Evidence map›Paper›PMID 38477669›Full record

ArticleeLife2024

Structural constraints on the emergence of oscillations in multi-population neural networks.

Jie Zang, Shenquan Liu, Pascal Helson, Arvind Kumar

Open access · goldAbstract read
In one paragraph

Article in eLife, 2024. 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
0.4field-weighted citation impact, top 41% of its field
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, 2 citations in OpenAlex.

  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

4 authors at 2 institutions in 2 countries.

Jie ZangSchool of Mathematics, South China University of Technology, Guangzhou, China.ORCID https://orcid.org/0000-0003-2655-3343
Shenquan LiuSchool of Mathematics, South China University of Technology, Guangzhou, China.
Pascal HelsonDivision of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-2877-3705
Arvind KumarDivision of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.ORCID https://orcid.org/0000-0002-8044-9195
KTH Royal Institute of Technology · SEScience for Life Laboratory · SE

Funding

National Natural Science Foundation of China 11872183National Natural Science Foundation of China-Guangdong Joint Fund 11572127Vetenskapsrådet 2018-03118Vetenskapsrådet StratNeuro
6 · The paper itself

Abstract

Oscillations arise in many real-world systems and are associated with both functional and dysfunctional states. Whether a network can oscillate can be estimated if we know the strength of interaction between nodes. But in real-world networks (in particular in biological networks) it is usually not possible to know the exact connection weights. Therefore, it is important to determine the structural properties of a network necessary to generate oscillations. Here, we provide a proof that uses dynamical system theory to prove that an odd number of inhibitory nodes and strong enough connections are necessary to generate oscillations in a single cycle threshold-linear network. We illustrate these analytical results in a biologically plausible network with either firing-rate based or spiking neurons. Our work provides structural properties necessary to generate oscillations in a network. We use this knowledge to reconcile recent experimental findings about oscillations in basal ganglia with classical findings.

Indexed as

Basal GangliaKnowledgeNeural Networks, ComputerNeuronsSystems Theorybasal ganglianetwork dynamicsnetwork structureneural networksneurosciencenoneoscillations

Identifiers

PMID38477669
PMCPMC10937037
OpenAlexW4387869141

What OpenQuestion holds

Textmetadata
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.