Literature DB >> 10426404

Deblurring.

A Gevins1, J Le, H Leong, L K McEvoy, M E Smith.   

Abstract

In most instances, traditional EEG methodology provides insufficient spatial detail to identify relationships between brain electrical events and structures and functions visualized by magnetic resonance imaging or positron emission tomography. This article describes a method called Deblurring for increasing the spatial detail of the EEG and for fusing neurophysiologic and neuroanatomic data. Deblurring estimates potentials near the outer convexity of the cortex using a realistic finite element model of the structure of a subject's head determined from their magnetic resonance images. Deblurring is not a source localization technique and thus makes no assumptions about the number or type of generator sources. The validity of Deblurring has been initially tested by comparing deblurred data with potentials measured with subdural grid recordings. Results suggest that deblurred topographic maps, registered with a subject's magnetic resonance imaging and rendered in three dimensions, provide better spatial detail than has heretofore been obtained with scalp EEG recordings. Example results are presented from research studies of somatosensory stimulation, movement, language, attention and working memory. Deblurred ictal EEG data are also presented, indicating that this technique may have future clinical application as an aid to seizure localization and surgical planning.

Entities:  

Keywords:  NASA Discipline Neuroscience; Non-NASA Center

Mesh:

Year:  1999        PMID: 10426404     DOI: 10.1097/00004691-199905000-00002

Source DB:  PubMed          Journal:  J Clin Neurophysiol        ISSN: 0736-0258            Impact factor:   2.177


  9 in total

1.  Integrated volume visualization of functional image data and anatomical surfaces using normal fusion.

Authors:  R Stokking; K J Zuiderveld; M A Viergever
Journal:  Hum Brain Mapp       Date:  2001-04       Impact factor: 5.038

2.  High-resolution electro-encephalogram: source estimates of Laplacian-transformed somatosensory-evoked potentials using a realistic subject head model constructed from magnetic resonance images.

Authors:  F Babiloni; C Babiloni; L Locche; F Cincotti; P M Rossini; F Carducci
Journal:  Med Biol Eng Comput       Date:  2000-09       Impact factor: 2.602

3.  Linear inverse source estimate of combined EEG and MEG data related to voluntary movements.

Authors:  F Babiloni; F Carducci; F Cincotti; C Del Gratta; V Pizzella; G L Romani; P M Rossini; F Tecchio; C Babiloni
Journal:  Hum Brain Mapp       Date:  2001-12       Impact factor: 5.038

Review 4.  Issues and considerations for using the scalp surface Laplacian in EEG/ERP research: A tutorial review.

Authors:  Jürgen Kayser; Craig E Tenke
Journal:  Int J Psychophysiol       Date:  2015-04-25       Impact factor: 2.997

5.  Comparison of different cortical connectivity estimators for high-resolution EEG recordings.

Authors:  Laura Astolfi; Febo Cincotti; Donatella Mattia; M Grazia Marciani; Luiz A Baccala; Fabrizio de Vico Fallani; Serenella Salinari; Mauro Ursino; Melissa Zavaglia; Lei Ding; J Christopher Edgar; Gregory A Miller; Bin He; Fabio Babiloni
Journal:  Hum Brain Mapp       Date:  2007-02       Impact factor: 5.038

6.  Neurophysiological pharmacodynamic measures of groups and individuals extended from simple cognitive tasks to more "lifelike" activities.

Authors:  Alan Gevins; Cynthia S Chan; An Jiang; Lita Sam-Vargas
Journal:  Clin Neurophysiol       Date:  2012-11-26       Impact factor: 3.708

7.  Changes in scalp potentials and spatial smoothing effects of inclusion of dura layer in human head models for EEG simulations.

Authors:  Ceon Ramon; Paolo Garguilo; Egill A Fridgeirsson; Jens Haueisen
Journal:  Front Neuroeng       Date:  2014-08-05

8.  Taking the EEG Back Into the Brain: The Power of Multiple Discrete Sources.

Authors:  Michael Scherg; Patrick Berg; Nobukazu Nakasato; Sándor Beniczky
Journal:  Front Neurol       Date:  2019-08-20       Impact factor: 4.003

9.  EEG/MEG source imaging: methods, challenges, and open issues.

Authors:  Katrina Wendel; Outi Väisänen; Jaakko Malmivuo; Nevzat G Gencer; Bart Vanrumste; Piotr Durka; Ratko Magjarević; Selma Supek; Mihail Lucian Pascu; Hugues Fontenelle; Rolando Grave de Peralta Menendez
Journal:  Comput Intell Neurosci       Date:  2009-07-20
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.