While debugging some code implementing a modified version of BCM I came about something that I wasn’t expecting: the behaviour of Lowpass.filt() in Nengo 2.8.0 and 3.0.0 seems to be different.

Specifically, in Nengo 3.0.0 the method returns values that are scaled of a factor of 100, as can be seen by running the same exact model with the two different backends.

As an example and proof of this, observe the `theta`

variable that is the given by:

```
self.lowpass = nengo.Lowpass( 1.0 )
theta = self.lowpass.filt( out_rates )
```

in Nengo 2.8.0

and in Nengo 3.0.0

I guess that this is by design, having seen the following commit:

In any case, this is causing problems with my BCM implementation because my algorithm now thinks that post-synaptic activations are always over threshold.

Which would be the best, cleanest, most logical way to deal with the issue? Divide my `theta`

by a factor of 100, which I imagine is due to the simulation step being `dt=0.001`

?