Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Other literature type . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
ZENODO
Other literature type . 2026
License: CC BY
Data sources: Datacite
versions View all 2 versions
addClaim

Sensitivity Analysis of Perceptual Stabilization Regimes under Historical Compression

Authors: Osmolovskyi, Kostiantyn;

Sensitivity Analysis of Perceptual Stabilization Regimes under Historical Compression

Abstract

Sensitivity Analysis of Perceptual Stabilization Regimes under Historical Compression provides a robustness check for the minimal toy model of perceptual stabilization under historical compression and overload. The note tests whether the regime distinctions introduced in the toy model depend on a single selected parameter setting or remain visible under broader variation of overload, resources, historical dominance, signal support, thresholds, and modulation parameters. The note does not introduce a new perceptual model, biological implementation, clinical interpretation, or empirical validation protocol. Its purpose is methodological: to examine the stability of regime separability among stabilization failure, partial stabilization, false completion, and full stabilization within the specified toy-model framework. The analysis uses controlled grid sweeps and random parameter sampling to test how regime boundaries shift under variation of the model’s parameters. The results show that all final regimes remain reachable across parameter variation, while false completion occupies a non-zero but bounded region of the parameter space. This supports the interpretation that false completion is structurally possible in the toy model without being forced as a default outcome. The central contribution of the note is to show that the model is calibration-sensitive but not calibration-arbitrary. Parameter choices shift boundaries among regimes, but they do not collapse the logical distinctions between non-recruitment, recruited-but-insufficient stabilization, dominance-driven false completion, and full stabilization. The note functions as a simulation companion to A Toy Model of Perceptual Stabilization under Historical Compression and Overload. It strengthens the methodological role of the toy model by showing that its qualitative regime structure remains distinguishable under systematic parameter variation.

Keywords

(MeSH) Cognitive Science, (EuroSciVoc) Artificial intelligence

  • BIP!
    Impact byBIP!
    citations
    The total number of citations received by all articles of the researcher of interest.
    12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
citations
The total number of citations received by all articles of the researcher of interest.
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Average
Average
Average
Green