EEG based brain source localization comparison of sLORETA and eLORETA

Abstract Human brain generates electromagnetic signals during certain activation inside the brain. The localization of the active sources which are responsible for such activation is termed as brain source localization. This process of source estimation with the help of EEG which is also known as EEG inverse problem is helpful to understand physiological, pathological, mental, functional abnormalities and cognitive behaviour of the brain. This understanding leads for the specification for diagnoses of various brain disorders such as epilepsy and tumour. Different approaches are devised to exactly localize the active sources with minimum localization error, less complexity and more validation which include minimum norm, low resolution brain electromagnetic tomography (LORETA), standardized LORETA, exact LORETA, Multiple Signal classifier, focal under determined system solution etc. This paper discusses and compares the ability of localizing the sources for two low resolution methods i.e., sLORETA and eLORETA respectively. The ERP data with visual stimulus is used for comparison at four different time instants for both methods (sLORETA and eLORETA) and then corresponding activation in terms of scalp map, slice view and cortex map is discussed.

[1]  E. Halgren,et al.  Dynamic Statistical Parametric Mapping Combining fMRI and MEG for High-Resolution Imaging of Cortical Activity , 2000, Neuron.

[2]  F. L. D. Silva,et al.  EEG signal processing , 2000, Clinical Neurophysiology.

[3]  Mario Tudor,et al.  [Hans Berger (1873-1941)--the history of electroencephalography]. , 2005, Acta medica Croatica : casopis Hravatske akademije medicinskih znanosti.

[4]  Richard M. Leahy,et al.  Source localization using recursively applied and projected (RAP) MUSIC , 1997 .

[5]  Roberto D. Pascual-Marqui,et al.  Discrete, 3D distributed, linear imaging methods of electric neuronal activity. Part 1: exact, zero error localization , 2007, 0710.3341.

[6]  Albert Tarantola,et al.  Inverse problem theory - and methods for model parameter estimation , 2004 .

[7]  Fusheng Yang,et al.  Shrinking LORETA-FOCUSS: a recursive approach to estimating high spatial resolution electrical activity in the brain , 2003, First International IEEE EMBS Conference on Neural Engineering, 2003. Conference Proceedings..

[8]  Aamir Saeed Malik,et al.  Reference-free reduction of ballistocardiogram artifact from EEG data using EMD-PCA , 2014, 2014 5th International Conference on Intelligent and Advanced Systems (ICIAS).

[9]  L. Zhukov,et al.  Independent component analysis for EEG source localization , 2000, IEEE Engineering in Medicine and Biology Magazine.

[10]  R D Pascual-Marqui,et al.  Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. , 2002, Methods and findings in experimental and clinical pharmacology.

[11]  J.C. Mosher,et al.  Recursive MUSIC: A framework for EEG and MEG source localization , 1998, IEEE Transactions on Biomedical Engineering.

[12]  A. Ben Hamida,et al.  New hybrid method for the 3D reconstruction of neuronal activity in the brain , 2008, 2008 15th International Conference on Systems, Signals and Image Processing.

[13]  N. Badruddin,et al.  Automatic eye-blink artifact removal method based on EMD-CCA , 2013, 2013 ICME International Conference on Complex Medical Engineering.

[14]  N. Thakor,et al.  Quantitative EEG analysis methods and clinical applications , 2009 .

[15]  C.Y. Song,et al.  Hybrid Weighted Minimum Norm Method A new method based LORETA to solve EEG inverse problem , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[16]  Aamir Saeed Malik,et al.  A survey of methods used for source localization using EEG signals , 2014, Biomed. Signal Process. Control..

[17]  Bart Vanrumste,et al.  EEG/MEG Source Imaging: Methods, Challenges, and Open Issues , 2009, Comput. Intell. Neurosci..

[18]  I F Gorodnitsky,et al.  Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. , 1995, Electroencephalography and clinical neurophysiology.

[19]  Aamir Saeed Malik,et al.  Representing EEG source localization using Finite Element Method , 2013, 2013 IEEE International Conference on Control System, Computing and Engineering.

[20]  Aamir Saeed Malik,et al.  Reduction of Ballistocardiogram Artifact Using EMD-AF , 2013, ICONIP.