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Dynamical Systems in Neuroscience:

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250 Excitabilitysquid axonmodel0 mV0 mV-50 mV-50 mV5 ms5 msFigure 7.26: Variable-size action potentials <strong>in</strong> squid giant axon and revised Hodgk<strong>in</strong>-Huxley model (Clay 1998) <strong>in</strong> response to brief steps of currents of variable magnitudes(data was k<strong>in</strong>dly provided by John Clay).Conversely, if the neuron was briefly hyperpolarized and then released from hyperpolarization,it could fire a rebound post-<strong>in</strong>hibitory spike, as we discuss later <strong>in</strong> thischapter (see Fig. 7.29). Apparently, releas<strong>in</strong>g from hyperpolarization does not qualifyas a superthreshold stimulation. Why then the neuron fired?7.2.5 Threshold manifoldsThe problem of formulat<strong>in</strong>g a mathematical def<strong>in</strong>ition of fir<strong>in</strong>g thresholds was firsttackled by FitzHugh (1955). Us<strong>in</strong>g geometrical analysis of neural models, he noticedthat thresholds, if exist, are never numbers but manifolds, e.g., curves <strong>in</strong> twodimensionalsystems. We illustrate his concept <strong>in</strong> Fig. 7.27 us<strong>in</strong>g phase plane analysisof the I Na,p +I K -model.Integrators do have well-def<strong>in</strong>ed threshold manifolds. S<strong>in</strong>ce an <strong>in</strong>tegrator neuron isnear a saddle-node bifurcation, whether on or off an <strong>in</strong>variant circle, there is a saddlepo<strong>in</strong>t with its stable manifold; see Fig. 7.27a. This manifold separates two regions ofthe phase space, and for this reason often called a separatrix. Depend<strong>in</strong>g on the prioractivity of the neuron and the size of the <strong>in</strong>put, its state can end up <strong>in</strong> the shadedarea and generate a subthreshold potential, or <strong>in</strong> the white area and generate an actionpotential. An <strong>in</strong>termediate-size <strong>in</strong>put cannot reduce the size of the action potential,but can only delay its occurrence. In the extreme case, a perturbation can put the statevector precisely on the threshold manifold, and the system converges to the saddle, atleast <strong>in</strong> theory. S<strong>in</strong>ce the saddle is unstable, small noise present <strong>in</strong> neurons pushes thestate either to the left or to the right, result<strong>in</strong>g <strong>in</strong> either a long subthreshold potentialor a large-amplitude spike with a long latency, as we discuss <strong>in</strong> Sect. 7.2.9 and show<strong>in</strong> Fig. 7.34. F<strong>in</strong>ally, notice that a neuron has a s<strong>in</strong>gle threshold value of membranepotential only when its threshold manifold is a straight vertical l<strong>in</strong>e.Resonators may or may not have well-def<strong>in</strong>ed threshold manifolds, depend<strong>in</strong>g onthe type of bifurcation. Consider a resonator neuron <strong>in</strong> the bistable regime; that is,sufficiently near a subcritical Andronov-Hopf bifurcation with an unstable limit cycle

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