Please wait while the simulation loads
This page requires JavaScript and access to the MathJax servers.

Inhibitory
$a_{ii}$
$a_{ie}$
$\tau_i$
$\theta_i$
$g_i$
$\sigma_i$
$N_i$
$\alpha_i$
$\beta_i$
Excitatory
$a_{ee}$
$a_{ei}$
$\tau_e$
$\theta_e$
$g_e$
$\sigma_e$
$N_e$
$\alpha_e$
$\gamma_e$
$\beta_e$

Time stepping
$\Delta t$
Stimulus
$A$
$f$
Presets
This application relies on the HTML5 Canvas element and Javascript. If you have Javascript disabled, try re-enabling it for this page.
E-cell firing rate ∈[0,1]
I-cell firing rate ∈[0,1]
E/I trajectories in phase space
Steady-state adaptation
Firing rate variables
Red=E Green=I Blue=|E-I|
Adaptation variables
Red=I Green=E Blue=|E-I|
E/I trajectories in phase space
With, without adaptation
Click to start
\[\textrm{E-cells: } \tau_e \dot{U_e} = -U_e + f( a_{ee} \cdot K_e \star U_e - a_{ie} \cdot K_i \star U_i - \theta_e + g_e S(t) - \beta_e V_e)\] \[\textrm{I-cells: } \tau_i \dot{U_i} = -U_i + f( a_{ei} \cdot K_e \star U_e - a_{ii} \cdot K_i \star U_i - \theta_i + g_i S(t) - \beta_i V_i )\] \[\textrm{E-cell adaptation: } \tau_{ve} \dot{V_e} = U_e - V_e,\,\, \tau_{ve} = \begin{cases} \alpha_e & \text{if }V_e< U_e \\ \gamma_e & \text{if }V_e\ge U_e\end{cases} \] \[\textrm{I-cell adaptation: } \alpha_i \dot{V_i} = U_i - V_i \] \[\textrm{Interaction kernel (normalized to 1): } K_{e,i}(x,y) \propto \exp\left(\frac{1}{2} \frac{x^2}{\sigma_{x\,e,i}^2}+\frac{1}{2} \frac{y^2}{\sigma_{y\,e,i}^2}\right)\]

Wave State Demonstration

This page is part of the github.com/michaelerule/neuralfield repository, which collects various implementations of the Wilson-Cowan neural field and similar equations over the years. The project can be browsed as a website here.

We used these and similar equations to model flicker-induced geometric hallucinations, optogenetic stimulation in motor cortex, and retinal waves.

Simulation