Fig 1. Neuron model, synaptic plasticity rule and learning of spike timings.

A: Synaptic inputs targeting dendritic NMDA activation zones (A1, red endings with enlargement) propagate, together with possible NMDA-spikes, to the somatic spike trigger zone (A1, blue). Individual postsynaptic potentials in a dendritic branch (PSPs, arriving e.g. at time $t_i^{\text{pre}}$, A2), may trigger NMDA-spikes, e.g. at time $t_d^{\mathrm{d}}=5\text{ms}$ (solid) or 15 ms (dashed) after $t_i^{\text{pre}}$, forming a local dendritic plateau potential of 50 ms duration (A3). A somatic spike triggered at t^s during the ongoing NMDA-spike (A4) causes a synaptic weight change $\Delta w_{di}^{\text{sds}}$ that is large/small depending on whether the NMDA-spike was triggered 5/15 ms after the presynaptic spike (A5, solid/dashed circle, respectively). A5: $\Delta w_{di}^{\text{sds}}$ as a function of $t^s-t_i^{\text{pre}}$ for a NMDA-spike at 5 (solid) and 15 ms (dashed). B: Raster plots of freely generated somatic spikes from test trials that are interleaved with learning trials. For the full somato-dendritic synaptic plasticity rule (sdSP) the somatic spikes converge to the 3 target times with a precision of ±3 ms (top), while the rule neglecting the dendritic spikes (i.e. suppressing the term ${\dot{w}}_{di}^{\text{sds}}$) achieves a precision of only ±14 ms (bottom). C: The two spike distributions from C after 3000 presentations.