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

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## 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. |

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## 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.

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## Requirements

- Python 3.8+  - Packages: `numpy`, `pandas`    ```bash  pip install numpy pandas  ```

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## 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.

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## 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 |

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## 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/

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## Contact

**James D. Bourassa**  Quantum AetherDynamics Institute  Email: [e-mail]