Evidence map›Paper›PMID 33488373›Full record

ArticleFrontiers in computational neuroscience2020

Critical and Ictal Phases in Simulated EEG Signals on a Small-World Network.

Louis R Nemzer, Gary D Cravens, Robert M Worth, Francis Motta, Andon Placzek, Victor Castro, Jennie Q Lou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in computational neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.3field-weighted citation impact, top 23% 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

6 citing papers in PubMed, 13 citations in OpenAlex.

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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

7 authors at 4 institutions in 2 countries.

Louis R NemzerDepartment of Chemistry and Physics, Halmos College of Arts and Sciences, Nova Southeastern University, Fort Lauderdale, FL, United States.
Gary D CravensDepartment of Health Informatics, Dr. Kiran C. Patel College of Osteopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States.
Robert M WorthDepartment of Mathematical Sciences, Indiana University - Purdue University Indianapolis, Indianapolis, IN, United States.
Francis MottaDepartment of Mathematical Sciences, Florida Atlantic University, Boca Raton, FL, United States.
Andon PlaczekDepartment of Medical Education, Dr. Kiran C. Patel College of Allopathic Medicine, Nova Southeastern University, Fort Lauderdale, FL, United States.
Victor CastroDepartment of Chemistry and Physics, Halmos College of Arts and Sciences, Nova Southeastern University, Fort Lauderdale, FL, United States.
Jennie Q LouCollege of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.
Nova Southeastern University · USFlorida Atlantic University · USKhalifa University of Science and Technology · AEUniversity of Indianapolis · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Healthy brain function is marked by neuronal network dynamics at or near the critical phase, which separates regimes of instability and stasis. A failure to remain at this critical point can lead to neurological disorders such as epilepsy, which is associated with pathological synchronization of neuronal oscillations. Using full Hodgkin-Huxley (HH) simulations on a Small-World Network, we are able to generate synthetic electroencephalogram (EEG) signals with intervals corresponding to seizure (ictal) or non-seizure (interictal) states that can occur based on the hyperexcitability of the artificial neurons and the strength and topology of the synaptic connections between them. These interictal simulations can be further classified into scale-free critical phases and disjoint subcritical exponential phases. By changing the HH parameters, we can model seizures due to a variety of causes, including traumatic brain injury (TBI), congenital channelopathies, and idiopathic etiologies, as well as the effects of anticonvulsant drugs. The results of this work may be used to help identify parameters from actual patient EEG or electrocorticographic (ECoG) data associated with ictogenesis, as well as generating simulated data for training machine-learning seizure prediction algorithms.

Indexed as

criticalityepilepsyepileptic seizuresepileptogensisneuronphase transitionsimulation—computerssmall-world networks

Identifiers

PMID33488373
PMCPMC7820784
OpenAlexW3119003677

What OpenQuestion holds

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LicenceCC BY
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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.