Feedback: Doug (20170222) - mobeets/nullSpaceControl GitHub Wiki
Doug feedback
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Intro
- Intro feels like it misdirects by talking about muscle literature
- feels a little long-winded
- could cite the muscles when you introduce the hyps, but maybe not in the intro
- just start up front with what you're interested in: neural redundancy; it's been unaddressed so far, understanding the selection process is important, etc.
- seems like a paragraph too long
- "We initially considered" <-- Yes. Should be second paragraph.
- "unknown whether the results regarding muscle literature" <-- what results?
- "different mapping" totally unclear at this point; or just "mapping"
- also can reference 1B here
- "each type of cursor movement" <-- unclear
- "the brain can produce only a limited..."
- maybe focus on M1? touch on this in discussion
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Velocity vs. direction
- Fig. 1: hung up on monkey really wanting v=4 vs. v=2, for example
- direction makes much more sense
- maybe just remove velocity? to be more vague
- also, text refers to cursor-vel axis as "output-potent"
- maybe no reason to have two histogram traces in C,D
- don't hear about "cursor movement direction" until page 9
- should talk about this earlier, say in intro
- Fig. 1: hung up on monkey really wanting v=4 vs. v=2, for example
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"choose"/"select"/"decision"/etc.
- pick a word and stick with it
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Doug: when he reads about FA or preprocessing, he wants to know what it would be like without it
- need a sentence that explains why we needed to do this
- otherwise, doesn't understand the impacts this will have on the results
- also be more explicit about the fact that this isn't just a preprocessing, this is actually how the experiments were run; this will also help the reader believe you
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discussion point:
- trial dynamics might explain a lot; difficult to go from UP to DOWN, e.g.
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Results:
- say number of monkeys
- center-out task: no explanation, no citation, no reference to methods
- typo: "we made be able to"
- "previous" vs. "different" --> important thing is that it's "different" right?
- "estimating the error...does not capture..." <- didn't understand what this was about (motivation for using mean/cov error)
- IME part: seemed undermotivated, and possibly undersold
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Fig. 2:
- explain why you're showing only the top 3 dims
- would be nice to give better intuition for how the prediction is made
- feels like there could be some sort of better way to explain quantitatively why these fits aren't good; you just have to wait til later figs...
- maybe add a table?
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Fig. 6
- need units on A
- no ref to B in the text
- C: need help interpreting this figure
- why does MnkN look messy?
- need more hand-holding
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Discussion:
- first para: yeah it's different than muscles, but what do we learn about M1?
- how population size, spatial clustering of neurons affects range of activity that's possible in these spaces (e.g. this is just from a Utah array)
- why was BCI the right way to do this experiment? not totally sold that you had to, so really nail it in
- the "how" and "why" the brain is "choosing" in this way is unclear
- what's the cartoon model for how this space looks like, when the monkey needs to move up, say? is the animal actively going to a remembered state that's likely to work?
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Methods: seems really good
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Liked title: Predicting the selection of behaviorally
- likes it better than redundancy