A Neurocognitive Threshold-Adaptation Map for Stress, Resilience, Sensitization, and Shutdown

NTAM is a discrete-time systems-level computational scaffold for activation load, stress pressure, threshold entry and occupancy, adaptive regulatory traces, maladaptive sensitizing traces, and bounded mode states. The v5.5 consolidated release integrates canonical reference scenarios, invariant tests, an equal-dose stress-shape audit, a 189-cell priming-state sweep, history-dependent controller comparisons, robustness tests, and mutation and representation audits. The compact source bundle provides runnable Python and Wolfram Language implementations, frozen reference outputs and cross-language comparison routines embedded in Python, the manuscript PDF, and a README with reproduction instructions and SHA-256 integrity hashes. The reported results are model-internal computational findings and do not constitute empirical neuroscience, diagnosis, treatment validation, or a biological neural-circuit model.