BACKGROUND: The perception of global form requires integration of local visual cues across space and is the foundation for object recognition. Here we used magnetoencephalography (MEG) to study the location and time course of neuronal activity associated with the perception of global structure from local image features. To minimize neuronal activity to low-level stimulus properties, such as luminance and contrast, the local image features were held constant during all phases of the MEG recording. This allowed us to assess the relative importance of striate (V1) versus extrastriate cortex in global form perception. METHODOLOGY/PRINCIPAL FINDINGS: Stimuli were horizontal, rotational and radial Glass patterns. Glass patterns without coherent structure were viewed during the baseline period to ensure neuronal responses reflected perception of structure and not changes in local image features. The spatial distribution of task-related changes in source power was mapped using Synthetic Aperture Magnetometry
TY - BOOK. T1 - Clinical applications of magnetoencephalography. AU - Tobimatsu, Shozo. AU - Kakigi, Ryusuke. PY - 2016/1/1. Y1 - 2016/1/1. N2 - This book presents an overview of the recent advances in clinical applications of magnetoencephalography (MEG). With the expansion of MEG to neuroscience, its clinical applications have also been actively pursued. Featuring contributions from prominent experts in the fields, the book focuses on the current status of the application of MEG, not only to each nervous system but also to various diseases such as epilepsy, neurological disorders, and psychiatric disorders, while also examining the feasibility of using MEG for these diseases. Clinical Applications of Magnetoencephalography offers an indispensable resource for neurologists, neurosurgeons, pediatricians, and psychiatrists, as well as researchers in the field of neuroscience.. AB - This book presents an overview of the recent advances in clinical applications of magnetoencephalography (MEG). With ...
The aim of the protocol is to study the resting brain activation profile of 3 groups of people, using a new fMRI procedure, called fMRI-SAM. fMRI-SAM will be applied to 25 Alzheimers disease (AD) patients, 25 patients suffering from amnestic - mild cognitive impairment (MCI) - a clinical picture which may be a prodromal form of AD - and 60 healthy controls. The first analysis of the data will search differences of brain activation profiles between the 3 groups. In the second step, the investigators will study the predictive value of fMRI-SAM to detect MCI patients who will later convert to AD ...
Neuroimaging studies in Anorexia Nervosa (AN) have shown increased activation in reward and cognitive control regions in response to food, and a behavioral attentional bias (AB) towards food stimuli is reported. This study aimed to further investigate the neural processing of food using magnetoencephalography (MEG). Participants were 13 females with restricting-type AN, 14 females recovered from restricting-type AN, and 15 female healthy controls. MEG data was acquired whilst participants viewed high- and low-calorie food pictures. Attention was assessed with a reaction time task and eye tracking. Time-series analysis suggested increased neural activity in response to both calorie conditions in the AN groups, consistent with an early AB. Increased activity was observed at 150 ms in the current AN group. Neuronal activity at this latency was at normal level in the recovered group; however, this group exhibited enhanced activity at 320 ms after stimulus. Consistent with previous studies,
I describe methods for the detection of brain activation and functional connectivity in cortically constrained maps of current density computed from magnetoencephalography (MEG) data using multivariate statistical analysis. I apply time-frequency (wavelet) analysis to individual epochs to produce dynamic images of brain signal power on the cerebral cortex in multiple time-frequency bands, and I form observation matrices by putting together the power from all frequency bands and all trials. To detect changes in brain activity, I fit these observations into separate multivariate linear models for each time band and cortical location with experimental conditions as predictor variables; the resulting Roys maximum statistic maps are thresholded for significance using permutation tests and the maximum statistic approach. A source is considered significant if it exceeds a statistical threshold, which is chosen to control the familywise error rate, or the probability of at least one false positive, ...
The aim of the present study was to analyse the magnetoencephalogram (MEG) background activity in patients with Alzheimers disease (AD) using the Lempel-Ziv (LZ) complexity. This non-linear method measures the complexity of finite sequences and is related to the number of distinct substrings and the rate of their occurrence along the sequence. The MEGs were recorded with a 148-channel whole-head magnetometer (MAGNES 2500 WH, 4D Neuroimaging) in 21 patients with AD and in 21 age-matched control subjects. Artefact-free epochs were selected for complexity analysis. Results showed that MEG signals from AD patients had lower complexity than control subjects MEGs and the differences were statistically significant (p,0.01). In order to reduce the dimension of the LZ complexity results, a principal components analysis (PCA) was applied, and only the first principal component was retained. The first component score from PCA was graphically analysed using a box plot and a receiver-operating ...
Magnetoencephalography (MEG) is used to measure the auditory evoked magnetic field (AEF), which reflects language-related performance. In young children, however, the simultaneous quantification of the bilateral auditory-evoked response during binaural hearing is difficult using conventional adult-sized MEG systems. Recently, a child-customised MEG device has facilitated the acquisition of bi-hemispheric recordings, even in young children. Using the child-customised MEG device, we previously reported that language-related performance was reflected in the strength of the early component (P50m) of the auditory evoked magnetic field (AEF) in typically developing (TD) young children (2 to 5 years old) [Eur J Neurosci 2012, 35:644-650]. The aim of this study was to investigate how this neurophysiological index in each hemisphere is correlated with language performance in autism spectrum disorder (ASD) and TD children. We used magnetoencephalography (MEG) to measure the auditory evoked magnetic field (AEF),
In this study, we aimed to explore the possibility of evaluating the attitudes of subjects as to whether they liked or disliked visually presented pictures. We measured magnetoencephalgraphic (MEG) responses and conducted a phase analysis of the specific alpha band frequency component. We gave ten subjects a questionnaire with images of animals prepared beforehand. We selected 30 pictures, from which 15 pictures were used as positive impression images (Good Images) and 15 pictures as negative impression images (Bad Images). The MEG responses were measured with a 122-channel magnetometer system. We obtained the power spectrum of MEG responses and carried out a phase analysis of the peak frequency of the alpha band. As a result, significant phase synchronicity was confirmed for the negative impression images.. ...
A new technique called constrained source space imaging is introduced that holds promise for ultrafast acquisition of functional magnetic resonance imaging data. A sparse set of arbitrarily positioned, coarse voxels is first localized using radiofrequency selective excitation, from which magnetization signals are separated using only the spatial sensitivities of multichannel receiver coils, without the need for k-space encoding using imaging gradients. This method permits very fast acquisitions of targeted magnetization without complex or time-consuming image reconstruction techniques. Furthermore, because the data acquisition is performed without imaging gradients, T2* decays can be densely sampled and processed for contrast enhancement to improve functional magnetic resonance imaging data quality. Here, the constrained source space imaging technique is validated in proof-of-concept form, for a simple functional magnetic resonance imaging motor task using a prototype dual-band stimulated echo
To provide an effective substrate for cognitive processes, functional brain networks should be able to reorganize and coordinate on a sub-second temporal scale. We used magnetoencephalography recordings of spontaneous activity to characterize whole-brain functional connectivity dynamics at high temporal resolution. Using a novel approach that identifies the points in time at which unique patterns of activity recur, we reveal transient (100-200 ms) brain states with spatial topographies similar to those of well-known resting state networks. By assessing temporal changes in the occurrence of these states, we demonstrate that within-network functional connectivity is underpinned by coordinated neuronal dynamics that fluctuate much more rapidly than has previously been shown. We further evaluate cross-network interactions, and show that anticorrelation between the default mode network and parietal regions of the dorsal attention network is consistent with an inability of the system to transition directly
Spatially focal source estimates for magnetoencephalography (MEG) and electroencephalography (EEG) data can be obtained by imposing a minimum ℓ1-norm constraint on the distribution of the source currents. Anatomical information about the expected locations and orientations of the sources can be included in the source models. In particular, the sources can be assumed to be oriented perpendicular to the cortical surface. We introduce a minimum ℓ1-norm estimation source modeling approach with loose orientation constraints (ℓ1LOC), which integrates the estimation of the orientation, location, and strength of the source currents into a cost function to jointly model the residual error and the ℓ1-norm of the source estimates. Evaluation with simulated MEG data indicated that the ℓ1LOC method can provide low spatial dispersion, high localization accuracy, and high source detection rates. Application to somatosensory and auditory MEG data resulted in physiologically reasonable source ...
A lot of the neuroscience focuses on what happens in the brain when/before/after subject does/thinks/feels x. A lot, but not all. So what happens in the brain when subject is specifically told to NOT do/think/feel x. Jha et al. (2015) used magnetoencephalography, a non-invasive method to record the electrical activity of neurons, to see what…
The Electroencephalographiy (EEG) and Magnetoencephalography (MEG) are two non-invasive imaging modalities that measures the brain activity. Obtaining the brain activity with the distributed source model from these measurements is an ill-posed problem due to the high number of unknowns compared to the number of measurements. A unique solution is obtained by assuming a prior on the sources. The idea is to reduce the solution space size from the number of sources (S) to a smaller space. Assuming that sources inside each functional region have equal activation allows us to reduce the number of columns in the leadfield matrix from S to a number of regions (K). These regions are obtained from a dMRI parcellation-based region growing algorithm. A region is assumed to contain sources that have similar fibers distribution. To obtain a sparse solution, we assume that only a few regions are active simultaneously. BIC1 is used to obtain the optimal number of regions (Kp) that explains the MEG/EEG data. We
This article describes how to record amygdala activity with magnetoencephalography (MEG). In addition this article will describe how to ...
[email protected] Abstract-Diagonal loading imparts Robustness to the adaptive beamformer against signal mismatch due to low sample support. It helps to achieve desired sidelobe level and to improve Signal to Interference plus Noise Ratio (SINR). In this paper, variants of Minimum Variance Distortionless Response-Sample Matrix Inversion (MVDR-SMI) beamformer with diagonal loading are analyzed. A novel hybrid algorithm, MVDR-SMI beamformer with Colored Adaptive Diagonal Loading is also proposed in this paper. The simulation experiments show improvement in directivity and SINR compared to other existing MVDR-SMI beamformers with diagonal loading. Index Terms- Smart Antenna, Adaptive beamforming, Uniform Linear Array, Minimum Variance Distortionless Response Beamformer (MVDR), Sample-Matrix Inversion (SMI), and Adaptive colored diagonal loading. data) is low. The lower band on sidelobe levels of the beamformer when no interference sources were found at an angle is also calculated. Training ...
On a similar note, Gadolinium is sometimes injected before an MRI to increase the contrast of the tissue that needs to be imaged. Gadolinium is ferromagnetic, which is why it shows up well in an MRI and is used as a contrast dye. However, its not enough to cause any issues from the magnetic field.. Now all that said, even though the iron in the human body doesnt have ferromagnetic properties, there are still some lesser known effects magnets can have in an especially strong enough field.. For example, small animals like frogs and mice can be levitated in very powerful magnetic fields, because when a magnetic field is strong enough, the water and other elements including the iron in their body that arent normally magnetic experience the repulsive diamagnetic and attractive paramagnetic forces. These forces are much weaker than the ferromagnetic force that attracts iron, which is why it only becomes apparent with a very powerful magnet like the one at the National High Magnetic Field Laboratory ...
A new general linear model (GLM) beamformer method is described for processing magnetoencephalography (MEG) data. A standard nonlinear beamformer is used to determine the time course of neuronal activation for each point in a predefined source space. A Hilbert transform gives the envelope of oscillatory activity at each location in any chosen frequency band (not necessary in the case of sustained (DC) fields), enabling the general linear model to be applied and a volumetric T statistic image to be determined. The new method is illustrated by a two-source simulation (sustained field and 20 Hz) and is shown to provide accurate localization. The method is also shown to locate accurately the increasing and decreasing gamma activities to the temporal and frontal lobes, respectively, in the case of a scintillating scotoma. The new method brings the advantages of the general linear model to the analysis of MEG data and should prove useful for the localization of changing patterns of activity across all ...
MEG analysis involves enormous datasets that require vast computer processing power to manipulate them. Having overcome the initial difficulties in artefact identification, MEG data analysis still involves considerable complexity. The fundamental issue is that of the inverse problem. This concept, in relation to MEG, summarises the challenge of precisely localising in three dimensional (3D) space the underlying neural sources of a magnetic recording. In reality, there may be many equally plausible combinations of neural sources, and thus, without additional constraints the solution is not unique. Yet, this is a challenge our own brains overcome daily by using constraints that reflect sensible prior assumptions, for example in deciding if a visual object is small and close, or large and far away. We have existing expectations about object size to guide us.. Methods to solve the inverse problem, therefore, need to make additional assumptions, such as the brain activity being spatially sparse or ...
Beamformers are a widely-used tool in brain analysis with magnetoencephalography (MEG) and electroencephalography (EEG). For the construction of the beamformer filters realistic head volume conductor modeling is necessary for accurately computing the EEG and MEG leadfields, i.e., for solving the EEG and MEG forward problem. In this work, we investigate the influence of including realistic head tissue compartments into a finite element method (FEM) model on the beamformers localization ability. Specifically, we investigate the effect of including cerebrospinal fluid, gray matter, and white matter distinction, as well as segmenting the skull bone into compacta and spongiosa, and modeling white matter anisotropy. We simulate an interictal epileptic measurement with white sensor noise. Beamformer filters are constructed with unit gain, unit array gain, and unit noise gain constraint. Beamformer source positions are determined by evaluating power and excess sample kurtosis (g2) of the source-waveforms at
The reconstruction of brain sources from non-invasive electroencephalography (EEG) or magnetoencephalography (MEG) via source imaging can be distorted by information redundancy in case of high-resolution recordings. Dimensionality reduction approaches such as spatial projection may be used to alleviate this problem. In this proof-of-principle paper we apply spatial projection to solve the problem of information redundancy in case of source reconstruction via spatiotemporal Kalman filtering (STKF), which is based on state-space modeling. We compare two approaches for incorporating spatial projection into the STKF algorithm and select the best approach based on its performance in source localization with respect to accurate estimation of source location, lack of spurious sources, computational speed and small number of required optimization steps in state-space model parameter estimation. We use state-of-the-art simulated EEG data based on neuronal population models, for which the number and location of
Chapters two and three introduce the physiological origins of the MEG signal and the instrumentation required to record it. Chapter four describes data acquisition and preprocessing, from the methods used in the recruitment of participants to the scanning parameters employed for our MEG and MRI acquisitions. Chapters five to seven present three empirical studies. The first investigates the relationship between MEG derived measurements of functional connectivity and cortical myeloarchitecture. We demonstrate that covariation of cortical myelin is significantly predicted by MEG-derived measurements of functional connectivity both within individual frequency bands and by their linear and non-linear combination. Chapter six presents an exploratory analysis into the impact of aging and sex-differences on MEG derived measurements of sensorimotor responses and whole-brain functional connectivity. We find trends indicating increased oscillatory responses with age. Further, we find female volunteers to ...
When choosing between two options, correlates of their value are represented in neural activity throughout the brain. Whether these representations reflect activity that is fundamental to the computational process of value comparison, as opposed to other computations covarying with value, is unknown. We investigated activity in a biophysically plausible network model that transforms inputs relating to value into categorical choices. A set of characteristic time-varying signals emerged that reflect value comparison. We tested these model predictions using magnetoencephalography data recorded from human subjects performing value-guided decisions. Parietal and prefrontal signals matched closely with model predictions. These results provide a mechanistic explanation of neural signals recorded during value-guided choice and a means of distinguishing computational roles of different cortical regions whose activity covaries with value.
i. Shepherd, G M. The Major Senses: Sight, Hearing, Smell, Taste, and Touch-The Dana Guide. Dana Foundation website. November 2007 http://www.dana.org/news/brainhealth/detail.aspx?id=10064. ii. Stein, J.F. Neuroscience: an introduction. Wiley. 2006. iii. Henshaw, J. M. A Tour of the Senses: how your brain interprets the world. Johns Hopkins University Press. 2012. iv. Bossomaier, T. R. J. Introduction to the Senses: from biology to computer science. Cambridge University Press. 2012. v. Brynie, F.H. Brain Sense: the science of the senses and how we process the world around us. Amacom. 2009. vi. The Brain from Top to Bottom: The Senses: Vision. Canadian Institute of Health Research; Institute of Neurosciences, Mental Health and Addiction. http://thebrain.mcgill.ca/flash/a/a_02/a_02_cr/a_02_cr_vis/a_02_cr_vis.html. vii. Lu, Z.-L., & Sperling, G. Measuring sensory memory: Magnetoencephalography habituation and psychophysics. In Z.-L. Lu & L. Kaufman (Eds.) Magnetic source imaging of the human brain. ...
i. Shepherd, G M. The Major Senses: Sight, Hearing, Smell, Taste, and Touch-The Dana Guide. Dana Foundation website. November 2007 http://www.dana.org/news/brainhealth/detail.aspx?id=10064. ii. Stein, J.F. Neuroscience: an introduction. Wiley. 2006. iii. Henshaw, J. M. A Tour of the Senses: how your brain interprets the world. Johns Hopkins University Press. 2012. iv. Bossomaier, T. R. J. Introduction to the Senses: from biology to computer science. Cambridge University Press. 2012. v. Brynie, F.H. Brain Sense: the science of the senses and how we process the world around us. Amacom. 2009. vi. The Brain from Top to Bottom: The Senses: Vision. Canadian Institute of Health Research; Institute of Neurosciences, Mental Health and Addiction. http://thebrain.mcgill.ca/flash/a/a_02/a_02_cr/a_02_cr_vis/a_02_cr_vis.html. vii. Lu, Z.-L., & Sperling, G. Measuring sensory memory: Magnetoencephalography habituation and psychophysics. In Z.-L. Lu & L. Kaufman (Eds.) Magnetic source imaging of the human brain. ...
Predictive coding suggests that the brain infers the causes of its sensations by combining sensory evidence with internal predictions based on available prior knowledge. However, the neurophysiological correlates of (pre-)activated prior knowledge serving these predictions are still unknown. Based on the idea that such pre-activated prior knowledge must be maintained until needed we measured the amount of maintained information in neural signals via the active information storage (AIS) measure. AIS was calculated on whole-brain beamformer-reconstructed source time-courses from magnetoencephalography (MEG) recordings of 52 human subjects during the baseline of a Mooney face/house detection task. Pre-activation of prior knowledge for faces showed as alpha- and beta-band related AIS increases in content specific areas; these AIS increases were behaviourally relevant in brain area FFA. Further, AIS allowed decoding of the cued category on a trial-by-trial basis. Our results support accounts that ...
Magnetoencephalography (MEG) and electroencephalography (EEG) are imaging methods that measure neuronal dynamics non invasively with high temporal precision. It is often desired in MEG and EEG analysis to estimate the neu-ral sources of the signals. Strategies used for this purpose often take into account the covariance between sensors to yield more precise estimates of the sources. Here we investigate in greater detail how the quality of such covariance estimates conditions the estimation of MEG and EEG sources. We investigated three distinct source localization methods: dynamic Statistical Parametric Maps (dSPM), the linearly constrained minimum variance (LCMV) beamformer and Mixed-Norm Estimates (MxNE). We implemented and evaluated automated strategies for improving the quality of covariance estimates at different stages of data processing. Our results show that irrespective of the source localization method, accuracy can suffer from improper covariance estimation but can be improved by relying on
In this study, we identified a mechanism by which event-related fields can be produced from oscillatory brain activity. We demonstrated that amplitude fluctuations of ongoing oscillations with respect to peaks and troughs are not symmetrically modulated. Because of this asymmetry, slow ERFs are produced from the amplitude modulations of the ∼10 Hz alpha activity in response to visual stimuli. It is important to note that the amplitude fluctuations of the oscillatory activity can remain asymmetric throughout the trial; however, it is primarily the asymmetric modulations in response to a stimulus that are important here. Had the magnitudes of the peaks and troughs been symmetrically decreased, no shift in the ERF would have been generated (Fig. 1C). Our findings support studies by, for example, Stam et al. (1999) and Breakspear and Terry (2002), challenging the conventional view that ongoing EEG/MEG signals are linear with a Gaussian distribution.. Although our analysis is based on MEG data, the ...
This study uses a placebo-controlled, crossover design to investigate the effect of modafinil (100 mg, p.o.), methylphenidate (20 mg, p.o.), and lorazepam (1 mg, p.o.) in 15 healthy male volunteers. The acute effect of the medications will be measured by MEG, EEG and simple cognition testing. Study procedures will be performed over 5 separate days. During an initial screening visit, Study Day 1, subjects will consent to enroll and undergo clinical evaluation sufficient to determine they are eligible to participate in the study. Upon qualification and enrollment, subjects will be randomly assigned to receive either placebo or one of the active medications on Study Days 2 - 5. Medications or placebo will be administered orally. Subjects will arrive at the MEG center in the morning on Study Day 2 and baseline MEG and EEG scans will be performed along with baseline cognition testing. The medication or placebo will be administered immediately following the baseline scans and cognition testing. ...
March 13, 2007 C.H. Wolters. EEG/MEG-based source reconstruction of cerebral activity is an important tool both in clinical practice and research and in cognitive neuroscience. . . .. ...
A nearly $4 million project, funded by National Science Foundation, to design and build the first MEG system designed specifically for
My research concerns spatiotemporal imaging of human brain function. I have applied integrated magnetoencephalography (MEG), electroencephalography (EEG), and functional magnetic resonance imaging (fMRI) to studies of cortical processing of visual information, including contrast patterns and visual motion. My research involves development of techniques for the analysis of multimodal biomedical imaging data, in particular, for the use of fMRI data to inform the source estimation (inverse problem) of MEG and EEG. Currently I am studying theoretical characteristics of the sensitivity of MEG and EEG sensor arrays and the cancellation of signals when multiple brain areas are active simultaneously. I am applying the source estimation methods to experimental data in collaboration with several researches how are using MEG/EEG/fMRI to study cognitive functions in normal and clinical populations, including dyslexia, obsessive-compulsive disorder, and migraine.. ...
Current imaging modalities include the Electroencephalogram (EEG) which records electrical voltages from electrodes placed on the scalp and the Magnetoencephalogram (MEG) which records the magnetic field from SQUID sensors placed above the head. Both MEG and EEG have a high temporal resolution (milliseconds), capable of detecting e.g., the 40Hz Gamma response implicated in object representation (Tallon-Baudry and Bertrand, 1999). Their spatial resolution is, however, usually of the order of centimeters rather than millimeters. This varies a great deal, depending on the nature of the neuronal activity one is trying to localize. It depends in particular on the number of sources that is activated at the time data is recorded. In practice this implies that e.g. for isolating subtle cognitive components, a lower resolution is to be expected, whilst the stronger early components of an auditory response can be localized to within millimeters in the brainstem. In contrast, functional Magnetic Resonance ...
We assess the suitability of conventional parametric statistics for analyzing oscillatory activity, as measured with electroencephalography/magnetoencephalography (EEG/MEG). The approach we consider is based on narrow-band power time-frequency decompositions of single-trial data. The ensuing power measures have a chi(2)-distribution. The use of the general linear model (GLM) under normal error assumptions is, therefore, difficult to motivate for these data. This is unfortunate because the GLM plays a central role in classical inference and is the standard estimation and inference framework for neuroimaging data. The key contribution of this work is to show that, in many circumstances, one can appeal to the central limit theorem and assume normality for generative models of power. If this is not appropriate, one can transform the data to render the error terms approximately normal. These considerations allow one to analyze induced and evoked oscillations using standard frameworks like statistical
Researchers from the University of Minnesota Medical School and Brain Sciences Center at the Minneapolis VA Medical Center have identified a way to diagnose Alzheimers and other brain diseases. Using magnetoencephalography (MEG) and various mathematic algorithms, the researchers were able to identify and classify the brain disease in 142 research subjects that had been previously diagnosed. Magnetoencephalography is a non-invasive measurement of magnetic fields in the brain and the tests last between 45-60 seconds ...
arousal consciousness neural systems fMRI motor cortex EEG MEG microdialysis epilepsy 46-6079A 617-324-1880 … sources of neural activity in the brain from EEG and MEG recordings made during cognitive, motor and somatosensory … ...
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Some wounded soldiers leaving the war-zones in Iraq and Afghanistan have arrived home only to find themselves caught in the crossfire of a new battle - a legal one. For some of the 300,000 or more members of the armed forces who suffer from post-traumatic stress disorder (PTSD), the legal battle ensuing from the Veterans Administrations denial of long-term disability benefits is extremely important. Without these government benefits, vulnerable veterans who are not prepared to Continue Reading →. ...
Non-invasive MEG recordings reveal that patterns of spontaneous activity in the resting brain are shorter lived than previously thought.
Magnetoencephalogram Systems developed at KIT IEEE Trans. Applied Superconduct. Vol. 9, No.2, June 1999, pp.4057-4062 Three Axis SQUID Magnetometers for Low-Frequency Geophysical Applications IEEE Trans. Magnetics, Vol.35, No.5, September 1999, pp.3974...
Welcome to the Magnetoencephalography (MEG) Lab at the McGovern Institute for Brain Research at MIT.. MEG is a safe and noninvasive technology for measuring human brain activity. It is based on detection of the tiny magnetic fluctuations caused by electrical currents within the brain. An array of sensitive detectors surrounds the head, measuring magnetic signals with millisecond precision and allowing researchers to study the rapid brain events that underlie human cognition.. Our MEG scanner, an Elekta Neuromag Triux with 306 channels plus 128 channels for EEG, was installed in 2011 and is the first of its kind in North America. It is housed within a magnetically shielded room to reduce background noise.. The MEG lab is part of the Martinos Imaging Center at MIT, operating as a core facility, and accessible to all members of the local research community. Potential users should contact Dimitrios Pantazis for more information ...
Described herein is a non-invasive determination of locations of neural activity in a brain. In particular, methods and systems have been developed that utilize a FINES algorithm for use in three-dimensional (3-D) dipole source localization to locate neural activity in a brain.
The forward module contains functions with a user interface that will be easily understood by experimenced programmers and methods developers and can be considered medium-level functions. They have a clear and consistent programming interface (API) which hides the specific details particular volume conduction models and that allows software developers to write forward methods without having to worry about integrating it with the inverse methods worry about data handling. The low-level functions on which the functions in the forward module depend are located in a private subdirectory which is not accessible from the MATLAB command line. The forward module is complemented by an inverse module that contains the implementation of various high-quality inverse source estimation algorithms, such as dipole fitting, beamforming and linear estimation using the minimum-norm approach. Instead of implementing all forward methods completely from scratch, the FieldTrip forward module makes use of some high ...
In this report, we study the problem of the three-dimensional reconstruction of the electrical activity of the brain from electroencephalography (EEG) and magnetoencephalography (MEG). We use a variational approach based upon three main methods and ideas. The first one is the optimal control of systems governed by elliptic partial differential equations, the second is the regularization of the solutions while preserving the discontinuities (the edges), and the third one is the use of geometric information obtained from magnetic resonance images (MRI) to constrain the solutions in an anatomically «reasonable» way.
Many important real world problems give rise to an Inverse problem (IP). These include medical imaging, non-destructive testing, oil and gas exploration, land-mine detection and process control. For example, in the exploration for oil and gas, one needs to assess the structure of the interior of the earth from observations made at the surface. Typically, an explosion is created and the resulting shockwaves together with their reflections are used to build a model of the structure of the earth. In magnetoencephalography one needs to determine the electric current in the neurones from the measurement of the magnetic field outside the head. In the field of medical imaging IP forms an important tool in diagnostic investigations. For example, PET and SPECT are two modern imaging techniques whose success is dependent on solving IPs.. At their simplest level IP are concerned with obtaining information about the interior of a body from data which is available at its surface. Mathematically, this is a ...
A collaborative workspace for analyses of brain imaging data. Occupancy expected early 2017.. I-LABS faculty and researchers tackle some of the greatest questions about how children learn languages, how they develop socially and emotionally, how their cognition skills grow and how their brains develop physically. I-LABS findings serve not only academic researchers and scholars, but also clinicians, educators, legislators, policy-makers and families around the world who can utilize I-LABS research in tangible and practical ways every day.. I-LABS integrates multiple brain-imaging tools in novel ways to discover the mechanisms of early learning. These tools include magnetoencephalography (MEG), electroencephalography (EEG), magnetic resonance imaging (MRI and fMRI) and diffusion tensor imaging (DTI). Since its arrival, I-LABS MEG machine has attracted worldwide attention from scientists and visitors across Europe, Asia and the Middle East.. To facilitate I-LABS growing integrative work, an ...
We studied 24 pairs of participants engaged in real-time controlled interactions (18) and measured neural activity with magnetoencephalography (MEG) from one participant within each pair. Each pair of participants played an interactive game that requires the generation and understanding of novel, mutually negotiated communicative actions (i.e., communicative interactions between a "Communicator" and an "Addressee" pair; Fig. 1 and Movie S1). We distinguished neural activity specifically associated with those communicative actions from activity evoked during another interactive game that involved the same stimuli, responses, attention, and between-participant dependencies but no communicative necessities (i.e., instrumental interactions between a "Salesman" and a "Roadworker" pair; Fig. 1 and Movie S2). Within each task, participants alternated between those two task-specific roles on a trial-by-trial basis (80 trials in each task). We further distinguished neural activity common to both ...
This lecture series covers a number of mathematical methods that are used in the analysis of brain imaging data. Each lecture describes a different category of model and shows how it is applied to a particular aspect of brain imaging analysis. The applications cover data from functional Magnetic Resonance Imaging (fMRI), Magnetoencephalography (MEG) and Electroencephalography (EEG ...
Research report provides a comprehensive review of brain monitoring devices market by the following Products: IntraCranial Pressure (ICP) Monitors, Electroencephalography (EEG) Devices and Magnetoencephalography (MEG) Devices.
The purpose of this study is the use of magnetoencephalography or MEG (a machine that measures magnetic activity in your brain) and electroencephalography or
Brain, Back, Cost, Memory, Neuroimaging, Organization, Working Memory, Lead, Clustering, Efficiency, Future, Longitudinal Studies, Magnetoencephalography, Metric, Rest, Electrodes, Human, Investigator, Nervous System, Neuroscience