Literature DB >> 20872095

Open database of epileptic EEG with MRI and postoperational assessment of foci--a real world verification for the EEG inverse solutions.

Piotr Zwoliński1, Marcin Roszkowski, Jaroslaw Zygierewicz, Stefan Haufe, Guido Nolte, Piotr J Durka.   

Abstract

This paper introduces a freely accessible database http://eeg.pl/epi , containing 23 datasets from patients diagnosed with and operated on for drug-resistant epilepsy. This was collected as part of the clinical routine at the Warsaw Memorial Child Hospital. Each record contains (1) pre-surgical electroencephalography (EEG) recording (10-20 system) with inter-ictal discharges marked separately by an expert, (2) a full set of magnetic resonance imaging (MRI) scans for calculations of the realistic forward models, (3) structural placement of the epileptogenic zone, recognized by electrocorticography (ECoG) and post-surgical results, plotted on pre-surgical MRI scans in transverse, sagittal and coronal projections, (4) brief clinical description of each case. The main goal of this project is evaluation of possible improvements of localization of epileptic foci from the surface EEG recordings. These datasets offer a unique possibility for evaluating different EEG inverse solutions. We present preliminary results from a subset of these cases, including comparison of different schemes for the EEG inverse solution and preprocessing. We report also a finding which relates to the selective parametrization of single waveforms by multivariate matching pursuit, which is used in the preprocessing for the inverse solutions. It seems to offer a possibility of tracing the spatial evolution of seizures in time.

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Year:  2010        PMID: 20872095      PMCID: PMC2974908          DOI: 10.1007/s12021-010-9086-6

Source DB:  PubMed          Journal:  Neuroinformatics        ISSN: 1539-2791


  20 in total

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Authors:  Piotr J Durka; Artur Matysiak; Eduardo Martínez Montes; Pedro Valdés Sosa; Katarzyna J Blinowska
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Review 5.  Interictal EEG and the diagnosis of epilepsy.

Authors:  Jyoti Pillai; Michael R Sperling
Journal:  Epilepsia       Date:  2006       Impact factor: 5.864

6.  Quantification of the benefit from integrating MEG and EEG data in minimum l2-norm estimation.

Authors:  A Molins; S M Stufflebeam; E N Brown; M S Hämäläinen
Journal:  Neuroimage       Date:  2008-06-14       Impact factor: 6.556

7.  A distributed spatio-temporal EEG/MEG inverse solver.

Authors:  Wanmei Ou; Matti S Hämäläinen; Polina Golland
Journal:  Neuroimage       Date:  2008-06-14       Impact factor: 6.556

Review 8.  Potential fields, EEG maps, and cortical spike generators.

Authors:  P K Wong
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1998-02

9.  Localization of brain electrical activity via linearly constrained minimum variance spatial filtering.

Authors:  B D Van Veen; W van Drongelen; M Yuchtman; A Suzuki
Journal:  IEEE Trans Biomed Eng       Date:  1997-09       Impact factor: 4.538

10.  Sixty years of clinical electroencephalography.

Authors:  K Karbowski
Journal:  Eur Neurol       Date:  1990       Impact factor: 1.710

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  4 in total

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Journal:  Neurol Sci       Date:  2021-02-23       Impact factor: 3.307

2.  Multivariate matching pursuit in optimal Gabor dictionaries: theory and software with interface for EEG/MEG via Svarog.

Authors:  Rafał Kuś; Piotr Tadeusz Różański; Piotr Jerzy Durka
Journal:  Biomed Eng Online       Date:  2013-09-23       Impact factor: 2.819

3.  Link Prediction Investigation of Dynamic Information Flow in Epilepsy.

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Journal:  J Healthc Eng       Date:  2018-07-02       Impact factor: 2.682

4.  The role of network connectivity on epileptiform activity.

Authors:  G Giacopelli; D Tegolo; M Migliore
Journal:  Sci Rep       Date:  2021-10-21       Impact factor: 4.379

  4 in total

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