The lifetime of the coherent response: sealed laws of its rise, its peak, and its fall

When a recurrent network is perturbed, how long does its stimulus-locked response live? We define T_c as the post-stimulus time by which the coherent (cross-trial-reproducible) response accumulates 80% of its energy, and report its life-cycle as sealed results (public preregistrations before any blind quantity, single runs, failures included), each given both as it fell and under a pedestal-exclusion criterion that separates the response's lifetime from the noise floor of the estimator. Rise: on the stable side, coherent lifetime is set by the relaxation time — Spearman(T_c, 1/|λ|) = +0.943 (p = 3.5 × 10⁻²¹, 43 virgin networks), and +0.937 under a post-hoc quality gate: the paper's most robust result. Peak: lifetime is maximal precisely at the edge of chaos — median 110.5 samples versus 3.0 in deep order and 18.0 in deep chaos (37× and 6×), replicating wholesale in a second sealed protocol's fresh networks; under the quality gate the peak persists but roughly halves (19.5× and 3.2×), because near the edge the response is long-lived and weak per trial, exactly where a clipped estimator's noise pedestal accumulates. Fall: on the chaotic side the sealed protocol returned Spearman −0.567 with an ln–ln slope of −0.559 (95% CI [−0.79, −0.33]), excluding the −1 exponent of our own naive divergence derivation. That direction is robust — it survives every deletion we tried, and partialling out the generator parameter leaves −0.511 — but the magnitude is not: gated, the correlation falls to −0.438 (below the sealed bar) and the slope to −0.342, so the honest interval for the exponent is −0.34 to −0.56 and "λ^(−0.56)" should be read as its upper end. We also report a methodological result of independent interest: the split-half reliability of T_c is +0.976 across an order-to-chaos population but only +0.103 within the chaotic band where the decay claim lives — a target's reliability must be measured on the domain of the claim, not on a wider population where ranking is easy. Maximal coherent time is nonetheless not maximal complexity: the sealed protocol that replicated the edge peak established that the λ stratum maximizing T_c is not the one maximizing reproducible dimensionality, and a companion paper (doi:10.5281/zenodo.22168818) shows that at controlled saturation the edge confers no richness advantage at all. We close with the measurement boundary, mapped by three known-truth benches: at realistic recording geometries every T_c estimator we built fails validation — one would have fabricated an inverted result — so the lifetime laws remain laws of the simulated world, awaiting high-trial-count recordings.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-01
DOI
https://doi.org/10.5281/zenodo.22238035
Primary Topic
Protein Structure and Dynamics
Type
preprint
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
preprint

The lifetime of the coherent response: sealed laws of its rise, its peak, and its fall

Nicolás Federico Galindez
Zenodo (CERN European Organization for Nuclear Research)
Protein Structure and Dynamics
preprint

The lifetime of the coherent response: sealed laws of its rise, its peak, and its fall

Nicolás Federico Galindez
preprint en

Abstract

When a recurrent network is perturbed, how long does its stimulus-locked response live? We define T_c as the post-stimulus time by which the coherent (cross-trial-reproducible) response accumulates 80% of its energy, and report its life-cycle as sealed results (public preregistrations before any blind quantity, single runs, failures included), each given both as it fell and under a pedestal-exclusion criterion that separates the response's lifetime from the noise floor of the estimator. Rise: on the stable side, coherent lifetime is set by the relaxation time — Spearman(T_c, 1/|λ|) = +0.943 (p = 3.5 × 10⁻²¹, 43 virgin networks), and +0.937 under a post-hoc quality gate: the paper's most robust result. Peak: lifetime is maximal precisely at the edge of chaos — median 110.5 samples versus 3.0 in deep order and 18.0 in deep chaos (37× and 6×), replicating wholesale in a second sealed protocol's fresh networks; under the quality gate the peak persists but roughly halves (19.5× and 3.2×), because near the edge the response is long-lived and weak per trial, exactly where a clipped estimator's noise pedestal accumulates. Fall: on the chaotic side the sealed protocol returned Spearman −0.567 with an ln–ln slope of −0.559 (95% CI [−0.79, −0.33]), excluding the −1 exponent of our own naive divergence derivation. That direction is robust — it survives every deletion we tried, and partialling out the generator parameter leaves −0.511 — but the magnitude is not: gated, the correlation falls to −0.438 (below the sealed bar) and the slope to −0.342, so the honest interval for the exponent is −0.34 to −0.56 and "λ^(−0.56)" should be read as its upper end. We also report a methodological result of independent interest: the split-half reliability of T_c is +0.976 across an order-to-chaos population but only +0.103 within the chaotic band where the decay claim lives — a target's reliability must be measured on the domain of the claim, not on a wider population where ranking is easy. Maximal coherent time is nonetheless not maximal complexity: the sealed protocol that replicated the edge peak established that the λ stratum maximizing T_c is not the one maximizing reproducible dimensionality, and a companion paper (doi:10.5281/zenodo.22168818) shows that at controlled saturation the edge confers no richness advantage at all. We close with the measurement boundary, mapped by three known-truth benches: at realistic recording geometries every T_c estimator we built fails validation — one would have fabricated an inverted result — so the lifetime laws remain laws of the simulated world, awaiting high-trial-count recordings.

Zenodo (CERN European Organization for Nuclear Research)
Protein Structure and Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.