  Rats and mice use their whiskers to probe the environment. By rhythmically
swiping their whiskers back and forth they can detect the existence of an
object, locate it, and identify its texture. Localization can be accomplished
by inferring the position of the whisker. Rhythmic neurons that track the phase
of the whisking cycle encode information about the azimuthal location of the
whisker. These neurons are characterized by preferred phases of firing that are
narrowly distributed. Consequently, pooling the rhythmic signal from several
upstream neurons is expected to result in a much narrower distribution of
preferred phases in the downstream population, which however has not been
observed empirically. Here, we show how spike-timing-dependent plasticity
(STDP) can provide a solution to this conundrum. We investigated the effect of
STDP on the utility of a neural population to transmit rhythmic information
downstream using the framework of a modeling study. We found that under a wide
range of parameters, STDP facilitated the transfer of rhythmic information
despite the fact that all the synaptic weights remained dynamic. As a result,
the preferred phase of the downstream neuron was not fixed, but rather drifted
in time at a drift velocity that depended on the preferred phase, thus inducing
a distribution of preferred phases. We further analyzed how the STDP rule
governs the distribution of preferred phases in the downstream population. This
link between the STDP rule and the distribution of preferred phases constitutes
a natural test for our theory.
