**avgs_by_3latgroup.zip**
Average t-statistic maps in .nii format for 3 groups defined by laterality classification from Bruckert thesis (left, right or bilateral according to word generation on Doppler). Filename specifies group then contrast, where WG1 is word generation (contrast with rest), AN5 is auditory naming (contrast with backward speech), PP1 is semantic matching (Palm Trees and Pyramids) vs rest, PP3 is perceptual control for semantic matching vs rest, PP5 is semantic matching minus perceptual control.
Files created with averaged_matrix.m
**avgs_mirror_by_3latgroup.zip**
Average t-statistic mirror maps in .nii format for 3 groups defined by laterality classification from Bruckert thesis (left, right or bilateral according to word generation on Doppler). Filenames as for avgs_by_3latgroup.zip.
Files created with averaged_mirror_matrix.m , which reads files created with make_diff_ni.m.
**SCRIPTS USING THE FOLLOWING FILES WILL DEFAULT TO LOOKING FOR THEM IN A SUBFOLDER IN WORKING DIRECTORY CALLED BRUCKERT/DATA_PROCESSED/**
**bigdf.csv** (with data dictionary)
Long form data file with LI for individuals; combines all methods for laterality computation and all masks and contrasts. Created using Process_LI_mirror_ftcd.rmd. See bigdf_data_dictionary for variables.
**bruckert_demog.csv** (with data dictionary)
List of participants with details of original classification of laterality, plus handedness.
**demoDop_RH_WG.csv**
Averaged cerebral blood flow data (after processing) for right-handers in original Bruckert study. Long form with columns for Time (in sec), Condition (L channel, R channel or difference), and CBFV value. Used for Figure 1.
**Doppler_GAM_PP1.csv and Doppler_GAM_WG1.csv** (with data dictionary)
Outputs from Compute_GAM_LI.rmd. Applies the complex GAM model from Thompson et al to the raw .exp files from fTCD to give an estimate of laterality index and its standard error. WG1 is word generation and PP1 is semantic matching.
**jn_all.csv**
Output from sample participant from LI toolbox. Very large file with thresholds in row and bootstrapped LIs in columns. Used by LIhistos_create.rmd.
**mirrorsummary.csv** (with data dictionary)
Output from mirror.m; stores LIs from mirror method for all participants, contrasts and ROIs.
**PPTT_trial_inclusion_x.csv and WordGen_trial_inclusion.x.csv**
Use in Compute_GAM_LI.rmd to identify trials marked for exclusion. In the script, statistical criteria are used to remove spikes and dropout artefacts; these files just note rare trials where there are other reasons to remove trials, e.g. participant talks through rest period.
**threshvals.csv** (with data dictionary)
Output from LI_toolbox, giving threshold levels, N suprathreshold voxels L and R, and LIs for a sample participant. Used in creating Figure 2.
**toolboxsummary.csv** (with data dictionary)
Output from LI_DB.m, i.e. same as output from LI Toolbox, except that the confidence interval for weighted mean is saved instead of range.
