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 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 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 The Localization of Activity Sources in a Three-Dimensional Model of the Human Brain Using the Joint Analysis of EEG / sMRI Data

2019 ◽  
Vol 17 (3) ◽  
pp. 18-28
Author(s):  
E. Bykova ◽  
A. Savostyanov
Keyword(s):  
Inverse Problem ◽  
Brain Activity ◽  
Three Dimensional ◽  
Human Head ◽  
Joint Analysis ◽  
Dimensional Model ◽  
Three Dimensional Model ◽  
Use Of Data ◽  
The Individual ◽  
The Brain

Despite the large number of existing methods of the diagnosis of the brain, brain remains the least studied part of the human body. Electroencephalography (EEG) is one of the most popular methods of studying of brain activity due to its relative cheapness, harmless, and mobility of equipment. While analyzing the EEG data of the brain, the problem of solving of the inverse problem of electroencephalography, the localization of the sources of electrical activity of the brain, arises. This problem can be formulated as follows: according to the signals recorded on the surface of the head, it is necessary to determine the location of sources of these signals in the brain. The purpose of my research is to develop a software system for localization of brain activity sources based on the joint analysis of EEG and sMRI data. There are various approaches to solving of the inverse problem of EEG. To obtain the most exact results, some of them involve the use of data on the individual anatomy of the human head – structural magnetic resonance imaging (sMRI data). In this paper, one of these approaches is supposed to be used – Electromagnetic Spatiotemporal Independent Component Analysis (EMSICA) proposed by A. Tsai. The article describes the main stages of the system, such as preprocessing of the initial data; the calculation of the special matrix of the EMSICA approach, the values of which show the level of activity of a certain part of the brain; visualization of brain activity sources on its three-dimensional model.

scholarly journals Recording brain activities in unshielded Earth’s field with optically pumped atomic magnetometers

2020 ◽  
Vol 6 (24) ◽  
pp. eaba8792 ◽  
Author(s):  
Rui Zhang ◽  
Wei Xiao ◽  
Yudong Ding ◽  
Yulong Feng ◽  
Xiang Peng ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Medical Diagnosis ◽  
Alpha Rhythm ◽  
Brain Activity ◽  
High Sensitivity ◽  
Noninvasive Method ◽  
Optically Pumped ◽  
Field Noise ◽  
The Relationship ◽  
The Brain

Understanding the relationship between brain activity and specific mental function is important for medical diagnosis of brain symptoms, such as epilepsy. Magnetoencephalography (MEG), which uses an array of high-sensitivity magnetometers to record magnetic field signals generated from neural currents occurring naturally in the brain, is a noninvasive method for locating the brain activities. The MEG is normally performed in a magnetically shielded room. Here, we introduce an unshielded MEG system based on optically pumped atomic magnetometers. We build an atomic magnetic gradiometer, together with feedback methods, to reduce the environment magnetic field noise. We successfully observe the alpha rhythm signals related to closed eyes and clear auditory evoked field signals in unshielded Earth’s field. Combined with improvements in the miniaturization of the atomic magnetometer, our method is promising to realize a practical wearable and movable unshielded MEG system and bring new insights into medical diagnosis of brain symptoms.

scholarly journals Fronto-Temporal Analysis of EEG Signals of Patients with Depression: Characterisation, Nonlinear Dynamics and Surrogate Analysis

2020 ◽  
Author(s):  
Subha D. Puthankattil
Keyword(s):  
Time Series ◽  
Unipolar Depression ◽  
Temporal Analysis ◽  
Mental States ◽  
Eeg Signals ◽  
Biosignal Analysis ◽  
Eyes Closed ◽  
Eyes Open ◽  
Eeg Recordings ◽  
The Brain

The recent advances in signal processing techniques have enabled the analysis of biosignals from brain so as to enhance the predictive capability of mental states. Biosignal analysis has been successfully used to characterise EEG signals of unipolar depression patients. Methods of characterisation of EEG signals and the use of nonlinear parameters are the major highlights of this chapter. Bipolar frontopolar-temporal EEG recordings obtained under eyes open and eyes closed conditions are used for the analysis. A discussion on the reliability of the use of energy distribution and Relative Wavelet Energy calculations for distinguishing unipolar depression patients from healthy controls is presented. The potential of the application of Wavelet Entropy to differentiate states of the brain under normal and pathologic condition is introduced. Details are given on the suitability of ascertaining certain nonlinear indices on the feature extraction, assuming the time series to be highly nonlinear. The assumption of nonlinearity of the measured EEG time series is further verified using surrogate analysis. The studies discussed in this chapter indicate lower values of nonlinear measures for patients. The higher values of signal energy associated with the delta bands of depression patients in the lower frequency range are regarded as a major characteristic indicative of a state of depression. The chapter concludes by presenting the important results in this direction that may lead to better insight on the brain activity and cognitive processes. These measures are hence posited to be potential biomarkers for the detection of depression.

scholarly journals A Software Package for the Modeling of Electrophysiological Activity Data

2022 ◽  
Vol 17 (1) ◽  
pp. 1-10
Author(s):  
A.I. Boyko ◽  
S.D. Rykunov ◽  
M.N. Ustinin
Keyword(s):  
Time Series ◽  
Time Dependence ◽  
Software Package ◽  
Dipole Model ◽  
Input Output ◽  
Equivalent Current Dipole ◽  
Current Dipole ◽  
Output Module ◽  
Calculation Module ◽  
The Brain

A complex of programs has been developed for computer modeling of multichannel time series recorded in various experiments on electromagnetic fields created by the human body. Sets of coordinates and directions of sensors for magnetic encephalographs of several types, electroencephalographs and magnetic cardiographs are used as models of devices. To study the human brain, magnetic resonance tomograms are used as head models; to study the heart, a body model in the form of a half-space with a flat boundary is used. The sources are placed in the model space, for them the direct problem is solved in the physical model corresponding to the device used. For a magnetic encephalograph and an electroencephalograph, an equivalent current dipole model in a spherical conductor is used, for a magnetic cardiograph, an equivalent current dipole model in a flat conductor or a magnetic dipole model is used. For each source, a time dependence is set and a multichannel time series is calculated. Then the time series from all sources are summed and the noise component is added. The program consists of three modules: an input-output module, a calculation module and a visualization module. The input-output module is responsible for loading device models, brain models, and field source parameters. The calculation module is responsible for directly calculating the field and transforming coordinates between the index system and the head system. The visualization module is responsible for the image of the brain model, the position of the field sources, a graphical representation of the amplitude-time dependence of the field sources and the calculated values of the total field. The user interface has been developed. The software package provides: interactive placement of field sources in the head or body space and editing of the amplitude-time dependence; batch loading of a large number of sources; noise modeling; simulation of low-channel planar magnetometers of various orders, specifying the shape of the device, the number of sensors and their parameters. Magnetic and electric fields produced by sources in the brain areas responsible for processing speech stimuli are considered. The resulting multichannel signal can be used to test various data analysis methods and for the experiment planning.

scholarly journals Assessment of changes in the electrical activity of the brain during general anesthesia using portable electroencephalography

2020 ◽  
Vol 49 (2) ◽  
Author(s):  
Verónica Gaviria García ◽  
Daniel Loaiza López ◽  
Carolina Serna Rojas ◽  
Sara Ríos Arismendy ◽  
Eduardo Montoya Guevara ◽  
...  
Keyword(s):  
Electrical Activity ◽  
General Anesthesia ◽  
Brain Activity ◽  
Low Cost ◽  
Conscious State ◽  
Depth Of Anesthesia ◽  
Cross Sectional ◽  
Eyes Closed ◽  
Eeg Recordings ◽  
The Brain

Introduction: The analysis of the electrical activity of the brain using scalp electrodes with electroencephalography (EEG) could reveal the depth of anesthesia of a patient during surgery. However, conventional EEG equipment, due to its price and size, are not a practical option for the operating room and the commercial units used in surgery do not provide access to the electrical activity. The availability of low-cost portable technologies could provide for further research on the brain activity under general anesthesia and facilitate our quest for new markers of depth of anesthesia. Objective: To assess the capabilities of a portable EEG technology to capture brain rhythms associated with the state of consciousness and the general anesthesia status of surgical patients anesthetized with propofol. Methods: Observational, cross-sectional trial that reviewed 10 EEG recordings captured using OpenBCI portable low-cost technology, in female patients undergoing general anesthesia with propofol. The signal from the frontal electrodes was analyzed with spectral analysis and the results were compared against the reports in the literature. Results: The signal captured with frontal electrodes, particularly α rhythm, enabled the distinction between resting with eyes closed and with eyes opened in a conscious state, and sustained anesthesia during surgery. Conclusions: It is possible to differentiate a resting state from sustained anesthesia, replicating previous findings with conventional technologies. These results pave the way to the use of portable technologies such as the OpenBCI tool, to explore the brain dynamics during anesthesia.

scholarly journals Localizing Brain Activity from Multiple Distinct Sources via EEG

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
George Dassios ◽  
Michael Doschoris ◽  
Konstantia Satrazemi
Keyword(s):  
Inverse Problem ◽  
Surface Potential ◽  
Brain Activity ◽  
Sufficient Conditions ◽  
Measured Data ◽  
Single Dipole ◽  
Eeg Data ◽  
Necessary And Sufficient ◽  
Spherical Conductor ◽  
The Brain

An important question arousing in the framework of electroencephalography (EEG) is the possibility to recognize, by means of a recorded surface potential, the number of activated areas in the brain. In the present paper, employing a homogeneous spherical conductor serving as an approximation of the brain, we provide a criterion which determines whether the measured surface potential is evoked by a single or multiple localized neuronal excitations. We show that the uniqueness of the inverse problem for a single dipole is closely connected with attaining certain relations connecting the measured data. Further, we present the necessary and sufficient conditions which decide whether the collected data originates from a single dipole or from numerous dipoles. In the case where the EEG data arouses from multiple parallel dipoles, an isolation of the source is, in general, not possible.

scholarly journals Mining the Mind: Linear Discriminant Analysis of MEG Source Reconstruction Time Series Supports Dynamic Changes in Deep Brain Regions During Meditation Sessions

2021 ◽  
Author(s):  
Daniela Calvetti ◽  
Brian Johnson ◽  
Annalisa Pascarella ◽  
Francesca Pitolli ◽  
Erkki Somersalo ◽  
...  
Keyword(s):  
Time Series ◽  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Longitudinal Studies ◽  
Brain Activity ◽  
Brain Regions ◽  
Brain Atlas ◽  
Meditation Practice ◽  
Linear Discriminant ◽  
The Brain

AbstractMeditation practices have been claimed to have a positive effect on the regulation of mood and emotions for quite some time by practitioners, and in recent times there has been a sustained effort to provide a more precise description of the influence of meditation on the human brain. Longitudinal studies have reported morphological changes in cortical thickness and volume in selected brain regions due to meditation practice, which is interpreted as an evidence its effectiveness beyond the subjective self reporting. Using magnetoencephalography (MEG) or electroencephalography to quantify the changes in brain activity during meditation practice represents a challenge, as no clear hypothesis about the spatial or temporal pattern of such changes is available to date. In this article we consider MEG data collected during meditation sessions of experienced Buddhist monks practicing focused attention (Samatha) and open monitoring (Vipassana) meditation, contrasted by resting state with eyes closed. The MEG data are first mapped to time series of brain activity averaged over brain regions corresponding to a standard Destrieux brain atlas. Next, by bootstrapping and spectral analysis, the data are mapped to matrices representing random samples of power spectral densities in $$\alpha$$ α , $$\beta$$ β , $$\gamma$$ γ , and $$\theta$$ θ frequency bands. We use linear discriminant analysis to demonstrate that the samples corresponding to different meditative or resting states contain enough fingerprints of the brain state to allow a separation between different states, and we identify the brain regions that appear to contribute to the separation. Our findings suggest that the cingulate cortex, insular cortex and some of the internal structures, most notably the accumbens, the caudate and the putamen nuclei, the thalamus and the amygdalae stand out as separating regions, which seems to correlate well with earlier findings based on longitudinal studies.

scholarly journals Formation of attention in men and women during tasks performance with high cognitive load

2017 ◽  
Vol 23 (2) ◽  
pp. 9-14
Author(s):  
M. Bondarenko ◽  
O. Bondarenko ◽  
V. Kravchenko ◽  
M. Makarchuk
Keyword(s):  
Cognitive Load ◽  
Theta Rhythm ◽  
Alpha Rhythm ◽  
Spectral Power ◽  
Brain Activity ◽  
Visual Content ◽  
Voluntary Attention ◽  
Dominant Eye ◽  
The Brain ◽  
Theta Range

The differences in brain mechanisms that underlie the switch between involuntary and voluntary attention associated with gender were investigated. We compared reaction time, the number of errors and the electrical activity of the brain during the Emotional Stroop test on the background of visual content that contained affective images when presenting stimuli through a dominant and non-dominant eye in 20 men and 20 women. The model of significant cognitive load was created, when it is quite difficult to correctly respond to the relevant characteristics of the stimulus. Different patterns of brain activity have been found: in women, this task is accompanied by an increase in spectral power in the theta range of the predominantly left hemisphere; in men, the power of alpha rhythm in the parietal-occipital associative cortex decreases with the local increase of theta rhythm in the posterior-frontal areas and beta-rhythm in left prefrontal zone. Under the conditions of high cognitive load created by the distracting visual content and the perception of visual stimuli through the non-dominant eye, the brain mechanisms of voluntary attention provide a more thorough analysis of the relevant stimuli in women that is seen in accurate responses over a longer period in comparison with men.

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