Evidence map›Paper›PMID 35110405›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2022

Noninvasive inference methods for interaction and noise intensities of coupled oscillators using only spike time data.

Fumito Mori, Hiroshi Kori

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. 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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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

2 authors.

Fumito MoriFaculty of Design, Kyushu University, Fukuoka 815-8540, Japan; mori@design.kyushu-u.ac.jp kori@k.u-tokyo.ac.jp.ORCID 0000-0002-2018-5917
Hiroshi KoriDepartment of Complexity Science and Engineering, University of Tokyo, Chiba 277-8561, Japan mori@design.kyushu-u.ac.jp kori@k.u-tokyo.ac.jp.ORCID 0000-0003-2899-7896

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Measurements of interaction intensity are generally achieved by observing responses to perturbations. In biological and chemical systems, external stimuli tend to deteriorate their inherent nature, and thus, it is necessary to develop noninvasive inference methods. In this paper, we propose theoretical methods to infer coupling strength and noise intensity simultaneously in two well-synchronized noisy oscillators through observations of spontaneously fluctuating events such as neural spikes. A phase oscillator model is applied to derive formulae relating each of the parameters to spike time statistics. Using these formulae, each parameter is inferred from a specific set of statistics. We verify these methods using the FitzHugh-Nagumo model as well as the phase model. Our methods do not require external perturbations and thus can be applied to various experimental systems.

Indexed as

biological rhythmscoupled oscillatorsinference methodperiod variabilitystochastic dynamical systems

Identifiers

PMID35110405
PMCPMC8833164

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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.