Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress 2023 EHA Congress 2023 ASCO Annual Meeting
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
Brain Topography
Published in: Brain Topography 4/2018

01-07-2018 | Original Paper

Spatio-temporal Reconstruction of Neural Sources Using Indirect Dominant Mode Rejection

Authors: Alireza Talesh Jafadideh, Babak Mohammadzadeh Asl

Published in: Brain Topography | Issue 4/2018

Login to get access

Abstract

Adaptive minimum variance based beamformers (MVB) have been successfully applied to magnetoencephalogram (MEG) and electroencephalogram (EEG) data to localize brain activities. However, the performance of these beamformers falls down in situations where correlated or interference sources exist. To overcome this problem, we propose indirect dominant mode rejection (iDMR) beamformer application in brain source localization. This method by modifying measurement covariance matrix makes MVB applicable in source localization in the presence of correlated and interference sources. Numerical results on both EEG and MEG data demonstrate that presented approach accurately reconstructs time courses of active sources and localizes those sources with high spatial resolution. In addition, the results of real AEF data show the good performance of iDMR in empirical situations. Hence, iDMR can be reliably used for brain source localization especially when there are correlated and interference sources.
Footnotes
2
A point of the posterior root of the zygomatic arch lying immediately in front of the upper end of the tragus.
 
Literature
Baillet S, Mosher JC, Leahy RM (2001) Electromagnetic brain mapping. IEEE Signal Process Mag 18(6):14–30CrossRef
Berg P, Scherg M (1994) A fast method for forward computation of multiple-shell spherical head models. Electroencephalogr Clin Neurophysiol 90(1):58–64CrossRefPubMed
Brookes M, Stevenson C, Barnes G, Hillebrand A, Simpson M, Francis S, Morrisa P (2007) Beamformer reconstruction of correlated sources using a modified source model. Neuroimage 34(4):1454–1465CrossRefPubMed
Brookes MJ, Vrba J, Robinson SE, Stevenson CM, Peters AP, Barnes GR, Hillebrand A, Morris PG (2008) Optimising experimental design for MEG beamformer imaging. Neuroimage 39(4):1788–1802CrossRefPubMed
Chen YS, Cheng CY, Hsieh JC, Chen LF (2006) Maximum contrast beamformer for electromagnetic mapping of brain activity. IEEE Trans Biomed Eng 53(9):1765–1774CrossRefPubMed
Chowdhury RA, Younes Z, Tanguy H, Marcel H, Eliane K, Jean-Marc L, Christophe. G (2015) MEG–EEG information fusion and electromagnetic source imaging: from theory to clinical application in epilepsy. Brain Topogr 18(6):785–812CrossRef
Dai Y, Zhang W, Dickens DL, He B (2012) Source connectivity analysis from MEG and its application to epilepsy source localization. Brain Topogr 25(2):157–166CrossRefPubMed
Dinh C, Strohmeier D, Luessi M, Güllmar DG, Baumgarten D, Haueisen J, Hamalainen MS (2015) Real-time MEG source localization using regional clustering. Brain Topogr 28(6):771–784CrossRefPubMedPubMedCentral
Gorodnitsky J, George, Rao B (1995) Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm. Electroencephalogr Clin Neurophysiol 95(4)231–251CrossRefPubMed
Greenblatt RE, Ossadtchi A, Pflieger ME (2005) Local linear estimators for the bioelectromagnetic inverse problem. IEEE Trans Signal Process 53(9):3403–3412CrossRef
Huang M-X, Shih JJ, Lee RR, Harrington DL, Thoma RJ, Weisend MP, Hanlon F, Paulson KM, Li T, Martin K, Miller GA, Canive JM (2004) Commonalities and differences among vectorized beamformers in electromagnetic source imaging. Brain Topogr 16(3):139–158CrossRefPubMed
Hui HB, Pantazis D, Bressler SL, Leahy RM (2010) Identifying true cortical interactions in MEG using the nulling beamformer. Neuroimage 49(4):3161–3174CrossRefPubMed
Hyvärinen A, Karhunen J, Oja E (2004) Independent component analysis, vol 46. Wiley, New York
Jonmohamadi Y, Poudel G, Innes C, Weiss D, Krueger R, Jones R (2014) Comparison of beamformers for EEG source signal reconstruction. Biomed Signal Process Control 14:175–188CrossRef
Kimura T, Kako M, Kamiyama H, Ishiyama A, Kasai N, Watanabe Y (2007) Inverse solution for time-correlated multiple sources using Beamformer method, vol 1300. International Congress Series, pp 417–420
Mills T, Marc L, Sandra NM, Margot JT, Maher AQ (2012) Techniques for detection and localization of weak hippocampal and medial frontal sources using beamformers in MEG. Brain Topogr 25(3):248–263CrossRefPubMed
Moiseev A, Herdman AT (2013) Multi-core beamformers: derivation, limitations and improvements. Neuroimage 71:135–146CrossRefPubMed
Moiseev A, Gaspar JM, Schneider JA, Herdman AT (2011) Application of multi-source minimum variance beamformers for reconstruction of correlated neural activity. NeuroImage 58(2):481–496CrossRefPubMed
Mosher JC, Leahy RM (1992) Multiple dipole modeling and localization from spatiotemporal MEG data. IEEE Trans Biomed Eng 39(6):541–557CrossRefPubMed
Mosher JC, Leahy RM (1998) Recursive MUSIC: a framework for EEG and MEG source localization. IEEE Trans Biomed Eng 45(11):1342–1354CrossRefPubMed
Mosher JC, Leahy RM (1999) Source localization using recursively applied and projected (RAP) MUSIC. IEEE Trans Signal Process 47(2):332–340CrossRef
Pascual-Marqui RD (2002) Standardized low resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol 24:5–12PubMed
Popescu M, Popescu E, Chan T, Blunt S, Lewine J (2008) Spatial-temporal reconstruction of bilateral auditory steady state responses using MEG beamformers. IEEE Trans Biomed Eng 55(3):1092–1102CrossRefPubMed
Quraan M, Cheyne D (2010) Reconstruction of correlated brain activity with adaptive spatialfilters in MEG. NeuroImage 49(3):2387–2400CrossRefPubMed
Santos EL, Zoltowski MD, Rangaswamy M (2007) Indirect dominant mode rejection: a solution to low sample support beamforming. IEEE Trans Signal Process 55(7):3283–3293CrossRef
Sekihara K, Nagarajan SS (2008) Adaptive spatial filters for electromagnetic brain imaging. Springer, Berlin
Sekihara K, Nagarajan S, Poeppel D, Marantz A, Miyashita Y (2001) Reconstructing spatio-temporal activities of neural sources using an MEG Vector beamformer technique. IEEE Trans Biomed Eng 48(7):760–771CrossRefPubMed
Sekihara K, Nagarajan S, Poeppel D, Marantz A (2004) Asymptotic SNR of scalar and vector minimum-variance beamformers for neuromagnetic source reconstruction. IEEE Trans Biomed Eng 51(10):1726–1734CrossRefPubMedPubMedCentral
Shahbazi F, Ewald A, Nolte G (2015) Self-consistent MUSIC: an approach to the localization of true brain interactions from EEG/MEG data. Neuroimage 112(6):299–309CrossRefPubMed
Tikhonov AN, Arsenin VY (1997) Solutions of Ill-posed problems. Wiley, New York, NY
Uutela K, Hamalainen M, Somersalo E (1999) Visualization of magnetoencephalographic data using minimum current estimates. Neuroimage 10(2):173–180CrossRefPubMed
Van Veen B, van Drongelen W, Yuchtman M, Suzuki A (1997) Localization of brain electrical activity via linearly constrained minimum variance spatial filtering. IEEE Trans Biomed Eng 44(9):867–880CrossRefPubMed
Xiang Y, Peng D, Yang Z (2015) Blind source separation: dependent component analysis. Springer, New YorkCrossRef
Xu XL, Xu B, He B (2004) An alternative subspace approach to EEG dipole source localization. Phys Med Biol 49:327–343CrossRefPubMed
Yeung N, Bogacz R, Holroyd CB, Cohen JD (2004) Detection of synchronized oscillations in the electroencephalogram: an evaluation of methods. Psychophysiology 41(6)822–832CrossRefPubMed
Metadata
Title
Spatio-temporal Reconstruction of Neural Sources Using Indirect Dominant Mode Rejection
Authors
Alireza Talesh Jafadideh
Babak Mohammadzadeh Asl
Publication date
01-07-2018
Publisher
Springer US
Published in
Brain Topography / Issue 4/2018
Print ISSN: 0896-0267
Electronic ISSN: 1573-6792
DOI
https://doi.org/10.1007/s10548-018-0645-8

Other articles of this Issue 4/2018

Brain Topography 4/2018 Go to the issue

Original Paper

Movement-Related Somatosensory Activity Is Altered in Patients with Multiple Sclerosis

Original Paper

Alteration and Role of Interhemispheric and Intrahemispheric Connectivity in Motor Network After Stroke

Original Paper

Bridging the Gap Towards Awareness Detection in Disorders of Consciousness: An Experimental Study on the Mirror Neuron System

Original Paper

Localizing Event-Related Potentials Using Multi-source Minimum Variance Beamformers: A Validation Study

Review

Visualizing the Human Subcortex Using Ultra-high Field Magnetic Resonance Imaging

Original Paper

An Eye Fixation-Related Potential Study in Two Reading Tasks: Reading to Memorize and Reading to Make a Decision