Evidence map›Paper›PMID 40279616›Full record

ArticlePhysical review letters2025

Hierarchy of Chaotic Dynamics in Random Modular Networks.

Łukasz Kuśmierz, Ulises Pereira-Obilinovic, Zhixin Lu, Dana Mastrovito, Stefan Mihalas

Abstract read
In one paragraph

Article in Physical review letters, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Łukasz KuśmierzAllen Institute, Seattle, Washington, USA.
Ulises Pereira-ObilinovicAllen Institute, Seattle, Washington, USA.
Zhixin LuAllen Institute, Seattle, Washington, USA.
Dana MastrovitoAllen Institute, Seattle, Washington, USA.
Stefan MihalasAllen Institute, Seattle, Washington, USA.

Funding

From diverse dynamics to diverse computation via neural cell typesRF1DA055669 · NIDA · ALLEN INSTITUTE · PI MIHALAS, STEFAN, SHEA-BROWN, ERIC TODD · 2021 to 2021
$1.1M
NIDA NIH HHS RF1 DA055669
6 · The paper itself

Abstract

We introduce a model of randomly connected neural populations and study its dynamics by means of the dynamical mean-field theory and simulations. Our analysis uncovers a rich phase diagram, featuring high- and low-dimensional chaotic phases, separated by a crossover region characterized by low values of the maximal Lyapunov exponent and participation ratio dimension, but with high values of the Lyapunov dimension that change significantly across the region. Counterintuitively, chaos can be attenuated by either adding noise to strongly modular connectivity or by introducing modularity into random connectivity. Extending the model to include a multilevel, hierarchical connectivity reveals that a loose balance between activities across levels drives the system towards the edge of chaos.

Identifiers

PMID40279616
PMCPMC13193674

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.