So now on the right here, what we're looking at is a more realistic model
with a simple model of non linearity that won't let the response go up too high.
And now what we see is something useful.
What we see is if we're looking at a contrast,
1 minus 1 that's a task a versus b comparison.
Then the best design has an inter-stimulus interval of about
a stimulus every two seconds or so and no rest.
If all I care about is comparing A versus B, I should fill my task with As and Bs.
I don't need to jitter or have any rest, and that's optimal.
Once I start including rest intervals,
which creates jitter in the design, then the efficiency only goes down.
The last principal is optimization.
Optimize your design choices with specific study goals and constraints in mind.
They could be psychological, neural or statistical.
In particular, we'll look at specifying a series of things.
One is, specify a set of contrasts that you care about.
It's an ANOVA design, two by two ANOVA,
you might specify that you care about the main effects and the interaction.
That's three contrasts.
You can specify the relative importance of each contrast and
think about which effects you really care about detecting.
You can also think about the desired high-pass filtering cutoff,
how much noise do you want to remove, and so
how much do you need to keep the design out of that noise range.