שמור ב:
| מחבר ראשי: | |
|---|---|
| פורמט: | Recurso digital |
| שפה: | |
| יצא לאור: |
Zenodo
2026
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| גישה מקוונת: | https://doi.org/10.5281/zenodo.19362256 |
| תגים: |
הוספת תג
אין תגיות, היה/י הראשונ/ה לתייג את הרשומה!
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תוכן הענינים:
- <p>The package contains four Python analysis scripts, two per-subject result tables (CSV), and a developmental trajectory figure. Scripts require only NumPy, pandas, and matplotlib (no scipy or MNE).</p> <p>Contents:<br>- phi_approx_mea.py — Computes Consciousness Potential Φ and Consciousness Index C(Φ)×100 from Wagenaar et al. (2006) MEA spike-train recordings (.spk.txt.bz2). Reproduces developmental trajectory from DIV 7 (C×100 = 0.6) to peak at DIV 25 (C×100 = 50.9).<br>- eeg_phi_analysis_v2.py — Global Φ analysis for OpenNeuro ds004504 (88 subjects: 36 AD, 29 HC, 23 FTD). Pure Python MATLAB 5.0 reader; no scipy or MNE required.<br>- eeg_analysis_final.py — Post-processing: outlier exclusion, within-dataset calibration of Φ_ref, group statistics, Mann-Whitney U, Cohen's d, Spearman correlations.<br>- eeg_regional_analysis.py — Region-specific analysis (frontal, temporal, parietal, central, occipital) and cross-regional Granger causality (frontal→temporal d = 0.81 for AD vs HC).<br>- eeg_phi_results_calibrated.csv — Per-subject Φ, C×100, and component values for 86 analyzable EEG subjects.<br>- eeg_regional_results.csv — Per-subject regional I_M and cross-regional GC values.<br>- phi_approx_developmental_trajectory.png — MEA C×100 trajectory figure (DIV 7–35).<br>- README.md — Dependencies, usage instructions, parameter descriptions, and data source links.</p> <p>Data sources: Wagenaar et al. (2006) MEA corpus (https://neurodatasharing.bme.gatech.edu/development-data/); OpenNeuro ds004504 (Miltiadous et al., 2023, https://doi.org/10.18112/openneuro.ds004504.v1.0.7). Raw data not redistributed.</p>