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Dynamical Systems in Neuroscience:

Dynamical Systems in Neuroscience:

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Two-Dimensional <strong>Systems</strong> 103derivative, V' (mV/ms)membranepotential (mV)2001000-100-80 -60 -40 -20 0 20 40membrane potential, V (mV)40200-20-40cortical pyramidal neuron cortical <strong>in</strong>terneuron bra<strong>in</strong>stem neuron-600 50 100-80 -60 -40 -20 0 20 40membrane potential, V (mV)-80 -60 -40 -20 0 20 40membrane potential, V (mV)0 20 40 60 0 10 20time (ms)Figure 4.11: Limit cycles correspond<strong>in</strong>g to tonic spik<strong>in</strong>g of three types of neuronsrecorded <strong>in</strong> vitro.ẏ = µg(x, y) (slow variable)where small parameter µ describes the ratio of time scales of variables x and y. Typically,fast variable x has a cubic-like nullcl<strong>in</strong>e that <strong>in</strong>tersects the y-nullcl<strong>in</strong>e somewhere<strong>in</strong> the middle branch, as <strong>in</strong> Fig. 4.12a, result<strong>in</strong>g <strong>in</strong> relaxation oscillations. The periodictrajectory of the system slides down along the left (stable) branch of the cubic nullcl<strong>in</strong>euntil it reaches the left knee A. At this moment, it quickly jumps to the po<strong>in</strong>t B andthen slowly slides up along the right (also stable) branch of the cubic nullcl<strong>in</strong>e. Uponreach<strong>in</strong>g the right knee C, the system jumps to the left branch and starts to slide downaga<strong>in</strong>, thereby complet<strong>in</strong>g one oscillation. Relaxation oscillations are easy to graspconceptually, but some of their features are quite difficult to study mathematically.We consider relaxation oscillations <strong>in</strong> detail <strong>in</strong> Sect. 6.3.4.Notice that the jumps <strong>in</strong> Fig. 4.12a are nearly horizontal — a dist<strong>in</strong>ctive signature ofrelaxation oscillations that is due to the disparately different time scales <strong>in</strong> the system.Although many neuronal models have fast and slow time scales and could be reducedto the fast/slow form above, they do not exhibit relaxation oscillations because theparameter µ is not small enough. Anybody who records from neurons would probablynotice the weird square shape of “spikes” <strong>in</strong> Fig. 4.12b, someth<strong>in</strong>g that most biologicalneurons do not exhibit. Nevertheless, relaxation oscillations <strong>in</strong> fast/slow systems areimportant when we consider neuronal burst<strong>in</strong>g <strong>in</strong> Chap. 9, though the fast variable xis two-dimensional there.

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