</strong>ates at another equilibrium,as <strong>in</strong> Fig. 4.25. A trajectory is homocl<strong>in</strong>ic if it orig<strong>in</strong>ates and term<strong>in</strong>ates at the sameequilibrium. These types of trajectories play an important role <strong>in</strong> geometrical analysisof dynamical systems.Heterocl<strong>in</strong>ic trajectories connect unstable and stable equilibria, as <strong>in</strong> Fig. 4.26, andthey are ubiquitous <strong>in</strong> dynamical systems hav<strong>in</strong>g two or more equilibrium po<strong>in</strong>ts. Infact, there are <strong>in</strong>f<strong>in</strong>itely many heterocl<strong>in</strong>ic trajectories <strong>in</strong> Fig. 4.26, s<strong>in</strong>ce all trajectories<strong>in</strong>side the bold loop orig<strong>in</strong>ate at the unstable focus and term<strong>in</strong>ate at the stable node.(F<strong>in</strong>d the exceptional trajectory that ends elsewhere.)In contrast, homocl<strong>in</strong>ic trajectories are rare. First, a homocl<strong>in</strong>ic trajectory divergesfrom an equilibrium, therefore the equilibrium must be unstable. Next, the trajectorymakes a loop and returns to the same equilibrium, as <strong>in</strong> Fig. 4.27. It needs to hitthe unstable equilibrium precisely, s<strong>in</strong>ce a small error would make it deviate from theunstable equilibrium. Though uncommon, homocl<strong>in</strong>ic trajectories <strong>in</strong>dicate that thesystem undergoes a bifurcation — appearance or disappearance of a limit cycle. Thehomocl<strong>in</strong>ic trajectory <strong>in</strong> Fig. 4.27 <strong>in</strong>dicates that the limit cycle <strong>in</strong> Fig. 4.23 is aboutto (dis)appear via saddle homocl<strong>in</strong>ic orbit bifurcation. The homocl<strong>in</strong>ic trajectory <strong>in</strong>Fig. 4.28 <strong>in</strong>dicates that a limit cycle is about to (dis)appear via saddle-node on <strong>in</strong>variantcircle bifurcation. We study these bifurcations <strong>in</strong> detail <strong>in</strong> Chap. 6.4.3.4 Saddle-node bifurcationIn Fig. 4.29 we simulate the <strong>in</strong>jection of a ramp current I <strong>in</strong>to the I Na,p +I K -modelhav<strong>in</strong>g high-threshold K + current. Our goal is to understand the transition from the

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