 
Summary: Supplementary Methods
This section gives additional information about the choice of parameters and the initial conditions
used in the numerical simulations of Figs. 48. We have checked that none of the reported results
required finetuning of the model parameters.
Number of synapses. All shown simulations except Fig. 4a and Fig. 7cd were made with N =
500. This choice was dictated by computation time and memory constraints. In Fig. 4a, we also
show the tempotron's capacity limit for N = 1000 and N = 1500. In Fig. 7cd, where each afferent
spiked three times, the total number of input spikes was approximately preserved by reducing N
to 168. By simulating up to N = 10, 000 for selected parameters and reduced sample size, we
checked that the shown behavior approximates the large N limit.
Time scales. In most of the results, we used the value = 15 ms for the PSP decay time constant.
This is close to the optimal value (Fig. 4b) when assuming a reasonable pattern duration of T =
500 ms. For the decay time constant of synaptic currents, we have chosen s = /4, which for
= 15 ms is compatible with experimental results for fast synapses.
Tempotron learning. In the tempotron learning, we chose the maximal value of synaptic changes
to be = 104
/V0 (except in Fig. 4). This yields near optimal convergence time with N = 500,
T = 500 ms, and = 15 ms, the parameter valuesq used throughout the work. When is far
from its optimal, learning times become sensitive to the choice of . Empirically we found that
= 3 × 103
