scholarly journals Study of Attention Deficit and Hyperactivity Disorder Using the Method of Functional Tomography Based On Magnetic Encephalography Data

2019 ◽  
Vol 14 (2) ◽  
pp. 517-532
Author(s):  
M.N. Ustinin ◽  
S.D. Rykunov ◽  
A.I. Boyko ◽  
O.A. Maslova ◽  
N.M. Pankratova
Keyword(s):  
Time Series ◽  
Frequency Band ◽  
Attention Deficit ◽  
Brain Activity ◽  
Current Dipole ◽  
Hyperactivity Disorder ◽  
Psychic Disorders ◽  
Magnetic Encephalography ◽  
Delta Rhythm ◽  
The Brain

New method for the magnetic encephalography data analysis was proposed, making it possible to transform multichannel time series into the spatial structure of the human brain activity. In this paper we applied this method to the analysis of magnetic encephalograms, obtained from subjects with attention deficit and hyperactivity disorder. We have considered the experimental data, obtained with 275-channel magnetic encephalographs in McGill University and Montreal University. Magnetic encephalograms of the brain spontaneous activity were registered for 5 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 broad frequency band 0.3-50 Hz. It was found that frequency band relations are different in different experiments. We proposed to use these relations by the summary electric power produced by the sources in selected frequency band. The delta rhythm in frequency band 0.3 to 4 Hz was studied in detail. It was found, that many delta rhythm dipoles were localized outside the brain, and their spectrum consists of the heartbeat harmonics. It was concluded that in experiments considered, the delta rhythm represents the vascular activity of the head. To study the spatial distribution of all rhythms from theta to gamma the partial spectra of the brain divisions were calculated. The partial spectrum includes all frequencies produced by the dipole sources located in the region of brain selected at the magnetic resonance image. The method can be further applied to study encephalograms in various psychic disorders.

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

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.

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

2018 ◽  
Vol 13 (2) ◽  
pp. 426-436 ◽  
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.

scholarly journals Reconstruction of the Human Brain Functional Structure Based on the Electroencephalography Data

2020 ◽  
Vol 15 (1) ◽  
pp. 106-117 ◽  
Author(s):  
M.N. Ustinin ◽  
S.D. Rykunov ◽  
A.I. Boyko ◽  
O.A. Maslova
Keyword(s):  
Inverse Problem ◽  
Time Series ◽  
Alpha Rhythm ◽  
Brain Activity ◽  
Spectral Band ◽  
Field Measurements ◽  
Functional Structure ◽  
Current Dipole ◽  
Eyes Closed ◽  
The Brain

New method for the data analysis was proposed, making it possible to transform multichannel time series into the spatial structure of the system under study. The method was successfully used to investigate biological and physical objects based on the magnetic field measurements. In this paper we further develop this method to analyze the data of the experiments where the electric field is measured. The brain activity in the state of subject “eyes closed” was registered by the 19-channel electric encephalograph, using the 10-20 scheme. The electroencephalograms were obtained in resting state and with arbitrary hands motions. Detailed multichannel spectra were obtained by the Fourier transform of the whole time series. All spectral data revealed the broad alpha rhythm peak in the frequency band 9-12 Hz. For all spectral components in this band the inverse problem was solved, and the 3D map of the brain activity was calculated. The inverse problem was solved in elementary current dipole model for one-layer spherical conductor without any restrictions for the source position. The combined analysis of the magnetic resonance image and the brain functional structure leads to the conclusion that this structure generally corresponds to the modern knowledge about the alpha rhythm. The 3D map of the vector field of the dominating directions of the alpha rhythm sources was also generated. The proposed method can be used to study the spatial distribution of the brain activity in any spectral band of the electroencephalography data.

scholarly journals Topological Data Analysis reveals robust alterations in the whole-brain and frontal lobe functional connectomes in Attention-Deficit/Hyperactivity Disorder

2019 ◽  
Author(s):  
Zeus Gracia-Tabuenca ◽  
Juan Carlos Díaz-Patiño ◽  
Isaac Arelio ◽  
Sarael Alcauter
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Data Analysis ◽  
Frontal Lobe ◽  
Attention Deficit ◽  
Brain Network ◽  
Topological Data Analysis ◽  
Hyperactivity Disorder ◽  
The Brain ◽  
Connectivity Threshold ◽  
Topological Data

AbstractThe functional organization of the brain network (connectome) has been widely studied as a graph; however, methodological issues may affect the results, such as the brain parcellation scheme or the selection of a proper threshold value. Instead of exploring the brain in terms of a static connectivity threshold, this work explores its algebraic topology as a function of the filtration value (i.e., the connectivity threshold), a process termed the Rips filtration in Topological Data Analysis. Specifically, we characterized the transition from all nodes being isolated to being connected into a single component as a function of the filtration value, in a public dataset of children with attention-deficit/hyperactivity disorder (ADHD) and typically developing children. Results were highly congruent when using four different brain segmentations (atlases), and exhibited significant differences for the brain topology of children with ADHD, both at the whole brain network and at the functional sub-network levels, particularly involving the frontal lobe and the default mode network. Therefore, this approach may contribute to identify the neurophysio-pathology of ADHD, reducing the bias of connectomics-related methods.HighlightsTopological Data Analysis was implemented in functional connectomes.Betti curves were assessed based on the area under the curve, slope and kurtosis.The explored variables were robust along four different brain atlases.ADHD showed lower areas, suggesting decreased functional segregation.Frontal and default mode networks showed the greatest differences between groups.Graphical Abstract

scholarly journals VirtEl - Software for Magnetic Encephalography Data Analysis by the Method of Virtual Electrodes

2019 ◽  
Vol 14 (1) ◽  
pp. 340-354 ◽  
Author(s):  
S.D. Rykunov ◽  
E.D. Rykunova ◽  
A.I. Boyko ◽  
M.N. Ustinin
Keyword(s):  
Time Series ◽  
Brain Area ◽  
Three Dimensional ◽  
Large Radius ◽  
Magnetic Encephalography ◽  
Electrode Method ◽  
The Fourier Transform ◽  
Virtual Electrodes ◽  
The Brain ◽  
Virtual Electrode

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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