A Current-Based EEG Amplifier and Validation With a Saline Phantom and an SSVEP Paradigm.

Magnetoencephalography (MEG) can measure brain activity in ms-level temporal resolution. MEG sensors are super sensitive devices for magnetic signals of the brain but are also prone to electromagnetic interferences. The MEG device is located inside the magnetically shielded room (MSR), and any monitoring device used inside the MSR requires special shielding and its location must be carefully selected to suppress electromagnetic interference. Eye-tracker measures eye movements, providing spatial location of the gaze, pupil diameters, and eye blinks. Eye tracking in MEG enables, for example, categorization of the MEG data based on gaze position and interactive stimulus using gaze position. Combining the methods together will require considering the electromagnetic interference for the MEG—that is, additional shielding, positioning of the eye tracker, and subject-specific issues related to make-up and eye-corrective lenses.

Introduction and problem formulation Elucidating how the human brain is structured and how it functions is a fundamental aim of human neuroscience. To achieve such an aim, the activity of the human brain has been measured using noninvasive neuroimaging techniques, the most popular of which is functional magnetic resonance imaging (fMRI) (Ogawa et al . 1990). The fMRI signals are obtained at a spatial resolution of typically 3mm and measure changes of blood flow and blood oxygen consumption whose temporal dynamics are slower than that of neuronal electrical activities, resulting in a poor temporal resolution of the order of seconds. In contrast, magnetoencephalography (MEG) and electroencephalography (EEG) can detect changes of neuronal activities by the millisecond measurement of magnetic and electric fields, respectively, outside the skull (Hamalainen et al . 1993; Nunez & Srinivasan 2006). The high temporal resolution of MEG (and EEG) is useful, especially for studying the dynamic integration of functionally specialized brain regions, which is a subject of growing interest in human neuroscience (de Pasquale et al . 2012). The major problem of MEG is that spatial brain activity patterns are not easily understandable from sensor measurements. This is because the magnetic fields produced by neuronal current sources are superimposed to form rather uninterpretable spatial patterns of signals on sensors. Estimating the position and intensity of these current sources from the sensor measurements is called source reconstruction, or source localization. Solving the source reconstruction problem allows the mapping of temporally dynamic electrical activities in the human brain (Baillet et al . 2001). Since how brain regions are dynamically integrated to produce a variety of functions is of great interest in human neuroscience research, the mission of MEG source reconstruction is not only to localize position of the current sources, but also to identify directed interactions between these sources. A possible approach to this involves constructing a dynamic model of brain electrical activities, as well as developing an estimation algorithm for the source positions and interactions that are parametrized in this model.

Electroencephalography (EEG) is the electrical neural activity recording modality with high temporal and low spatial resolution. Here we propose a novel technique that we call vibroEEG improving significantly the source localization accuracy of EEG. Our method combines electric potential acquisition in concert with acoustic excitation of the vibrational modes of the electrically active cerebral cortex which displace periodically the sources of the low frequency neural electrical activity. The sources residing on the maxima of the induced modes will be maximally weighted in the corresponding spectral components of the broadband signals measured on the noninvasive electrodes. In vibroEEG, for the first time the rich internal geometry of the cerebral cortex can be utilized to separate sources of neural activity lying close in the sense of the Euclidean metric. When the modes are excited locally using phased arrays the neural activity can essentially be probed at any cortical location. When a single transducer is used to induce the excitations, the EEG gain matrix is still being enriched with numerous independent gain vectors increasing its rank. We show theoretically and on numerical simulation that in both cases the source localization accuracy improves substantially.

THINGS-data reflects three large-scale neuroimaging and behavioral datasets of object processing in humans, comprising densely sampled functional MRI and magnetoencephalographic recordings, as well as 4.70 million similarity judgments in response to thousands of photographic images for up to 1854 objects.

Chapter 50 - Magnetoencephalography (MEG) and other neurophysiological investigations

Predicting the recognition of natural scenes from single trial MEG recordings of brain activity

New advances in structural neuroimaging have revealed the intricate and extensive connections within the brain, data which have informed a number of ambitious projects such as the mapping of the human connectome. Elucidation of the structural connections of the brain, at both the macro and micro levels, promises new perspectives on brain structure and function that could translate into improved outcomes in functional neurosurgery. The understanding of neuronal structural connectivity afforded by these data now offers a vista on the brain, in both healthy and diseased states, that could not be seen with traditional neuroimaging. Concurrent with these developments in structural imaging, a complementary modality called magnetoencephalography (MEG) has been garnering great attention because it too holds promise for being able to shed light on the intricacies of functional brain connectivity. MEG is based upon the elemental principle of physics that an electrical current generates a magnetic field. Hence, MEG uses highly sensitive biomagnetometers to measure extracranial magnetic fields produced by intracellular neuronal currents. Put simply then, MEG is a measure of neurophysiological activity, which captures the magnetic fields generated by synchronized intraneuronal electrical activity. As such, MEG recordings offer exquisite resolution in the time and oscillatory domain and, as well, when co-registered with magnetic resonance imaging (MRI), offer excellent resolution in the spatial domain. Recent advances in MEG computational and graph theoretical methods have led to studies of connectivity in the time-frequency domain. As such, MEG can elucidate a neurophysiological-based functional circuitry that may enhance what is seen with MRI connectivity studies. In particular, MEG may offer additional insight not possible by MRI when used to study complex eloquent function, where the precise timing and coordination of brain areas is critical. This article will review the traditional use of MEG for functional neurosurgery, describe recent advances in MEG connectivity analyses, and consider the additional benefits that could be gained with the inclusion of MEG connectivity studies. Since MEG has been most widely applied to the study of epilepsy, we will frame this article within the context of epilepsy surgery and functional neurosurgery for epilepsy.

Cortex-muscle coherence (CMC) reflects coupling between magnetoencephalography (MEG) and surface electromyography (sEMG), being strongest during isometric contraction but absent, for unknown reasons, in some individuals. We used a novel nonmagnetic high-density sEMG (HD-sEMG) electrode grid (36 mm × 12 mm; 60 electrodes separated by 3 mm) to study effects of sEMG recording site, electrode derivation, and rectification on the strength of CMC. Monopolar sEMG from right thenar and 306-channel whole-scalp MEG were recorded from 14 subjects during 4-min isometric thumb abduction. CMC was computed for 60 monopolar, 55 bipolar, and 32 Laplacian HD-sEMG derivations, and two derivations were computed to mimic "macroscopic" monopolar and bipolar sEMG (electrode diameter 9 mm; interelectrode distance 21 mm). With unrectified sEMG, 12 subjects showed statistically significant CMC in 91-95% of the HD-sEMG channels, with maximum coherence at ∼25 Hz. CMC was about a fifth stronger for monopolar than bipolar and Laplacian derivations. Monopolar derivations resulted in most uniform CMC distributions across the thenar and in tightest cortical source clusters in the left rolandic hand area. CMC was 19-27% stronger for HD-sEMG than for "macroscopic" monopolar or bipolar derivations. EMG rectification reduced the CMC peak by a quarter, resulted in a more uniformly distributed CMC across the thenar, and provided more tightly clustered cortical sources than unrectifed sEMGs. Moreover, it revealed CMC at ∼12 Hz. We conclude that HD-sEMG, especially with monopolar derivation, can facilitate detection of CMC and that individual muscle anatomy cannot explain the high interindividual CMC variability.

Emulation of somatosensory evoked potential (SEP) components with the 3-shell head model and the problem of ‘ghost potential fields’ when using an average reference in brain mapping

The view of brain activity is determined by the method used, for example, conventional scalp electroencephalography (EEG) provides a blurred vision, subdural invasive electrodes a view like a magnifying lens, and intracerebral electrodes, a tunnel view. The development of sophisticated algorithms for source localization of magnetoencephalography (MEG) and EEG provides a new approach to recognize and localize source attributes. Intracellular and extracellular currents are the sources of electric/magnetic fields. The intracellular current (primary current) is surrounded by a magnetic field, whereas extracellular currents are due to passive volume conduction induced by the electric field. EEG and MEG are complementary recording techniques because both methods have certain advantages and disadvantages. MEG has some favorable characteristics for source localizations; for example, secondary volume currents are in general not so important and the modeling of the conductivities of the different brain tissues (gray–white matter, skull, scalp) do not play a major role. Modern MEG–multichannel systems with up to 300 channels provide a fast and contact-less measurement of the predominantly tangential components of the brain activity. On the other hand, EEG records both radial and tangential components, but secondary volume conduction plays a significant role and must be considered adequately by a realistic head model (Boundary Element Model, Finite Element Model). For source localization, special electroanatomic and physical characteristics have to be considered, because the solution of the inverse problem is not unique. Therefore, additional assumptions have to be made for the source model and the allowed source space. Very often the equivalent current dipole (ECD), which describes the center of gravity of the electrical activity, is used for the description of focal epileptic activity. This model provides in many cases a good estimation of the underlying source but a careful evaluation of the results with respect to stability and reproducibility have to be considered. In addition to the ECD, more elaborate source models, for example, multiple dipoles, beam former, or current density analysis can be used. In addition, the coherence analysis provides a better understanding of the brain dynamics. As in all functional imaging methods, the extension of activity and noise artifacts require special consideration. The depth resolution of MEG recordings depends on technical conditions such as the use of gradiometers or magnetometers. In addition to scalp EEG/MEG recordings, also simultaneously recorded electrocorticography (ECoG) and MEG recordings can be performed offering a better three-dimensional view of deeper localized epileptic activities. Source localization aims to detect focal epileptic activity within the interictal or even ictal onset of the epileptic network. In addition to the localization of epileptic activity, its spatial relationship to functional important areas (e.g., motor/speech) is a major task with regard to surgical planning. For this task a multimodal coregistration of MEG/EEG and functional magnetic resonance imaging (fMRI) as well as tractography by means of diffusion tensor imaging (DTI) can be used (Fig. 1). (A) Streamtube visualization of the right optic radiation based on diffusion tensor imaging (DTI). (B) For navigation, a three-dimensional object representing the optic radiation (wrapping the individual fibers) and two distinct magnetic source imaging (MSI) foci (red) are generated. (C) Relation of optic radiation (visualized as streamlines) to MSI foci. (D–F) Sagittal/coronal (axial view of T1-weighted images with registered DTI. Localization of focal epileptic activity is below the optic tract. (Stefan et al., 2006). The sensitivity of MEG for specific epileptic activity is approximately 70%. The MEG, compared to video-EEG monitoring and MRI, provided additional information during presurgical evaluation in 35% (Stefan et al., 2003). In patients, for whom interictal and focal epileptic seizures during long-term scalp EEG recordings were inconclusive (25 of 105 patients) MEG was able to localize in the lobe, which has been resected later on, in 44%. All these patients had an improvement of seizure frequency postoperatively (six patients were seizure-free; five patients had a reduction >50%) (Paulini et al., 2007). When comparing noninvasive magnetic source imaging and invasive seizure-onset localization, a positive predictive value of magnetic source imaging (MSI) for seizure localization was 82–90% (Knowlton et al., 2006). MEG predicted outcome following surgery for intractable epilepsy in children with normal or nonfocal MRI findings (RamachandranNair et al., 2007). There are special situations during presurgical evaluation in which MSI is helpful: for example, patients after surgery, multiple stage surgery, patients with missing cooperation for prolonged invasive recordings or contraindications for invasive recordings. Furthermore, presurgical invasive recordings can be guided by MEG and in some cases might be even omitted. The combined multimodal use of MEG/EEG, MRI, fMRI, single photon emission computed tomography (SPECT), and functional neuronavigation can be used for functional preservation in epilepsy surgery (Ganslandt et al., 1999). The author has no conflict of interest to disclose.

Magnetoencephalography (MEG) records the magnetic field generated by electrical activity of cortical neurons. The signal is not distorted or attenuated, and it is contactless recording that can be performed comfortably even for longer than an hour. It has excellent and decent temporal resolution, especially when it is combined with the patient's own brain magnetic resonance imaging (magnetic source imaging). Data of MEG and electroencephalography are not mutually exclusive and it is recorded simultaneously and interpreted together. MEG has been shown to be useful in detecting the irritative zone in both lesional and nonlesional epilepsy surgery. It has provided valuable and additive information regarding the lesion that should be resected in epilepsy surgery. Better outcomes in epilepsy surgery were related to the localization of the irritative zone with MEG. The value of MEG in epilepsy surgery is recruiting more patients to epilepsy surgery and providing critical information for surgical planning. MEG cortical mapping is helpful in younger pediatric patients, especially when the epileptogenic zone is close to the eloquent cortex. MEG is also used in both basic and clinical research of epilepsy other than surgery. MEG is a valuable diagnostic modality for diagnosis and treatment, as well as research in epilepsy.

Magnetoencephalography (MEG) is the measurement of the magnetic field generated by the electrical activity of neurons. It is usually combined with a magnetic resonance imaging to get what is called magnetic source imaging. The technology that has helped record these minute magnetic fields is super-conducting quantum interference detector which is like a highly sensitive magnetic field meter. To attenuate the external magnetic noise the MEG is housed inside a magnetically shielded room. The actual sensors recording magnetic fields are magnetometers and/or gradiometers. MEG fields pass through the head without any distortion. This is a significant advantage of MEG over electroencephalography. MEG provides a high spatial and temporal resolution. The recording and identification information should be according to the American Clinical Magnetoencephalography Society guidelines published in 2011. MEG currently has two approved indications in the United States, one is for pre-operative brain mapping and the other is for use in epilepsy surgery. MEG studies have shown functional brain tissue inside brain tumors.

Nowadays, it is well understood that brain activity generates a variable electromagnetic field that can be detected quite accurately by using scalp electrodes as well as by superconductive magnetic sensors. Electroencephalography (EEG) and magnetoencephalography (MEG) are therefore useful techniques for the study of brain dynamics and functional cortical connectivity because of their high temporal resolution i.e., milliseconds (Nunez, P., 1981).

Commonly used noninvasive fetal monitoring is based on fetal heart rate (FHR) variability analysis of the Doppler ultrasound signal coming from the mechanical activity of the fetal heart. However, in most of bedside monitors there is an invasive option that during a labor the FHR signal can be obtained directly from the scalp electrode. The determination of cardiac intervals using the Doppler ultrasound signal is more difficult than in electrocardiography, where the R-waves are evident. We investigated the influence of the signal acquisition methods on the FHR variability analysis. The LabView based instrumentation for simultaneous signal acquisition from two fetal monitor channels recording mechanical and electrical heart activity was developed. The 185 pairs of indices describing both the long- and the short-term FHR variability were calculated within one-minute windows. The results reveal that the accuracy of the ultrasound method is to low for reliable measurement of beat-to-beat intervals, what is particularly visible in the reduction of the short-term variability indices.Keywordsfetal monitoringfetal heart rateDoppler ul-trasound

An EEG signal is a measurement of currents that flow during synaptic excitations of the dendrites of many pyramidal neurons in the cerebral cortex.EEG is used to denote electrical neural activity of the brain. Electroencephalography (EEG) is the recording of electric potentials produced by the local collective partial synchrony of electrical field activity in cortical neuropile, today most commonly measured by an array of electrodes attached to the scalp using water-based gel.