  A common way of studying the relationship between neural activity and
behavior is through the analysis of neuronal spike trains that are recorded
using one or more electrodes implanted in the brain. Each spike train typically
contains spikes generated by multiple neurons. A natural question that arises
is "what is the number of neurons $\nu$ generating the spike train?"; This
article proposes a method-of-moments technique for estimating $\nu$. This
technique estimates the noise nonparametrically using data from the silent
region of the spike train and it applies to isolated spikes with a possibly
small, but nonnegligible, presence of overlapping spikes. Conditions are
established in which the resulting estimator for $\nu$ is shown to be strongly
consistent. To gauge its finite sample performance, the technique is applied to
simulated spike trains as well as to actual neuronal spike train data.
