ISE

Overview

This repository contains the ISE experiment materials (PsychoPy), supporting stimuli, and analysis scripts for scoring free-recall and recognition outcomes. The PsychoPy task produces per-participant CSV/LOG/PSYDAT files, and the RMarkdown scripts compute summary scores and strategy selections from those outputs.

Repository Structure

• ISE_PY/: PsychoPy experiment files and audio stimuli
• ISE_PY/word_recall_1_new.psyexp: Builder source for the task
• ISE_PY/word_recall_1_new.py: Generated PsychoPy script (v2024.1.5)
• ISE_PY/word_recall_1_new_lastrun.py: Last-run script snapshot
• ISE_data/: Raw participant data organized by subject folder
• ise_scripts/: Analysis and utility scripts
• ise_scripts/summaryscore_ISE.Rmd: Main scoring pipeline for Study 1
• ise_scripts/File_renaming_BASHscript.sh: Utility to normalize filenames to participant IDs
• ise_scripts/study_2.1/: Study 2.1 analysis scripts and raw data staging
• ise_osf/: Export-ready CSVs and column index for OSF
• Manuscript/: Manuscript PDFs

Experiment Pipeline (PsychoPy)

• The task is defined in ISE_PY/word_recall_1_new.psyexp and exported to word_recall_1_new.py.
• The experiment uses PsychoPy audio via prefs.hardware['audioLib'] = 'ptb' and expects a 1920x1080 fullscreen window by default.
• Data output defaults to a data/ directory alongside the script and uses the pattern: data/<participant>_word_recall_1_new_<timestamp>.(csv|log|psydat)

Analysis Pipeline

Summary Scoring (Study 1)

• ise_scripts/summaryscore_ISE.Rmd reads all CSVs under ISE_data/.
• Free Recall (FR) scoring is computed by filtering: Condition == "Free", SoundCondition in {Silence, Natural, Repeated}, TrialType == "Real" and summing FreeScore.
• Recognition (IR) scoring is computed by filtering Condition == "Recognition" and using ir_condition with SoundCondition and TrialType to compute target/lure counts and scores.
• Strategy variables are pulled from RespFinalStrat1.response and RespFinalStrat2.response, with fallback to trials_3.RespFinalStrat1.response / trials_3.RespFinalStrat2.response when present.
• The script uses row windows (e.g., FR 140:190, IR 300:410) to find the first non-missing response in a flexible way.

Study 2.1

• ise_scripts/study_2.1/summaryscore_ISE.Rmd mirrors the Study 1 logic but targets ise_scripts/study_2.1/ISE_data_raw/.

Running the Experiment

1. Open ISE_PY/word_recall_1_new.psyexp in PsychoPy Builder (v2024.1.5).
2. Ensure the audio stimuli files (e.g., CS1.mp3, SS1.mp3, etc.) are present in ISE_PY/.
3. Run from Builder or execute word_recall_1_new.py via PsychoPy Runner.

Running the Analysis

1. Update the hardcoded parent_directory in ise_scripts/summaryscore_ISE.Rmd to the local path where your ISE_data lives.
2. Knit the RMarkdown or run the chunks in RStudio.
3. Repeat for Study 2.1 if needed, using the study-specific Rmd.

Notes on Paths and Reproducibility

Many scripts use absolute paths (e.g., /Users/dannyzweben/Desktop/CABLAB_Files/...). For portability, set a project root variable and build paths relative to it.

Data Handling

Raw participant data is intentionally ignored by git (see .gitignore). Keep data locally or in a secure data store and point the scripts to those locations.