12.07.2015 Views

Dynamical Systems in Neuroscience:

Dynamical Systems in Neuroscience:

Dynamical Systems in Neuroscience:

SHOW MORE
SHOW LESS
  • No tags were found...

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

Conductance-Based Models 139This model is <strong>in</strong> many respects equivalent to the I Ca +I K -model proposed by Morrisand Lecar (1981) to describe voltage oscillations <strong>in</strong> the barnacle giant muscle fiber.A reasonable assumption based on experimental observations is that the Na + gat<strong>in</strong>gvariable m(t) is much faster than the voltage variable V (t), so that m approaches theasymptotic value m ∞ (V ) practically <strong>in</strong>stantaneously. In this case we can substitutem = m ∞ (V ) <strong>in</strong> the voltage equation and reduce the three-dimensional system aboveto a planar systemleak I L<strong>in</strong>stantaneous I Na,p IC ˙V{ }} { { }} { { }} K{= I − g L (V −E L ) − g Na m ∞ (V ) (V −E Na ) − g K n (V −E K ) (5.1)ṅ = (n ∞ (V ) − n)/τ(V ) , (5.2)which was considered <strong>in</strong> detail <strong>in</strong> the previous chapter. In Fig. 5.4 we summarize itsdynamic repertoire. A strik<strong>in</strong>g observation is that the other m<strong>in</strong>imal models can havesimilar nullcl<strong>in</strong>es and similar dynamic repertoire, even though they consist of quitedifferent ionic currents.5.1.3 I Na,t -modelAn <strong>in</strong>terest<strong>in</strong>g example of a spik<strong>in</strong>g mechanism, implicitly present <strong>in</strong> practically everybiological neuron, is given by the I Na,t -modelC ˙V = I −leak I L{ }} {g L (V − E L ) −ṁ = (m ∞ (V ) − m)/τ m (V ) ,ḣ = (h ∞ (V ) − h)/τ h (V ) ,I Na,t{ }} {g Na m 3 h(V − E Na ) ,consist<strong>in</strong>g only of an Ohmic leak current and a transient voltage-gated <strong>in</strong>ward Na +current. How could such a model generate action potentials? The upstroke of an actionpotential is generated because of the regenerative process <strong>in</strong>volv<strong>in</strong>g the activation gatem. This mechanism is similar to the one <strong>in</strong> the Hodgk<strong>in</strong>-Huxley model or <strong>in</strong> theI Na,p +I K -model: Increase of m results <strong>in</strong> <strong>in</strong>crease of the <strong>in</strong>ward current, hence moredepolarization and further <strong>in</strong>crease of m until the excited state is achieved. At theexcited state there is a balance of the Na + <strong>in</strong>ward current and the leak outward current.S<strong>in</strong>ce there is no I K , the downstroke from the excited state occurs via a differentmechanism: While <strong>in</strong> the excited state, the Na + current <strong>in</strong>activates (turns off) and theOhmic leak current slowly repolarizes the membrane potential toward the leak reversepotential E L , which determ<strong>in</strong>es the rest<strong>in</strong>g state. While at rest, the Na + currentde<strong>in</strong>activates; i.e., becomes available, and the neuron is ready to generate anotheraction potential. This mechanism is summarized <strong>in</strong> Fig. 5.5.To study the dynamics of the I Na,t -model, we first reduce it to a planar system.Assum<strong>in</strong>g that activation dynamics is <strong>in</strong>stantaneous, we use m = m ∞ (V ) <strong>in</strong> the voltage

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!