Evidence map›Paper›PMID 34529192›Full record

ArticleJournal of mathematical neuroscience2021

Canard solutions in neural mass models: consequences on critical regimes.

Elif Köksal Ersöz, Fabrice Wendling

Abstract read
In one paragraph

Article in Journal of mathematical neuroscience, 2021. 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

2 authors.

Elif Köksal ErsözUniv Rennes, INSERM, LTSI-U1099, Campus de Beaulieu, F - 35000, Rennes, France.
Fabrice WendlingUniv Rennes, INSERM, LTSI-U1099, Campus de Beaulieu, F - 35000, Rennes, France. fabrice.wendling@inserm.fr.

Funding

Manipulating multisite endogenous brain rhythms disrupts epileptic seizuresR01NS092760 · NINDS · ILLINOIS INSTITUTE OF TECHNOLOGY · PI MOGUL, DAVID J · 2016 to 2020
$1.3M
European Research Council 855109NINDS NIH HHS R01 NS092760NINDS NIH HHS R01 NS092760-01A1
6 · The paper itself

Abstract

Mathematical models at multiple temporal and spatial scales can unveil the fundamental mechanisms of critical transitions in brain activities. Neural mass models (NMMs) consider the average temporal dynamics of interconnected neuronal subpopulations without explicitly representing the underlying cellular activity. The mesoscopic level offered by the neural mass formulation has been used to model electroencephalographic (EEG) recordings and to investigate various cerebral mechanisms, such as the generation of physiological and pathological brain activities. In this work, we consider a NMM widely accepted in the context of epilepsy, which includes four interacting neuronal subpopulations with different synaptic kinetics. Due to the resulting three-time-scale structure, the model yields complex oscillations of relaxation and bursting types. By applying the principles of geometric singular perturbation theory, we unveil the existence of the canard solutions and detail how they organize the complex oscillations and excitability properties of the model. In particular, we show that boundaries between pathological epileptic discharges and physiological background activity are determined by the canard solutions. Finally we report the existence of canard-mediated small-amplitude frequency-specific oscillations in simulated local field potentials for decreased inhibition conditions. Interestingly, such oscillations are actually observed in intracerebral EEG signals recorded in epileptic patients during pre-ictal periods, close to seizure onsets.

Indexed as

BurstingCanardsEpilepsyExcitabilityMultiple time-scale systemsNeural mass model

Identifiers

PMID34529192
PMCPMC8446153

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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.