Evidence map›Paper›PMID 35104646›Full record

ArticleNeurobiology of disease2022

Quantifying seizure termination patterns reveals limited pathways to seizure end.

Pariya Salami, Mia Borzello, Mark A Kramer, M Brandon Westover, Sydney S Cash

Open access · goldAbstract read
In one paragraph

Article in Neurobiology of disease, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
2.3field-weighted citation impact, top 12% 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

18 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
  2. Thalamocortical network dynamics in focal epilepsy: SEEG investigation.bioRxiv : the preprint server for biology · 2026
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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

5 authors at 3 institutions in 1 country.

Pariya SalamiDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: psalami@mgh.harvard.edu.
Mia BorzelloDepartment of Cognitive Science, University of California, San Diego, CA, USA; Computational Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA.
Mark A KramerDepartment of Mathematics and Statistics, Boston University, Boston, MA, USA.
M Brandon WestoverDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Sydney S CashDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Massachusetts General Hospital · USBoston University · USSalk Institute for Biological Studies · US

Funding

Seizure localization in humans: the effect of inhibitory surround on the EEGR01NS084142 · NINDS · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SCHEVON, CATHERINE A · 2013 to 2022
$6.0M
Neurophysiology of Human Cortical EpilepsyR01NS062092 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S · 2010 to 2021
$4.7M
Integrative Motor Activity Biomarker for the Risk of Alzheimer's RiskRF1AG064312 · NIA · BRIGHAM AND WOMEN'S HOSPITAL · PI HU, KUN · 2019 to 2019
$3.6M
Multimodal Network Connectivity Architecture (MOCA) of the Brain and its Role in the Recovery of Consciousness in Comatose Cardiac Arrest PatientsR01NS102574 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI GREER, DAVID MATTHEW, WU, ONA · 2018 to 2022
$3.4M
Investigation of Sleep in the Intensive Care Unit (ICU-SLEEP)R01NS102190 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$3.2M
Big Data and Deep Learning for the Interictal-Ictal-Injury ContiuumR01NS107291 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI WESTOVER, MICHAEL BRANDON · 2018 to 2022
$2.8M
Understanding the Fast and Slow Spatiotemporal Dynamics of Human SeizuresR01NS110669 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI CASH, SYDNEY S, EDEN, URI TZVI · 2019 to 2023
$2.3M
Seizure focus delineation using spontaneous and stimulus evoked EEG featuresK24NS088568 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S · 2015 to 2019
$923k
NIA NIH HHS RF1 AG064312NINDS NIH HHS K24 NS088568NINDS NIH HHS R01 NS062092NINDS NIH HHS R01 NS084142NINDS NIH HHS R01 NS102190NINDS NIH HHS R01 NS102574NINDS NIH HHS R01 NS107291NINDS NIH HHS R01 NS110669
6 · The paper itself

Abstract

objectiveDespite their possible importance in the design of novel neuromodulatory approaches and in understanding status epilepticus, the dynamics and mechanisms of seizure termination are not well studied. We examined intracranial recordings from patients with epilepsy to differentiate seizure termination patterns and investigated whether these patterns are indicative of different underlying mechanisms.

methodsSeizures were classified into one of two termination patterns: (a) those that end simultaneously across the brain (synchronous), and (b) those whose termination is piecemeal across the cortex (asynchronous). Both types ended with either a burst suppression pattern, or continuous seizure activity. These patterns were quantified and compared using burst suppression ratio, absolute energy, and network connectivity.

resultsSeizures with electrographic generalization showed burst suppression patterns in 90% of cases, compared with only 60% of seizures which remained focal. Interestingly, we found similar absolute energy and burst suppression ratios in seizures with synchronous and asynchronous termination, while seizures with continuous seizure activity were found to be different from seizures with burst suppression, showing lower energy during seizure and lower burst suppression ratio at the start and end of seizure. Finally, network density was observed to increase with seizure progression, with significantly lower densities in seizures with continuous seizure activity compared to seizures with burst suppression. SIGNIFICANCE: Based on this spatiotemporal classification scheme, we suggest that there are a limited number of seizure termination patterns and dynamics. If this bears out, it would imply that the number of mechanisms underlying seizure termination is also constrained. Seizures with different termination patterns exhibit different dynamics even before their start. This may provide useful clues about how seizures may be managed, which in turn may lead to more targeted modes of therapy for seizure control.

Indexed as

Brain WavesEpilepsyBrainElectroencephalographyHumansSeizuresAsynchronous endingBurst suppressionSeizure terminationSynchronous ending

Identifiers

PMID35104646
PMCPMC8860887
OpenAlexW4210762667

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.