ePoster · Computational Neuroscience
A computationally efficient simplification of the Brunel-Wang NMDA model: Numerical approach and first results
Jan-Eirik Skaar, Nicolai Haug, Hans Ekkehard Plesser · Bernstein Conference 2024
A model for NMDA-receptor-mediated synaptic currents generating persistent activity proposed by Wang and Brunel [1–3] has been widely adopted in computational neuroscience, both for spiking-neuron and mean-field models [2, 4]. The model describes NMDA synaptic dynamics by a phenomenological two-dimensional nonlinear ODE system for the gating variable $S(t)$ evolving according to $$ \frac{dS_j}{dt} = -\frac{S_j}{\tau_d} + \alpha x_j (1 - S_j) \\ \frac{dx_j}{dt} = - \frac{x_j}{\tau_r} + \sum_k \delta(t - t_j^k) $$ where indices $j$ mark presynaptic neurons and $k$ spike times. Due to the nonline