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Analyses

The scripts here describe how the relevants outputs, e.g., RDMs, are computed from GLM outputs or raw timeseries. In addition to the scripts in utils/, these scripts assume that Kendrick Kay's knkutils have been added to the path.

Table of Contents

  1. GLM
  2. ROIs
  3. tSNR
  4. Parse GLMs
  5. Maps
  6. Metric Means
  7. EPI Maps
  8. RDMs
  9. R^2 Control Analysis

GLMs [00]

Running analyses/00_run_glms/main.m runs three GLMs for each participant: 1. One with odd runs only 2. One with even runs only 3. One with all runs Additionally, the GLM is run for both high-resolution and simulated low-resolution data.

ROIs [01]

The scripts in this directory are used to either draw ROIs in each participant or to transform the hOc1 (V1) ROI into each subjects' native space.

tSNR [02]

Running analyses/02_tsnr/main.m does the following: Computes the mean tSNR at each cortical depth, averaged across the entire ROI.

Parse GLMs [03]

Running analyses/03_parse_glms/main.m extracts values at each vertex based on ROI, vein masking, and other restrictions. It also computes the GLM metrics specified in analyses/Constants.m for each vertex, and saves everything to a big .mat file.

Maps [04]

analyses/04_maps/main.m saves maps of GLM metrics in each VTC ROI for each subject and each depth

Mean EPI Maps [04a]

analyses/04a_epi_mask_redoutline/main.m plots in a red outline the 'dark' vertices that we identify as likely veins and exclude from most analyses.

Metric Means [05]

analyses/04_maps/main.m saves maps of GLM metrics in each VTC ROI for each subject and each depth

RSMs [06]

analyses/06_rsms/main.m is a function used to save RSMs across depths and conditions. analyses/06_rsms/main_r2_control.m is identical, but further restricts vertices based on the results from 07_variance_explained/, i.e., sets of vertices matched for variance explained across partitions

R2 matching [07]

analyses/05_r2_matching has a few scripts:

  1. write_matching_indices.m: finds and writes the indices for vertices in each partition that are matched for R2
  2. analyze_mean_vals.m: performs statistical tests that population at each is matched in R2
  3. main.m: saves R2 in each partition after doing matching for later statistical testing across, e.g., depths