Physiological Bases of Magnetoencephalography and Electroencephalography

Author(s):  
Yoshio Okada

Understanding the physiological bases of magnetoencephalography (MEG) and electroencephalography (EEG) provides the foundation for developing these techniques as tools for studying human brain functions because this information can serve as a guide for planning experimental studies and for interpreting the data. During the past 50 years, the concept of electrophysiology of neurons has been profoundly modified as new types of active conductance have been discovered in the dendrites and soma. The biophysical models of individual neurons and neuronal networks developed within the framework of modern electrophysiology have provided quantitatively accurate accounts of evoked magnetic fields, extracellular potentials, and intracellular potentials in principal neurons in the tissues within a single theoretical framework. These results are consistent with the conclusion that intracellular currents in active tissues produce both MEG and EEG signals in the cerebellum, hippocampus, and cerebral cortex. We now know that the calcium and potassium currents are the major currents shaping the waveforms of MEG and EEG and that the sodium and potassium currents generate the spikes and high-frequency signals detectable outside the brain. The current dipole moment density, defined as current dipole moment per unit surface area of the active cortex, is governed by the intracellular volume fraction and basic kinetics of the active conductances. This quantity, which is conserved across the evolutionary scale ranging from reptiles to humans, may serve as a useful physiological constraint in interpreting MEG and EEG signals. It is hoped that this foundation will help advance the research on human brain functions.

2009 ◽  
Vol 18 (08) ◽  
pp. 1467-1480
Author(s):  
JUHONG YANG ◽  
YUKI SAITO ◽  
QIWEI SHI ◽  
JIANTING CAO ◽  
TOSHIHISA TANAKA ◽  
...  

Magnetoencephalography (MEG) is a powerful and non-invasive technique for measuring human brain activity with a high temporal resolution. The motivation for studying MEG data analysis is to extract the essential features from real-world measured data and represent them corresponding to the human brain functions. This usually depends on how to reduce a high level noise from the measurement. In this paper, a novel multistage MEG data analysis method based on the empirical mode decomposition (EMD) and independent component analysis (ICA) approaches is proposed for the feature extraction. Moreover, EMD and ICA algorithms are investigated for analyzing the MEG single-trial data which is recorded from the experiment of phantom. The analyzed results are presented to illustrate the effectiveness and high performance both in high level noise reduction by EMD associated with ICA approach and source localization by equivalent current dipole fitting method.


2007 ◽  
Vol 353-358 ◽  
pp. 687-690
Author(s):  
Yan Dong Yu ◽  
De Liang Yin ◽  
Bao You Zhang

Cavity growth is a typical microstructure feature in superplastic forming (SPF) of materials. Substantial growth and interlink of cavities in superplastic deformation usually lead to reduction in elongation, even to failure. Consequently, it is necessary to investigate the mechanism and model of cavity growth. In this paper, experimental studies on cavity growth were carried out by means of superplastic tension of ZK60 magnesium alloys. Scanning electronic microscope (SEM) was employed for observation of fractography. Experimental cavity radius and volume fraction were determined by optical microscopy and corresponding picture-based analysis software. It is found that, the fractured surfaces after a superplastic elongation have a mixed characteristic of intergranular cavities and dimples. Further, the cavity growth is identified to follow a exponentially increasing mode.


2018 ◽  
Vol 916 ◽  
pp. 221-225
Author(s):  
Ji Zu Lv ◽  
Liang Yu Li ◽  
Cheng Zhi Hu ◽  
Min Li Bai ◽  
Sheng Nan Chang ◽  
...  

Nanofluids is an innovative study of nanotechnology applied to the traditional field of thermal engineering. It refers to the metal or non-metallic nanopowder was dispersed into water, alcohol, oil and other traditional heat transfer medium, to prepared as a new heat transfer medium with high thermal conductivity. The role of nanofluids in strengthening heat transfer has been confirmed by a large number of experimental studies. Its heat transfer mechanism is mainly divided into two aspects. On the one hand, the addition of nanoparticles enhances the thermal conductivity. On the other hand, due to the interaction between the nanoparticles and base fluid causing the changes in the flow characteristics, which is also the main factor affecting the heat transfer of nanofluids. Therefore, a intensive study on the flow characteristics of nanofluids will make the study of heat transfer more meaningful. In this experiment, the flow characteristics of SiO2-water nanofluids in two-dimensional backward step flow are quantitatively studied by PIV. The results show that under the same Reynolds number, the turbulence of nanofluids is larger than that of pure water. With the increase of nanofluids volume fraction, the flow characteristics are constantly changing. The quantitative analysis proved that the nanofluids disturbance was enhanced compared with the base liquid, which resulting in the heat transfer enhancement.


KronoScope ◽  
2013 ◽  
Vol 13 (2) ◽  
pp. 228-239
Author(s):  
Rémy Lestienne

Abstract J.T. Fraser used to emphasize the uniqueness of the human brain in its capacity for apprehending the various dimensions of “nootemporality” (Fraser 1982 and 1987). Indeed, our brain allows us to sense the flow of time, to measure delays, to remember past events or to predict future outcomes. In these achievements, the human brain reveals itself far superior to its animal counterpart. Women and men are the only beings, I believe, who are able to think about what they will do the next day. This is because such a thought implies three intellectual abilities that are proper to mankind: the capacity to take their own thoughts as objects of their thinking, the ability of mental time travels—to the past thanks to their episodic memory or to the future—and the possibility to project very far into the future, as a consequence of their enlarged and complexified forebrain. But there are severe limits to our timing abilities of which we are often unaware. Our sensibility to the passing time, like other of our intellectual abilities, is often competing with other brain functions, because they use at least in part the same neural networks. This is particularly the case regarding attention. The deeper the level of attention required, the looser is our perception of the flow of time. When we pay attention to something, when we fix our attention, then our inner sense of the flux of time freezes. This limitation should not sound too unfamiliar to the reader of J.T. Fraser who wrote in his book Time, Conflict, and Human Values (1999) about “time as a nested hierarchy of unresolvable conflicts.”


Brain ◽  
2019 ◽  
Vol 142 (12) ◽  
pp. 3991-4002 ◽  
Author(s):  
Martijn P van den Heuvel ◽  
Lianne H Scholtens ◽  
Siemon C de Lange ◽  
Rory Pijnenburg ◽  
Wiepke Cahn ◽  
...  

See Vértes and Seidlitz (doi:10.1093/brain/awz353) for a scientific commentary on this article. Is schizophrenia a by-product of human brain evolution? By comparing the human and chimpanzee connectomes, van den Heuvel et al. demonstrate that connections unique to the human brain show greater involvement in schizophrenia pathology. Modifications in service of higher-order brain functions may have rendered the brain more vulnerable to dysfunction.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Mohammad Ali Salehinejad ◽  
Miles Wischnewski ◽  
Elham Ghanavati ◽  
Mohsen Mosayebi-Samani ◽  
Min-Fang Kuo ◽  
...  

AbstractCircadian rhythms have natural relative variations among humans known as chronotype. Chronotype or being a morning or evening person, has a specific physiological, behavioural, and also genetic manifestation. Whether and how chronotype modulates human brain physiology and cognition is, however, not well understood. Here we examine how cortical excitability, neuroplasticity, and cognition are associated with chronotype in early and late chronotype individuals. We monitor motor cortical excitability, brain stimulation-induced neuroplasticity, and examine motor learning and cognitive functions at circadian-preferred and non-preferred times of day in 32 individuals. Motor learning and cognitive performance (working memory, and attention) along with their electrophysiological components are significantly enhanced at the circadian-preferred, compared to the non-preferred time. This outperformance is associated with enhanced cortical excitability (prominent cortical facilitation, diminished cortical inhibition), and long-term potentiation/depression-like plasticity. Our data show convergent findings of how chronotype can modulate human brain functions from basic physiological mechanisms to behaviour and higher-order cognition.


2021 ◽  
Vol 42 (3) ◽  
pp. 130
Author(s):  
Sudip Dhakal

The difficulties in performing experimental studies related to diseases of the human brain have fostered a range of disease models from highly expensive and complex animal models to simple, robust, unicellular yeast models. Yeast models have been used in numerous studies to understand Alzheimer’s disease (AD) pathogenesis and to search for drugs targeting AD. Thanks to the conservation of fundamental eukaryotic processes including ageing and the availability of appropriate technological platforms, budding yeast are a simple model eukaryote to assist with understanding human cell biology, offering a platform to study human diseases. This article aims to provide insights from yeast models on the contributions of amyloid beta, a causative agent in AD, and recent research findings on AD chemoprevention.


2017 ◽  
pp. 115-186 ◽  
Author(s):  
John C. Ashton ◽  
Megan J. Dowie ◽  
Michelle Glass

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