Summary: weekly mtg 20160810 (Byron, Steve, Aaron, Matt, me) - mobeets/nullSpaceControl GitHub Wiki

Discussed

Fig. 1

B.

  • add a funnel? funnel on the BCI mapping? in the BCI mapping? make the box itself a funnel?
  • box itself a funnel, wide arrow coming in, tiny arrow coming out
  • make box flow vertical (also add in array, above monkey's head)
  • make a straighter dotted trajectory
  • lower monkey so he's looking at the screen
  • add more units

Fig. 2

A.

  • have dotted max lines intersect the axes, potentially label them as max; maybe they're not a perfect box
  • get rid of the gray cloud
  • get rid of black points?

B-D.

  • make sure to mention in text that we're binning output behavior
  • maybe try with rectangles/squares?
  • make them thinner, and say "consider three bins" rather than them spanning all outputs

Fig. 3

A.

  • draw the screen
  • to distinguish cursor vs. center
  • also, target doesn't lie on outer ring
  • make sure the dotted line lines up with the vector
  • can this fit in Fig. 1?

B-D.

  • skip

Fig. 4

A.

  • make x-labels into titles
  • show where 0 is, give some ticks

B.

  • pick a different dim? need to make tuning clear
  • make x-labels into titles
  • show where 0 is, give some ticks
  • maybe pack stuff into the x-lim, e.g., find 95% max
  • 8x2 instead of 4x4?

C. stand-alone figure

Fig. 5

B.

  • arrows not clear from rotation
  • make ellipses longer so it's clear they're not rotations?
  • maybe find new way of viewing hypotheses?

C. this one is more effective

Fig. 8

A.

  • order from best to worst
  • pick more distinct colors
  • can also rescale vertical axis so we can see all

QUESTION:

  • source of baseline mean?
  • orthonormalized vs. spikes/bin vs. ordered columns
    • orthonormalized and SCALED
    • SVD/sort on null space
    • okay, so just do PCA on observed null space activity for displaying/evaluating

TO DO:

  • use a TRUE Uncontrolled a la baseline/minimum that has a uniform distribution
  • do a similar improvement on minimum/baseline, where it uses true data
  • check hypotheses in SSS, for detcov vs. learning
  • supplemental fig for performance under two mappings, and with IME (similar to last fig of matt's elife paper)
  • supplemental fig for where behavior converged

To discuss

  • new figures
  • how to cover hypotheses in results, figures, etc. here
  • non-physiological predictions: here
  • new hab vs. cloud plots: here
  • Steve's Special Space (SSS)
  • eliminate cursor magnitudes near zero?: here