DOI: 10.6084/m9.figshare.25125470.v1
title: The right posterior parietal cortex mediates spatial reorienting of attentional choice bias

description: Codes are written in Matlab. <br>
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Folder Descriptions:<br>
1) SessionComparison --<br>
To compare behavioral and mADC parameters between stimulation sessions (‘sham’, ‘stim’) across cued and uncued locations. Contains data file and codes to generate the Main Figures 2-5 (excluding model comparisons) and Supplementary Figures S3(a, b), S4-7. <br>
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A) Data file (“rPPC_tES_Data.mat”) -- contains the values of parameters (HR, FAR, MLR, d', c, RT) for the stimulation sessions for the two main experiment cohorts (cTBS, tACS at 40 Hz), and one control cohort (tACS at 60 Hz). Data for each cohort is stored in a structure of the same name (e.g., "tACS40" for the cohort of tACS at 40 Hz). Kindly change the ‘task_ID’ in each code to the correct task number (1 = cTBS, 2 = tACS40, 3 = tACS60) to get the results for corresponding task. The variable names for all cohorts follow the same details as listed below:<br>
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i) numSubjects: Number of participants in the cohort (n=28 for cTBS, n=26 for tACS at 40/60 Hz). <br>
ii) sessions: Stimulation sessions involved: (a) cTBS --&gt; Sham and Stim; (b) tACS 40/60 Hz --&gt; Sham, Stim and Post (see Figure 1a).<br>
iii) angles: The five orientation change angles used for each participant. They are consistent for cTBS and tACS_60Hz cohorts but are different for some participants in tACS_40Hz cohort (see Methods).<br>
iv) all_angles: The set of unique orientation change angles used across all participants in a cohort.<br>
v) Params: Behavioural (HR, FAR, MLR, RT) and mADC estimated parameters (d',c) --&gt; (a) for Cued, Uncued and Delta (=cued-uncued); (b) Dimension: [numberOfsubjects x sessions]. Results are summarized in Figures 2-5.<br>
vi) PsychCurve: For generating psychometric/psychophysical curves (see Figures 2a, 4a, S4). Contains HR and d' measures for each orientation change angle --&gt; (a) for Cued and Uncued; (b) Dimension: [numberOfsubjects x numberOfAngles x sessions(sham,stim)] <br>
vii) ChangeHemi: Same as 'Params', but calculated for trials where change occurred on the Ipsilateral visual (right) hemifield or contralateral visual (left) hemifield w.r.t. hemisphere of stimulation (right). <br>
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B) Codes – <br>
i) Figure_SessionCompare.m: To compare ‘sham’ vs ‘stim’ (or ‘post’ in tACS cohorts) measures of parameters at the Cued and Uncued locations. See Main Figures 2(b-d), 3(a, b), 4(b-d), 5(a, b), and Supplementary Figures S6(a, b, d, e). <br>
ii) Figure_DeltaScatter.m: Generates scatter plots to compare ‘sham’ and ‘stim’ (or ‘post’ in tACS cohorts) measures of the attentional modulation of parameters, i.e., Delta (= cued – uncued). See Main Figures 2e, 3(c, d), 4e, 5(c, d), and Supplementary Figures S6 (C, F) and S7(b, c). <br>
iii) Figure_DeltaHistogram.m: Generates histograms to compare ‘sham’ and ‘stim’ (or ‘post’ in tACS cohorts) ) measures of the attentional modulation of parameters, i.e., Delta (= cued – uncued). See the same figures as for Figure_DeltaScatter.m <br>
iv) Figure_PsychCurves.m: Generates psychometric (for HR) and psychophysical (for d’) curves as a function of orientation change angle magnitudes for each session (‘sham’, ‘stim’ and ‘post’). See Main Figures 2a, 4a, and Supplementary Figure S4. <br>
v) Figure_SessionCompare_RT.m: To compare ‘sham’ vs ‘stim’ (or ‘post’ in tACS cohorts) measures of Reaction Time (RT) at the Cued and Uncued locations. See Supplementary Figure S3(a, b). <br>
vi) Figure_Crit_vs_AggrResps.m: Measures the bend correlation between changes in criterion and changes in aggregate hit, false alarm and mislocalization responses after stimulation. See Supplementary Figure S5. <br>
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2) ModelComparison – <br>
To compare the sensitivity and criterion estimates as obtained using either the “selective bias-effect”, “selective sensitivity-effect” and “both-effects” mADC models. Kindly change the ‘task_ID’ in each code to the correct task number (1 = cTBS, 2 = tACS40) to get the results for corresponding task. <br>
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A) Data files: (“CTables_cTBS.mat” and “CTables_tACS40.mat”) in the ‘Data’ folder. <br>
B) Code (‘Fit_sens_crit_const.m’): Runs the three mADC models and computes the AICc and BIC values. See Main Figures 3f and 5f. <br>
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3) MotorMEP – <br>
Code file (‘motorMEP.m’) generates a line plot of the MEP as a function of time after cTBS, and fits bi-exponential and polynomial functions to the data obtained from the data files (.xlsx format) for each participant (n=7). See Supplementary Figure S2b. <br>
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4) RandPermTest – <br>
Code file (‘Figure_RandPermHistogram.m’) generates histograms of the distributions for (a) goodness-of-fit significance values of the mADC model (see Supplementary Figure S1(c, d), and (b) goodness-of-fit p-values comparing the distribution of responses with and without eye-tracking rejection (see Supplementary Figure S1(e, f)). <br>
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5) CommonFunctions – contains codes to run the mADC models and codes used for general figure formatting. Use function 'GetStatistics' to obtain Cohen's d, signrank p-values, and confidence intervals. <br>