A simple method for calculating the depth of EEG sources using minimum norm estimates (MNE)

Pinto, Bruno; Quintão, Carla

doi:10.1007/s11517-007-0204-z

Cited by 6 publications

(7 citation statements)

References 23 publications

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“…The head model was computed through the use of OpenMEEG (Gramfort, Papadopoulo, Olivi, & Clerc 2010) based on the EEG cap that was used. The source of the brain electrical signal was reconstructed by applying the Minimum Norm Method (wMNE; output mode: Kernel; Pinto & Silva 2007). The source orientation was unconstrained, meaning that each vertex of the cortex surface contained three dipoles with orthogonal directions.…”

Section: Methodsmentioning

confidence: 99%

Effects of auditory distraction on voluntary movements: exploring the underlying mechanisms associated with parallel processing

Bigliassi

Karageorghis

Nowicky

et al. 2017

Psychological Research

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Highly demanding cognitive-motor tasks can be negatively influenced by the presence of auditory stimuli. The human brain attempts to partially suppress the processing of potential distractors in order that motor tasks can be completed successfully. The present study sought to further understand the attentional neural systems that activate in response to potential distractors during the execution of movements. Nineteen participants (9 women and 10 men) were administered isometric ankle-dorsiflexion tasks for 10 s at a light intensity. Electroencephalography was used to assess the electrical activity in the brain, and a music excerpt was used to distract participants. Three conditions were administered: auditory distraction during the execution of movement (auditory distraction; AD), movement execution in the absence of auditory distraction (control; CO), and auditory distraction in the absence of movement (stimulus-only; SO). AD was compared with SO to identify the mechanisms underlying the attentional processing associated with attentional shifts from internal association (task-related) to external (task-unrelated) sensory cues. The results of the present study indicated that the EMG amplitude was not compromised when the auditory stimulus was administered. Accordingly, EEG activity was upregulated at 0.368 s in AD when compared to SO. Source reconstruction analysis indicated that right and central parietal regions of the cortex activated at 0.368 s in order to reduce the processing of task-irrelevant stimuli during the execution of movements. The brain mechanisms that underlie the control of potential distractors during exercise were possibly associated with the activity of the frontoparietal network.

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Section: Methodsmentioning

confidence: 99%

Effects of auditory distraction on voluntary movements: exploring the underlying mechanisms associated with parallel processing

Bigliassi

Karageorghis

Nowicky

et al. 2017

Psychological Research

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“…9 Various methods have been proposed for choosing suitable constraints for the inverse EEG problem, the most wellknown being the minimum norm (MN) constraint. [10][11][12] Techniques relying on the MN constraint are based on a search for the solution with minimum power, along with regularization. 8 In other words, when the system is underdetermined, the solution is obtained by minimizing the l 2 -norm of the solution components.…”

Section: Introductionmentioning

confidence: 99%

“…Various methods have been proposed for choosing suitable constraints for the inverse EEG problem, the most well‐known being the minimum norm (MN) constraint . Techniques relying on the MN constraint are based on a search for the solution with minimum power, along with regularization .…”

Section: Introductionmentioning

confidence: 99%

EEG source localization using a sparsity prior based onBrodmann areas

Saha

Nesterets

Rana

et al. 2017

Int J Imaging Syst Tech

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Localizing the sources of electrical activity in the brain from electroencephalographic (EEG) data is an important tool for noninvasive study of brain dynamics. Generally, the source localization process involves a high‐dimensional inverse problem that has an infinite number of solutions and thus requires additional constraints to be considered to have a unique solution. In this article, we propose a novel method for EEG source localization. The proposed method is based on dividing the cerebral cortex of the brain into a finite number of “functional zones” which correspond to unitary functional areas in the brain. To specify the sparsity profile of human brain activity more concisely, the proposed approach considers grouping of the electrical current dipoles inside each of the functional zones. In this article, we investigate the use of Brodmann's areas as the functional zones while sparse Bayesian learning is used to perform sparse approximation. Numerical experiments are conducted on a realistic head model obtained from segmentation of MRI images of the head and includes four major compartments namely scalp, skull, cerebrospinal fluid (CSF), and brain with relative conductivity values. Three different electrode setups are tested in the numerical experiments. The results demonstrate that the proposed approach is quite promising in solving the EEG source localization problem. In a noiseless environment with 71 electrodes, the proposed method was found to accurately locate up to 6 simultaneously active sources with accuracy >70%.

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“…Minimum norm methods have e. g. been used to reconstruct pipeline defects in nondestructive testing [13]. They have also been widely applied in the reconstruction of current sources from EEG and MEG measurements of the human brain and MCG measurements of the human heart [11,18,20].…”

Section: Introductionmentioning

confidence: 99%

Magnetic nanoparticle imaging by means of minimum norm estimates from remanence measurements

Baumgarten

Liehr

Wiekhorst

et al. 2008

Med Biol Eng Comput

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In magnetic nanoparticle imaging, magnetic nanoparticles are coated and functionalized to bind to specific targets. After measuring their magnetic relaxation or remanence, their distribution can be determined by means of inverse methods. The reconstruction algorithm presented in this paper includes first a dipole fit using a Levenberg-Marquardt optimizer to determine the reconstruction plane. Secondly, a minimum norm estimate is obtained on a regular grid placed in that plane. Computer simulations involving different parameter sets and conditions show that the used approach allows for the reconstruction of distributed sources, although the reconstructed shapes are distorted by blurring effects. The reconstruction quality depends on the signal-to-noise ratio of the measurements and decreases with larger sensor-source distances and higher grid spacings. In phantom measurements, the magnetic remanence of nanoparticle columns with clinical relevant sizes is determined with two common measurement systems. The reconstructions from these measurements indicate that the approach is applicable for clinical measurements. Our results provide parameter sets for successful application of minimum norm approaches to Magnetic Nanoparticle Imaging.

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A simple method for calculating the depth of EEG sources using minimum norm estimates (MNE)

Cited by 6 publications

References 23 publications

Effects of auditory distraction on voluntary movements: exploring the underlying mechanisms associated with parallel processing

Effects of auditory distraction on voluntary movements: exploring the underlying mechanisms associated with parallel processing

EEG source localization using a sparsity prior based onBrodmann areas

Magnetic nanoparticle imaging by means of minimum norm estimates from remanence measurements

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