Mahasamadhi P2 — The Last Light: A Spiking-Network Model Showing the Dying-Brain Gamma Surge Requires Interneuron-First Metabolic Failure

Version 2 (2026-08-04). Revised to the NLL Universal Paper Format v6. The original text is retained in full; nothing has been deleted. Corrections appear as marked blocks placed at the section that carries the claim, and each one states what the paper said, what the data show, the corrected claim, why it happened, and what still stands. This version adds scoping notes; no claim is retracted.The design is the strongest in the corpus — 800 excitatory and 200 inhibitory units, 20 seeds per arm, a necessity test that abolished the surge in 0 of 20 seeds when vulnerability was reversed, and replication in an independent conductance-based model.Two scoping notes: the 19.4× magnitude is model-specific and should not be read as matching Borjigin or Xu, since the surge ratio is peak over mean baseline; and disinhibition producing transient synchrony is partly entailed by the architecture, so direction and necessity are the claim rather than magnitude. Everything below this line is the original description from version 1. It is retained unchanged for the record. Where it conflicts with the corrections above, the corrections stand. Two framings it repeats have since been withdrawn in full — the Bhaya Quiescence Law and the Buddhi S-Curve. Both are addressed in Maya-Meta P1, now superseded, and in the self-audit of Maya-Meta P2. The Last Light asks a simple mechanical question about a striking observation: dying brains show a brief, powerful surge of fast "gamma" rhythm in the seconds before they fall silent (Borjigin et al. 2013, rats; Xu et al. 2023, dying human patients). Why would a brain running out of fuel suddenly look more organised, not less? This paper tests a specific answer — that the brain's inhibitory "brake" cells (fast-spiking interneurons), being the most energy-hungry, fail first, briefly releasing the excitatory cells into one synchronised flare before silence. A minimal excitatory/inhibitory "PING" spiking neural network (800 excitatory + 200 fast-spiking inhibitory leaky-integrate-and-fire neurons, ~70 Hz baseline gamma) is driven to death by a falling metabolic budget that grows an ATP-gated potassium current; the interneurons carry higher metabolic vulnerability, so they silence first. Across 20 seeds this produces a gamma surge of 19.4 ± 3.8× the living baseline (surged in 20/20 seeds). The decisive necessity test — reversing which population fails first, so the excitatory cells die before the brakes — abolishes the surge entirely (1.2 ± 0.3×, 0/20). The effect survives every sensitivity sweep (metabolic scale, inhibition-first margin, baseline activity) and grows when death is slower (12→28× as time-to-death rises from 1.5 to 8 s) — precisely the rate-dependence the empirical recordings hinted at. The necessity result reproduces in a more biophysical conductance-based model. This paper also answers a question the previous paper in the series left open. Mahasamadhi P1 (Computational Tanatology) watched the same kind of neuromorphic mind die but could not confirm the near-death surge, honestly reporting it as unconfirmed and rate-dependent. P2 builds the mechanism P1 lacked, finds the surge, and confirms its rate-dependence. Honest caveats: this is a prototype simulation with free parameters (reported via sensitivity sweeps, not hidden); the surge is somewhat bursty rather than a single clean transient; the conductance-based robustness confirms the mechanism, not the absolute magnitude; the biology is analogical; and all results are from a single researcher on a single machine (NVIDIA RTX 4060) and await independent replication. Scope-lock per Maya-Meta P2: this is a reproducible signature within an excitatory/inhibitory spiking architecture, NOT a claim about human death, subjective near-death experience, or clinical medicine. Bhaya and Buddhi are treated as Properties, not Laws, and are not measured in this substrate. Series: Part of the Mahasamadhi Series — computational tanatology, the study of death dynamics in artificial neural systems. Second paper in the series, now becoming its own standalone series line. Links: GitHub Repository (private — to request access: email research@nexuslearninglabs.in with subject "Code Access Request — Mahasamadhi-P2" and your research context): https://github.com/venky2099/Mahasamadhi-P2 | Interactive Dashboard: https://venky2099.github.io/Mahasamadhi-P2/docs/dashboard.html | FAQ: https://venky2099.github.io/Mahasamadhi-P2/docs/faq.html Nexus Learning Labs, Bengaluru · UDYAM-KR-02-0122422 · BHASKAR IN-0526-9452JS · ORCID: 0000-0002-3315-7907 · Canary: MayaNexusVS2026NLL_Bengaluru