TSA Bus 4 Speech Servo Encoding: Cross-Correlation Between Articulatory Servo Signals and Intracranial High-Gamma Activity During Word Production (v1.0)

Analysis scripts and results for the "Bus 4" speech encoding analysis within the Self-Referential Signal Theory (TSA / Théorie du Signal Autoréférentielle) framework. Using intracranial sEEG data from the SingleWordProductionDutch dataset (Verwoert & Herff 2022, Sub-09: 117 contacts, 100 Dutch words read aloud), we extract 10 articulatory servo signals from the patient's audio (amplitude, voicing, pitch, lip closure, lip rounding, jaw/F1, tongue position/F2, tongue height, nasality, uvular) and compute systematic cross-correlations with high-gamma (70–150 Hz) envelope in 6 brain regions. Key finding: Motor cortex is the ONLY region positively correlated with all articulatory servos (r = 0.83–0.88, p < 0.001), confirming it as the servo command output. The anterior insula shows the strongest NEGATIVE correlations (r = –0.62 to –0.75, p < 0.001), non-selective across articulators, consistent with encoding pre-articulatory bodily uncertainty (residual prediction error in TSA). This dissociation — Motor positive/content-specific vs. Insula negative/content-agnostic — supports the TSA claim that speech production requires both the oscillatory content bus (Bus 4) and the interoceptive confirmation signal (Bus 1). HG onset cascade (voice-aligned): Motor –213ms, vSMC +290ms, STG +423ms, Insula +538ms. Package includes: 2 Python scripts (HG cascade v4 + servo cross-correlation v2), 24 result figures (cascade plots, cross-correlation matrix, lag analysis, articulatory servo traces, somatotopy maps, per-word examples), 3 CSV data files, and a detailed README.