Analysis Pipeline Description The analysis code for Idiosyncratic Relation Between Human Brain Activity and Behavior. The analysis is separated into 7 MATLAB files. All data in this repository are in a mat format, but we have added the Tools for NIFTI and Analyze toolbox (Tools_for_NIfti folder) and a sample Nifiti file (Nifti_Header_Info.nii) containing header information the for anyone wishing to convert mat files into NIFTI format. All code used in the analyses will generate the necessary NIFTI files. Part 1: Standard Group Level Analysis GLM_Analysis_1_Group_Difference.m performs standard group level analysis where for task- and behavior-based activation. For task-based this analysis calculates the amount activation in a brain region across subjects. For behavior-bases this analysis calculates differences between subjects with higher or lower than median average behavioral performance. Part 2: Calculate Within-Subject Differences Activation Differences in Behavior GLM_Analysis_2_Calculate_High_vs_Low_Behavior_Maps.m calculates the differences fast and slow RT blocks (or high vs low confidence blocks) within a person to be used for subsequent analyses. For convivence and speed we have included the files generated by this part of the analysis DiffMaps_Ttest_Smooth_[X]mm.mat. Part 3: Within-Subject Reliability and Subject-to-Group Similarity Analysis GLM_Analysis_3_Within_and_Subj2Grp_Analysis.m this analysis performs the within-subject reliability, subject to group similarity, fingerprinting and spatial similarity analysis. This code will generate the figures found in Figure 3A-C and Figure S2 and S3. For the spatial figures, you can use any plotting tool that takes NIFTI files, but our figures we generated using Nilearn. Part 4: Binary Spatial Similarity GLM_Analysis_3_Within_and_Subj2Grp_Analysis.m calculates the consistency in a voxel activation across subject. The file will generate NIFTI images that were used in creating Figure 3D and Figure S5. Part 5: ROI Based Analysis GLM_Analysis_5_ROI_Based_Similarity.m performs within-subject reliability and subject to group similarity analysis using average activation from 200 brain regions from the Schaefer-Yeo atlas. For convivence we have included the activations per ROI in the RoiData.m file. Activation data was extracted using MarsBar toolbox and we have added the ROIs in MarsBar compatible format in the ROI directory. Part 6: Model Simulation GLM_Analysis_6_Model_Simulation.m perform within-subject reliability, subject to group similarity and fingerprinting for activation pattern from modeled subjects. The 6 free parameters values were estimated using the BADs Toolbox. To code to estimate these values is in the Part_1_Idetify_Parameter_Values.m in the Code_Utils directory. Futhermore, to estimate the number of independent voxels for fingerprint analysis use the Part_2_Fingerprinting_Identify_Number_of_Voxels_For_Fitting.m code in the Code_Utils directory. Part 7: Expected Random Values GLM_Analysis_7_Expected_Random_Value.m estimates the expected value for the spatial overlap and consistency analysis.