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.

Synchronization (see www.izhikevich.com) 50915. Use the approaches of W<strong>in</strong>free, Kuramoto, and Malk<strong>in</strong> to transform the quadratic<strong>in</strong>tegrate-and-fire neuron ˙v = 1 + v 2 + εp(t) <strong>in</strong> Ex. 9 to its phase modelwith T = π.˙ϑ = 1 + ε (s<strong>in</strong> 2 ϑ) p(t) ,16. Use the approaches of W<strong>in</strong>free, Kuramoto, and Malk<strong>in</strong> to transform the Andronov-Hopf oscillator ż = (1 + i)z − z|z| 2 + εp(t) with real p(t) to its phase modelwith T = 2π.˙ϑ = 1 + ε (− s<strong>in</strong> ϑ)p(t) ,17. (PRC for Andronov-Hopf) Consider a weakly perturbed system near supercriticalAndronov-Hopf bifurcation (see Sect. 6.1.3)ż = (b + i)z + (−1 + di)z|z| 2 + ɛp(t) , z ∈ C .with b > 0. Let ε = b √ b/ɛ be small. Prove that the correspond<strong>in</strong>g phase modelis˙θ = 1 + d + ε Im {(1 + di)p(t)e −iθ } .When the forc<strong>in</strong>g p(t) is one-dimensional, i.e., p(t) = cq(t) with c ∈ C and scalarfunction q(t), the phase model has s<strong>in</strong>usoidal form˙θ = 1 + d + εs s<strong>in</strong>(θ − ψ)q(t) ,with the strength s and the phase shift ψ depend<strong>in</strong>g only on d and c.18. (Delayed coupl<strong>in</strong>g) Show that weakly coupled oscillatorsẋ i = f(x i ) + εn∑g ij (x i (t), x j (t − d ij ))with explicit axonal conduction delays d ij ≥ 0 have the phase modelj=1ϕ ′ i = ω i +n∑H ij (ϕ j − d ij − ϕ i )j≠iwhere ′ = d/dτ, τ = εt is the slow time, and H(χ) is def<strong>in</strong>ed by (10.16). Thus,explicit delays result <strong>in</strong> explicit phase shifts.19. Determ<strong>in</strong>e the existence and stability of synchronized states <strong>in</strong> the system˙ϕ 1 = ω 1 + c 1 s<strong>in</strong>(ϕ 2 − ϕ 1 )˙ϕ 2 = ω 2 + c 2 s<strong>in</strong>(ϕ 1 − ϕ 2 )as a function of the parameters ω = ω 2 − ω 1 and c = c 2 − c 1 .

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

Saved successfully!

Ooh no, something went wrong!