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{\rtf1\ansi\ansicpg1252\cocoartf2709 \cocoatextscaling0\cocoaplatform0{\fonttbl\f0\fswiss\fcharset0 Helvetica;} {\colortbl;\red255\green255\blue255;\red0\green0\blue0;\red255\green255\blue255;} {\*\expandedcolortbl;;\cssrgb\c0\c1\c1;\cssrgb\c100000\c100000\c100000\c0;} \paperw11900\paperh16840\margl1440\margr1440\vieww21640\viewh8400\viewkind0 \pard\tx566\tx1133\tx1700\tx2267\tx2834\tx3401\tx3968\tx4535\tx5102\tx5669\tx6236\tx6803\pardirnatural\partightenfactor0 \f0\fs24 \cf0 Required software:\ \ 1. MATLAB & MemToolbox\ 2. R\ \ Analysis script order:\ \ tdcs_1_data_cleaning.R\ # Get the valid three sessions each participant (n=48) : \ # 0. keep only valid extId. \ # 1. Correct human error during data collection according to the notes: ID 115 session 2 belong to 116 session 1\ # 2. Check each participants and its session number and trial number\ # 3. remove invalid trails, sessions and participant \ #\ # required input: \ # 1. downloaded in rawData Folder from https://www.tatool-web.com/#!/analytics and unzip to input Folder\ # 2. conditionList.csv in the working directory\ # 3. customized function: reduceReplica.R \ \ # Output: \ # 1. ~cleaned/ort_tdcs.csv\ \ # Basic session information for running the analysis \ # R version 4.1.3 (2022-03-10)\ # Platform: x86_64-apple-darwin17.0 (64-bit)\ # Running under: macOS Monterey 12.2.1\ # Additional packages: see tdcs_3_analysis.R comments\ \ tdcs_2_FitIntoModels.m\ \ % % Compare the model and get the parameters:\ % % Require: \ % % 0. MemToolbox (Suchow et al., 2013)\ % % 1. datastruct.m \ % % 2. compareModels.m\ % % 3. getParamters_tDCS.m \ \ % input: ~/cleaned/ort_tdcs.csv\ \ % output: \ % 1. overal ~/ICs.mat in cleaned folder; based on overal ICs: cleaned/outputICS/dAIC_M1_M2.csv\ % & cleaned/outputICS/dBIC_M1_M2.csv & cleaned/outputICS/eachCondFit.csv folder for future\ % plotting needs\ % 2. ~/output/capacity_*.csv & precision_*.csv \ \ % MATLAB R2021a\ \ tdcs_3_analysis.R\ \ general input: \ demographics.csv\ ~ output/ *.csv\ \ output: ~ output/ Descriptive Statistics of Performance After Each Stimulation.docx\ \ \ required script: 'analysis_plot_model_comparison.R'\ # Model comparision results####\ # Input: dAIC_M1_M2.csv & dBIC_M1_M2.csv; eachCondFit.csv\ # Output: ~ cleaned/outputICS/ AIC_all.docx & BIC_all.docx ; summaryAICBIC.docx \ \ required script: 'analysis_main.R'\ # Main analysis ####\ # 1. descriptive stats (Table 1 in the manuscript)\ # 2. plot the main resutls (Figure 2 in the manuscript)\ # 3. Two-way mixed ANOVA test\ # Input: capacityF & precisionF\ # Output: Table_descriptive_changes.docx, main_results_figure.png, ANOVA_stats.docx, \cf2 \cb3 Summary for Posterior Distribution ANOVA.docx\cf0 \cb1 \ \ required script: 'analysis_follow.R'\ # compared against zero, one-sample t-tests----\ # 1. compared against zero, one-sample t-tests\ # 2. paired t-test on capacity at set size 6\ # Input: capacityF & precisionF\ # Output: t_stats.docx, \cf2 \cb3 Summary for Posterior Distribution t-tests.docx, PPC compared to zero and DLPFC at set size six.docx\cf0 \cb1 \ \ required script: 'analysis_questionnaires.R'\ # post stimulation rating (supplementary analysis)\ # Input: Sessions & Questionnaires.xlsx\ # Output: Adverse Effect Table.docx\ \ run extra sensitivity analyses: 'analysis_main_sensitivity.R\'92 & 'analysis_follow_sensitivity.R\'92\ \ \ }
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the replications study
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