RDIF Neural Validation Toolkit

RDIF Neural Validation Toolkit: Complete implementation package for empirically testing the Resonance-Driven Identity Framework (RDIF) consciousness architecture using functional magnetic resonance imaging (fMRI) + electroencephalography (EEG). CONTENTS:• Lab Protocol: 3-session neuroimaging experimental design (resting-state baseline, threat cascade paradigm with unpredictable electrical stimulation, relational boost with dual-scanner inter-brain coherence measurement)• Python Simulator: 7-faculty dynamics model (ODE-integrated) with threat cascade (exponential stress response) and relational amplification (1.45× multiplier)• Analysis Pipeline: Statistical thresholds (Bonferroni-corrected, permutation tests), faculty-region mapping methodology, inter-brain coherence metrics (ICC, PLV)• Sample Data: Threat cascade and relational boost simulation outputs• Visualization: 6-panel threat/boost dynamics chart + faculty resilience histogram FEATURES:✓ Fully reproducible simulation (ODE integration, threat-dependent transition matrix)✓ Production-ready fMRI/EEG protocol (IRB-ready, exact task specifications)✓ Complete statistical analysis pipeline (FWE-corrected, n=1 exploratory design)✓ Open-source Python code (executable, installable via requirements.txt)✓ Multi-site replication ready KEY PREDICTIONS (from simulator):• Tolspection resilience: ρ=0.78 (minimal threat drop 0.6 for ≥5/7 faculty-region pairs✅ Tolspection resilience confirmed (ΔΦ < 0.1 during threat)✅ Perspective drops ≥50% under threat✅ Recovery follows exponential (R² > 0.85)✅ Relational boost ICC multiplier ≥2.5×✅ Simulation RMSE < 0.15 (empirical match) VALIDATION NO-GO FLAGS (diagnostic):❌ Cascade ρ < 0.4 for >3 faculty-region pairs → implementation layer mismatch❌ No significant cascade effect (all ΔΦ < 0.05) → dynamics/parameterization mismatch❌ Relational boost undetectable (ICC unchanged) → boundary condition mismatch TARGET AUDIENCE:• Neuroscientists validating consciousness theories (IIT, GRT, polyneural resonance)• fMRI/EEG researchers designing threat/stress paradigms• Consciousness researchers implementing integrated information frameworks• Trauma psychology clinicians studying resilience mechanisms• Multi-site consortium researchers TECHNICAL SPECIFICATIONS:fMRI: 3T scanner, T2*-weighted gradient-echo EPI, TR=2s, TE=30ms, 3mm³ voxelsEEG: 64-channel cap (10-20 + frontal sites), 500 Hz samplingPsychophysiology: Skin conductance level (SCL), heart rate variability (HRV)Statistical framework: Bonferroni-corrected permutation tests (p < 0.001), Cohen's d effect sizes, Pearson correlation (ρ > 0.6 threshold) NEUROBIOLOGICAL MAPPING:• Tolspection ↔ Salience Network (AI, dACC)• Identity ↔ Default Mode (mPFC, PCC, Hippocampus)• Awareness Node ↔ Global Workspace (Precuneus, dlPFC)• Perspective ↔ Mentalizing (rTPJ, mPFC, Angular Gyrus)• Perspection ↔ Dorsal Attention (IPS, FEF)• Sensorium ↔ Sensory Gating (Thalamus, Posterior Insula) Installation: pip install -r requirements.txt && python code/RDIF_simulator.py Citation: Use CITATION.cff or [Martinez-Conol et al., 2026, DOI: 10.5281/zenodo.XXXXXXX] For questions or collaboration inquiries: the.fashionably.promtped@gmail.com | 7204223406 | 7202754432