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The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy

Brain(2024)10.1093/brain/awae189Source: DataRank Database

The interictal suppression hypothesis is the dominant differentiator of seizure onset zones in focal epilepsy is a research paper published in Brain (2024). On theSindex it has a DataRank of 0. It has been cited 25 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access25 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (19 grants)Impact (FWCI 7.23)OA: hybridTopics (49)IDs (PubMed, PMC, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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Authors (16)

Jared Shless ORCID,Sarah K. Bick ORCID,Ghassan S. Makhoul ORCID,A Negi ORCID,Camden E. Bibro

Live enrichment

PubMed:38874456 PMC:PMC11370787 OpenAlex:https://openalex.org/W4399670246

National Institutes of Health

Grant: T32-EB001628, T32-EB021937, T32-GM007347, F31-NS131056, R01-NS112252, F31-NS120401, R00NS097618

NINDS NIH HHS

Grant: R01 NS134625

NIGMS NIH HHS

Grant: T32 GM007347

NICHD NIH HHS

Grant: P50 HD103537

NINDS NIH HHS

Grant: R01 NS112252

NIGMS NIH HHS

Grant: T32 GM152284

NIBIB NIH HHS

Grant: T32 EB021937

NIBIB NIH HHS

Grant: T32 EB001628

NINDS NIH HHS

Grant: F31 NS131056

NINDS NIH HHS

Grant: R00 NS097618

NINDS NIH HHS

Grant: F31 NS120401

National Institutes of Health

Grant: 5T32EB001628-15

Postdoctoral Training in Biomedical MRI and MRS

National Institutes of Health

Grant: 1F31NS120401-01A1

Directed connectivity analysis of resting-state SEEG and DWI to improve lateralization and localization in focal epilepsy

National Institutes of Health

Grant: 5R01NS112252-04

Relating Vigilance to Connectivity and Neurocognition in Temporal Lobe Epilepsy

National Institutes of Health

Grant: 1F31NS131056-01A1

Dynamic multimodal connectivity analysis of brain networks in focal epilepsy

National Institutes of Health

Grant: 5R00NS097618-04

MULTIMODAL MAPPING OF SUBCORTICAL AND CORTICAL FUNCTIONAL NETWORK DISTURBANCES IN FOCAL EPILEPSY

National Institutes of Health

Grant: 3R01NS134625-02S1

Development of multimodal network analyses to improve epilepsy surgery outcomes

National Institutes of Health

Grant: 5T32EB021937-10

Training Program for Innovative Engineering Research in Surgery and Intervention

National Institutes of Health

Grant: 5T32GM007347-08

MEDICAL SCIENTIST TRAINING PROGRAM

FWCI

7.23

Citation Percentile

1.0%

Citation Trend

2024

2025

2026

hybridLicense: cc-by-nc

journalhttps://academic.oup.com/brain/advance-article-pdf/doi/10.1093/brain/awae189/58233611/awae189.pdf

publisherhttps://academic.oup.com/brain/advance-article-pdf/doi/10.1093/brain/awae189/58233611/awae189.pdf

publisherhttps://academic.oup.com/brain/advance-article-pdf/doi/10.1093/brain/awae189/58935876/awae189.pdf

publisherhttps://academic.oup.com/brain/article-pdf/147/9/3009/59004256/awae189.pdf

journalhttps://doi.org/10.1093/brain/awae189

Fields of Study

Epilepsy research and treatmentEEG and Brain-Computer InterfacesFunctional Brain Connectivity Studies03 medical and health sciences0302 clinical medicine

MeSH Terms

Drug Resistant EpilepsyUnsupervised Machine LearningAdolescentAdultBrainElectroencephalographyEpilepsies, PartialFemaleHumansMaleMiddle AgedSeizuresYoung AdultConnectome

Keywords

IctalConnectomeStereoelectroencephalographyNeuroscienceEpilepsyElectroencephalographyPrincipal component analysisPsychologyMedicineComputer scienceFunctional connectivityArtificial intelligenceMachine LearningConnectomicsDrug-resistant Focal EpilepsyStereo ElectroencephalographyInterictal Suppression HypothesisMaleAdultDrug Resistant EpilepsyAdolescentBrainMiddle AgedYoung AdultSeizuresHumansOriginal ArticleFemaleEpilepsies, PartialUnsupervised Machine Learning

Sustainable Development Goals

SDG 0: Good health and well-being