[CaCL] an application of TFCA

[Nathan Rasmussen]

The paper here is my end-of-term writeup for Per Sederberg's EEG class, in
which we used TFCA to process experimental data. The thing most relevant to
the TFCA reading is the "Data Analysis" section, which tries to state
briefly what it is, how it works, and why we use it.

Marty: please send out the "bootstrapping gets impossibly conservative"
paper.

Marty, re yer sadnesses: So what you want to show is that task A causes
significant activation in the forebrain, and task B causes significant
activation in the aftbrain, and doing both tasks causes both? I guess I
still don't see the problem. Either that means I know how to solve it, or
I'm too dumb to even get it, so ... in the first case "I don't see why
you're sad" means "you don't need to be sad," and in the second case, it
means "I'm heartless AND dumb." (I blame scurvy for both of these.)

If I'm right, TFCA your data, bootstrap a significance level, and then
check out the forebrain and hindbrain sensors to see if there's a
significant difference between with-task and without-task, right? If I'm
wrong, well, maroon me on a threshold-free islet amid the briny vastness
and curse my bones over your next bottle o' rum. ... Or, try and make me
see what you're talking about. Either one.
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