This wiki contains the data/code dictionary identifying the files within this project repository. It does not detail the linked github repo or OSF projects. Raw neuroimaging data and metadata are available here: https://openneuro.org/datasets/ds004226 Each file in this repository is described below: * analysis/ * average_patterns.m - smooth and average patterns for each condition * check_movement.m - script to check head motion * extract_pattern_similarity.m - extract similarity matrices from selected regions * extract_patterns.m - extract stimulus-specific patterns from selected regions * feature_select.m - perform reliability based feature selection * globals.par - general imaging parameters file * make_onsents.ipynb - script to generate onsets/duration files * par_glm_glm1/2.m - parameters files for GLMs * pattern_similarity_by_threshold.csv - what is says on the tin * prep.par - general preprocessing parameters * reliability_maps.m - generate reliability maps * rsa.R - perform representational similarity analysis * summed_analysis.R - perform pattern summation analysis * visualization/ * _mask.nii files - binarized feature selected brain maps * _rel.nii files - nonbinarized voxelwise reliability maps * brain_viz.ipynb - script for generating images for figures * behavioral_data/ * adim_data.csv - action dimension data * fmri_behavior - full data from each scanner participant * intask_ratings.R - assembly of fMRI task rating data * intask_situation_action.csv - situation action ratings from fMRI * intask_situation_state.csv - situation state ratings from fMRI * intask_state_action.csv - state action ratings from fMRI * mdim_data.csv - mental state dimension data * onine_pairs.csv - stimulus pairs for online rating task * online_ratings.R - assemble and analyze online ratings * online_situation_action.csv - situation action ratings from online study * online_situation_state.csv - situation state ratings from online study * online_state_action.csv - state action ratings from online study * sdim_data.csv - situation dimension data * sitrep_rating_data.csv - raw rating data from online task * sitrep_ratingssubject_data.csv - subject-level information from online task * design/ * power.R - parametric power analysis for this study * sitrep_post-scan.qsf - qualtrics survey for post test * online_task/ (note: all meant to run within MySocialBrain.org - not functional as standalone) * sitrep.html - main html page for online rating task * sitrep.js - main javascript for online rating task * sitrep.php - main backend script for online rating task * sitrep_consent_paid.html - consent form for online task * sitrep_instruct_paid.html - instructions for online task * sitrep_results_paid.html - results html for online task * sitrep_test_paid.html - trial html for online task * sitrep_exp/ * Code/ - this folder contains the code for the expriment. There are three versions of the code. * SkyraShortFinalVersion.py - this file contains the code that is to be run for the practice task. * SkyraCompleteRunFinalVersion.py - this file contains the code for the actual experiment. * OnsetCompleteFinalVersion.py - this file contains the code to create the onset and duration files for analysis. * stimulus_selection/ * 100(actions|situations|states).csv - these files contain sets of 100 of each stimulus type, produced by the initial word vector based selection in vector_based_selection.R * action_vectors.csv - vectors for each action word, extracted from pretrained fastText vectors via extract_vectors.py * allverbratings.csv - all human ratings of all verbs (actions) on the ACT-FAST dimensions, compiled from the linked action taxonomy project * allverbratings_gerunds.csv - same as above, but with all verbs in '-ing' form * allverbs_gerunds.txt - just the actions (as verb gerunds) from the above, without ratings * allverbs_gerunds_manual_subset.txt - a manually selected subset of gerunds which eliminates some problematic cases prior to automatic selection of actions * average_DIAMONDS_100.csv - across-participant mean ratings for each of 100 sitations on the DIAMONDS taxonomy * DIAMONDS_correlations.csv - correlations between the average ratings * DIAMONDS_rating_summary.csv - summary statistics of the ratings * DIAMONDS_ratings_raw.csv - raw participant-level ratings of the situations on the DIAMONDS dimensions * extract_vectors.py - extracts word vectors from pretrained fastText embedding * final_stimuli/ * 60(actions|situations|states).csv - final sets of each stimulus type used in the experiment. produced by rating_based_selection.R * get_situation_words.py - break multiword situations into individual words, omitting stopwords * initial_situations.csv - initial list of situation stimuli * initial_states.csv - initial list of state stimuli * initial_states.txt - as above, but in txt format * pc166.csv - ratings of mental states on 3d Mind Model * rating_based_selection.R - final stage of stimulus selection, based on ratings of each type of stimuli * situation_vectors.csv - word vectors for the situation words * state_vectors.csv - word vectors for the state words * tokenized_situations.csv - situation phrases broken up by word * unique_situation_words.txt - list of the unique words across all situations * vector_based_selection.R - initial phase of stimulus selection, based on word vectors from the fastText embedding * sumpats/ featured selected activity patterns for each stimulus for pattern summation analyses