KTz neuron parameters

neuron type

x₀ =

y₀ =

z₀ =

Κ =

T =

δ =

λ =

x_R =

H =

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stimuli parameters

stimulus type:

I_ext(t) = I ∑_i=0^(N-1)[(k)ⁱδ_t,t₀+iΔt]

I =

N_stimuli =

t₀ =

Δt =

k =

I_ext(t) = I ∑_i=0^(N-1)[(k)^kδ_t,t₀+kΔt]

I =

N_sti =

t₀ =

Δt =

k =

Δt_s =

N_ser =

m =

I_ext(t) = I cos(ωt - φ), t_i ≤ t ≤ t_f

I =

ω =

φ =

t_i =

t_f =

I_ext(t) = f(t)
f(t+1) = (1 - 1/τ_f)f(t) + g(t)
g(t+1) = (1 - 1/τ_g)g(t) + Jθ(x'(t))

τ_f =

τ_g =

J =

I =

N_stimulus =

t₀ =

Δt =

I_ext(t) = f(t)
f(t+1) = (1 - 1/τ_f)f(t) + g(t)
g(t+1) = (1 - 1/τ_g)g(t) + (J + ε(t))θ(x'(t))
0 ≤ ε(t) ≤ R

τ_f =

τ_g =

J =

|R| =

I =

N_stimulus =

t₀ =

Δt =

I_ext(t) = a(t-t₀) + I₀; t₀ ≤ t ≤ t₁

I₀ =

a =

t₀ =

t₁ =

I_ext(t) = f(t)
f(t+1) = (1 - 1/τ_f)f(t) + g(t)
g(t+1) = (1 - 1/τ_g)g(t) + Jθ(x'(t))

τ_f =

τ_g =

J =

I =

N_stimulus,1 =

t_0,1 =

Δt₁ =

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simulation parameters

t_start =

t_max =

equations...

x(t+1) = tanh((x(t) - Ky(t) + z(t) + H + I_ext)/T)
y(t+1) = x(t)
z(t+1) = (1-δ)z(t) - λ(x(t) - x_R)

x(t+1) = tanh((x(t) - Ky(t) + H + I_ext)/T)
y(t+1) = x(t)

x(t+1) = f((x(t) - Ky(t) + z(t) + H + I_ext)/T)
y(t+1) = x(t)
z(t+1) = (1-δ)z(t) - λ(x(t) - x_R)
f(u) = u / (1+|u|)

x(t+1) = f((x(t) - Ky(t) + H + I_ext)/T)
y(t+1) = x(t)
f(u) = u / (1+|u|)