Hatsopoulos lab Center Out.

- We use a 50% eval split since there's plenty of data (8 sessions with total 640 trials per condition. That's a lot!). Scratch can still train fine with less data.
- Using cycle-held out pattterns, there's a way dramatic failure in held-out conditions which is redundant to convey; it is enough to use wedge to demonstrate both interpolative and extrapolative generalization patterns in one experiment.
- In cycle pilots we still saw gains ~no gains from PT on held-in conditions and some gain on nearby held-out conditions.