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)