MEG/EEG in the Study of Brain Function

2017 ◽  
pp. 304-310
Author(s):  
Riitta Hari ◽  
Aina Puce
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Social Neuroscience ◽  
Future Research ◽  
Noninvasive Methods ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
Combined Use ◽  
Eeg Recordings ◽  
Two Sides

This chapter summarizes some relative advantages and disadvantages of MEG and EEG, most of which have been previously elaborated. MEG and EEG are the two sides of the same coin and provide complementary information about the human brain’s neurodynamics. The combined use of MEG or EEG together and with other noninvasive methods used to study human brain function is advocated to be important for future research in systems and cognitive/social neuroscience. This chapter also examines combined use and interpretation of MEG/EEG with MRI/fMRI, and performing EEG recordings during non-invasive brain stimulation.

scholarly journals The brain timewise: how timing shapes and supports brain function

2015 ◽  
Vol 370 (1668) ◽  
pp. 20140170 ◽  
Author(s):  
Riitta Hari ◽  
Lauri Parkkonen
Keyword(s):  
Human Brain ◽  
Brain Imaging ◽  
Brain Function ◽  
Temporal Dynamics ◽  
Generative Models ◽  
Network Activity ◽  
Brain Diseases ◽  
Specific Information ◽  
Non Invasive ◽  
The Brain

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.

scholarly journals A Review of the State of the Art in Non-Contact Sensing for COVID-19

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5665
Author(s):  
William Taylor ◽  
Qammer H. Abbasi ◽  
Kia Dashtipour ◽  
Shuja Ansari ◽  
Syed Aziz Shah ◽  
...  
Keyword(s):  
Healthcare Workers ◽  
State Of The Art ◽  
Future Research ◽  
Research Directions ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
Current State ◽  
Global Pandemic ◽  
Future Research Directions ◽  
Contact Sensing

COVID-19, caused by SARS-CoV-2, has resulted in a global pandemic recently. With no approved vaccination or treatment, governments around the world have issued guidance to their citizens to remain at home in efforts to control the spread of the disease. The goal of controlling the spread of the virus is to prevent strain on hospitals. In this paper, we focus on how non-invasive methods are being used to detect COVID-19 and assist healthcare workers in caring for COVID-19 patients. Early detection of COVID-19 can allow for early isolation to prevent further spread. This study outlines the advantages and disadvantages and a breakdown of the methods applied in the current state-of-the-art approaches. In addition, the paper highlights some future research directions, which need to be explored further to produce innovative technologies to control this pandemic.

scholarly journals Heart rate variability as it pertains to sports related concussion and post-concussion syndrome

Neurology ◽  
2018 ◽  
Vol 91 (23 Supplement 1) ◽  
pp. S20.3-S21
Author(s):  
Thomas Bottiglieri ◽  
Randy Casals
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Brain Injury ◽  
Brain Function ◽  
Future Research ◽  
Post Concussion Syndrome ◽  
Non Invasive ◽  
Ovid Medline ◽  
Rigorous Study ◽  
Subjective Reports

ContextSports related concussions (SRC), occur frequently in contact and collision sports and detection relies predominantly on subjective reports by athletes themselves. A non-invasive means of monitoring brain function and injury is desirable. Existing literature has established autonomic nervous system (ANS) dysfunction in the setting of brain injury. Heart rate variability (HRV) has been accepted as a means of measuring ANS function and correlation of ANS dysregulation after brain injury through HRV measurement can aid in the detection of concussions, monitoring of recovery, and may offer a target for intervention.MethodsThe studies included were found on the Ovid MEDLINE, PubMed, and Google Scholar databases through searches of the following keywords: HRV, heart rate variability and concussion, post-concussion syndrome, and HRV biofeedback. We excluded studies that were not in English and did not meet the inclusion criteria of pertaining to SRC, sports performance, or ANS function.DesignClinical review.ResultsCurrent literature supports the notion that SRC causes dysregulation of the ANS, which can be detecting through changes in HRV. Monitoring HR and analyzing HRV can be used as a tool to detect SRC, monitor recovery, and set a target for treatment. Biofeedback techniques targeting HRV have been used to improve HRV and expedite recovery from SRC.ConclusionExisting literature has shown HRV is a tool for concussion detection and HRV biofeedback can aid in recovery. More rigorous study of the best ways to measure HRV in athletes, qualify and quantify changes in HRV specific to SRC, timing of change, timing of resolution of ANS dysfunction, and clinical significance of persistent HRV change after injury were all identified as targets for future research. Interventional studies evaluating the use of biofeedback as a means of improving HRV and reducing concussion symptoms severity and duration are warranted as well.

scholarly journals Principles of Dynamic Network Reconfiguration across Diverse Brain States

2017 ◽  
Author(s):  
James M. Shine ◽  
Russell A. Poldrack
Keyword(s):  
Human Brain ◽  
Network Structure ◽  
Brain Function ◽  
Dynamic Network ◽  
Future Research ◽  
Network Reconfiguration ◽  
Diverse Range ◽  
Electrophysiological Studies ◽  
Brain States ◽  
The Relationship

Recent methodological advances have enabled researchers to track the network structure of the human brain over time. Together, these studies provide novel insights into effective brain function, highlighting the importance of the systems-level perspective in understanding the manner in which the human brain organizes its activity to facilitate behavior. Here, we review a range of recent fMRI and electrophysiological studies that have mapped the relationship between inter-regional communication and network structure across a diverse range of brain states. In doing so, we identify both behavioral and biological axes that may underlie the tendency for network reconfiguration. We conclude our review by providing suggestions for future research endeavors that may help to refine our understanding of the functioning of the human brain.

scholarly journals Diagnosis of liver fibrosis: an emphasis on elastography

2021 ◽  
pp. 72-81
Author(s):  
I. I. Zhirkov ◽  
A. V. Gordienko ◽  
I. M. Pavlovich ◽  
B. A. Chumak ◽  
V. V. Yakovlev
Keyword(s):  
Liver Fibrosis ◽  
Liver Biopsy ◽  
Initial Examination ◽  
Morphological Examination ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
Combined Use ◽  
Liver Elastography ◽  
Diagnostic Capabilities

In the strategy of managing patients with chronic diffuse liver diseases, the priority areas are the determination of the diagnosis with the determination of the main risk factors, the activity of the process (steatosis, steatohepatitis), as well as the degree of fibrous transformation. The rate of progression of liver fibrosis is a decisive factor that will determine the prognosis, treatment tactics and the likelihood of severe complications. The “gold standard” for diagnosing chronic liver pathology is a puncture liver biopsy with morphological examination of the liver tissue. At the same time, potential complications, contraindications to the procedure, low patient compliance, as well as errors in the interpretation of the results obtained due to various reasons are significant limitations of this diagnostic method. These shortcomings were the reason for the search for reliable non-invasive methods for diagnosing liver fibrosis both during the initial examination and during subsequent monitoring in dynamics. Modern methods of liver elastography are widely used for non-invasive assessment of fibrosis, demonstrating good diagnostic capabilities and significantly reducing the need for liver biopsy. Various elastography methods, which have their own advantages and disadvantages, effectively complement each other, which is successfully used in clinical practice in the diagnosis of fibrous transformation. The combined use of elastographic methods and commercial predictive diagnostic panels will increase the diagnostic accuracy in the determination of liver fibrosis.

MEG-EEG Primer

2017 ◽  
Author(s):  
Riitta Hari, MD, PhD ◽  
Aina Puce, PhD
Keyword(s):  
Human Brain ◽  
Brain Function ◽  
Brain Disorders ◽  
Eeg Signals ◽  
Noninvasive Methods ◽  
Brain Signals ◽  
Current State ◽  
Social Events ◽  
Data Collection And Analysis

This book provides newcomers and more experienced researchers with the very basics of magnetoencephalography (MEG) and electroencephalography (EEG)—two noninvasive methods that can inform about the neurodynamics of the human brain on a millisecond scale. These two closely related methods are addressed side by side, starting from their physical and physiological bases and then advancing to methods of data acquisition, analysis, visualization, and interpretation. Special attention is paid to careful experimentation, guiding the readers to differentiate brain signals from various biological and non-biological artifacts and to ascertain that the collected data are reliable. The strengths and weaknesses of MEG and EEG are presented relative to each other and to other available brain-imaging methods. Necessary instrumentation and laboratory set-ups, as well as potential pitfalls in data collection and analysis are discussed. Spontaneous brain rhythms and evoked responses to sensory and multisensory stimulation are covered and examined both in healthy individuals and in various brain disorders, such as epilepsy. MEG/EEG signals related to motor, cognitive, and social events are discussed as well. The integration of MEG and EEG information with other methods to assess human brain function is discussed with respect to the current state-of-the art in the field. The book ends with a look to future developments in equipment design, and experimentation, emphasizing the role of accurate temporal information for human brain function.

scholarly journals Comparative analysis of neurointerface technologies for the problem of their reasonable choice in human-machine information systems

2020 ◽  
Vol 100 (4) ◽  
pp. 135-148
Author(s):  
Roman Butsiy ◽  
Serhii Lupenko
Keyword(s):  
Comparative Analysis ◽  
Spatial Patterns ◽  
Future Research ◽  
Bayesian Classifiers ◽  
Advantages And Disadvantages ◽  
Non Invasive ◽  
Adaptive Parameters ◽  
Software And Hardware ◽  
Reasonable Choice ◽  
Operator Control

The market of modern neurointerfaces, despite its active development, unfortunately, can offer users only a number of existing prototypes that have a relatively low accuracy and identification reliability of the human operator control effects. In addition, any neurointerface on the market must be individually tailored to each operator, which makes it difficult to objectify its accuracy, precision and reliability. The first step in solving the above problems is to conduct a comparative analysis of different price segments of the market of existing neurointerface technologies, as presented in this article. The market research revealed that despite the disadvantages of electroencephalography, it is one of the most accessible non-invasive methods of recording biological signals in neurointerface systems. To facilitate future research, the main advantages and disadvantages of known models and methods of signal analysis in neurointerfaces have been considered and analyzed. In particular, in the context of signal pre-processing, advantages and disadvantages of such methods as Common Average Referencing, Independent Component Analysis, Common Spatial Patterns, Surface Laplacian, Common Spatio-Spatial Patterns and Adaptive Filtering are considered. At the stage of evaluating the informative characteristics of the signal, the analysis of models and methods based on the models of adaptive parameters of autoregression, bilinear autoregression, multidimensional autoregression, fast Fourier transform, wavelet transformation, wave packet decomposition is performed. Besides, a comparative analysis of the most common methods of identification (recognition) of control effects of the human neurointerface operator, namely, the method of discriminant analysis, the method of reference vectors, nonlinear Bayesian classifiers, classifiers of nearest neighbors, artificial neural networks is carried out. The study of neurointerface technologies provides researchers with additional grounds for a sound choice of mathematical, software and hardware of neurointerface systems, as well as contributes to the development of new versions with increased accuracy, reliability and reliability.

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