Amplified prefrontal control of voluntary action in Tourette syndrome Charlotte L Rae, Jim Parkinson, Sophie Betka, Cassandra D Gould van Praag, Samira Bouyagoub, Liliana Polyanska, Dennis EO Larsson, Neil A Harrison, Sarah N Garfinkel, Hugo D Critchley In this study, 23 participants with Tourette syndrome and 21 controls undertook an intentional inhibition task, during fMRI. Following manuscript peer review, the OSF repository was updated to contain the following items. Note that 'R1' denotes revised items following peer review (use these if arriving at the OSF repository from the final published manuscript) (see 1.7-1.10 and 3.4-3.9). Following review by an in-house statistician as part of seeking to ensure our results are reproducible, as part of the follow-on project https://osf.io/6yknx/, the OSF repository was updated. Note that 'R2' denotes revised items following statistician review. EXCLUDED PARTICIPANTS: CN09 & CN18 – excluded after data collection, but prior to analysis, as became clear during data collection did not meet inclusion/exclusion criteria TS02 – excluded as did not participate in MRI TS06 – excluded as did not participate in clinical questionnaires TS11 – excluded as withdrew prior to data collection TS15 – excluded after data collection, but prior to analysis, as it became clear during data collection they did not meet inclusion/exclusion criteria 1. DEMOGRAPHIC, CLINICAL, AND BEHAVIOURAL DATA 1.1 .jasp statistics file (all_dem_clin_beh_data_int_inhib_fp_MRI.jasp) Contains statistical analyses of the following (summary) data: - demographics (gender, age, years of education) - clinical questionnaire scores (TS and controls: YBOCS, ASRS; TS only: YGTSS, PUTS) - comorbid diagnosis status for ADHD and OCD (TS only) - indices of motor behaviour on intentional inhibition task (%Choose-Go, %NoGo errors, %Go omissions, RTs on Go, NoGo-error, and Choose-Go trials) - above indices of motor behaviour on intentional inhibition task, separated by face prime type (neutral, angry, scrambled) - detection and discrimination task d-prime scores 1.2 csv file (all_dem_clin_beh_data_int_inhib_fp_MRI.csv) Contains data analysed in 1.1 1.3 .jasp statistics file (CN_dem_clin_beh_data_int_inhib_fp_MRI.jasp) Contains statistical analyses of the detection and discrimination task d-prime scores in controls 1.4 csv file (CN_dem_clin_beh_data_int_inhib_fp_MRI.csv) Contains data analysed in 1.3 1.5 .jasp statistics file (TS_dem_clin_beh_data_int_inhib_fp_MRI.jasp) Contains statistical analyses of the detection and discrimination task d-prime scores in TS 1.6 csv file (TS_dem_clin_beh_data_int_inhib_fp_MRI.csv) Contains data analysed in 1.5 1.7 .jasp statistics file (all_dem_clin_beh_data_int_inhib_fp_MRI_r1.jasp) As for 1.1 but updated R1 version 1.8 .csv file (all_dem_clin_beh_data_int_inhib_fp_MRI_r1.csv) Contains data analysed in 1.7 1.9 .csv file (CN_dem_clin_beh_data_int_inhib_fp_MRI_r1.csv) As for 1.4 but updated R1 version (no additional statistics run so no accompanying .jasp file) 1.10 .csv file (TS_dem_clin_beh_data_int_inhib_fp_MRI_r1.csv) As for 1.6 but updated R1 version (no additional statistics run so no accompanying .jasp file) R2 /DATA_INTEN_INHIB_TASK/ Contains sub-folders (one for each participant) with .mat data file from intentional inhibition task /DATA_QUESTIONNAIRES/ Contains sub-folders (one for each participant) with: - pdf of questionnaire output from online web survey - .xls of questionnaire responses to each item and questionnaire overall score 2. TIC REGRESSORS 2.1 spike_tic_regressor_howto_CR.doc Word doc with written and screenshot instructions on how to create tic regressors for entry to the fMRI design matrix in SPM. 2.2 spike_tic_regressor_novideo_howto_CR.doc Word doc with instructions on how to process participants for whom video recording failed, using the back-up written notes on when tics were observed during data acquisition. 2.3 AddTmk_TicMarker_v2_CR.s2s Spike software (Cambridge Electronic Design) script to define tic periods in the Spike video recordings aligned to the fMRI. This creates a new channel in the Spike file that records the video and fMRI, and creates a new GUI-based window to place markers indicating the onset and offset of tics. Version 2 of this script enables numerical tags to be added to indicate the bodily location at which tics were produced: % 1 eye % 2 face % 3 head % 4 eye & face % 5 eye & head % 6 face & head % 7 eye & face & head % 8 hand % 9 arm % 10 foot % 11 leg % 12 body % 13 body & limb % 14 multicombo 2.4 tics_to_onsets.m Matlab script that takes the exported .mat file from the Spike timeline (see instructions in 2.1), and converts this to tic onsets and durations for importing to SPM. Option on lines 79-81 to set events in the GLM regressor as at the visible onset of the tic, or 500ms or 1000ms prior to tic onset (e.g. if interested in looking at activity preceding tics). 2.5 bibletics_to_onsets.m Matlab script that takes manually created .mat file (see instructions in 2.2), for occasions when videos failed, and converts this to tic onsets and durations for importing to SPM. Option on lines 84-86 to set events in the GLM regressor as at the visible onset of the tic, or 500ms or 1000ms prior to tic onset (e.g. if interested in looking at activity preceding tics). 2.6 percent_tic_types_inten_inhib_June2019.m Matlab script that extracts the tic types from the exported (or manually created for failed videos) .mat files, and calculates the percentages by muscle location (e.g. face/body) 2.7 percent_tic_types_inten_inhib.xls Output of 2.6 2.8 matlab_tic_files folder Output of 2.3 (for most participants) and manually created for 3 participants in whom video recording failed. These are entered to 2.4 (most participants) or 2.5 (3 failed videos). 3. INTENTIONAL INHIBITION TASK 3.1 task_code_and_stimuli folder Psychtoolbox code to deliver task and stimuli 3.2 AnalyseBehavioural_aug2019.m Matlab script to extract behavioural measures from individual participant .mat output files 3.3 ts_ii_datasummary_150819.xls Data output file from 3.2 3.4 FacePrimingBehav_extractBehavData_FP.m Matlab script to extract behavioural measures (per trial) from individual participant .mat output files, separating by face prime type 3.5 FacePrimingBehav_extractBehavData.m Matlab script to extract behavioural measures (per trial) from individual participant .mat output files, collapsing across face prime types 3.6 FacePrimingBehav_CalculateMeanBehavData_FP.m Calculate means from output of 3.4 3.7 FacePrimingBehav_CalculateMeanBehavData.m Calculate means from output of 3.5, also separating by 3 blocks of experiment 3.8 ts_ii_data_summary_FP_05-May-2020_FP.xlsx Data output file from 3.6 3.9 ts_ii_data_summary_15-May-2020_Block.xlsx Data output file from 3.7 4. UNIVARIATE fMRI ANALYSIS SCRIPTS 4.1 batch_preproc_SPM12.m SPM preprocessing script 4.2 job_preproc_allModules_SPM12_CR.mat SPM job file, called by 4.1 4.3 onsets_actcon_nov2018_rearrangefordcm.m SPM script to generate <names> <onsets> <durations> 4.4 batch_firstlevel_model_all3runs_SPM12_nov2018.m SPM first level model specification script 4.5 job_firstlevel_model_all3runs_SPM12_CR.mat SPM job file, called by 4.3 4.6 concat_actcon_nov2018.m SPM script to concatenate the 3 fMRI runs together 4.7 batch_firstlevel_estimate_all3runs_SPM12_nov2018.m SPM first level model estimation script 4.8 job_firstlevel_estimate_all3runs_SPM12_CR.mat SPM job file, called by 4.5 4.9 batch_firstlevel_contrasts_actcon_SPM12_may2019.m SPM first level contrast generation script 4.10 job_firstlevel_contrasts_actcon_SPM12_CR.mat SPM job file, called by 4.7 5. UNIVARIATE fMRI SECOND-LEVEL MODELS 5.1 Analysis4_may2019_ts_cn_medcomcovs Second-level design matrix, including both controls and TS. Contains: - Analysis4_may2019_ts_cn_medcomcovs_fullfactorial.mat (SPM batch file specifying and estimating second-level model) - contrasts_setup_Analysis4_may2019_ts_cn_medcomcovs_fullfac.mat (SPM batch file generating contrasts) - covs.mat (SPM covariates file) - SPM beta images - SPM con images (t contrasts), ess images (F contrasts), and associated T/F contrast images - FDRc05 thresholded statistic images (for all significant contrasts) in .nii format (number appending each filename = minimum cluster size for FDRc05 at cluster-forming threshold of p<0.001) - Anatomy toolbox labels for all significant contrasts (thresholded at FDRc05) in .txt format 5.2 Analysis4_may2019_symptomsev_medcomcovs 4 second-level design matrices, in TS only - ChooseGo PUTS - ChooseGo YGTSS - ChooseNoGo PUTS - ChooseNoGo YGTSS 6. PPI ANALYSIS SCRIPTS 6.1 PPI_extract_eigenvariate_ts_act_con.m SPM script to extract VOIs for PPIs 6.2 PPI_create_matlabbatch.m SPM script to create PPI, calling job files in 6.3-6.6 6.3 PPI_create_21CN_23TS_chogo_antIFG.m 6.4 PPI_create_21CN_23TS_chogo_pSMA.m 6.5 PPI_create_21CN_23TS_chonogo_antIFG.m 6.6 PPI_create_21CN_23TS_chonogo_pSMA.m 6.7 batch_PPI_firstlevel_ticregressor_act_con.m SPM script to specify and estimate first level PPI model, and calculate contrast for PPI interaction 7. PPI SECOND-LEVEL MODELS 12 second-level models: 4 in both controls & TS; 4 in TS only examining correlations with PUTS; 4 in TS only examining correlations with YGTSS 7.1 PPI_chogo_antIFG_p1_gp_cov_TSCN 7.2 PPI_chogo_pSMA_p1_gp_cov_TSCN 7.3 PPI_chonogo_antIFG_p1_gp_cov_TSCN 7.4 PPI_chonogo_pSMA_p1_gp_cov_TSCN 7.5 PPI_chogo_antIFG_p1_gp_cov_TS_PUTS 7.6 PPI_chogo_pSMA_p1_gp_cov_TS_PUTS 7.7 PPI_chonogo_antIFG_p1_gp_cov_TS_PUTS 7.8 PPI_chonogo_pSMA_p1_gp_cov_TS_PUTS 7.9 PPI_chogo_antIFG_p1_gp_cov_TS_YGTSSsev 7.10 PPI_chogo_pSMA_p1_gp_cov_TS_YGTSSsev 7.11 PPI_chonogo_antIFG_p1_gp_cov_TS_YGTSSsev 7.12 PPI_chonogo_pSMA_p1_gp_cov_TS_YGTSSsev