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gk2Putils

For formatting a markdown document check: (https://commonmark.org/help/)

Setting up

Installation

  • fork the gk2Putils repository
  • clone your own forked repository
  • create a new branch to work with

    git branch BRANCHNAME

  • activate the branch by using checkout

    git checkout BRANCHNAME

  • make changes, add, and commit them to your branch

    git commit -a -m "TYPE COMMIT MESSAGE"

  • push the branch to your own remote fork

    git push --set-upstream origin BRANCHNAME

Set the paths

If something changed on the data location then set the correct paths

  • set the data path in utils/setDataPath.m
  • set the session path in utils/setSesPath.m
  • set the export path in utils/setExportPath.m

Get started by selecting which dataset(s) to analyze:

  1. make sure that the appropriate .csv file exists in the top dataPath folder (else create/update it)
  2. run the gk_datasetQuery command to select one or more datasets. For example:

    ds = gk_datasetQuery('week','w11','expID','contrast','mouseID','M19')

  3. Perform analysis using the package.

    Example pipeline

  • Get the tuned ROIs based on a critical p-value (ANOVA between responses to different conditions)

    xpr = gk_getTunedROIs(ds,'F',2,2,0.001)

  • Plot the continuous timecourse relative to stimulus

    cell = xpr.tunedGlobalIDs(1)
    gk_plotStimNeuron(ds, cell)

  • Export tuned neurons in a PPT file

    gk_exp_plotTuning(ds,'F',2,2,'export',0.00001)

    • The upper row of plots is using: gk_plot_trials.m
    • The lower row of plots is using: gk_plot_tuning.m <-- Needs to be adjusted

  • Calculate the contrast response functions (single vs double NakaRushton)

    CRF = gk_get_CRFs(xpr, cell)

  • Fit a NakaRuston function

    fit = gk_fitNakaRushton(CRF,1)

  • Plot the CRF with fitted NakaRushton

    gk_plotNakaRushton(fit)