Evidence map›Paper›PMID 40404918›Full record

ArticleCommunications medicine2025

Inter-seizure variability in thalamic recruitment and its implications for precision thalamic neuromodulation.

Pariya Salami, Angelique C Paulk, Daniel J Soper, Pierre Bourdillon, Peter N Hadar, Omar A Alamoudi, Nathaniel D Sisterson, R Mark Richardson, Sandipan Pati, Sydney S Cash

Abstract read
In one paragraph

Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. A guide to neuromodulation in drug-resistant epilepsy.Epileptic disorders : international epilepsy journal with videotape · 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

10 authors.

Pariya SalamiDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. psalami@mgh.harvard.edu.ORCID http://orcid.org/0000-0001-6260-8634
Angelique C PaulkDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4413-3417
Daniel J SoperDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Pierre BourdillonDepartment of Neurosurgery, Hospital Foundation Adolphe de Rothschild, Paris, France.ORCID http://orcid.org/0000-0002-8441-1311
Peter N HadarDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-1681-4717
Omar A AlamoudiTexas Comprehensive Epilepsy Program, Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Nathaniel D SistersonBrain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
R Mark RichardsonBrain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0003-2620-7387
Sandipan PatiTexas Comprehensive Epilepsy Program, Department of Neurology, The University of Texas Health Science Center at Houston, Houston, TX, USA.ORCID http://orcid.org/0000-0003-4171-2138
Sydney S CashDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.ORCID http://orcid.org/0000-0002-4557-6391

Funding

Neuroscience Resident Research ProgramR25NS065743 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S, WILLIAMS, ZIV · 2009 to 2023
$11.8M
Neurophysiology of Human Cortical EpilepsyR01NS062092 · NINDS · MASSACHUSETTS GENERAL HOSPITAL · PI CASH, SYDNEY S · 2010 to 2021
$4.7M
Multi-Scale Cortical Dynamics in Human EpilepsyR01NS079533 · NINDS · BROWN UNIVERSITY · PI TRUCCOLO, WILSON · 2012 to 2022
$3.4M
Multiscale analysis and modeling of spatiotemporal dynamics in human epilepsyR01NS072023 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI EDEN, URI TZVI, KRAMER, MARK ALAN · 2011 to 2015
$1.8M
NINDS NIH HHS R01 NS062092NINDS NIH HHS R01 NS072023NINDS NIH HHS R01 NS079533NINDS NIH HHS R25 NS065743United States Department of Defense | United States Army | Army Medical Command | Congressionally Directed Medical Research Programs (CDMRP) W81XWH-22-1-0315U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS) K24-NS088568
6 · The paper itself

Abstract

backgroundThalamic stimulation is a promising approach to controlling seizures in patients with intractable epilepsy. It does not, however, provide good control for everyone. A big issue is that the role of the thalamus in seizure organization and propagation is unclear. When using responsive stimulation devices, they must detect seizure activity before sending stimulation. So, it's important to know which parts of the thalamus are involved in different seizures.

methodsTo better choose thalamic targets for stimulation, we studied how different seizures spread to each stimulation target. Expert reviews and automated tools were used to identify seizure spread recorded from invasive recordings. We categorized seizures based on how they start and spread, and determined whether seizures reached thalamic areas early or late. We used generalized linear models (GLM) to evaluate which seizure properties are predictive of time of spread to the thalamus, testing effect significance using Wald tests.

resultsWe show that seizures with <2 Hz synchronized-spiking patterns do not spread early to the thalamus, while seizures starting with faster activity (<20 Hz) spread early to all thalamic areas. Most importantly, seizures that begin broadly across the brain quickly recruit the centromedian and pulvinar areas, suggesting these may be better stimulation targets in such cases. Alternatively, seizures that start deep in the temporal lobe tend to involve the anterior part of the thalamus, meaning the centromedian might not be the best choice for those seizures.

conclusionsOur results suggest that by analyzing electrical activity during seizures, we can better predict which parts of the thalamus are involved. This could lead to more effective stimulation treatments for people with epilepsy.

Identifiers

PMID40404918
PMCPMC12098681

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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.