Neural Coherence Simulation Dataset (QDL Framework)

# Neural Coherence Simulation Dataset (QDL Framework) This archive contains synthetic data and simulation code supporting the manuscript: **"Predicted and Testable Neural Coherence Effects Under a Quantized Dimensional Ledger Framework"** Author: **James D. Bourassa** Institution: Quantum AetherDynamics Institute --- ## Contents | File | Description ||------|-------------|| `dataset.csv` | Monte Carlo simulation output: PLV + SNR values at 10, 16, 26, 42 Hz (50 runs/frequency; 200 rows total). || `simulation_code.py` | Python script that reproduces `dataset.csv`. || `LICENSE.txt` | CC-BY 4.0 license text. || `README.md` | This documentation file. | --- ## Purpose These files evaluate testable predictions of neural coherence under the Quantized Dimensional Ledger (QDL) framework, including phase-locking and SNR behavior used in the manuscript's simulations and Appendix B. --- ## Requirements - Python 3.8+ - Packages: `numpy`, `pandas` ```bash pip install numpy pandas ``` --- ## How to Reproduce the Dataset ```bashpython simulation_code.py``` This will generate `dataset.csv` in the current directory with the same structure as provided here. --- ## Data Format (`dataset.csv`) | Column | Meaning ||--------|---------|| `run` | Trial index (1–50 per frequency) || `frequency_Hz` | Driving frequency: 10, 16, 26, or 42 Hz || `PLV` | Phase-Locking Value (0–1; higher is stronger entrainment) || `SNR_dB` | Signal-to-noise ratio (dB), typically ~5–8 dB | --- ## License (CC-BY 4.0) This dataset and code are released under the **Creative Commons Attribution 4.0 International** license. You are free to share and adapt the material for any purpose, even commercially, with appropriate credit. **Attribution suggestion:** Bourassa, J.D. (2025). *Neural Coherence Simulation Dataset (QDL Framework)*. Zenodo. DOI: _[to be assigned]_ Full text: https://creativecommons.org/licenses/by/4.0/ --- ## Contact **James D. Bourassa** Quantum AetherDynamics Institute Email: [e-mail]