EEG-based brain source localization using visual stimuli

Munsif Ali Jatoi, Nidal Kamel, Aamir Saeed Malik, Ibrahima Faye, Jose M. Bornot, Tahamina Begum

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low-resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.

LanguageEnglish
Pages55-64
Number of pages10
JournalInternational Journal of Imaging Systems and Technology
Volume26
Issue number1
DOIs
Publication statusPublished - 1 Mar 2016

Fingerprint

Electroencephalography
Brain
Finite difference method
Tomography
Magnetic resonance imaging
Signal processing
Current density
Imaging techniques

Keywords

  • brain activation
  • EEG
  • finite difference method
  • LORETA
  • MRI
  • sLORETA
  • source localization

Cite this

Jatoi, Munsif Ali ; Kamel, Nidal ; Malik, Aamir Saeed ; Faye, Ibrahima ; Bornot, Jose M. ; Begum, Tahamina. / EEG-based brain source localization using visual stimuli. In: International Journal of Imaging Systems and Technology. 2016 ; Vol. 26, No. 1. pp. 55-64.
@article{5b878c01d2a14bc893e57e45705bc539,
title = "EEG-based brain source localization using visual stimuli",
abstract = "Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low-resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.",
keywords = "brain activation, EEG, finite difference method, LORETA, MRI, sLORETA, source localization",
author = "Jatoi, {Munsif Ali} and Nidal Kamel and Malik, {Aamir Saeed} and Ibrahima Faye and Bornot, {Jose M.} and Tahamina Begum",
year = "2016",
month = "3",
day = "1",
doi = "10.1002/ima.22157",
language = "English",
volume = "26",
pages = "55--64",
journal = "International Journal of Imaging Systems and Technology",
issn = "0899-9457",
number = "1",

}

EEG-based brain source localization using visual stimuli. / Jatoi, Munsif Ali; Kamel, Nidal; Malik, Aamir Saeed; Faye, Ibrahima; Bornot, Jose M.; Begum, Tahamina.

In: International Journal of Imaging Systems and Technology, Vol. 26, No. 1, 01.03.2016, p. 55-64.

Research output: Contribution to journalArticle

TY - JOUR

T1 - EEG-based brain source localization using visual stimuli

AU - Jatoi, Munsif Ali

AU - Kamel, Nidal

AU - Malik, Aamir Saeed

AU - Faye, Ibrahima

AU - Bornot, Jose M.

AU - Begum, Tahamina

PY - 2016/3/1

Y1 - 2016/3/1

N2 - Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low-resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.

AB - Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low-resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.

KW - brain activation

KW - EEG

KW - finite difference method

KW - LORETA

KW - MRI

KW - sLORETA

KW - source localization

UR - http://www.scopus.com/inward/record.url?scp=84962809029&partnerID=8YFLogxK

U2 - 10.1002/ima.22157

DO - 10.1002/ima.22157

M3 - Article

VL - 26

SP - 55

EP - 64

JO - International Journal of Imaging Systems and Technology

T2 - International Journal of Imaging Systems and Technology

JF - International Journal of Imaging Systems and Technology

SN - 0899-9457

IS - 1

ER -