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Dynamical Systems in Neuroscience:

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352 Burst<strong>in</strong>g9.2.1 Fast-slow burstersWe say that a neuron is a fast-slow burster if its behavior can be described by afast-slow system of the formẋ = f(x, u) (fast spik<strong>in</strong>g),˙u = µg(x, u) (slow modulation).(9.1)The vector x ∈ R m describes fast variables responsible for spik<strong>in</strong>g. It <strong>in</strong>cludes themembrane potential V , activation and <strong>in</strong>activation gat<strong>in</strong>g variables for fast currents,etc. The vector u ∈ R k describes relatively slow variables that modulate fast spik<strong>in</strong>g,e.g., gat<strong>in</strong>g variable of a slow K + current, <strong>in</strong>tracellular concentration of Ca 2+ ions,etc. The small parameter µ represents the ratio of time scales between spik<strong>in</strong>g andmodulation. When we analyze models, we assume that µ ≪ 1; that is, it could be assmall as we wish. The results obta<strong>in</strong>ed via such an analysis may not have any sensewhen µ is of the order 0.1 or greater.To analyze bursters, we first assume that µ = 0, so that we can consider thefast and slow systems separately. This constitutes the method of dissection of neuralburst<strong>in</strong>g pioneered by R<strong>in</strong>zel (1985). In fact, we have done this many times <strong>in</strong> theprevious chapters when we substituted m = m ∞ (V ) <strong>in</strong>to the voltage equation. Thefast subsystem can be rest<strong>in</strong>g (but excitable), bistable, or spik<strong>in</strong>g depend<strong>in</strong>g on thevalue of u; see Fig. 9.11. Burst<strong>in</strong>g occurs when u visits the spik<strong>in</strong>g and quiescentareas periodically. Many important aspects of burst<strong>in</strong>g behavior can be understoodvia phase portrait analysis of the fast subsystemẋ = f(x, u) , x ∈ R m ,treat<strong>in</strong>g u ∈ R k as a vector of slowly chang<strong>in</strong>g bifurcation parameters.We say that the burster is of the “m+k” type when the fast subsystem is m-dimensional and the slow subsystem is k-dimensional. There are some “1+1” and“2+0” bursters, see Ex. 1 — Ex. 4, though they do not correspond to any knownneuron. Most of the burst<strong>in</strong>g models <strong>in</strong> this chapter are of the “2+1” and “2+2” type.9.2.2 Phase portraitsS<strong>in</strong>ce most burst<strong>in</strong>g models are at least of the “2+1” type, their phase space is atleast three-dimensional. Analyz<strong>in</strong>g and depict<strong>in</strong>g multi-dimensional phase portraits ischalleng<strong>in</strong>g. Even understand<strong>in</strong>g the geometry of a s<strong>in</strong>gle burst<strong>in</strong>g trajectory depicted<strong>in</strong> Fig. 9.12 is difficult unless one uses a stereoscope.In Fig. 9.13 we <strong>in</strong>vestigate geometrically the I Na,p +I K +I K(M) -model, which is afast-slow burster of the “2+1” type. The naked burst<strong>in</strong>g trajectory is shown <strong>in</strong> thelower left corner. We set µ = 0 (i.e., τ slow (V ) = +∞) and slice the three-dimensionalspace by planes n slow =const, shown <strong>in</strong> the top right corner. Phase portraits of thetwo-dimensional fast subsystem with fixed n slow are shown <strong>in</strong> the middle of the figure.Notice how the limit cycle attractors and the equilibria of the fast subsystem depend on

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