Evidence map›Paper›PMID 31795065›Full record

ArticleNeuroImage. Clinical2019

Connectivity strength, time lag structure and the epilepsy network in resting-state fMRI.

S Kathleen Bandt, Pierre Besson, Ben Ridley, Francesca Pizzo, Romain Carron, Jean Regis, Fabrice Bartolomei, Jean Philippe Ranjeva, Maxime Guye

Open access · goldAbstract read
In one paragraph

Article in NeuroImage. Clinical, 2019. 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
0.9field-weighted citation impact, top 27% 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, 14 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

9 authors at 3 institutions in 3 countries.

S Kathleen BandtDepartment of Neurological Surgery, Northwestern University, Chicago, IL, USA; ANISE Lab, Northwestern University, Chicago, IL, USA. Electronic address: katie.bandt@northwestern.edu.
Pierre BessonDepartment of Neurological Surgery, Northwestern University, Chicago, IL, USA; ANISE Lab, Northwestern University, Chicago, IL, USA; Department of Radiology, Northwestern University, Chicago, IL, USA.
Ben RidleyCNRS, CRMBM, Aix Marseille Univ., France; AP-HM, CHU Timone, Pôle d'Imagerie Médicale, CEMEREM, Marseille, France.
Francesca PizzoInstitut de Neurosciences des Systèmes, Aix Marseille Univ., Inserm UMR 1106, INS, France; Clinical Neurophysiology, APHM, Hôpital de la Timone, Marseille, France.
Romain CarronInstitut de Neurosciences des Systèmes, Aix Marseille Univ., Inserm UMR 1106, INS, France; Department of Functional and Stereotactic Neurosurgery, Timone University Hospital, Marseille, France.
Jean RegisInstitut de Neurosciences des Systèmes, Aix Marseille Univ., Inserm UMR 1106, INS, France; Department of Functional and Stereotactic Neurosurgery, Timone University Hospital, Marseille, France.
Fabrice BartolomeiInstitut de Neurosciences des Systèmes, Aix Marseille Univ., Inserm UMR 1106, INS, France; Clinical Neurophysiology, APHM, Hôpital de la Timone, Marseille, France.
Jean Philippe RanjevaCNRS, CRMBM, Aix Marseille Univ., France; AP-HM, CHU Timone, Pôle d'Imagerie Médicale, CEMEREM, Marseille, France.
Maxime GuyeCNRS, CRMBM, Aix Marseille Univ., France; AP-HM, CHU Timone, Pôle d'Imagerie Médicale, CEMEREM, Marseille, France; Institut de Neurosciences des Systèmes, Aix Marseille Univ., Inserm UMR 1106, INS, France; Clinical Neurophysiology, APHM, Hôpital de la Timone, Marseille, France.
Inserm · FRCentre National de la Recherche Scientifique · FRNorthwestern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The relationship between the epilepsy network, intrinsic brain networks and hypersynchrony in epilepsy remains incompletely understood. To converge upon a synthesized understanding of these features, we studied two elements of functional connectivity in epilepsy: correlation and time lag structure using resting state fMRI data from both SEEG-defined epileptic brain regions and whole-brain fMRI analysis. Functional connectivity (FC) was analyzed in 15 patients with epilepsy and 36 controls. Correlation strength and time lag were selected to investigate the magnitude of and temporal interdependency across brain regions. Zone-based analysis was carried out investigating directed correlation strength and time lag between both SEEG-defined nodes of the epilepsy network and between the epileptogenic zone and all other brain regions. Findings were compared between patients and controls and against a functional atlas. FC analysis on the nodal and whole brain levels identifies consistent patterns of altered correlation strength and altered time lag architecture in epilepsy patients compared to controls. These patterns include 1) broadly distributed increased strength of correlation between the seizure onset node and the remainder of the brain, 2) decreased time lag within the seizure onset node, and 3) globally increased time lag throughout all regions of the brain not involved in seizure onset or propagation. Comparing the topographic distribution of findings against a functional atlas, all resting state networks were involved to a variable degree. These local and whole brain findings presented here lead us to propose the network steal hypothesis as a possible mechanistic explanation for the non-seizure clinical manifestations of epilepsy.

Indexed as

AdultAlgorithmsBrainBrain MappingElectroencephalographyEpilepsyFemaleFunctional LateralityHumansMagnetic Resonance ImagingMaleMiddle AgedNerve NetNeural PathwaysNeuropsychological TestsRestEpilepsy networkFunctional connectivityResting state networks

Identifiers

PMID31795065
PMCPMC6881607
OpenAlexW2982051960

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.