Description
The Reduced Wong-Wang (RWW) model is a biophysically-based neural mass model that describes the dynamics of NMDA-mediated synaptic gating (Deco et al., 2013). It captures the slow dynamics relevant for resting-state fMRI and has been widely used for modeling whole-brain functional connectivity.
RWW is the dynamical mean-field (DMF) reduction of the Wong & Wang (2006) spiking model. Each network node is described by a single state variable S representing the average NMDA synaptic gating (fraction of open channels).
The total synaptic input x combines local excitatory recurrence (w), external input (I_o), and long-range network coupling (instant and delayed) scaled by the synaptic coupling strength J_N. The sigmoid transfer function H(x) maps the total input current to the average population firing rate. In a network setting, the global coupling strength G (a coupling parameter) scales the structural connectivity weights that modulate inter-regional communication.