Spatial distribution of non-linear interdependency measures for focal hemisphere identification in epileptic patients from interictal intracranial EEG

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1471-2202

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Spatial distribution of non-linear interdependency measures for focal hemisphere identification in epileptic patients from interictal intracranial EEG ; volume:10 ; number:1 ; day:13 ; month:7 ; year:2009 ; pages:1-2 ; date:9.2009
BMC neuroscience ; 10, Heft 1 (13.7.2009), 1-2, 9.2009

Creator: Pannunzi, Mario

Contributor: Ferraina, Stefano
Del Giudice, Paolo
SpringerLink (Online service)

DOI: 10.1186/1471-2202-10-S1-P81

URN: urn:nbn:de:1111-2016032142

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:51 AM CEST

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Pannunzi, Mario
Ferraina, Stefano
Del Giudice, Paolo
SpringerLink (Online service)

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Spatial distribution of non-linear interdependency measures for focal hemisphere identification in epileptic patients from interictal intracranial EEG

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Other Objects (12)

Functional and effective connectivity during focal epileptic seizures [Poster]

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A multi-context learning approach for EEG epileptic seizure detection

Detecting epileptic seizures with multimodal non-EEG data from wearables

Epileptic seizure detection from EEG signals using logistic model trees

Focused ultrasound-mediated suppression of chemically-induced acute epileptic EEG activity

Validating EEG source imaging using intracranial electrical stimulation

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection

Stable high frequency background EEG activity distinguishes epileptic from healthy brain regions

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Adaptive Filtering for Epileptic Event Detection in the EEG

EPIC: Annotated epileptic EEG independent components for artifact reduction

Hemisphere specific EEG related to alternate nostril yoga breathing

Asymmetric hemisphere activation in tenderness: evidence from EEG signals

A multi-context learning approach for EEG epileptic seizure detection

Detecting epileptic seizures with multimodal non-EEG data from wearables

Epileptic seizure detection from EEG signals using logistic model trees

Focused ultrasound-mediated suppression of chemically-induced acute epileptic EEG activity

Validating EEG source imaging using intracranial electrical stimulation

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection

Stable high frequency background EEG activity distinguishes epileptic from healthy brain regions

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Focused ultrasound-mediated suppression of chemically-induced acute epileptic EEG activity

Validating EEG source imaging using intracranial electrical stimulation

Improved epileptic seizure detection combining dynamic feature normalization with EEG novelty detection

Stable high frequency background EEG activity distinguishes epileptic from healthy brain regions

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