Evidence map›Paper›PMID 40443801›Full record

ArticleFrontiers in neuroscience2025

Case Report: Electro-cortical network effects of an acute stroke revealed by high-density electroencephalography.

Elena Monai, Brinda Sevak, Klevest Gjini, Lorenzo Pini, Giulio Tononi, Aaron F Struck, Melanie Boly

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 2025. 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. Review
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.

Elena MonaiDepartment of Neurology, University of Wisconsin-Madison, Madison, WI, United States.
Brinda SevakDepartment of Neurology, University of Wisconsin-Madison, Madison, WI, United States.
Klevest GjiniDepartment of Neurology, University of Wisconsin-Madison, Madison, WI, United States.
Lorenzo PiniPadova Neuroscience Center, University of Padua, Padua, Italy.
Giulio TononiWisconsin Institute for Sleep and Consciousness, University of Wisconsin-Madison, Madison, WI, United States.
Aaron F StruckDepartment of Neurology, University of Wisconsin-Madison, Madison, WI, United States.
Melanie BolyDepartment of Neurology, University of Wisconsin-Madison, Madison, WI, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Focal lesions such as a stroke can cause not only local effects but also distant effects in anatomically intact regions. The impact of stroke lesions on brain networks has been mapped using neuroimaging techniques such as functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI). In the present study, we established the feasibility of detecting network dysfunction at the electrocortical level using high-density electroencephalography (HD-EEG). Case report: We studied brain function using HD-EEG in a patient with an acute left middle cerebral artery stroke. Slowing in the delta range was present beyond the ischemic focus, extending to the perilesional regions as well as distant regions. There was also delta connectivity in the stroke hemisphere with slowing affecting mainly distant regions that were interconnected with the site of the ischemic region (i.e., network-level diaschisis), although this was not statistically significant. Conclusion: This case study illustrates the feasibility of using HD-EEG to map local and distant electrical activity consequences of an acute stroke on cortical functions. Such a technique could be clinically useful to improve personalized stroke-network mapping in patients with acute cortical lesions.

Indexed as

diaschisisHD-EEGnetworkslow wavestroke

Identifiers

PMID40443801
PMCPMC12119589

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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.