Evidence map›Paper›PMID 39562932›Full record

ArticlePhysical review. E2024

Neuromodulatory effects on synchrony and network reorganization in networks of coupled Kuramoto oscillators.

Sinan Aktay, Leonard M Sander, Michal Zochowski

Abstract read
In one paragraph

Article in Physical review. E, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Sinan AktayBiophysics Program, <a href="https://ror.org/00jmfr291">University of Michigan, Ann Arbor</a>, Michigan 48105, USA.
Leonard M SanderDepartment of Physics, <a href="https://ror.org/00jmfr291">University of Michigan, Ann Arbor</a>, Michigan 48105, USA.
Michal ZochowskiBiophysics Program, <a href="https://ror.org/00jmfr291">University of Michigan, Ann Arbor</a>, Michigan 48105, USA.

Funding

CRCNS: Acetylcholine and state-dependent neural network reorganizationR01MH135565 · NIMH · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ATON, SARA J, ZOCHOWSKI, MICHAL R · 2023 to 2025
$949k
NIMH NIH HHS R01 MH135565
6 · The paper itself

Abstract

Neuromodulatory processes in the brain can critically change signal processing on a cellular level, leading to dramatic changes in network level reorganization. Here, we use coupled nonidentical Kuramoto oscillators to investigate how changes in the shape of phase response curves from Type 1 to Type 2, mediated by varying ACh levels, coupled with activity-dependent plasticity may alter network reorganization. We first show that, when plasticity is absent, the Type 1 networks with symmetric adjacency matrix, as expected, exhibit asynchronous dynamics with oscillators of the highest natural frequency robustly evolving faster in terms of their phase dynamics. However, interestingly, Type 1 networks with an asymmetric connectivity matrix can produce stable synchrony (so-called splay states) with complex phase relationships. At the same time, Type 2 networks synchronize independent of the symmetry of their connectivity matrix, with oscillators locked so that those with higher natural frequency have a constant phase lead as compared to those with lower natural frequency. This relationship establishes a robust mapping between the frequency and oscillators' phases in the network, leading to structure and frequency mapping when plasticity is present. Finally, we show that biologically realistic, phase-locking dependent, connection plasticity naturally produces splay states in Type 1 networks that do not display the structure-frequency reorganization observed in synchronized Type II networks. These results indicate that the formation of splay states in the brain could be a common phenomenon.

Identifiers

PMID39562932
PMCPMC11876786

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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.