Behavioral plots

[mobeets]

Acquisition times

Actual progress

Inferred WMP progress

Inferred WMP progress, during WMP only (relative to avg during Intuitive)

[mobeets]

From manuscript:

"We included sessions in which there existed a block of at least 100 consecutive trials that showed both substantial learning of the second mapping and consistent behavior. To identify trials showing substantial learning, we computed the running mean of the target acquisition time, smoothed with a 100-trial boxcar shifted one trial at a time. The smoothed acquisition time for a trial then corresponded to the average acquisition time within a 100-trial window centered on that trial. We then normalized these values so that $1$ corresponded to the largest acquisition time in the first 25 trials using the second mapping, and $0$ corresponded to the smallest acquisition time in the subsequent trials using the second mapping. We defined trials showing substantial learning as those with normalized acquisition times below $0.5$.

"Next, to identify trials with consistent behavior, we computed the running variance of the target acquisition time. This was computed by taking the variance of the smoothed acquisition time above in a 100-trial boxcar, shifted one trial at a time. We then normalized these variances so that $1$ corresponded to the largest variance in the first half of trials using the second mapping, and $0$ corresponded to the smallest variance in any trial using the second mapping. We defined trials showing stable behavior as those with normalized variance below $0.5$. We selected the longest block of at least 100 trials in each session that passed both of these criteria. If no such block of trials was found, we excluded that session from our analyses. This procedure resulted in the 41 sessions across three monkeys that we included in our analyses."

[mobeets]

sessions skipped:

20130527 20130612 20131208

what happened?

[mobeets]

Also, there are now more sessions I could include...

 '20120222'    '20120303'    '20120327'    '20130528'

'20130619'    '20131124'    '20131125'    '20131211'

'20160402'    '20131214'

[mobeets]

Ahh...I see. I was using a file called 'goodTrials_trialLength', but the params were actually based on progress, with the following opts:

    muThresh: 0.5000
   varThresh: 0.5000
trialsInARow: 10
groupEvalFcn: @numel
minGroupSize: 150
   meanBinSz: 150
varMeanBinSz: 100
    varBinSz: 100
     behavNm: 'progress'

Note that values different from the text are minGroupSize=100, meanBinSz=100, trialsInARow=100, and behavNm=trial_length

Relevant code in nullSpaceControl: behav2.plotThreshTrials tmpShowBehav behav2.asymptotesAll plot.plotBehavAllSessions

[mobeets]

a few notes:

• maybe use first 50 to define max of smoothed mean?
• trials can skip up to 10 trials and still be considered part of a group
• we take the longest set of trials passing criteria

[mobeets]

updated:

opts =

         muThresh: 0.5000
        varThresh: 0.5000
        meanBinSz: 100
         varBinSz: 100
     maxTrialSkip: 10
     minGroupSize: 100
          behavNm: 'trial_length'
lastBaselineTrial: 50

normalized acquisition time:

raw acquisition time:

[mobeets]

example session: 20131218

[mobeets]

[mobeets]

updated with all sessions:

[mobeets]

Should I include incorrect trials or no? I was not before. I think it makes sense based on the way I choose the max time to normalize to. If I include incorrect trials, then the max time will always be the max trial length no matter what, provided there is at least one incorrect trial in the first 50 trials. So this makes learning look like it's happening faster...

[mobeets]

not including incorrects:

[mobeets]