iModel

Linear filter, Common input, Poisson

This 1D linear filter model generates a stimulus-modulated source of Poisson common input that drives units in a second stage. The second stage units simply combine the common input spikes with spikes from independent Poisson sources. This model was designed for testing spike train cross-correlation analyses and for educational exercises.

The stimulus, **s(t)**, is convolved with a linear filter. The
output is scaled and half-wave rectified (not shown) to form a time
varying rate, **r**_{c}(t), that drives an inhomogeneous
Poisson process. The resulting spike train, the output of **unit
c**, is the source of common input to **unit 1** and **unit
2**. These two second layer units accept each spike
from the common input independently with probabilities **p1** and
**p2**, respectively. In addition to the common input spikes, the
output spike trains of units 1 and 2 include a set of independent
(homogeneous) Poisson spikes generated with rates **r**_{a}
and **r**_{b}, respectively.

Additional parameters allow for a refractory period to be imposed on
the spikes of **unit c**, and for the spikes of units 1 and 2 to be
converted to bursts. An arbitrary number of second layer units can
be defined. For detailed parameter descriptions, follow the link for
the model class below.