scholarly journals Less Is Enough: Assessment of the Random Sampling Method for the Analysis of Magnetoencephalography (MEG) Data

2019 ◽  
Vol 24 (4) ◽  
pp. 98
Author(s):  
Cristina Campi ◽  
Annalisa Pascarella ◽  
Francesca Pitolli
Keyword(s):  
Magnetic Field ◽  
Random Sampling ◽  
Sampling Method ◽  
Brain Activity ◽  
Memory Storage ◽  
Non Invasive ◽  
Regularization Techniques ◽  
Ill Posed ◽  
The Brain ◽  
The Magnetic Field

Magnetoencephalography (MEG) aims at reconstructing the unknown neuroelectric activity in the brain from non-invasive measurements of the magnetic field induced by neural sources. The solution of this ill-posed, ill-conditioned inverse problem is usually dealt with using regularization techniques that are often time-consuming, and computationally and memory storage demanding. In this paper we analyze how a slimmer procedure, random sampling, affects the estimation of the brain activity generated by both synthetic and real sources.

Magneto-encefalografie

1996 ◽  
Vol 8 (3) ◽  
pp. 64-70
Author(s):  
M.J. Peters ◽  
F. Reinders
Keyword(s):  
Magnetic Field ◽  
Epileptic Focus ◽  
Current Dipole ◽  
Non Invasive ◽  
Active Population ◽  
Presurgical Mapping ◽  
The Brain ◽  
Weak Fields ◽  
The Magnetic Field ◽  
Realistic Shape

SummaryA magnetoencephalogram (MEG) is the registration of the magnetic field in points near the head. Because MEG's are weak fields, they have to be measured by means of superconducting sensors. The electric active population of neurons can be computed from the distribution of the magnetic field at a certain instant of time. This is called the inverse problem. In order to solve this probem, both the generators and the head have to be modelled. Usually, a patch of active neurons is modelled as a current dipole. Commonly, the head is described by three compartments, representing the brain, the skull and the scalp. The compartments may have the shape of spheres or they may have a realistic shape. Integration of EEG and MEG with MRI leads to a technique for functional imaging of the brain with a time resolution of one millisecond and a spatial resolution of one centimetre. Clinical applications are the non-invasive localization of an epileptic focus or the presurgical mapping of the sensorimotor cortex.

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 MEG as a Medical Diagnostic Tool in the Greek Population

2015 ◽  
Vol 58 (3) ◽  
pp. 71-78 ◽  
Author(s):  
Photios Anninos ◽  
Adam Adamopoulos ◽  
Athanasia Kotini
Keyword(s):  
Research Work ◽  
Research Field ◽  
Greek Population ◽  
Brain Disorders ◽  
Important Research ◽  
Non Invasive ◽  
Medical Diagnostic ◽  
Invasive Method ◽  
The Brain ◽  
The Magnetic Field

Magnetoencephalography (MEG) is the recording of the magnetic field produced by the flowing of ions in the brain. This article reports our experience in the application of MEG in patients and healthy volunteers in the Greek population. We provide a brief description of our research work. The MEG data were recorded in a magnetically shielded room with a whole-head 122 channel or an one-channel biomagnetometer. Our results lead us to believe that the MEG is an important research field which is evolving quickly with a number of interesting findings with respect to normal and abnormal functions of the human brain. It could provide clinical practice with an easy to perform non invasive method, which could be adjunct to conventional methods for the evaluation of brain disorders.

scholarly journals Introduction to the identification of brain waves based on their frequency

2018 ◽  
Vol 210 ◽  
pp. 05012 ◽  
Author(s):  
Zuzana Koudelková ◽  
Martin Strmiska
Keyword(s):  
Brain Activity ◽  
Computer Interface ◽  
Brain Wave ◽  
Non Invasive ◽  
Brain Waves ◽  
Analytical Reasoning ◽  
Brain Signals ◽  
Electroencephalogram Eeg ◽  
The Brain ◽  
Research Type

A Brain Computer Interface (BCI) enables to get electrical signals from the brain. In this paper, the research type of BCI was non-invasive, which capture the brain signals using electroencephalogram (EEG). EEG senses the signals from the surface of the head, where one of the important criteria is the brain wave frequency. This paper provides the measurement of EEG using the Emotiv EPOC headset and applications developed by Emotiv System. Two types of the measurements were taken to describe brain waves by their frequency. The first type of the measurements was based on logical and analytical reasoning, which was captured during solving mathematical exercise. The second type was based on relax mind during listening three types of relaxing music. The results of the measurements were displayed as a visualization of a brain activity.

scholarly journals Transcranial magnetic stimulation: studying the brain--behaviour relationship by induction of ‘virtual lesions’

1999 ◽  
Vol 354 (1387) ◽  
pp. 1229-1238 ◽  
Author(s):  
Alvaro Pascual-Leone
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Magnetic Stimulation ◽  
Brain Connectivity ◽  
Brain Activity ◽  
Causal Link ◽  
Non Invasive ◽  
Invasive Method ◽  
Normal Humans ◽  
The Brain ◽  
Neuroimaging Techniques

Transcranial magnetic stimulation (TMS) provides a non-invasive method of induction of a focal current in the brain and transient modulation of the function of the targeted cortex. Despite limited understanding about focality and mechanisms of action, TMS provides a unique opportunity of studying brain-behaviour relations in normal humans. TMS can enhance the results of other neuroimaging techniques by establishing the causal link between brain activity and task performance, and by exploring functional brain connectivity.

scholarly journals An inversion method based on random sampling for real-time MEG neuroimaging

2019 ◽  
Vol 10 (2) ◽  
pp. 25-34 ◽  
Author(s):  
Annalisa Pascarella ◽  
Francesca Pitolli
Keyword(s):  
Real Time ◽  
Random Sampling ◽  
Active Regions ◽  
Electric Activity ◽  
Memory Storage ◽  
Inversion Method ◽  
High Temporal Resolution ◽  
Meg Inverse Problem ◽  
The Brain ◽  
Realistic Data

Abstract The MagnetoEncephaloGraphy (MEG) has gained great interest in neurorehabilitation training due to its high temporal resolution. The challenge is to localize the active regions of the brain in a fast and accurate way. In this paper we use an inversion method based on random spatial sampling to solve the real-time MEG inverse problem. Several numerical tests on synthetic but realistic data show that the method takes just a few hundredths of a second on a laptop to produce an accurate map of the electric activity inside the brain. Moreover, it requires very little memory storage. For these reasons the random sampling method is particularly attractive in real-time MEG applications.

scholarly journals A Robust Emotion Extraction System from EEG Signal Dataset using Machine Learning

2021 ◽  
pp. 319-330
Author(s):  
Muthulakshmi P ◽  
Gopika R
Keyword(s):  
Machine Learning ◽  
Brain Activity ◽  
Extraction System ◽  
Eeg Signal ◽  
Eeg Asymmetry ◽  
Non Invasive ◽  
Brain Signals ◽  
Human Stress ◽  
Invasive Method ◽  
The Brain

The project entitled “A Robust Emotion Extraction System from EEG signal Dataset using Machine Learning” has been developed using MATLAB. The brain activity produces the different kinds of signals like electrical and magnetic signals. This activity can be recorded using different kind of approaches, which are normally classified as invasive and non-invasive. In invasive methods surgical intervention are made to implant certain device in the brain whereas in non-invasive methods no such intervention is made. Among the different non-invasive methods, Electroencephalography is one of the most commonly used methods to record the brain signals. EEG is regarded as direct and simple non-invasive method to record the brain electrical activity. Current flow in the neurons of the brain is represented as voltage fluctuation (EEG). EEG waves which can be represented as the signal over time are recorded by the electrodes places on scalp over the brain. EEG Asymmetry and Spectral Centroids techniques in extracting unique features for human stress. In our proposed work we have to classify the EEG signal whether that is stress or not. In our proposed work we will extract the features and optimizing Using Genetic Algorithm then we finally classify the EEG signal.

scholarly journals Magnetic Field Mapping and Correction for Moving OP-MEG

2021 ◽  
Author(s):  
Stephanie J Mellor ◽  
Tim M Tierney ◽  
George C O'Neill ◽  
Nicholas Alexander ◽  
Robert A Seymour ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Brain Activity ◽  
Low Frequency ◽  
Optically Pumped ◽  
Magnetic Field Mapping ◽  
Modelling Method ◽  
Movement Artefact ◽  
Power Spectral ◽  
Background Magnetic Field ◽  
The Magnetic Field

Background: Optically pumped magnetometers (OPMs) have made moving, wearable magnetoencephalography (MEG) possible. The OPMs typically used for MEG require a low background magnetic field to operate, which is achieved using both passive and active magnetic shielding. However, the background magnetic field is never truly zero Tesla, and so the field at each of the OPMs changes as the participant moves. This leads to position and orientation dependent changes in the measurements, which manifest as low frequency artefacts in MEG data. Objective: We modelled the spatial variation in the magnetic field and used the model to predict the movement artefact found in a dataset. Methods: We demonstrate a method for modelling this field with a triaxial magnetometer, then showed that we can use the same technique to predict the movement artefact in a real OPM-based MEG (OP-MEG) dataset. Results: Using an 86-channel OP-MEG system, we found that this modelling method maximally reduced the power spectral density of the data by 26.2 ± 0.6 dB at 0 Hz, when applied over 5 s non-overlapping windows. Conclusion: The magnetic field inside our state-of-the art magnetically shielded room can be well described by low-order spherical harmonic functions. We achieved a large reduction in movement noise when we applied this model to OP-MEG data. Significance: Real-time implementation of this method could reduce passive shielding requirements for OP-MEG recording and allow the measurement of low-frequency brain activity during natural participant movement.

Two Realizations of the Wearable PPG Sensor Working in Reflectance Mode for Measurement in Weak Magnetic Field

2021 ◽  
Vol 10 (1) ◽  
pp. 55
Author(s):  
Jiří Přibil ◽  
Anna Přibilová ◽  
Ivan Frollo
Keyword(s):  
Magnetic Field ◽  
Weak Magnetic Field ◽  
Wearable Sensors ◽  
Control Device ◽  
Wireless Transmission ◽  
Electromagnetic Disturbance ◽  
Non Invasive ◽  
Field Environment ◽  
Scanning Area ◽  
The Magnetic Field

The paper describes and compares properties of two realizations of wearable sensors based on the photoplethysmography (PPG) principle for non-invasive acquisition of the human heart rate. The designed sensors enable measurement of the PPG signal in the magnetic field environment with the inherent radiofrequency and electromagnetic disturbance. They can monitor the stress of a tested person during examination in the scanning area of the open-air magnetic resonance tomograph. The performed auxiliary experiments verify the practical functionality of both developed sensors including real-time wireless transmission of the measured PPG signal samples to the control device for further analysis and processing.

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