Dynamical Systems in Neuroscience:
Dynamical Systems in Neuroscience: Dynamical Systems in Neuroscience:
164 Conductance-Based Modelsmodels is mostly due to the seminal paper by John Rinzel and Bard Ermentrout “Analysisof Neural Excitability and Oscillations”, published as a chapter in Koch and Segev’sbook Methods in Neuronal Modeling (1989, second edition in 1999). Not only did theyintroduced the geometrical methods to a wide computational neuroscience audience,but also were able to explain a number of outstanding problems, such as the origin ofClass 1 and 2 excitability observed by Hodgkin in 1949.Rinzel and Ermentrout illustrated most of the concepts using the Morris-Lecar(1981) model, which is a I Ca + I K -minimal voltage-gated model equivalent to the I Na,p+ I K -model considered above. Due to its simplicity, the Morris-Lecar model is widelyused in computational neuroscience research. This is the reason we use its analogue,the I Na,p + I K -model, throughout the book.Hutcheon and Yarom (2000) suggested to classify all currents into amplifying andresonant. There have been no attempts to classify various electrophysiological mechanismsof excitability in neurons, though minimal models, such as the I Na,t -model orthe I Ca +I K(C) -model, would not surprise most researchers. The other models wouldprobably look bizarre for classical electrophysiologists, though they provide a goodopportunity to practice geometrical phase plane analysis and support FitzHugh’s observationthat N-shaped V -nullcline is the key characteristic of neuronal dynamics.Izhikevich (2003) took advantage of this observation and suggested the simple model(5.5, 5.6) that captures the spike-generation mechanism of many known neuronal types,see Chap. 8.Exercises1. Show that the I A -model cannot have a limit cycle attractor when I A has instantaneousactivation kinetics. (Hint: Use Bendixson criterion.)2. When the injected dc-current I or the Na + maximal conductance g Na in theI Na,p +I K -model have large values, the excited state (V ≈ −20 mV) becomesstable. Sketch possible intersections of nullclines of the model.3. Using I as a bifurcation parameter, determine the saddle-node bifurcation diagramof• the I Na,t -model with parameters as in Fig. 5.6a,• the I A -model with parameters as in Fig. 5.14a.4. Why is g in Fig. 5.22c negative when V is hyperpolarized?5. In Fig. 5.25 we plot the currents that constitute the right-hand side of the voltageequation (5.3),I − I fast (V ) and I slow (V ) = g(V − E K ) ,on the (V, I)-plane. The curves define fast and slow movements of the state ofthe system. Interpret the figure. (Hint: treat the curves as “sort-of-nullclines”).
Conductance-Based Models 165500I slow (V) = g(V-E K )500I slow (V) = g(V-E K )400400membrane current, Imembrane current, I3002001000-100 E K -60 -20 0 20membrane voltage, V (mV)5004003002001000 15I-I fast (V)0 15I-I fast (V)I slow (V) = g(V-E K )membrane current, I membrane current, I3002001000E K-100 -60 -20 0 20membrane voltage, V (mV)5004003002001000 15I-I fast (V)0 15I-I fast (V)I slow (V) = g(V-E K )00-100 E K -60 -20 0 20membrane voltage, V (mV)-100 E K -60 -20 0 20membrane voltage, V (mV)Figure 5.25: Ex. 5: The (V, I)-phase plane of the I Na,p +I K -model (compare withFig. 5.4).6. Show that I Cl +I K -model can have oscillations. (Hint: inject negative dc-currentso that the voltage-gated Cl − current becomes inward/amplifying).7. (NMDA+I K -model) Show that a neuronal model consisting of an NMDA currentand a resonant current, say I K , can exhibit excitability and periodic spiking.8. The Nernst potential of an ion is a function of its concentration inside/outside thecell membrane, which may change. Consider the I Na,p +E Na ([Na + ] in/out )-modeland show that it can exhibit excitability and oscillations on a slow time scale.9. Determine when the I A -model has a limit cycle attractor without assumingτ h (V ) ≪ τ m (V ).10. [Ph.D.] There are Na + -gated and Cl − -gated currents besides the Ca 2+ -gatedcurrents considered in this book. In addition, the Nernst potentials may changeas concentrations of ions inside/outside the cell membrane change. This maylead to new minimal models. Classify and study all these models.
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164 Conductance-Based Modelsmodels is mostly due to the sem<strong>in</strong>al paper by John R<strong>in</strong>zel and Bard Ermentrout “Analysisof Neural Excitability and Oscillations”, published as a chapter <strong>in</strong> Koch and Segev’sbook Methods <strong>in</strong> Neuronal Model<strong>in</strong>g (1989, second edition <strong>in</strong> 1999). Not only did they<strong>in</strong>troduced the geometrical methods to a wide computational neuroscience audience,but also were able to expla<strong>in</strong> a number of outstand<strong>in</strong>g problems, such as the orig<strong>in</strong> ofClass 1 and 2 excitability observed by Hodgk<strong>in</strong> <strong>in</strong> 1949.R<strong>in</strong>zel and Ermentrout illustrated most of the concepts us<strong>in</strong>g the Morris-Lecar(1981) model, which is a I Ca + I K -m<strong>in</strong>imal voltage-gated model equivalent to the I Na,p+ I K -model considered above. Due to its simplicity, the Morris-Lecar model is widelyused <strong>in</strong> computational neuroscience research. This is the reason we use its analogue,the I Na,p + I K -model, throughout the book.Hutcheon and Yarom (2000) suggested to classify all currents <strong>in</strong>to amplify<strong>in</strong>g andresonant. There have been no attempts to classify various electrophysiological mechanismsof excitability <strong>in</strong> neurons, though m<strong>in</strong>imal models, such as the I Na,t -model orthe I Ca +I K(C) -model, would not surprise most researchers. The other models wouldprobably look bizarre for classical electrophysiologists, though they provide a goodopportunity to practice geometrical phase plane analysis and support FitzHugh’s observationthat N-shaped V -nullcl<strong>in</strong>e is the key characteristic of neuronal dynamics.Izhikevich (2003) took advantage of this observation and suggested the simple model(5.5, 5.6) that captures the spike-generation mechanism of many known neuronal types,see Chap. 8.Exercises1. Show that the I A -model cannot have a limit cycle attractor when I A has <strong>in</strong>stantaneousactivation k<strong>in</strong>etics. (H<strong>in</strong>t: Use Bendixson criterion.)2. When the <strong>in</strong>jected dc-current I or the Na + maximal conductance g Na <strong>in</strong> theI Na,p +I K -model have large values, the excited state (V ≈ −20 mV) becomesstable. Sketch possible <strong>in</strong>tersections of nullcl<strong>in</strong>es of the model.3. Us<strong>in</strong>g I as a bifurcation parameter, determ<strong>in</strong>e the saddle-node bifurcation diagramof• the I Na,t -model with parameters as <strong>in</strong> Fig. 5.6a,• the I A -model with parameters as <strong>in</strong> Fig. 5.14a.4. Why is g <strong>in</strong> Fig. 5.22c negative when V is hyperpolarized?5. In Fig. 5.25 we plot the currents that constitute the right-hand side of the voltageequation (5.3),I − I fast (V ) and I slow (V ) = g(V − E K ) ,on the (V, I)-plane. The curves def<strong>in</strong>e fast and slow movements of the state ofthe system. Interpret the figure. (H<strong>in</strong>t: treat the curves as “sort-of-nullcl<strong>in</strong>es”).