Software for the analysis of magnetic encephalography data by the method of virtual electrodes

A new method of analyzing magnetic encephalography data, the virtual electrode method, was developed. According to magnetic encephalography data, a functional tomogram is constructed — the spatial distribution of field sources on a discrete grid. A functional tomogram displays on the head space the information contained in the multichannel time series of an encephalogram. This is achieved by solving the inverse problem for all elementary oscillations extracted using the Fourier transform. Each oscillation frequency corresponds to a three-dimensional grid node in which the source is located. The user sets the location, size and shape of the brain area for a detailed study of the frequency structure of a functional tomogram - a virtual electrode. The set of oscillations that fall into a given region represents the partial spectrum of this region. The time series of the encephalogram measured by the virtual electrode is restored using this spectrum. The method was applied to the analysis of magnetic encephalography data in two variations - a virtual electrode of a large radius and a point virtual electrode.

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Correlation of the Brain Compartments in the Attention Deficit and Hyperactivity Disorder Calculated by the Method of Virtual Electrodes from Magnetic Encephalography Data

Математическая биология и биоинформатика ◽

10.17537/2020.15.471 ◽

2020 ◽

Vol 15 (2) ◽

pp. 471-486

Author(s):

M.N. Ustinin ◽

A.I. Boyko ◽

S.D. Rykunov

Keyword(s):

Time Series ◽

Attention Deficit ◽

Spectral Power ◽

Spectral Band ◽

Problem Solution ◽

Hyperactivity Disorder ◽

Magnetic Encephalography ◽

Virtual Electrodes ◽

The Brain ◽

Virtual Electrode

New method to study the correlation of the human brain compartments based on the magnetic encephalography data analysis was proposed. The time series for the correlation analysis are generated by the method of virtual electrodes. First, the multichannel time series of the subject with confirmed attention deficit and hyperactivity disorder are transformed into the functional tomogram - spatial distribution of the magnetic field sources structure on the discrete grid. This structure is provided by the inverse problem solution for all elementary oscillations, found by the Fourier transform. Each frequency produces the elementary current dipole located in the node of the 3D grid. The virtual electrode includes the part of space, producing the activity under study. The time series for this activity is obtained by the summation of the spectral power of all sources, covered by the virtual electrode. To test the method, in this article we selected ten basic compartments of the brain, including frontal lobe, parietal lobe, occipital lobe and others. Each compartment was included in the virtual electrode, obtained from the subjects' MRI. We studied the correlation between compartments in the frequency bands, corresponding to four brain rhythms: theta, alpha, beta, and gamma. The time series for each electrode were calculated for the period of 300 seconds. The correlation coefficient between power series was calculated on the 1 second epoch and then averaged. The results were represented as matrices. The method can be used to study correlations of the arbitrary parts of the brain in any spectral band.

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Multi-Angular Electroretinography (maERG): Topographic mapping of the retinal function combining real and virtual electrodes

IEEE Transactions on Biomedical Engineering ◽

10.1109/tbme.2021.3075617 ◽

2021 ◽

pp. 1-1

Author(s):

Mercedes Gauthier ◽

Antoine Brassard-Simard ◽

Mathieu Gauvin ◽

Pierre Lachapelle ◽

Jean-Marc Lina

Keyword(s):

Retinal Function ◽

Topographic Mapping ◽

Virtual Electrodes

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Representations of the temporal envelope of sounds in human auditory cortex: Can the results from invasive intracortical “depth” electrode recordings be replicated using non-invasive MEG “virtual electrodes”?

NeuroImage ◽

10.1016/j.neuroimage.2012.09.017 ◽

2013 ◽

Vol 64 ◽

pp. 185-196 ◽

Cited By ~ 15

Author(s):

Rebecca E. Millman ◽

Garreth Prendergast ◽

Mark Hymers ◽

Gary G.R. Green

Keyword(s):

Auditory Cortex ◽

Temporal Envelope ◽

Non Invasive ◽

Depth Electrode ◽

Human Auditory Cortex ◽

Virtual Electrodes

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Estimation of the Directions of Alpha Rhythm Elementary Sources Using the Method of Human Brain Functional Tomography Based On the Magnetic Encephalography Data

Математическая биология и биоинформатика ◽

10.17537/2018.13.426 ◽

2018 ◽

Vol 13 (2) ◽

pp. 426-436 ◽

Cited By ~ 3

Author(s):

M.N. Ustinin ◽

S.D. Rykunov ◽

A.I. Boyko ◽

O.A. Maslova ◽

K.D. Walton ◽

...

Keyword(s):

Inverse Problem ◽

Time Series ◽

Human Brain ◽

Alpha Rhythm ◽

Brain Activity ◽

Problem Solution ◽

New York University ◽

Magnetic Encephalography ◽

The Brain ◽

Calculation Grid

New method for the magnetic encephalography data analysis was proposed. The method transforms multichannel time series into the spatial structure of the human brain activity. In this paper we further develop this method to determine the dominant direction of the electrical sources of brain activity at each node of the calculation grid. We have considered the experimental data, obtained with three 275-channel magnetic encephalographs in New York University, McGill University and Montreal University. The human alpha rhythm phenomenon was selected as a model object. Magnetic encephalograms of the brain spontaneous activity were registered for 5-7 minutes in magnetically shielded room. Detailed multichannel spectra were obtained by the Fourier transform of the whole time series. For all spectral components, the inverse problem was solved in elementary current dipole model and the functional structure of the brain activity was calculated in the frequency band 8-12 Hz. In order to estimate the local activity direction, at the each node of calculation grid the vector of the inverse problem solution was selected, having the maximal spectral power. So, the 3D-map of the brain activity vector field was produced – the directional functional tomogram. Such maps were generated for 15 subjects and some common patterns were revealed in the directions of the alpha rhythm elementary sources. The proposed method can be used to study the local properties of the brain activity in any spectral band and in any brain compartment.

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Development of an anatomically detailed MRI-derived rabbit ventricular model and assessment of its impact on simulations of electrophysiological function

AJP Heart and Circulatory Physiology ◽

10.1152/ajpheart.00606.2009 ◽

2010 ◽

Vol 298 (2) ◽

pp. H699-H718 ◽

Cited By ~ 122

Author(s):

Martin J. Bishop ◽

Gernot Plank ◽

Rebecca A. B. Burton ◽

Jürgen E. Schneider ◽

David J. Gavaghan ◽

...

Keyword(s):

Cardiac Function ◽

Complex Model ◽

Patient Specific ◽

Small Scale ◽

Data Simulation ◽

Simplified Models ◽

Anatomical Features ◽

Patient Specific Modeling ◽

Rule Based Approach ◽

Virtual Electrodes

Recent advances in magnetic resonance (MR) imaging technology have unveiled a wealth of information regarding cardiac histoanatomical complexity. However, methods to faithfully translate this level of fine-scale structural detail into computational whole ventricular models are still in their infancy, and, thus, the relevance of this additional complexity for simulations of cardiac function has yet to be elucidated. Here, we describe the development of a highly detailed finite-element computational model (resolution: ∼125 μm) of rabbit ventricles constructed from high-resolution MR data (raw data resolution: 43 × 43 × 36 μm), including the processes of segmentation (using a combination of level-set approaches), identification of relevant anatomical features, mesh generation, and myocyte orientation representation (using a rule-based approach). Full access is provided to the completed model and MR data. Simulation results were compared with those from a simplified model built from the same images but excluding finer anatomical features (vessels/endocardial structures). Initial simulations showed that the presence of trabeculations can provide shortcut paths for excitation, causing regional differences in activation after pacing between models. Endocardial structures gave rise to small-scale virtual electrodes upon the application of external field stimulation, which appeared to protect parts of the endocardium in the complex model from strong polarizations, whereas intramural virtual electrodes caused by blood vessels and extracellular cleft spaces appeared to reduce polarization of the epicardium. Postshock, these differences resulted in the genesis of new excitation wavefronts that were not observed in more simplified models. Furthermore, global differences in the stimulus recovery rates of apex/base regions were observed, causing differences in the ensuing arrhythmogenic episodes. In conclusion, structurally simplified models are well suited for a large range of cardiac modeling applications. However, important differences are seen when behavior at microscales is relevant, particularly when examining the effects of external electrical stimulation on tissue electrophysiology and arrhythmia induction. This highlights the utility of histoanatomically detailed models for investigations of cardiac function, in particular for future patient-specific modeling.

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