Evidence map›Paper›PMID 33923035›Full record

ArticleEntropy (Basel, Switzerland)2021

Cross-Scale Causality and Information Transfer in Simulated Epileptic Seizures.

Kajari Gupta, Milan Paluš

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Kajari GuptaDepartment of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou Věží 2, 182 07 Prague 8, Czech Republic.
Milan PalušDepartment of Complex Systems, Institute of Computer Science of the Czech Academy of Sciences, Pod Vodárenskou Věží 2, 182 07 Prague 8, Czech Republic.ORCID 0000-0001-8474-1436

Funding

Akademie Věd České Republiky Praemium Academiae awarded to M. PalusGrantová Agentura České Republiky GA19-16066S
6 · The paper itself

Abstract

An information-theoretic approach for detecting causality and information transfer was applied to phases and amplitudes of oscillatory components related to different time scales and obtained using the wavelet transform from a time series generated by the Epileptor model. Three main time scales and their causal interactions were identified in the simulated epileptic seizures, in agreement with the interactions of the model variables. An approach consisting of wavelet transform, conditional mutual information estimation, and surrogate data testing applied to a single time series generated by the model was demonstrated to be successful in the identification of all directional (causal) interactions between the three different time scales described in the model. Thus, the methodology was prepared for the identification of causal cross-frequency phase-phase and phase-amplitude interactions in experimental and clinical neural data.

Indexed as

epilepsy modelGranger causalityinformation transferinteractionsmultiscale dynamics

Identifiers

PMID33923035
PMCPMC8146730

What OpenQuestion holds

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Registered trials

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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.