LCYA: Locus Coeruleus - Young Adults Study

Overview

This repository contains the supplementary materials and analysis code for the LCYA (Locus Coeruleus - Young Adults) study. The study investigates the effects and interactions of concurrent physical and cognitive effort on behavioral performance and pupillometric responses in younger adults.

Study Design

Main Research Question

How do concurrent physical effort (handgrip force) and cognitive effort (task difficulty) affect:

• Behavioral performance (accuracy, reaction time)
• Physiological arousal (pupil responses measured via AUC metrics)
• Individual differences in effort-related effects
• Brain-behavior relationships

Tasks

Participants performed perceptual discrimination tasks under varying levels of physical and cognitive effort:

• ADT (Auditory Discrimination Task): Frequency discrimination with concurrent handgrip
• VDT (Visual Discrimination Task): Contrast discrimination with concurrent handgrip
• CDT (Change Detection Task): Arrow direction change detection with concurrent handgrip
• MST (Mnemonic Similarity Task): Memory-based similarity judgments

Experimental Manipulations

• Cognitive Effort: Stimulus difficulty (Easy vs. Hard discrimination)
• Physical Effort: Handgrip force levels (Low: 5% MVC vs. High: 40% MVC)
• Pupillometry: Continuous pupil diameter measurement for arousal assessment

Repository Structure

LCYA/
├── analysis/
│   ├── main/                          # Publication-scale R Markdown workflow
│   └── manuscript_scripts/
│       ├── figures/                   # Figure-specific generation scripts (Figures 2–4)
│       ├── Bivariate_Individual_Differences_brms.R
│       ├── Final_Individual_Differences_Verification.R
│       ├── LCYA_AUC_Analysis.R
│       ├── LCYA_Final_Corrected_Analysis.R
│       ├── Updated_Individual_Differences_Accuracy_RT_SubjectMeans.R
│       └── response_bias_analysis.R
├── code/
│   ├── plot_objects/                  # ggplot object definitions
│   ├── preprocessing/                 # Eyetracker preprocessing utilities
│   └── utilities/                     # Shared helper functions
├── documentation/
│   ├── ANALYSIS_OVERVIEW.md
│   ├── CODE_DOCUMENTATION.md
│   ├── REPOSITORY_STRUCTURE.md
│   └── results_reports/
│       ├── FINAL_RESULTS_COMPARISON.md
│       ├── INDIVIDUAL_DIFFERENCES_FINAL_SUMMARY.md
│       ├── Individual_Differences_Brms_Report.md
│       ├── PHYSIOLOGICAL_EFFECTS_ANALYSIS_SUMMARY.md
│       └── subject_means/
│           ├── ANALYSIS_COMPLETE_SUMMARY.md
│           ├── VERIFICATION_SUMMARY.md
│           └── results/
│               ├── individual_differences_subject_means_summary.csv
│               ├── individual_differences_subject_means_report.md
│               └── updated_manuscript_text.md
├── figures/
│   └── publication/                   # Publication-ready PNG exports
├── CONTRIBUTING.md
├── LICENSE
└── README.md

Key Files

Main Analysis

• analysis/main/Aggregated_analysis_publication.Rmd - Complete analysis pipeline and results

Manuscript-Verified Scripts and Reports

The table below links each Results subsection and figure to the script that generated it:

Result / Figure	Script	Key Outputs
Full manuscript pipeline	analysis/manuscript_scripts/LCYA_Final_Corrected_Analysis.R	Behavioral, physiological, and individual-differences statistics written to documentation/results_reports/.
Pupillometry AUC models	analysis/manuscript_scripts/LCYA_AUC_Analysis.R	Total, Cognitive, and Physical AUC model summaries.
Figure 2 – Task performance	analysis/manuscript_scripts/figures/Figure2_Clean_Final_Version.R	figures/publication/Figure2_Task_Performance_Effects.png.
Figure 3 – Pupil waveforms	analysis/manuscript_scripts/figures/LCYA_Isolated_Cognitive_AUC_Analysis.R	figures/publication/Figure3_Pupil_Waveforms.png plus LMM output.
Figure 4 – Total & Cognitive AUC bars	analysis/manuscript_scripts/figures/LCYA_Updated_Combined_AUC_Plots.R	Figure4_Total_AUC.png, Figure4_Cognitive_AUC.png.
Figure 4 – Combined layout	analysis/manuscript_scripts/figures/LCYA_Figure4_Merged_AUC_Plot.R	Figure4_Merged_Total_Cognitive_AUC.png.
Bayesian individual differences	analysis/manuscript_scripts/Bivariate_Individual_Differences_brms.R	documentation/results_reports/Individual_Differences_Brms_Report.md.
Subject-means individual differences	analysis/manuscript_scripts/Updated_Individual_Differences_Accuracy_RT_SubjectMeans.R	CSV + markdown in documentation/results_reports/subject_means/results/.
Frequentist verification	analysis/manuscript_scripts/Final_Individual_Differences_Verification.R	Confirms quoted correlations for Total & Cognitive AUC.
Response bias analysis	analysis/manuscript_scripts/response_bias_analysis.R	GLMM summary for Same/Different judgments.

Data Preprocessing

• code/preprocessing/eyetracker_mat_to_csv_converter.m - Convert individual MATLAB eyetracker files to CSV
• code/preprocessing/batch_convert_eyetracker_files.m - Batch conversion of all eyetracker files
• code/preprocessing/README.md - Detailed preprocessing documentation

Figures

Publication-ready exports are bundled under figures/publication/:

Figure	File	Generated by
Figure 2 – Behavioral performance	Figure2_Task_Performance_Effects.png	Figure2_Clean_Final_Version.R
Figure 3 – Pupil waveforms	Figure3_Pupil_Waveforms.png	LCYA_Isolated_Cognitive_AUC_Analysis.R
Figure 4 – Total AUC	Figure4_Total_AUC.png	LCYA_Updated_Combined_AUC_Plots.R
Figure 4 – Cognitive AUC	Figure4_Cognitive_AUC.png	LCYA_Updated_Combined_AUC_Plots.R
Figure 4 – Combined layout	Figure4_Merged_Total_Cognitive_AUC.png	LCYA_Figure4_Merged_AUC_Plot.R

Dependencies

The analysis requires the following R packages:

• dplyr, ggplot2, tidyr - Data manipulation and visualization
• gridExtra, cowplot - Plot arrangement
• viridis, ggridges - Advanced plotting
• raincloudplots - Distribution visualizations
• report - Statistical reporting

Usage

1. Install the required R packages (tidyverse, lme4, lmerTest, brms, mgcv, patchwork, ggplot2, etc.).
2. Set your working directory to the repository root.
3. Run analysis/main/Aggregated_analysis_publication.Rmd for the full reproduction, or execute the figure-specific scripts in analysis/manuscript_scripts/figures/ to regenerate individual panels.
4. For the updated subject-means individual-differences analysis, run analysis/manuscript_scripts/Updated_Individual_Differences_Accuracy_RT_SubjectMeans.R; outputs land in documentation/results_reports/subject_means/results/.

Citation

If you use this code or data, please cite: [Your paper citation will go here]

Contact

Mohammad Dastgheib mdast003@ucr.edu

License

This project is licensed under the MIT License - see the LICENSE file for details.

This allows anyone to use, modify, and distribute the code with attribution.