Consistency of magnetoencephalographic functional connectivity and network reconstruction using a template versus native MRI for co‐registration

PubMed Central

Douw, Linda; Stam, Cornelis J.; Tewarie, Prejaas; Hillebrand, Arjan

2017-01-01

Abstract Introduction Studies using functional connectivity and network analyses based on magnetoencephalography (MEG) with source localization are rapidly emerging in neuroscientific literature. However, these analyses currently depend on the availability of costly and sometimes burdensome individual MR scans for co‐registration. We evaluated the consistency of these measures when using a template MRI, instead of native MRI, for the analysis of functional connectivity and network topology. Methods Seventeen healthy participants underwent resting‐state eyes‐closed MEG and anatomical MRI. These data were projected into source space using an atlas‐based peak voxel and a centroid beamforming approach either using (1) participants’ native MRIs or (2) the Montreal Neurological Institute's template. For both methods, time series were reconstructed from 78 cortical atlas regions. Relative power was determined in six classical frequency bands per region and globally averaged. Functional connectivity (phase lag index) between each pair of regions was calculated. The adjacency matrices were then used to reconstruct functional networks, of which regional and global metrics were determined. Intraclass correlation coefficients were calculated and Bland–Altman plots were made to quantify the consistency and potential bias of the use of template versus native MRI. Results Co‐registration with the template yielded largely consistent relative power, connectivity, and network estimates compared to native MRI. Discussion These findings indicate that there is no (systematic) bias or inconsistency between template and native MRI co‐registration of MEG. They open up possibilities for retrospective and prospective analyses to MEG datasets in the general population that have no native MRIs available. Hum Brain Mapp, 2017. © 2017 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. Hum Brain Mapp 39:104–119, 2018. © 2017 Wiley Periodicals, Inc. PMID:28990264

Hyperedge bundling: A practical solution to spurious interactions in MEG/EEG source connectivity analyses.

PubMed

Wang, Sheng H; Lobier, Muriel; Siebenhühner, Felix; Puoliväli, Tuomas; Palva, Satu; Palva, J Matias

2018-06-01

Inter-areal functional connectivity (FC), neuronal synchronization in particular, is thought to constitute a key systems-level mechanism for coordination of neuronal processing and communication between brain regions. Evidence to support this hypothesis has been gained largely using invasive electrophysiological approaches. In humans, neuronal activity can be non-invasively recorded only with magneto- and electroencephalography (MEG/EEG), which have been used to assess FC networks with high temporal resolution and whole-scalp coverage. However, even in source-reconstructed MEG/EEG data, signal mixing, or "source leakage", is a significant confounder for FC analyses and network localization. Signal mixing leads to two distinct kinds of false-positive observations: artificial interactions (AI) caused directly by mixing and spurious interactions (SI) arising indirectly from the spread of signals from true interacting sources to nearby false loci. To date, several interaction metrics have been developed to solve the AI problem, but the SI problem has remained largely intractable in MEG/EEG all-to-all source connectivity studies. Here, we advance a novel approach for correcting SIs in FC analyses using source-reconstructed MEG/EEG data. Our approach is to bundle observed FC connections into hyperedges by their adjacency in signal mixing. Using realistic simulations, we show here that bundling yields hyperedges with good separability of true positives and little loss in the true positive rate. Hyperedge bundling thus significantly decreases graph noise by minimizing the false-positive to true-positive ratio. Finally, we demonstrate the advantage of edge bundling in the visualization of large-scale cortical networks with real MEG data. We propose that hypergraphs yielded by bundling represent well the set of true cortical interactions that are detectable and dissociable in MEG/EEG connectivity analysis. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Sensor Level Functional Connectivity Topography Comparison Between Different References Based EEG and MEG

PubMed Central

Huang, Yunzhi; Zhang, Junpeng; Cui, Yuan; Yang, Gang; Liu, Qi; Yin, Guangfu

2018-01-01

Sensor-level functional connectivity topography (sFCT) contributes significantly to our understanding of brain networks. sFCT can be constructed using either electroencephalography (EEG) or magnetoencephalography (MEG). Here, we compared sFCT within the EEG modality and between EEG and MEG modalities. We first used simulations to look at how different EEG references—including the Reference Electrode Standardization Technique (REST), average reference (AR), linked mastoids (LM), and left mastoid references (LR)—affect EEG-based sFCT. The results showed that REST decreased the reference effects on scalp EEG recordings, making REST-based sFCT closer to the ground truth (sFCT based on ideal recordings). For the inter-modality simulation comparisons, we compared each type of EEG-sFCT with MEG-sFCT using three metrics to quantize the differences: Relative Error (RE), Overlap Rate (OR), and Hamming Distance (HD). When two sFCTs are similar, RE and HD are low, while OR is high. Results showed that among all reference schemes, EEG-and MEG-sFCT were most similar when the EEG was REST-based and the EEG and MEG were recorded simultaneously. Next, we analyzed simultaneously recorded MEG and EEG data from publicly available face-recognition experiments using a similar procedure as in the simulations. The results showed (1) if MEG-sFCT is the standard, REST—and LM-based sFCT provided results closer to this standard in the terms of HD; (2) REST-based sFCT and MEG-sFCT had the highest similarity in terms of RE; (3) REST-based sFCT had the most overlapping edges with MEG-sFCT in terms of OR. This study thus provides new insights into the effect of different reference schemes on sFCT and the similarity between MEG and EEG in terms of sFCT. PMID:29867395

MEG connectivity analysis in patients with Alzheimer's disease using cross mutual information and spectral coherence.

PubMed

Alonso, Joan Francesc; Poza, Jesús; Mañanas, Miguel Angel; Romero, Sergio; Fernández, Alberto; Hornero, Roberto

2011-01-01

Alzheimer's disease (AD) is an irreversible brain disorder which represents the most common form of dementia in western countries. An early and accurate diagnosis of AD would enable to develop new strategies for managing the disease; however, nowadays there is no single test that can accurately predict the development of AD. In this sense, only a few studies have focused on the magnetoencephalographic (MEG) AD connectivity patterns. This study compares brain connectivity in terms of linear and nonlinear couplings by means of spectral coherence and cross mutual information function (CMIF), respectively. The variables defined from these functions provide statistically significant differences (p < 0.05) between AD patients and control subjects, especially the variables obtained from CMIF. The results suggest that AD is characterized by both decreases and increases of functional couplings in different frequency bands as well as by an increase in regularity, that is, more evident statistical deterministic relationships in AD patients' MEG connectivity. The significant differences obtained indicate that AD could disturb brain interactions causing abnormal brain connectivity and operation. Furthermore, the combination of coherence and CMIF features to perform a diagnostic test based on logistic regression improved the tests based on individual variables for its robustness.

Functional connectivity changes detected with magnetoencephalography after mild traumatic brain injury

PubMed Central

Dimitriadis, Stavros I.; Zouridakis, George; Rezaie, Roozbeh; Babajani-Feremi, Abbas; Papanicolaou, Andrew C.

2015-01-01

Mild traumatic brain injury (mTBI) may affect normal cognition and behavior by disrupting the functional connectivity networks that mediate efficient communication among brain regions. In this study, we analyzed brain connectivity profiles from resting state Magnetoencephalographic (MEG) recordings obtained from 31 mTBI patients and 55 normal controls. We used phase-locking value estimates to compute functional connectivity graphs to quantify frequency-specific couplings between sensors at various frequency bands. Overall, normal controls showed a dense network of strong local connections and a limited number of long-range connections that accounted for approximately 20% of all connections, whereas mTBI patients showed networks characterized by weak local connections and strong long-range connections that accounted for more than 60% of all connections. Comparison of the two distinct general patterns at different frequencies using a tensor representation for the connectivity graphs and tensor subspace analysis for optimal feature extraction showed that mTBI patients could be separated from normal controls with 100% classification accuracy in the alpha band. These encouraging findings support the hypothesis that MEG-based functional connectivity patterns may be used as biomarkers that can provide more accurate diagnoses, help guide treatment, and monitor effectiveness of intervention in mTBI. PMID:26640764

A symmetric multivariate leakage correction for MEG connectomes

PubMed Central

Colclough, G.L.; Brookes, M.J.; Smith, S.M.; Woolrich, M.W.

2015-01-01

Ambiguities in the source reconstruction of magnetoencephalographic (MEG) measurements can cause spurious correlations between estimated source time-courses. In this paper, we propose a symmetric orthogonalisation method to correct for these artificial correlations between a set of multiple regions of interest (ROIs). This process enables the straightforward application of network modelling methods, including partial correlation or multivariate autoregressive modelling, to infer connectomes, or functional networks, from the corrected ROIs. Here, we apply the correction to simulated MEG recordings of simple networks and to a resting-state dataset collected from eight subjects, before computing the partial correlations between power envelopes of the corrected ROItime-courses. We show accurate reconstruction of our simulated networks, and in the analysis of real MEGresting-state connectivity, we find dense bilateral connections within the motor and visual networks, together with longer-range direct fronto-parietal connections. PMID:25862259

Beamformer source analysis and connectivity on concurrent EEG and MEG data during voluntary movements.

PubMed

Muthuraman, Muthuraman; Hellriegel, Helge; Hoogenboom, Nienke; Anwar, Abdul Rauf; Mideksa, Kidist Gebremariam; Krause, Holger; Schnitzler, Alfons; Deuschl, Günther; Raethjen, Jan

2014-01-01

Electroencephalography (EEG) and magnetoencephalography (MEG) are the two modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different source analysis methods, to locate the dipoles in the brain from which these dynamics originate, have been readily applied to both modalities alone. However, direct comparisons and possible advantages of combining both modalities have rarely been assessed during voluntary movements using coherent source analysis. In the present study, the cortical and sub-cortical network of coherent sources at the finger tapping task frequency (2-4 Hz) and the modes of interaction within this network were analysed in 15 healthy subjects using a beamformer approach called the dynamic imaging of coherent sources (DICS) with subsequent source signal reconstruction and renormalized partial directed coherence analysis (RPDC). MEG and EEG data were recorded simultaneously allowing the comparison of each of the modalities separately to that of the combined approach. We found the identified network of coherent sources for the finger tapping task as described in earlier studies when using only the MEG or combined MEG+EEG whereas the EEG data alone failed to detect single sub-cortical sources. The signal-to-noise ratio (SNR) level of the coherent rhythmic activity at the tapping frequency in MEG and combined MEG+EEG data was significantly higher than EEG alone. The functional connectivity analysis revealed that the combined approach had more active connections compared to either of the modalities during the finger tapping (FT) task. These results indicate that MEG is superior in the detection of deep coherent sources and that the SNR seems to be more vital than the sensitivity to theoretical dipole orientation and the volume conduction effect in the case of EEG.

Beamformer Source Analysis and Connectivity on Concurrent EEG and MEG Data during Voluntary Movements

PubMed Central

Muthuraman, Muthuraman; Hellriegel, Helge; Hoogenboom, Nienke; Anwar, Abdul Rauf; Mideksa, Kidist Gebremariam; Krause, Holger; Schnitzler, Alfons; Deuschl, Günther; Raethjen, Jan

2014-01-01

Electroencephalography (EEG) and magnetoencephalography (MEG) are the two modalities for measuring neuronal dynamics at a millisecond temporal resolution. Different source analysis methods, to locate the dipoles in the brain from which these dynamics originate, have been readily applied to both modalities alone. However, direct comparisons and possible advantages of combining both modalities have rarely been assessed during voluntary movements using coherent source analysis. In the present study, the cortical and sub-cortical network of coherent sources at the finger tapping task frequency (2–4 Hz) and the modes of interaction within this network were analysed in 15 healthy subjects using a beamformer approach called the dynamic imaging of coherent sources (DICS) with subsequent source signal reconstruction and renormalized partial directed coherence analysis (RPDC). MEG and EEG data were recorded simultaneously allowing the comparison of each of the modalities separately to that of the combined approach. We found the identified network of coherent sources for the finger tapping task as described in earlier studies when using only the MEG or combined MEG+EEG whereas the EEG data alone failed to detect single sub-cortical sources. The signal-to-noise ratio (SNR) level of the coherent rhythmic activity at the tapping frequency in MEG and combined MEG+EEG data was significantly higher than EEG alone. The functional connectivity analysis revealed that the combined approach had more active connections compared to either of the modalities during the finger tapping (FT) task. These results indicate that MEG is superior in the detection of deep coherent sources and that the SNR seems to be more vital than the sensitivity to theoretical dipole orientation and the volume conduction effect in the case of EEG. PMID:24618596

Multimodal effective connectivity analysis reveals seizure focus and propagation in musicogenic epilepsy.

PubMed

Klamer, Silke; Rona, Sabine; Elshahabi, Adham; Lerche, Holger; Braun, Christoph; Honegger, Jürgen; Erb, Michael; Focke, Niels K

2015-06-01

Dynamic causal modeling (DCM) is a method to non-invasively assess effective connectivity between brain regions. 'Musicogenic epilepsy' is a rare reflex epilepsy syndrome in which seizures can be elicited by musical stimuli and thus represents a unique possibility to investigate complex human brain networks and test connectivity analysis tools. We investigated effective connectivity in a case of musicogenic epilepsy using DCM for fMRI, high-density (hd-) EEG and MEG and validated results with intracranial EEG recordings. A patient with musicogenic seizures was examined using hd-EEG/fMRI and simultaneous '256-channel hd-EEG'/'whole head MEG' to characterize the epileptogenic focus and propagation effects using source analysis techniques and DCM. Results were validated with invasive EEG recordings. We recorded one seizure with hd-EEG/fMRI and four auras with hd-EEG/MEG. During the seizures, increases of activity could be observed in the right mesial temporal region as well as bilateral mesial frontal regions. Effective connectivity analysis of fMRI and hd-EEG/MEG indicated that right mesial temporal neuronal activity drives changes in the frontal areas consistently in all three modalities, which was confirmed by the results of invasive EEG recordings. Seizures thus seem to originate in the right mesial temporal lobe and propagate to mesial frontal regions. Using DCM for fMRI, hd-EEG and MEG we were able to correctly localize focus and propagation of epileptic activity and thereby characterize the underlying epileptic network in a patient with musicogenic epilepsy. The concordance between all three functional modalities validated by invasive monitoring is noteworthy, both for epileptic activity spread as well as for effective connectivity analysis in general. Copyright © 2015 Elsevier Inc. All rights reserved.

Dissociation of face-selective cortical responses by attention.

PubMed

Furey, Maura L; Tanskanen, Topi; Beauchamp, Michael S; Avikainen, Sari; Uutela, Kimmo; Hari, Riitta; Haxby, James V

2006-01-24

We studied attentional modulation of cortical processing of faces and houses with functional MRI and magnetoencephalography (MEG). MEG detected an early, transient face-selective response. Directing attention to houses in "double-exposure" pictures of superimposed faces and houses strongly suppressed the characteristic, face-selective functional MRI response in the fusiform gyrus. By contrast, attention had no effect on the M170, the early, face-selective response detected with MEG. Late (>190 ms) category-related MEG responses elicited by faces and houses, however, were strongly modulated by attention. These results indicate that hemodynamic and electrophysiological measures of face-selective cortical processing complement each other. The hemodynamic signals reflect primarily late responses that can be modulated by feedback connections. By contrast, the early, face-specific M170 that was not modulated by attention likely reflects a rapid, feed-forward phase of face-selective processing.

Predicting haemodynamic networks using electrophysiology: The role of non-linear and cross-frequency interactions

PubMed Central

Tewarie, P.; Bright, M.G.; Hillebrand, A.; Robson, S.E.; Gascoyne, L.E.; Morris, P.G.; Meier, J.; Van Mieghem, P.; Brookes, M.J.

2016-01-01

Understanding the electrophysiological basis of resting state networks (RSNs) in the human brain is a critical step towards elucidating how inter-areal connectivity supports healthy brain function. In recent years, the relationship between RSNs (typically measured using haemodynamic signals) and electrophysiology has been explored using functional Magnetic Resonance Imaging (fMRI) and magnetoencephalography (MEG). Significant progress has been made, with similar spatial structure observable in both modalities. However, there is a pressing need to understand this relationship beyond simple visual similarity of RSN patterns. Here, we introduce a mathematical model to predict fMRI-based RSNs using MEG. Our unique model, based upon a multivariate Taylor series, incorporates both phase and amplitude based MEG connectivity metrics, as well as linear and non-linear interactions within and between neural oscillations measured in multiple frequency bands. We show that including non-linear interactions, multiple frequency bands and cross-frequency terms significantly improves fMRI network prediction. This shows that fMRI connectivity is not only the result of direct electrophysiological connections, but is also driven by the overlap of connectivity profiles between separate regions. Our results indicate that a complete understanding of the electrophysiological basis of RSNs goes beyond simple frequency-specific analysis, and further exploration of non-linear and cross-frequency interactions will shed new light on distributed network connectivity, and its perturbation in pathology. PMID:26827811

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

PubMed

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical, inver-covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fMRI, MEG and EEG data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in MEG beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

Oscillations, networks, and their development: MEG connectivity changes with age.

PubMed

Schäfer, Carmen B; Morgan, Benjamin R; Ye, Annette X; Taylor, Margot J; Doesburg, Sam M

2014-10-01

Magnetoencephalographic (MEG) investigations of inter-regional amplitude correlations have yielded new insights into the organization and neurophysiology of resting-state networks (RSNs) first identified using fMRI. Inter-regional MEG amplitude correlations in adult RSNs have been shown to be most prominent in alpha and beta frequency ranges and to express strong congruence with RSN topologies found using fMRI. Despite such advances, little is known about how oscillatory connectivity in RSNs develops throughout childhood and adolescence. This study used a novel fMRI-guided MEG approach to investigate the maturation of resting-state amplitude correlations in physiologically relevant frequency ranges within and among six RSNs in 59 participants, aged 6-34 years. We report age-related increases in inter-regional amplitude correlations that were largest in alpha and beta frequency bands. In contrast to fMRI reports, these changes were observed both within and between the various RSNs analyzed. Our results provide the first evidence of developmental changes in spontaneous neurophysiological connectivity in source-resolved RSNs, which indicate increasing integration within and among intrinsic functional brain networks throughout childhood, adolescence, and early adulthood. Copyright © 2014 Wiley Periodicals, Inc.

Effect of Field Spread on Resting-State Magneto Encephalography Functional Network Analysis: A Computational Modeling Study.

PubMed

Silva Pereira, Silvana; Hindriks, Rikkert; Mühlberg, Stefanie; Maris, Eric; van Ede, Freek; Griffa, Alessandra; Hagmann, Patric; Deco, Gustavo

2017-11-01

A popular way to analyze resting-state electroencephalography (EEG) and magneto encephalography (MEG) data is to treat them as a functional network in which sensors are identified with nodes and the interaction between channel time series and the network connections. Although conceptually appealing, the network-theoretical approach to sensor-level EEG and MEG data is challenged by the fact that EEG and MEG time series are mixtures of source activity. It is, therefore, of interest to assess the relationship between functional networks of source activity and the ensuing sensor-level networks. Since these topological features are of high interest in experimental studies, we address the question of to what extent the network topology can be reconstructed from sensor-level functional connectivity (FC) measures in case of MEG data. Simple simulations that consider only a small number of regions do not allow to assess network properties; therefore, we use a diffusion magnetic resonance imaging-constrained whole-brain computational model of resting-state activity. Our motivation lies behind the fact that still many contributions found in the literature perform network analysis at sensor level, and we aim at showing the discrepancies between source- and sensor-level network topologies by using realistic simulations of resting-state cortical activity. Our main findings are that the effect of field spread on network topology depends on the type of interaction (instantaneous or lagged) and leads to an underestimation of lagged FC at sensor level due to instantaneous mixing of cortical signals, instantaneous interaction is more sensitive to field spread than lagged interaction, and discrepancies are reduced when using planar gradiometers rather than axial gradiometers. We, therefore, recommend using lagged interaction measures on planar gradiometer data when investigating network properties of resting-state sensor-level MEG data.

Dynamic recruitment of resting state sub-networks

PubMed Central

O'Neill, George C.; Bauer, Markus; Woolrich, Mark W.; Morris, Peter G.; Barnes, Gareth R.; Brookes, Matthew J.

2015-01-01

Resting state networks (RSNs) are of fundamental importance in human systems neuroscience with evidence suggesting that they are integral to healthy brain function and perturbed in pathology. Despite rapid progress in this area, the temporal dynamics governing the functional connectivities that underlie RSN structure remain poorly understood. Here, we present a framework to help further our understanding of RSN dynamics. We describe a methodology which exploits the direct nature and high temporal resolution of magnetoencephalography (MEG). This technique, which builds on previous work, extends from solving fundamental confounds in MEG (source leakage) to multivariate modelling of transient connectivity. The resulting processing pipeline facilitates direct (electrophysiological) measurement of dynamic functional networks. Our results show that, when functional connectivity is assessed in small time windows, the canonical sensorimotor network can be decomposed into a number of transiently synchronising sub-networks, recruitment of which depends on current mental state. These rapidly changing sub-networks are spatially focal with, for example, bilateral primary sensory and motor areas resolved into two separate sub-networks. The likely interpretation is that the larger canonical sensorimotor network most often seen in neuroimaging studies reflects only a temporal aggregate of these transient sub-networks. Our approach opens new frontiers to study RSN dynamics, showing that MEG is capable of revealing the spatial, temporal and spectral signature of the human connectome in health and disease. PMID:25899137

Clinical symptoms and alpha band resting-state functional connectivity imaging in patients with schizophrenia: implications for novel approaches to treatment

PubMed Central

Hinkley, Leighton B.N.; Vinogradov, Sophia; Guggisberg, Adrian G.; Fisher, Melissa; Findlay, Anne M.; Nagarajan, Srikantan S.

2011-01-01

Background Schizophrenia is associated with functional decoupling between cortical regions, but we do not know whether and where this occurs in low-frequency electromagnetic oscillations. The goal of this study was to use magnetoencephalography (MEG) to identify brain regions that exhibit abnormal resting-state connectivity in the alpha frequency range in patients with schizophrenia and investigate associations between functional connectivity and clinical symptoms in stable outpatient participants. Method Thirty patients with schizophrenia and fifteen healthy comparison participants were scanned in resting-state MEG (eyes closed). Functional connectivity MEGI (fcMEGI) data were reconstructed globally in the alpha range, quantified by the mean imaginary coherence between a voxel and the rest of the brain. Results In patients, decreased connectivity was observed in left pre-frontal cortex (PFC) and right superior temporal cortex while increased connectivity was observed in left extrastriate cortex and the right inferior PFC. Functional connectivity of left inferior parietal cortex was negatively related to positive symptoms. Low left PFC connectivity was associated with negative symptoms. Functional connectivity of midline PFC was negatively correlated with depressed symptoms. Functional connectivity of right PFC was associated with other (cognitive) symptoms. Conclusions This study demonstrates direct functional disconnection in schizophrenia between specific cortical fields within low-frequency resting-state oscillations. Impaired alpha coupling in frontal, parietal, and temporal regions is associated with clinical symptoms in these stable outpatients. Our findings indicate that this level of functional disconnection between cortical regions is an important treatment target in schizophrenia. PMID:21861988

Using joint ICA to link function and structure using MEG and DTI in schizophrenia

PubMed Central

Stephen, JM; Coffman, BA; Jung, RE; Bustillo, JR; Aine, CJ; Calhoun, VD

2013-01-01

In this study we employed joint independent component analysis (jICA) to perform a novel multivariate integration of magnetoencephalography (MEG) and diffusion tensor imaging (DTI) data to investigate the link between function and structure. This model-free approach allows one to identify covariation across modalities with different temporal and spatial scales [temporal variation in MEG and spatial variation in fractional anisotropy (FA) maps]. Healthy controls (HC) and patients with schizophrenia (SP) participated in an auditory/visual multisensory integration paradigm to probe cortical connectivity in schizophrenia. To allow direct comparisons across participants and groups, the MEG data were registered to an average head position and regional waveforms were obtained by calculating the local field power of the planar gradiometers. Diffusion tensor images obtained in the same individuals were preprocessed to provide FA maps for each participant. The MEG/FA data were then integrated using the jICA software (http://mialab.mrn.org/software/fit). We identified MEG/FA components that demonstrated significantly different (p < 0.05) covariation in MEG/FA data between diagnostic groups (SP vs. HC) and three components that captured the predominant sensory responses in the MEG data. Lower FA values in bilateral posterior parietal regions, which include anterior/posterior association tracts, were associated with reduced MEG amplitude (120-170 ms) of the visual response in occipital sensors in SP relative to HC. Additionally, increased FA in a right medial frontal region was linked with larger amplitude late MEG activity (300-400 ms) in bilateral central channels for SP relative to HC. Step-wise linear regression provided evidence that right temporal, occipital and late central components were significant predictors of reaction time and cognitive performance based on the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) cognitive assessment battery. These results point to dysfunction in a posterior visual processing network in schizophrenia, with reduced MEG amplitude, reduced FA and poorer overall performance on the MATRICS. Interestingly, the spatial location of the MEG activity and the associated FA regions are spatially consistent with white matter regions that subserve these brain areas. This novel approach provides evidence for significant pairing between function (electrophysiology) and structure (white matter integrity) and demonstrates the sensitivity of this multivariate, multimodal integration technique to group differences in function and structure. PMID:23777757

Neuromagnetic Vistas into Typical and Atypical Development of Frontal Lobe Functions

PubMed Central

Taylor, Margot J.; Doesburg, Sam M.; Pang, Elizabeth W.

2014-01-01

The frontal lobes are involved in many higher-order cognitive functions such as social cognition executive functions and language and speech. These functions are complex and follow a prolonged developmental course from childhood through to early adulthood. Magnetoencephalography (MEG) is ideal for the study of development of these functions, due to its combination of temporal and spatial resolution which allows the determination of age-related changes in both neural timing and location. There are several challenges for MEG developmental studies: to design tasks appropriate to capture the neurodevelopmental trajectory of these cognitive functions, and to develop appropriate analysis strategies to capture various aspects of neuromagnetic frontal lobe activity. Here, we review our MEG research on social and executive functions, and speech in typically developing children and in two clinical groups – children with autism spectrum disorder and children born very preterm. The studies include facial emotional processing, inhibition, visual short-term memory, speech production, and resting-state networks. We present data from event-related analyses as well as on oscillations and connectivity analyses and review their contributions to understanding frontal lobe cognitive development. We also discuss the challenges of testing young children in the MEG and the development of age-appropriate technologies and paradigms. PMID:24994980

An Internet-Based Real-Time Audiovisual Link for Dual MEG Recordings

PubMed Central

Zhdanov, Andrey; Nurminen, Jussi; Baess, Pamela; Hirvenkari, Lotta; Jousmäki, Veikko; Mäkelä, Jyrki P.; Mandel, Anne; Meronen, Lassi; Hari, Riitta; Parkkonen, Lauri

2015-01-01

Hyperscanning Most neuroimaging studies of human social cognition have focused on brain activity of single subjects. More recently, “two-person neuroimaging” has been introduced, with simultaneous recordings of brain signals from two subjects involved in social interaction. These simultaneous “hyperscanning” recordings have already been carried out with a spectrum of neuroimaging modalities, such as functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and functional near-infrared spectroscopy (fNIRS). Dual MEG Setup We have recently developed a setup for simultaneous magnetoencephalographic (MEG) recordings of two subjects that communicate in real time over an audio link between two geographically separated MEG laboratories. Here we present an extended version of the setup, where we have added a video connection and replaced the telephone-landline-based link with an Internet connection. Our setup enabled transmission of video and audio streams between the sites with a one-way communication latency of about 130 ms. Our software that allows reproducing the setup is publicly available. Validation We demonstrate that the audiovisual Internet-based link can mediate real-time interaction between two subjects who try to mirror each others’ hand movements that they can see via the video link. All the nine pairs were able to synchronize their behavior. In addition to the video, we captured the subjects’ movements with accelerometers attached to their index fingers; we determined from these signals that the average synchronization accuracy was 215 ms. In one subject pair we demonstrate inter-subject coherence patterns of the MEG signals that peak over the sensorimotor areas contralateral to the hand used in the task. PMID:26098628

Direction of Amygdala-Neocortex Interaction During Dynamic Facial Expression Processing.

PubMed

Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Yoshikawa, Sakiko; Toichi, Motomi

2017-03-01

Dynamic facial expressions of emotion strongly elicit multifaceted emotional, perceptual, cognitive, and motor responses. Neuroimaging studies revealed that some subcortical (e.g., amygdala) and neocortical (e.g., superior temporal sulcus and inferior frontal gyrus) brain regions and their functional interaction were involved in processing dynamic facial expressions. However, the direction of the functional interaction between the amygdala and the neocortex remains unknown. To investigate this issue, we re-analyzed functional magnetic resonance imaging (fMRI) data from 2 studies and magnetoencephalography (MEG) data from 1 study. First, a psychophysiological interaction analysis of the fMRI data confirmed the functional interaction between the amygdala and neocortical regions. Then, dynamic causal modeling analysis was used to compare models with forward, backward, or bidirectional effective connectivity between the amygdala and neocortical networks in the fMRI and MEG data. The results consistently supported the model of effective connectivity from the amygdala to the neocortex. Further increasing time-window analysis of the MEG demonstrated that this model was valid after 200 ms from the stimulus onset. These data suggest that emotional processing in the amygdala rapidly modulates some neocortical processing, such as perception, recognition, and motor mimicry, when observing dynamic facial expressions of emotion. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Diffusion tensor tractography detection of functional pathway for the spread of epileptiform activity between temporal lobe and Rolandic region.

PubMed

Bhardwaj, Ratan D; Mahmoodabadi, Sina Zarei; Otsubo, Hiroshi; Snead, O Carter; Rutka, James T; Widjaja, Elysa

2010-02-01

The aim of the study was to assess the connectivity between magnetoencephalographic (MEG) dipoles in the temporal lobe and Rolandic region in children with temporal lobe epilepsy using diffusion tensor imaging (DTI) tractography. Six pediatric patients with intractable focal epilepsy had MEG performed, which showed MEG dipoles over both temporal and Rolandic regions in a unilateral hemisphere. DTI tractography was performed on each patient. Six control subjects were studied for comparison. Two volumes of interest (VOIs) that encompassed the MEG dipoles were drawn, one placed in temporal lobe and the other in Rolandic region. Similar VOIs were placed in the contralateral side in the patients and on both sides in controls. Fractional anisotropy (FA) and trace of the external capsules were compared between patients and controls. In all patients, a tractography pathway traversing through the external capsule, connecting the temporal and Rolandic MEG dipoles, was visualized. However, on the contralateral hemisphere in each patient, there was no evidence of a similar fiber tract. There was no corresponding tractography pathway identified in either hemisphere within the controls. There were no significant differences in FA and trace between the seizure focus side and contralateral side in the patients. There was no significant difference in FA, but a difference in trace between patients and controls. We have found aberrant tractography pathway traversing through the external capsule, connecting two distant foci of epileptiform activity. Chronic interictal epileptogenic discharge could play a causal role in the de novo organization of these tracts.

Electrophysiological Source Imaging: A Noninvasive Window to Brain Dynamics.

PubMed

He, Bin; Sohrabpour, Abbas; Brown, Emery; Liu, Zhongming

2018-06-04

Brain activity and connectivity are distributed in the three-dimensional space and evolve in time. It is important to image brain dynamics with high spatial and temporal resolution. Electroencephalography (EEG) and magnetoencephalography (MEG) are noninvasive measurements associated with complex neural activations and interactions that encode brain functions. Electrophysiological source imaging estimates the underlying brain electrical sources from EEG and MEG measurements. It offers increasingly improved spatial resolution and intrinsically high temporal resolution for imaging large-scale brain activity and connectivity on a wide range of timescales. Integration of electrophysiological source imaging and functional magnetic resonance imaging could further enhance spatiotemporal resolution and specificity to an extent that is not attainable with either technique alone. We review methodological developments in electrophysiological source imaging over the past three decades and envision its future advancement into a powerful functional neuroimaging technology for basic and clinical neuroscience applications.

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

PubMed Central

Sotiropoulos, Stamatios N.; Brookes, Matthew J.; Woolrich, Mark W.

2018-01-01

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP. PMID:29474352

Ictal connectivity in childhood absence epilepsy: Associations with outcome.

PubMed

Tenney, Jeffrey R; Kadis, Darren S; Agler, William; Rozhkov, Leonid; Altaye, Mekibib; Xiang, Jing; Vannest, Jennifer; Glauser, Tracy A

2018-05-01

The understanding of childhood absence epilepsy (CAE) has been revolutionized over the past decade, but the biological mechanisms responsible for variable treatment outcomes are unknown. Our purpose in this prospective observational study was to determine how pretreatment ictal network pathways, defined using a combined electroencephalography (EEG)-functional magnetic resonance imaging (EEG-fMRI) and magnetoencephalography (MEG) effective connectivity analysis, were related to treatment response. Sixteen children with newly diagnosed and drug-naive CAE had 31 typical absence seizures during EEG-fMRI and 74 during MEG. The spatial extent of the pretreatment ictal network was defined using fMRI hemodynamic response with an event-related independent component analysis (eICA). This spatially defined pretreatment ictal network supplied prior information for MEG-effective connectivity analysis calculated using phase slope index (PSI). Treatment outcome was assessed 2 years following diagnosis and dichotomized to ethosuximide (ETX)-treatment responders (N = 11) or nonresponders (N = 5). Effective connectivity of the pretreatment ictal network was compared to the treatment response. Patterns of pretreatment connectivity demonstrated strongest connections in the thalamus and posterior brain regions (parietal, posterior cingulate, angular gyrus, precuneus, and occipital) at delta frequencies and the frontal cortices at gamma frequencies (P < .05). ETX treatment nonresponders had pretreatment connectivity, which was decreased in the precuneus region and increased in the frontal cortex compared to ETX responders (P < .05). Pretreatment ictal connectivity differences in children with CAE were associated with response to antiepileptic treatment. This is a possible mechanism for the variable treatment response seen in patients sharing the same epilepsy syndrome. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Detecting Mild Traumatic Brain Injury Using Resting State Magnetoencephalographic Connectivity

PubMed Central

da Costa, Leodante; Jetly, Rakesh; Pang, Elizabeth W.; Taylor, Margot J.

2016-01-01

Accurate means to detect mild traumatic brain injury (mTBI) using objective and quantitative measures remain elusive. Conventional imaging typically detects no abnormalities despite post-concussive symptoms. In the present study, we recorded resting state magnetoencephalograms (MEG) from adults with mTBI and controls. Atlas-guided reconstruction of resting state activity was performed for 90 cortical and subcortical regions, and calculation of inter-regional oscillatory phase synchrony at various frequencies was performed. We demonstrate that mTBI is associated with reduced network connectivity in the delta and gamma frequency range (>30 Hz), together with increased connectivity in the slower alpha band (8–12 Hz). A similar temporal pattern was associated with correlations between network connectivity and the length of time between the injury and the MEG scan. Using such resting state MEG network synchrony we were able to detect mTBI with 88% accuracy. Classification confidence was also correlated with clinical symptom severity scores. These results provide the first evidence that imaging of MEG network connectivity, in combination with machine learning, has the potential to accurately detect and determine the severity of mTBI. PMID:27906973

Multimodal approaches to functional connectivity in autism spectrum disorders: An integrative perspective.

PubMed

Mash, Lisa E; Reiter, Maya A; Linke, Annika C; Townsend, Jeanne; Müller, Ralph-Axel

2018-05-01

Atypical functional connectivity has been implicated in autism spectrum disorders (ASDs). However, the literature to date has been largely inconsistent, with mixed and conflicting reports of hypo- and hyper-connectivity. These discrepancies are partly due to differences between various neuroimaging modalities. Functional magnetic resonance imaging (fMRI), electroencephalography (EEG), and magnetoencephalography (MEG) measure distinct indices of functional connectivity (e.g., blood-oxygenation level-dependent [BOLD] signal vs. electrical activity). Furthermore, each method has unique benefits and disadvantages with respect to spatial and temporal resolution, vulnerability to specific artifacts, and practical implementation. Thus far, functional connectivity research on ASDs has remained almost exclusively unimodal; therefore, interpreting findings across modalities remains a challenge. Multimodal integration of fMRI, EEG, and MEG data is critical in resolving discrepancies in the literature, and working toward a unifying framework for interpreting past and future findings. This review aims to provide a theoretical foundation for future multimodal research on ASDs. First, we will discuss the merits and shortcomings of several popular theories in ASD functional connectivity research, using examples from the literature to date. Next, the neurophysiological relationships between imaging modalities, including their relationship with invasive neural recordings, will be reviewed. Finally, methodological approaches to multimodal data integration will be presented, and their future application to ASDs will be discussed. Analyses relating transient patterns of neural activity ("states") are particularly promising. This strategy provides a comparable measure across modalities, captures complex spatiotemporal patterns, and is a natural extension of recent dynamic fMRI research in ASDs. © 2017 Wiley Periodicals, Inc. Develop Neurobiol 78: 456-473, 2018. © 2017 Wiley Periodicals, Inc.

Oscillations during observations: Dynamic oscillatory networks serving visuospatial attention.

PubMed

Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Proskovec, Amy L; McDermott, Timothy J; Wilson, Tony W

2017-10-01

The dynamic allocation of neural resources to discrete features within a visual scene enables us to react quickly and accurately to salient environmental circumstances. A network of bilateral cortical regions is known to subserve such visuospatial attention functions; however the oscillatory and functional connectivity dynamics of information coding within this network are not fully understood. Particularly, the coding of information within prototypical attention-network hubs and the subsecond functional connections formed between these hubs have not been adequately characterized. Herein, we use the precise temporal resolution of magnetoencephalography (MEG) to define spectrally specific functional nodes and connections that underlie the deployment of attention in visual space. Twenty-three healthy young adults completed a visuospatial discrimination task designed to elicit multispectral activity in visual cortex during MEG, and the resulting data were preprocessed and reconstructed in the time-frequency domain. Oscillatory responses were projected to the cortical surface using a beamformer, and time series were extracted from peak voxels to examine their temporal evolution. Dynamic functional connectivity was then computed between nodes within each frequency band of interest. We find that visual attention network nodes are defined functionally by oscillatory frequency, that the allocation of attention to the visual space dynamically modulates functional connectivity between these regions on a millisecond timescale, and that these modulations significantly correlate with performance on a spatial discrimination task. We conclude that functional hubs underlying visuospatial attention are segregated not only anatomically but also by oscillatory frequency, and importantly that these oscillatory signatures promote dynamic communication between these hubs. Hum Brain Mapp 38:5128-5140, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

MEG-SIM: a web portal for testing MEG analysis methods using realistic simulated and empirical data.

PubMed

Aine, C J; Sanfratello, L; Ranken, D; Best, E; MacArthur, J A; Wallace, T; Gilliam, K; Donahue, C H; Montaño, R; Bryant, J E; Scott, A; Stephen, J M

2012-04-01

MEG and EEG measure electrophysiological activity in the brain with exquisite temporal resolution. Because of this unique strength relative to noninvasive hemodynamic-based measures (fMRI, PET), the complementary nature of hemodynamic and electrophysiological techniques is becoming more widely recognized (e.g., Human Connectome Project). However, the available analysis methods for solving the inverse problem for MEG and EEG have not been compared and standardized to the extent that they have for fMRI/PET. A number of factors, including the non-uniqueness of the solution to the inverse problem for MEG/EEG, have led to multiple analysis techniques which have not been tested on consistent datasets, making direct comparisons of techniques challenging (or impossible). Since each of the methods is known to have their own set of strengths and weaknesses, it would be beneficial to quantify them. Toward this end, we are announcing the establishment of a website containing an extensive series of realistic simulated data for testing purposes ( http://cobre.mrn.org/megsim/ ). Here, we present: 1) a brief overview of the basic types of inverse procedures; 2) the rationale and description of the testbed created; and 3) cases emphasizing functional connectivity (e.g., oscillatory activity) suitable for a wide assortment of analyses including independent component analysis (ICA), Granger Causality/Directed transfer function, and single-trial analysis.

MEG-SIM: A Web Portal for Testing MEG Analysis Methods using Realistic Simulated and Empirical Data

PubMed Central

Aine, C. J.; Sanfratello, L.; Ranken, D.; Best, E.; MacArthur, J. A.; Wallace, T.; Gilliam, K.; Donahue, C. H.; Montaño, R.; Bryant, J. E.; Scott, A.; Stephen, J. M.

2012-01-01

MEG and EEG measure electrophysiological activity in the brain with exquisite temporal resolution. Because of this unique strength relative to noninvasive hemodynamic-based measures (fMRI, PET), the complementary nature of hemodynamic and electrophysiological techniques is becoming more widely recognized (e.g., Human Connectome Project). However, the available analysis methods for solving the inverse problem for MEG and EEG have not been compared and standardized to the extent that they have for fMRI/PET. A number of factors, including the non-uniqueness of the solution to the inverse problem for MEG/EEG, have led to multiple analysis techniques which have not been tested on consistent datasets, making direct comparisons of techniques challenging (or impossible). Since each of the methods is known to have their own set of strengths and weaknesses, it would be beneficial to quantify them. Toward this end, we are announcing the establishment of a website containing an extensive series of realistic simulated data for testing purposes (http://cobre.mrn.org/megsim/). Here, we present: 1) a brief overview of the basic types of inverse procedures; 2) the rationale and description of the testbed created; and 3) cases emphasizing functional connectivity (e.g., oscillatory activity) suitable for a wide assortment of analyses including independent component analysis (ICA), Granger Causality/Directed transfer function, and single-trial analysis. PMID:22068921

Mission Connect Mild TBI Translational Research Consortium

DTIC Science & Technology

2012-08-01

as they relate to functional outcome. At 6 months post injury, patients will be screened for anterior pituitary function 121 subjects have been...are indicative of anterior pituitary function, including somatomedin (IGF-1), thyroid stimulating hormone (TSH), thyroxine (Free T4), prolactin, and...incidence of single and multiple pituitary hormone deficiencies. The clinical characteristics, MRI imaging results, EEG and MEG results of the

MEG Coherence and DTI Connectivity in mTLE

PubMed Central

Nazem-Zadeh, Mohammad-Reza; Bowyer, Susan M.; Moran, John E.; Davoodi-Bojd, Esmaeil; Zillgitt, Andrew; Weiland, Barbara J.; Bagher-Ebadian, Hassan; Mahmoudi, Fariborz; Elisevich, Kost; Soltanian-Zadeh, Hamid

2017-01-01

Purpose Magnetoencephalography (MEG) is a noninvasive imaging method for localization of focal epileptiform activity in patients with epilepsy. Diffusion tensor imaging (DTI) is a noninvasive imaging method for measuring the diffusion properties of the underlying white matter tracts through which epileptiform activity is propagated. This study investigates the relationship between the cerebral functional abnormalities quantified by MEG coherence and structural abnormalities quantified by DTI in mesial temporal lobe epilepsy (mTLE). Methods Resting state MEG data was analyzed using MEG coherence source imaging (MEG-CSI) method to determine the coherence in 54 anatomical sites in 17 adult mTLE patients with surgical resection and Engel class I outcome, and 17 age- and gender- matched controls. DTI tractography identified the fiber tracts passing through these same anatomical sites of the same subjects. Then, DTI nodal degree and laterality index were calculated and compared with the corresponding MEG coherence and laterality index. Results MEG coherence laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in insular cortex and both lateral orbitofrontal and superior temporal gyri (p<0.017). Likewise, DTI nodal degree laterality, after Bonferroni adjustment, showed significant differences for right versus left mTLE in gyrus rectus, insular cortex, precuneus and superior temporal gyrus (p<0.017). In insular cortex, MEG coherence laterality correlated with DTI nodal degree laterality (R2 = 0.46; p = 0.003) in the cases of mTLE. None of these anatomical sites showed statistically significant differences in coherence laterality between right and left sides of the controls. Coherence laterality was in agreement with the declared side of epileptogenicity in insular cortex (in 82% of patients) and both lateral orbitofrontal (88%) and superior temporal gyri (88%). Nodal degree laterality was also in agreement with the declared side of epileptogenicity in gyrus rectus (in 88% of patients), insular cortex (71%), precuneus (82%) and superior temporal gyrus (94%). Combining all significant laterality indices improved the lateralization accuracy to 94% and 100% for the coherence and nodal degree laterality indices, respectively. Conclusion The associated variations in diffusion properties of fiber tracts quantified by DTI and coherence measures quantified by MEG with respect to epileptogenicity possibly reflect the chronic microstructural cerebral changes associated with functional interictal activity. The proposed methodology for using MEG and DTI to investigate diffusion abnormalities related to focal epileptogenicity and propagation may provide a further means of noninvasive lateralization. PMID:27060092

Pursuing the flow of information: connectivity between bilateral premotor cortices predicts better accuracy in the phonological working memory task.

PubMed

Ono, Yumie; Nanjo, Tatsuya; Ishiyama, Atsushi

2013-01-01

Using Magnetoencephalography (MEG) we studied functional connectivity of cortical areas during phonological working memory task. Six subjects participated in the experiment and their neuronal activity was measured by a 306-channel MEG system. We used a modified version of the visual Sternberg paradigm, which required subjects to memorize 8 alphabet letters in 2s for a late recall period. We estimated functional connectivity of oscillatory regional brain activities during the encoding session for each trial of each subject using beamformer source reconstruction and Granger causality analysis. Regional brain activities were mostly found in the bilateral premotor cortex (Brodmann area (BA) 6: PMC), the right dorsolateral prefrontal cortex (BA 9: DLPFC), and the right frontal eye field (BA 8). Considering that the left and right PMCs participate in the functions of phonological loop (PL) and the visuospatial sketchpad (VS) in the Baddeley's model of working memory, respectively, our result suggests that subjects utilized either single function or both functions of working memory circuitry to execute the task. Interestingly, the accuracy of the task was significantly higher in the trials where the alpha band oscillatory activities in the bilateral PMCs established functional connectivity compared to those where the PMC was not working in conjunction with its counterpart. Similar relationship was found in the theta band oscillatory activities between the right PMC and the right DLPFC, however in this case the establishment of functional connectivity significantly decreased the accuracy of the task. These results suggest that sharing the memory load with both PL- and VS- type memory storage circuitries contributed to better performance in the highly-demanding cognitive task.

Extremely preterm children exhibit increased interhemispheric connectivity for language: findings from fMRI-constrained MEG analysis.

PubMed

Barnes-Davis, Maria E; Merhar, Stephanie L; Holland, Scott K; Kadis, Darren S

2018-04-16

Children born extremely preterm are at significant risk for cognitive impairment, including language deficits. The relationship between preterm birth and neurological changes that underlie cognitive deficits is poorly understood. We use a stories-listening task in fMRI and MEG to characterize language network representation and connectivity in children born extremely preterm (n = 15, <28 weeks gestation, ages 4-6 years), and in a group of typically developing control participants (n = 15, term birth, 4-6 years). Participants completed a brief neuropsychological assessment. Conventional fMRI analyses revealed no significant differences in language network representation across groups (p > .05, corrected). The whole-group fMRI activation map was parcellated to define the language network as a set of discrete nodes, and the timecourse of neuronal activity at each position was estimated using linearly constrained minimum variance beamformer in MEG. Virtual timecourses were subjected to connectivity and network-based analyses. We observed significantly increased beta-band functional connectivity in extremely preterm compared to controls (p < .05). Specifically, we observed an increase in connectivity between left and right perisylvian cortex. Subsequent effective connectivity analyses revealed that hyperconnectivity in preterms was due to significantly increased information flux originating from the right hemisphere (p < 0.05). The total strength and density of the language network were not related to language or nonverbal performance, suggesting that the observed hyperconnectivity is a "pure" effect of prematurity. Although our extremely preterm children exhibited typical language network architecture, we observed significantly altered network dynamics, indicating reliance on an alternative neural strategy for the language task. © 2018 The Authors. Developmental Science Published by John Wiley & Sons Ltd.

Magnetoencephalography in Stroke Recovery and Rehabilitation

PubMed Central

Paggiaro, Andrea; Birbaumer, Niels; Cavinato, Marianna; Turco, Cristina; Formaggio, Emanuela; Del Felice, Alessandra; Masiero, Stefano; Piccione, Francesco

2016-01-01

Magnetoencephalography (MEG) is a non-invasive neurophysiological technique used to study the cerebral cortex. Currently, MEG is mainly used clinically to localize epileptic foci and eloquent brain areas in order to avoid damage during neurosurgery. MEG might, however, also be of help in monitoring stroke recovery and rehabilitation. This review focuses on experimental use of MEG in neurorehabilitation. MEG has been employed to detect early modifications in neuroplasticity and connectivity, but there is insufficient evidence as to whether these methods are sensitive enough to be used as a clinical diagnostic test. MEG has also been exploited to derive the relationship between brain activity and movement kinematics for a motor-based brain–computer interface. In the current body of experimental research, MEG appears to be a powerful tool in neurorehabilitation, but it is necessary to produce new data to confirm its clinical utility. PMID:27065338

Brainstorm: A User-Friendly Application for MEG/EEG Analysis

PubMed Central

Tadel, François; Baillet, Sylvain; Mosher, John C.; Pantazis, Dimitrios; Leahy, Richard M.

2011-01-01

Brainstorm is a collaborative open-source application dedicated to magnetoencephalography (MEG) and electroencephalography (EEG) data visualization and processing, with an emphasis on cortical source estimation techniques and their integration with anatomical magnetic resonance imaging (MRI) data. The primary objective of the software is to connect MEG/EEG neuroscience investigators with both the best-established and cutting-edge methods through a simple and intuitive graphical user interface (GUI). PMID:21584256

Spectral power and functional connectivity changes during mindfulness meditation with eyes open: A magnetoencephalography (MEG) study in long-term meditators.

PubMed

Wong, W P; Camfield, D A; Woods, W; Sarris, J; Pipingas, A

2015-10-01

Whilst a number of previous studies have been conducted in order to investigate functional brain changes associated with eyes-closed meditation techniques, there is a relative scarcity in the literature with regards to changes occurring during eyes-open meditation. The current project used magnetoencephalography (MEG) to investigate differences in spectral power and functional connectivity between 11 long-term mindfulness meditators (LTMMs) with >5 years of experience and 12 meditation-naïve control participants both during baseline eyes-open rest and eyes-open open-monitoring (OM) mindfulness meditation. During resting with eyes-open, prior to meditating, greater mean alpha power was observed for LTMMs in comparison to controls. However, during the course of OM meditation, a significantly greater increase in theta power was observed over a broad fronto-centro-parietal region for control participants in comparison to LTMMs. In contrast, whole-head mean connectivity was found to be significantly greater for long-term meditators in comparison to controls in the theta band both during rest as well as during meditation. Additionally, mean connectivity was significantly lower for long-term meditators in the low gamma band during rest and significantly lower in both low and high gamma bands during meditation; and the variance of low-gamma connectivity scores for long-term meditators was significantly decreased compared to the control group. The current study provides important new information as to the trait functional changes in brain activity associated with long-term mindfulness meditation, as well as the state changes specifically associated with eyes-open open monitoring meditation techniques. Copyright © 2015 Elsevier B.V. All rights reserved.

Cognitive reserve is associated with the functional organization of the brain in healthy aging: a MEG study

PubMed Central

López, María E.; Aurtenetxe, Sara; Pereda, Ernesto; Cuesta, Pablo; Castellanos, Nazareth P.; Bruña, Ricardo; Niso, Guiomar; Maestú, Fernando; Bajo, Ricardo

2014-01-01

The proportion of elderly people in the population has increased rapidly in the last century and consequently “healthy aging” is expected to become a critical area of research in neuroscience. Evidence reveals how healthy aging depends on three main behavioral factors: social lifestyle, cognitive activity, and physical activity. In this study, we focused on the role of cognitive activity, concentrating specifically on educational and occupational attainment factors, which were considered two of the main pillars of cognitive reserve (CR). Twenty-one subjects with similar rates of social lifestyle, physical and cognitive activity were selected from a sample of 55 healthy adults. These subjects were divided into two groups according to their level of CR; one group comprised subjects with high CR (9 members) and the other one contained those with low CR (12 members). To evaluate the cortical brain connectivity network, all participants were recorded by Magnetoencephalography (MEG) while they performed a memory task (modified version of the Sternberg's Task). We then applied two algorithms [Phase Locking Value (PLV) and Phase Lag Index (PLI)] to study the dynamics of functional connectivity. In response to the same task, the subjects with lower CR presented higher functional connectivity than those with higher CR. These results may indicate that participants with low CR needed a greater “effort” than those with high CR to achieve the same level of cognitive performance. Therefore, we conclude that CR contributes to the modulation of the functional connectivity patterns of the aging brain. PMID:24982632

Lateralized theta wave connectivity and language performance in 2- to 5-year-old children.

PubMed

Kikuchi, Mitsuru; Shitamichi, Kiyomi; Yoshimura, Yuko; Ueno, Sanae; Remijn, Gerard B; Hirosawa, Tetsu; Munesue, Toshio; Tsubokawa, Tsunehisa; Haruta, Yasuhiro; Oi, Manabu; Higashida, Haruhiro; Minabe, Yoshio

2011-10-19

Recent neuroimaging studies support the view that a left-lateralized brain network is crucial for language development in children. However, no previous studies have demonstrated a clear link between lateralized brain functional network and language performance in preschool children. Magnetoencephalography (MEG) is a noninvasive brain imaging technique and is a practical neuroimaging method for use in young children. MEG produces a reference-free signal, and is therefore an ideal tool to compute coherence between two distant cortical rhythms. In the present study, using a custom child-sized MEG system, we investigated brain networks while 78 right-handed preschool human children (32-64 months; 96% were 3-4 years old) listened to stories with moving images. The results indicated that left dominance of parietotemporal coherence in theta band activity (6-8 Hz) was specifically correlated with higher performance of language-related tasks, whereas this laterality was not correlated with nonverbal cognitive performance, chronological age, or head circumference. Power analyses did not reveal any specific frequencies that contributed to higher language performance. Our results suggest that it is not the left dominance in theta oscillation per se, but the left-dominant phase-locked connectivity via theta oscillation that contributes to the development of language ability in young children.

Long noncoding RNA-MEG3 is involved in diabetes mellitus-related microvascular dysfunction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu, Gui-Zhen; Tian, Wei; Fu, Hai-Tao

Microvascular dysfunction is an important characteristic of diabetic retinopathy. Long non-coding RNAs (lncRNAs) play important roles in diverse biological processes. In this study, we investigated the role of lncRNA-MEG3 in diabetes-related microvascular dysfunction. We show that MEG3 expression level is significantly down-regulated in the retinas of STZ-induced diabetic mice, and endothelial cells upon high glucose and oxidative stress. MEG3 knockdown aggravates retinal vessel dysfunction in vivo, as shown by serious capillary degeneration, and increased microvascular leakage and inflammation. MEG3 knockdown also regulates retinal endothelial cell proliferation, migration, and tube formation in vitro. The role of MEG3 in endothelial cell function is mainlymore » mediated by the activation of PI3k/Akt signaling. MEG3 up-regulation may serve as a therapeutic strategy for treating diabetes-related microvascular complications. - Highlights: • LncRNA-MEG3 level is down-regulated upon diabetic stress. • MEG3 knockdown aggravates retinal vascular dysfunction in vivo. • MEG3 regulates retinal endothelial cell function in vitro. • MEG3 regulates endothelial cell function through PI3k/Akt signaling.« less

FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data.

PubMed

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.

Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals

NASA Astrophysics Data System (ADS)

Chella, Federico; Pizzella, Vittorio; Zappasodi, Filippo; Nolte, Guido; Marzetti, Laura

2016-05-01

Brain cognitive functions arise through the coordinated activity of several brain regions, which actually form complex dynamical systems operating at multiple frequencies. These systems often consist of interacting subsystems, whose characterization is of importance for a complete understanding of the brain interaction processes. To address this issue, we present a technique, namely the bispectral pairwise interacting source analysis (biPISA), for analyzing systems of cross-frequency interacting brain sources when multichannel electroencephalographic (EEG) or magnetoencephalographic (MEG) data are available. Specifically, the biPISA makes it possible to identify one or many subsystems of cross-frequency interacting sources by decomposing the antisymmetric components of the cross-bispectra between EEG or MEG signals, based on the assumption that interactions are pairwise. Thanks to the properties of the antisymmetric components of the cross-bispectra, biPISA is also robust to spurious interactions arising from mixing artifacts, i.e., volume conduction or field spread, which always affect EEG or MEG functional connectivity estimates. This method is an extension of the pairwise interacting source analysis (PISA), which was originally introduced for investigating interactions at the same frequency, to the study of cross-frequency interactions. The effectiveness of this approach is demonstrated in simulations for up to three interacting source pairs and for real MEG recordings of spontaneous brain activity. Simulations show that the performances of biPISA in estimating the phase difference between the interacting sources are affected by the increasing level of noise rather than by the number of the interacting subsystems. The analysis of real MEG data reveals an interaction between two pairs of sources of central mu and beta rhythms, localizing in the proximity of the left and right central sulci.

Persistent genital arousal disorder associated with functional hyperconnectivity of an epileptic focus.

PubMed

Anzellotti, F; Franciotti, R; Bonanni, L; Tamburro, G; Perrucci, M G; Thomas, A; Pizzella, V; Romani, G L; Onofrj, M

2010-04-28

Persistent Genital Arousal Disorder (PGAD) refers to the experience of persistent sensations of genital arousal that are felt to be unprovoked, intrusive and unrelieved by one or several orgasms. It is often mistaken for hypersexuality since PGAD often results in a high frequency of sexual behaviour. At present little is known with certainty about the etiology of this condition. We described a woman with typical PGAD symptoms and orgasmic seizures that we found to be related to a specific epileptic focus. We performed a EEG/MEG and fMRI spontaneous activity study during genital arousal symptoms and after the chronic administration of 300 mg/day of topiramate. From MEG data an epileptic focus was localized in the left posterior insular gyrus (LPIG). FMRI data evidenced that sexual excitation symptoms with PGAD could be correlated with an increased functional connectivity (FC) between different brain areas: LPIG (epileptic focus), left middle frontal gyrus, left inferior and superior temporal gyrus and left inferior parietal lobe. The reduction of the FC observed after antiepileptic therapy was more marked in the left than in the right hemisphere in agreement with the lateralization identified by MEG results. Treatment completely abolished PGAD symptoms and functional hyperconnectivity. The functional hyperconnectivity found in the neuronal network including the epileptic focus could suggest a possible central mechanism for PGAD. Copyright 2010 IBRO. Published by Elsevier Ltd. All rights reserved.

Deriving frequency-dependent spatial patterns in MEG-derived resting state sensorimotor network: A novel multiband ICA technique.

PubMed

Nugent, Allison C; Luber, Bruce; Carver, Frederick W; Robinson, Stephen E; Coppola, Richard; Zarate, Carlos A

2017-02-01

Recently, independent components analysis (ICA) of resting state magnetoencephalography (MEG) recordings has revealed resting state networks (RSNs) that exhibit fluctuations of band-limited power envelopes. Most of the work in this area has concentrated on networks derived from the power envelope of beta bandpass-filtered data. Although research has demonstrated that most networks show maximal correlation in the beta band, little is known about how spatial patterns of correlations may differ across frequencies. This study analyzed MEG data from 18 healthy subjects to determine if the spatial patterns of RSNs differed between delta, theta, alpha, beta, gamma, and high gamma frequency bands. To validate our method, we focused on the sensorimotor network, which is well-characterized and robust in both MEG and functional magnetic resonance imaging (fMRI) resting state data. Synthetic aperture magnetometry (SAM) was used to project signals into anatomical source space separately in each band before a group temporal ICA was performed over all subjects and bands. This method preserved the inherent correlation structure of the data and reflected connectivity derived from single-band ICA, but also allowed identification of spatial spectral modes that are consistent across subjects. The implications of these results on our understanding of sensorimotor function are discussed, as are the potential applications of this technique. Hum Brain Mapp 38:779-791, 2017. © 2016 Wiley Periodicals, Inc. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

PubMed Central

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages. PMID:21253357

Choice of Magnetometers and Gradiometers after Signal Space Separation.

PubMed

Garcés, Pilar; López-Sanz, David; Maestú, Fernando; Pereda, Ernesto

2017-12-16

Modern Elekta Neuromag MEG devices include 102 sensor triplets containing one magnetometer and two planar gradiometers. The first processing step is often a signal space separation (SSS), which provides a powerful noise reduction. A question commonly raised by researchers and reviewers relates to which data should be employed in analyses: (1) magnetometers only, (2) gradiometers only, (3) magnetometers and gradiometers together. The MEG community is currently divided with regard to the proper answer. First, we provide theoretical evidence that both gradiometers and magnetometers result from the backprojection of the same SSS components. Then, we compare resting state and task-related sensor and source estimations from magnetometers and gradiometers in real MEG recordings before and after SSS. SSS introduced a strong increase in the similarity between source time series derived from magnetometers and gradiometers (r² = 0.3-0.8 before SSS and r² > 0.80 after SSS). After SSS, resting state power spectrum and functional connectivity, as well as visual evoked responses, derived from both magnetometers and gradiometers were highly similar (Intraclass Correlation Coefficient > 0.8, r² > 0.8). After SSS, magnetometer and gradiometer data are estimated from a single set of SSS components (usually ≤ 80). Equivalent results can be obtained with both sensor types in typical MEG experiments.

IFCN-endorsed practical guidelines for clinical magnetoencephalography (MEG).

PubMed

Hari, Riitta; Baillet, Sylvain; Barnes, Gareth; Burgess, Richard; Forss, Nina; Gross, Joachim; Hämäläinen, Matti; Jensen, Ole; Kakigi, Ryusuke; Mauguière, François; Nakasato, Nobukatzu; Puce, Aina; Romani, Gian-Luca; Schnitzler, Alfons; Taulu, Samu

2018-04-17

Magnetoencephalography (MEG) records weak magnetic fields outside the human head and thereby provides millisecond-accurate information about neuronal currents supporting human brain function. MEG and electroencephalography (EEG) are closely related complementary methods and should be interpreted together whenever possible. This manuscript covers the basic physical and physiological principles of MEG and discusses the main aspects of state-of-the-art MEG data analysis. We provide guidelines for best practices of patient preparation, stimulus presentation, MEG data collection and analysis, as well as for MEG interpretation in routine clinical examinations. In 2017, about 200 whole-scalp MEG devices were in operation worldwide, many of them located in clinical environments. Yet, the established clinical indications for MEG examinations remain few, mainly restricted to the diagnostics of epilepsy and to preoperative functional evaluation of neurosurgical patients. We are confident that the extensive ongoing basic MEG research indicates potential for the evaluation of neurological and psychiatric syndromes, developmental disorders, and the integrity of cortical brain networks after stroke. Basic and clinical research is, thus, paving way for new clinical applications to be identified by an increasing number of practitioners of MEG. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Granger causal time-dependent source connectivity in the somatosensory network

NASA Astrophysics Data System (ADS)

Gao, Lin; Sommerlade, Linda; Coffman, Brian; Zhang, Tongsheng; Stephen, Julia M.; Li, Dichen; Wang, Jue; Grebogi, Celso; Schelter, Bjoern

2015-05-01

Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

Network Disruption and Cerebrospinal Fluid Amyloid-Beta and Phospho-Tau Levels in Mild Cognitive Impairment.

PubMed

Canuet, Leonides; Pusil, Sandra; López, María Eugenia; Bajo, Ricardo; Pineda-Pardo, José Ángel; Cuesta, Pablo; Gálvez, Gerardo; Gaztelu, José María; Lourido, Daniel; García-Ribas, Guillermo; Maestú, Fernando

2015-07-15

Synaptic dysfunction is a core deficit in Alzheimer's disease, preceding hallmark pathological abnormalities. Resting-state magnetoencephalography (MEG) was used to assess whether functional connectivity patterns, as an index of synaptic dysfunction, are associated with CSF biomarkers [i.e., phospho-tau (p-tau) and amyloid beta (Aβ42) levels]. We studied 12 human subjects diagnosed with mild cognitive impairment due to Alzheimer's disease, comparing those with normal and abnormal CSF levels of the biomarkers. We also evaluated the association between aberrant functional connections and structural connectivity abnormalities, measured with diffusion tensor imaging, as well as the convergent impact of cognitive deficits and CSF variables on network disorganization. One-third of the patients converted to Alzheimer's disease during a follow-up period of 2.5 years. Patients with abnomal CSF p-tau and Aβ42 levels exhibited both reduced and increased functional connectivity affecting limbic structures such as the anterior/posterior cingulate cortex, orbitofrontal cortex, and medial temporal areas in different frequency bands. A reduction in posterior cingulate functional connectivity mediated by p-tau was associated with impaired axonal integrity of the hippocampal cingulum. We noted that several connectivity abnormalities were predicted by CSF biomarkers and cognitive scores. These preliminary results indicate that CSF markers of amyloid deposition and neuronal injury in early Alzheimer's disease associate with a dual pattern of cortical network disruption, affecting key regions of the default mode network and the temporal cortex. MEG is useful to detect early synaptic dysfunction associated with Alzheimer's disease brain pathology in terms of functional network organization. In this preliminary study, we used magnetoencephalography and an integrative approach to explore the impact of CSF biomarkers, neuropsychological scores, and white matter structural abnormalities on neural function in mild cognitive impairment. Disruption in functional connectivity between several pairs of cortical regions associated with abnormal levels of biomarkers, cognitive deficits, or with impaired axonal integrity of hippocampal tracts. Amyloid deposition and tau protein-related neuronal injury in early Alzheimer's disease are associated with synaptic dysfunction and a dual pattern of cortical network disorganization (i.e., desynchronization and hypersynchronization) that affects key regions of the default mode network and temporal areas. Copyright © 2015 the authors 0270-6474/15/3510326-06$15.00/0.

Brain Network Analysis from High-Resolution EEG Signals

NASA Astrophysics Data System (ADS)

de Vico Fallani, Fabrizio; Babiloni, Fabio

Over the last decade, there has been a growing interest in the detection of the functional connectivity in the brain from different neuroelectromagnetic and hemodynamic signals recorded by several neuro-imaging devices such as the functional Magnetic Resonance Imaging (fMRI) scanner, electroencephalography (EEG) and magnetoencephalography (MEG) apparatus. Many methods have been proposed and discussed in the literature with the aim of estimating the functional relationships among different cerebral structures. However, the necessity of an objective comprehension of the network composed by the functional links of different brain regions is assuming an essential role in the Neuroscience. Consequently, there is a wide interest in the development and validation of mathematical tools that are appropriate to spot significant features that could describe concisely the structure of the estimated cerebral networks. The extraction of salient characteristics from brain connectivity patterns is an open challenging topic, since often the estimated cerebral networks have a relative large size and complex structure. Recently, it was realized that the functional connectivity networks estimated from actual brain-imaging technologies (MEG, fMRI and EEG) can be analyzed by means of the graph theory. Since a graph is a mathematical representation of a network, which is essentially reduced to nodes and connections between them, the use of a theoretical graph approach seems relevant and useful as firstly demonstrated on a set of anatomical brain networks. In those studies, the authors have employed two characteristic measures, the average shortest path L and the clustering index C, to extract respectively the global and local properties of the network structure. They have found that anatomical brain networks exhibit many local connections (i.e. a high C) and few random long distance connections (i.e. a low L). These values identify a particular model that interpolate between a regular lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an effective methodology improving the comprehension of the complex interactions in the brain.

Contributions of local speech encoding and functional connectivity to audio-visual speech perception

PubMed Central

Giordano, Bruno L; Ince, Robin A A; Gross, Joachim; Schyns, Philippe G; Panzeri, Stefano; Kayser, Christoph

2017-01-01

Seeing a speaker’s face enhances speech intelligibility in adverse environments. We investigated the underlying network mechanisms by quantifying local speech representations and directed connectivity in MEG data obtained while human participants listened to speech of varying acoustic SNR and visual context. During high acoustic SNR speech encoding by temporally entrained brain activity was strong in temporal and inferior frontal cortex, while during low SNR strong entrainment emerged in premotor and superior frontal cortex. These changes in local encoding were accompanied by changes in directed connectivity along the ventral stream and the auditory-premotor axis. Importantly, the behavioral benefit arising from seeing the speaker’s face was not predicted by changes in local encoding but rather by enhanced functional connectivity between temporal and inferior frontal cortex. Our results demonstrate a role of auditory-frontal interactions in visual speech representations and suggest that functional connectivity along the ventral pathway facilitates speech comprehension in multisensory environments. DOI: http://dx.doi.org/10.7554/eLife.24763.001 PMID:28590903

Cortical Tracking of Global and Local Variations of Speech Rhythm during Connected Natural Speech Perception.

PubMed

Alexandrou, Anna Maria; Saarinen, Timo; Kujala, Jan; Salmelin, Riitta

2018-06-19

During natural speech perception, listeners must track the global speaking rate, that is, the overall rate of incoming linguistic information, as well as transient, local speaking rate variations occurring within the global speaking rate. Here, we address the hypothesis that this tracking mechanism is achieved through coupling of cortical signals to the amplitude envelope of the perceived acoustic speech signals. Cortical signals were recorded with magnetoencephalography (MEG) while participants perceived spontaneously produced speech stimuli at three global speaking rates (slow, normal/habitual, and fast). Inherently to spontaneously produced speech, these stimuli also featured local variations in speaking rate. The coupling between cortical and acoustic speech signals was evaluated using audio-MEG coherence. Modulations in audio-MEG coherence spatially differentiated between tracking of global speaking rate, highlighting the temporal cortex bilaterally and the right parietal cortex, and sensitivity to local speaking rate variations, emphasizing the left parietal cortex. Cortical tuning to the temporal structure of natural connected speech thus seems to require the joint contribution of both auditory and parietal regions. These findings suggest that cortical tuning to speech rhythm operates on two functionally distinct levels: one encoding the global rhythmic structure of speech and the other associated with online, rapidly evolving temporal predictions. Thus, it may be proposed that speech perception is shaped by evolutionary tuning, a preference for certain speaking rates, and predictive tuning, associated with cortical tracking of the constantly changing rate of linguistic information in a speech stream.

Frequency-dependent oscillatory neural profiles during imitation.

PubMed

Sugata, Hisato; Hirata, Masayuki; Tamura, Yuichi; Onishi, Hisao; Goto, Tetsu; Araki, Toshihiko; Yorifuji, Shiro

2017-04-10

Imitation is a complex process that includes higher-order cognitive and motor function. This process requires an observation-execution matching system that transforms an observed action into an identical movement. Although the low-gamma band is thought to reflect higher cognitive processes, no studies have focused on it. Here, we used magnetoencephalography (MEG) to examine the neural oscillatory changes including the low-gamma band during imitation. Twelve healthy, right-handed participants performed a finger task consisting of four conditions (imitation, execution, observation, and rest). During the imitation and execution conditions, significant event-related desynchronizations (ERDs) were observed at the left frontal, central, and parietal MEG sensors in the alpha, beta, and low-gamma bands. Functional connectivity analysis at the sensor level revealed an imitation-related connectivity between a group of frontal sensors and a group of parietal sensors in the low-gamma band. Furthermore, source reconstruction with synthetic aperture magnetometry showed significant ERDs in the low-gamma band in the left sensorimotor area and the middle frontal gyrus (MFG) during the imitation condition when compared with the other three conditions. Our results suggest that the oscillatory neural activities of the low-gamma band at the sensorimotor area and MFG play an important role in the observation-execution matching system related to imitation.

Frequency-dependent oscillatory neural profiles during imitation

PubMed Central

Sugata, Hisato; Hirata, Masayuki; Tamura, Yuichi; Onishi, Hisao; Goto, Tetsu; Araki, Toshihiko; Yorifuji, Shiro

2017-01-01

Imitation is a complex process that includes higher-order cognitive and motor function. This process requires an observation-execution matching system that transforms an observed action into an identical movement. Although the low-gamma band is thought to reflect higher cognitive processes, no studies have focused on it. Here, we used magnetoencephalography (MEG) to examine the neural oscillatory changes including the low-gamma band during imitation. Twelve healthy, right-handed participants performed a finger task consisting of four conditions (imitation, execution, observation, and rest). During the imitation and execution conditions, significant event-related desynchronizations (ERDs) were observed at the left frontal, central, and parietal MEG sensors in the alpha, beta, and low-gamma bands. Functional connectivity analysis at the sensor level revealed an imitation-related connectivity between a group of frontal sensors and a group of parietal sensors in the low-gamma band. Furthermore, source reconstruction with synthetic aperture magnetometry showed significant ERDs in the low-gamma band in the left sensorimotor area and the middle frontal gyrus (MFG) during the imitation condition when compared with the other three conditions. Our results suggest that the oscillatory neural activities of the low-gamma band at the sensorimotor area and MFG play an important role in the observation-execution matching system related to imitation. PMID:28393878

Measuring alterations in oscillatory brain networks in schizophrenia with resting-state MEG: State-of-the-art and methodological challenges.

PubMed

Alamian, Golnoush; Hincapié, Ana-Sofía; Pascarella, Annalisa; Thiery, Thomas; Combrisson, Etienne; Saive, Anne-Lise; Martel, Véronique; Althukov, Dmitrii; Haesebaert, Frédéric; Jerbi, Karim

2017-09-01

Neuroimaging studies provide evidence of disturbed resting-state brain networks in Schizophrenia (SZ). However, untangling the neuronal mechanisms that subserve these baseline alterations requires measurement of their electrophysiological underpinnings. This systematic review specifically investigates the contributions of resting-state Magnetoencephalography (MEG) in elucidating abnormal neural organization in SZ patients. A systematic literature review of resting-state MEG studies in SZ was conducted. This literature is discussed in relation to findings from resting-state fMRI and EEG, as well as to task-based MEG research in SZ population. Importantly, methodological limitations are considered and recommendations to overcome current limitations are proposed. Resting-state MEG literature in SZ points towards altered local and long-range oscillatory network dynamics in various frequency bands. Critical methodological challenges with respect to experiment design, and data collection and analysis need to be taken into consideration. Spontaneous MEG data show that local and global neural organization is altered in SZ patients. MEG is a highly promising tool to fill in knowledge gaps about the neurophysiology of SZ. However, to reach its fullest potential, basic methodological challenges need to be overcome. MEG-based resting-state power and connectivity findings could be great assets to clinical and translational research in psychiatry, and SZ in particular. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Maturational trajectories of local and long-range functional connectivity in autism during face processing.

PubMed

Mamashli, Fahimeh; Khan, Sheraz; Bharadwaj, Hari; Losh, Ainsley; Pawlyszyn, Stephanie M; Hämäläinen, Matti S; Kenet, Tal

2018-06-26

Autism spectrum disorder (ASD) is characterized neurophysiologically by, among other things, functional connectivity abnormalities in the brain. Recent evidence suggests that the nature of these functional connectivity abnormalities might not be uniform throughout maturation. Comparing between adolescents and young adults (ages 14-21) with ASD and age- and IQ-matched typically developing (TD) individuals, we previously documented, using magnetoencephalography (MEG) data, that local functional connectivity in the fusiform face areas (FFA) and long-range functional connectivity between FFA and three higher order cortical areas were all reduced in ASD. Given the findings on abnormal maturation trajectories in ASD, we tested whether these results extend to preadolescent children (ages 7-13). We found that both local and long-range functional connectivity were in fact normal in this younger age group in ASD. Combining the two age groups, we found that local and long-range functional connectivity measures were positively correlated with age in TD, but negatively correlated with age in ASD. Last, we showed that local functional connectivity was the primary feature in predicting age in ASD group, but not in the TD group. Furthermore, local functional connectivity was only correlated with ASD severity in the older group. These results suggest that the direction of maturation of functional connectivity for processing of faces from childhood to young adulthood is itself abnormal in ASD, and that during the processing of faces, these trajectory abnormalities are more pronounced for local functional connectivity measures than they are for long-range functional connectivity measures. © 2018 Wiley Periodicals, Inc.

Long Noncoding RNA MEG3 Is an Epigenetic Determinant of Oncogenic Signaling in Functional Pancreatic Neuroendocrine Tumor Cells

PubMed Central

Iyer, Sucharitha; Modali, Sita D.

2017-01-01

ABSTRACT The long noncoding RNA (lncRNA) MEG3 is significantly downregulated in pancreatic neuroendocrine tumors (PNETs). MEG3 loss corresponds with aberrant upregulation of the oncogenic hepatocyte growth factor (HGF) receptor c-MET in PNETs. Meg3 overexpression in a mouse insulin-secreting PNET cell line, MIN6, downregulates c-Met expression. However, the molecular mechanism by which MEG3 regulates c-MET is not known. Using chromatin isolation by RNA purification and sequencing (ChIRP-Seq), we identified Meg3 binding to unique genomic regions in and around the c-Met gene. In the absence of Meg3, these c-Met regions displayed distinctive enhancer-signature histone modifications. Furthermore, Meg3 relied on functional enhancer of zeste homolog 2 (EZH2), a component of polycomb repressive complex 2 (PRC2), to inhibit c-Met expression. Another mechanism of lncRNA-mediated regulation of gene expression utilized triplex-forming GA-GT rich sequences. Transfection of such motifs from Meg3 RNA, termed triplex-forming oligonucleotides (TFOs), in MIN6 cells suppressed c-Met expression and enhanced cell proliferation, perhaps by modulating other targets. This study comprehensively establishes epigenetic mechanisms underlying Meg3 control of c-Met and the oncogenic consequences of Meg3 loss or c-Met gain. These findings have clinical relevance for targeting c-MET in PNETs. There is also the potential for pancreatic islet β-cell expansion through c-MET regulation to ameliorate β-cell loss in diabetes. PMID:28847847

Variability of magnetoencephalographic sensor sensitivity measures as a function of age, brain volume and cortical area

PubMed Central

Irimia, Andrei; Erhart, Matthew J.; Brown, Timothy T.

2014-01-01

Objective To assess the feasibility and appropriateness of magnetoencephalography (MEG) for both adult and pediatric studies, as well as for the developmental comparison of these factors across a wide range of ages. Methods For 45 subjects with ages from 1 to 24 years (infants, toddlers, school-age children and young adults), lead fields (LFs) of MEG sensors are computed using anatomically realistic boundary element models (BEMs) and individually-reconstructed cortical surfaces. Novel metrics are introduced to quantify MEG sensor focality. Results The variability of MEG focality is graphed as a function of brain volume and cortical area. Statistically significant differences in total cerebral volume, cortical area, MEG global sensitivity and LF focality are found between age groups. Conclusions Because MEG focality and sensitivity differ substantially across the age groups studied, the cortical LF maps explored here can provide important insights for the examination and interpretation of MEG signals from early childhood to young adulthood. Significance This is the first study to (1) investigate the relationship between MEG cortical LFs and brain volume as well as cortical area across development, and (2) compare LFs between subjects with different head sizes using detailed cortical reconstructions. PMID:24589347

Hyperedge bundling: Data, source code, and precautions to modeling-accuracy bias to synchrony estimates.

PubMed

Wang, Sheng H; Lobier, Muriel; Siebenhühner, Felix; Puoliväli, Tuomas; Palva, Satu; Palva, J Matias

2018-06-01

It has not been well documented that MEG/EEG functional connectivity graphs estimated with zero-lag-free interaction metrics are severely confounded by a multitude of spurious interactions (SI), i.e., the false-positive "ghosts" of true interactions [1], [2]. These SI are caused by the multivariate linear mixing between sources, and thus they pose a severe challenge to the validity of connectivity analysis. Due to the complex nature of signal mixing and the SI problem, there is a need to intuitively demonstrate how the SI are discovered and how they can be attenuated using a novel approach that we termed hyperedge bundling. Here we provide a dataset with software with which the readers can perform simulations in order to better understand the theory and the solution to SI. We include the supplementary material of [1] that is not directly relevant to the hyperedge bundling per se but reflects important properties of the MEG source model and the functional connectivity graphs. For example, the gyri of dorsal-lateral cortices are the most accurately modeled areas; the sulci of inferior temporal, frontal and the insula have the least modeling accuracy. Importantly, we found the interaction estimates are heavily biased by the modeling accuracy between regions, which means the estimates cannot be straightforwardly interpreted as the coupling between brain regions. This raise a red flag that the conventional method of thresholding graphs by estimate values is rather suboptimal: because the measured topology of the graph reflects the geometric property of source-model instead of the cortical interactions under investigation.

Oscillatory dynamics in the dorsal and ventral attention networks during the reorienting of attention.

PubMed

Proskovec, Amy L; Heinrichs-Graham, Elizabeth; Wiesman, Alex I; McDermott, Timothy J; Wilson, Tony W

2018-05-01

The ability to reorient attention within the visual field is central to daily functioning, and numerous fMRI studies have shown that the dorsal and ventral attention networks (DAN, VAN) are critical to such processes. However, despite the instantaneous nature of attentional shifts, the dynamics of oscillatory activity serving attentional reorientation remain poorly characterized. In this study, we utilized magnetoencephalography (MEG) and a Posner task to probe the dynamics of attentional reorienting in 29 healthy adults. MEG data were transformed into the time-frequency domain and significant oscillatory responses were imaged using a beamformer. Voxel time series were then extracted from peak voxels in the functional beamformer images. These time series were used to quantify the dynamics of attentional reorienting, and to compute dynamic functional connectivity. Our results indicated strong increases in theta and decreases in alpha and beta activity across many nodes in the DAN and VAN. Interestingly, theta responses were generally stronger during trials that required attentional reorienting relative to those that did not, while alpha and beta oscillations were more dynamic, with many regions exhibiting significantly stronger responses during non-reorienting trials initially, and the opposite pattern during later processing. Finally, stronger functional connectivity was found following target presentation (575-700 ms) between bilateral superior parietal lobules during attentional reorienting. In sum, these data show that visual attention is served by multiple cortical regions within the DAN and VAN, and that attentional reorienting processes are often associated with spectrally-specific oscillations that have largely distinct spatiotemporal dynamics. © 2018 Wiley Periodicals, Inc.

Scopolamine effects on functional brain connectivity: a pharmacological model of Alzheimer's disease.

PubMed

Bajo, R; Pusil, S; López, M E; Canuet, L; Pereda, E; Osipova, D; Maestú, F; Pekkonen, E

2015-07-01

Scopolamine administration may be considered as a psychopharmacological model of Alzheimer's disease (AD). Here, we studied a group of healthy elderly under scopolamine to test whether it elicits similar changes in brain connectivity as those observed in AD, thereby verifying a possible model of AD impairment. We did it by testing healthy elderly subjects in two experimental conditions: glycopyrrolate (placebo) and scopolamine administration. We then analyzed magnetoencephalographic (MEG) data corresponding to both conditions in resting-state with eyes closed. This analysis was performed in source space by combining a nonlinear frequency band-specific measure of functional connectivity (phase locking value, PLV) with network analysis methods. Under scopolamine, functional connectivity between several brain areas was significantly reduced as compared to placebo, in most frequency bands analyzed. Besides, regarding the two complex network indices studied (clustering and shortest path length), clustering significantly decreased in the alpha band while shortest path length significantly increased also in alpha band both after scopolamine administration. Overall our findings indicate that both PLV and graph analysis are suitable tools to measure brain connectivity changes induced by scopolamine, which causes alterations in brain connectivity apparently similar to those reported in AD.

Compact, ultra-low vibration, closed-cycle helium recycler for uninterrupted operation of MEG with SQUID magnetometers

NASA Astrophysics Data System (ADS)

Wang, Chao; Sun, Limin; Lichtenwalter, Ben; Zerkle, Brent; Okada, Yoshio

2016-06-01

A closed-cycle helium recycler was developed for continuous uninterrupted operation for magnetometer-based whole-head magnetoencephalography (MEG) systems. The recycler consists of a two stage 4 K pulse-tube cryocooler and is mounted on the roof of a magnetically shielded room (MSR). A flexible liquid helium (LHe) return line on the recycler is inserted into the fill port of the MEG system in the MSR through a slotted opening in the ceiling. The helium vapor is captured through a line that returns the gas to the top of the recycler assembly. A high-purity helium gas cylinder connected to the recycler assembly supplies the gas, which, after it is liquefied, increases the level of LHe in the MEG system during the start-up phase. No storage tank for evaporated helium gas nor a helium gas purifier is used. The recycler is capable of liquefying helium with a rate of ∼17 L/d after precooling the MEG system. It has provided a fully maintenance-free operation under computer control for 7 months without refill of helium. Although the recycler is used for single-orientation operation at this initial testing site, it is designed to operate at ±20° orientations, allowing the MEG system to be tilted for supine and reclining positions. Vibration of the recycler is dampened to an ultra-low level by using several vibration isolation methods, which enables uninterrupted operation during MEG measurements. Recyclers similar to this system may be quite useful even for MEG systems with 100% magnetometers.

Topology of Functional Connectivity and Hub Dynamics in the Beta Band As Temporal Prior for Natural Vision in the Human Brain.

PubMed

Betti, Viviana; Corbetta, Maurizio; de Pasquale, Francesco; Wens, Vincent; Della Penna, Stefania

2018-04-11

Networks hubs represent points of convergence for the integration of information across many different nodes and systems. Although a great deal is known on the topology of hub regions in the human brain, little is known about their temporal dynamics. Here, we examine the static and dynamic centrality of hub regions when measured in the absence of a task (rest) or during the observation of natural or synthetic visual stimuli. We used Magnetoencephalography (MEG) in humans (both sexes) to measure static and transient regional and network-level interaction in α- and β-band limited power (BLP) in three conditions: visual fixation (rest), viewing of movie clips (natural vision), and time-scrambled versions of the same clips (scrambled vision). Compared with rest, we observed in both movie conditions a robust decrement of α-BLP connectivity. Moreover, both movie conditions caused a significant reorganization of connections in the α band, especially between networks. In contrast, β-BLP connectivity was remarkably similar between rest and natural vision. Not only the topology did not change, but the joint dynamics of hubs in a core network during natural vision was predicted by similar fluctuations in the resting state. We interpret these findings by suggesting that slow-varying fluctuations of integration occurring in higher-order regions in the β band may be a mechanism to anticipate and predict slow-varying temporal patterns of the visual environment. SIGNIFICANCE STATEMENT A fundamental question in neuroscience concerns the function of spontaneous brain connectivity. Here, we tested the hypothesis that topology of intrinsic brain connectivity and its dynamics might predict those observed during natural vision. Using MEG, we tracked the static and time-varying brain functional connectivity when observers were either fixating or watching different movie clips. The spatial distribution of connections and the dynamics of centrality of a set of regions were similar during rest and movie in the β band, but not in the α band. These results support the hypothesis that the intrinsic β-rhythm integration occurs with a similar temporal structure during natural vision, possibly providing advanced information about incoming stimuli. Copyright © 2018 the authors 0270-6474/18/383858-14$15.00/0.

Functional Network Disruption in the Degenerative Dementias

PubMed Central

Pievani, Michela; de Haan, Willem; Wu, Tao; Seeley, William W; Frisoni, Giovanni B

2011-01-01

Despite considerable advances toward understanding the molecular pathophysiology of the neurodegenerative dementias, the mechanisms linking molecular changes to neuropathology and the latter to clinical symptoms remain largely obscure. Connectivity is a distinctive feature of the brain and the integrity of functional network dynamics is critical for normal functioning. A better understanding of network disruption in the neurodegenerative dementias may help bridge the gap between molecular changes, pathology and symptoms. Recent findings on functional network disruption as assessed with “resting-state” or intrinsic connectivity fMRI and EEG/MEG have shown distinct patterns of network disruption across the major neurodegenerative diseases. These network abnormalities are relatively specific to the clinical syndromes, and in Alzheimer's disease and frontotemporal dementia network disruption tracks the pattern of pathological changes. These findings may have a practical impact on diagnostic accuracy, allowing earlier detection of neurodegenerative diseases even at the pre-symptomatic stage, and tracking of disease progression. PMID:21778116

Syntactic Computations in the Language Network: Characterizing Dynamic Network Properties Using Representational Similarity Analysis

PubMed Central

Tyler, Lorraine K.; Cheung, Teresa P. L.; Devereux, Barry J.; Clarke, Alex

2013-01-01

The core human capacity of syntactic analysis involves a left hemisphere network involving left inferior frontal gyrus (LIFG) and posterior middle temporal gyrus (LMTG) and the anatomical connections between them. Here we use magnetoencephalography (MEG) to determine the spatio-temporal properties of syntactic computations in this network. Listeners heard spoken sentences containing a local syntactic ambiguity (e.g., “… landing planes …”), at the offset of which they heard a disambiguating verb and decided whether it was an acceptable/unacceptable continuation of the sentence. We charted the time-course of processing and resolving syntactic ambiguity by measuring MEG responses from the onset of each word in the ambiguous phrase and the disambiguating word. We used representational similarity analysis (RSA) to characterize syntactic information represented in the LIFG and left posterior middle temporal gyrus (LpMTG) over time and to investigate their relationship to each other. Testing a variety of lexico-syntactic and ambiguity models against the MEG data, our results suggest early lexico-syntactic responses in the LpMTG and later effects of ambiguity in the LIFG, pointing to a clear differentiation in the functional roles of these two regions. Our results suggest the LpMTG represents and transmits lexical information to the LIFG, which responds to and resolves the ambiguity. PMID:23730293

Maternally Expressed Gene 3, an imprinted non-coding RNA gene, is associated with meningioma pathogenesis and progression

PubMed Central

Zhang, Xun; Gejman, Roger; Mahta, Ali; Zhong, Ying; Rice, Kimberley A.; Zhou, Yunli; Cheunsuchon, Pornsuk; Louis, David N.; Klibanski, Anne

2010-01-01

Meningiomas are common tumors, representing 15-25% of all central nervous system tumors. NF2 gene inactivation on chromosome 22 has been shown as an early event in tumorigenesis; however, few factors underlying tumor growth and progression have been identified. Chromosomal abnormalities of 14q32 are often associated with meningioma pathogenesis and progression; therefore it has been proposed that an as yet unidentified tumor suppressor is present at this locus. MEG3 is an imprinted gene located at 14q32 that encodes a non-coding RNA with an anti-proliferative function. We found that MEG3 mRNA is highly expressed in normal arachnoidal cells. However, MEG3 is not expressed in the majority of human meningiomas or the human meningioma cell lines IOMM-Lee and CH157-MN. There is a strong association between loss of MEG3 expression and tumor grade. Allelic loss at the MEG3 locus is also observed in meningiomas, with increasing prevalence in higher grade tumors. In addition, there is an increase in CpG methylation within the promoter and the imprinting control region of MEG3 gene in meningiomas. Functionally, MEG3 suppresses DNA synthesis in both IOMM-Lee and CH157-MN cells by approximately 60% in BrdU incorporation assays. Colony-forming efficiency assays show that MEG3 inhibits colony formation in CH157-MN cells by approximately 80%. Furthermore, MEG3 stimulates p53-mediated transactivation in these cell lines. Therefore, these data are consistent with the hypothesis that MEG3, which encodes a non-coding RNA, may be a tumor suppressor gene at chromosome 14q32 involved in meningioma progression via a novel mechanism. PMID:20179190

Maternally expressed gene 3, an imprinted noncoding RNA gene, is associated with meningioma pathogenesis and progression.

PubMed

Zhang, Xun; Gejman, Roger; Mahta, Ali; Zhong, Ying; Rice, Kimberley A; Zhou, Yunli; Cheunsuchon, Pornsuk; Louis, David N; Klibanski, Anne

2010-03-15

Meningiomas are common tumors, representing 15% to 25% of all central nervous system tumors. NF2 gene inactivation on chromosome 22 has been shown as an early event in tumorigenesis; however, few factors underlying tumor growth and progression have been identified. The chromosomal abnormalities of 14q32 are often associated with meningioma pathogenesis and progression; therefore, it has been proposed that an as yet unidentified tumor suppressor is present at this locus. Maternally expressed gene 3 (MEG3) is an imprinted gene located at 14q32 which encodes a noncoding RNA with an antiproliferative function. We found that MEG3 mRNA is highly expressed in normal arachnoidal cells. However, MEG3 is not expressed in the majority of human meningiomas or the human meningioma cell lines IOMM-Lee and CH157-MN. There is a strong association between loss of MEG3 expression and tumor grade. Allelic loss at the MEG3 locus is also observed in meningiomas, with increasing prevalence in higher grade tumors. In addition, there is an increase in CpG methylation within the promoter and the imprinting control region of MEG3 gene in meningiomas. Functionally, MEG3 suppresses DNA synthesis in both IOMM-Lee and CH157-MN cells by approximately 60% in bromodeoxyuridine incorporation assays. Colony-forming efficiency assays show that MEG3 inhibits colony formation in CH157-MN cells by approximately 80%. Furthermore, MEG3 stimulates p53-mediated transactivation in these cell lines. Therefore, these data are consistent with the hypothesis that MEG3, which encodes a noncoding RNA, may be a tumor suppressor gene at chromosome 14q32 involved in meningioma progression via a novel mechanism.

Facilitating Neuronal Connectivity Analysis of Evoked Responses by Exposing Local Activity with Principal Component Analysis Preprocessing: Simulation of Evoked MEG

PubMed Central

Gao, Lin; Zhang, Tongsheng; Wang, Jue; Stephen, Julia

2014-01-01

When connectivity analysis is carried out for event related EEG and MEG, the presence of strong spatial correlations from spontaneous activity in background may mask the local neuronal evoked activity and lead to spurious connections. In this paper, we hypothesized PCA decomposition could be used to diminish the background activity and further improve the performance of connectivity analysis in event related experiments. The idea was tested using simulation, where we found that for the 306-channel Elekta Neuromag system, the first 4 PCs represent the dominant background activity, and the source connectivity pattern after preprocessing is consistent with the true connectivity pattern designed in the simulation. Improving signal to noise of the evoked responses by discarding the first few PCs demonstrates increased coherences at major physiological frequency bands when removing the first few PCs. Furthermore, the evoked information was maintained after PCA preprocessing. In conclusion, it is demonstrated that the first few PCs represent background activity, and PCA decomposition can be employed to remove it to expose the evoked activity for the channels under investigation. Therefore, PCA can be applied as a preprocessing approach to improve neuronal connectivity analysis for event related data. PMID:22918837

Facilitating neuronal connectivity analysis of evoked responses by exposing local activity with principal component analysis preprocessing: simulation of evoked MEG.

PubMed

Gao, Lin; Zhang, Tongsheng; Wang, Jue; Stephen, Julia

2013-04-01

When connectivity analysis is carried out for event related EEG and MEG, the presence of strong spatial correlations from spontaneous activity in background may mask the local neuronal evoked activity and lead to spurious connections. In this paper, we hypothesized PCA decomposition could be used to diminish the background activity and further improve the performance of connectivity analysis in event related experiments. The idea was tested using simulation, where we found that for the 306-channel Elekta Neuromag system, the first 4 PCs represent the dominant background activity, and the source connectivity pattern after preprocessing is consistent with the true connectivity pattern designed in the simulation. Improving signal to noise of the evoked responses by discarding the first few PCs demonstrates increased coherences at major physiological frequency bands when removing the first few PCs. Furthermore, the evoked information was maintained after PCA preprocessing. In conclusion, it is demonstrated that the first few PCs represent background activity, and PCA decomposition can be employed to remove it to expose the evoked activity for the channels under investigation. Therefore, PCA can be applied as a preprocessing approach to improve neuronal connectivity analysis for event related data.

Statistical Learning Effects in Musicians and Non-Musicians: An MEG Study

ERIC Educational Resources Information Center

Paraskevopoulos, Evangelos; Kuchenbuch, Anja; Herholz, Sibylle C.; Pantev, Christo

2012-01-01

This study aimed to assess the effect of musical training in statistical learning of tone sequences using Magnetoencephalography (MEG). Specifically, MEG recordings were used to investigate the neural and functional correlates of the pre-attentive ability for detection of deviance, from a statistically learned tone sequence. The effect of…

Decreased expression of MEG3 contributes to retinoblastoma progression and affects retinoblastoma cell growth by regulating the activity of Wnt/β-catenin pathway.

PubMed

Gao, Yali; Lu, Xiaohe

2016-02-01

The aberrant expression of MEG3 has been found in some types of cancers; however, little is known concerning the function of MEG3 in retinoblastoma. To elucidate the roles of MEG3 in retinoblastoma, MEG3 expression was quantified in 63 retinoblastoma samples and corresponding nontumor tissues in this work. Moreover, retinoblastoma cell lines were transfected with pcDNA3.1-MEG3 or si-MEG3, after which proliferation, apoptosis, and expression of β-catenin were assayed. TOP-Flash reporter assay was also used to investigate the activity of the Wnt/β-catenin pathway. The results showed that MEG3 was downregulated in retinoblastoma tissues, and the level of MEG3 was negatively associated with IIRC stages and nodal or distant metastasis. More importantly, Kaplan-Meier survival analysis demonstrated that patients with low MEG3 expression had poorer survival and multivariate Cox regression analysis revealed that MEG3 was an independent prognostic factor in retinoblastoma patients. We also observed that MEG3 expression can be modulated by DNA methylation by using 5-aza-CdR treatment. In addition, overexpression of MEG3 suppressed proliferation, promoted apoptosis, and influences the activity of the Wnt/β-catenin pathway in retinoblastoma cell lines. Furthermore, we found that Wnt/β-catenin pathway activator rescued the anticancer effect of MEG3 in retinoblastoma. In conclusion, our study for the first time demonstrated that MEG3 was a tumor suppressor by negatively regulating the activity of the Wnt/β-catenin pathway in the progression of retinoblastoma and might serve as a prognostic biomarker and molecular therapeutic target.

Adaptive expansion of the maize maternally expressed gene (Meg) family involves changes in expression patterns and protein secondary structures of its members

PubMed Central

2014-01-01

Background The Maternally expressed gene (Meg) family is a locally-duplicated gene family of maize which encodes cysteine-rich proteins (CRPs). The founding member of the family, Meg1, is required for normal development of the basal endosperm transfer cell layer (BETL) and is involved in the allocation of maternal nutrients to growing seeds. Despite the important roles of Meg1 in maize seed development, the evolutionary history of the Meg cluster and the activities of the duplicate genes are not understood. Results In maize, the Meg gene cluster resides in a 2.3 Mb-long genomic region that exhibits many features of non-centromeric heterochromatin. Using phylogenetic reconstruction and syntenic alignments, we identified the pedigree of the Meg family, in which 11 of its 13 members arose in maize after allotetraploidization ~4.8 mya. Phylogenetic and population-genetic analyses identified possible signatures suggesting recent positive selection in Meg homologs. Structural analyses of the Meg proteins indicated potentially adaptive changes in secondary structure from α-helix to β-strand during the expansion. Transcriptomic analysis of the maize endosperm indicated that 6 Meg genes are selectively activated in the BETL, and younger Meg genes are more active than older ones. In endosperms from B73 by Mo17 reciprocal crosses, most Meg genes did not display parent-specific expression patterns. Conclusions Recently-duplicated Meg genes have different protein secondary structures, and their expressions in the BETL dominate over those of older members. Together with the signs of positive selections in the young Meg genes, these results suggest that the expansion of the Meg family involves potentially adaptive transitions in which new members with novel functions prevailed over older members. PMID:25084677

Dynamic functional-structural coupling within acute functional state change phases: Evidence from a depression recognition study.

PubMed

Bi, Kun; Hua, Lingling; Wei, Maobin; Qin, Jiaolong; Lu, Qing; Yao, Zhijian

2016-02-01

Dynamic functional-structural connectivity (FC-SC) coupling might reflect the flexibility by which SC relates to functional connectivity (FC). However, during the dynamic acute state change phases of FC, the relationship between FC and SC may be distinctive and embody the abnormality inherent in depression. This study investigated the depression-related inter-network FC-SC coupling within particular dynamic acute state change phases of FC. Magnetoencephalography (MEG) and diffusion tensor imaging (DTI) data were collected from 26 depressive patients (13 women) and 26 age-matched controls (13 women). We constructed functional brain networks based on MEG data and structural networks from DTI data. The dynamic connectivity regression algorithm was used to identify the state change points of a time series of inter-network FC. The time period of FC that contained change points were partitioned into types of dynamic phases (acute rising phase, acute falling phase,acute rising and falling phase and abrupt FC variation phase) to explore the inter-network FC-SC coupling. The selected FC-SC couplings were then fed into the support vector machine (SVM) for depression recognition. The best discrimination accuracy was 82.7% (P=0.0069) with FC-SC couplings, particularly in the acute rising phase of FC. Within the FC phases of interest, the significant discriminative network pair was related to the salience network vs ventral attention network (SN-VAN) (P=0.0126) during the early rising phase (70-170ms). This study suffers from a small sample size, and the individual acute length of the state change phases was not considered. The increased values of significant discriminative vectors of FC-SC coupling in depression suggested that the capacity to process negative emotion might be more directly related to the SC abnormally and be indicative of more stringent and less dynamic brain function in SN-VAN, especially in the acute rising phase of FC. We demonstrated that depressive brain dysfunctions could be better characterized by reduced FC-SC coupling flexibility in this particular phase. Copyright © 2015 Elsevier B.V. All rights reserved.

Ghost interactions in MEG/EEG source space: A note of caution on inter-areal coupling measures.

PubMed

Palva, J Matias; Wang, Sheng H; Palva, Satu; Zhigalov, Alexander; Monto, Simo; Brookes, Matthew J; Schoffelen, Jan-Mathijs; Jerbi, Karim

2018-06-01

When combined with source modeling, magneto- (MEG) and electroencephalography (EEG) can be used to study long-range interactions among cortical processes non-invasively. Estimation of such inter-areal connectivity is nevertheless hindered by instantaneous field spread and volume conduction, which artificially introduce linear correlations and impair source separability in cortical current estimates. To overcome the inflating effects of linear source mixing inherent to standard interaction measures, alternative phase- and amplitude-correlation based connectivity measures, such as imaginary coherence and orthogonalized amplitude correlation have been proposed. Being by definition insensitive to zero-lag correlations, these techniques have become increasingly popular in the identification of correlations that cannot be attributed to field spread or volume conduction. We show here, however, that while these measures are immune to the direct effects of linear mixing, they may still reveal large numbers of spurious false positive connections through field spread in the vicinity of true interactions. This fundamental problem affects both region-of-interest-based analyses and all-to-all connectome mappings. Most importantly, beyond defining and illustrating the problem of spurious, or "ghost" interactions, we provide a rigorous quantification of this effect through extensive simulations. Additionally, we further show that signal mixing also significantly limits the separability of neuronal phase and amplitude correlations. We conclude that spurious correlations must be carefully considered in connectivity analyses in MEG/EEG source space even when using measures that are immune to zero-lag correlations. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Neural network classifications and correlation analysis of EEG and MEG activity accompanying spontaneous reversals of the Necker cube.

PubMed

Gaetz, M; Weinberg, H; Rzempoluck, E; Jantzen, K J

1998-04-01

It has recently been suggested that reentrant connections are essential in systems that process complex information [A. Damasio, H. Damasio, Cortical systems for the retrieval of concrete knowledge: the convergence zone framework, in: C. Koch, J.L. Davis (Eds.), Large Scale Neuronal Theories of the Brain, The MIT Press, Cambridge, 1995, pp. 61-74; G. Edelman, The Remembered Present, Basic Books, New York, 1989; M.I. Posner, M. Rothbart, Constructing neuronal theories of mind, in: C. Koch, J.L. Davis (Eds.), Large Scale Neuronal Theories of the Brain, The MIT Press, Cambridge, 1995, pp. 183-199; C. von der Malsburg, W. Schneider, A neuronal cocktail party processor, Biol. Cybem., 54 (1986) 29-40]. Reentry is not feedback, but parallel signalling in the time domain between spatially distributed maps, similar to a process of correlation between distributed systems. Accordingly, it was expected that during spontaneous reversals of the Necker cube, complex patterns of correlations between distributed systems would be present in the cortex. The present study included EEG (n=4) and MEG recordings (n=5). Two experimental questions were posed: (1) Can distributed cortical patterns present during perceptual reversals be classified differently using a generalised regression neural network (GRNN) compared to processing of a two-dimensional figure? (2) Does correlated cortical activity increase significantly during perception of a Necker cube reversal? One-second duration single trials of EEG and MEG data were analysed using the GRNN. Electrode/sensor pairings based on cortico-cortical connections were selected to assess correlated activity in each condition. The GRNN significantly classified single trials recorded during Necker cube reversals as different from single trials recorded during perception of a two-dimensional figure for both EEG and MEG. In addition, correlated cortical activity increased significantly in the Necker cube reversal condition for EEG and MEG compared to the perception of a non-reversing stimulus. Coherent MEG activity observed over occipital, parietal and temporal regions is believed to represent neural systems related to the perception of Necker cube reversals. Copyright 1998 Elsevier Science B.V.

Compliant finger sensor for sensorimotor studies in MEG and MR environment

NASA Astrophysics Data System (ADS)

Li, Y.; Yong, X.; Cheung, T. P. L.; Menon, C.

2016-07-01

Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) are widely used for functional brain imaging. The correlations between the sensorimotor functions of the hand and brain activities have been investigated in MEG/fMRI studies. Currently, limited information can be drawn from these studies due to the limitations of existing motion sensors that are used to detect hand movements. One major challenge in designing these motion sensors is to limit the signal interference between the motion sensors and the MEG/fMRI. In this work, a novel finger motion sensor, which contains low-ferromagnetic and non-conductive materials, is introduced. The finger sensor consists of four air-filled chambers. When compressed by finger(s), the pressure change in the chambers can be detected by the electronics of the finger sensor. Our study has validated that the interference between the finger sensor and an MEG is negligible. Also, by applying a support vector machine algorithm to the data obtained from the finger sensor, at least 11 finger patterns can be discriminated. Comparing to the use of traditional electromyography (EMG) in detecting finger motion, our proposed finger motion sensor is not only MEG/fMRI compatible, it is also easy to use. As the signals acquired from the sensor have a higher SNR than that of the EMG, no complex algorithms are required to detect different finger movement patterns. Future studies can utilize this motion sensor to investigate brain activations during different finger motions and correlate the activations with the sensory and motor functions respectively.

MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters.

PubMed

Hincapié, Ana-Sofía; Kujala, Jan; Mattout, Jérémie; Daligault, Sebastien; Delpuech, Claude; Mery, Domingo; Cosmelli, Diego; Jerbi, Karim

2016-01-01

Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation.

MEG Connectivity and Power Detections with Minimum Norm Estimates Require Different Regularization Parameters

PubMed Central

Hincapié, Ana-Sofía; Kujala, Jan; Mattout, Jérémie; Daligault, Sebastien; Delpuech, Claude; Mery, Domingo; Cosmelli, Diego; Jerbi, Karim

2016-01-01

Minimum Norm Estimation (MNE) is an inverse solution method widely used to reconstruct the source time series that underlie magnetoencephalography (MEG) data. MNE addresses the ill-posed nature of MEG source estimation through regularization (e.g., Tikhonov regularization). Selecting the best regularization parameter is a critical step. Generally, once set, it is common practice to keep the same coefficient throughout a study. However, it is yet to be known whether the optimal lambda for spectral power analysis of MEG source data coincides with the optimal regularization for source-level oscillatory coupling analysis. We addressed this question via extensive Monte-Carlo simulations of MEG data, where we generated 21,600 configurations of pairs of coupled sources with varying sizes, signal-to-noise ratio (SNR), and coupling strengths. Then, we searched for the Tikhonov regularization coefficients (lambda) that maximize detection performance for (a) power and (b) coherence. For coherence, the optimal lambda was two orders of magnitude smaller than the best lambda for power. Moreover, we found that the spatial extent of the interacting sources and SNR, but not the extent of coupling, were the main parameters affecting the best choice for lambda. Our findings suggest using less regularization when measuring oscillatory coupling compared to power estimation. PMID:27092179

Resolving human object recognition in space and time

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2014-01-01

A comprehensive picture of object processing in the human brain requires combining both spatial and temporal information about brain activity. Here, we acquired human magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) responses to 92 object images. Multivariate pattern classification applied to MEG revealed the time course of object processing: whereas individual images were discriminated by visual representations early, ordinate and superordinate category levels emerged relatively later. Using representational similarity analysis, we combine human fMRI and MEG to show content-specific correspondence between early MEG responses and primary visual cortex (V1), and later MEG responses and inferior temporal (IT) cortex. We identified transient and persistent neural activities during object processing, with sources in V1 and IT., Finally, human MEG signals were correlated to single-unit responses in monkey IT. Together, our findings provide an integrated space- and time-resolved view of human object categorization during the first few hundred milliseconds of vision. PMID:24464044

Particle swarm optimization and its application in MEG source localization using single time sliced data

NASA Astrophysics Data System (ADS)

Lin, Juan; Liu, Chenglian; Guo, Yongning

2014-10-01

The estimation of neural active sources from the magnetoencephalography (MEG) data is a very critical issue for both clinical neurology and brain functions research. A widely accepted source-modeling technique for MEG involves calculating a set of equivalent current dipoles (ECDs). Depth in the brain is one of difficulties in MEG source localization. Particle swarm optimization(PSO) is widely used to solve various optimization problems. In this paper we discuss its ability and robustness to find the global optimum in different depths of the brain when using single equivalent current dipole (sECD) model and single time sliced data. The results show that PSO is an effective global optimization to MEG source localization when given one dipole in different depths.

Decoding critical long non-coding RNA in ovarian cancer epithelial-to-mesenchymal transition.

PubMed

Mitra, Ramkrishna; Chen, Xi; Greenawalt, Evan J; Maulik, Ujjwal; Jiang, Wei; Zhao, Zhongming; Eischen, Christine M

2017-11-17

Long non-coding RNA (lncRNA) are emerging as contributors to malignancies. Little is understood about the contribution of lncRNA to epithelial-to-mesenchymal transition (EMT), which correlates with metastasis. Ovarian cancer is usually diagnosed after metastasis. Here we report an integrated analysis of >700 ovarian cancer molecular profiles, including genomic data sets, from four patient cohorts identifying lncRNA DNM3OS, MEG3, and MIAT overexpression and their reproducible gene regulation in ovarian cancer EMT. Genome-wide mapping shows 73% of MEG3-regulated EMT-linked pathway genes contain MEG3 binding sites. DNM3OS overexpression, but not MEG3 or MIAT, significantly correlates to worse overall patient survival. DNM3OS knockdown results in altered EMT-linked genes/pathways, mesenchymal-to-epithelial transition, and reduced cell migration and invasion. Proteotranscriptomic characterization further supports the DNM3OS and ovarian cancer EMT connection. TWIST1 overexpression and DNM3OS amplification provides an explanation for increased DNM3OS levels. Therefore, our results elucidate lncRNA that regulate EMT and demonstrate DNM3OS specifically contributes to EMT in ovarian cancer.

Epilepsy Surgery for Individuals with TSC

MedlinePlus

... tomography (PET), single-photon emission tomography (SPECT), magnetoencephalography (MEG), Diffusion Tensor Imaging (DTI), and functional MRI (fMRI). ... sclerosis: a comparison of high resolution EEG and MEG. Epilepsia 47:108-114 Jansen FE, Huffelen ACV, ...

Theta-Modulated Gamma-Band Synchronization Among Activated Regions During a Verb Generation Task

PubMed Central

Doesburg, Sam M.; Vinette, Sarah A.; Cheung, Michael J.; Pang, Elizabeth W.

2012-01-01

Expressive language is complex and involves processing within a distributed network of cortical regions. Functional MRI and magnetoencephalography (MEG) have identified brain areas critical for expressive language, but how these regions communicate across the network remains poorly understood. It is thought that synchronization of oscillations between neural populations, particularly at a gamma rate (>30 Hz), underlies functional integration within cortical networks. Modulation of gamma rhythms by theta-band oscillations (4–8 Hz) has been proposed as a mechanism for the integration of local cell coalitions into large-scale networks underlying cognition and perception. The present study tested the hypothesis that these oscillatory mechanisms of functional integration were present within the expressive language network. We recorded MEG while subjects performed a covert verb generation task. We localized activated cortical regions using beamformer analysis, calculated inter-regional phase locking between activated areas, and measured modulation of inter-regional gamma synchronization by theta phase. The results show task-dependent gamma-band synchronization among regions activated during the performance of the verb generation task, and we provide evidence that these transient and periodic instances of high-frequency connectivity were modulated by the phase of cortical theta oscillations. These findings suggest that oscillatory synchronization and cross-frequency interactions are mechanisms for functional integration among distributed brain areas supporting expressive language processing. PMID:22707946

The Role of Corpus Callosum Development in Functional Connectivity and Cognitive Processing

PubMed Central

Findlay, Anne M.; Honma, Susanne; Jeremy, Rita J.; Strominger, Zoe; Bukshpun, Polina; Wakahiro, Mari; Brown, Warren S.; Paul, Lynn K.; Barkovich, A. James; Mukherjee, Pratik; Nagarajan, Srikantan S.; Sherr, Elliott H.

2012-01-01

The corpus callosum is hypothesized to play a fundamental role in integrating information and mediating complex behaviors. Here, we demonstrate that lack of normal callosal development can lead to deficits in functional connectivity that are related to impairments in specific cognitive domains. We examined resting-state functional connectivity in individuals with agenesis of the corpus callosum (AgCC) and matched controls using magnetoencephalographic imaging (MEG-I) of coherence in the alpha (8–12 Hz), beta (12–30 Hz) and gamma (30–55 Hz) bands. Global connectivity (GC) was defined as synchronization between a region and the rest of the brain. In AgCC individuals, alpha band GC was significantly reduced in the dorsolateral pre-frontal (DLPFC), posterior parietal (PPC) and parieto-occipital cortices (PO). No significant differences in GC were seen in either the beta or gamma bands. We also explored the hypothesis that, in AgCC, this regional reduction in functional connectivity is explained primarily by a specific reduction in interhemispheric connectivity. However, our data suggest that reduced connectivity in these regions is driven by faulty coupling in both inter- and intrahemispheric connectivity. We also assessed whether the degree of connectivity correlated with behavioral performance, focusing on cognitive measures known to be impaired in AgCC individuals. Neuropsychological measures of verbal processing speed were significantly correlated with resting-state functional connectivity of the left medial and superior temporal lobe in AgCC participants. Connectivity of DLPFC correlated strongly with performance on the Tower of London in the AgCC cohort. These findings indicate that the abnormal callosal development produces salient but selective (alpha band only) resting-state functional connectivity disruptions that correlate with cognitive impairment. Understanding the relationship between impoverished functional connectivity and cognition is a key step in identifying the neural mechanisms of language and executive dysfunction in common neurodevelopmental and psychiatric disorders where disruptions of callosal development are consistently identified. PMID:22870191

Variability and bias between magnetoencephalography systems in non-invasive localization of the primary somatosensory cortex.

PubMed

Bardouille, Timothy; Power, Lindsey; Lalancette, Marc; Bishop, Ronald; Beyea, Steven; Taylor, Margot J; Dunkley, Benjamin T

2018-05-26

Magnetoencephalography (MEG) provides functional neuroimaging data for pre-surgical planning in patients with epilepsy or brain tumour. For mapping the primary somatosensory cortex (S1), MEG data are acquired while a patient undergoes median nerve stimulation (MNS) to localize components of the somatosensory evoked field (SEF). In clinical settings, only one MEG imaging session is usually possible due to limited resources. As such, it is important to have an a priori estimate of the expected variability in localization. Variability in S1 localization between mapping sessions using the same MEG system has been previously measured as 8 mm. There are different types of MEG systems available with varied hardware and software, and it is not known how using a different MEG system will impact on S1 localization. In our study, healthy participants underwent the MNS procedure with two different MEG systems (Vector View and CTF). We compared the location, amplitude and latency of SEF components between data from each system to quantify variability and bias between MEG systems. We found 8-11 mm variability in S1 localization between the two MEG systems, and no evidence for a systematic bias in location, amplitude or latency between the two systems. These findings suggest that S1 localization is not biased by the type of MEG system used, and that differences between the two systems are not a major contributor to variability in localization. Copyright © 2018. Published by Elsevier B.V.

Thalamocortical and intracortical laminar connectivity determines sleep spindle properties.

PubMed

Krishnan, Giri P; Rosen, Burke Q; Chen, Jen-Yung; Muller, Lyle; Sejnowski, Terrence J; Cash, Sydney S; Halgren, Eric; Bazhenov, Maxim

2018-06-27

Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.

Integration of Functional Magnetic Resonance Imaging and Magnetoencephalography Functional Maps Into a CyberKnife Planning System: Feasibility Study for Motor Activity Localization and Dose Planning.

PubMed

De Martin, Elena; Duran, Dunja; Ghielmetti, Francesco; Visani, Elisa; Aquino, Domenico; Marchetti, Marcello; Sebastiano, Davide Rossi; Cusumano, Davide; Bruzzone, Maria Grazia; Panzica, Ferruccio; Fariselli, Laura

2017-12-01

Magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) provide noninvasive localization of eloquent brain areas for presurgical planning. The aim of this study is the integration of MEG and fMRI maps into a CyberKnife (CK) system to optimize dose planning. Four patients with brain metastases in the motor area underwent functional imaging study of the hand motor cortex before radiosurgery. MEG data were acquired during a visually cued hand motor task. Motor activations were identified also using an fMRI block-designed paradigm. MEG and fMRI maps were then integrated into a CK system and contoured as organs at risk for treatment planning optimization. The integration of fMRI data into the CK system was achieved for all patients by means of a standardized protocol. We also implemented an ad hoc pipeline to convert the MEG signal into a DICOM standard, to make sure that it was readable by our CK treatment planning system. Inclusion of the activation areas into the optimization plan allowed the creation of treatment plans that reduced the irradiation of the motor cortex yet not affecting the brain peripheral dose. The availability of advanced neuroimaging techniques is playing an increasingly important role in radiosurgical planning strategy. We successfully imported MEG and fMRI activations into a CK system. This additional information can improve dose sparing of eloquent areas, allowing a more comprehensive investigation of the related dose-volume constraints that in theory could translate into a gain in tumor local control, and a reduction of neurological complications. Copyright © 2017 Elsevier Inc. All rights reserved.

Detecting Functional Connectivity During Audiovisual Integration with MEG: A Comparison of Connectivity Metrics.

PubMed

Ard, Tyler; Carver, Frederick W; Holroyd, Tom; Horwitz, Barry; Coppola, Richard

2015-08-01

In typical magnetoencephalography and/or electroencephalography functional connectivity analysis, researchers select one of several methods that measure a relationship between regions to determine connectivity, such as coherence, power correlations, and others. However, it is largely unknown if some are more suited than others for various types of investigations. In this study, the authors investigate seven connectivity metrics to evaluate which, if any, are sensitive to audiovisual integration by contrasting connectivity when tracking an audiovisual object versus connectivity when tracking a visual object uncorrelated with the auditory stimulus. The authors are able to assess the metrics' performances at detecting audiovisual integration by investigating connectivity between auditory and visual areas. Critically, the authors perform their investigation on a whole-cortex all-to-all mapping, avoiding confounds introduced in seed selection. The authors find that amplitude-based connectivity measures in the beta band detect strong connections between visual and auditory areas during audiovisual integration, specifically between V4/V5 and auditory cortices in the right hemisphere. Conversely, phase-based connectivity measures in the beta band as well as phase and power measures in alpha, gamma, and theta do not show connectivity between audiovisual areas. The authors postulate that while beta power correlations detect audiovisual integration in the current experimental context, it may not always be the best measure to detect connectivity. Instead, it is likely that the brain utilizes a variety of mechanisms in neuronal communication that may produce differential types of temporal relationships.

Cross-Correlation of Motor Activity Signals from dc-Magnetoencephalography, Near-Infrared Spectroscopy, and Electromyography

PubMed Central

Sander, Tilmann H.; Leistner, Stefanie; Wabnitz, Heidrun; Mackert, Bruno-Marcel; Macdonald, Rainer; Trahms, Lutz

2010-01-01

Neuronal and vascular responses due to finger movements were synchronously measured using dc-magnetoencephalography (dcMEG) and time-resolved near-infrared spectroscopy (trNIRS). The finger movements were monitored with electromyography (EMG). Cortical responses related to the finger movement sequence were extracted by independent component analysis from both the dcMEG and the trNIRS data. The temporal relations between EMG rate, dcMEG, and trNIRS responses were assessed pairwise using the cross-correlation function (CCF), which does not require epoch averaging. A positive lag on a scale of seconds was found for the maximum of the CCF between dcMEG and trNIRS. A zero lag is observed for the CCF between dcMEG and EMG. Additionally this CCF exhibits oscillations at the frequency of individual finger movements. These findings show that the dcMEG with a bandwidth up to 8 Hz records both slow and faster neuronal responses, whereas the vascular response is confirmed to change on a scale of seconds. PMID:20145717

Cross-correlation of motor activity signals from dc-magnetoencephalography, near-infrared spectroscopy, and electromyography.

PubMed

Sander, Tilmann H; Leistner, Stefanie; Wabnitz, Heidrun; Mackert, Bruno-Marcel; Macdonald, Rainer; Trahms, Lutz

2010-01-01

Neuronal and vascular responses due to finger movements were synchronously measured using dc-magnetoencephalography (dcMEG) and time-resolved near-infrared spectroscopy (trNIRS). The finger movements were monitored with electromyography (EMG). Cortical responses related to the finger movement sequence were extracted by independent component analysis from both the dcMEG and the trNIRS data. The temporal relations between EMG rate, dcMEG, and trNIRS responses were assessed pairwise using the cross-correlation function (CCF), which does not require epoch averaging. A positive lag on a scale of seconds was found for the maximum of the CCF between dcMEG and trNIRS. A zero lag is observed for the CCF between dcMEG and EMG. Additionally this CCF exhibits oscillations at the frequency of individual finger movements. These findings show that the dcMEG with a bandwidth up to 8 Hz records both slow and faster neuronal responses, whereas the vascular response is confirmed to change on a scale of seconds.

LncRNA MEG3 inhibited osteogenic differentiation of bone marrow mesenchymal stem cells from postmenopausal osteoporosis by targeting miR-133a-3p.

PubMed

Wang, Qiujun; Li, Ying; Zhang, Yuanxia; Ma, Lan; Lin, Lin; Meng, Jia; Jiang, Lihong; Wang, Liping; Zhou, Ping; Zhang, Yina

2017-05-01

Long non-coding RNA (lncRNA) MEG3 has proven to be an important regulator involved in the pathogenesis and development of various human diseases. However, the functional involvement of MEG3 in postmenopausal osteoporosis (PMOP) and its mechanism is still unclear. Bone marrow mesenchymal stem cells (BMSCs) were isolated and cultured from mouse pathologic models and patients with PMOP, respectively. The expression of MEG3 and miR-133a-3p in BMSCs was detected using qRT-PCR. The recombinant expression vector was constructed and transfected into BMSCs to regulate the endogenous expression of MEG3 and miR-133a-3p. The mineralized nodules formation, alkaline phosphatase (ALP) activity and Runx2, OCN, OPN expressions were used as specific markers for the differentiation of osteoblasts. The expressions of MEG3 and miR-133a-3p in BMSCs from PMOP were increased, and there was a positive correlation between MEG3 and miR-133a-3p expression in BMSCs. In the differentiation process from BMSCs to osteoblasts, the expressions of MEG3 and miR-133a-3p were markedly decreased, and MEG3 overexpression reversed the osteogenic induction-mediated downregulation of miR-133a-3p, which was accompanied by significant decline in SLC39A1 expression. Furthermore, miR-133a-3p silencing or upregulation eliminated the effects of MEG3 on the osteogenic differentiation of BMSCs through direct binding. The research indicated that MEG3 regulated the expression of miR-133a-3p, and inhibited the osteogenic differentiation of BMSCs induced PMOP. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Alpha, delta and theta rhythms in a neural net model. Comparison with MEG data.

PubMed

Kotini, A; Anninos, P

2016-01-07

The aim of this study is to provide information regarding the comparison of a neural model to MEG measurements. Our study population consisted of 10 epileptic patients and 10 normal subjects. The epileptic patients had high MEG amplitudes characterized with θ (4-7 Hz) or δ (2-3 Hz) rhythms and absence of α-rhythm (8-13 Hz). The statistical analysis of such activities corresponded to Poisson distribution. Conversely, the MEG from normal subjects had low amplitudes, higher frequencies and presence of α-rhythm (8-13 Hz). Such activities were not synchronized and their distributions were Gauss. These findings were in agreement with our theoretical neural model. The comparison of the neural network with MEG data provides information about the status of brain function in epileptic and normal states. Copyright © 2015 Elsevier Ltd. All rights reserved.

Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms.

PubMed

Cabral, Joana; Kringelbach, Morten L; Deco, Gustavo

2017-10-15

Over the last decade, we have observed a revolution in brain structural and functional Connectomics. On one hand, we have an ever-more detailed characterization of the brain's white matter structural connectome. On the other, we have a repertoire of consistent functional networks that form and dissipate over time during rest. Despite the evident spatial similarities between structural and functional connectivity, understanding how different time-evolving functional networks spontaneously emerge from a single structural network requires analyzing the problem from the perspective of complex network dynamics and dynamical system's theory. In that direction, bottom-up computational models are useful tools to test theoretical scenarios and depict the mechanisms at the genesis of resting-state activity. Here, we provide an overview of the different mechanistic scenarios proposed over the last decade via computational models. Importantly, we highlight the need of incorporating additional model constraints considering the properties observed at finer temporal scales with MEG and the dynamical properties of FC in order to refresh the list of candidate scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

A new wavelet transform to sparsely represent cortical current densities for EEG/MEG inverse problems.

PubMed

Liao, Ke; Zhu, Min; Ding, Lei

2013-08-01

The present study investigated the use of transform sparseness of cortical current density on human brain surface to improve electroencephalography/magnetoencephalography (EEG/MEG) inverse solutions. Transform sparseness was assessed by evaluating compressibility of cortical current densities in transform domains. To do that, a structure compression method from computer graphics was first adopted to compress cortical surface structure, either regular or irregular, into hierarchical multi-resolution meshes. Then, a new face-based wavelet method based on generated multi-resolution meshes was proposed to compress current density functions defined on cortical surfaces. Twelve cortical surface models were built by three EEG/MEG softwares and their structural compressibility was evaluated and compared by the proposed method. Monte Carlo simulations were implemented to evaluate the performance of the proposed wavelet method in compressing various cortical current density distributions as compared to other two available vertex-based wavelet methods. The present results indicate that the face-based wavelet method can achieve higher transform sparseness than vertex-based wavelet methods. Furthermore, basis functions from the face-based wavelet method have lower coherence against typical EEG and MEG measurement systems than vertex-based wavelet methods. Both high transform sparseness and low coherent measurements suggest that the proposed face-based wavelet method can improve the performance of L1-norm regularized EEG/MEG inverse solutions, which was further demonstrated in simulations and experimental setups using MEG data. Thus, this new transform on complicated cortical structure is promising to significantly advance EEG/MEG inverse source imaging technologies. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

MEG Working Memory N-Back Task Reveals Functional Deficits in Combat-Related Mild Traumatic Brain Injury.

PubMed

Huang, Ming-Xiong; Nichols, Sharon; Robb-Swan, Ashley; Angeles-Quinto, Annemarie; Harrington, Deborah L; Drake, Angela; Huang, Charles W; Song, Tao; Diwakar, Mithun; Risbrough, Victoria B; Matthews, Scott; Clifford, Royce; Cheng, Chung-Kuan; Huang, Jeffrey W; Sinha, Anusha; Yurgil, Kate A; Ji, Zhengwei; Lerman, Imanuel; Lee, Roland R; Baker, Dewleen G

2018-04-13

Combat-related mild traumatic brain injury (mTBI) is a leading cause of sustained cognitive impairment in military service members and Veterans. However, the mechanism of persistent cognitive deficits including working memory (WM) dysfunction is not fully understood in mTBI. Few studies of WM deficits in mTBI have taken advantage of the temporal and frequency resolution afforded by electromagnetic measurements. Using magnetoencephalography (MEG) and an N-back WM task, we investigated functional abnormalities in combat-related mTBI. Study participants included 25 symptomatic active-duty service members or Veterans with combat-related mTBI and 20 healthy controls with similar combat experiences. MEG source-magnitude images were obtained for alpha (8-12 Hz), beta (15-30 Hz), gamma (30-90 Hz), and low-frequency (1-7 Hz) bands. Compared with healthy combat controls, mTBI participants showed increased MEG signals across frequency bands in frontal pole (FP), ventromedial prefrontal cortex, orbitofrontal cortex (OFC), and anterior dorsolateral prefrontal cortex (dlPFC), but decreased MEG signals in anterior cingulate cortex. Hyperactivations in FP, OFC, and anterior dlPFC were associated with slower reaction times. MEG activations in lateral FP also negatively correlated with performance on tests of letter sequencing, verbal fluency, and digit symbol coding. The profound hyperactivations from FP suggest that FP is particularly vulnerable to combat-related mTBI.

Downregulated long non-coding RNA MEG3 in breast cancer regulates proliferation, migration and invasion by depending on p53’s transcriptional activity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Lin; Li, Yu; Yang, Bangxiang, E-mail: b19933009@qq.coom

Long non-coding RNAs (lncRNAs) was found to play critical roles in tumorigenesis, hence, screen of tumor-related lncRNAs, identification of their biological roles is important for understanding the processes of tumorigenesis. In this study, we identified the expressing difference of several tumor-related lncRNAs in breast cancer samples and found that, MEG3, which is downregulated in non-small cell lung cancer (NSCLC) tumor tissues, is also downregulated in breast cancer samples compared with adjacent tissues. For figuring out the effect of MEG3 in breast cancer cells MCF7 and MB231, we overexpressed MEG3 in these cells, and found that it resulted the inhibition ofmore » proliferation, colony formation, migration and invasion capacities by enhancing p53’s transcriptional activity on its target genes, including p21, Maspin and KAI1. MEG3 presented similar effects in MB157, which is a p53-null breast cancer cell line, when functional p53 but not p53R273H mutant, which lacks transcriptional activity, was introduced. Surprisingly, overexpression of MEG3 activates p53’s transcriptional activity by decreasing MDM2’s transcription level, and thus stabilizes and accumulates P53. Taken together, our findings indicate that MEG3 is downregulated in breast cancer tissues and affects breast cancer cells’ malignant behaviors, which indicate MEG3 a potential therapeutic target for breast cancer. - Highlights: • MEG3 RNA is widely downregulated in breast tumor tissue. • MEG3 regulates P53 indirectly through transcriptional regulation of MDM2. • Under unstressed condition, MEG3-related P53 accumulation transcriptionally activates p53’s target genes. • MEG3 expression level tightly regulates proliferation, colony formation, migration and invasion in breast tumor cells.« less

"Heating up" or "Cooling up" the Brain? MEG Evidence that Phrasal Verbs Are Lexical Units

ERIC Educational Resources Information Center

Cappelle, Bert; Shtyrov, Yury; Pulvermuller, Friedemann

2010-01-01

There is a considerable linguistic debate on whether phrasal verbs (e.g., "turn up," "break down") are processed as two separate words connected by a syntactic rule or whether they form a single lexical unit. Moreover, views differ on whether meaning (transparency vs. opacity) plays a role in determining their syntactically-connected or lexical…

Asymmetric Engagement of Amygdala and Its Gamma Connectivity in Early Emotional Face Processing

PubMed Central

Liu, Tai-Ying; Chen, Yong-Sheng; Hsieh, Jen-Chuen; Chen, Li-Fen

2015-01-01

The amygdala has been regarded as a key substrate for emotion processing. However, the engagement of the left and right amygdala during the early perceptual processing of different emotional faces remains unclear. We investigated the temporal profiles of oscillatory gamma activity in the amygdala and effective connectivity of the amygdala with the thalamus and cortical areas during implicit emotion-perceptual tasks using event-related magnetoencephalography (MEG). We found that within 100 ms after stimulus onset the right amygdala habituated to emotional faces rapidly (with duration around 20–30 ms), whereas activity in the left amygdala (with duration around 50–60 ms) sustained longer than that in the right. Our data suggest that the right amygdala could be linked to autonomic arousal generated by facial emotions and the left amygdala might be involved in decoding or evaluating expressive faces in the early perceptual emotion processing. The results of effective connectivity provide evidence that only negative emotional processing engages both cortical and subcortical pathways connected to the right amygdala, representing its evolutional significance (survival). These findings demonstrate the asymmetric engagement of bilateral amygdala in emotional face processing as well as the capability of MEG for assessing thalamo-cortico-limbic circuitry. PMID:25629899

Development of multichannel MEG system at IGCAR

NASA Astrophysics Data System (ADS)

Mariyappa, N.; Parasakthi, C.; Gireesan, K.; Sengottuvel, S.; Patel, Rajesh; Janawadkar, M. P.; Radhakrishnan, T. S.; Sundar, C. S.

2013-02-01

We describe some of the challenging aspects in the indigenous development of the whole head multichannel magnetoencephalography (MEG) system at IGCAR, Kalpakkam. These are: i) fabrication and testing of a helmet shaped sensor array holder of a polymeric material experimentally tested to be compatible with liquid helium temperatures, ii) the design and fabrication of the PCB adapter modules, keeping in mind the inter-track cross talk considerations between the electrical leads used to provide connections from SQUID at liquid helium temperature (4.2K) to the electronics at room temperature (300K) and iii) use of high resistance manganin wires for the 86 channels (86×8 leads) essential to reduce the total heat leak which, however, inevitably causes an attenuation of the SQUID output signal due to voltage drop in the leads. We have presently populated 22 of the 86 channels, which include 6 reference channels to reject the common mode noise. The whole head MEG system to cover all the lobes of the brain will be progressively assembled when other three PCB adapter modules, presently under fabrication, become available. The MEG system will be used for a variety of basic and clinical studies including localization of epileptic foci during pre-surgical mapping in collaboration with neurologists.

Electrophysiological resting-state biomarker for diagnosing mesial temporal lobe epilepsy with hippocampal sclerosis.

PubMed

Jin, Seung-Hyun; Chung, Chun Kee

2017-01-01

The main aim of the present study was to evaluate whether resting-state functional connectivity of magnetoencephalography (MEG) signals can differentiate patients with mesial temporal lobe epilepsy (MTLE) from healthy controls (HC) and can differentiate between right and left MTLE as a diagnostic biomarker. To this end, a support vector machine (SVM) method among various machine learning algorithms was employed. We compared resting-state functional networks between 46 MTLE (right MTLE=23; left MTLE=23) patients with histologically proven HS who were free of seizure after surgery, and 46 HC. The optimal SVM group classifier distinguished MTLE patients with a mean accuracy of 95.1% (sensitivity=95.8%; specificity=94.3%). Increased connectivity including the right posterior cingulate gyrus and decreased connectivity including at least one sensory-related resting-state network were key features reflecting the differences between MTLE patients and HC. The optimal SVM model distinguished between right and left MTLE patients with a mean accuracy of 76.2% (sensitivity=76.0%; specificity=76.5%). We showed the potential of electrophysiological resting-state functional connectivity, which reflects brain network reorganization in MTLE patients, as a possible diagnostic biomarker to differentiate MTLE patients from HC and differentiate between right and left MTLE patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Non-invasive Investigation of Human Hippocampal Rhythms Using Magnetoencephalography: A Review.

PubMed

Pu, Yi; Cheyne, Douglas O; Cornwell, Brian R; Johnson, Blake W

2018-01-01

Hippocampal rhythms are believed to support crucial cognitive processes including memory, navigation, and language. Due to the location of the hippocampus deep in the brain, studying hippocampal rhythms using non-invasive magnetoencephalography (MEG) recordings has generally been assumed to be methodologically challenging. However, with the advent of whole-head MEG systems in the 1990s and development of advanced source localization techniques, simulation and empirical studies have provided evidence that human hippocampal signals can be sensed by MEG and reliably reconstructed by source localization algorithms. This paper systematically reviews simulation studies and empirical evidence of the current capacities and limitations of MEG "deep source imaging" of the human hippocampus. Overall, these studies confirm that MEG provides a unique avenue to investigate human hippocampal rhythms in cognition, and can bridge the gap between animal studies and human hippocampal research, as well as elucidate the functional role and the behavioral correlates of human hippocampal oscillations.

Non-invasive Investigation of Human Hippocampal Rhythms Using Magnetoencephalography: A Review

PubMed Central

Pu, Yi; Cheyne, Douglas O.; Cornwell, Brian R.; Johnson, Blake W.

2018-01-01

Hippocampal rhythms are believed to support crucial cognitive processes including memory, navigation, and language. Due to the location of the hippocampus deep in the brain, studying hippocampal rhythms using non-invasive magnetoencephalography (MEG) recordings has generally been assumed to be methodologically challenging. However, with the advent of whole-head MEG systems in the 1990s and development of advanced source localization techniques, simulation and empirical studies have provided evidence that human hippocampal signals can be sensed by MEG and reliably reconstructed by source localization algorithms. This paper systematically reviews simulation studies and empirical evidence of the current capacities and limitations of MEG “deep source imaging” of the human hippocampus. Overall, these studies confirm that MEG provides a unique avenue to investigate human hippocampal rhythms in cognition, and can bridge the gap between animal studies and human hippocampal research, as well as elucidate the functional role and the behavioral correlates of human hippocampal oscillations. PMID:29755314

Evaluation of realistic layouts for next generation on-scalp MEG: spatial information density maps.

PubMed

Riaz, Bushra; Pfeiffer, Christoph; Schneiderman, Justin F

2017-08-01

While commercial magnetoencephalography (MEG) systems are the functional neuroimaging state-of-the-art in terms of spatio-temporal resolution, MEG sensors have not changed significantly since the 1990s. Interest in newer sensors that operate at less extreme temperatures, e.g., high critical temperature (high-T c ) SQUIDs, optically-pumped magnetometers, etc., is growing because they enable significant reductions in head-to-sensor standoff (on-scalp MEG). Various metrics quantify the advantages of on-scalp MEG, but a single straightforward one is lacking. Previous works have furthermore been limited to arbitrary and/or unrealistic sensor layouts. We introduce spatial information density (SID) maps for quantitative and qualitative evaluations of sensor arrays. SID-maps present the spatial distribution of information a sensor array extracts from a source space while accounting for relevant source and sensor parameters. We use it in a systematic comparison of three practical on-scalp MEG sensor array layouts (based on high-T c SQUIDs) and the standard Elekta Neuromag TRIUX magnetometer array. Results strengthen the case for on-scalp and specifically high-T c SQUID-based MEG while providing a path for the practical design of future MEG systems. SID-maps are furthermore general to arbitrary magnetic sensor technologies and source spaces and can thus be used for design and evaluation of sensor arrays for magnetocardiography, magnetic particle imaging, etc.

EEG and MEG: sensitivity to epileptic spike activity as function of source orientation and depth.

PubMed

Hunold, A; Funke, M E; Eichardt, R; Stenroos, M; Haueisen, J

2016-07-01

Simultaneous electroencephalography (EEG) and magnetoencephalography (MEG) recordings of neuronal activity from epileptic patients reveal situations in which either EEG or MEG or both modalities show visible interictal spikes. While different signal-to-noise ratios (SNRs) of the spikes in EEG and MEG have been reported, a quantitative relation of spike source orientation and depth as well as the background brain activity to the SNR has not been established. We investigated this quantitative relationship for both dipole and patch sources in an anatomically realistic cortex model. Altogether, 5600 dipole and 3300 patch sources were distributed on the segmented cortical surfaces of two volunteers. The sources were classified according to their quantified depths and orientations, ranging from 20 mm to 60 mm below the skin surface and radial and tangential, respectively. The source time-courses mimicked an interictal spike, and the simulated background activity emulated resting activity. Simulations were conducted with individual three-compartment boundary element models. The SNR was evaluated for 128 EEG, 102 MEG magnetometer, and 204 MEG gradiometer channels. For superficial dipole and superficial patch sources, EEG showed higher SNRs for dominantly radial orientations, and MEG showed higher values for dominantly tangential orientations. Gradiometers provided higher SNR than magnetometers for superficial sources, particularly for those with dominantly tangential orientations. The orientation dependent difference in SNR in EEG and MEG gradually changed as the sources were located deeper, where the interictal spikes generated higher SNRs in EEG compared to those in MEG for all source orientations. With deep sources, the SNRs in gradiometers and magnetometers were of the same order. To better detect spikes, both EEG and MEG should be used.

A supplementary functional connectivity microstate attached to the default mode network in depression revealed by resting-state magnetoencephalography.

PubMed

Zhang, Siqi; Tian, Shui; Chattun, Mohammad Ridwan; Tang, Hao; Yan, Rui; Bi, Kun; Yao, Zhijian; Lu, Qing

2018-04-20

Default mode network (DMN) has discernable involvement in the representation of negative, self-referential information in depression. Both increased and decreased resting-state functional connectivity between the anterior and posterior DMN have been observed in depression. These conflicting connectivity differences necessitated further exploration of the resting-state DMN dysfunction in depression. Hence, we investigated the time-varying dynamic interactions within the DMN via functional connectivity microstates in a sub-second level. 25 patients with depression and 25 matched healthy controls were enrolled in the MEG analysis. Spherical K-means algorithms embedded within an iterative optimization frame were applied to sliding windowed correlation matrices, resulting in sub-second alternations of two functional connectivity microstates for groups and highlighting the presence of functional variability. In the power dominant state, depressed patients showed a transient decreased pattern that reflected inter/intra-subnetwork deregulation. A supplementary negatively correlated state simultaneously presented with increased connectivity between the ventromedial prefrontal cortex (vmPFC) and the posterior cingulate cortex (PCC), two core nodes for the anterior and posterior DMN respectively. Additionally, depressed patients stayed longer in the supplementary microstate compared to healthy controls. During the time spent in the supplementary microstate, an attempt to compensate for the aberrant effect of vmPFC on PCC across DMN subnetworks was possibly made to balance the self-related processes disturbed by the dominant pattern. The functional compensation mechanism of the supplementary microstate attached to the dominant disrupted one provided a possible explanation to the existing inconsistent findings between the anterior and posterior DMN in depression. Copyright © 2018 Elsevier Inc. All rights reserved.

Optimized beamforming for simultaneous MEG and intracranial local field potential recordings in deep brain stimulation patients.

PubMed

Litvak, Vladimir; Eusebio, Alexandre; Jha, Ashwani; Oostenveld, Robert; Barnes, Gareth R; Penny, William D; Zrinzo, Ludvic; Hariz, Marwan I; Limousin, Patricia; Friston, Karl J; Brown, Peter

2010-05-01

Insight into how brain structures interact is critical for understanding the principles of functional brain architectures and may lead to better diagnosis and therapy for neuropsychiatric disorders. We recorded, simultaneously, magnetoencephalographic (MEG) signals and subcortical local field potentials (LFP) in a Parkinson's disease (PD) patient with bilateral deep brain stimulation (DBS) electrodes in the subthalamic nucleus (STN). These recordings offer a unique opportunity to characterize interactions between the subcortical structures and the neocortex. However, high-amplitude artefacts appeared in the MEG. These artefacts originated from the percutaneous extension wire, rather than from the actual DBS electrode and were locked to the heart beat. In this work, we show that MEG beamforming is capable of suppressing these artefacts and quantify the optimal regularization required. We demonstrate how beamforming makes it possible to localize cortical regions whose activity is coherent with the STN-LFP, extract artefact-free virtual electrode time-series from regions of interest and localize cortical areas exhibiting specific task-related power changes. This furnishes results that are consistent with previously reported results using artefact-free MEG data. Our findings demonstrate that physiologically meaningful information can be extracted from heavily contaminated MEG signals and pave the way for further analysis of combined MEG-LFP recordings in DBS patients. 2009 Elsevier Inc. All rights reserved.

Recovery of directed intracortical connectivity from fMRI data

NASA Astrophysics Data System (ADS)

Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

2016-06-01

The brain exhibits complex spatio-temporal patterns of activity. In particular, its baseline activity at rest has a specific structure: imaging techniques (e.g., fMRI, EEG and MEG) show that cortical areas experience correlated fluctuations, which is referred to as functional connectivity (FC). The present study relies on our recently developed model in which intracortical white-matter connections shape noise-driven fluctuations to reproduce FC observed in experimental data (here fMRI BOLD signal). Here noise has a functional role and represents the variability of neural activity. The model also incorporates anatomical information obtained using diffusion tensor imaging (DTI), which estimates the density of white-matter fibers (structural connectivity, SC). After optimization to match empirical FC, the model provides an estimation of the efficacies of these fibers, which we call effective connectivity (EC). EC differs from SC, as EC not only accounts for the density of neural fibers, but also the concentration of synapses formed at their end, the type of neurotransmitters associated and the excitability of target neural populations. In summary, the model combines anatomical SC and activity FC to evaluate what drives the neural dynamics, embodied in EC. EC can then be analyzed using graph theory to understand how it generates FC and to seek for functional communities among cortical areas (parcellation of 68 areas). We find that intracortical connections are not symmetric, which affects the dynamic range of cortical activity (i.e., variety of states it can exhibit).

Impact of SQUIDs on functional imaging in neuroscience

NASA Astrophysics Data System (ADS)

Della Penna, Stefania; Pizzella, Vittorio; Romani, Gian Luca

2014-04-01

This paper provides an overview on the basic principles and applications of magnetoencephalography (MEG), a technique that requires the use of many SQUIDs and thus represents one of the most important applications of superconducting electronics. Since the development of the first SQUID magnetometers, it was clear that these devices could be used to measure the ultra-low magnetic signals associated with the bioelectric activity of the neurons of the human brain. Forty years on from the first measurement of magnetic alpha rhythm by David Cohen, MEG has become a fundamental tool for the investigation of brain functions. The simple localization of cerebral sources activated by sensory stimulation performed in the early years has been successively expanded to the identification of the sequence of neuronal pool activations, thus decrypting information of the hierarchy underlying cerebral processing. This goal has been achieved thanks to the development of complex instrumentation, namely whole head MEG systems, allowing simultaneous measurement of magnetic fields all over the scalp with an exquisite time resolution. The latest trends in MEG, such as the study of brain networks, i.e. how the brain organizes itself in a coherent and stable way, are discussed. These sound applications together with the latest technological developments aimed at implementing systems able to record MEG signals and magnetic resonance imaging (MRI) of the head with the same set-up pave the way to high performance systems for brain functional investigation in the healthy and the sick population.

Consistency and similarity of MEG- and fMRI-signal time courses during movie viewing.

PubMed

Lankinen, Kaisu; Saari, Jukka; Hlushchuk, Yevhen; Tikka, Pia; Parkkonen, Lauri; Hari, Riitta; Koskinen, Miika

2018-06-01

Movie viewing allows human perception and cognition to be studied in complex, real-life-like situations in a brain-imaging laboratory. Previous studies with functional magnetic resonance imaging (fMRI) and with magneto- and electroencephalography (MEG and EEG) have demonstrated consistent temporal dynamics of brain activity across movie viewers. However, little is known about the similarities and differences of fMRI and MEG or EEG dynamics during such naturalistic situations. We thus compared MEG and fMRI responses to the same 15-min black-and-white movie in the same eight subjects who watched the movie twice during both MEG and fMRI recordings. We analyzed intra- and intersubject voxel-wise correlations within each imaging modality as well as the correlation of the MEG envelopes and fMRI signals. The fMRI signals showed voxel-wise within- and between-subjects correlations up to r = 0.66 and r = 0.37, respectively, whereas these correlations were clearly weaker for the envelopes of band-pass filtered (7 frequency bands below 100 Hz) MEG signals (within-subjects correlation r < 0.14 and between-subjects r < 0.05). Direct MEG-fMRI voxel-wise correlations were unreliable. Notably, applying a spatial-filtering approach to the MEG data uncovered consistent canonical variates that showed considerably stronger (up to r = 0.25) between-subjects correlations than the univariate voxel-wise analysis. Furthermore, the envelopes of the time courses of these variates up to about 10 Hz showed association with fMRI signals in a general linear model. Similarities between envelopes of MEG canonical variates and fMRI voxel time-courses were seen mostly in occipital, but also in temporal and frontal brain regions, whereas intra- and intersubject correlations for MEG and fMRI separately were strongest only in the occipital areas. In contrast to the conventional univariate analysis, the spatial-filtering approach was able to uncover associations between the MEG envelopes and fMRI time courses, shedding light on the similarities of hemodynamic and electromagnetic brain activities during movie viewing. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Multimodal imaging of repetition priming: Using fMRI, MEG, and intracranial EEG to reveal spatiotemporal profiles of word processing.

PubMed

McDonald, Carrie R; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M; Trongnetrpunya, Amy; Sherfey, Jason S; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K; Cash, Sydney S; Leonard, Matthew K; Hagler, Donald J; Dale, Anders M; Halgren, Eric

2010-11-01

Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, 'N') and words that repeated (old, 'O'). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs. O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs. O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350 to 450 ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. Copyright 2010 Elsevier Inc. All rights reserved.

Multimodal imaging of repetition priming: Using fMRI, MEG, and intracranial EEG to reveal spatiotemporal profiles of word processing

PubMed Central

McDonald, Carrie R.; Thesen, Thomas; Carlson, Chad; Blumberg, Mark; Girard, Holly M.; Trongnetrpunya, Amy; Sherfey, Jason S.; Devinsky, Orrin; Kuzniecky, Rubin; Dolye, Werner K.; Cash, Sydney S.; Leonard, Matt K.; Hagler, Donald J.; Dale, Anders M.; Halgren, Eric

2010-01-01

Repetition priming is a core feature of memory processing whose anatomical correlates remain poorly understood. In this study, we use advanced multimodal imaging (functional magnetic resonance imaging (fMRI) and magnetoencephalography; MEG) to investigate the spatiotemporal profile of repetition priming. We use intracranial electroencephalography (iEEG) to validate our fMRI/MEG measurements. Twelve controls completed a semantic judgment task with fMRI and MEG that included words presented once (new, ‘N’) and words that repeated (old, ‘O’). Six patients with epilepsy completed the same task during iEEG recordings. Blood-oxygen level dependent (BOLD) responses for N vs O words were examined across the cortical surface and within regions of interest. MEG waveforms for N vs O words were estimated using a noise-normalized minimum norm solution, and used to interpret the timecourse of fMRI. Spatial concordance was observed between fMRI and MEG repetition effects from 350–450ms within bilateral occipitotemporal and medial temporal, left prefrontal, and left posterior temporal cortex. Additionally, MEG revealed widespread sources within left temporoparietal regions, whereas fMRI revealed bilateral reductions in occipitotemporal and left superior frontal, and increases in inferior parietal, precuneus, and dorsolateral prefrontal activity. BOLD suppression in left posterior temporal, left inferior prefrontal, and right occipitotemporal cortex correlated with MEG repetition-related reductions. IEEG responses from all three regions supported the timecourse of MEG and localization of fMRI. Furthermore, iEEG decreases to repeated words were associated with decreased gamma power in several regions, providing evidence that gamma oscillations are tightly coupled to cognitive phenomena and reflect regional activations seen in the BOLD signal. PMID:20620212

A Subspace Pursuit–based Iterative Greedy Hierarchical Solution to the Neuromagnetic Inverse Problem

PubMed Central

Babadi, Behtash; Obregon-Henao, Gabriel; Lamus, Camilo; Hämäläinen, Matti S.; Brown, Emery N.; Purdon, Patrick L.

2013-01-01

Magnetoencephalography (MEG) is an important non-invasive method for studying activity within the human brain. Source localization methods can be used to estimate spatiotemporal activity from MEG measurements with high temporal resolution, but the spatial resolution of these estimates is poor due to the ill-posed nature of the MEG inverse problem. Recent developments in source localization methodology have emphasized temporal as well as spatial constraints to improve source localization accuracy, but these methods can be computationally intense. Solutions emphasizing spatial sparsity hold tremendous promise, since the underlying neurophysiological processes generating MEG signals are often sparse in nature, whether in the form of focal sources, or distributed sources representing large-scale functional networks. Recent developments in the theory of compressed sensing (CS) provide a rigorous framework to estimate signals with sparse structure. In particular, a class of CS algorithms referred to as greedy pursuit algorithms can provide both high recovery accuracy and low computational complexity. Greedy pursuit algorithms are difficult to apply directly to the MEG inverse problem because of the high-dimensional structure of the MEG source space and the high spatial correlation in MEG measurements. In this paper, we develop a novel greedy pursuit algorithm for sparse MEG source localization that overcomes these fundamental problems. This algorithm, which we refer to as the Subspace Pursuit-based Iterative Greedy Hierarchical (SPIGH) inverse solution, exhibits very low computational complexity while achieving very high localization accuracy. We evaluate the performance of the proposed algorithm using comprehensive simulations, as well as the analysis of human MEG data during spontaneous brain activity and somatosensory stimuli. These studies reveal substantial performance gains provided by the SPIGH algorithm in terms of computational complexity, localization accuracy, and robustness. PMID:24055554

Atypical brain lateralisation in the auditory cortex and language performance in 3- to 7-year-old children with high-functioning autism spectrum disorder: a child-customised magnetoencephalography (MEG) study.

PubMed

Yoshimura, Yuko; Kikuchi, Mitsuru; Shitamichi, Kiyomi; Ueno, Sanae; Munesue, Toshio; Ono, Yasuki; Tsubokawa, Tsunehisa; Haruta, Yasuhiro; Oi, Manabu; Niida, Yo; Remijn, Gerard B; Takahashi, Tsutomu; Suzuki, Michio; Higashida, Haruhiro; Minabe, Yoshio

2013-10-08

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), which reflects language-related performance. We investigated the P50m that is evoked by voice stimuli (/ne/) bilaterally in 33 young children (3 to 7 years old) with ASD and in 30 young children who were typically developing (TD). The children were matched according to their age (in months) and gender. Most of the children with ASD were high-functioning subjects. The results showed that the children with ASD exhibited significantly less leftward lateralisation in their P50m intensity compared with the TD children. Furthermore, the results of a multiple regression analysis indicated that a shorter P50m latency in both hemispheres was specifically correlated with higher language-related performance in the TD children, whereas this latency was not correlated with non-verbal cognitive performance or chronological age. The children with ASD did not show any correlation between P50m latency and language-related performance; instead, increasing chronological age was a significant predictor of shorter P50m latency in the right hemisphere. Using a child-customised MEG device, we studied the P50m component that was evoked through binaural human voice stimuli in young ASD and TD children to examine differences in auditory cortex function that are associated with language development. Our results suggest that there is atypical brain function in the auditory cortex in young children with ASD, regardless of language development.

Sparse EEG/MEG source estimation via a group lasso

PubMed Central

Lim, Michael; Ales, Justin M.; Cottereau, Benoit R.; Hastie, Trevor

2017-01-01

Non-invasive recordings of human brain activity through electroencephalography (EEG) or magnetoencelphalography (MEG) are of value for both basic science and clinical applications in sensory, cognitive, and affective neuroscience. Here we introduce a new approach to estimating the intra-cranial sources of EEG/MEG activity measured from extra-cranial sensors. The approach is based on the group lasso, a sparse-prior inverse that has been adapted to take advantage of functionally-defined regions of interest for the definition of physiologically meaningful groups within a functionally-based common space. Detailed simulations using realistic source-geometries and data from a human Visual Evoked Potential experiment demonstrate that the group-lasso method has improved performance over traditional ℓ2 minimum-norm methods. In addition, we show that pooling source estimates across subjects over functionally defined regions of interest results in improvements in the accuracy of source estimates for both the group-lasso and minimum-norm approaches. PMID:28604790

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG).

PubMed

Gavaret, M; Maillard, L; Jung, J

2015-03-01

High-resolution EEG (HR-EEG) and magnetoencephalography (MEG) allow the recording of spontaneous or evoked electromagnetic brain activity with excellent temporal resolution. Data must be recorded with high temporal resolution (sampling rate) and high spatial resolution (number of channels). Data analyses are based on several steps with selection of electromagnetic signals, elaboration of a head model and use of algorithms in order to solve the inverse problem. Due to considerable technical advances in spatial resolution, these tools now represent real methods of ElectroMagnetic Source Imaging. HR-EEG and MEG constitute non-invasive and complementary examinations, characterized by distinct sensitivities according to the location and orientation of intracerebral generators. In the presurgical assessment of drug-resistant partial epilepsies, HR-EEG and MEG can characterize and localize interictal activities and thus the irritative zone. HR-EEG and MEG often yield significant additional data that are complementary to other presurgical investigations and particularly relevant in MRI-negative cases. Currently, the determination of the epileptogenic zone and functional brain mapping remain rather less well-validated indications. In France, in 2014, HR-EEG is now part of standard clinical investigation of epilepsy, while MEG remains a research technique. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Fetal auditory evoked responses to onset of amplitude modulated sounds. A fetal magnetoencephalography (fMEG) study.

PubMed

Draganova, R; Schollbach, A; Schleger, F; Braendle, J; Brucker, S; Abele, H; Kagan, K O; Wallwiener, D; Fritsche, A; Eswaran, H; Preissl, H

2018-06-01

The human fetal auditory system is functional around the 25th week of gestational age when the thalamocortical connections are established. Fetal magnetoencephalography (fMEG) provides evidence for fetal auditory brain responses to pure tones and syllables. Fifty-five pregnant women between 31 and 40 weeks of gestation were included in the study. Fetal MEG was recorded during the presentation of an amplitude modulated tone (AM) with a carrier frequency of 500 Hz to the maternal abdomen modulated by low modulation rates (MRs) - 2/s and 4/s, middle MR - 8/s and high MRs - 27/s, 42/s, 78/s and 91/s. The aim was to determine whether the fetal brain responds differently to envelope slopes and intensity change at the onset of the AM sounds. A significant decrease of the response latencies of transient event-related responses (ERR) to high and middle MRs in comparison to the low MRs was observed. The highest fetal response rate was achieved by modulation rates of 2/s, 4/s and 27/s (70%, 57%, and 86%, respectively). Additionally, a maturation effect of the ERR (response latency vs. gestational age) was observed only for 4/s MR. The significant difference between the response latencies to low, middle, and high MRs suggests that still before birth the fetal brain processes the sound slopes at the onset in different integration time-windows, depending on the time for the intensity increase or stimulus power density at the onset, which is a prerequisite for language acquisition. Copyright © 2018 Elsevier B.V. All rights reserved.

Predicting depression based on dynamic regional connectivity: a windowed Granger causality analysis of MEG recordings.

PubMed

Lu, Qing; Bi, Kun; Liu, Chu; Luo, Guoping; Tang, Hao; Yao, Zhijian

2013-10-16

Abnormal inter-regional causalities can be mapped for the objective diagnosis of various diseases. These inter-regional connectivities are usually calculated over an entire scan and used to characterize the stationary strength of the connections. However, the connectivity within networks may undergo substantial changes during a scan. In this study, we developed an objective depression recognition approach using the dynamic regional interactions that occur in response to sad facial stimuli. The whole time-period magnetoencephalography (MEG) signals from the visual cortex, amygdala, anterior cingulate cortex (ACC) and inferior frontal gyrus (IFG) were separated into sequential time intervals. The Granger causality mapping method was used to identify the pairwise interaction pattern within each time interval. Feature selection was then undertaken within a minimum redundancy-maximum relevance (mRMR) framework. Typical classifiers were utilized to predict those patients who had depression. The overall performances of these classifiers were similar, and the highest classification accuracy rate was 87.5%. The best discriminative performance was obtained when the number of features was within a robust range. The discriminative network pattern obtained through support vector machine (SVM) analyses displayed abnormal causal connectivities that involved the amygdala during the early and late stages. These early and late connections in the amygdala appear to reveal a negative bias to coarse expression information processing and abnormal negative modulation in patients with depression, which may critically affect depression discrimination. © 2013 Elsevier B.V. All rights reserved.

Interactions between core and matrix thalamocortical projections in human sleep spindle synchronization

PubMed Central

Bonjean, Maxime; Baker, Tanya; Bazhenov, Maxim; Cash, Sydney; Halgren, Eric; Sejnowski, Terrence

2012-01-01

Sleep spindles, which are bursts of 11–15 Hz that occur during non-REM sleep, are highly synchronous across the scalp when measured with EEG, but have low spatial coherence and exhibit low correlation with EEG signals when simultaneously measured with MEG spindles in humans. We developed a computational model to explore the hypothesis that the spatial coherence of the EEG spindle is a consequence of diffuse matrix projections of the thalamus to layer 1 compared to the focal projections of the core pathway to layer 4 recorded by the MEG. Increasing the fanout of thalamocortical connectivity in the matrix pathway while keeping the core pathway fixed led to increased synchrony of the spindle activity in the superficial cortical layers in the model. In agreement with cortical recordings, the latency for spindles to spread from the core to the matrix was independent of the thalamocortical fanout but highly dependent on the probability of connections between cortical areas. PMID:22496571

An FPGA-based trigger for the phase II of the MEG experiment

NASA Astrophysics Data System (ADS)

Baldini, A.; Bemporad, C.; Cei, F.; Galli, L.; Grassi, M.; Morsani, F.; Nicolò, D.; Ritt, S.; Venturini, M.

2016-07-01

For the phase II of MEG, we are going to develop a combined trigger and DAQ system. Here we focus on the former side, which operates an on-line reconstruction of detector signals and event selection within 450 μs from event occurrence. Trigger concentrator boards (TCB) are under development to gather data from different crates, each connected to a set of detector channels, to accomplish higher-level algorithms to issue a trigger in the case of a candidate signal event. We describe the major features of the new system, in comparison with phase I, as well as its performances in terms of selection efficiency and background rejection.

Spatial MEG laterality maps for language: clinical applications in epilepsy.

PubMed

D'Arcy, Ryan C N; Bardouille, Timothy; Newman, Aaron J; McWhinney, Sean R; Debay, Drew; Sadler, R Mark; Clarke, David B; Esser, Michael J

2013-08-01

Functional imaging is increasingly being used to provide a noninvasive alternative to intracarotid sodium amobarbitol testing (i.e., the Wada test). Although magnetoencephalography (MEG) has shown significant potential in this regard, the resultant output is often reduced to a simplified estimate of laterality. Such estimates belie the richness of functional imaging data and consequently limit the potential value. We present a novel approach that utilizes MEG data to compute "complex laterality vectors" and consequently "laterality maps" for a given function. Language function was examined in healthy controls and in people with epilepsy. When compared with traditional laterality index (LI) approaches, the resultant maps provided critical information about the magnitude and spatial characteristics of lateralized function. Specifically, it was possible to more clearly define low LI scores resulting from strong bilateral activation, high LI scores resulting from weak unilateral activation, and most importantly, the spatial distribution of lateralized activation. We argue that the laterality concept is better presented with the inherent spatial sensitivity of activation maps, rather than being collapsed into a one-dimensional index. Copyright © 2012 Wiley Periodicals, Inc.

BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research

NASA Astrophysics Data System (ADS)

Okada, Yoshio; Hämäläinen, Matti; Pratt, Kevin; Mascarenas, Anthony; Miller, Paul; Han, Menglai; Robles, Jose; Cavallini, Anders; Power, Bill; Sieng, Kosal; Sun, Limin; Lew, Seok; Doshi, Chiran; Ahtam, Banu; Dinh, Christoph; Esch, Lorenz; Grant, Ellen; Nummenmaa, Aapo; Paulson, Douglas

2016-09-01

We developed a 375-channel, whole-head magnetoencephalography (MEG) system ("BabyMEG") for studying the electrophysiological development of human brain during the first years of life. The helmet accommodates heads up to 95% of 36-month old boys in the USA. The unique two-layer sensor array consists of: (1) 270 magnetometers (10 mm diameter, ˜15 mm coil-to-coil spacing) in the inner layer, (2) thirty-five three-axis magnetometers (20 mm × 20 mm) in the outer layer 4 cm away from the inner layer. Additionally, there are three three-axis reference magnetometers. With the help of a remotely operated position adjustment mechanism, the sensor array can be positioned to provide a uniform short spacing (mean 8.5 mm) between the sensor array and room temperature surface of the dewar. The sensors are connected to superconducting quantum interference devices (SQUIDs) operating at 4.2 K with median sensitivity levels of 7.5 fT/√Hz for the inner and 4 fT/√Hz for the outer layer sensors. SQUID outputs are digitized by a 24-bit acquisition system. A closed-cycle helium recycler provides maintenance-free continuous operation, eliminating the need for helium, with no interruption needed during MEG measurements. BabyMEG with the recycler has been fully operational from March, 2015. Ongoing spontaneous brain activity can be monitored in real time without interference from external magnetic noise sources including the recycler, using a combination of a lightly shielded two-layer magnetically shielded room, an external active shielding, a signal-space projection method, and a synthetic gradiometer approach. Evoked responses in the cortex can be clearly detected without averaging. These new design features and capabilities represent several advances in MEG, increasing the utility of this technique in basic neuroscience as well as in clinical research and patient studies.

BabyMEG: A whole-head pediatric magnetoencephalography system for human brain development research.

PubMed

Okada, Yoshio; Hämäläinen, Matti; Pratt, Kevin; Mascarenas, Anthony; Miller, Paul; Han, Menglai; Robles, Jose; Cavallini, Anders; Power, Bill; Sieng, Kosal; Sun, Limin; Lew, Seok; Doshi, Chiran; Ahtam, Banu; Dinh, Christoph; Esch, Lorenz; Grant, Ellen; Nummenmaa, Aapo; Paulson, Douglas

2016-09-01

We developed a 375-channel, whole-head magnetoencephalography (MEG) system ("BabyMEG") for studying the electrophysiological development of human brain during the first years of life. The helmet accommodates heads up to 95% of 36-month old boys in the USA. The unique two-layer sensor array consists of: (1) 270 magnetometers (10 mm diameter, ∼15 mm coil-to-coil spacing) in the inner layer, (2) thirty-five three-axis magnetometers (20 mm × 20 mm) in the outer layer 4 cm away from the inner layer. Additionally, there are three three-axis reference magnetometers. With the help of a remotely operated position adjustment mechanism, the sensor array can be positioned to provide a uniform short spacing (mean 8.5 mm) between the sensor array and room temperature surface of the dewar. The sensors are connected to superconducting quantum interference devices (SQUIDs) operating at 4.2 K with median sensitivity levels of 7.5 fT/√Hz for the inner and 4 fT/√Hz for the outer layer sensors. SQUID outputs are digitized by a 24-bit acquisition system. A closed-cycle helium recycler provides maintenance-free continuous operation, eliminating the need for helium, with no interruption needed during MEG measurements. BabyMEG with the recycler has been fully operational from March, 2015. Ongoing spontaneous brain activity can be monitored in real time without interference from external magnetic noise sources including the recycler, using a combination of a lightly shielded two-layer magnetically shielded room, an external active shielding, a signal-space projection method, and a synthetic gradiometer approach. Evoked responses in the cortex can be clearly detected without averaging. These new design features and capabilities represent several advances in MEG, increasing the utility of this technique in basic neuroscience as well as in clinical research and patient studies.

Skull Defects in Finite Element Head Models for Source Reconstruction from Magnetoencephalography Signals

PubMed Central

Lau, Stephan; Güllmar, Daniel; Flemming, Lars; Grayden, David B.; Cook, Mark J.; Wolters, Carsten H.; Haueisen, Jens

2016-01-01

Magnetoencephalography (MEG) signals are influenced by skull defects. However, there is a lack of evidence of this influence during source reconstruction. Our objectives are to characterize errors in source reconstruction from MEG signals due to ignoring skull defects and to assess the ability of an exact finite element head model to eliminate such errors. A detailed finite element model of the head of a rabbit used in a physical experiment was constructed from magnetic resonance and co-registered computer tomography imaging that differentiated nine tissue types. Sources of the MEG measurements above intact skull and above skull defects respectively were reconstructed using a finite element model with the intact skull and one incorporating the skull defects. The forward simulation of the MEG signals reproduced the experimentally observed characteristic magnitude and topography changes due to skull defects. Sources reconstructed from measured MEG signals above intact skull matched the known physical locations and orientations. Ignoring skull defects in the head model during reconstruction displaced sources under a skull defect away from that defect. Sources next to a defect were reoriented. When skull defects, with their physical conductivity, were incorporated in the head model, the location and orientation errors were mostly eliminated. The conductivity of the skull defect material non-uniformly modulated the influence on MEG signals. We propose concrete guidelines for taking into account conducting skull defects during MEG coil placement and modeling. Exact finite element head models can improve localization of brain function, specifically after surgery. PMID:27092044

Statistical learning of multisensory regularities is enhanced in musicians: An MEG study.

PubMed

Paraskevopoulos, Evangelos; Chalas, Nikolas; Kartsidis, Panagiotis; Wollbrink, Andreas; Bamidis, Panagiotis

2018-07-15

The present study used magnetoencephalography (MEG) to identify the neural correlates of audiovisual statistical learning, while disentangling the differential contributions of uni- and multi-modal statistical mismatch responses in humans. The applied paradigm was based on a combination of a statistical learning paradigm and a multisensory oddball one, combining an audiovisual, an auditory and a visual stimulation stream, along with the corresponding deviances. Plasticity effects due to musical expertise were investigated by comparing the behavioral and MEG responses of musicians to non-musicians. The behavioral results indicated that the learning was successful for both musicians and non-musicians. The unimodal MEG responses are consistent with previous studies, revealing the contribution of Heschl's gyrus for the identification of auditory statistical mismatches and the contribution of medial temporal and visual association areas for the visual modality. The cortical network underlying audiovisual statistical learning was found to be partly common and partly distinct from the corresponding unimodal networks, comprising right temporal and left inferior frontal sources. Musicians showed enhanced activation in superior temporal and superior frontal gyrus. Connectivity and information processing flow amongst the sources comprising the cortical network of audiovisual statistical learning, as estimated by transfer entropy, was reorganized in musicians, indicating enhanced top-down processing. This neuroplastic effect showed a cross-modal stability between the auditory and audiovisual modalities. Copyright © 2018 Elsevier Inc. All rights reserved.

Gating of memory encoding of time-delayed cross-frequency MEG networks revealed by graph filtration based on persistent homology

PubMed Central

Hahm, Jarang; Lee, Hyekyoung; Park, Hyojin; Kang, Eunjoo; Kim, Yu Kyeong; Chung, Chun Kee; Kang, Hyejin; Lee, Dong Soo

2017-01-01

To explain gating of memory encoding, magnetoencephalography (MEG) was analyzed over multi-regional network of negative correlations between alpha band power during cue (cue-alpha) and gamma band power during item presentation (item-gamma) in Remember (R) and No-remember (NR) condition. Persistent homology with graph filtration on alpha-gamma correlation disclosed topological invariants to explain memory gating. Instruction compliance (R-hits minus NR-hits) was significantly related to negative coupling between the left superior occipital (cue-alpha) and the left dorsolateral superior frontal gyri (item-gamma) on permutation test, where the coupling was stronger in R than NR. In good memory performers (R-hits minus false alarm), the coupling was stronger in R than NR between the right posterior cingulate (cue-alpha) and the left fusiform gyri (item-gamma). Gating of memory encoding was dictated by inter-regional negative alpha-gamma coupling. Our graph filtration over MEG network revealed these inter-regional time-delayed cross-frequency connectivity serve gating of memory encoding. PMID:28169281

Altered long-range alpha-band synchronization during visual short-term memory retention in children born very preterm.

PubMed

Doesburg, Sam M; Ribary, Urs; Herdman, Anthony T; Miller, Steven P; Poskitt, Kenneth J; Moiseev, Alexander; Whitfield, Michael F; Synnes, Anne; Grunau, Ruth E

2011-02-01

Children born very preterm, even when intelligence is broadly normal, often experience selective difficulties in executive function and visual-spatial processing. Development of structural cortical connectivity is known to be altered in this group, and functional magnetic resonance imaging (fMRI) evidence indicates that very preterm children recruit different patterns of functional connectivity between cortical regions during cognition. Synchronization of neural oscillations across brain areas has been proposed as a mechanism for dynamically assigning functional coupling to support perceptual and cognitive processing, but little is known about what role oscillatory synchronization may play in the altered neurocognitive development of very preterm children. To investigate this, we recorded magnetoencephalographic (MEG) activity while 7-8 year old children born very preterm and age-matched full-term controls performed a visual short-term memory task. Very preterm children exhibited reduced long-range synchronization in the alpha-band during visual short-term memory retention, indicating that cortical alpha rhythms may play a critical role in altered patterns functional connectivity expressed by this population during cognitive and perceptual processing. Long-range alpha-band synchronization was also correlated with task performance and visual-perceptual ability within the very preterm group, indicating that altered alpha oscillatory mechanisms mediating transient functional integration between cortical regions may be relevant to selective problems in neurocognitive development in this vulnerable population at school age. Copyright © 2010 Elsevier Inc. All rights reserved.

Neuromagnetic correlates of audiovisual word processing in the developing brain.

PubMed

Dinga, Samantha; Wu, Di; Huang, Shuyang; Wu, Caiyun; Wang, Xiaoshan; Shi, Jingping; Hu, Yue; Liang, Chun; Zhang, Fawen; Lu, Meng; Leiken, Kimberly; Xiang, Jing

2018-06-01

The brain undergoes enormous changes during childhood. Little is known about how the brain develops to serve word processing. The objective of the present study was to investigate the maturational changes of word processing in children and adolescents using magnetoencephalography (MEG). Responses to a word processing task were investigated in sixty healthy participants. Each participant was presented with simultaneous visual and auditory word pairs in "match" and "mismatch" conditions. The patterns of neuromagnetic activation from MEG recordings were analyzed at both sensor and source levels. Topography and source imaging revealed that word processing transitioned from bilateral connections to unilateral connections as age increased from 6 to 17 years old. Correlation analyses of language networks revealed that the path length of word processing networks negatively correlated with age (r = -0.833, p < 0.0001), while the connection strength (r = 0.541, p < 0.01) and the clustering coefficient (r = 0.705, p < 0.001) of word processing networks were positively correlated with age. In addition, males had more visual connections, whereas females had more auditory connections. The correlations between gender and path length, gender and connection strength, and gender and clustering coefficient demonstrated a developmental trend without reaching statistical significance. The results indicate that the developmental trajectory of word processing is gender specific. Since the neuromagnetic signatures of these gender-specific paths to adult word processing were determined using non-invasive, objective, and quantitative methods, the results may play a key role in understanding language impairments in pediatric patients in the future. Copyright © 2018 Elsevier B.V. All rights reserved.

A pilot treatment study for mild traumatic brain injury: Neuroimaging changes detected by MEG after low-intensity pulse-based transcranial electrical stimulation.

PubMed

Huang, Ming-Xiong; Swan, Ashley Robb; Quinto, Annemarie Angeles; Matthews, Scott; Harrington, Deborah L; Nichols, Sharon; Bruder, Barry J; Snook, Corey C; Huang, Charles W; Baker, Dewleen G; Lee, Roland R

2017-01-01

Mild traumatic brain injury (mTBI) is a leading cause of sustained impairments in military service members, Veterans, and civilians. However, few treatments are available for mTBI, partially because the mechanism of persistent mTBI deficits is not fully understood. We used magnetoencephalography (MEG) to investigate neuronal changes in individuals with mTBI following a passive neurofeedback-based treatment programme called IASIS. This programme involved applying low-intensity pulses using transcranial electrical stimulation (LIP-tES) with electroencephalography monitoring. Study participants included six individuals with mTBI and persistent post-concussive symptoms (PCS). MEG exams were performed at baseline and follow-up to evaluate the effect of IASIS on brain functioning. At the baseline MEG exam, all participants had abnormal slow-waves. In the follow-up MEG exam, the participants showed significantly reduced abnormal slow-waves with an average reduction of 53.6 ± 24.6% in slow-wave total score. The participants also showed significant reduction of PCS scores after IASIS treatment, with an average reduction of 52.76 ± 26.4% in PCS total score. The present study demonstrates, for the first time, the neuroimaging-based documentation of the effect of LIP-tES treatment on brain functioning in mTBI. The mechanisms of LIP-tES treatment are discussed, with an emphasis on LIP-tES's potentiation of the mTBI healing process.

The impact of acute psychosocial stress on magnetoencephalographic correlates of emotional attention and exogenous visual attention.

PubMed

Elling, Ludger; Schupp, Harald; Bayer, Janine; Bröckelmann, Ann-Kathrin; Steinberg, Christian; Dobel, Christian; Junghofer, Markus

2012-01-01

Stress-induced acute activation of the cerebral catecholaminergic systems has often been found in rodents. However, little is known regarding the consequences of this activation on higher cognitive functions in humans. Theoretical inferences would suggest increased distractibility in the sense of increased exogenous attention and emotional attention. The present study investigated the influence of acute stress responses on magnetoencephalographic (MEG) correlates of visual attention. Healthy male subjects were presented emotional and neutral pictures in three subsequent MEG recording sessions after being exposed to a TSST-like social stressor, intended to trigger a HPA-response. The subjects anticipation of another follow-up stressor was designed to sustain the short-lived central catecholaminergic stress reactions throughout the ongoing MEG recordings. The heart rate indicates a stable level of anticipatory stress during this time span, subsequent cortisol concentrations and self-report measures of stress were increased. With regard to the MEG correlates of attentional functions, we found that the N1m amplitude remained constantly elevated during stressor anticipation. The magnetic early posterior negativity (EPNm) was present but, surprisingly, was not at all modulated during stressor anticipation. This suggests that a general increase of the influence of exogenous attention but no specific effect regarding emotional attention in this time interval. Regarding the time course of the effects, an influence of the HPA on these MEG correlates of attention seems less likely. An influence of cerebral catecholaminergic systems is plausible, but not definite.

What you need to know to become a MEG technologist.

PubMed

Mason, Karen M; Ebersole, Susan M; Fujiwara, Hisako; Lowe, James P; Bowyer, Susan M

2013-09-01

Magnetoencephalography (MEG) is a way to noninvasively localize sources of electrical activity within the human brain, by measuring the very weak magnetic fields just outside of the head. This paper is an introduction to MEG for technologists who are interested in performing MEG studies. We have organized the paper into a brief overview of what MEG measures and how it does it, as well as a short history of the MEG manufacturers. There is a discussion of the differences in coils/sensors used to detect the magnetic fields, followed by a detailed description of what an average MEG technologist does to perform a MEG study. Some MEG centers may require more duties from the MEG technologist than are listed here and others may require fewer duties. We finish the paper with the contraindications for a MEG study, a job description for the MEG technologist, and a MEG procedure checklist to help keep the tasks organized.

Simultaneous EEG and MEG source reconstruction in sparse electromagnetic source imaging.

PubMed

Ding, Lei; Yuan, Han

2013-04-01

Electroencephalography (EEG) and magnetoencephalography (MEG) have different sensitivities to differently configured brain activations, making them complimentary in providing independent information for better detection and inverse reconstruction of brain sources. In the present study, we developed an integrative approach, which integrates a novel sparse electromagnetic source imaging method, i.e., variation-based cortical current density (VB-SCCD), together with the combined use of EEG and MEG data in reconstructing complex brain activity. To perform simultaneous analysis of multimodal data, we proposed to normalize EEG and MEG signals according to their individual noise levels to create unit-free measures. Our Monte Carlo simulations demonstrated that this integrative approach is capable of reconstructing complex cortical brain activations (up to 10 simultaneously activated and randomly located sources). Results from experimental data showed that complex brain activations evoked in a face recognition task were successfully reconstructed using the integrative approach, which were consistent with other research findings and validated by independent data from functional magnetic resonance imaging using the same stimulus protocol. Reconstructed cortical brain activations from both simulations and experimental data provided precise source localizations as well as accurate spatial extents of localized sources. In comparison with studies using EEG or MEG alone, the performance of cortical source reconstructions using combined EEG and MEG was significantly improved. We demonstrated that this new sparse ESI methodology with integrated analysis of EEG and MEG data could accurately probe spatiotemporal processes of complex human brain activations. This is promising for noninvasively studying large-scale brain networks of high clinical and scientific significance. Copyright © 2011 Wiley Periodicals, Inc.

Guiding transcranial brain stimulation by EEG/MEG to interact with ongoing brain activity and associated functions: A position paper

PubMed Central

Thut, Gregor; Bergmann, Til Ole; Fröhlich, Flavio; Soekadar, Surjo R.; Brittain, John-Stuart; Valero-Cabré, Antoni; Sack, Alexander; Miniussi, Carlo; Antal, Andrea; Siebner, Hartwig Roman; Ziemann, Ulf; Herrmann, Christoph S.

2017-01-01

Non-invasive transcranial brain stimulation (NTBS) techniques have a wide range of applications but also suffer from a number of limitations mainly related to poor specificity of intervention and variable effect size. These limitations motivated recent efforts to focus on the temporal dimension of NTBS with respect to the ongoing brain activity. Temporal patterns of ongoing neuronal activity, in particular brain oscillations and their fluctuations, can be traced with electro- or magnetoencephalography (EEG/MEG), to guide the timing as well as the stimulation settings of NTBS. These novel, online and offline EEG/MEG-guided NTBS-approaches are tailored to specifically interact with the underlying brain activity. Online EEG/MEG has been used to guide the timing of NTBS (i.e., when to stimulate): by taking into account instantaneous phase or power of oscillatory brain activity, NTBS can be aligned to fluctuations in excitability states. Moreover, offline EEG/MEG recordings prior to interventions can inform researchers and clinicians how to stimulate: by frequency-tuning NTBS to the oscillation of interest, intrinsic brain oscillations can be up- or down-regulated. In this paper, we provide an overview of existing approaches and ideas of EEG/MEG-guided interventions, and their promises and caveats. We point out potential future lines of research to address challenges. PMID:28233641

Non-Gaussian probabilistic MEG source localisation based on kernel density estimation☆

PubMed Central

Mohseni, Hamid R.; Kringelbach, Morten L.; Woolrich, Mark W.; Baker, Adam; Aziz, Tipu Z.; Probert-Smith, Penny

2014-01-01

There is strong evidence to suggest that data recorded from magnetoencephalography (MEG) follows a non-Gaussian distribution. However, existing standard methods for source localisation model the data using only second order statistics, and therefore use the inherent assumption of a Gaussian distribution. In this paper, we present a new general method for non-Gaussian source estimation of stationary signals for localising brain activity from MEG data. By providing a Bayesian formulation for MEG source localisation, we show that the source probability density function (pdf), which is not necessarily Gaussian, can be estimated using multivariate kernel density estimators. In the case of Gaussian data, the solution of the method is equivalent to that of widely used linearly constrained minimum variance (LCMV) beamformer. The method is also extended to handle data with highly correlated sources using the marginal distribution of the estimated joint distribution, which, in the case of Gaussian measurements, corresponds to the null-beamformer. The proposed non-Gaussian source localisation approach is shown to give better spatial estimates than the LCMV beamformer, both in simulations incorporating non-Gaussian signals, and in real MEG measurements of auditory and visual evoked responses, where the highly correlated sources are known to be difficult to estimate. PMID:24055702

MEG and fMRI Fusion for Non-Linear Estimation of Neural and BOLD Signal Changes

PubMed Central

Plis, Sergey M.; Calhoun, Vince D.; Weisend, Michael P.; Eichele, Tom; Lane, Terran

2010-01-01

The combined analysis of magnetoencephalography (MEG)/electroencephalography and functional magnetic resonance imaging (fMRI) measurements can lead to improvement in the description of the dynamical and spatial properties of brain activity. In this paper we empirically demonstrate this improvement using simulated and recorded task related MEG and fMRI activity. Neural activity estimates were derived using a dynamic Bayesian network with continuous real valued parameters by means of a sequential Monte Carlo technique. In synthetic data, we show that MEG and fMRI fusion improves estimation of the indirectly observed neural activity and smooths tracking of the blood oxygenation level dependent (BOLD) response. In recordings of task related neural activity the combination of MEG and fMRI produces a result with greater signal-to-noise ratio, that confirms the expectation arising from the nature of the experiment. The highly non-linear model of the BOLD response poses a difficult inference problem for neural activity estimation; computational requirements are also high due to the time and space complexity. We show that joint analysis of the data improves the system's behavior by stabilizing the differential equations system and by requiring fewer computational resources. PMID:21120141

Differences in MEG gamma oscillatory power during performance of a prosaccade task in adolescents with FASD

PubMed Central

Stephen, Julia M.; Coffman, Brian A.; Stone, David B.; Kodituwakku, Piyadasa

2013-01-01

Fetal alcohol spectrum disorder (FASD) is characterized by a broad range of behavioral and cognitive deficits that impact the long-term quality of life for affected individuals. However, the underlying changes in brain structure and function associated with these cognitive impairments are not well-understood. Previous studies identified deficits in behavioral performance of prosaccade tasks in children with FASD. In this study, we investigated group differences in gamma oscillations during performance of a prosaccade task. We collected magnetoencephalography (MEG) data from 15 adolescents with FASD and 20 age-matched healthy controls (HC) with a mean age of 15.9 ± 0.4 years during performance of a prosaccade task. Eye movement was recorded and synchronized to the MEG data using an MEG compatible eye-tracker. The MEG data were analyzed relative to the onset of the visual saccade. Time-frequency analysis was performed using Fieldtrip with a focus on group differences in gamma-band oscillations. Following left target presentation, we identified four clusters over right frontal, right parietal, and left temporal/occipital cortex, with significantly different gamma-band (30–50 Hz) power between FASD and HC. Furthermore, visual M100 latencies described in Coffman etal. (2012) corresponded with increased gamma power over right central cortex in FASD only. Gamma-band differences were not identified for stimulus-averaged responses implying that these gamma-band differences were related to differences in saccade network functioning. These differences in gamma-band power may provide indications of atypical development of cortical networks in individuals with FASD. PMID:24399957

A K-means multivariate approach for clustering independent components from magnetoencephalographic data.

PubMed

Spadone, Sara; de Pasquale, Francesco; Mantini, Dante; Della Penna, Stefania

2012-09-01

Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means based (MAGMICK). The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK are: i) the implementation of an efficient set of "MEG fingerprints" designed to summarize properties of MEG ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version of the standard K-means procedure to improve its data-driven character. This algorithm groups the obtained ICs automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint on the ICs independence, i.e. components coming from the same session (at subject level) or subject (at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate that the method can extract consistent patterns of spatial topography and spectral properties across sessions and subjects that are in good agreement with the literature. In addition, these results are compared to those from a modified version of affinity propagation clustering method. The comparison, evaluated in terms of different clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually, these results are confirmed by a comparison with a MEG tailored version of the self-organizing group ICA, which is largely used for fMRI IC clustering. Copyright © 2012 Elsevier Inc. All rights reserved.

Magnetoencephalography-guided surgery in frontal lobe epilepsy using neuronavigation and intraoperative MR imaging.

PubMed

Sommer, Björn; Roessler, Karl; Rampp, Stefan; Hamer, Hajo M; Blumcke, Ingmar; Stefan, Hermann; Buchfelder, Michael

2016-10-01

Especially in hidden lesions causing drug-resistant frontal lobe epilepsy (FLE), the localization of the epileptic zone EZ can be a challenge. Magnetoencephalography (MEG) can raise the chances for localization of the (EZ) in combination with electroencephalography (EEG). We investigated the impact of MEG-guided epilepsy surgery with the aid of neuronavigation and intraoperative MR imaging (iopMRI) on seizure outcome of FLE patients. Twenty-eight patients (15 females, 13 males; mean age 31.0±11.1 years) underwent surgery in our department. All patients underwent presurgical MEG monitoring (two-sensor Magnes II or whole head WH3600 MEG system; 4-D Neuroimaging, San Diego, CA, USA). Of those, six patients (group 1) with MRI-negative FLE were operated on before 2002 with intraoperative electrocorticography (ECoG) and invasive EEG mapping only. Eleven patients with MRI-negative FLE (group 2) and eleven with lesional FLE (group 3) underwent surgery using 1.5T-iopMRI and neuronavigation, including intraoperative visualization of the MEG localizations in 22 and functional MR imaging (for motor and speech areas) as well as DTI fiber tracking (for language and pyramidal tracts) in 13 patients. In the first group, complete resection of the defined EZ including the MEG localization according to the latest postoperative MRI was achieved in four out of six patients. Groups two and three had complete removal of the MEG localizations in 20/22 (91%, 10 of 11 each). Intraoperative MRI revealed incomplete resection of the MEG localizations of four patients (12%; two in both groups), leading to successful re-resection. Transient and permanent neurological deficits alike occurred in 7.1%, surgery-associated complications in 11% of all patients. In the first group, excellent seizure outcome (Engel Class IA) was achieved in three (50%), in the second in 7 patients (61%) and third group in 8 patients (64%, two iopMRI-based re-resections). Mean follow-up was 70.3 months (from 12 to 284 months). In our series, MEG-guided resection using neuronavigation and iopMR imaging led to promising seizure control rates. Even in non-lesional FLE, seizure control rates and the probability of complete resection of the MEG localizations was similar to lesional FLE using multimodal navigation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain

PubMed Central

Lin, Fa-Hsuan; Witzel, Thomas; Hämäläinen, Matti S.; Dale, Anders M.; Belliveau, John W.; Stufflebeam, Steven M.

2010-01-01

This paper presents a computationally efficient source estimation algorithm that localizes cortical oscillations and their phase relationships. The proposed method employs wavelet-transformed magnetoencephalography (MEG) data and uses anatomical MRI to constrain the current locations to the cortical mantle. In addition, the locations of the sources can be further confined with the help of functional MRI (fMRI) data. As a result, we obtain spatiotemporal maps of spectral power and phase relationships. As an example, we show how the phase locking value (PLV), that is, the trial-by-trial phase relationship between the stimulus and response, can be imaged on the cortex. We apply the method to spontaneous, evoked, and driven cortical oscillations measured with MEG. We test the method of combining MEG, structural MRI, and fMRI using simulated cortical oscillations along Heschl’s gyrus (HG). We also analyze sustained auditory gamma-band neuromagnetic fields from MEG and fMRI measurements. Our results show that combining the MEG recording with fMRI improves source localization for the non-noise-normalized wavelet power. In contrast, noise-normalized spectral power or PLV localization may not benefit from the fMRI constraint. We show that if the thresholds are not properly chosen, noise-normalized spectral power or PLV estimates may contain false (phantom) sources, independent of the inclusion of the fMRI prior information. The proposed algorithm can be used for evoked MEG/EEG and block-designed or event-related fMRI paradigms, or for spontaneous MEG data sets. Spectral spatiotemporal imaging of cortical oscillations and interactions in the human brain can provide further understanding of large-scale neural activity and communication between different brain regions. PMID:15488408

[Biophysical foundations of magnetoencephalograhy].

PubMed

Pastor, J; Sola, R G

It is sought to expose in a simple but rigorous way the physical, neurobiological and methodological foundations of the magnetoencephalography (MEG). We start from the basic properties of the classical electromagnetism, analyzing in detail the concepts of electric and magnetic fields, the Maxwell s equations and the multipolar development of potentials. All these tools are very important to know the peculiarities of the MEG studies. Later on, they are reviewed very briefly the different types of potentials generated by the neurons and their implication in the MEG. Lastly, some necessary technical characteristics will be commented for detection of the very weak neuromagnetic fields. It is shortly exposed the concept of tunnel effect, in one that detection systems used at the present time are based (SQUID). MEG is a very promising recent technique that is used in epilepsy studies, evoked potentials and other functional pathologies. Its utility in clinic continues being even controversial. However, it is fundamental to know the mechanisms that justify their use in order to know better their benefits and limitations.

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

NASA Astrophysics Data System (ADS)

Gutiérrez, David

2008-08-01

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEG data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation.

High-pressure Phase Ge nanoparticles and Si-ZnS nanocomposites: New Paradigms to Improve the Efficiency of MEG Solar Cells

NASA Astrophysics Data System (ADS)

Wippermann, Stefan; Voros, Marton; Somogyi, Balint; Gali, Adam; Rocca, Dario; Gygi, Francois; Zimanyi, Gergely; Galli, Giulia

2014-03-01

The efficiency of nanoparticle (NP) solar cells may substantially exceed the Shockley-Queisser limit by exploiting multi-exciton generation. However, (i) quantum confinement tends to increase the electronic gap and thus the MEG threshold beyond the solar spectrum and (ii) charge extraction through NP networks may be hindered by facile recombination. Using ab initio calculations we found that (i) Ge NPs with exotic core structures such as BC8 exhibit significantly lower gaps and MEG thresholds than particles with diamond cores, and an order of magnitude higher MEG rates. (ii) We also investigated Si NPs embedded in a ZnS host matrix and observed complementary charge transport networks, where electron transport occurs by hopping between NPs and hole transport through the ZnS-matrix. Such complementary pathways may substantially reduce recombination, as was indeed observed in recent experiments. We employed several levels of theory, including DFT with hybrid functionals and GW calculations.

The Cambridge Centre for Ageing and Neuroscience (Cam-CAN) data repository: Structural and functional MRI, MEG, and cognitive data from a cross-sectional adult lifespan sample.

PubMed

Taylor, Jason R; Williams, Nitin; Cusack, Rhodri; Auer, Tibor; Shafto, Meredith A; Dixon, Marie; Tyler, Lorraine K; Cam-Can; Henson, Richard N

2017-01-01

This paper describes the data repository for the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) initial study cohort. The Cam-CAN Stage 2 repository contains multi-modal (MRI, MEG, and cognitive-behavioural) data from a large (approximately N=700), cross-sectional adult lifespan (18-87years old) population-based sample. The study is designed to characterise age-related changes in cognition and brain structure and function, and to uncover the neurocognitive mechanisms that support healthy cognitive ageing. The database contains raw and preprocessed structural MRI, functional MRI (active tasks and resting state), and MEG data (active tasks and resting state), as well as derived scores from cognitive behavioural experiments spanning five broad domains (attention, emotion, action, language, and memory), and demographic and neuropsychological data. The dataset thus provides a depth of neurocognitive phenotyping that is currently unparalleled, enabling integrative analyses of age-related changes in brain structure, brain function, and cognition, and providing a testbed for novel analyses of multi-modal neuroimaging data. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Graph theoretical analysis of complex networks in the brain

PubMed Central

Stam, Cornelis J; Reijneveld, Jaap C

2007-01-01

Since the discovery of small-world and scale-free networks the study of complex systems from a network perspective has taken an enormous flight. In recent years many important properties of complex networks have been delineated. In particular, significant progress has been made in understanding the relationship between the structural properties of networks and the nature of dynamics taking place on these networks. For instance, the 'synchronizability' of complex networks of coupled oscillators can be determined by graph spectral analysis. These developments in the theory of complex networks have inspired new applications in the field of neuroscience. Graph analysis has been used in the study of models of neural networks, anatomical connectivity, and functional connectivity based upon fMRI, EEG and MEG. These studies suggest that the human brain can be modelled as a complex network, and may have a small-world structure both at the level of anatomical as well as functional connectivity. This small-world structure is hypothesized to reflect an optimal situation associated with rapid synchronization and information transfer, minimal wiring costs, as well as a balance between local processing and global integration. The topological structure of functional networks is probably restrained by genetic and anatomical factors, but can be modified during tasks. There is also increasing evidence that various types of brain disease such as Alzheimer's disease, schizophrenia, brain tumours and epilepsy may be associated with deviations of the functional network topology from the optimal small-world pattern. PMID:17908336

Large-scale functional networks connect differently for processing words and symbol strings.

PubMed

Liljeström, Mia; Vartiainen, Johanna; Kujala, Jan; Salmelin, Riitta

2018-01-01

Reconfigurations of synchronized large-scale networks are thought to be central neural mechanisms that support cognition and behavior in the human brain. Magnetoencephalography (MEG) recordings together with recent advances in network analysis now allow for sub-second snapshots of such networks. In the present study, we compared frequency-resolved functional connectivity patterns underlying reading of single words and visual recognition of symbol strings. Word reading emphasized coherence in a left-lateralized network with nodes in classical perisylvian language regions, whereas symbol processing recruited a bilateral network, including connections between frontal and parietal regions previously associated with spatial attention and visual working memory. Our results illustrate the flexible nature of functional networks, whereby processing of different form categories, written words vs. symbol strings, leads to the formation of large-scale functional networks that operate at distinct oscillatory frequencies and incorporate task-relevant regions. These results suggest that category-specific processing should be viewed not so much as a local process but as a distributed neural process implemented in signature networks. For words, increased coherence was detected particularly in the alpha (8-13 Hz) and high gamma (60-90 Hz) frequency bands, whereas increased coherence for symbol strings was observed in the high beta (21-29 Hz) and low gamma (30-45 Hz) frequency range. These findings attest to the role of coherence in specific frequency bands as a general mechanism for integrating stimulus-dependent information across brain regions.

MEG3, HCN3 and linc01105 influence the proliferation and apoptosis of neuroblastoma cells via the HIF-1α and p53 pathways.

PubMed

Tang, Weitao; Dong, Kuiran; Li, Kai; Dong, Rui; Zheng, Shan

2016-11-08

The purpose of this study was to investigate the differential expression and functional roles of long non-coding RNAs (lncRNAs) in neuroblastoma tissue. LncRNA microarrays were used to identify differentially expressed lncRNAs between tumor and para-tumor tissues. In total, in tumor tissues, 3,098 and 1,704 lncRNAs were upregulated and downregulated, respectively. HCN3 and linc01105 exhibited the higher expression (P < 0.05; P < 0.01, respectively) in neuroblastoma tissue, whereas MEG3 displayed the lower expression (P < 0.01). HIF-1α expression was negatively correlated with cell proliferation in the linc01105 KD group. In addition, Noxa and Bid expression was positively correlated with cell apoptosis. Moreover, linc01105 knockdown promoted cell proliferation, whereas MEG3 overexpression inhibited proliferation. Finally, linc01105 knockdown, MEG3 overexpression and HCN3 knockdown all increased apoptosis. The correlation coefficients between those three lncRNAs and the International Neuroblastoma Staging System (INSS) stage were -0.48, -0.58 and -0.55, respectively. In conclusion, we have identified lncRNAs that are differentially expressed in neuroblastoma tissues. The lncRNAs HCN3, linc01105, and MEG3 may be important in biological behaviors of neuroblastoma through mechanisms involving p53 pathway members such as HIF-1α, Noxa, and Bid. The expressions of MEG3, HCN3 and linc01105 are all negatively correlated with the INSS stage.

fMRI-vs-MEG evaluation of post-stroke interhemispheric asymmetries in primary sensorimotor hand areas.

PubMed

Altamura, Claudia; Torquati, Kahtya; Zappasodi, Filippo; Ferretti, Antonio; Pizzella, Vittorio; Tibuzzi, Francesco; Vernieri, Fabrizio; Pasqualetti, Patrizio; Landi, Doriana; Del Gratta, Cosimo; Romani, Gian-Luca; Maria Rossini, Paolo; Tecchio, Franca

2007-04-01

Growing evidence emphasizes a positive role of brain ipsilesional (IL) reorganization in stroke patients with partial recovery. Ten patients affected by a monohemispheric stroke in the middle cerebral artery territory underwent functional magnetic resonance (fMRI) and magnetoencephalography (MEG) evaluation of the primary sensory (S1) activation via the same paradigm (median nerve galvanic stimulation). Four patients did not present S1 fMRI activation [Rossini, P.M., Altamura, C., Ferretti, A., Vernieri, F., Zappasodi, F., Caulo, M., Pizzella, V., Del Gratta, C., Romani, G.L., Tecchio, F., 2004. Does cerebrovascular disease affect the coupling between neuronal activity and local haemodynamics? Brain 127, 99-110], although inclusion criteria required bilateral identifiable MEG responses. Mean Euclidean distance between fMRI and MEG S1 activation Talairach coordinates was 10.1+/-2.9 mm, with a 3D intra-class correlation (ICC) coefficient of 0.986. Interhemispheric asymmetries, evaluated by an MEG procedure independent of Talairach transformation, were outside or at the boundaries of reference ranges in 6 patients. In 3 of them, the IL activation presented medial or lateral shift with respect to the omega-shaped post-rolandic area while in the other 3, IL areas were outside the peri-rolandic region. In conclusion, despite dissociated intensity, the MEG and fMRI activations displayed good spatial consistency in stroke patients, thus confirming excessive interhemispheric asymmetries as a suitable indicator of unusual recruitments in the ipsilesional hemisphere, within or outside the peri-rolandic region.

Joint Estimation of Effective Brain Wave Activation Modes Using EEG/MEG Sensor Arrays and Multimodal MRI Volumes.

PubMed

Galinsky, Vitaly L; Martinez, Antigona; Paulus, Martin P; Frank, Lawrence R

2018-04-13

In this letter, we present a new method for integration of sensor-based multifrequency bands of electroencephalography and magnetoencephalography data sets into a voxel-based structural-temporal magnetic resonance imaging analysis by utilizing the general joint estimation using entropy regularization (JESTER) framework. This allows enhancement of the spatial-temporal localization of brain function and the ability to relate it to morphological features and structural connectivity. This method has broad implications for both basic neuroscience research and clinical neuroscience focused on identifying disease-relevant biomarkers by enhancing the spatial-temporal resolution of the estimates derived from current neuroimaging modalities, thereby providing a better picture of the normal human brain in basic neuroimaging experiments and variations associated with disease states.

A Healthy Brain in a Healthy Body: Brain Network Correlates of Physical and Mental Fitness

PubMed Central

Douw, Linda; Nieboer, Dagmar; van Dijk, Bob W.; Stam, Cornelis J.; Twisk, Jos W. R.

2014-01-01

A healthy lifestyle is an important focus in today's society. The physical benefits of regular exercise are abundantly clear, but physical fitness is also associated with better cognitive performance. How these two factors together relate to characteristics of the brain is still incompletely understood. By applying mathematical concepts from ‘network theory’, insights in the organization and dynamics of brain functioning can be obtained. We test the hypothesis that neural network organization mediates the association between cardio respiratory fitness (i.e. VO2 max) and cognitive functioning. A healthy cohort was studied (n = 219, 113 women, age range 41–44 years). Subjects underwent resting-state eyes-closed magneto-encephalography (MEG). Five artifact-free epochs were analyzed and averaged in six frequency bands (delta-gamma). The phase lag index (PLI) was used as a measure of functional connectivity between all sensors. Modularity analysis was performed, and both within and between-module connectivity of each sensor was calculated. Subjects underwent a maximum oxygen uptake (VO2 max) measurement as an indicator of cardio respiratory fitness. All subjects were tested with a commonly used Dutch intelligence test. Intelligence quotient (IQ) was related to VO2 max. In addition, VO2 max was negatively associated with upper alpha and beta band modularity. Particularly increased intermodular connectivity in the beta band was associated with higher VO2 max and IQ, further indicating a benefit of more global network integration as opposed to local connections. Within-module connectivity showed a spatially varied pattern of correlation, while average connectivity did not show significant results. Mediation analysis was not significant. The occurrence of less modularity in the resting-state is associated with better cardio respiratory fitness, while having increased intermodular connectivity, as opposed to within-module connections, is related to better physical and mental fitness. PMID:24498438

Assessment of hemispheric dominance for receptive language in pediatric patients under sedation using magnetoencephalography.

PubMed

Rezaie, Roozbeh; Narayana, Shalini; Schiller, Katherine; Birg, Liliya; Wheless, James W; Boop, Frederick A; Papanicolaou, Andrew C

2014-01-01

Non-invasive assessment of hemispheric dominance for receptive language using magnetoencephalography (MEG) is now a well-established procedure used across several epilepsy centers in the context of pre-surgical evaluation of children and adults while awake, alert and attentive. However, the utility of MEG for the same purpose, in cases of sedated patients, is contested. Establishment of the efficiency of MEG is especially important in the case of children who, for a number of reasons, must be assessed under sedation. Here we explored the efficacy of MEG language mapping under sedation through retrospective review of 95 consecutive pediatric patients, who underwent our receptive language test as part of routine clinical evaluation. Localization of receptive language cortex and subsequent determination of laterality was successfully completed in 78% (n = 36) and 55% (n = 27) of non-sedated and sedated patients, respectively. Moreover, the proportion of patients deemed left hemisphere dominant for receptive language did not differ between non-sedated and sedated patients, exceeding 90% in both groups. Considering the challenges associated with assessing brain function in pediatric patients, the success of passive MEG in the context of the cases reviewed in this study support the utility of this method in pre-surgical receptive language mapping.

Assessment of hemispheric dominance for receptive language in pediatric patients under sedation using magnetoencephalography

PubMed Central

Rezaie, Roozbeh; Narayana, Shalini; Schiller, Katherine; Birg, Liliya; Wheless, James W.; Boop, Frederick A.; Papanicolaou, Andrew C.

2014-01-01

Non-invasive assessment of hemispheric dominance for receptive language using magnetoencephalography (MEG) is now a well-established procedure used across several epilepsy centers in the context of pre-surgical evaluation of children and adults while awake, alert and attentive. However, the utility of MEG for the same purpose, in cases of sedated patients, is contested. Establishment of the efficiency of MEG is especially important in the case of children who, for a number of reasons, must be assessed under sedation. Here we explored the efficacy of MEG language mapping under sedation through retrospective review of 95 consecutive pediatric patients, who underwent our receptive language test as part of routine clinical evaluation. Localization of receptive language cortex and subsequent determination of laterality was successfully completed in 78% (n = 36) and 55% (n = 27) of non-sedated and sedated patients, respectively. Moreover, the proportion of patients deemed left hemisphere dominant for receptive language did not differ between non-sedated and sedated patients, exceeding 90% in both groups. Considering the challenges associated with assessing brain function in pediatric patients, the success of passive MEG in the context of the cases reviewed in this study support the utility of this method in pre-surgical receptive language mapping. PMID:25191260

Real-Time Control of a Neuroprosthetic Hand by Magnetoencephalographic Signals from Paralysed Patients.

PubMed

Fukuma, Ryohei; Yanagisawa, Takufumi; Saitoh, Youichi; Hosomi, Koichi; Kishima, Haruhiko; Shimizu, Takeshi; Sugata, Hisato; Yokoi, Hiroshi; Hirata, Masayuki; Kamitani, Yukiyasu; Yoshimine, Toshiki

2016-02-24

Neuroprosthetic arms might potentially restore motor functions for severely paralysed patients. Invasive measurements of cortical currents using electrocorticography have been widely used for neuroprosthetic control. Moreover, magnetoencephalography (MEG) exhibits characteristic brain signals similar to those of invasively measured signals. However, it remains unclear whether non-invasively measured signals convey enough motor information to control a neuroprosthetic hand, especially for severely paralysed patients whose sensorimotor cortex might be reorganized. We tested an MEG-based neuroprosthetic system to evaluate the accuracy of using cortical currents in the sensorimotor cortex of severely paralysed patients to control a prosthetic hand. The patients attempted to grasp with or open their paralysed hand while the slow components of MEG signals (slow movement fields; SMFs) were recorded. Even without actual movements, the SMFs of all patients indicated characteristic spatiotemporal patterns similar to actual movements, and the SMFs were successfully used to control a neuroprosthetic hand in a closed-loop condition. These results demonstrate that the slow components of MEG signals carry sufficient information to classify movement types. Successful control by paralysed patients suggests the feasibility of using an MEG-based neuroprosthetic hand to predict a patient's ability to control an invasive neuroprosthesis via the same signal sources as the non-invasive method.

Real-Time Control of a Neuroprosthetic Hand by Magnetoencephalographic Signals from Paralysed Patients

PubMed Central

Fukuma, Ryohei; Yanagisawa, Takufumi; Saitoh, Youichi; Hosomi, Koichi; Kishima, Haruhiko; Shimizu, Takeshi; Sugata, Hisato; Yokoi, Hiroshi; Hirata, Masayuki; Kamitani, Yukiyasu; Yoshimine, Toshiki

2016-01-01

Neuroprosthetic arms might potentially restore motor functions for severely paralysed patients. Invasive measurements of cortical currents using electrocorticography have been widely used for neuroprosthetic control. Moreover, magnetoencephalography (MEG) exhibits characteristic brain signals similar to those of invasively measured signals. However, it remains unclear whether non-invasively measured signals convey enough motor information to control a neuroprosthetic hand, especially for severely paralysed patients whose sensorimotor cortex might be reorganized. We tested an MEG-based neuroprosthetic system to evaluate the accuracy of using cortical currents in the sensorimotor cortex of severely paralysed patients to control a prosthetic hand. The patients attempted to grasp with or open their paralysed hand while the slow components of MEG signals (slow movement fields; SMFs) were recorded. Even without actual movements, the SMFs of all patients indicated characteristic spatiotemporal patterns similar to actual movements, and the SMFs were successfully used to control a neuroprosthetic hand in a closed-loop condition. These results demonstrate that the slow components of MEG signals carry sufficient information to classify movement types. Successful control by paralysed patients suggests the feasibility of using an MEG-based neuroprosthetic hand to predict a patient’s ability to control an invasive neuroprosthesis via the same signal sources as the non-invasive method. PMID:26904967

Spatiotemporal frequency tuning of BOLD and gamma band MEG responses compared in primary visual cortex.

PubMed

Muthukumaraswamy, Suresh D; Singh, Krish D

2008-05-01

In this study, the spatial and temporal frequency tuning characteristics of the MEG gamma (40-60 Hz) rhythm and the BOLD response in primary visual cortex were measured and compared. In an identical MEG/fMRI paradigm, 10 participants viewed reversing square wave gratings at 2 spatial frequencies [0.5 and 3 cycles per degree (cpd)] reversing at 5 temporal frequencies (0, 1 6, 10, 15 Hz). Three-dimensional images of MEG source power were generated with synthetic aperture magnetometry (SAM) and showed a high degree of spatial correspondence with BOLD responses in primary visual cortex with a mean spatial separation of 6.5 mm, but the two modalities showed different tuning characteristics. The gamma rhythm showed a clear increase in induced power for the high spatial frequency stimulus while BOLD showed no difference in activity for the two spatial frequencies used. Both imaging modalities showed a general increase of activity with temporal frequency, however, BOLD plateaued around 6-10 Hz while the MEG generally increased with a dip exhibited at 6 Hz. These results demonstrate that the two modalities may show activation in similar spatial locations but that the functional pattern of these activations may differ in a complex manner, suggesting that they may be tuned to different aspects of neuronal activity.

A Realistic Neural Mass Model of the Cortex with Laminar-Specific Connections and Synaptic Plasticity – Evaluation with Auditory Habituation

PubMed Central

Wang, Peng; Knösche, Thomas R.

2013-01-01

In this work we propose a biologically realistic local cortical circuit model (LCCM), based on neural masses, that incorporates important aspects of the functional organization of the brain that have not been covered by previous models: (1) activity dependent plasticity of excitatory synaptic couplings via depleting and recycling of neurotransmitters and (2) realistic inter-laminar dynamics via laminar-specific distribution of and connections between neural populations. The potential of the LCCM was demonstrated by accounting for the process of auditory habituation. The model parameters were specified using Bayesian inference. It was found that: (1) besides the major serial excitatory information pathway (layer 4 to layer 2/3 to layer 5/6), there exists a parallel “short-cut” pathway (layer 4 to layer 5/6), (2) the excitatory signal flow from the pyramidal cells to the inhibitory interneurons seems to be more intra-laminar while, in contrast, the inhibitory signal flow from inhibitory interneurons to the pyramidal cells seems to be both intra- and inter-laminar, and (3) the habituation rates of the connections are unsymmetrical: forward connections (from layer 4 to layer 2/3) are more strongly habituated than backward connections (from Layer 5/6 to layer 4). Our evaluation demonstrates that the novel features of the LCCM are of crucial importance for mechanistic explanations of brain function. The incorporation of these features into a mass model makes them applicable to modeling based on macroscopic data (like EEG or MEG), which are usually available in human experiments. Our LCCM is therefore a valuable building block for future realistic models of human cognitive function. PMID:24205009

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

PubMed Central

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for “temporal receptive windows” that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision-making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or EEG/MEG) by taking into account inter-areal heterogeneity. PMID:26439530

The Contribution of Increased Gamma Band Connectivity to Visual Non-Verbal Reasoning in Autistic Children: A MEG Study

PubMed Central

Takesaki, Natsumi; Kikuchi, Mitsuru; Yoshimura, Yuko; Hiraishi, Hirotoshi; Hasegawa, Chiaki; Kaneda, Reizo; Nakatani, Hideo; Takahashi, Tetsuya; Mottron, Laurent; Minabe, Yoshio

2016-01-01

Some individuals with autism spectrum (AS) perform better on visual reasoning tasks than would be predicted by their general cognitive performance. In individuals with AS, mechanisms in the brain’s visual area that underlie visual processing play a more prominent role in visual reasoning tasks than they do in normal individuals. In addition, increased connectivity with the visual area is thought to be one of the neural bases of autistic visual cognitive abilities. However, the contribution of such brain connectivity to visual cognitive abilities is not well understood, particularly in children. In this study, we investigated how functional connectivity between the visual areas and higher-order regions, which is reflected by alpha, beta and gamma band oscillations, contributes to the performance of visual reasoning tasks in typically developing (TD) (n = 18) children and AS children (n = 18). Brain activity was measured using a custom child-sized magneto-encephalograph. Imaginary coherence analysis was used as a proxy to estimate the functional connectivity between the occipital and other areas of the brain. Stronger connectivity from the occipital area, as evidenced by higher imaginary coherence in the gamma band, was associated with higher performance in the AS children only. We observed no significant correlation between the alpha or beta bands imaginary coherence and performance in the both groups. Alpha and beta bands reflect top-down pathways, while gamma band oscillations reflect a bottom-up influence. Therefore, our results suggest that visual reasoning in AS children is at least partially based on an enhanced reliance on visual perception and increased bottom-up connectivity from the visual areas. PMID:27631982

Biosynthesis and secretion of functional protein S by a human megakaryoblastic cell line (MEG-01)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ogura, M.; Tanabe, N.; Nishioka, J.

A human megakaryoblastic cell line (MEG-01) was investigated for the presence of protein S in culture medium and cell lysates using a specific enzyme-linked immunoassay (ELISA) and a functional assay. When 5 X 10(5) MEG-01 cells/mL was subcultured in RPMI 1640 medium with 10% fetal calf serum (FCS), the concentration of protein S antigen in the culture medium increased progressively with time from less than 8 ng/mL on day 0 to 105.6 +/- 6.0 ng/mL on day 13. Vitamin K2(1 microgram/mL) increased the production of functional protein S, whereas warfarin (1 microgram/mL) profoundly decreased the quantity and the specific activitymore » of secreted protein S. By an indirect immunofluorescent technique, protein S antigen was detected in both MEG-01 cells and human bone marrow megakaryocytes. Immunoblot analysis of culture medium revealed two distinct bands (mol wt 84,000 and 78,000) that are identical to the doublets of purified plasma protein S. De novo synthesis of protein S was demonstrated by the presence of specific immunoprecipitable radioactivity in the medium after 5 hours of labeling of the cells with (/sup 35/S)-methionine as a 84,000 mol wt protein. Plasma protein S levels of nine patients with severe aplastic anemia were not significantly different from those of normal controls. These results suggest that megakaryocytes produce functional protein S and contain the enzymes required for the carboxylation of selected glutamic acid residues, and that protein S synthesized by megakaryocytes does not represent a main source of plasma protein S.« less

Multivariate pattern analysis of MEG and EEG: A comparison of representational structure in time and space.

PubMed

Cichy, Radoslaw Martin; Pantazis, Dimitrios

2017-09-01

Multivariate pattern analysis of magnetoencephalography (MEG) and electroencephalography (EEG) data can reveal the rapid neural dynamics underlying cognition. However, MEG and EEG have systematic differences in sampling neural activity. This poses the question to which degree such measurement differences consistently bias the results of multivariate analysis applied to MEG and EEG activation patterns. To investigate, we conducted a concurrent MEG/EEG study while participants viewed images of everyday objects. We applied multivariate classification analyses to MEG and EEG data, and compared the resulting time courses to each other, and to fMRI data for an independent evaluation in space. We found that both MEG and EEG revealed the millisecond spatio-temporal dynamics of visual processing with largely equivalent results. Beyond yielding convergent results, we found that MEG and EEG also captured partly unique aspects of visual representations. Those unique components emerged earlier in time for MEG than for EEG. Identifying the sources of those unique components with fMRI, we found the locus for both MEG and EEG in high-level visual cortex, and in addition for MEG in low-level visual cortex. Together, our results show that multivariate analyses of MEG and EEG data offer a convergent and complimentary view on neural processing, and motivate the wider adoption of these methods in both MEG and EEG research. Copyright © 2017 Elsevier Inc. All rights reserved.

An intra-neural microstimulation system for ultra-high field magnetic resonance imaging and magnetoencephalography.

PubMed

Glover, Paul M; Watkins, Roger H; O'Neill, George C; Ackerley, Rochelle; Sanchez-Panchuelo, Rosa; McGlone, Francis; Brookes, Matthew J; Wessberg, Johan; Francis, Susan T

2017-10-01

Intra-neural microstimulation (INMS) is a technique that allows the precise delivery of low-current electrical pulses into human peripheral nerves. Single unit INMS can be used to stimulate individual afferent nerve fibres during microneurography. Combining this with neuroimaging allows the unique monitoring of central nervous system activation in response to unitary, controlled tactile input, with functional magnetic resonance imaging (fMRI) providing exquisite spatial localisation of brain activity and magnetoencephalography (MEG) high temporal resolution. INMS systems suitable for use within electrophysiology laboratories have been available for many years. We describe an INMS system specifically designed to provide compatibility with both ultra-high field (7T) fMRI and MEG. Numerous technical and safety issues are addressed. The system is fully analogue, allowing for arbitrary frequency and amplitude INMS stimulation. Unitary recordings obtained within both the MRI and MEG screened-room environments are comparable with those obtained in 'clean' electrophysiology recording environments. Single unit INMS (current <7μA, 200μs pulses) of individual mechanoreceptive afferents produces appropriate and robust responses during fMRI and MEG. This custom-built MRI- and MEG-compatible stimulator overcomes issues with existing INMS approaches; it allows well-controlled switching between recording and stimulus mode, prevents electrical shocks because of long cable lengths, permits unlimited patterns of stimulation, and provides a system with improved work-flow and participant comfort. We demonstrate that the requirements for an INMS-integrated system, which can be used with both fMRI and MEG imaging systems, have been fully met. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

MEG3, HCN3 and linc01105 influence the proliferation and apoptosis of neuroblastoma cells via the HIF-1α and p53 pathways

PubMed Central

Tang, Weitao; Dong, Kuiran; Li, Kai; Dong, Rui; Zheng, Shan

2016-01-01

The purpose of this study was to investigate the differential expression and functional roles of long non-coding RNAs (lncRNAs) in neuroblastoma tissue. LncRNA microarrays were used to identify differentially expressed lncRNAs between tumor and para-tumor tissues. In total, in tumor tissues, 3,098 and 1,704 lncRNAs were upregulated and downregulated, respectively. HCN3 and linc01105 exhibited the higher expression (P < 0.05; P < 0.01, respectively) in neuroblastoma tissue, whereas MEG3 displayed the lower expression (P < 0.01). HIF-1α expression was negatively correlated with cell proliferation in the linc01105 KD group. In addition, Noxa and Bid expression was positively correlated with cell apoptosis. Moreover, linc01105 knockdown promoted cell proliferation, whereas MEG3 overexpression inhibited proliferation. Finally, linc01105 knockdown, MEG3 overexpression and HCN3 knockdown all increased apoptosis. The correlation coefficients between those three lncRNAs and the International Neuroblastoma Staging System (INSS) stage were −0.48, −0.58 and −0.55, respectively. In conclusion, we have identified lncRNAs that are differentially expressed in neuroblastoma tissues. The lncRNAs HCN3, linc01105, and MEG3 may be important in biological behaviors of neuroblastoma through mechanisms involving p53 pathway members such as HIF-1α, Noxa, and Bid. The expressions of MEG3, HCN3 and linc01105 are all negatively correlated with the INSS stage. PMID:27824082

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM☆

PubMed Central

López, J.D.; Litvak, V.; Espinosa, J.J.; Friston, K.; Barnes, G.R.

2014-01-01

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy—an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. PMID:24041874

Graph properties of synchronized cortical networks during visual working memory maintenance.

PubMed

Palva, Satu; Monto, Simo; Palva, J Matias

2010-02-15

Oscillatory synchronization facilitates communication in neuronal networks and is intimately associated with human cognition. Neuronal activity in the human brain can be non-invasively imaged with magneto- (MEG) and electroencephalography (EEG), but the large-scale structure of synchronized cortical networks supporting cognitive processing has remained uncharacterized. We combined simultaneous MEG and EEG (MEEG) recordings with minimum-norm-estimate-based inverse modeling to investigate the structure of oscillatory phase synchronized networks that were active during visual working memory (VWM) maintenance. Inter-areal phase-synchrony was quantified as a function of time and frequency by single-trial phase-difference estimates of cortical patches covering the entire cortical surfaces. The resulting networks were characterized with a number of network metrics that were then compared between delta/theta- (3-6 Hz), alpha- (7-13 Hz), beta- (16-25 Hz), and gamma- (30-80 Hz) frequency bands. We found several salient differences between frequency bands. Alpha- and beta-band networks were more clustered and small-world like but had smaller global efficiency than the networks in the delta/theta and gamma bands. Alpha- and beta-band networks also had truncated-power-law degree distributions and high k-core numbers. The data converge on showing that during the VWM-retention period, human cortical alpha- and beta-band networks have a memory-load dependent, scale-free small-world structure with densely connected core-like structures. These data further show that synchronized dynamic networks underlying a specific cognitive state can exhibit distinct frequency-dependent network structures that could support distinct functional roles. Copyright 2009 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Khosla, D.; Singh, M.

The estimation of three-dimensional dipole current sources on the cortical surface from the measured magnetoencephalogram (MEG) is a highly under determined inverse problem as there are many {open_quotes}feasible{close_quotes} images which are consistent with the MEG data. Previous approaches to this problem have concentrated on the use of weighted minimum norm inverse methods. While these methods ensure a unique solution, they often produce overly smoothed solutions and exhibit severe sensitivity to noise. In this paper we explore the maximum entropy approach to obtain better solutions to the problem. This estimation technique selects that image from the possible set of feasible imagesmore » which has the maximum entropy permitted by the information available to us. In order to account for the presence of noise in the data, we have also incorporated a noise rejection or likelihood term into our maximum entropy method. This makes our approach mirror a Bayesian maximum a posteriori (MAP) formulation. Additional information from other functional techniques like functional magnetic resonance imaging (fMRI) can be incorporated in the proposed method in the form of a prior bias function to improve solutions. We demonstrate the method with experimental phantom data from a clinical 122 channel MEG system.« less

Altered retrieval of melodic information in congenital amusia: insights from dynamic causal modeling of MEG data.

PubMed

Albouy, Philippe; Mattout, Jérémie; Sanchez, Gaëtan; Tillmann, Barbara; Caclin, Anne

2015-01-01

Congenital amusia is a neuro-developmental disorder that primarily manifests as a difficulty in the perception and memory of pitch-based materials, including music. Recent findings have shown that the amusic brain exhibits altered functioning of a fronto-temporal network during pitch perception and short-term memory. Within this network, during the encoding of melodies, a decreased right backward frontal-to-temporal connectivity was reported in amusia, along with an abnormal connectivity within and between auditory cortices. The present study investigated whether connectivity patterns between these regions were affected during the short-term memory retrieval of melodies. Amusics and controls had to indicate whether sequences of six tones that were presented in pairs were the same or different. When melodies were different only one tone changed in the second melody. Brain responses to the changed tone in "Different" trials and to its equivalent (original) tone in "Same" trials were compared between groups using Dynamic Causal Modeling (DCM). DCM results confirmed that congenital amusia is characterized by an altered effective connectivity within and between the two auditory cortices during sound processing. Furthermore, right temporal-to-frontal message passing was altered in comparison to controls, with notably an increase in "Same" trials. An additional analysis in control participants emphasized that the detection of an unexpected event in the typically functioning brain is supported by right fronto-temporal connections. The results can be interpreted in a predictive coding framework as reflecting an abnormal prediction error sent by temporal auditory regions towards frontal areas in the amusic brain.

LncRNA MEG3 repressed malignant melanoma progression via inactivating Wnt signaling pathway.

PubMed

Li, Peng; Gao, Ying; Li, Jun; Zhou, Yu; Yuan, Jing; Guan, Huiwen; Yao, Peng

2018-05-21

Accumulating evidence has indicated that MEG3 can serve as a tumor suppressive lncRNA in various tumors. It is aberrantly expressed in multiple cancers. However, the biological roles of MEG3 in melanoma are poorly understood. Therefore, in our study, we concentrated on the biological mechanism of MEG3 in melanoma progression. First, we observed that MEG3 was obviously decreased in melanoma cells including A375, SK-MEL-1, B16, and A2058 cells compared to human epidermal melanocytes HEMa-LP. MEG3 was restored by transfecting LV-MEG3 in to A375 and A2058 cells. Subsequently, we found that overexpression of MEG3 was able to inhibit cell proliferation and colony formation capacity. Meanwhile, melanoma cell apoptosis was induced by up-regulation of MEG3. Overexpression of MEG3 greatly repressed melanoma cell migration and invasion ability. In addition, Wnt signaling pathway has been identified in the progression of various cancers. Here, in our study, it was indicated that Wnt signaling was highly activated in melanoma cells with β-catenin expression significantly increased and GSK-3β decreased. Interestingly, MEG restoration strongly inactivated Wnt signaling pathway by reducing β-catenin and CyclinD1, elevating GSK-3β levels in vitro. Finally, in vivo experiments were carried out to confirm the inhibitory roles of MEG3 in vivo. Taken these together, we suggested that MEG3 can inhibit melanoma development through blocking Wnt signaling pathway. © 2018 Wiley Periodicals, Inc.

Mapping the Alzheimer’s Brain with Connectomics

PubMed Central

Xie, Teng; He, Yong

2012-01-01

Alzheimer’s disease (AD) is the most common form of dementia. As an incurable, progressive, and neurodegenerative disease, it causes cognitive and memory deficits. However, the biological mechanisms underlying the disease are not thoroughly understood. In recent years, non-invasive neuroimaging and neurophysiological techniques [e.g., structural magnetic resonance imaging (MRI), diffusion MRI, functional MRI, and EEG/MEG] and graph theory based network analysis have provided a new perspective on structural and functional connectivity patterns of the human brain (i.e., the human connectome) in health and disease. Using these powerful approaches, several recent studies of patients with AD exhibited abnormal topological organization in both global and regional properties of neuronal networks, indicating that AD not only affects specific brain regions, but also alters the structural and functional associations between distinct brain regions. Specifically, disruptive organization in the whole-brain networks in AD is involved in the loss of small-world characters and the re-organization of hub distributions. These aberrant neuronal connectivity patterns were associated with cognitive deficits in patients with AD, even with genetic factors in healthy aging. These studies provide empirical evidence to support the existence of an aberrant connectome of AD. In this review we will summarize recent advances discovered in large-scale brain network studies of AD, mainly focusing on graph theoretical analysis of brain connectivity abnormalities. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis and monitoring. PMID:22291664

Frequency domain beamforming of magnetoencephalographic beta band activity in epilepsy patients with focal cortical dysplasia.

PubMed

Heers, Marcel; Hirschmann, Jan; Jacobs, Julia; Dümpelmann, Matthias; Butz, Markus; von Lehe, Marec; Elger, Christian E; Schnitzler, Alfons; Wellmer, Jörg

2014-09-01

Spike-based magnetoencephalography (MEG) source localization is an established method in the presurgical evaluation of epilepsy patients. Focal cortical dysplasias (FCDs) are associated with focal epileptic discharges of variable morphologies in the beta frequency band in addition to single epileptic spikes. Therefore, we investigated the potential diagnostic value of MEG-based localization of spike-independent beta band (12-30Hz) activity generated by epileptogenic lesions. Five patients with FCD IIB underwent MEG. In one patient, invasive EEG (iEEG) was recorded simultaneously with MEG. In two patients, iEEG succeeded MEG, and two patients had MEG only. MEG and iEEG were evaluated for epileptic spikes. Two minutes of iEEG data and MEG epochs with no spikes as well as MEG epochs with epileptic spikes were analyzed in the frequency domain. MEG oscillatory beta band activity was localized using Dynamic Imaging of Coherent Sources. Intralesional beta band activity was coherent between simultaneous MEG and iEEG recordings. Continuous 14Hz beta band power correlated with the rate of interictal epileptic discharges detected in iEEG. In cases where visual MEG evaluation revealed epileptic spikes, the sources of beta band activity localized within <2cm of the epileptogenic lesion as shown on magnetic resonance imaging. This result held even when visually marked epileptic spikes were deselected. When epileptic spikes were detectable in iEEG but not MEG, MEG beta band activity source localization failed. Source localization of beta band activity has the potential to contribute to the identification of epileptic foci in addition to source localization of visually marked epileptic spikes. Thus, this technique may assist in the localization of epileptic foci in patients with suspected FCD. Copyright © 2014 Elsevier B.V. All rights reserved.

Artemis 123: development of a whole-head infant and young child MEG system

PubMed Central

Roberts, Timothy P. L.; Paulson, Douglas N.; Hirschkoff, Eugene; Pratt, Kevin; Mascarenas, Anthony; Miller, Paul; Han, Mengali; Caffrey, Jason; Kincade, Chuck; Power, Bill; Murray, Rebecca; Chow, Vivian; Fisk, Charlie; Ku, Matthew; Chudnovskaya, Darina; Dell, John; Golembski, Rachel; Lam, Peter; Blaskey, Lisa; Kuschner, Emily; Bloy, Luke; Gaetz, William; Edgar, J. Christopher

2014-01-01

Background: A major motivation in designing the new infant and child magnetoencephalography (MEG) system described in this manuscript is the premise that electrophysiological signatures (resting activity and evoked responses) may serve as biomarkers of neurodevelopmental disorders, with neuronal abnormalities in conditions such as autism spectrum disorder (ASD) potentially detectable early in development. Whole-head MEG systems are generally optimized/sized for adults. Since magnetic field produced by neuronal currents decreases as a function of distance2 and infants and young children have smaller head sizes (and thus increased brain-to-sensor distance), whole-head adult MEG systems do not provide optimal signal-to-noise in younger individuals. This spurred development of a whole-head infant and young child MEG system – Artemis 123. Methods:In addition to describing the design of the Artemis 123, the focus of this manuscript is the use of Artemis 123 to obtain auditory evoked neuromagnetic recordings and resting-state data in young children. Data were collected from a 14-month-old female, an 18-month-old female, and a 48-month-old male. Phantom data are also provided to show localization accuracy. Results:Examination of Artemis 123 auditory data showed generalizability and reproducibility, with auditory responses observed in all participants. The auditory MEG measures were also found to be manipulable, exhibiting sensitivity to tone frequency. Furthermore, there appeared to be a predictable sensitivity of evoked components to development, with latencies decreasing with age. Examination of resting-state data showed characteristic oscillatory activity. Finally, phantom data showed that dipole sources could be localized with an error less than 0.5 cm. Conclusions:Artemis 123 allows efficient recording of high-quality whole-head MEG in infants four years and younger. Future work will involve examining the feasibility of obtaining somatosensory and visual recordings in similar-age children as well as obtaining recordings from younger infants. Thus, the Artemis 123 offers the promise of detecting earlier diagnostic signatures in such neurodevelopmental disorders. PMID:24624069

High-alpha band synchronization across frontal, parietal and visual cortex mediates behavioral and neuronal effects of visuospatial attention.

PubMed

Lobier, Muriel; Palva, J Matias; Palva, Satu

2018-01-15

Visuospatial attention prioritizes processing of attended visual stimuli. It is characterized by lateralized alpha-band (8-14 Hz) amplitude suppression in visual cortex and increased neuronal activity in a network of frontal and parietal areas. It has remained unknown what mechanisms coordinate neuronal processing among frontoparietal network and visual cortices and implement the attention-related modulations of alpha-band amplitudes and behavior. We investigated whether large-scale network synchronization could be such a mechanism. We recorded human cortical activity with magnetoencephalography (MEG) during a visuospatial attention task. We then identified the frequencies and anatomical networks of inter-areal phase synchronization from source localized MEG data. We found that visuospatial attention is associated with robust and sustained long-range synchronization of cortical oscillations exclusively in the high-alpha (10-14 Hz) frequency band. This synchronization connected frontal, parietal and visual regions and was observed concurrently with amplitude suppression of low-alpha (6-9 Hz) band oscillations in visual cortex. Furthermore, stronger high-alpha phase synchronization was associated with decreased reaction times to attended stimuli and larger suppression of alpha-band amplitudes. These results thus show that high-alpha band phase synchronization is functionally significant and could coordinate the neuronal communication underlying the implementation of visuospatial attention. Copyright © 2017 Elsevier Inc. All rights reserved.

Added diagnostic value of magnetoencephalography (MEG) in patients suspected for epilepsy, where previous, extensive EEG workup was unrevealing.

PubMed

Duez, Lene; Beniczky, Sándor; Tankisi, Hatice; Hansen, Peter Orm; Sidenius, Per; Sabers, Anne; Fuglsang-Frederiksen, Anders

2016-10-01

To elucidate the possible additional diagnostic yield of MEG in the workup of patients with suspected epilepsy, where repeated EEGs, including sleep-recordings failed to identify abnormalities. Fifty-two consecutive patients with clinical suspicion of epilepsy and at least three normal EEGs, including sleep-EEG, were prospectively analyzed. The reference standard was inferred from the diagnosis obtained from the medical charts, after at least one-year follow-up. MEG (306-channel, whole-head) and simultaneous EEG (MEG-EEG) was recorded for one hour. The added sensitivity of MEG was calculated from the cases where abnormalities were seen in MEG but not EEG. Twenty-two patients had the diagnosis epilepsy according to the reference standard. MEG-EEG detected abnormalities, and supported the diagnosis in nine of the 22 patients with the diagnosis epilepsy at one-year follow-up. Sensitivity of MEG-EEG was 41%. The added sensitivity of MEG was 18%. MEG-EEG was normal in 28 of the 30 patients categorized as 'not epilepsy' at one year follow-up, yielding a specificity of 93%. MEG provides additional diagnostic information in patients suspected for epilepsy, where repeated EEG recordings fail to demonstrate abnormality. MEG should be included in the diagnostic workup of patients where the conventional, widely available methods are unrevealing. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

PubMed

Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

The effects of neurofeedback on oscillatory processes related to tinnitus.

PubMed

Hartmann, Thomas; Lorenz, Isabel; Müller, Nadia; Langguth, Berthold; Weisz, Nathan

2014-01-01

Although widely used, no proof exists for the feasibility of neurofeedback for reinstating the disordered excitatory-inhibitory balance, marked by a decrease in auditory alpha power, in tinnitus patients. The current study scrutinizes the ability of neurofeedback to focally increase alpha power in auditory areas in comparison to the more common rTMS. Resting-state MEG was measured before and after neurofeedback (n = 8) and rTMS (n = 9) intervention respectively. Source level power and functional connectivity were analyzed with a focus on the alpha band. Only neurofeedback produced a significant decrease in tinnitus symptoms and-more important for the context of the study-a spatially circumscribed increase in alpha power in right auditory regions. Connectivity analysis revealed higher outgoing connectivity in a region ultimately neighboring the area in which power increases were observed. Neurofeedback decreases tinnitus symptoms and increases alpha power in a spatially circumscribed manner. In addition, compared to a more established brain stimulation-based intervention, neurofeedback is a promising approach to renormalize the excitatory-inhibitory imbalance putatively underlying tinnitus. This study is the first to demonstrate the feasibility of focally enhancing alpha activity in tinnitus patients by means of neurofeedback.

Characterising intra- and inter-intrinsic network synchrony in combat-related post-traumatic stress disorder.

PubMed

Dunkley, Benjamin T; Doesburg, Sam M; Jetly, Rakesh; Sedge, Paul A; Pang, Elizabeth W; Taylor, Margot J

2015-11-30

Soldiers with post-traumatic stress disorder (PTSD) exhibit elevated gamma-band synchrony in left fronto-temporal cortex, and connectivity measures in these regions correlate with comorbidities and PTSD severity, which suggests increased gamma synchrony is related to symptomology. However, little is known about the role of intrinsic, phase-synchronised networks in the disorder. Using magnetoencephalography (MEG), we characterised spectral connectivity in the default-mode, salience, visual, and attention networks during resting-state in a PTSD population and a trauma-exposed control group. Intrinsic network connectivity was examined in canonical frequency bands. We observed increased inter-network synchronisation in the PTSD group compared with controls in the gamma (30-80 Hz) and high-gamma range (80-150 Hz). Analyses of connectivity and symptomology revealed that PTSD severity was positively associated with beta synchrony in the ventral-attention-to-salience networks, and gamma synchrony within the salience network, but also negatively correlated with beta synchrony within the visual network. These novel results show that frequency-specific, network-level atypicalities may reflect trauma-related alterations of ongoing functional connectivity, and correlations of beta synchrony in attentional-to-salience and visual networks with PTSD severity suggest complicated network interactions mediate symptoms. These results contribute to accumulating evidence that PTSD is a complicated network-based disorder expressed as altered neural interactions. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography

PubMed Central

Niso, Guiomar; Gorgolewski, Krzysztof J.; Bock, Elizabeth; Brooks, Teon L.; Flandin, Guillaume; Gramfort, Alexandre; Henson, Richard N.; Jas, Mainak; Litvak, Vladimir; T. Moreau, Jeremy; Oostenveld, Robert; Schoffelen, Jan-Mathijs; Tadel, Francois; Wexler, Joseph; Baillet, Sylvain

2018-01-01

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone. PMID:29917016

MEG-BIDS, the brain imaging data structure extended to magnetoencephalography.

PubMed

Niso, Guiomar; Gorgolewski, Krzysztof J; Bock, Elizabeth; Brooks, Teon L; Flandin, Guillaume; Gramfort, Alexandre; Henson, Richard N; Jas, Mainak; Litvak, Vladimir; T Moreau, Jeremy; Oostenveld, Robert; Schoffelen, Jan-Mathijs; Tadel, Francois; Wexler, Joseph; Baillet, Sylvain

2018-06-19

We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone.

Fenofibrate inhibited pancreatic cancer cells proliferation via activation of p53 mediated by upregulation of LncRNA MEG3

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Duanmin; Su, Cunjin; Jiang, Min

There is still no suitable drug for pancreatic cancer treatment, which is one of the most aggressive human tumors. Maternally expressed gene 3 (MEG3), a LncRNA, has been suggested as a tumor suppressor in a range of human tumors. Studies found fenofibrate exerted anti-tumor roles in various human cancer cell lines. However, its role in pancreatic cancer remains unknown. The present study aimed to explore the impacts of fenofibrate on pancreatic cancer cell lines, and to investigate MEG3 role in its anti-tumor mechanisms. We used MTT assay to determine cells proliferation, genome-wide LncRNA microarray analysis to identify differently expressed LncRNAs,more » siRNA or pCDNA-MEG3 transfection to interfere or upregulate MEG3 expression, western blot to detect protein levels, real-time PCR to determine MEG3 level. Fenofibrate significantly inhibited proliferation of pancreatic cancer cells, increased MEG3 expression and p53 levels. Moreover, knockdown of MEG3 attenuated cytotoxicity induced by fenofibrate. Furthermore, overexpression of MEG3 induced cells death and increased p53 expression. Our results indicated fenofibrate inhibited pancreatic cancer cells proliferation via activation of p53 mediated by upregulation of MEG3. - Highlights: • We found that fenofibrate suppressed proliferation of pancreatic cancer cells. • We found fenofibrate increased LncRNA-MEG3 expression and p53 level in PANC-1 cells. • Inhibition of MEG3 expression attenuated anti-tumor effects of fenofibrate.« less

Benchmarking for On-Scalp MEG Sensors.

PubMed

Xie, Minshu; Schneiderman, Justin F; Chukharkin, Maxim L; Kalabukhov, Alexei; Riaz, Bushra; Lundqvist, Daniel; Whitmarsh, Stephen; Hamalainen, Matti; Jousmaki, Veikko; Oostenveld, Robert; Winkler, Dag

2017-06-01

We present a benchmarking protocol for quantitatively comparing emerging on-scalp magnetoencephalography (MEG) sensor technologies to their counterparts in state-of-the-art MEG systems. As a means of validation, we compare a high-critical-temperature superconducting quantum interference device (high T c SQUID) with the low- T c SQUIDs of an Elekta Neuromag TRIUX system in MEG recordings of auditory and somatosensory evoked fields (SEFs) on one human subject. We measure the expected signal gain for the auditory-evoked fields (deeper sources) and notice some unfamiliar features in the on-scalp sensor-based recordings of SEFs (shallower sources). The experimental results serve as a proof of principle for the benchmarking protocol. This approach is straightforward, general to various on-scalp MEG sensors, and convenient to use on human subjects. The unexpected features in the SEFs suggest on-scalp MEG sensors may reveal information about neuromagnetic sources that is otherwise difficult to extract from state-of-the-art MEG recordings. As the first systematically established on-scalp MEG benchmarking protocol, magnetic sensor developers can employ this method to prove the utility of their technology in MEG recordings. Further exploration of the SEFs with on-scalp MEG sensors may reveal unique information about their sources.

Algorithmic procedures for Bayesian MEG/EEG source reconstruction in SPM.

PubMed

López, J D; Litvak, V; Espinosa, J J; Friston, K; Barnes, G R

2014-01-01

The MEG/EEG inverse problem is ill-posed, giving different source reconstructions depending on the initial assumption sets. Parametric Empirical Bayes allows one to implement most popular MEG/EEG inversion schemes (Minimum Norm, LORETA, etc.) within the same generic Bayesian framework. It also provides a cost-function in terms of the variational Free energy-an approximation to the marginal likelihood or evidence of the solution. In this manuscript, we revisit the algorithm for MEG/EEG source reconstruction with a view to providing a didactic and practical guide. The aim is to promote and help standardise the development and consolidation of other schemes within the same framework. We describe the implementation in the Statistical Parametric Mapping (SPM) software package, carefully explaining each of its stages with the help of a simple simulated data example. We focus on the Multiple Sparse Priors (MSP) model, which we compare with the well-known Minimum Norm and LORETA models, using the negative variational Free energy for model comparison. The manuscript is accompanied by Matlab scripts to allow the reader to test and explore the underlying algorithm. © 2013. Published by Elsevier Inc. All rights reserved.

Deletions and epimutations affecting the human 14q32.2 imprinted region in individuals with paternal and maternal upd(14)-like phenotypes.

PubMed

Kagami, Masayo; Sekita, Yoichi; Nishimura, Gen; Irie, Masahito; Kato, Fumiko; Okada, Michiyo; Yamamori, Shunji; Kishimoto, Hiroshi; Nakayama, Masahiro; Tanaka, Yukichi; Matsuoka, Kentarou; Takahashi, Tsutomu; Noguchi, Mika; Tanaka, Yoko; Masumoto, Kouji; Utsunomiya, Takeshi; Kouzan, Hiroko; Komatsu, Yumiko; Ohashi, Hirofumi; Kurosawa, Kenji; Kosaki, Kenjirou; Ferguson-Smith, Anne C; Ishino, Fumitoshi; Ogata, Tsutomu

2008-02-01

Human chromosome 14q32.2 carries a cluster of imprinted genes including paternally expressed genes (PEGs) such as DLK1 and RTL1 and maternally expressed genes (MEGs) such as MEG3 (also known as GTL2), RTL1as (RTL1 antisense) and MEG8 (refs. 1,2), together with the intergenic differentially methylated region (IG-DMR) and the MEG3-DMR. Consistent with this, paternal and maternal uniparental disomy for chromosome 14 (upd(14)pat and upd(14)mat) cause distinct phenotypes. We studied eight individuals (cases 1-8) with a upd(14)pat-like phenotype and three individuals (cases 9-11) with a upd(14)mat-like phenotype in the absence of upd(14) and identified various deletions and epimutations affecting the imprinted region. The results, together with recent mouse data, imply that the IG-DMR has an important cis-acting regulatory function on the maternally inherited chromosome and that excessive RTL1 expression and decreased DLK1 and RTL1 expression are relevant to upd(14)pat-like and upd(14)mat-like phenotypes, respectively.

On the use of EEG or MEG brain imaging tools in neuromarketing research.

PubMed

Vecchiato, Giovanni; Astolfi, Laura; De Vico Fallani, Fabrizio; Toppi, Jlenia; Aloise, Fabio; Bez, Francesco; Wei, Daming; Kong, Wanzeng; Dai, Jounging; Cincotti, Febo; Mattia, Donatella; Babiloni, Fabio

2011-01-01

Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI) methodology, also largely used in the marketing research. In addition, EEG and MEG technologies have greatly improved their spatial resolution in the last decades with the introduction of advanced signal processing methodologies. By presenting data gathered through MEG and high resolution EEG we will show which kind of information it is possible to gather with these methodologies while the persons are watching marketing relevant stimuli. Such information will be related to the memorization and pleasantness related to such stimuli. We noted that temporal and frequency patterns of brain signals are able to provide possible descriptors conveying information about the cognitive and emotional processes in subjects observing commercial advertisements. These information could be unobtainable through common tools used in standard marketing research. We also show an example of how an EEG methodology could be used to analyze cultural differences between fruition of video commercials of carbonated beverages in Western and Eastern countries.

On the Use of EEG or MEG Brain Imaging Tools in Neuromarketing Research

PubMed Central

Vecchiato, Giovanni; Astolfi, Laura; De Vico Fallani, Fabrizio; Toppi, Jlenia; Aloise, Fabio; Bez, Francesco; Wei, Daming; Kong, Wanzeng; Dai, Jounging; Cincotti, Febo; Mattia, Donatella; Babiloni, Fabio

2011-01-01

Here we present an overview of some published papers of interest for the marketing research employing electroencephalogram (EEG) and magnetoencephalogram (MEG) methods. The interest for these methodologies relies in their high-temporal resolution as opposed to the investigation of such problem with the functional Magnetic Resonance Imaging (fMRI) methodology, also largely used in the marketing research. In addition, EEG and MEG technologies have greatly improved their spatial resolution in the last decades with the introduction of advanced signal processing methodologies. By presenting data gathered through MEG and high resolution EEG we will show which kind of information it is possible to gather with these methodologies while the persons are watching marketing relevant stimuli. Such information will be related to the memorization and pleasantness related to such stimuli. We noted that temporal and frequency patterns of brain signals are able to provide possible descriptors conveying information about the cognitive and emotional processes in subjects observing commercial advertisements. These information could be unobtainable through common tools used in standard marketing research. We also show an example of how an EEG methodology could be used to analyze cultural differences between fruition of video commercials of carbonated beverages in Western and Eastern countries. PMID:21960996

Fusion of magnetometer and gradiometer sensors of MEG in the presence of multiplicative error.

PubMed

Mohseni, Hamid R; Woolrich, Mark W; Kringelbach, Morten L; Luckhoo, Henry; Smith, Penny Probert; Aziz, Tipu Z

2012-07-01

Novel neuroimaging techniques have provided unprecedented information on the structure and function of the living human brain. Multimodal fusion of data from different sensors promises to radically improve this understanding, yet optimal methods have not been developed. Here, we demonstrate a novel method for combining multichannel signals. We show how this method can be used to fuse signals from the magnetometer and gradiometer sensors used in magnetoencephalography (MEG), and through extensive experiments using simulation, head phantom and real MEG data, show that it is both robust and accurate. This new approach works by assuming that the lead fields have multiplicative error. The criterion to estimate the error is given within a spatial filter framework such that the estimated power is minimized in the worst case scenario. The method is compared to, and found better than, existing approaches. The closed-form solution and the conditions under which the multiplicative error can be optimally estimated are provided. This novel approach can also be employed for multimodal fusion of other multichannel signals such as MEG and EEG. Although the multiplicative error is estimated based on beamforming, other methods for source analysis can equally be used after the lead-field modification.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

Development of face recognition: Dynamic causal modelling of MEG data.

PubMed

He, Wei; Johnson, Blake W

2018-04-01

Electrophysiological studies of adults indicate that brain activity is enhanced during viewing of repeated faces, at a latency of about 250 ms after the onset of the face (M250/N250). The present study aimed to determine if this effect was also present in preschool-aged children, whose brain activity was measured in a custom-sized pediatric MEG system. The results showed that, unlike adults, face repetition did not show any significant modulation of M250 amplitude in children; however children's M250 latencies were significantly faster for repeated than non-repeated faces. Dynamic causal modelling (DCM) of the M250 in both age groups tested the effects of face repetition within the core face network including the occipital face area (OFA), the fusiform face area (FFA), and the superior temporal sulcus (STS). DCM revealed that repetition of identical faces altered both forward and backward connections in children and adults; however the modulations involved inputs to both FFA and OFA in adults but only to OFA in children. These findings suggest that the amplitude-insensitivity of the immature M250 may be due to a weaker connection between the FFA and lower visual areas. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Error-prone bypass of O6-methylguanine by DNA polymerase of Pseudomonas aeruginosa phage PaP1.

PubMed

Gu, Shiling; Xiong, Jingyuan; Shi, Ying; You, Jia; Zou, Zhenyu; Liu, Xiaoying; Zhang, Huidong

2017-09-01

O 6 -Methylguanine (O 6 -MeG) is highly mutagenic and is commonly found in DNA exposed to methylating agents, generally leads to G:C to A:T mutagenesis. To study DNA replication encountering O 6 -MeG by the DNA polymerase (gp90) of P. aeruginosa phage PaP1, we analyzed steady-state and pre-steady-state kinetics of nucleotide incorporation opposite O 6 -MeG by gp90 exo - . O 6 -MeG partially inhibited full-length extension by gp90 exo - . O 6 -MeG greatly reduces dNTP incorporation efficiency, resulting in 67-fold preferential error-prone incorporation of dTTP than dCTP. Gp90 exo - extends beyond T:O 6 -MeG 2-fold more efficiently than C:O 6 -MeG. Incorporation of dCTP opposite G and incorporation of dCTP or dTTP opposite O 6 -MeG show fast burst phases. The pre-steady-state incorporation efficiency (k pol /K d,dNTP ) is decreased in the order of dCTP:G>dTTP:O 6 -MeG>dCTP:O 6 -MeG. The presence of O 6 -MeG at template does not affect the binding affinity of polymerase to DNA but it weakened their binding in the presence of dCTP and Mg 2+ . Misincorporation of dTTP opposite O 6 -MeG further weakens the binding affinity of polymerase to DNA. The priority of dTTP incorporation opposite O 6 -MeG is originated from the fact that dTTP can induce a faster conformational change step and a faster chemical step than dCTP. This study reveals that gp90 bypasses O 6 -MeG in an error-prone manner and provides further understanding in DNA replication encountering mutagenic alkylation DNA damage for P. aeruginosa phage PaP1. Copyright © 2017 Elsevier B.V. All rights reserved.

Intracranial EEG potentials estimated from MEG sources: A new approach to correlate MEG and iEEG data in epilepsy.

PubMed

Grova, Christophe; Aiguabella, Maria; Zelmann, Rina; Lina, Jean-Marc; Hall, Jeffery A; Kobayashi, Eliane

2016-05-01

Detection of epileptic spikes in MagnetoEncephaloGraphy (MEG) requires synchronized neuronal activity over a minimum of 4cm2. We previously validated the Maximum Entropy on the Mean (MEM) as a source localization able to recover the spatial extent of the epileptic spike generators. The purpose of this study was to evaluate quantitatively, using intracranial EEG (iEEG), the spatial extent recovered from MEG sources by estimating iEEG potentials generated by these MEG sources. We evaluated five patients with focal epilepsy who had a pre-operative MEG acquisition and iEEG with MRI-compatible electrodes. Individual MEG epileptic spikes were localized along the cortical surface segmented from a pre-operative MRI, which was co-registered with the MRI obtained with iEEG electrodes in place for identification of iEEG contacts. An iEEG forward model estimated the influence of every dipolar source of the cortical surface on each iEEG contact. This iEEG forward model was applied to MEG sources to estimate iEEG potentials that would have been generated by these sources. MEG-estimated iEEG potentials were compared with measured iEEG potentials using four source localization methods: two variants of MEM and two standard methods equivalent to minimum norm and LORETA estimates. Our results demonstrated an excellent MEG/iEEG correspondence in the presumed focus for four out of five patients. In one patient, the deep generator identified in iEEG could not be localized in MEG. MEG-estimated iEEG potentials is a promising method to evaluate which MEG sources could be retrieved and validated with iEEG data, providing accurate results especially when applied to MEM localizations. Hum Brain Mapp 37:1661-1683, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Comparing multilayer brain networks between groups: Introducing graph metrics and recommendations.

PubMed

Mandke, Kanad; Meier, Jil; Brookes, Matthew J; O'Dea, Reuben D; Van Mieghem, Piet; Stam, Cornelis J; Hillebrand, Arjan; Tewarie, Prejaas

2018-02-01

There is an increasing awareness of the advantages of multi-modal neuroimaging. Networks obtained from different modalities are usually treated in isolation, which is however contradictory to accumulating evidence that these networks show non-trivial interdependencies. Even networks obtained from a single modality, such as frequency-band specific functional networks measured from magnetoencephalography (MEG) are often treated independently. Here, we discuss how a multilayer network framework allows for integration of multiple networks into a single network description and how graph metrics can be applied to quantify multilayer network organisation for group comparison. We analyse how well-known biases for single layer networks, such as effects of group differences in link density and/or average connectivity, influence multilayer networks, and we compare four schemes that aim to correct for such biases: the minimum spanning tree (MST), effective graph resistance cost minimisation, efficiency cost optimisation (ECO) and a normalisation scheme based on singular value decomposition (SVD). These schemes can be applied to the layers independently or to the multilayer network as a whole. For correction applied to whole multilayer networks, only the SVD showed sufficient bias correction. For correction applied to individual layers, three schemes (ECO, MST, SVD) could correct for biases. By using generative models as well as empirical MEG and functional magnetic resonance imaging (fMRI) data, we further demonstrated that all schemes were sensitive to identify network topology when the original networks were perturbed. In conclusion, uncorrected multilayer network analysis leads to biases. These biases may differ between centres and studies and could consequently lead to unreproducible results in a similar manner as for single layer networks. We therefore recommend using correction schemes prior to multilayer network analysis for group comparisons. Copyright © 2017 Elsevier Inc. All rights reserved.

Technical solutions for simultaneous MEG and SEEG recordings: towards routine clinical use.

PubMed

Badier, J M; Dubarry, A S; Gavaret, M; Chen, S; Trébuchon, A S; Marquis, P; Régis, J; Bartolomei, F; Bénar, C G; Carron, R

2017-09-21

The simultaneous recording of intracerebral EEG (stereotaxic EEG, SEEG) and magnetoencephalography (MEG) is a promising strategy that provides both local and global views on brain pathological activity. Yet, acquiring simultaneous signals poses difficult technical issues that hamper their use in clinical routine. Our objective was thus to develop a set of solutions for recording a high number of SEEG channels while preserving signal quality. We recorded data in a patient with drug resistant epilepsy during presurgical evaluation. We used dedicated insertion screws and optically insulated amplifiers. We recorded 137 SEEG contacts on 10 depth electrodes (5-15 contacts each) and 248 MEG channels (magnetometers). Signal quality was assessed by comparing the distribution of RMS values in different frequency bands to a reference set of MEG acquisitions. The quality of signals was excellent for both MEG and SEEG; for MEG, it was comparable to that of MEG signals without concurrent SEEG. Discharges involving several structures on SEEG were visible on MEG, whereas discharges limited in space were not seen at the surface. SEEG can now be recorded simultaneously with whole-head MEG in routine. This opens new avenues, both methodologically for understanding signals and improving signal processing methods, and clinically for future combined analyses.

Good practice for conducting and reporting MEG research

PubMed Central

Gross, Joachim; Baillet, Sylvain; Barnes, Gareth R.; Henson, Richard N.; Hillebrand, Arjan; Jensen, Ole; Jerbi, Karim; Litvak, Vladimir; Maess, Burkhard; Oostenveld, Robert; Parkkonen, Lauri; Taylor, Jason R.; van Wassenhove, Virginie; Wibral, Michael; Schoffelen, Jan-Mathijs

2013-01-01

Magnetoencephalographic (MEG) recordings are a rich source of information about the neural dynamics underlying cognitive processes in the brain, with excellent temporal and good spatial resolution. In recent years there have been considerable advances in MEG hardware developments and methods. Sophisticated analysis techniques are now routinely applied and continuously improved, leading to fascinating insights into the intricate dynamics of neural processes. However, the rapidly increasing level of complexity of the different steps in a MEG study make it difficult for novices, and sometimes even for experts, to stay aware of possible limitations and caveats. Furthermore, the complexity of MEG data acquisition and data analysis requires special attention when describing MEG studies in publications, in order to facilitate interpretation and reproduction of the results. This manuscript aims at making recommendations for a number of important data acquisition and data analysis steps and suggests details that should be specified in manuscripts reporting MEG studies. These recommendations will hopefully serve as guidelines that help to strengthen the position of the MEG research community within the field of neuroscience, and may foster discussion in order to further enhance the quality and impact of MEG research. PMID:23046981

MEG3 is a prognostic factor for CRC and promotes chemosensitivity by enhancing oxaliplatin-induced cell apoptosis.

PubMed

Li, Lixia; Shang, Jian; Zhang, Yupeng; Liu, Shi; Peng, Yanan; Zhou, Zhou; Pan, Huaqing; Wang, Xiaobing; Chen, Lipng; Zhao, Qiu

2017-09-01

A major reason for the failure of advanced colorectal cancer (CRC) treatment is the occurrence of chemoresistance to oxaliplatin-based chemotherapy. Recently, studies have shown that long non-coding RNAs (lncRNAs) play an important role in drug resistance. Using HiSeq sequencing methods, we identified that lncRNAs show differential expression levels in oxaliplatin-resistant (OxR) and non-resistant CRC patients. RT-qPCR was then performed in tissues and serum samples, and lncRNA MEG3 was verified to be downregulated in non-responding patients and to have considerable discriminating potential to identify responding patients from non-responding patients. Moreover, decreased serum MEG3 expression was associated with poor chemoresponse and low survival rate in CRC patients receiving oxaliplatin treatment. Subsequently, OxR cell lines were established, and MEG3 was significantly downregulated in HT29 OxR and SW480 OxR cells. In addition, overexpression of MEG3 with pMEG3 reversed oxaliplatin resistance in both CRC cell lines. Flow cytometric apoptosis analysis indicated that MEG3 promoted CRC cell apoptosis. More importantly, MEG3 enhanced oxaliplatin‑induced cell cytotoxicity in CRC. In conclusion, our integrated approach demonstrated that decreased expression of lncRNA MEG3 in CRC confers potent poor therapeutic efficacy, and that MEG3 promotes chemosensitivity by enhancing oxaliplatin-induced cell apoptosis. Thus, overexpression of MEG3 may be a future direction by which to develop a novel therapeutic strategy to overcome oxaliplatin resistance of CRC patients.

How to Build a Functional Connectomic Biomarker for Mild Cognitive Impairment From Source Reconstructed MEG Resting-State Activity: The Combination of ROI Representation and Connectivity Estimator Matters.

PubMed

Dimitriadis, Stavros I; López, María E; Bruña, Ricardo; Cuesta, Pablo; Marcos, Alberto; Maestú, Fernando; Pereda, Ernesto

2018-01-01

Our work aimed to demonstrate the combination of machine learning and graph theory for the designing of a connectomic biomarker for mild cognitive impairment (MCI) subjects using eyes-closed neuromagnetic recordings. The whole analysis based on source-reconstructed neuromagnetic activity. As ROI representation, we employed the principal component analysis (PCA) and centroid approaches. As representative bi-variate connectivity estimators for the estimation of intra and cross-frequency interactions, we adopted the phase locking value (PLV), the imaginary part (iPLV) and the correlation of the envelope (CorrEnv). Both intra and cross-frequency interactions (CFC) have been estimated with the three connectivity estimators within the seven frequency bands (intra-frequency) and in pairs (CFC), correspondingly. We demonstrated how different versions of functional connectivity graphs single-layer (SL-FCG) and multi-layer (ML-FCG) can give us a different view of the functional interactions across the brain areas. Finally, we applied machine learning techniques with main scope to build a reliable connectomic biomarker by analyzing both SL-FCG and ML-FCG in two different options: as a whole unit using a tensorial extraction algorithm and as single pair-wise coupling estimations. We concluded that edge-weighed feature selection strategy outperformed the tensorial treatment of SL-FCG and ML-FCG. The highest classification performance was obtained with the centroid ROI representation and edge-weighted analysis of the SL-FCG reaching the 98% for the CorrEnv in α 1 :α 2 and 94% for the iPLV in α 2 . Classification performance based on the multi-layer participation coefficient, a multiplexity index reached 52% for iPLV and 52% for CorrEnv. Selected functional connections that build the multivariate connectomic biomarker in the edge-weighted scenario are located in default-mode, fronto-parietal, and cingulo-opercular network. Our analysis supports the notion of analyzing FCG simultaneously in intra and cross-frequency whole brain interactions with various connectivity estimators in beamformed recordings.

Integration of a Cryocooler into a SQUID Magnetospinography System for Reduction of Liquid Helium Consumption

NASA Astrophysics Data System (ADS)

Adachi, Yoshiaki; Oyama, Daisuke; Kawai, Jun; Ogata, Hisanao; Uehara, Gen

We are currently developing a magnetospinography (MSG) system for noninvasive functional imaging of the spinal cord. The MSG system is a device for observing a weak magnetic field accompanied by the neural activity of the spinal cord by using an array of low-temperature superconducting quantum interference device (SQUID) magnetic flux sensors. As in the case of other biomagnetic measurement systems such as the magnetoencephalography (MEG) system, the running cost of the MSG system is mainly dependent on the liquid helium (LHe) consumption of a dewar vessel. We integrated a cryocooler into the MSG system to reduce LHe consumption. A pulse tube cryocooler with a cooling power of 0.5Wat 4 K was placed adjacent to a magnetically shielded room and was directly connected to the thermal radiation shield of the dewar by an electrically isolated transfer tube. Cold helium gas was circulated between the cryocooler and the radiation shield. Consequently, the temperature of the radiation shield decreased below 40 K. Previous studies have shown that the detection of a weak magnetic field is often hindered by severe low-frequency band noise from the cryocooler. However, the band of the MSG signals is much higher than that of the cryocooler noise. Therefore, the noise can be filtered out and has a less detrimental effect on MSG measurement than on other biomagnetic field measurements such as MEG measurement. As a result, LHe consumption was reduced by 46%, with no increase in the noise floor.

Elevating Endogenous GABA Levels with GAT-1 Blockade Modulates Evoked but Not Induced Responses in Human Visual Cortex

PubMed Central

Muthukumaraswamy, Suresh D; Myers, Jim F M; Wilson, Sue J; Nutt, David J; Hamandi, Khalid; Lingford-Hughes, Anne; Singh, Krish D

2013-01-01

The electroencephalographic/magnetoencephalographic (EEG/MEG) signal is generated primarily by the summation of the postsynaptic currents of cortical principal cells. At a microcircuit level, these glutamatergic principal cells are reciprocally connected to GABAergic interneurons. Here we investigated the relative sensitivity of visual evoked and induced responses to altered levels of endogenous GABAergic inhibition. To do this, we pharmacologically manipulated the GABA system using tiagabine, which blocks the synaptic GABA transporter 1, and so increases endogenous GABA levels. In a single-blinded and placebo-controlled crossover study of 15 healthy participants, we administered either 15 mg of tiagabine or a placebo. We recorded whole-head MEG, while participants viewed a visual grating stimulus, before, 1, 3 and 5 h post tiagabine ingestion. Using beamformer source localization, we reconstructed responses from early visual cortices. Our results showed no change in either stimulus-induced gamma-band amplitude increases or stimulus-induced alpha amplitude decreases. However, the same data showed a 45% reduction in the evoked response component at ∼80 ms. These data demonstrate that, in early visual cortex the evoked response shows a greater sensitivity compared with induced oscillations to pharmacologically increased endogenous GABA levels. We suggest that previous studies correlating GABA concentrations as measured by magnetic resonance spectroscopy to gamma oscillation frequency may reflect underlying variations such as interneuron/inhibitory synapse density rather than functional synaptic GABA concentrations. PMID:23361120

5S rRNA-derived and tRNA-derived SINEs in fruit bats.

PubMed

Gogolevsky, Konstantin P; Vassetzky, Nikita S; Kramerov, Dmitri A

2009-05-01

Most short retroposons (SINEs) descend from cellular tRNA of 7SL RNA. Here, four new SINEs were found in megabats (Megachiroptera) but neither in microbats nor in other mammals. Two of them, MEG-RS and MEG-RL, descend from another cellular RNA, 5S rRNA; one (MEG-T2) is a tRNA-derived SINE; and MEG-TR is a hybrid tRNA/5S rRNA SINE. Insertion locus analysis suggests that these SINEs were active in the recent fruit bat evolution. Analysis of MEG-RS and MEG-RL in comparison with other few 5S rRNA-derived SINEs demonstrates that the internal RNA polymerase III promoter is their most invariant region, while the secondary structure is more variable. The mechanisms underlying the modular structure of these and other SINEs as well as their variation are discussed. The scenario of evolution of MEG SINEs is proposed.

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies.

PubMed

Puce, Aina; Hämäläinen, Matti S

2017-05-31

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed.

Synthesis, bioactivity, 3D-QSAR studies of novel dibenzofuran derivatives as PTP-MEG2 inhibitors

PubMed Central

Zhang, Yu-Ze; Jin, Wen-Yan; Li, Hong-Lian; Zhou, Hui; Cheng, Xian-Chao; Wang, Run-Ling

2017-01-01

PTP-MEG2 plays a critical role in the diverse cell signalling processes, so targeting PTP-MEG2 is a promising strategy for various human diseases treatments. In this study, a series of novel dibenzofuran derivatives was synthesized and assayed for their PTP-MEG2 inhibitory activities. 10a with highest inhibitory activity (320 nM) exhibited significant selectivity for PTP-MEG2 over its close homolog SHP2, CDC25 (IC50 > 50 μM). By means of the powerful “HipHop” technique, a 3D-QSAR study was carried out to explore structure activity relationship of these molecules. The generated pharmacophore model revealed that the one RA, three Hyd, and two HBA features play an important role in binding to the active site of the target protein-PTP-MEG2. Docking simulation study indicated that 10a achieved its potency and specificity for PTP-MEG2 by targeting unique nearby peripheral binding pockets and the active site. The absorption, distribution, metabolism and excretion (ADME) predictions showed that the 11 compounds hold high potential to be novel lead compounds for targeting PTP-MEG2. Our findings here can provide a new strategy or useful insights for designing the effective PTP-MEG2 inhibitors. PMID:28388567

Long non-coding RNA MEG3 inhibits the proliferation and metastasis of oral squamous cell carcinoma by regulating the WNT/β-catenin signaling pathway.

PubMed

Liu, Zongxiang; Wu, Cui; Xie, Nina; Wang, Penglai

2017-10-01

This study aimed to investigate how long non-coding RNA (lncRNA) maternally expressed gene 3 (MEG3) inhibits the growth and metastasis of oral squamous cell carcinoma (OSCC) by regulating WNT/β-catenin signaling pathway in order to explore the antitumor effect of MEG3 and to provide a potential molecular target for the treatment of OSCC. The RT-qPCR technique was used to quantitatively analyze the expression of MEG3 in cancer and adjacent tissues collected from the patients after surgery. Using the Lipofectamine method, the MEG3 overexpression vector and the siRNA interference vector were constructed and transfected into SCC15 and Cal27 cells, respectively, followed by cell proliferation, apoptosis and metastasis analyses. The semi-quantitative analysis of the expression of the β-catenin protein in transfected cells was performed by the western blot analysis, and the activity of the WNT/β-catenin signaling pathway was analyzed using the TOP/FOP flash reporters. In addition, the cells were treated with decitabine to investigate the correlation between the MEG3 expression and the DNA methylation. Results showed that the expression level of MEG3 was significantly decreased in OSCC (p<0.05) and overexpression of MEG3 inhibited the proliferation and metastasis of cancer cells and promoted apoptosis. Importantly, MEG3 played a role as a tumor suppressor by inhibiting the WNT/β-catenin signaling pathway. In addition, the expression of the MEG3 was significantly affected by the degree of DNA methylation. It was concluded that the lncRNA MEG3 can inhibit the growth and metastasis of OSCC by negatively regulating the WNT/β-catenin signaling pathway.

In silico design of a DNA-based HIV-1 multi-epitope vaccine for Chinese populations

PubMed Central

Yang, Yi; Sun, Weilai; Guo, Jingjing; Zhao, Guangyu; Sun, Shihui; Yu, Hong; Guo, Yan; Li, Jungfeng; Jin, Xia; Du, Lanying; Jiang, Shibo; Kou, Zhihua; Zhou, Yusen

2015-01-01

The development of an HIV-1 vaccine that is capable of inducing effective and broadly cross-reactive humoral and cellular immune responses remains a challenging task because of the extensive diversity of HIV-1, the difference of virus subtypes (clades) in different geographical regions, and the polymorphism of human leukocyte antigens (HLA). We performed an in silico design of 3 DNA vaccines, designated pJW4303-MEG1, pJW4303-MEG2 and pJW4303-MEG3, encoding multi-epitopes that are highly conserved within the HIV-1 subtypes most prevalent in China and can be recognized through HLA alleles dominant in China. The pJW4303-MEG1-encoded protein consisted of one Th epitope in Env, and one, 2, and 6 epitopes in Pol, Env, and Gag proteins, respectively, with a GGGS linker sequence between epitopes. The pJW4303-MEG2-encoded protein contained similar epitopes in a different order, but with the same linker as pJW4303-MEG1. The pJW4303-MEG3-encoded protein contained the same epitopes in the same order as that of pJW4303-MEG2, but with a different linker sequence (AAY). To evaluate immunogenicity, mice were immunized intramuscularly with these DNA vaccines. Both pJW4303-MEG1 and pJW4303-MEG2 vaccines induced equally potent humoral and cellular immune responses in the vaccinated mice, while pJW4303-MEG3 did not induce immune responses. These results indicate that both epitope and linker sequences are important in designing effective epitope-based vaccines against HIV-1 and other viruses. PMID:25839222

Multimodal imaging of spike propagation: a technical case report.

PubMed

Tanaka, N; Grant, P E; Suzuki, N; Madsen, J R; Bergin, A M; Hämäläinen, M S; Stufflebeam, S M

2012-06-01

We report an 11-year-old boy with intractable epilepsy, who had cortical dysplasia in the right superior frontal gyrus. Spatiotemporal source analysis of MEG and EEG spikes demonstrated a similar time course of spike propagation from the superior to inferior frontal gyri, as observed on intracranial EEG. The tractography reconstructed from DTI showed a fiber connection between these areas. Our multimodal approach demonstrates spike propagation and a white matter tract guiding the propagation.

On the Potential of a New Generation of Magnetometers for MEG: A Beamformer Simulation Study

PubMed Central

Boto, Elena; Bowtell, Richard; Krüger, Peter; Fromhold, T. Mark; Morris, Peter G.; Meyer, Sofie S.; Barnes, Gareth R.; Brookes, Matthew J.

2016-01-01

Magnetoencephalography (MEG) is a sophisticated tool which yields rich information on the spatial, spectral and temporal signatures of human brain function. Despite unique potential, MEG is limited by a low signal-to-noise ratio (SNR) which is caused by both the inherently small magnetic fields generated by the brain, and the scalp-to-sensor distance. The latter is limited in current systems due to a requirement for pickup coils to be cryogenically cooled. Recent work suggests that optically-pumped magnetometers (OPMs) might be a viable alternative to superconducting detectors for MEG measurement. They have the advantage that sensors can be brought to within ~4 mm of the scalp, thus offering increased sensitivity. Here, using simulations, we quantify the advantages of hypothetical OPM systems in terms of sensitivity, reconstruction accuracy and spatial resolution. Our results show that a multi-channel whole-head OPM system offers (on average) a fivefold improvement in sensitivity for an adult brain, as well as clear improvements in reconstruction accuracy and spatial resolution. However, we also show that such improvements depend critically on accurate forward models; indeed, the reconstruction accuracy of our simulated OPM system only outperformed that of a simulated superconducting system in cases where forward field error was less than 5%. Overall, our results imply that the realisation of a viable whole-head multi-channel OPM system could generate a step change in the utility of MEG as a means to assess brain electrophysiological activity in health and disease. However in practice, this will require both improved hardware and modelling algorithms. PMID:27564416

Source counting in MEG neuroimaging

NASA Astrophysics Data System (ADS)

Lei, Tianhu; Dell, John; Magee, Ralphy; Roberts, Timothy P. L.

2009-02-01

Magnetoencephalography (MEG) is a multi-channel, functional imaging technique. It measures the magnetic field produced by the primary electric currents inside the brain via a sensor array composed of a large number of superconducting quantum interference devices. The measurements are then used to estimate the locations, strengths, and orientations of these electric currents. This magnetic source imaging technique encompasses a great variety of signal processing and modeling techniques which include Inverse problem, MUltiple SIgnal Classification (MUSIC), Beamforming (BF), and Independent Component Analysis (ICA) method. A key problem with Inverse problem, MUSIC and ICA methods is that the number of sources must be detected a priori. Although BF method scans the source space on a point-to-point basis, the selection of peaks as sources, however, is finally made by subjective thresholding. In practice expert data analysts often select results based on physiological plausibility. This paper presents an eigenstructure approach for the source number detection in MEG neuroimaging. By sorting eigenvalues of the estimated covariance matrix of the acquired MEG data, the measured data space is partitioned into the signal and noise subspaces. The partition is implemented by utilizing information theoretic criteria. The order of the signal subspace gives an estimate of the number of sources. The approach does not refer to any model or hypothesis, hence, is an entirely data-led operation. It possesses clear physical interpretation and efficient computation procedure. The theoretical derivation of this method and the results obtained by using the real MEG data are included to demonstrates their agreement and the promise of the proposed approach.

Voxel-wise resting-state MEG source magnitude imaging study reveals neurocircuitry abnormality in active-duty service members and veterans with PTSD

PubMed Central

Huang, Ming-Xiong; Yurgil, Kate A.; Robb, Ashley; Angeles, Annemarie; Diwakar, Mithun; Risbrough, Victoria B.; Nichols, Sharon L.; McLay, Robert; Theilmann, Rebecca J.; Song, Tao; Huang, Charles W.; Lee, Roland R.; Baker, Dewleen G.

2014-01-01

Post-traumatic stress disorder (PTSD) is a leading cause of sustained impairment, distress, and poor quality of life in military personnel, veterans, and civilians. Indirect functional neuroimaging studies using PET or fMRI with fear-related stimuli support a PTSD neurocircuitry model that includes amygdala, hippocampus, and ventromedial prefrontal cortex (vmPFC). However, it is not clear if this model can fully account for PTSD abnormalities detected directly by electromagnetic-based source imaging techniques in resting-state. The present study examined resting-state magnetoencephalography (MEG) signals in 25 active-duty service members and veterans with PTSD and 30 healthy volunteers. In contrast to the healthy volunteers, individuals with PTSD showed: 1) hyperactivity from amygdala, hippocampus, posterolateral orbitofrontal cortex (OFC), dorsomedial prefrontal cortex (dmPFC), and insular cortex in high-frequency (i.e., beta, gamma, and high-gamma) bands; 2) hypoactivity from vmPFC, Frontal Pole (FP), and dorsolateral prefrontal cortex (dlPFC) in high-frequency bands; 3) extensive hypoactivity from dlPFC, FP, anterior temporal lobes, precuneous cortex, and sensorimotor cortex in alpha and low-frequency bands; and 4) in individuals with PTSD, MEG activity in the left amygdala and posterolateral OFC correlated positively with PTSD symptom scores, whereas MEG activity in vmPFC and precuneous correlated negatively with symptom score. The present study showed that MEG source imaging technique revealed new abnormalities in the resting-state electromagnetic signals from the PTSD neurocircuitry. Particularly, posterolateral OFC and precuneous may play important roles in the PTSD neurocircuitry model. PMID:25180160

MEG biomarker of Alzheimer's disease: Absence of a prefrontal generator during auditory sensory gating.

PubMed

Josef Golubic, Sanja; Aine, Cheryl J; Stephen, Julia M; Adair, John C; Knoefel, Janice E; Supek, Selma

2017-10-01

Magnetoencephalography (MEG), a direct measure of neuronal activity, is an underexplored tool in the search for biomarkers of Alzheimer's disease (AD). In this study, we used MEG source estimates of auditory gating generators, nonlinear correlations with neuropsychological results, and multivariate analyses to examine the sensitivity and specificity of gating topology modulation to detect AD. Our results demonstrated the use of MEG localization of a medial prefrontal (mPFC) gating generator as a discrete (binary) detector of AD at the individual level and resulted in recategorizing the participant categories in: (1) controls with mPFC generator localized in response to both the standard and deviant tones; (2) a possible preclinical stage of AD participants (a lower functioning group of controls) in which mPFC activation was localized to the deviant tone only; and (3) symptomatic AD in which mPFC activation was not localized to either the deviant or standard tones. This approach showed a large effect size (0.9) and high accuracy, sensitivity, and specificity (100%) in identifying symptomatic AD patients within a limited research sample. The present results demonstrate high potential of mPFC activation as a noninvasive biomarker of AD pathology during putative preclinical and clinical stages. Hum Brain Mapp 38:5180-5194, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Spectral-Spatial Differentiation of Brain Activity During Mental Imagery of Improvisational Music Performance Using MEG.

PubMed

Boasen, Jared; Takeshita, Yuya; Kuriki, Shinya; Yokosawa, Koichi

2018-01-01

Group musical improvisation is thought to be akin to conversation, and therapeutically has been shown to be effective at improving communicativeness, sociability, creative expression, and overall psychological health. To understand these therapeutic effects, clarifying the nature of brain activity during improvisational cognition is important. Some insight regarding brain activity during improvisational music cognition has been gained via functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). However, we have found no reports based on magnetoencephalography (MEG). With the present study, we aimed to demonstrate the feasibility of improvisational music performance experimentation in MEG. We designed a novel MEG-compatible keyboard, and used it with experienced musicians ( N = 13) in a music performance paradigm to spectral-spatially differentiate spontaneous brain activity during mental imagery of improvisational music performance. Analyses of source activity revealed that mental imagery of improvisational music performance induced greater theta (5-7 Hz) activity in left temporal areas associated with rhythm production and communication, greater alpha (8-12 Hz) activity in left premotor and parietal areas associated with sensorimotor integration, and less beta (15-29 Hz) activity in right frontal areas associated with inhibition control. These findings support the notion that musical improvisation is conversational, and suggest that creation of novel auditory content is facilitated by a more internally-directed, disinhibited cognitive state.

The magnetic lead field theorem in the quasi-static approximation and its use for magnetoencephalography forward calculation in realistic volume conductors.

PubMed

Nolte, Guido

2003-11-21

The equation for the magnetic lead field for a given magnetoencephalography (MEG) channel is well known for arbitrary frequencies omega but is not directly applicable to MEG in the quasi-static approximation. In this paper we derive an equation for omega = 0 starting from the very definition of the lead field instead of using Helmholtz's reciprocity theorems. The results are (a) the transpose of the conductivity times the lead field is divergence-free, and (b) the lead field differs from the one in any other volume conductor by a gradient of a scalar function. Consequently, for a piecewise homogeneous and isotropic volume conductor, the lead field is always tangential at the outermost surface. Based on this theoretical result, we formulated a simple and fast method for the MEG forward calculation for one shell of arbitrary shape: we correct the corresponding lead field for a spherical volume conductor by a superposition of basis functions, gradients of harmonic functions constructed here from spherical harmonics, with coefficients fitted to the boundary conditions. The algorithm was tested for a prolate spheroid of realistic shape for which the analytical solution is known. For high order in the expansion, we found the solutions to be essentially exact and for reasonable accuracies much fewer multiplications are needed than in typical implementations of the boundary element methods. The generalization to more shells is straightforward.

Lexical mediation of phonotactic frequency effects on spoken word recognition: A Granger causality analysis of MRI-constrained MEG/EEG data.

PubMed

Gow, David W; Olson, Bruna B

2015-07-01

Phonotactic frequency effects play a crucial role in a number of debates over language processing and representation. It is unclear however, whether these effects reflect prelexical sensitivity to phonotactic frequency, or lexical "gang effects" in speech perception. In this paper, we use Granger causality analysis of MR-constrained MEG/EEG data to understand how phonotactic frequency influences neural processing dynamics during auditory lexical decision. Effective connectivity analysis showed weaker feedforward influence from brain regions involved in acoustic-phonetic processing (superior temporal gyrus) to lexical areas (supramarginal gyrus) for high phonotactic frequency words, but stronger top-down lexical influence for the same items. Low entropy nonwords (nonwords judged to closely resemble real words) showed a similar pattern of interactions between brain regions involved in lexical and acoustic-phonetic processing. These results contradict the predictions of a feedforward model of phonotactic frequency facilitation, but support the predictions of a lexically mediated account.

Lexical mediation of phonotactic frequency effects on spoken word recognition: A Granger causality analysis of MRI-constrained MEG/EEG data

PubMed Central

Gow, David W.; Olson, Bruna B.

2015-01-01

Phonotactic frequency effects play a crucial role in a number of debates over language processing and representation. It is unclear however, whether these effects reflect prelexical sensitivity to phonotactic frequency, or lexical “gang effects” in speech perception. In this paper, we use Granger causality analysis of MR-constrained MEG/EEG data to understand how phonotactic frequency influences neural processing dynamics during auditory lexical decision. Effective connectivity analysis showed weaker feedforward influence from brain regions involved in acoustic-phonetic processing (superior temporal gyrus) to lexical areas (supramarginal gyrus) for high phonotactic frequency words, but stronger top-down lexical influence for the same items. Low entropy nonwords (nonwords judged to closely resemble real words) showed a similar pattern of interactions between brain regions involved in lexical and acoustic-phonetic processing. These results contradict the predictions of a feedforward model of phonotactic frequency facilitation, but support the predictions of a lexically mediated account. PMID:25883413

Magnetoencephalography and normal pressure hydrocephalus: A case report.

PubMed

Kotini, A; Birbilis, T; Anninos, P; Seimenis, I

2018-04-18

A 82-year-old male experiencing headaches, dementia, urinary incontinence and gait instability was diagnosed with normal pressure hydrocephalus (NPH) and underwent a resting state magnetoencephalography (MEG) examination. MEG data were recorded in a magnetically shielded room with a whole-head 122 channel biomagnetometer. Following MEG, a ventriculoperitoneal (VP) shunt was placed in his head and greatly improved his symptomatology. Spontaneous MEG recordings revealed lower magnetic fields at frontal and frontotemporal regions compared to central and posterior regions. This finding correlated well with the significant ventricular distention, and specifically the enlargement of the frontal horns of the lateral ventricles, observed in presurgical CT. The regional pattern of MEG signal decrease in NPH seems to be quite different from that encountered in brain atrophy. In the latter case, a more generalized distribution of low magnetic fields is observed, possibly reflecting the high sensitivity of MEG to activity originating in sulci. Acquired data suggest that MEG may be able to differentiate between NPH and brain atrophy. Furthermore, MEG could potentially constitute a non-invasive, non-imaging tool, useful in the selection of patients with NPH to undergo shunt surgery. The findings of this study warrant further research in patient groups before firm conclusions can be drawn.

A Review of Issues Related to Data Acquisition and Analysis in EEG/MEG Studies

PubMed Central

Puce, Aina; Hämäläinen, Matti S.

2017-01-01

Electroencephalography (EEG) and magnetoencephalography (MEG) are non-invasive electrophysiological methods, which record electric potentials and magnetic fields due to electric currents in synchronously-active neurons. With MEG being more sensitive to neural activity from tangential currents and EEG being able to detect both radial and tangential sources, the two methods are complementary. Over the years, neurophysiological studies have changed considerably: high-density recordings are becoming de rigueur; there is interest in both spontaneous and evoked activity; and sophisticated artifact detection and removal methods are available. Improved head models for source estimation have also increased the precision of the current estimates, particularly for EEG and combined EEG/MEG. Because of their complementarity, more investigators are beginning to perform simultaneous EEG/MEG studies to gain more complete information about neural activity. Given the increase in methodological complexity in EEG/MEG, it is important to gather data that are of high quality and that are as artifact free as possible. Here, we discuss some issues in data acquisition and analysis of EEG and MEG data. Practical considerations for different types of EEG and MEG studies are also discussed. PMID:28561761

Boosting specificity of MEG artifact removal by weighted support vector machine.

PubMed

Duan, Fang; Phothisonothai, Montri; Kikuchi, Mitsuru; Yoshimura, Yuko; Minabe, Yoshio; Watanabe, Kastumi; Aihara, Kazuyuki

2013-01-01

An automatic artifact removal method of magnetoencephalogram (MEG) was presented in this paper. The method proposed is based on independent components analysis (ICA) and support vector machine (SVM). However, different from the previous studies, in this paper we consider two factors which would influence the performance. First, the imbalance factor of independent components (ICs) of MEG is handled by weighted SVM. Second, instead of simply setting a fixed weight to each class, a re-weighting scheme is used for the preservation of useful MEG ICs. Experimental results on manually marked MEG dataset showed that the method proposed could correctly distinguish the artifacts from the MEG ICs. Meanwhile, 99.72% ± 0.67 of MEG ICs were preserved. The classification accuracy was 97.91% ± 1.39. In addition, it was found that this method was not sensitive to individual differences. The cross validation (leave-one-subject-out) results showed an averaged accuracy of 97.41% ± 2.14.

Evidence for shear-mediated Ca2+ entry through mechanosensitive cation channels in human platelets and a megakaryocytic cell line.

PubMed

Ilkan, Zeki; Wright, Joy R; Goodall, Alison H; Gibbins, Jonathan M; Jones, Chris I; Mahaut-Smith, Martyn P

2017-06-02

The role of mechanosensitive (MS) Ca 2+ -permeable ion channels in platelets is unclear, despite the importance of shear stress in platelet function and life-threatening thrombus formation. We therefore sought to investigate the expression and functional relevance of MS channels in human platelets. The effect of shear stress on Ca 2+ entry in human platelets and Meg-01 megakaryocytic cells loaded with Fluo-3 was examined by confocal microscopy. Cells were attached to glass coverslips within flow chambers that allowed applications of physiological and pathological shear stress. Arterial shear (1002.6 s -1 ) induced a sustained increase in [Ca 2+ ] i in Meg-01 cells and enhanced the frequency of repetitive Ca 2+ transients by 80% in platelets. These Ca 2+ increases were abrogated by the MS channel inhibitor Grammostola spatulata mechanotoxin 4 (GsMTx-4) or by chelation of extracellular Ca 2+ Thrombus formation was studied on collagen-coated surfaces using DiOC 6 -stained platelets. In addition, [Ca 2+ ] i and functional responses of washed platelet suspensions were studied with Fura-2 and light transmission aggregometry, respectively. Thrombus size was reduced 50% by GsMTx-4, independently of P2X1 receptors. In contrast, GsMTx-4 had no effect on collagen-induced aggregation or on Ca 2+ influx via TRPC6 or Orai1 channels and caused only a minor inhibition of P2X1-dependent Ca 2+ entry. The Piezo1 agonist, Yoda1, potentiated shear-dependent platelet Ca 2+ transients by 170%. Piezo1 mRNA transcripts and protein were detected with quantitative RT-PCR and Western blotting, respectively, in both platelets and Meg-01 cells. We conclude that platelets and Meg-01 cells express the MS cation channel Piezo1, which may contribute to Ca 2+ entry and thrombus formation under arterial shear. © 2017 by The American Society for Biochemistry and Molecular Biology, Inc.

Frequency-phase analysis of resting-state functional MRI

PubMed Central

Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert

2017-01-01

We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522

Early visual analysis tool using magnetoencephalography for treatment and recovery of neuronal dysfunction.

PubMed

Rasheed, Waqas; Neoh, Yee Yik; Bin Hamid, Nor Hisham; Reza, Faruque; Idris, Zamzuri; Tang, Tong Boon

2017-10-01

Functional neuroimaging modalities play an important role in deciding the diagnosis and course of treatment of neuronal dysfunction and degeneration. This article presents an analytical tool with visualization by exploiting the strengths of the MEG (magnetoencephalographic) neuroimaging technique. The tool automates MEG data import (in tSSS format), channel information extraction, time/frequency decomposition, and circular graph visualization (connectogram) for simple result inspection. For advanced users, the tool also provides magnitude squared coherence (MSC) values allowing personalized threshold levels, and the computation of default model from MEG data of control population. Default model obtained from healthy population data serves as a useful benchmark to diagnose and monitor neuronal recovery during treatment. The proposed tool further provides optional labels with international 10-10 system nomenclature in order to facilitate comparison studies with EEG (electroencephalography) sensor space. Potential applications in epilepsy and traumatic brain injury studies are also discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Direction of Magnetoencephalography Sources Associated with Feedback and Feedforward Contributions in a Visual Object Recognition Task

PubMed Central

Ahlfors, Seppo P.; Jones, Stephanie R.; Ahveninen, Jyrki; Hämäläinen, Matti S.; Belliveau, John W.; Bar, Moshe

2014-01-01

Identifying inter-area communication in terms of the hierarchical organization of functional brain areas is of considerable interest in human neuroimaging. Previous studies have suggested that the direction of magneto- and electroencephalography (MEG, EEG) source currents depends on the layer-specific input patterns into a cortical area. We examined the direction in MEG source currents in a visual object recognition experiment in which there were specific expectations of activation in the fusiform region being driven by either feedforward or feedback inputs. The source for the early non-specific visual evoked response, presumably corresponding to feedforward driven activity, pointed outward, i.e., away from the white matter. In contrast, the source for the later, object-recognition related signals, expected to be driven by feedback inputs, pointed inward, toward the white matter. Associating specific features of the MEG/EEG source waveforms to feedforward and feedback inputs could provide unique information about the activation patterns within hierarchically organized cortical areas. PMID:25445356

TopoToolbox: using sensor topography to calculate psychologically meaningful measures from event-related EEG/MEG.

PubMed

Tian, Xing; Poeppel, David; Huber, David E

2011-01-01

The open-source toolbox "TopoToolbox" is a suite of functions that use sensor topography to calculate psychologically meaningful measures (similarity, magnitude, and timing) from multisensor event-related EEG and MEG data. Using a GUI and data visualization, TopoToolbox can be used to calculate and test the topographic similarity between different conditions (Tian and Huber, 2008). This topographic similarity indicates whether different conditions involve a different distribution of underlying neural sources. Furthermore, this similarity calculation can be applied at different time points to discover when a response pattern emerges (Tian and Poeppel, 2010). Because the topographic patterns are obtained separately for each individual, these patterns are used to produce reliable measures of response magnitude that can be compared across individuals using conventional statistics (Davelaar et al. Submitted and Huber et al., 2008). TopoToolbox can be freely downloaded. It runs under MATLAB (The MathWorks, Inc.) and supports user-defined data structure as well as standard EEG/MEG data import using EEGLAB (Delorme and Makeig, 2004).

Sparsity enables estimation of both subcortical and cortical activity from MEG and EEG

PubMed Central

Krishnaswamy, Pavitra; Obregon-Henao, Gabriel; Ahveninen, Jyrki; Khan, Sheraz; Iglesias, Juan Eugenio; Hämäläinen, Matti S.; Purdon, Patrick L.

2017-01-01

Subcortical structures play a critical role in brain function. However, options for assessing electrophysiological activity in these structures are limited. Electromagnetic fields generated by neuronal activity in subcortical structures can be recorded noninvasively, using magnetoencephalography (MEG) and electroencephalography (EEG). However, these subcortical signals are much weaker than those generated by cortical activity. In addition, we show here that it is difficult to resolve subcortical sources because distributed cortical activity can explain the MEG and EEG patterns generated by deep sources. We then demonstrate that if the cortical activity is spatially sparse, both cortical and subcortical sources can be resolved with M/EEG. Building on this insight, we develop a hierarchical sparse inverse solution for M/EEG. We assess the performance of this algorithm on realistic simulations and auditory evoked response data, and show that thalamic and brainstem sources can be correctly estimated in the presence of cortical activity. Our work provides alternative perspectives and tools for characterizing electrophysiological activity in subcortical structures in the human brain. PMID:29138310

Using EEG/MEG Data of Cognitive Processes in Brain-Computer Interfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gutierrez, David

2008-08-11

Brain-computer interfaces (BCIs) aim at providing a non-muscular channel for sending commands to the external world using electroencephalographic (EEG) and, more recently, magnetoencephalographic (MEG) measurements of the brain function. Most of the current implementations of BCIs rely on EEG/MEG data of motor activities as such neural processes are well characterized, while the use of data related to cognitive activities has been neglected due to its intrinsic complexity. However, cognitive data usually has larger amplitude, lasts longer and, in some cases, cognitive brain signals are easier to control at will than motor signals. This paper briefy reviews the use of EEG/MEGmore » data of cognitive processes in the implementation of BCIs. Specifically, this paper reviews some of the neuromechanisms, signal features, and processing methods involved. This paper also refers to some of the author's work in the area of detection and classifcation of cognitive signals for BCIs using variability enhancement, parametric modeling, and spatial fltering, as well as recent developments in BCI performance evaluation.« less

Early Prefrontal Brain Responses to the Hedonic Quality of Emotional Words – A Simultaneous EEG and MEG Study

PubMed Central

Keuper, Kati; Zwitserlood, Pienie; Rehbein, Maimu A.; Eden, Annuschka S.; Laeger, Inga; Junghöfer, Markus; Zwanzger, Peter; Dobel, Christian

2013-01-01

The hedonic meaning of words affects word recognition, as shown by behavioral, functional imaging, and event-related potential (ERP) studies. However, the spatiotemporal dynamics and cognitive functions behind are elusive, partly due to methodological limitations of previous studies. Here, we account for these difficulties by computing combined electro-magnetoencephalographic (EEG/MEG) source localization techniques. Participants covertly read emotionally high-arousing positive and negative nouns, while EEG and MEG were recorded simultaneously. Combined EEG/MEG current-density reconstructions for the P1 (80–120 ms), P2 (150–190 ms) and EPN component (200–300 ms) were computed using realistic individual head models, with a cortical constraint. Relative to negative words, the P1 to positive words predominantly involved language-related structures (left middle temporal and inferior frontal regions), and posterior structures related to directed attention (occipital and parietal regions). Effects shifted to the right hemisphere in the P2 component. By contrast, negative words received more activation in the P1 time-range only, recruiting prefrontal regions, including the anterior cingulate cortex (ACC). Effects in the EPN were not statistically significant. These findings show that different neuronal networks are active when positive versus negative words are processed. We account for these effects in terms of an “emotional tagging” of word forms during language acquisition. These tags then give rise to different processing strategies, including enhanced lexical processing of positive words and a very fast language-independent alert response to negative words. The valence-specific recruitment of different networks might underlie fast adaptive responses to both approach- and withdrawal-related stimuli, be they acquired or biological. PMID:23940642

Surface modification and multiple exciton generation studies of lead(II) sulfide nanoparticles

NASA Astrophysics Data System (ADS)

Zemke, Jennifer M.

2011-12-01

Solar energy is a green alternative to fossil fuels but solar technologies to date have been plagued by low conversion efficiencies and high input costs making solar power inaccessible to much of the developing world. Semiconductor nanoparticles (NPs) may provide a route to efficient, economical solar devices through a phenomenon called multiple exciton generation (MEG). Through MEG, semiconductor NPs use a high-energy input photon to create more than one exciton (electron-hole pair) per photon absorbed, thereby exhibiting large photoconversion efficiencies. While MEG has been studied in many NP systems, and we understand some of the factors that affect MEG, a rigorous analysis of the NP-ligand interface with respect to MEG is missing. This dissertation describes how the NP ligand shell directly affects MEG and subsequent charge carrier recombination. Chapter I describes the motivation for studying MEG with respect to NP surface chemistry. Chapter II provides an in-depth overview of the transient absorption experiment used to measure MEG in the NP samples. Chapter III highlights the effect of oleic acid and sodium 2, 3-dimercaptopropane sulfonate on MEG in PbS NPs. The differences in carrier recombination were accounted for by two differences between these ligands: the coordinating atom and/or the secondary structure of the ligand. Because of these hypotheses, experiments were designed to elucidate the origin of these effects by controlling the NP ligand shell. Chapter IV details a viable synthetic route to thiol and amine-capped PbS NPs using sodium 3-mercaptopropane sulfonate as an intermediate ligand. With the versatile ligand exchange described in Chapter IV, the MEG yield and carrier recombination was investigated for ligands with varying headgroups but the same secondary structure. The correlation of ligand donor atom to MEG is outlined in Chapter V. Finally, Chapter VI discusses the conclusions and future outlook of the research reported in this dissertation. This dissertation includes previously published and unpublished co-authored material.

Epileptogenic zone localization using magnetoencephalography predicts seizure freedom in epilepsy surgery

PubMed Central

Englot, Dario J.; Nagarajan, Srikantan S.; Imber, Brandon S.; Raygor, Kunal P.; Honma, Susanne M.; Mizuiri, Danielle; Mantle, Mary; Knowlton, Robert C.; Kirsch, Heidi E.; Chang, Edward F.

2015-01-01

Objective The efficacy of epilepsy surgery depends critically upon successful localization of the epileptogenic zone. Magnetoencephalography (MEG) enables non-invasive detection of interictal spike activity in epilepsy, which can then be localized in three dimensions using magnetic source imaging (MSI) techniques. However, the clinical value of MEG in the pre-surgical epilepsy evaluation is not fully understood, as studies to date are limited by either a lack of long-term seizure outcomes or small sample size. Methods We performed a retrospective cohort study of focal epilepsy patients who received MEG for interictal spike mapping followed by surgical resection at our institution. Results We studied 132 surgical patients, with mean post-operative follow-up of 3.6 years (minimum 1 year). Dipole source modelling was successful in 103 (78%) patients, while no interictal spikes were seen in others. Among patients with successful dipole modelling, MEG findings were concordant with and specific to: i) the region of resection in 66% of patients, ii) invasive electrocorticography (ECoG) findings in 67% of individuals, and iii) the MRI abnormality in 74% of cases. MEG showed discordant lateralization in ~5% of cases. After surgery, 70% of all patients achieved seizure-freedom (Engel class I outcome). Whereas 85% of patients with concordant and specific MEG findings became seizure-free, this outcome was achieved by only 37% of individuals with MEG findings that were non-specific or discordant with the region of resection (χ2 = 26.4, p < 0.001). MEG reliability was comparable in patients with or without localized scalp EEG, and overall, localizing MEG findings predicted seizure freedom with an odds ratio of 5.11 (2.23–11.8, 95% CI). Significance MEG is a valuable tool for non-invasive interictal spike mapping in epilepsy surgery, including patients with non-localized findings on long-term EEG monitoring, and localization of the epileptogenic zone using MEG is associated with improved seizure outcomes. PMID:25921215

Down-regulation of long non-coding RNA MEG3 indicates an unfavorable prognosis in non-small cell lung cancer: Evidence from the GEO database.

PubMed

Zhang, Zichao; Liu, Tiantian; Wang, Kai; Qu, Xiao; Pang, Zhaofei; Liu, Shaorui; Liu, Qi; Du, Jiajun

2017-09-30

Long non-coding RNA (lncRNA) MEG3 (maternally expressed gene 3) is an imprinted gene that suppresses cells growth in various tumors. However, the association between MEG3 expression and prognosis in non-small cell lung cancer (NSCLC) has not been fully investigated. Seven datasets with 1144 patients were obtained from Gene Expression Omnibus (GEO) database (Affymetrix U133 Plus 2.0 platform). Association between MEG3 and other variables was tested using the chi-squared test. Kaplan-Meier survival analysis was carried out to explore the association between MEG3 expression and overall survival (OS)/progression free survival (PFS). Results of univariate and multivariate Cox regression analysis were represented in HR and 95%CI form. Summarized results and publication bias were showed by forest plots and funnel plots respectively. Differential expression of MEG3 was related to stage (GSE31210OS and GSE31210PFS), histology (GSE29013OS and GSE29013PFS) and gender (GSE29013PFS). In summary, low MEG3 expression was associated with shorter long-term survival time in several datasets (GSE3141 (p=0.039), GSE30219 (p=0.008) for OS and GSE30219 (p=0.048) for PFS). We found that MEG3 was an independent prognostic factor in GSE30219 for PFS (HR 0.666, 95%CI 0.458-0.969, p=0.033). The summarized results suggested that low MEG3 expression was a poor prognostic factor in NSCLC (HR=0.77, 95%CI 0.63-0.95). Specifically, the association between low MEG3 expression and poor prognosis was markedly significant in younger patients (≤60years old) (HR0.602, 95%CI 0.417-0.867, p=0.007). These findings indicate that MEG3 could be a novel prognostic factor for NSCLC patients. Copyright © 2017 Elsevier B.V. All rights reserved.

Long noncoding RNA MEG3 mediated angiogenesis after cerebral infarction through regulating p53/NOX4 axis.

PubMed

Zhan, Renya; Xu, Kangli; Pan, Jianwei; Xu, Qingsheng; Xu, Shengjie; Shen, Jian

2017-08-26

This study aimed to explore the mechanism of lncRNA MEG3 on angiogenesis after cerebral infarction (CI). The rat brain microvascular endothelial cells (RBMVECs) isolated from rat was used to establish CI model, which were treated with oxygen-glucose deprivation/reoxygenation (OGD/R). The genes mRNA and protein expression levels in RBMVECs were determined by the quantitative real-time polymerase chain reaction (RT-qPCR) and western blot, respectively. The flow cytometry was used to measured cell apoptosis and intracellular reactive oxygen species (ROS) generation. The RBMVECs activities was detected by MTT method. The RNA-immunoprecipitation (RIP) assay was used to detect the interaction between MEG3 and p53, and the relationship between p53 and NOX4 was proved by chromatin co-immunoprecipitation (chip) assay. The results showed that OGD or OGD/R increased MEG3 and NOX4 expression, and there was positive correlation between MEG3 and NOX4 expression in RBMVECs. Next, knockdown of MEG3 indicated that inhibition of MEG3 was conducive to protect RBMVECs against OGD/R-induced apoptosis, with decreased NOX4 and p53 expression, further enhanced pro-angiogenic factors (HIF-1α and VEGF) expression, and reduced intracellular ROS generation. And then the RIP and CHIP assay demonstrated that MEG3 could interacted with p53 and regulated its expression, and p53 exerted significant binding in the promoters for NOX4, suggesting that MEG3 regulated NOX4 expression via p53. At last, knockdown of NOX4 indicated that inhibition of NOX4 protected RBMVECs against OGD/R-induced apoptosis, with increased cell viability and pro-angiogenic factors expression, and reduced ROS generation. LncRNA MEG3 was an important regulator in OGD/R induced-RBMVECs apoptosis and the mechanism of MEG3 on angiogenesis after CI was reduced ROS by p53/NOX4 axis. Copyright © 2017 Elsevier Inc. All rights reserved.

Information spreading by a combination of MEG source estimation and multivariate pattern classification.

PubMed

Sato, Masashi; Yamashita, Okito; Sato, Masa-Aki; Miyawaki, Yoichi

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of "information spreading" may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined.

Information spreading by a combination of MEG source estimation and multivariate pattern classification

PubMed Central

Sato, Masashi; Yamashita, Okito; Sato, Masa-aki

2018-01-01

To understand information representation in human brain activity, it is important to investigate its fine spatial patterns at high temporal resolution. One possible approach is to use source estimation of magnetoencephalography (MEG) signals. Previous studies have mainly quantified accuracy of this technique according to positional deviations and dispersion of estimated sources, but it remains unclear how accurately MEG source estimation restores information content represented by spatial patterns of brain activity. In this study, using simulated MEG signals representing artificial experimental conditions, we performed MEG source estimation and multivariate pattern analysis to examine whether MEG source estimation can restore information content represented by patterns of cortical current in source brain areas. Classification analysis revealed that the corresponding artificial experimental conditions were predicted accurately from patterns of cortical current estimated in the source brain areas. However, accurate predictions were also possible from brain areas whose original sources were not defined. Searchlight decoding further revealed that this unexpected prediction was possible across wide brain areas beyond the original source locations, indicating that information contained in the original sources can spread through MEG source estimation. This phenomenon of “information spreading” may easily lead to false-positive interpretations when MEG source estimation and classification analysis are combined to identify brain areas that represent target information. Real MEG data analyses also showed that presented stimuli were able to be predicted in the higher visual cortex at the same latency as in the primary visual cortex, also suggesting that information spreading took place. These results indicate that careful inspection is necessary to avoid false-positive interpretations when MEG source estimation and multivariate pattern analysis are combined. PMID:29912968

Acupuncture induces divergent alterations of functional connectivity within conventional frequency bands: evidence from MEG recordings.

PubMed

You, Youbo; Bai, Lijun; Dai, Ruwei; Zhong, Chongguang; Xue, Ting; Wang, Hu; Liu, Zhenyu; Wei, Wenjuan; Tian, Jie

2012-01-01

As an ancient Chinese healing modality which has gained increasing popularity in modern society, acupuncture involves stimulation with fine needles inserted into acupoints. Both traditional literature and clinical data indicated that modulation effects largely depend on specific designated acupoints. However, scientific representations of acupoint specificity remain controversial. In the present study, considering the new findings on the sustained effects of acupuncture and its time-varied temporal characteristics, we employed an electrophysiological imaging modality namely magnetoencephalography with a temporal resolution on the order of milliseconds. Taken into account the differential band-limited signal modulations induced by acupuncture, we sought to explore whether or not stimulation at Stomach Meridian 36 (ST36) and a nearby non-meridian point (NAP) would evoke divergent functional connectivity alterations within delta, theta, alpha, beta and gamma bands. Whole-head scanning was performed on 28 healthy participants during an eyes-closed no-task condition both preceding and following acupuncture. Data analysis involved calculation of band-limited power (BLP) followed by pair-wise BLP correlations. Further averaging was conducted to obtain local and remote connectivity. Statistical analyses revealed the increased connection degree of the left temporal cortex within delta (0.5-4 Hz), beta (13-30 Hz) and gamma (30-48 Hz) bands following verum acupuncture. Moreover, we not only validated the closer linkage of the left temporal cortex with the prefrontal and frontal cortices, but further pinpointed that such patterns were more extensively distributed in the ST36 group in the delta and beta bands compared to the restriction only to the delta band for NAP. Psychophysical results for significant pain threshold elevation further confirmed the analgesic effect of acupuncture at ST36. In conclusion, our findings may provide a new perspective to lend support for the specificity of neural expression underlying acupuncture.

Convergent evidence for hierarchical prediction networks from human electrocorticography and magnetoencephalography.

PubMed

Phillips, Holly N; Blenkmann, Alejandro; Hughes, Laura E; Kochen, Silvia; Bekinschtein, Tristan A; Cam-Can; Rowe, James B

2016-09-01

We propose that sensory inputs are processed in terms of optimised predictions and prediction error signals within hierarchical neurocognitive models. The combination of non-invasive brain imaging and generative network models has provided support for hierarchical frontotemporal interactions in oddball tasks, including recent identification of a temporal expectancy signal acting on prefrontal cortex. However, these studies are limited by the need to invert magnetoencephalographic or electroencephalographic sensor signals to localise activity from cortical 'nodes' in the network, or to infer neural responses from indirect measures such as the fMRI BOLD signal. To overcome this limitation, we examined frontotemporal interactions estimated from direct cortical recordings from two human participants with cortical electrode grids (electrocorticography - ECoG). Their frontotemporal network dynamics were compared to those identified by magnetoencephalography (MEG) in forty healthy adults. All participants performed the same auditory oddball task with standard tones interspersed with five deviant tone types. We normalised post-operative electrode locations to standardised anatomic space, to compare across modalities, and inverted the MEG to cortical sources using the estimated lead field from subject-specific head models. A mismatch negativity signal in frontal and temporal cortex was identified in all subjects. Generative models of the electrocorticographic and magnetoencephalographic data were separately compared using the free-energy estimate of the model evidence. Model comparison confirmed the same critical features of hierarchical frontotemporal networks in each patient as in the group-wise MEG analysis. These features included bilateral, feedforward and feedback frontotemporal modulated connectivity, in addition to an asymmetric expectancy driving input on left frontal cortex. The invasive ECoG provides an important step in construct validation of the use of neural generative models of MEG, which in turn enables generalisation to larger populations. Together, they give convergent evidence for the hierarchical interactions in frontotemporal networks for expectation and processing of sensory inputs. Crown Copyright © 2016. Published by Elsevier Ltd. All rights reserved.

Rejecting deep brain stimulation artefacts from MEG data using ICA and mutual information.

PubMed

Abbasi, Omid; Hirschmann, Jan; Schmitz, Georg; Schnitzler, Alfons; Butz, Markus

2016-08-01

Recording brain activity during deep brain stimulation (DBS) using magnetoencephalography (MEG) can potentially help clarifying the neurophysiological mechanism of DBS. The DBS artefact, however, distorts MEG data significantly. We present an artefact rejection approach to remove the DBS artefact from MEG data. We developed an approach consisting of four consecutive steps: (i) independent component analysis was used to decompose MEG data to independent components (ICs); (ii) mutual information (MI) between stimulation signal and all ICs was calculated; (iii) artefactual ICs were identified by means of an MI threshold; and (iv) the MEG signal was reconstructed using only non-artefactual ICs. This approach was applied to MEG data from five Parkinson's disease patients with implanted DBS stimulators. MEG was recorded with DBS ON (unilateral stimulation of the subthalamic nucleus) and DBS OFF during two experimental conditions: a visual attention task and alternating right and left median nerve stimulation. With the presented approach most of the artefact could be removed. The signal of interest could be retrieved in both conditions. In contrast to existing artefact rejection methods for MEG-DBS data (tSSS and S(3)P), the proposed method uses the actual artefact source, i.e. the stimulation signal, as reference signal. Using the presented method, the DBS artefact can be significantly rejected and the physiological data can be restored. This will facilitate research addressing the impact of DBS on brain activity during rest and various tasks. Copyright © 2016 Elsevier B.V. All rights reserved.

Magnetoencephalographic Mapping of Epileptic Spike Population Using Distributed Source Analysis: Comparison With Intracranial Electroencephalographic Spikes.

PubMed

Tanaka, Naoaki; Papadelis, Christos; Tamilia, Eleonora; Madsen, Joseph R; Pearl, Phillip L; Stufflebeam, Steven M

2018-04-27

This study evaluates magnetoencephalographic (MEG) spike population as compared with intracranial electroencephalographic (IEEG) spikes using a quantitative method based on distributed source analysis. We retrospectively studied eight patients with medically intractable epilepsy who had an MEG and subsequent IEEG monitoring. Fifty MEG spikes were analyzed in each patient using minimum norm estimate. For individual spikes, each vertex in the source space was considered activated when its source amplitude at the peak latency was higher than a threshold, which was set at 50% of the maximum amplitude over all vertices. We mapped the total count of activation at each vertex. We also analyzed 50 IEEG spikes in the same manner over the intracranial electrodes and created the activation count map. The location of the electrodes was obtained in the MEG source space by coregistering postimplantation computed tomography to MRI. We estimated the MEG- and IEEG-active regions associated with the spike populations using the vertices/electrodes with a count over 25. The activation count maps of MEG spikes demonstrated the localization associated with the spike population by variable count values at each vertex. The MEG-active region overlapped with 65 to 85% of the IEEG-active region in our patient group. Mapping the MEG spike population is valid for demonstrating the trend of spikes clustering in patients with epilepsy. In addition, comparison of MEG and IEEG spikes quantitatively may be informative for understanding their relationship.

MNE software for processing MEG and EEG data

PubMed Central

Gramfort, A.; Luessi, M.; Larson, E.; Engemann, D.; Strohmeier, D.; Brodbeck, C.; Parkkonen, L.; Hämäläinen, M.

2013-01-01

Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals originating from neural currents in the brain. Using these signals to characterize and locate brain activity is a challenging task, as evidenced by several decades of methodological contributions. MNE, whose name stems from its capability to compute cortically-constrained minimum-norm current estimates from M/EEG data, is a software package that provides comprehensive analysis tools and workflows including preprocessing, source estimation, time–frequency analysis, statistical analysis, and several methods to estimate functional connectivity between distributed brain regions. The present paper gives detailed information about the MNE package and describes typical use cases while also warning about potential caveats in analysis. The MNE package is a collaborative effort of multiple institutes striving to implement and share best methods and to facilitate distribution of analysis pipelines to advance reproducibility of research. Full documentation is available at http://martinos.org/mne. PMID:24161808

The Human Connectome Project: A data acquisition perspective

PubMed Central

Van Essen, D.C.; Ugurbil, K.; Auerbach, E.; Barch, D.; Behrens, T.E.J.; Bucholz, R.; Chang, A.; Chen, L.; Corbetta, M.; Curtiss, S.W.; Della Penna, S.; Feinberg, D.; Glasser, M.F.; Harel, N.; Heath, A.C.; Larson-Prior, L.; Marcus, D.; Michalareas, G.; Moeller, S.; Oostenveld, R.; Petersen, S.E.; Prior, F.; Schlaggar, B.L.; Smith, S.M.; Snyder, A.Z.; Xu, J.; Yacoub, E.

2012-01-01

The Human Connectome Project (HCP) is an ambitious 5-year effort to characterize brain connectivity and function and their variability in healthy adults. This review summarizes the data acquisition plans being implemented by a consortium of HCP investigators who will study a population of 1200 subjects (twins and their non-twin siblings) using multiple imaging modalities along with extensive behavioral and genetic data. The imaging modalities will include diffusion imaging (dMRI), resting-state fMRI (R-fMRI), task-evoked fMRI (T-fMRI), T1- and T2-weighted MRI for structural and myelin mapping, plus combined magnetoencephalography and electroencephalography (MEG/EEG). Given the importance of obtaining the best possible data quality, we discuss the efforts underway during the first two years of the grant (Phase I) to refine and optimize many aspects of HCP data acquisition, including a new 7T scanner, a customized 3T scanner, and improved MR pulse sequences. PMID:22366334

Wedge MUSIC: a novel approach to examine experimental differences of brain source connectivity patterns from EEG/MEG data.

PubMed

Ewald, Arne; Avarvand, Forooz Shahbazi; Nolte, Guido

2014-11-01

We introduce a novel method to estimate bivariate synchronization, i.e. interacting brain sources at a specific frequency or band, from MEG or EEG data robust to artifacts of volume conduction. The data driven calculation is solely based on the imaginary part of the cross-spectrum as opposed to the imaginary part of coherency. In principle, the method quantifies how strong a synchronization between a distinct pair of brain sources is present in the data. As an input of the method all pairs of pre-defined locations inside the brain can be used which is computationally exhaustive. In contrast to that, reference sources can be used that have been identified by any source reconstruction technique in a prior analysis step. We introduce different variants of the method and evaluate the performance in simulations. As a particular advantage of the proposed methodology, we demonstrate that the novel approach is capable of investigating differences in brain source interactions between experimental conditions or with respect to a certain baseline. For measured data, we first show the application on resting state MEG data where we find locally synchronized sources in the motor-cortex based on the sensorimotor idle rhythms. Finally, we show an example on EEG motor imagery data where we contrast hand and foot movements. Here, we also find local interactions in the expected brain areas. Copyright © 2014. Published by Elsevier Inc.

Visual areas become less engaged in associative recall following memory stabilization.

PubMed

Nieuwenhuis, Ingrid L C; Takashima, Atsuko; Oostenveld, Robert; Fernández, Guillén; Jensen, Ole

2008-04-15

Numerous studies have focused on changes in the activity in the hippocampus and higher association areas with consolidation and memory stabilization. Even though perceptual areas are engaged in memory recall, little is known about how memory stabilization is reflected in those areas. Using magnetoencephalography (MEG) we investigated changes in visual areas with memory stabilization. Subjects were trained on associating a face to one of eight locations. The first set of associations ('stabilized') was learned in three sessions distributed over a week. The second set ('labile') was learned in one session just prior to the MEG measurement. In the recall session only the face was presented and subjects had to indicate the correct location using a joystick. The MEG data revealed robust gamma activity during recall, which started in early visual cortex and propagated to higher visual and parietal brain areas. The occipital gamma power was higher for the labile than the stabilized condition (time=0.65-0.9 s). Also the event-related field strength was higher during recall of labile than stabilized associations (time=0.59-1.5 s). We propose that recall of the spatial associations prior to memory stabilization involves a top-down process relying on reconstructing learned representations in visual areas. This process is reflected in gamma band activity consistent with the notion that neuronal synchronization in the gamma band is required for visual representations. More direct synaptic connections are formed with memory stabilization, thus decreasing the dependence on visual areas.

An MEG Investigation of Neural Biomarkers and Language in Nonverbal Children with Autism Spectrum Disorders

DTIC Science & Technology

2014-09-01

Award Number: W81XWH-13-1-0293 TITLE: An MEG Investigation of Neural Biomarkers and Language in...SUBTITLE 5a. CONTRACT NUMBER An MEG Investigation of Neural Biomarkers and Language in Nonverbal Children with Autism Spectrum Disorders 5b...technique to correct MEG data for subject movement during recording. This correction reduces signal loss due to movement, resulting in higher

Magnetoencephalography signals are influenced by skull defects.

PubMed

Lau, S; Flemming, L; Haueisen, J

2014-08-01

Magnetoencephalography (MEG) signals had previously been hypothesized to have negligible sensitivity to skull defects. The objective is to experimentally investigate the influence of conducting skull defects on MEG and EEG signals. A miniaturized electric dipole was implanted in vivo into rabbit brains. Simultaneous recording using 64-channel EEG and 16-channel MEG was conducted, first above the intact skull and then above a skull defect. Skull defects were filled with agar gels, which had been formulated to have tissue-like homogeneous conductivities. The dipole was moved beneath the skull defects, and measurements were taken at regularly spaced points. The EEG signal amplitude increased 2-10 times, whereas the MEG signal amplitude reduced by as much as 20%. The EEG signal amplitude deviated more when the source was under the edge of the defect, whereas the MEG signal amplitude deviated more when the source was central under the defect. The change in MEG field-map topography (relative difference measure, RDM(∗)=0.15) was geometrically related to the skull defect edge. MEG and EEG signals can be substantially affected by skull defects. MEG source modeling requires realistic volume conductor head models that incorporate skull defects. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Spatial patterning of P granules by RNA-induced phase separation of the intrinsically-disordered protein MEG-3

PubMed Central

Smith, Jarrett; Calidas, Deepika; Schmidt, Helen; Lu, Tu; Rasoloson, Dominique; Seydoux, Geraldine

2016-01-01

RNA granules are non-membrane bound cellular compartments that contain RNA and RNA binding proteins. The molecular mechanisms that regulate the spatial distribution of RNA granules in cells are poorly understood. During polarization of the C. elegans zygote, germline RNA granules, called P granules, assemble preferentially in the posterior cytoplasm. We present evidence that P granule asymmetry depends on RNA-induced phase separation of the granule scaffold MEG-3. MEG-3 is an intrinsically disordered protein that binds and phase separates with RNA in vitro. In vivo, MEG-3 forms a posterior-rich concentration gradient that is anti-correlated with a gradient in the RNA-binding protein MEX-5. MEX-5 is necessary and sufficient to suppress MEG-3 granule formation in vivo, and suppresses RNA-induced MEG-3 phase separation in vitro. Our findings suggest that MEX-5 interferes with MEG-3’s access to RNA, thus locally suppressing MEG-3 phase separation to drive P granule asymmetry. Regulated access to RNA, combined with RNA-induced phase separation of key scaffolding proteins, may be a general mechanism for controlling the formation of RNA granules in space and time. DOI: http://dx.doi.org/10.7554/eLife.21337.001 PMID:27914198

Magnetoencephalographic responses in relation to temporal and spatial factors of sound fields

NASA Astrophysics Data System (ADS)

Soeta, Yoshiharu; Nakagawa, Seiji; Tonoike, Mitsuo; Hotehama, Takuya; Ando, Yoichi

2004-05-01

To establish the guidelines based on brain functions for designing sound fields such as a concert hall and an opera house, the activities of the human brain to the temporal and spatial factors of the sound field have been investigated using magnetoencephalography (MEG). MEG is a noninvasive technique for investigating neuronal activity in human brain. First of all, the auditory evoked responses in change of the magnitude of the interaural cross-correlation (IACC) were analyzed. IACC is one of the spatial factors, which has great influence on the degree of subjective preference and diffuseness for sound fields. The results indicated that the peak amplitude of N1m, which was found over the left and right temporal lobes around 100 ms after the stimulus onset, decreased with increasing the IACC. Second, the responses corresponding to subjective preference for one of the typical temporal factors, i.e., the initial delay gap between a direct sound and the first reflection, were investigated. The results showed that the effective duration of the autocorrelation function of MEG between 8 and 13 Hz became longer during presentations of a preferred stimulus. These results indicate that the brain may be relaxed, and repeat a similar temporal rhythm under preferred sound fields.

Complexity analysis of spontaneous brain activity in mood disorders: A magnetoencephalography study of bipolar disorder and major depression.

PubMed

Fernández, Alberto; Al-Timemy, Ali H; Ferre, Francisco; Rubio, Gabriel; Escudero, Javier

2018-04-26

The lack of a biomarker for Bipolar Disorder (BD) causes problems in the differential diagnosis with other mood disorders such as major depression (MD), and misdiagnosis frequently occurs. Bearing this in mind, we investigated non-linear magnetoencephalography (MEG) patterns in BD and MD. Lempel-Ziv Complexity (LZC) was used to evaluate the resting-state MEG activity in a cross-sectional sample of 60 subjects, including 20 patients with MD, 16 patients with BD type-I, and 24 control (CON) subjects. Particular attention was paid to the role of age. The results were aggregated by scalp region. Overall, MD patients showed significantly higher LZC scores than BD patients and CONs. Linear regression analyses demonstrated distinct tendencies of complexity progression as a function of age, with BD patients showing a divergent tendency as compared with MD and CON groups. Logistic regressions confirmed such distinct relationship with age, which allowed the classification of diagnostic groups. The patterns of neural complexity in BD and MD showed not only quantitative differences in their non-linear MEG characteristics but also divergent trajectories of progression as a function of age. Moreover, neural complexity patterns in BD patients resembled those previously observed in schizophrenia, thus supporting preceding evidence of common neuropathological processes. Copyright © 2018 Elsevier Inc. All rights reserved.

Music and the brain - design of an MEG compatible piano.

PubMed

Chacon-Castano, Julian; Rathbone, Daniel R; Hoffman, Rachel; Heng Yang; Pantazis, Dimitrios; Yang, Jason; Hornberger, Erik; Hanumara, Nevan C

2017-07-01

Magnetoencephalography (MEG) neuroimaging has been used to study subjects' responses when listening to music, but research into the effects of playing music has been limited by the lack of MEG compatible instruments that can operate in a magnetically shielded environment without creating electromagnetic interference. This paper describes the design and preliminary testing of an MEG compatible piano keyboard with 25 full size keys that employs a novel 3-state optical encoder design and electronics to provide realistic velocity-controlled volume modulation. This instrument will allow researchers to study musical performance on a finer timescale than fMRI and enable a range of MEG studies.

ElectroMagnetoEncephalography Software: Overview and Integration with Other EEG/MEG Toolboxes

PubMed Central

Peyk, Peter; De Cesarei, Andrea; Junghöfer, Markus

2011-01-01

EMEGS (electromagnetic encephalography software) is a MATLAB toolbox designed to provide novice as well as expert users in the field of neuroscience with a variety of functions to perform analysis of EEG and MEG data. The software consists of a set of graphical interfaces devoted to preprocessing, analysis, and visualization of electromagnetic data. Moreover, it can be extended using a plug-in interface. Here, an overview of the capabilities of the toolbox is provided, together with a simple tutorial for both a standard ERP analysis and a time-frequency analysis. Latest features and future directions of the software development are presented in the final section. PMID:21577273

ElectroMagnetoEncephalography software: overview and integration with other EEG/MEG toolboxes.

PubMed

Peyk, Peter; De Cesarei, Andrea; Junghöfer, Markus

2011-01-01

EMEGS (electromagnetic encephalography software) is a MATLAB toolbox designed to provide novice as well as expert users in the field of neuroscience with a variety of functions to perform analysis of EEG and MEG data. The software consists of a set of graphical interfaces devoted to preprocessing, analysis, and visualization of electromagnetic data. Moreover, it can be extended using a plug-in interface. Here, an overview of the capabilities of the toolbox is provided, together with a simple tutorial for both a standard ERP analysis and a time-frequency analysis. Latest features and future directions of the software development are presented in the final section.

Spectral-Spatial Differentiation of Brain Activity During Mental Imagery of Improvisational Music Performance Using MEG

PubMed Central

Boasen, Jared; Takeshita, Yuya; Kuriki, Shinya; Yokosawa, Koichi

2018-01-01

Group musical improvisation is thought to be akin to conversation, and therapeutically has been shown to be effective at improving communicativeness, sociability, creative expression, and overall psychological health. To understand these therapeutic effects, clarifying the nature of brain activity during improvisational cognition is important. Some insight regarding brain activity during improvisational music cognition has been gained via functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). However, we have found no reports based on magnetoencephalography (MEG). With the present study, we aimed to demonstrate the feasibility of improvisational music performance experimentation in MEG. We designed a novel MEG-compatible keyboard, and used it with experienced musicians (N = 13) in a music performance paradigm to spectral-spatially differentiate spontaneous brain activity during mental imagery of improvisational music performance. Analyses of source activity revealed that mental imagery of improvisational music performance induced greater theta (5–7 Hz) activity in left temporal areas associated with rhythm production and communication, greater alpha (8–12 Hz) activity in left premotor and parietal areas associated with sensorimotor integration, and less beta (15–29 Hz) activity in right frontal areas associated with inhibition control. These findings support the notion that musical improvisation is conversational, and suggest that creation of novel auditory content is facilitated by a more internally-directed, disinhibited cognitive state. PMID:29740300

An Evaluation of the PCB-TOX-SPOT Water Toxicity Test

DTIC Science & Technology

2011-09-15

Guidelines (70 kg person, 15 liter [L]/day consumption), when available; 1 year MEG for copper, fluoroacetate, and strychnine ; < 7 day MEG for nicotine... strychnine ; < 7 day MEG for nicotine; fenamiphos MEG estimated from terbufos (Richards, personal communication), b mg/L c Data from FOUO Widder et al...Ulitzur S. 1977. Control of luciferase synthesis in a newly isolated strain of Photobacterium leiognathi. Arch Microbiol.,Dec 15;115(3):347-51

Imaging DC MEG Fields Associated with Epileptic Onset

NASA Astrophysics Data System (ADS)

Weiland, B. J.; Bowyer, S. M.; Moran, J. E.; Jenrow, K.; Tepley, N.

2004-10-01

Magnetoencephalography (MEG) is a non-invasive brain imaging modality, with high spatial and temporal resolution, used to evaluate and quantify the magnetic fields associated with neuronal activity. Complex partial epileptic seizures are characterized by hypersynchronous neuronal activity believed to arise from a zone of epileptogenesis. This study investigated the characteristics of direct current (DC) MEG shifts arising at epileptic onset. MEG data were acquired with rats using a six-channel first order gradiometer system. Limbic status epilepticus was induced by IA (femoral) administration of kainic acid. DC-MEG shifts were observed at the onset of epileptic spike train activity and status epilepticus. Epilepsy is also being studied in patients undergoing presurgical mapping from the Comprehensive Epilepsy Center at Henry Ford Hospital using a whole head Neuromagnetometer. Preliminary data analysis shows that DC-MEG waveforms, qualitatively similar to those seen in the animal model, are evident prior to seizure activity in human subjects.

fMRI and MEG in the study of typical and atypical cognitive development.

PubMed

Taylor, M J; Donner, E J; Pang, E W

2012-01-01

The tremendous changes in brain structure over childhood are critical to the development of cognitive functions. Neuroimaging provides a means of linking these brain-behaviour relations, as task protocols can be adapted for use with young children to assess the development of cognitive functions in both typical and atypical populations. This paper reviews some of our research using magnetoencephalography (MEG) and functional MRI (fMRI) in the study of cognitive development, with a focus on frontal lobe functions. Working memory for complex abstract patterns showed clear development in terms of the recruitment of frontal regions, seen with fMRI, with indications of strategy differences across the age range, from 6 to 35 years of age. Right hippocampal involvement was also evident in these n-back tasks, demonstrating its involvement in recognition in simple working memory protocols. Children born very preterm (7 to 9 years of age) showed reduced fMRI activation particularly in the precuneus and right hippocampal regions relative to control children. In a large normative n-back study (n=90) with upright and inverted faces, MEG data also showed right hippocampal activation that was present across the age range; frontal sources were evident only from 10 years of age. Other studies have investigated the development of set shifting, an executive function that is often deficit in atypical populations. fMRI showed recruitment of frontal areas, including the insula, that have significantly different patterns in children (7 to 14 years of age) with autism spectrum disorder compared to typically developing children, indicating that successful performance implicated differing strategies in these two groups of children. These types of studies will help our understanding of both normal brain-behaviour development and cognitive dysfunction in atypically developing populations. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Comparative studies of brain activation with MEG and functional MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

George, J.S.; Aine, C.J.; Sanders, J.A.

The past two years have witnessed the emergence of MRI as a functional imaging methodology. Initial demonstrations involved the injection of a paramagnetic contrast agent and required ultrafast echo planar imaging capability to adequately resolve the passage of the injected bolus. By measuring the local reduction in image intensity due to magnetic susceptibility, it was possible to calculate blood volume, which changes as a function of neural activation. Later developments have exploited endogenous contrast mechanisms to monitor changes in blood volume or in venous blood oxygen content. Recently, we and others have demonstrated that it is possible to make suchmore » measurements in a clinical imager, suggesting that the large installed base of such machines might be utilized for functional imaging. Although it is likely that functional MRI (fMRI) will subsume some of the clinical and basic neuroscience applications now touted for MEG, it is also clear that these techniques offer different largely complementary, capabilities. At the very least, it is useful to compare and cross-validate the activation maps produced by these techniques. Such studies will be valuable as a check on results of neuromagnetic distributed current reconstructions and will allow better characterization of the relationship between neurophysiological activation and associated hemodynamic changes. A more exciting prospect is the development of analyses that combine information from the two modalities to produce a better description of underlying neural activity than is possible with either technique in isolation. In this paper we describe some results from initial comparative studies and outline several techniques that can be used to treat MEG and fMRI data within a unified computational framework.« less

MEG-EEG Information Fusion and Electromagnetic Source Imaging: From Theory to Clinical Application in Epilepsy.

PubMed

Chowdhury, Rasheda Arman; Zerouali, Younes; Hedrich, Tanguy; Heers, Marcel; Kobayashi, Eliane; Lina, Jean-Marc; Grova, Christophe

2015-11-01

The purpose of this study is to develop and quantitatively assess whether fusion of EEG and MEG (MEEG) data within the maximum entropy on the mean (MEM) framework increases the spatial accuracy of source localization, by yielding better recovery of the spatial extent and propagation pathway of the underlying generators of inter-ictal epileptic discharges (IEDs). The key element in this study is the integration of the complementary information from EEG and MEG data within the MEM framework. MEEG was compared with EEG and MEG when localizing single transient IEDs. The fusion approach was evaluated using realistic simulation models involving one or two spatially extended sources mimicking propagation patterns of IEDs. We also assessed the impact of the number of EEG electrodes required for an efficient EEG-MEG fusion. MEM was compared with minimum norm estimate, dynamic statistical parametric mapping, and standardized low-resolution electromagnetic tomography. The fusion approach was finally assessed on real epileptic data recorded from two patients showing IEDs simultaneously in EEG and MEG. Overall the localization of MEEG data using MEM provided better recovery of the source spatial extent, more sensitivity to the source depth and more accurate detection of the onset and propagation of IEDs than EEG or MEG alone. MEM was more accurate than the other methods. MEEG proved more robust than EEG and MEG for single IED localization in low signal-to-noise ratio conditions. We also showed that only few EEG electrodes are required to bring additional relevant information to MEG during MEM fusion.

Automatic detection and visualisation of MEG ripple oscillations in epilepsy.

PubMed

van Klink, Nicole; van Rosmalen, Frank; Nenonen, Jukka; Burnos, Sergey; Helle, Liisa; Taulu, Samu; Furlong, Paul Lawrence; Zijlmans, Maeike; Hillebrand, Arjan

2017-01-01

High frequency oscillations (HFOs, 80-500 Hz) in invasive EEG are a biomarker for the epileptic focus. Ripples (80-250 Hz) have also been identified in non-invasive MEG, yet detection is impeded by noise, their low occurrence rates, and the workload of visual analysis. We propose a method that identifies ripples in MEG through noise reduction, beamforming and automatic detection with minimal user effort. We analysed 15 min of presurgical resting-state interictal MEG data of 25 patients with epilepsy. The MEG signal-to-noise was improved by using a cross-validation signal space separation method, and by calculating ~ 2400 beamformer-based virtual sensors in the grey matter. Ripples in these sensors were automatically detected by an algorithm optimized for MEG. A small subset of the identified ripples was visually checked. Ripple locations were compared with MEG spike dipole locations and the resection area if available. Running the automatic detection algorithm resulted in on average 905 ripples per patient, of which on average 148 ripples were visually reviewed. Reviewing took approximately 5 min per patient, and identified ripples in 16 out of 25 patients. In 14 patients the ripple locations showed good or moderate concordance with the MEG spikes. For six out of eight patients who had surgery, the ripple locations showed concordance with the resection area: 4/5 with good outcome and 2/3 with poor outcome. Automatic ripple detection in beamformer-based virtual sensors is a feasible non-invasive tool for the identification of ripples in MEG. Our method requires minimal user effort and is easily applicable in a clinical setting.

Chemistries for Protection and Decontamination

DTIC Science & Technology

2008-03-01

t i o n Measurement of Oxygen Uptake, Supported Catalyst and CEES in Solvent-Free System TDA R e s e a r c h Tests with HD • At CUBRC (Buffalo...dual gas burettes for HD tests at CUBRC . The dual burette on the left was connected to a flask with the catalyst and HD (and to an empty flask as a...Hill, Zhen Luo, Daniel Hillesheim • ECBC: Larry Procell • CUBRC : Meg Stapleton, Rich Fitzpatrick • Battelle: John Ontiveros, Walter Miller • ARO

MEG time-frequency analyses for pre- and post-surgical evaluation of patients with epileptic rhythmic fast activity.

PubMed

Sueda, Keitaro; Takeuchi, Fumiya; Shiraishi, Hideaki; Nakane, Shingo; Asahina, Naoko; Kohsaka, Shinobu; Nakama, Hideyuki; Otsuki, Taisuke; Sawamura, Yutaka; Saitoh, Shinji

2010-02-01

To evaluate the effectiveness of surgery for epilepsy, we analyzed rhythmic fast activity by magnetoencephalography (MEG) before and after surgery using time-frequency analysis. To assess reliability, the results obtained by pre-surgical MEG and intraoperative electrocorticography were compared. Four children with symptomatic localization-related epilepsy caused by circumscribed cortical lesion were examined in the present study using 204-channel helmet-shaped MEG with a sampling rate of 600Hz. One patient had dysembryoplastic neuroepithelial tumor (DNT) and three patients had focal cortical dysplasia (FCD). Aberrant areas were superimposed, to reconstruct 3D MRI images, and illustrated as moving images. In three patients, short-time Fourier transform (STFT) analyses of MEG showed rhythmic activities just above the lesion with FCD and in the vicinity of DNT. In one patient with FCD in the medial temporal lobe, rhythmic activity appeared in the ipsilateral frontal lobe and temporal lateral aspect. These findings correlate well with the results obtained by intraoperative electrocorticography. After the surgery, three patients were relieved of their seizures, and the area of rhythmic MEG activity disappeared or become smaller. One patient had residual rhythmic MEG activity, and she suffered from seizure relapse. Time-frequency analyses using STFT successfully depicted MEG rhythmic fast activity, and would provide valuable information for pre- and post-surgical evaluations to define surgical strategies for patients with epilepsy.

[Effects of recombinant human alpha-2b and gamma interferons on bone marrow megakaryocyte progenitors (CFU-Meg) from patients with chronic myelocytic leukemia].

PubMed

Tanabe, Y; Dan, K; Kuriya, S; Nomura, T

1989-10-01

The effects of recombinant human interferon (IFN) alpha-2b and gamma on the bone marrow megakaryocyte progenitors (CFU-Meg) were compared between eight patients in the chronic phase of Ph1-positive chronic myelocytic leukemia (CML) and five hematologically normal patients. CFU-Meg was assayed in plasma clot culture added with phytohemagglutinin-stimulated leukocyte-conditioned medium as a source of colony stimulating activity. The average count of CFU-Meg colonies formed from the bone marrow of CML patients was 5.5 times that of normal controls. Spontaneous CFU-Meg colonies were grown in seven of eight CML patients, but in none of five controls. Colony formation by CFU-Meg in CML as well as normal bone marrow was suppressed by the two preparations of IFN in a dose dependent fashion. Their suppressive influence on colonies from CFU-Meg was comparable between CML and normal bone marrow at lower concentrations, but was less marked for CML than normal bone marrow at higher concentrations. The formation of CFU-Meg colonies from CML bone marrow was more severely suppressed by IFN-gamma than IFN-alpha-2b. Depletion of either T lymphocytes or adherent cells from the CML bone marrow cells diminished the suppressive effects of IFN-gamma, but had no influence on the effects of IFN-alpha-2b.

Requirements for Coregistration Accuracy in On-Scalp MEG.

PubMed

Zetter, Rasmus; Iivanainen, Joonas; Stenroos, Matti; Parkkonen, Lauri

2018-06-22

Recent advances in magnetic sensing has made on-scalp magnetoencephalography (MEG) possible. In particular, optically-pumped magnetometers (OPMs) have reached sensitivity levels that enable their use in MEG. In contrast to the SQUID sensors used in current MEG systems, OPMs do not require cryogenic cooling and can thus be placed within millimetres from the head, enabling the construction of sensor arrays that conform to the shape of an individual's head. To properly estimate the location of neural sources within the brain, one must accurately know the position and orientation of sensors in relation to the head. With the adaptable on-scalp MEG sensor arrays, this coregistration becomes more challenging than in current SQUID-based MEG systems that use rigid sensor arrays. Here, we used simulations to quantify how accurately one needs to know the position and orientation of sensors in an on-scalp MEG system. The effects that different types of localisation errors have on forward modelling and source estimates obtained by minimum-norm estimation, dipole fitting, and beamforming are detailed. We found that sensor position errors generally have a larger effect than orientation errors and that these errors affect the localisation accuracy of superficial sources the most. To obtain similar or higher accuracy than with current SQUID-based MEG systems, RMS sensor position and orientation errors should be [Formula: see text] and [Formula: see text], respectively.

State space truncation with quantified errors for accurate solutions to discrete Chemical Master Equation

PubMed Central

Cao, Youfang; Terebus, Anna; Liang, Jie

2016-01-01

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEG), we truncate the state space by limiting the total molecular copy numbers in each MEG. We further describe a theoretical framework for analysis of the truncation error in the steady state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of 1) the birth and death model, 2) the single gene expression model, 3) the genetic toggle switch model, and 4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate out theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks. PMID:27105653

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cao, Youfang; Terebus, Anna; Liang, Jie

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. Wemore » further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.« less

State Space Truncation with Quantified Errors for Accurate Solutions to Discrete Chemical Master Equation

DOE PAGES

Cao, Youfang; Terebus, Anna; Liang, Jie

2016-04-22

The discrete chemical master equation (dCME) provides a general framework for studying stochasticity in mesoscopic reaction networks. Since its direct solution rapidly becomes intractable due to the increasing size of the state space, truncation of the state space is necessary for solving most dCMEs. It is therefore important to assess the consequences of state space truncations so errors can be quantified and minimized. Here we describe a novel method for state space truncation. By partitioning a reaction network into multiple molecular equivalence groups (MEGs), we truncate the state space by limiting the total molecular copy numbers in each MEG. Wemore » further describe a theoretical framework for analysis of the truncation error in the steady-state probability landscape using reflecting boundaries. By aggregating the state space based on the usage of a MEG and constructing an aggregated Markov process, we show that the truncation error of a MEG can be asymptotically bounded by the probability of states on the reflecting boundary of the MEG. Furthermore, truncating states of an arbitrary MEG will not undermine the estimated error of truncating any other MEGs. We then provide an overall error estimate for networks with multiple MEGs. To rapidly determine the appropriate size of an arbitrary MEG, we also introduce an a priori method to estimate the upper bound of its truncation error. This a priori estimate can be rapidly computed from reaction rates of the network, without the need of costly trial solutions of the dCME. As examples, we show results of applying our methods to the four stochastic networks of (1) the birth and death model, (2) the single gene expression model, (3) the genetic toggle switch model, and (4) the phage lambda bistable epigenetic switch model. We demonstrate how truncation errors and steady-state probability landscapes can be computed using different sizes of the MEG(s) and how the results validate our theories. Overall, the novel state space truncation and error analysis methods developed here can be used to ensure accurate direct solutions to the dCME for a large number of stochastic networks.« less

Increases in Language Lateralization in Normal Children as Observed Using Magnetoencephalography

ERIC Educational Resources Information Center

Ressel, Volker; Wilke, Marko; Lidzba, Karen; Lutzenberger, Werner; Krageloh-Mann, Ingeborg

2008-01-01

Previous functional magnetic resonance imaging (fMRI) studies investigating hemispheric dominance for language have shown that hemispheric specialization increases with age. We employed magnetoencephalography (MEG) to investigate these effects as a function of normal development. In sum, 22 healthy children aged 7-16 years were investigated using…

Auditory training changes temporal lobe connectivity in 'Wernicke's aphasia': a randomised trial.

PubMed

Woodhead, Zoe Vj; Crinion, Jennifer; Teki, Sundeep; Penny, Will; Price, Cathy J; Leff, Alexander P

2017-07-01

Aphasia is one of the most disabling sequelae after stroke, occurring in 25%-40% of stroke survivors. However, there remains a lack of good evidence for the efficacy or mechanisms of speech comprehension rehabilitation. This within-subjects trial tested two concurrent interventions in 20 patients with chronic aphasia with speech comprehension impairment following left hemisphere stroke: (1) phonological training using 'Earobics' software and (2) a pharmacological intervention using donepezil, an acetylcholinesterase inhibitor. Donepezil was tested in a double-blind, placebo-controlled, cross-over design using block randomisation with bias minimisation. The primary outcome measure was speech comprehension score on the comprehensive aphasia test. Magnetoencephalography (MEG) with an established index of auditory perception, the mismatch negativity response, tested whether the therapies altered effective connectivity at the lower (primary) or higher (secondary) level of the auditory network. Phonological training improved speech comprehension abilities and was particularly effective for patients with severe deficits. No major adverse effects of donepezil were observed, but it had an unpredicted negative effect on speech comprehension. The MEG analysis demonstrated that phonological training increased synaptic gain in the left superior temporal gyrus (STG). Patients with more severe speech comprehension impairments also showed strengthening of bidirectional connections between the left and right STG. Phonological training resulted in a small but significant improvement in speech comprehension, whereas donepezil had a negative effect. The connectivity results indicated that training reshaped higher order phonological representations in the left STG and (in more severe patients) induced stronger interhemispheric transfer of information between higher levels of auditory cortex.Clinical trial registrationThis trial was registered with EudraCT (2005-004215-30, https:// eudract .ema.europa.eu/) and ISRCTN (68939136, http://www.isrctn.com/). © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Recording epileptic activity with MEG in a light-weight magnetic shield.

PubMed

De Tiège, Xavier; Op de Beeck, Marc; Funke, Michael; Legros, Benjamin; Parkkonen, Lauri; Goldman, Serge; Van Bogaert, Patrick

2008-12-01

Ten patients with focal epilepsy were studied with magnetoencephalography (MEG) to determine if a new light-weight magnetically shielded room (lMSR) provides sufficient attenuation of magnetic interference to detect and localize the magnetic correlates of epileptic activity. Interictal MEG epileptic events co-localizing with the presumed location of the epileptogenic zone were found in all patients. MEG measurements performed in the lMSR provide an adequate signal-to-noise ratio for non-invasive localization of epileptic foci.

Recording temporal lobe epileptic activity with MEG in a light-weight magnetic shield.

PubMed

Carrette, Evelien; Op de Beeck, Marc; Bourguignon, Mathieu; Boon, Paul; Vonck, Kristl; Legros, Benjamin; Goldman, Serge; Van Bogaert, Patrick; De Tiège, Xavier

2011-06-01

To assess the interictal epileptic discharges (IEDs) detection rate of magnetoencephalography (MEG) recordings performed in a new light-weight magnetic shielding (LMSR) concept in a large group of consecutive patients with presumed mesiotemporal lobe epilepsy (MTLE). Thirty-eight patients (23 women; age range: 6-63 years) with presumed MTLE were prospectively studied. MEG investigations were performed with the 306-channel Elekta Neuromag® MEG-system installed in a normal hospital environment into a LMSR (MaxShield, Elekta Oy). Equivalent current dipoles (ECD, g/% > 80%) corresponding to epileptic events were fitted to each patient's spherical head model at IEDs onset and peak and then superimposed on the patient's co-registered MRI. IEDs were observed in 26 out of 38 patients (68.4%). Temporal ECDs were mesial in 14 patients, anterior in 23 patients and posterior in 8 patients. Interestingly, in 6 patients, ECDs fitted at spike-onset were localized in the hippocampus while at the peak of the spike, they had an anterior temporal location. MEG using LMSR provides adequate signal to noise ratio (SNR) to allow reliable detection and localization of single epileptic abnormalities on continuous MEG data in 68% of patients with presumed MTLE. Moreover, mesial temporal epileptic sources were detected in 54% of patients with abnormal MEG. The SNR of MEG data acquired using the LMSR is therefore suitable for the non-invasive localization of epileptic foci in patients with MTLE. The use of LMSR, which are cheaper and smaller than conventional MSR, should facilitate the development of MEG in clinical environments. Copyright © 2011 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.

PubMed

Huang, Ming-Xiong; Huang, Charles W; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L; Baker, Dewleen G; Song, Tao; Harrington, Deborah L; Theilmann, Rebecca J; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M; Edgar, J Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T; Drake, Angela; Lee, Roland R

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses. © 2013.

MEG Source Imaging Method using Fast L1 Minimum-norm and its Applications to Signals with Brain Noise and Human Resting-state Source Amplitude Images

PubMed Central

Huang, Ming-Xiong; Huang, Charles W.; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L.; Baker, Dewleen G.; Song, Tao; Harrington, Deborah L.; Theilmann, Rebecca J.; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M.; Edgar, J. Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T.; Drake, Angela; Lee, Roland R.

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL’s performance of was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL’s performance was then examined in the analysis of human mediannerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer’s problems of signal leaking and distorted source time-courses. PMID:24055704

Long noncoding RNA MEG3 inhibits proliferation of chronic myeloid leukemia cells by sponging microRNA21.

PubMed

Li, Ziye; Yang, Lin; Liu, Xiaojun; Nie, Ziyuan; Luo, Jianmin

2018-05-14

The long noncoding RNA (lnc) maternally expressed 3 (MEG3) is downregulated in many types of cancers. However, the relationship between lncRNA MEG3, microRNA-21 (miR-21) and chronic myeloid leukemia (CML) blast crisis is unknown. This study examined bone marrow samples from 40 CML patients and 10 healthy donors. Proliferation and apoptosis assays, real-time polymerase chain reaction (PCR), bisulfite sequencing PCR, Western blotting, luciferase assay, RNA pull-down, RNA immunoprecipitation (RIP), co-immunoprecipitation (CoIP) and Chromatin immunoprecipitation (ChIP) were performed. We found that MEG3 and PTEN expression were down-regulated, whereas, MDM2, DNMT1 and miR-21 were up-regulated in the accelerated and blast phases of CML. Treated with 5-azacytidine decreased the level of MDM2, DNMT1 and miR21, but increased the level of MEG3 and PTEN. Overexpression of MEG3 and silencing the expression of miR-21 inhibited proliferation and induced apoptosis. MEG3 overexpression and silencing the expression of miR21 influence the levels of MMP-2, MMP-9, bcl-2 and Bax. MEG3 was able to interact with MDM2 and EZH2. MDM2 could interact with DNMT1 and PTEN. MYC and AKT can interact with EZH2. ChIP-seq showed that the promoter of KLF4 and SFRP2 interacts with DNMT1. In conclusion, lncRNA MEG3 and its target miR21 may serve as novel therapeutic targets for CML blast crisis; and demethylation drugs might also have potential clinical application in treating CML blast crisis. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

Single-subject-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mild traumatic brain injury

PubMed Central

Huang, Ming-Xiong; Nichols, Sharon; Baker, Dewleen G.; Robb, Ashley; Angeles, Annemarie; Yurgil, Kate A.; Drake, Angela; Levy, Michael; Song, Tao; McLay, Robert; Theilmann, Rebecca J.; Diwakar, Mithun; Risbrough, Victoria B.; Ji, Zhengwei; Huang, Charles W.; Chang, Douglas G.; Harrington, Deborah L.; Muzzatti, Laura; Canive, Jose M.; Christopher Edgar, J.; Chen, Yu-Han; Lee, Roland R.

2014-01-01

Traumatic brain injury (TBI) is a leading cause of sustained impairment in military and civilian populations. However, mild TBI (mTBI) can be difficult to detect using conventional MRI or CT. Injured brain tissues in mTBI patients generate abnormal slow-waves (1–4 Hz) that can be measured and localized by resting-state magnetoencephalography (MEG). In this study, we develop a voxel-based whole-brain MEG slow-wave imaging approach for detecting abnormality in patients with mTBI on a single-subject basis. A normative database of resting-state MEG source magnitude images (1–4 Hz) from 79 healthy control subjects was established for all brain voxels. The high-resolution MEG source magnitude images were obtained by our recent Fast-VESTAL method. In 84 mTBI patients with persistent post-concussive symptoms (36 from blasts, and 48 from non-blast causes), our method detected abnormalities at the positive detection rates of 84.5%, 86.1%, and 83.3% for the combined (blast-induced plus with non-blast causes), blast, and non-blast mTBI groups, respectively. We found that prefrontal, posterior parietal, inferior temporal, hippocampus, and cerebella areas were particularly vulnerable to head trauma. The result also showed that MEG slow-wave generation in prefrontal areas positively correlated with personality change, trouble concentrating, affective lability, and depression symptoms. Discussion is provided regarding the neuronal mechanisms of MEG slow-wave generation due to deafferentation caused by axonal injury and/or blockages/limitations of cholinergic transmission in TBI. This study provides an effective way for using MEG slow-wave source imaging to localize affected areas and supports MEG as a tool for assisting the diagnosis of mTBI. PMID:25009772

Lead Telluride Quantum Dot Solar Cells Displaying External Quantum Efficiencies Exceeding 120%

PubMed Central

2015-01-01

Multiple exciton generation (MEG) in semiconducting quantum dots is a process that produces multiple charge-carrier pairs from a single excitation. MEG is a possible route to bypass the Shockley-Queisser limit in single-junction solar cells but it remains challenging to harvest charge-carrier pairs generated by MEG in working photovoltaic devices. Initial yields of additional carrier pairs may be reduced due to ultrafast intraband relaxation processes that compete with MEG at early times. Quantum dots of materials that display reduced carrier cooling rates (e.g., PbTe) are therefore promising candidates to increase the impact of MEG in photovoltaic devices. Here we demonstrate PbTe quantum dot-based solar cells, which produce extractable charge carrier pairs with an external quantum efficiency above 120%, and we estimate an internal quantum efficiency exceeding 150%. Resolving the charge carrier kinetics on the ultrafast time scale with pump–probe transient absorption and pump–push–photocurrent measurements, we identify a delayed cooling effect above the threshold energy for MEG. PMID:26488847

TopoToolbox: Using Sensor Topography to Calculate Psychologically Meaningful Measures from Event-Related EEG/MEG

PubMed Central

Tian, Xing; Poeppel, David; Huber, David E.

2011-01-01

The open-source toolbox “TopoToolbox” is a suite of functions that use sensor topography to calculate psychologically meaningful measures (similarity, magnitude, and timing) from multisensor event-related EEG and MEG data. Using a GUI and data visualization, TopoToolbox can be used to calculate and test the topographic similarity between different conditions (Tian and Huber, 2008). This topographic similarity indicates whether different conditions involve a different distribution of underlying neural sources. Furthermore, this similarity calculation can be applied at different time points to discover when a response pattern emerges (Tian and Poeppel, 2010). Because the topographic patterns are obtained separately for each individual, these patterns are used to produce reliable measures of response magnitude that can be compared across individuals using conventional statistics (Davelaar et al. Submitted and Huber et al., 2008). TopoToolbox can be freely downloaded. It runs under MATLAB (The MathWorks, Inc.) and supports user-defined data structure as well as standard EEG/MEG data import using EEGLAB (Delorme and Makeig, 2004). PMID:21577268

PyEEG: an open source Python module for EEG/MEG feature extraction.

PubMed

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

PubMed Central

Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

2011-01-01

Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction. PMID:21512582

Multiple exciton generation in chiral carbon nanotubes: Density functional theory based computation

NASA Astrophysics Data System (ADS)

Kryjevski, Andrei; Mihaylov, Deyan; Kilina, Svetlana; Kilin, Dmitri

2017-10-01

We use a Boltzmann transport equation (BE) to study time evolution of a photo-excited state in a nanoparticle including phonon-mediated exciton relaxation and the multiple exciton generation (MEG) processes, such as exciton-to-biexciton multiplication and biexciton-to-exciton recombination. BE collision integrals are computed using Kadanoff-Baym-Keldysh many-body perturbation theory based on density functional theory simulations, including exciton effects. We compute internal quantum efficiency (QE), which is the number of excitons generated from an absorbed photon in the course of the relaxation. We apply this approach to chiral single-wall carbon nanotubes (SWCNTs), such as (6,2) and (6,5). We predict efficient MEG in the (6,2) and (6,5) SWCNTs within the solar spectrum range starting at the 2Eg energy threshold and with QE reaching ˜1.6 at about 3Eg, where Eg is the electronic gap.

Multiple exciton generation in chiral carbon nanotubes: Density functional theory based computation.

PubMed

Kryjevski, Andrei; Mihaylov, Deyan; Kilina, Svetlana; Kilin, Dmitri

2017-10-21

We use a Boltzmann transport equation (BE) to study time evolution of a photo-excited state in a nanoparticle including phonon-mediated exciton relaxation and the multiple exciton generation (MEG) processes, such as exciton-to-biexciton multiplication and biexciton-to-exciton recombination. BE collision integrals are computed using Kadanoff-Baym-Keldysh many-body perturbation theory based on density functional theory simulations, including exciton effects. We compute internal quantum efficiency (QE), which is the number of excitons generated from an absorbed photon in the course of the relaxation. We apply this approach to chiral single-wall carbon nanotubes (SWCNTs), such as (6,2) and (6,5). We predict efficient MEG in the (6,2) and (6,5) SWCNTs within the solar spectrum range starting at the 2E g energy threshold and with QE reaching ∼1.6 at about 3E g , where E g is the electronic gap.

Neuroplasticity of prehensile neural networks after quadriplegia.

PubMed

Di Rienzo, F; Guillot, A; Mateo, S; Daligault, S; Delpuech, C; Rode, G; Collet, C

2014-08-22

Targeting cortical neuroplasticity through rehabilitation-based practice is believed to enhance functional recovery after spinal cord injury (SCI). While prehensile performance is severely disturbed after C6-C7 SCI, subjects with tetraplegia can learn a compensatory passive prehension using the tenodesis effect. During tenodesis, an active wrist extension triggers a passive flexion of the fingers allowing grasping. We investigated whether motor imagery training could promote activity-dependent neuroplasticity and improve prehensile tenodesis performance. SCI participants (n=6) and healthy participants (HP, n=6) took part in a repeated measurement design. After an extended baseline period of 3 weeks including repeated magnetoencephalography (MEG) measurements, MI training was embedded within the classical course of physiotherapy for 5 additional weeks (three sessions per week). An immediate MEG post-test and a follow-up at 2 months were performed. Before MI training, compensatory activations and recruitment of deafferented cortical regions characterized the cortical activity during actual and imagined prehension in SCI participants. After MI training, MEG data yielded reduced compensatory activations. Cortical recruitment became similar to that in HP. Behavioral analysis evidenced decreased movement variability suggesting motor learning of tenodesis. Data suggest that MI training participated to reverse compensatory neuroplasticity in SCI participants, and promoted the integration of new upper limb prehensile coordination in the neural networks functionally dedicated to the control of healthy prehension before injury. Copyright © 2014 IBRO. Published by Elsevier Ltd. All rights reserved.

Directional information flow in patients with Alzheimer's disease. A source-space resting-state MEG study.

PubMed

Engels, M M A; Yu, M; Stam, C J; Gouw, A A; van der Flier, W M; Scheltens, Ph; van Straaten, E C W; Hillebrand, A

2017-01-01

In a recent magnetoencephalography (MEG) study, we found posterior-to-anterior information flow over the cortex in higher frequency bands in healthy subjects, with a reversed pattern in the theta band. A disruption of information flow may underlie clinical symptoms in Alzheimer's disease (AD). In AD, highly connected regions (hubs) in posterior areas are mostly disrupted. We therefore hypothesized that in AD the information flow from these hub regions would be disturbed. We used resting-state MEG recordings from 27 early-onset AD patients and 26 healthy controls. Using beamformer-based virtual electrodes, we estimated neuronal oscillatory activity for 78 cortical regions of interest (ROIs) and 12 subcortical ROIs of the AAL atlas, and calculated the directed phase transfer entropy (dPTE) as a measure of information flow between these ROIs. Group differences were evaluated using permutation tests and, for the AD group, associations between dPTE and general cognition or CSF biomarkers were determined using Spearman correlation coefficients. We confirmed the previously reported posterior-to-anterior information flow in the higher frequency bands in the healthy controls, and found it to be disturbed in the beta band in AD. Most prominently, the information flow from the precuneus and the visual cortex, towards frontal and subcortical structures, was decreased in AD. These disruptions did not correlate with cognitive impairment or CSF biomarkers. We conclude that AD pathology may affect the flow of information between brain regions, particularly from posterior hub regions, and that changes in the information flow in the beta band indicate an aspect of the pathophysiological process in AD.

Second Language Research Using Magnetoencephalography: A Review

ERIC Educational Resources Information Center

Schmidt, Gwen L.; Roberts, Timothy P. L.

2009-01-01

In this review we show how magnetoencephalography (MEG) is a constructive tool for language research and review MEG findings in second language (L2) research. MEG is the magnetic analog of electroencephalography (EEG), and its primary advantage over other cross-sectional (e.g. magnetic resonance imaging, or positron emission tomography) functional…

Canonical correlation analysis of synchronous neural interactions and cognitive deficits in Alzheimer's dementia

NASA Astrophysics Data System (ADS)

Karageorgiou, Elissaios; Lewis, Scott M.; Riley McCarten, J.; Leuthold, Arthur C.; Hemmy, Laura S.; McPherson, Susan E.; Rottunda, Susan J.; Rubins, David M.; Georgopoulos, Apostolos P.

2012-10-01

In previous work (Georgopoulos et al 2007 J. Neural Eng. 4 349-55) we reported on the use of magnetoencephalographic (MEG) synchronous neural interactions (SNI) as a functional biomarker in Alzheimer's dementia (AD) diagnosis. Here we report on the application of canonical correlation analysis to investigate the relations between SNI and cognitive neuropsychological (NP) domains in AD patients. First, we performed individual correlations between each SNI and each NP, which provided an initial link between SNI and specific cognitive tests. Next, we performed factor analysis on each set, followed by a canonical correlation analysis between the derived SNI and NP factors. This last analysis optimally associated the entire MEG signal with cognitive function. The results revealed that SNI as a whole were mostly associated with memory and language, and, slightly less, executive function, processing speed and visuospatial abilities, thus differentiating functions subserved by the frontoparietal and the temporal cortices. These findings provide a direct interpretation of the information carried by the SNI and set the basis for identifying specific neural disease phenotypes according to cognitive deficits.

Note: Unshielded bilateral magnetoencephalography system using two-dimensional gradiometers

NASA Astrophysics Data System (ADS)

Seki, Yusuke; Kandori, Akihiko; Ogata, Kuniomi; Miyashita, Tsuyoshi; Kumagai, Yukio; Ohnuma, Mitsuru; Konaka, Kuni; Naritomi, Hiroaki

2010-09-01

Magnetoencephalography (MEG) noninvasively measures neuronal activity with high temporal resolution. The aim of this study was to develop a new type of MEG system that can measure bilateral MEG waveforms without a magnetically shielded room, which is an obstacle to reducing both the cost and size of an MEG system. An unshielded bilateral MEG system was developed using four two-dimensional (2D) gradiometers and two symmetric cryostats. The 2D gradiometer, which is based on a low-Tc superconducting quantum interference device and wire-wound pickup coil detects a magnetic-field gradient in two orthogonal directions, or ∂/∂x(∂2Bz/∂z2), and reduces environmental magnetic-field noise by more than 50 dB. The cryostats can be symmetrically positioned in three directions: vertical, horizontal, and rotational. This makes it possible to detect bilateral neuronal activity in the cerebral cortex simultaneously. Bilateral auditory-evoked fields (AEF) of 18 elderly subjects were measured in an unshielded hospital environment using the MEG system. As a result, both the ipsilateral and the contralateral AEF component N100m, which is the magnetic counterpart of electric N100 in electroencephalography and appears about 100 ms after the onset of an auditory stimulus, were successfully detected for all the subjects. Moreover, the ipsilateral P50m and the contralateral P50m were also detected for 12 (67%) and 16 (89%) subjects, respectively. Experimental results demonstrate that the unshielded bilateral MEG system can detect MEG waveforms, which are associated with brain dysfunction such as epilepsy, Alzheimer's disease, and Down syndrome.

Magnetoencephalogram blind source separation and component selection procedure to improve the diagnosis of Alzheimer's disease patients.

PubMed

Escudero, Javier; Hornero, Roberto; Abásolo, Daniel; Fernández, Alberto; Poza, Jesús

2007-01-01

The aim of this study was to improve the diagnosis of Alzheimer's disease (AD) patients applying a blind source separation (BSS) and component selection procedure to their magnetoencephalogram (MEG) recordings. MEGs from 18 AD patients and 18 control subjects were decomposed with the algorithm for multiple unknown signals extraction. MEG channels and components were characterized by their mean frequency, spectral entropy, approximate entropy, and Lempel-Ziv complexity. Using Student's t-test, the components which accounted for the most significant differences between groups were selected. Then, these relevant components were used to partially reconstruct the MEG channels. By means of a linear discriminant analysis, we found that the BSS-preprocessed MEGs classified the subjects with an accuracy of 80.6%, whereas 72.2% accuracy was obtained without the BSS and component selection procedure.

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach

PubMed Central

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A.; Zhang, Wenbo

2016-01-01

Objective Combined source imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a non-invasive fashion. Source imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source imaging algorithms to both find the network nodes (regions of interest) and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Methods Source imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from inter-ictal and ictal signals recorded by EEG and/or MEG. Results Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ~20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Conclusion Our study indicates that combined source imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). Significance The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions. PMID:27740473

Noninvasive Electromagnetic Source Imaging and Granger Causality Analysis: An Electrophysiological Connectome (eConnectome) Approach.

PubMed

Sohrabpour, Abbas; Ye, Shuai; Worrell, Gregory A; Zhang, Wenbo; He, Bin

2016-12-01

Combined source-imaging techniques and directional connectivity analysis can provide useful information about the underlying brain networks in a noninvasive fashion. Source-imaging techniques have been used successfully to either determine the source of activity or to extract source time-courses for Granger causality analysis, previously. In this work, we utilize source-imaging algorithms to both find the network nodes [regions of interest (ROI)] and then extract the activation time series for further Granger causality analysis. The aim of this work is to find network nodes objectively from noninvasive electromagnetic signals, extract activation time-courses, and apply Granger analysis on the extracted series to study brain networks under realistic conditions. Source-imaging methods are used to identify network nodes and extract time-courses and then Granger causality analysis is applied to delineate the directional functional connectivity of underlying brain networks. Computer simulations studies where the underlying network (nodes and connectivity pattern) is known were performed; additionally, this approach has been evaluated in partial epilepsy patients to study epilepsy networks from interictal and ictal signals recorded by EEG and/or Magnetoencephalography (MEG). Localization errors of network nodes are less than 5 mm and normalized connectivity errors of ∼20% in estimating underlying brain networks in simulation studies. Additionally, two focal epilepsy patients were studied and the identified nodes driving the epileptic network were concordant with clinical findings from intracranial recordings or surgical resection. Our study indicates that combined source-imaging algorithms with Granger causality analysis can identify underlying networks precisely (both in terms of network nodes location and internodal connectivity). The combined source imaging and Granger analysis technique is an effective tool for studying normal or pathological brain conditions.

Altered Neural Oscillations During Multisensory Integration in Adolescents with Fetal Alcohol Spectrum Disorder.

PubMed

Bolaños, Alfredo D; Coffman, Brian A; Candelaria-Cook, Felicha T; Kodituwakku, Piyadasa; Stephen, Julia M

2017-12-01

Children with fetal alcohol spectrum disorder (FASD), who were exposed to alcohol in utero, display a broad range of sensory, cognitive, and behavioral deficits, which are broadly theorized to be rooted in altered brain function and structure. Based on the role of neural oscillations in multisensory integration from past studies, we hypothesized that adolescents with FASD would show a decrease in oscillatory power during event-related gamma oscillatory activity (30 to 100 Hz), when compared to typically developing healthy controls (HC), and that such decrease in oscillatory power would predict behavioral performance. We measured sensory neurophysiology using magnetoencephalography (MEG) during passive auditory, somatosensory, and multisensory (synchronous) stimulation in 19 adolescents (12 to 21 years) with FASD and 23 age- and gender-matched HC. We employed a cross-hemisphere multisensory paradigm to assess interhemispheric connectivity deficits in children with FASD. Time-frequency analysis of MEG data revealed a significant decrease in gamma oscillatory power for both unisensory and multisensory conditions in the FASD group relative to HC, based on permutation testing of significant group differences. Greater beta oscillatory power (15 to 30 Hz) was also noted in the FASD group compared to HC in both unisensory and multisensory conditions. Regression analysis revealed greater predictive power of multisensory oscillations from unisensory oscillations in the FASD group compared to the HC group. Furthermore, multisensory oscillatory power, for both groups, predicted performance on the Intra-Extradimensional Set Shift Task and the Cambridge Gambling Task. Altered oscillatory power in the FASD group may reflect a restricted ability to process somatosensory and multisensory stimuli during day-to-day interactions. These alterations in neural oscillations may be associated with the neurobehavioral deficits experienced by adolescents with FASD and may carry over to adulthood. Copyright © 2017 by the Research Society on Alcoholism.

A 20-channel magnetoencephalography system based on optically pumped magnetometers

NASA Astrophysics Data System (ADS)

Borna, Amir; Carter, Tony R.; Goldberg, Josh D.; Colombo, Anthony P.; Jau, Yuan-Yu; Berry, Christopher; McKay, Jim; Stephen, Julia; Weisend, Michael; Schwindt, Peter D. D.

2017-12-01

We describe a multichannel magnetoencephalography (MEG) system that uses optically pumped magnetometers (OPMs) to sense the magnetic fields of the human brain. The system consists of an array of 20 OPM channels conforming to the human subject’s head, a person-sized magnetic shield containing the array and the human subject, a laser system to drive the OPM array, and various control and data acquisition systems. We conducted two MEG experiments: auditory evoked magnetic field and somatosensory evoked magnetic field, on three healthy male subjects, using both our OPM array and a 306-channel Elekta-Neuromag superconducting quantum interference device (SQUID) MEG system. The described OPM array measures the tangential components of the magnetic field as opposed to the radial component measured by most SQUID-based MEG systems. Herein, we compare the results of the OPM- and SQUID-based MEG systems on the auditory and somatosensory data recorded in the same individuals on both systems.

Improving MEG source localizations: an automated method for complete artifact removal based on independent component analysis.

PubMed

Mantini, D; Franciotti, R; Romani, G L; Pizzella, V

2008-03-01

The major limitation for the acquisition of high-quality magnetoencephalography (MEG) recordings is the presence of disturbances of physiological and technical origins: eye movements, cardiac signals, muscular contractions, and environmental noise are serious problems for MEG signal analysis. In the last years, multi-channel MEG systems have undergone rapid technological developments in terms of noise reduction, and many processing methods have been proposed for artifact rejection. Independent component analysis (ICA) has already shown to be an effective and generally applicable technique for concurrently removing artifacts and noise from the MEG recordings. However, no standardized automated system based on ICA has become available so far, because of the intrinsic difficulty in the reliable categorization of the source signals obtained with this technique. In this work, approximate entropy (ApEn), a measure of data regularity, is successfully used for the classification of the signals produced by ICA, allowing for an automated artifact rejection. The proposed method has been tested using MEG data sets collected during somatosensory, auditory and visual stimulation. It was demonstrated to be effective in attenuating both biological artifacts and environmental noise, in order to reconstruct clear signals that can be used for improving brain source localizations.

The preference of probability over negative values in action selection.

PubMed

Neyedli, Heather F; Welsh, Timothy N

2015-01-01

It has previously been found that when participants are presented with a pair of motor prospects, they can select the prospect with the largest maximum expected gain (MEG). Many of those decisions, however, were trivial because of large differences in MEG between the prospects. The purpose of the present study was to explore participants' preferences when making non-trivial decisions between two motor prospects. Participants were presented with pairs of prospects that: 1) differed in MEG with either only the values or only the probabilities differing between the prospects; and 2) had similar MEG with one prospect having a larger probability of hitting the target and a higher penalty value and the other prospect a smaller probability of hitting the target but a lower penalty value. In different experiments, participants either had 400 ms or 2000 ms to decide between the prospects. It was found that participants chose the configuration with the larger MEG more often when the probability varied between prospects than when the value varied. In pairs with similar MEGs, participants preferred a larger probability of hitting the target over a smaller penalty value. These results indicate that participants prefer probability information over negative value information in a motor selection task.

Two magneto-encephalographic epileptic foci did not coincide with the electrocorticographic ictal onset zone in a patient with temporal lobe epilepsy.

PubMed

Hisada, K; Morioka, T; Nishio, S; Yamamoto, T; Fukui, M

2001-12-01

To evaluate the usefulness and limitations of magneto-encephalography (MEG) for epilepsy surgery, we compared 'interictal' epileptic spike fields on MEG with ictal electrocorticography (ECoG) using invasive chronic subdural electrodes in a patient with intractable medial temporal lobe epilepsy (MTLE) associated with vitamin K deficiency intracerebral hemorrhage. A 19-year-old male with an 8-year history of refractory complex partial seizures, secondarily generalized, and right hemispheric atrophy and porencephaly in the right frontal lobe on MRI, was studied with MEG to define the interictal paroxysmal sources based on the single-dipole model. This was followed by invasive ECoG monitoring to delineate the epileptogenic zone. MEG demonstrated two paroxysmal foci, one each on the right lateral temporal and frontal lobes. Ictal ECoG recordings revealed an ictal onset zone on the right medial temporal lobe, which was different from that defined by MEG. Anterior temporal lobectomy with hippocampectomy was performed and the patient has been seizure free for two years. Our results indicate that interictal MEG does not always define the epileptogenic zone in patients with MTLE.

Resting-State Oscillatory Activity in Children Born Small for Gestational Age: An MEG Study

PubMed Central

Boersma, Maria; de Bie, Henrica M. A.; Oostrom, Kim J.; van Dijk, Bob W.; Hillebrand, Arjan; van Wijk, Bernadette C. M.; Delemarre-van de Waal, Henriëtte A.; Stam, Cornelis J.

2013-01-01

Growth restriction in utero during a period that is critical for normal growth of the brain, has previously been associated with deviations in cognitive abilities and brain anatomical and functional changes. We measured magnetoencephalography (MEG) in 4- to 7-year-old children to test if children born small for gestational age (SGA) show deviations in resting-state brain oscillatory activity. Children born SGA with postnatally spontaneous catch-up growth [SGA+; six boys, seven girls; mean age 6.3 year (SD = 0.9)] and children born appropriate for gestational age [AGA; seven boys, three girls; mean age 6.0 year (SD = 1.2)] participated in a resting-state MEG study. We calculated absolute and relative power spectra and used non-parametric statistics to test for group differences. SGA+ and AGA born children showed no significant differences in absolute and relative power except for reduced absolute gamma band power in SGA children. At the time of MEG investigation, SGA+ children showed significantly lower head circumference (HC) and a trend toward lower IQ, however there was no association of HC or IQ with absolute or relative power. Except for reduced absolute gamma band power, our findings suggest normal brain activity patterns at school age in a group of children born SGA in which spontaneous catch-up growth of bodily length after birth occurred. Although previous findings suggest that being born SGA alters brain oscillatory activity early in neonatal life, we show that these neonatal alterations do not persist at early school age when spontaneous postnatal catch-up growth occurs after birth. PMID:24068993

Radiation Hardness tests with neutron flux on different Silicon photomultiplier devices

NASA Astrophysics Data System (ADS)

Cattaneo, P. W.; Cervi, T.; Menegolli, A.; Oddone, M.; Prata, M.; Prata, M. C.; Rossella, M.

2017-07-01

Radiation hardness is an important requirement for solid state readout devices operating in high radiation environments common in particle physics experiments. The MEG II experiment, at PSI, Switzerland, investigates the forbidden decay μ+ → e+ γ. Exploiting the most intense muon beam of the world. A significant flux of non-thermal neutrons (kinetic energy Ek>= 0.5 MeV) is present in the experimental hall produced along the beam-line and in the hall itself. We present the effects of neutron fluxes comparable to the MEG II expected doses on several Silicon Photomultiplier (SiPMs). The tested models are: AdvanSiD ASD-NUV3S-P50 (used in MEG II experiment), AdvanSiD ASD-NUV3S-P40, AdvanSiD ASD-RGB3S-P40, Hamamatsu and Excelitas C30742-33-050-X. The neutron source is the thermal Sub-critical Multiplication complex (SM1) moderated with water, located at the University of Pavia (Italy). We report the change of SiPMs most important electric parameters: dark current, dark pulse frequency, gain, direct bias resistance, as a function of the integrated neutron fluency.

Analyzing EEG and MEG signals recorded during tES, a reply.

PubMed

Noury, Nima; Siegel, Markus

2018-02-15

Transcranial Electric Stimulation (tES) is a widely used non-invasive brain stimulation technique. However, strong stimulation artifacts complicate the investigation of neural activity with EEG or MEG during tES. Thus, studying brain signals during tES requires detailed knowledge about the properties of these artifacts. Recently, we characterized the phase- and amplitude-relationship between tES stimulation currents and tES artifacts in EEG and MEG and provided a mathematical model of these artifacts (Noury and Siegel, 2017, and Noury et al., 2016, respectively). Among several other features, we showed that, independent of the stimulation current, the amplitude of tES artifacts is modulated time locked to heartbeat and respiration. In response to our work, a recent paper (Neuling et al., 2017) raised several points concerning the employed stimulation device and methodology. Here, we discuss these points, explain potential misunderstandings, and show that none of the raised concerns are applicable to our results. Furthermore, we explain in detail the physics underlying tES artifacts, and discuss several approaches how to study brain function during tES in the presence of residual artifacts. Copyright © 2017 Elsevier Inc. All rights reserved.

Emotion processing in the visual brain: a MEG analysis.

PubMed

Peyk, Peter; Schupp, Harald T; Elbert, Thomas; Junghöfer, Markus

2008-06-01

Recent functional magnetic resonance imaging (fMRI) and event-related brain potential (ERP) studies provide empirical support for the notion that emotional cues guide selective attention. Extending this line of research, whole head magneto-encephalogram (MEG) was measured while participants viewed in separate experimental blocks a continuous stream of either pleasant and neutral or unpleasant and neutral pictures, presented for 330 ms each. Event-related magnetic fields (ERF) were analyzed after intersubject sensor coregistration, complemented by minimum norm estimates (MNE) to explore neural generator sources. Both streams of analysis converge by demonstrating the selective emotion processing in an early (120-170 ms) and a late time interval (220-310 ms). ERF analysis revealed that the polarity of the emotion difference fields was reversed across early and late intervals suggesting distinct patterns of activation in the visual processing stream. Source analysis revealed the amplified processing of emotional pictures in visual processing areas with more pronounced occipito-parieto-temporal activation in the early time interval, and a stronger engagement of more anterior, temporal, regions in the later interval. Confirming previous ERP studies showing facilitated emotion processing, the present data suggest that MEG provides a complementary look at the spread of activation in the visual processing stream.

Gamma band activity associated with BCI performance: simultaneous MEG/EEG study.

PubMed

Ahn, Minkyu; Ahn, Sangtae; Hong, Jun H; Cho, Hohyun; Kim, Kiwoong; Kim, Bong S; Chang, Jin W; Jun, Sung C

2013-01-01

While brain computer interface (BCI) can be employed with patients and healthy subjects, there are problems that must be resolved before BCI can be useful to the public. In the most popular motor imagery (MI) BCI system, a significant number of target users (called "BCI-Illiterates") cannot modulate their neuronal signals sufficiently to use the BCI system. This causes performance variability among subjects and even among sessions within a subject. The mechanism of such BCI-Illiteracy and possible solutions still remain to be determined. Gamma oscillation is known to be involved in various fundamental brain functions, and may play a role in MI. In this study, we investigated the association of gamma activity with MI performance among subjects. Ten simultaneous MEG/EEG experiments were conducted; MI performance for each was estimated by EEG data, and the gamma activity associated with BCI performance was investigated with MEG data. Our results showed that gamma activity had a high positive correlation with MI performance in the prefrontal area. This trend was also found across sessions within one subject. In conclusion, gamma rhythms generated in the prefrontal area appear to play a critical role in BCI performance.

Prestimulus Network Integration of Auditory Cortex Predisposes Near-Threshold Perception Independently of Local Excitability

PubMed Central

Leske, Sabine; Ruhnau, Philipp; Frey, Julia; Lithari, Chrysa; Müller, Nadia; Hartmann, Thomas; Weisz, Nathan

2015-01-01

An ever-increasing number of studies are pointing to the importance of network properties of the brain for understanding behavior such as conscious perception. However, with regards to the influence of prestimulus brain states on perception, this network perspective has rarely been taken. Our recent framework predicts that brain regions crucial for a conscious percept are coupled prior to stimulus arrival, forming pre-established pathways of information flow and influencing perceptual awareness. Using magnetoencephalography (MEG) and graph theoretical measures, we investigated auditory conscious perception in a near-threshold (NT) task and found strong support for this framework. Relevant auditory regions showed an increased prestimulus interhemispheric connectivity. The left auditory cortex was characterized by a hub-like behavior and an enhanced integration into the brain functional network prior to perceptual awareness. Right auditory regions were decoupled from non-auditory regions, presumably forming an integrated information processing unit with the left auditory cortex. In addition, we show for the first time for the auditory modality that local excitability, measured by decreased alpha power in the auditory cortex, increases prior to conscious percepts. Importantly, we were able to show that connectivity states seem to be largely independent from local excitability states in the context of a NT paradigm. PMID:26408799

Elucidating the neurophysiological underpinnings of autism spectrum disorder: new developments.

PubMed

Luckhardt, C; Jarczok, T A; Bender, S

2014-09-01

The study of neurophysiological approaches together with rare and common risk factors for Autism Spectrum Disorder (ASD) allows elucidating the specific underlying neurobiology of ASD. Whereas most neurophysiologically based research in ASD to date has focussed on case-control differences based on the DSM- or ICD-based categorical ASD diagnosis, more recent studies have aimed at studying genetically and/or neurophysiologically defined homogeneous ASD subgroups for specific neuronal biomarkers. This review addresses the neurophysiological investigation of ASD by evoked and event-related potentials, by EEG/MEG connectivity measures such as coherence, and transcranial magnetic stimulation. As an example of classical neurophysiological studies in ASD, we report event-related potential studies which have illustrated which brain areas and processing stages are affected in the visual perception of socially relevant stimuli. However, a paradigm shift has taken place in recent years focussing on how these findings can be tracked down to basic neuronal functions such as deficits in cortico-cortical connectivity and the interaction between brain areas. Disconnectivity, for example, can again be related to genetically induced shifts in the excitation/inhibition balance. Genetic causes of ASD may be grouped by their effects on the brain's system level to identify ASD subgroups which respond differentially to therapeutic interventions.

A Comparative Study on the Detection of Covert Attention in Event-Related EEG and MEG Signals to Control a BCI

PubMed Central

Reichert, Christoph; Dürschmid, Stefan; Heinze, Hans-Jochen; Hinrichs, Hermann

2017-01-01

In brain-computer interface (BCI) applications the detection of neural processing as revealed by event-related potentials (ERPs) is a frequently used approach to regain communication for people unable to interact through any peripheral muscle control. However, the commonly used electroencephalography (EEG) provides signals of low signal-to-noise ratio, making the systems slow and inaccurate. As an alternative noninvasive recording technique, the magnetoencephalography (MEG) could provide more advantageous electrophysiological signals due to a higher number of sensors and the magnetic fields not being influenced by volume conduction. We investigated whether MEG provides higher accuracy in detecting event-related fields (ERFs) compared to detecting ERPs in simultaneously recorded EEG, both evoked by a covert attention task, and whether a combination of the modalities is advantageous. In our approach, a detection algorithm based on spatial filtering is used to identify ERP/ERF components in a data-driven manner. We found that MEG achieves higher decoding accuracy (DA) compared to EEG and that the combination of both further improves the performance significantly. However, MEG data showed poor performance in cross-subject classification, indicating that the algorithm's ability for transfer learning across subjects is better in EEG. Here we show that BCI control by covert attention is feasible with EEG and MEG using a data-driven spatial filter approach with a clear advantage of the MEG regarding DA but with a better transfer learning in EEG. PMID:29085279

Reliable Early Classification on Multivariate Time Series with Numerical and Categorical Attributes

DTIC Science & Technology

2015-05-22

design a procedure of feature extraction in REACT named MEG (Mining Equivalence classes with shapelet Generators) based on the concept of...Equivalence Classes Mining [12, 15]. MEG can efficiently and effectively generate the discriminative features. In addition, several strategies are proposed...technique of parallel computing [4] to propose a process of pa- rallel MEG for substantially reducing the computational overhead of discovering shapelet

Assessment of the Utility of Ictal Magnetoencephalography in the Localization of the Epileptic Seizure Onset Zone.

PubMed

Alkawadri, Rafeed; Burgess, Richard C; Kakisaka, Yosuke; Mosher, John C; Alexopoulos, Andreas V

2018-06-11

Literature on ictal magnetoencephalography (MEG) in clinical practice and the relationship to other modalities is limited because of the brevity of routine studies. To investigate the utility and reliability of ictal MEG in the localization of the epileptogenic zone. A retrospective medical record review and prospective analysis of a novel ictal rhythm analysis method was conducted at a tertiary epilepsy center with a wide base of referrals for epilepsy surgery evaluation and included consecutive cases of patients who experienced epileptic seizures during routine MEG studies from March 2008 to February 2012. A total of 377 studies screened. Data were analyzed from November 2011 to October 2015. Presurgical workup and interictal and ictal MEG data were reviewed. The localizing value of using extended-source localization of a narrow band identified visually at onset was analyzed. Of the 44 included patients, the mean (SD) age at the time of recording was 19.3 (14.9) years, and 25 (57%) were male. The mean duration of recording was 51.2 minutes. Seizures were provoked by known triggers in 3 patients and were spontaneous otherwise. Twenty-five patients (57%) had 1 seizure, 6 (14%) had 2, and 13 (30%) had 3 or more. Magnetoencephalography single equivalent current dipole analysis was possible in 29 patients (66%), of whom 8 (28%) had no clear interictal discharges. Sublobar concordance between ictal and interictal dipoles was seen in 18 of 21 patients (86%). Three patients (7%) showed clear ictal MEG patterns without electroencephalography changes. Ictal MEG dipoles correlated with the lobe of onset in 7 of 8 patients (88%) who underwent intracranial electroencephalography evaluations. Reasons for failure to identify ictal dipoles included diffuse or poor dipolar ictal patterns, no MEG changes, and movement artifact. Resection of areas containing a minimum-norm estimate of a narrow band at onset, not single equivalent current dipole, was associated with sustained seizure freedom. Ictal MEG data can provide reliable localization, including in cases that are difficult to localize by other modalities. These findings support the use of extended-source localization for seizures recorded during MEG.

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults.

PubMed

Tsvetanov, Kamen A; Henson, Richard N A; Tyler, Lorraine K; Davis, Simon W; Shafto, Meredith A; Taylor, Jason R; Williams, Nitin; Cam-Can; Rowe, James B

2015-06-01

In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood-oxygenation level-dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting-state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath-hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age-related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population-based Cambridge Centre for Ageing and Neuroscience cohort (Cam-CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task-based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects of age on task-based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing. The results from the mediation analysis demonstrate that RSFA is modulated by measures of vascular function and is not driven solely by changes in the variance of neural activity. Based on these findings we propose that the RSFA scaling method is articularly useful in large scale and longitudinal neuroimaging studies of ageing, or with frail participants, where alternative measures of vascular reactivity are impractical. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

The effect of ageing on fMRI: Correction for the confounding effects of vascular reactivity evaluated by joint fMRI and MEG in 335 adults

PubMed Central

Henson, Richard N. A.; Tyler, Lorraine K.; Davis, Simon W.; Shafto, Meredith A.; Taylor, Jason R.; Williams, Nitin; Cam‐CAN; Rowe, James B.

2015-01-01

Abstract In functional magnetic resonance imaging (fMRI) research one is typically interested in neural activity. However, the blood‐oxygenation level‐dependent (BOLD) signal is a composite of both neural and vascular activity. As factors such as age or medication may alter vascular function, it is essential to account for changes in neurovascular coupling when investigating neurocognitive functioning with fMRI. The resting‐state fluctuation amplitude (RSFA) in the fMRI signal (rsfMRI) has been proposed as an index of vascular reactivity. The RSFA compares favourably with other techniques such as breath‐hold and hypercapnia, but the latter are more difficult to perform in some populations, such as older adults. The RSFA is therefore a candidate for use in adjusting for age‐related changes in vascular reactivity in fMRI studies. The use of RSFA is predicated on its sensitivity to vascular rather than neural factors; however, the extent to which each of these factors contributes to RSFA remains to be characterized. The present work addressed these issues by comparing RSFA (i.e., rsfMRI variability) to proxy measures of (i) cardiovascular function in terms of heart rate (HR) and heart rate variability (HRV) and (ii) neural activity in terms of resting state magnetoencephalography (rsMEG). We derived summary scores of RSFA, a sensorimotor task BOLD activation, cardiovascular function and rsMEG variability for 335 healthy older adults in the population‐based Cambridge Centre for Ageing and Neuroscience cohort (Cam‐CAN; www.cam-can.com). Mediation analysis revealed that the effects of ageing on RSFA were significantly mediated by vascular factors, but importantly not by the variability in neuronal activity. Furthermore, the converse effects of ageing on the rsMEG variability were not mediated by vascular factors. We then examined the effect of RSFA scaling of task‐based BOLD in the sensorimotor task. The scaling analysis revealed that much of the effects of age on task‐based activation studies with fMRI do not survive correction for changes in vascular reactivity, and are likely to have been overestimated in previous fMRI studies of ageing. The results from the mediation analysis demonstrate that RSFA is modulated by measures of vascular function and is not driven solely by changes in the variance of neural activity. Based on these findings we propose that the RSFA scaling method is articularly useful in large scale and longitudinal neuroimaging studies of ageing, or with frail participants, where alternative measures of vascular reactivity are impractical. Hum Brain Mapp 36:2248–2269, 2015. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:25727740

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals.

PubMed

Kauppi, Jukka-Pekka; Kandemir, Melih; Saarinen, Veli-Matti; Hirvenkari, Lotta; Parkkonen, Lauri; Klami, Arto; Hari, Riitta; Kaski, Samuel

2015-05-15

We hypothesize that brain activity can be used to control future information retrieval systems. To this end, we conducted a feasibility study on predicting the relevance of visual objects from brain activity. We analyze both magnetoencephalographic (MEG) and gaze signals from nine subjects who were viewing image collages, a subset of which was relevant to a predetermined task. We report three findings: i) the relevance of an image a subject looks at can be decoded from MEG signals with performance significantly better than chance, ii) fusion of gaze-based and MEG-based classifiers significantly improves the prediction performance compared to using either signal alone, and iii) non-linear classification of the MEG signals using Gaussian process classifiers outperforms linear classification. These findings break new ground for building brain-activity-based interactive image retrieval systems, as well as for systems utilizing feedback both from brain activity and eye movements. Copyright © 2015 Elsevier Inc. All rights reserved.

A 20-channel magnetoencephalography system based on optically pumped magnetometers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Borna, Amir; Carter, Tony R.; Goldberg, Josh D.

In this paper, we describe a multichannel magnetoencephalography (MEG) system that uses optically pumped magnetometers (OPMs) to sense the magnetic fields of the human brain. The system consists of an array of 20 OPM channels conforming to the human subject's head, a person-sized magnetic shield containing the array and the human subject, a laser system to drive the OPM array, and various control and data acquisition systems. We conducted two MEG experiments: auditory evoked magnetic field and somatosensory evoked magnetic field, on three healthy male subjects, using both our OPM array and a 306-channel Elekta-Neuromag superconducting quantum interference device (SQUID)more » MEG system. The described OPM array measures the tangential components of the magnetic field as opposed to the radial component measured by most SQUID-based MEG systems. Finally, herein, we compare the results of the OPM- and SQUID-based MEG systems on the auditory and somatosensory data recorded in the same individuals on both systems.« less

A 20-channel magnetoencephalography system based on optically pumped magnetometers

DOE PAGES

Borna, Amir; Carter, Tony R.; Goldberg, Josh D.; ...

2017-10-16

In this paper, we describe a multichannel magnetoencephalography (MEG) system that uses optically pumped magnetometers (OPMs) to sense the magnetic fields of the human brain. The system consists of an array of 20 OPM channels conforming to the human subject's head, a person-sized magnetic shield containing the array and the human subject, a laser system to drive the OPM array, and various control and data acquisition systems. We conducted two MEG experiments: auditory evoked magnetic field and somatosensory evoked magnetic field, on three healthy male subjects, using both our OPM array and a 306-channel Elekta-Neuromag superconducting quantum interference device (SQUID)more » MEG system. The described OPM array measures the tangential components of the magnetic field as opposed to the radial component measured by most SQUID-based MEG systems. Finally, herein, we compare the results of the OPM- and SQUID-based MEG systems on the auditory and somatosensory data recorded in the same individuals on both systems.« less

Monitoring Neurocognitive Performance and Electrophysiological Activity After Mild Traumatic Brain Injury (mTBI)

DTIC Science & Technology

2014-03-01

return to duty’ decisions. 15. SUBJECT TERMS Traumatic Brain Injury, mTBI, concussion, Magnetoencephalography, MEG , MRI, biomarkers, actigraphy 16...within approximately two years of the writing of this report. 3. KEYWORDS Traumatic Brain Injury, mTBI, concussion, Magnetoencephalography, MEG , MRI...Merrifield, PhD) i. Magnetoencephalography ( MEG ) laboratory is fully operational after two weeks of cool down and testing in February 2014. Pilot testing

Marine Resiliency Study II

DTIC Science & Technology

2016-07-06

prevention or treatment protocols, or the use of new technology (e.g. MEG ). 5. In coordination with HQMC, NIMH and Army STARRS, to determine...experimental designs such as targeted prevention or treatment protocols or the use of new technology (e.g. MEG ) to identify biomarkers. A specific goal of the...blast sensors, and to analyze MEG data in relation to blast event outcomes during field training. Of the enrolled Marines in the Demonstration Project 4

Multiple Exciton Generation in Semiconductor Nanostructures: DFT-based Computation

NASA Astrophysics Data System (ADS)

Mihaylov, Deyan; Kryjevski, Andrei; Kilin, Dmitri; Kilina, Svetlana; Vogel, Dayton

Multiple exciton generation (MEG) in nm-sized H-passivated Si nanowires (NWs), and quasi 2D nanofilms depends strongly on the degree of the core structural disorder as shown by the perturbation theory calculations based on the DFT simulations. In perturbation theory, we work to the 2nd order in the electron-photon coupling and in the (approximate) RPA-screened Coulomb interaction. We also include the effect of excitons for which we solve Bethe-Salpeter Equation. To describe MEG we calculate exciton-to-biexciton as well as biexciton-to-exciton rates and quantum efficiency (QE). We consider 3D arrays of Si29H36 quantum dots, NWs, and quasi 2D silicon nanofilms, all with both crystalline and amorphous core structures. Efficient MEG with QE of 1.3 up to 1.8 at the photon energy of about 3Egap is predicted in these nanoparticles except for the crystalline NW and film where QE ~=1. MEG in the amorphous nanoparticles is enhanced by the electron localization due to structural disorder. The exciton effects significantly red-shift QE vs. photon energy curves. Nm-sized a-Si NWs and films are predicted to have effective MEG within the solar spectrum range. Also, we find efficient MEG in the chiral single-wall Carbon nanotubes and in a perovskite nanostructure.

Localization of MEG human brain responses to retinotopic visual stimuli with contrasting source reconstruction approaches

PubMed Central

Cicmil, Nela; Bridge, Holly; Parker, Andrew J.; Woolrich, Mark W.; Krug, Kristine

2014-01-01

Magnetoencephalography (MEG) allows the physiological recording of human brain activity at high temporal resolution. However, spatial localization of the source of the MEG signal is an ill-posed problem as the signal alone cannot constrain a unique solution and additional prior assumptions must be enforced. An adequate source reconstruction method for investigating the human visual system should place the sources of early visual activity in known locations in the occipital cortex. We localized sources of retinotopic MEG signals from the human brain with contrasting reconstruction approaches (minimum norm, multiple sparse priors, and beamformer) and compared these to the visual retinotopic map obtained with fMRI in the same individuals. When reconstructing brain responses to visual stimuli that differed by angular position, we found reliable localization to the appropriate retinotopic visual field quadrant by a minimum norm approach and by beamforming. Retinotopic map eccentricity in accordance with the fMRI map could not consistently be localized using an annular stimulus with any reconstruction method, but confining eccentricity stimuli to one visual field quadrant resulted in significant improvement with the minimum norm. These results inform the application of source analysis approaches for future MEG studies of the visual system, and indicate some current limits on localization accuracy of MEG signals. PMID:24904268

The brain in time: insights from neuromagnetic recordings.

PubMed

Hari, Riitta; Parkkonen, Lauri; Nangini, Cathy

2010-03-01

The millisecond time resolution of magnetoencephalography (MEG) is instrumental for investigating the brain basis of sensory processing, motor planning, cognition, and social interaction. We review the basic principles, recent progress, and future potential of MEG in noninvasive tracking of human brain activity. Cortical activation sequences from tens to hundreds of milliseconds can be followed during, e.g., perception, motor action, imitation, and language processing by recording both spontaneous and evoked brain signals. Moreover, tagging of sensory input can be used to reveal neuronal mechanisms of binaural interaction and perception of ambiguous images. The results support the emerging ideas of multiple, hierarchically organized temporal scales in human brain function. Instrumentation and data analysis methods are rapidly progressing, enabling attempts to decode the four-dimensional spatiotemporal signal patterns to reveal correlates of behavior and mental contents.

MEG-guided analysis of 7T-MRI in patients with epilepsy.

PubMed

Colon, A J; Osch, M J P van; Buijs, M; Grond, J V D; Hillebrand, A; Schijns, O; Wagner, G J; Ossenblok, P; Hofman, P; Buchem, M A V; Boon, P

2018-05-26

To study possible detection of structural abnormalities on 7T MRI that were not detected on 3T MRI and estimate the added value of MEG-guidance. For abnormalities found, analysis of convergence between clinical, MEG and 7T MRI localization of suspected epileptogenic foci. In adult patients with well-documented localization-related epilepsy in whom a previous 3T MRI did not demonstrate an epileptogenic lesion but MEG indicated a plausible epileptogenic focus, 7T MRI was performed. Based on semiologic data, visual analysis of the 7T images was performed as well as based on prior MEG results. Correlation with other data from the patient charts, for as far as these were available, was analysed. To establish the level of concordance between the three observers the generalized or Fleiss kappa was calculated. In 3/19 patients abnormalities that, based on semiology, could plausibly represent an epileptogenic lesion were detected using 7T MRI. In an additional 3/19 an abnormality was detected after MEG-guidance. However, in these later cases there was no concordance among the three observers with regard to the presence of a structural abnormality. In one of these three cases intracranial recording was performed, proving the possible abnormality on 7T MRI to be the epileptogenic focus. In 32% of patients 7T MRI showed abnormalities that could indicate an epileptogenic lesion whereas previous 3T MRI did not, especially when visual inspection was guided by the presence of focal interictal MEG abnormalities. Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Myricetin and methyl eugenol combination enhances the anticancer activity, cell cycle arrest and apoptosis induction of cis-platin against HeLa cervical cancer cell lines

PubMed Central

Yi, Jin-Ling; Shi, Song; Shen, Yan-Li; Wang, Ling; Chen, Hai-Yan; Zhu, Jun; Ding, Yan

2015-01-01

Drug combination therapies are common practice in the treatment of cancer. In this study, we evaluated the anticancer effects of myricetin (MYR), methyl eugenol (MEG) and cisplatin (CP) both separately as well as in combination against cervical cancer (HeLa) cells. To demonstrate whether MYR and MEG enhance the anticancer activity of CP against cervical cancer cells, we treated HeLa cells with MYR and MEG alone or in combination with cisplatin and evaluated cell growth and apoptosis using MTT (3 (4, 5 dimethyl thiazol 2yl) 2, 5 diphenyltetrazolium bromide) assay, LDH release assay, flow cytometry and fluorescence microscopy. The results revealed that, as compared to single drug treatment, the combination of MYR or MEG with CP resulted in greater effect in inhibiting cancer cell growth and inducing apoptosis. Cell apoptosis induction, Caspase-3 activity, cell cycle arrest and mitochondrial membrane potential loss were systematically studied to reveal the mechanisms of synergy between MYR, MEG and CP. Combination of MYR or MEG with CP resulted in more potent apoptosis induction as revealed by fluorescence microscopy using Hoechst 33258 and AO-ETBR staining. The combination treatment also increased the number of cells in G0/G1 phase dramatically as compared to single drug treatment. Mitochondrial membrane potential loss (ΛΨm) as well as Caspase-3 activity was much higher in combination treatment as compared to single drug treatment. Findings of this investigation suggest that MYR and MEG combined with cisplatin is a potential clinical chemotherapeutic approach in human cervical cancer. PMID:25972998

Reactive Melt Extrusion To Improve the Dissolution Performance and Physical Stability of Naproxen Amorphous Solid Dispersions.

PubMed

Liu, Xu; Zhou, Lin; Zhang, Feng

2017-03-06

The purpose of this study was to investigate the reaction between naproxen (NPX) and meglumine (MEG) at elevated temperature and to study the effect of this reaction on the physical stabilities and in vitro drug-release properties of melt-extruded naproxen amorphous solid dispersions (ASDs). Differential scanning calorimetry, hot-stage polarized light microscopy, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy analyses demonstrated that in situ salt formation with proton transfer between NPX and MEG occurred at elevated temperature during the melt extrusion process. The amorphous NPX-MEG salt was physically most stable when two components were present at a 1:1 molar ratio. Polymeric carriers, including povidone, copovidone, and SOLUPLUS, did not interfere with the reaction between NPX and MEG during melt extrusion. Compared to the traditional NPX ASDs consisting of NPX and polymer only, NPX-MEG ASDs were physically more stable and remained amorphous following four months storage at 40 °C and 75% RH (relative humidity). Based on nonsink dissolution testing and polarized light microscopy analyses, we concluded that the conventional NPX ASDs composed of NPX and polymers failed to improve the NPX dissolution rate due to the rapid recrystallization of NPX in contact with aqueous medium. The dissolution rate of NPX-MEG ASDs was two times greater than the corresponding physical mixtures and conventional NPX ASDs. This study demonstrated that the acid-base reaction between NPX and MEG during melt extrusion significantly improved the physical stability and the dissolution rate of NPX ASDs.

Increase of Total Nephron Albumin Filtration and Reabsorption in Diabetic Nephropathy.

PubMed

Mori, Keita P; Yokoi, Hideki; Kasahara, Masato; Imamaki, Hirotaka; Ishii, Akira; Kuwabara, Takashige; Koga, Kenichi; Kato, Yukiko; Toda, Naohiro; Ohno, Shoko; Kuwahara, Koichiro; Endo, Tomomi; Nakao, Kazuwa; Yanagita, Motoko; Mukoyama, Masashi; Mori, Kiyoshi

2017-01-01

The amount of albumin filtered through the glomeruli and reabsorbed at the proximal tubules in normal and in diabetic kidneys is debated. The megalin/cubilin complex mediates protein reabsorption, but genetic knockout of megalin is perinatally lethal. To overcome current technical problems, we generated a drug-inducible megalin-knockout mouse line, megalin(lox/lox);Ndrg1-CreER T2 (iMegKO), in which megalin expression can be shut off at any time by administration of tamoxifen (Tam). Tam administration in adult iMegKO mice decreased the expression of renal megalin protein by 92% compared with that in wild-type C57BL/6J mice and almost completely abrogated renal reabsorption of intravenously injected retinol-binding protein. Furthermore, urinary albumin excretion increased to 175 μg/d (0.46 mg albumin/mg creatinine) in Tam-treated iMegKO mice, suggesting that this was the amount of total nephron albumin filtration. By comparing Tam-treated, streptozotocin-induced diabetic iMegKO mice with Tam-treated nondiabetic iMegKO mice, we estimated that the development of diabetes led to a 1.9-fold increase in total nephron albumin filtration, a 1.8-fold increase in reabsorption, and a significant reduction in reabsorption efficiency (86% efficiency versus 96% efficiency in nondiabetic mice). Insulin treatment normalized these abnormalities. Akita;iMegKO mice, another model of type 1 diabetes, showed equivalent results. Finally, nondiabetic iMegKO mice had a glomerular sieving coefficient of albumin of 1.7×10 -5 , which approximately doubled in diabetic iMegKO mice. This study reveals actual values and changes of albumin filtration and reabsorption in early diabetic nephropathy in mice, bringing new insights to our understanding of renal albumin dynamics associated with the hyperfiltration status of diabetic nephropathy. Copyright © 2016 by the American Society of Nephrology.

Phytoremediation of ethylene glycol and its derivatives by the burhead plant (Echinodorus cordifolius (L.)): effect of molecular size.

PubMed

Teamkao, Pattrarat; Thiravetyan, Paitip

2010-11-01

Ethylene glycol (EG) is a group of dihydroxy alcohol that has been utilised in a variety of industrial and residential settings. EG contaminated wastewater has a high chemical oxygen demand (COD), which causes environmental problems. The aim of this research was to investigate the efficiency of the burhead plant (Echinodorus cordifolius (L.)) in the removal of mono-, di- and triethylene glycol (MEG, DEG and TEG), the first three members of the dihydroxy alcohol group, from synthetic wastewaters, to examine the toxic effect of EG on the plant and to identify differences among MEG, DEG, and TEG removal. It was found that the COD of synthetic wastewaters decreased to levels below the standard effluent (COD=120 mg L⁻¹) on day 18, 21 and 33 for MEG, DEG and TEG, respectively. On day 18 of the experiment, the burhead plant removed approximately 2000, 1950 and 730 mg L⁻¹ of MEG, DEG and TEG, respectively. The removal rate of MEG was faster than that of DEG and TEG, suggesting that the molecular size of the EG had affected its rate of removal. The concentrations of MEG, DEG, and TEG in plant tissue were measured to show that burhead can take up EG, and the major site of EG accumulation is the leaf. The molar of MEG that was taken up into the plant leaf was higher than that of DEG and TEG. This suggested that EG of smaller molecular sizes can be taken up more rapidly by the plant than EG of larger molecular sizes. EG concentrations in the leaf increased to a peak concentration and then slowly decreased. GC-MS analysis of DEG-treated plant tissue found MEG, 1,4-dioxan-2-one, neophytadiene, and 2-propenamide, that may be DEG-degradation products and/or compounds that are induced when plants are exposed to DEG. The result indicates that burhead can potentially be used for EG removal. Copyright © 2010 Elsevier Ltd. All rights reserved.

Magnetoencephalography and ictal SPECT in patients with failed epilepsy surgery.

PubMed

El Tahry, Riёm; Wang, Z Irene; Thandar, Aung; Podkorytova, Irina; Krishnan, Balu; Tousseyn, Simon; Guiyun, Wu; Burgess, Richard C; Alexopoulos, Andreas V

2018-06-06

Selected patients with intractable focal epilepsy who have failed a previous epilepsy surgery can become seizure-free with reoperation. Preoperative evaluation is exceedingly challenging in this cohort. We aim to investigate the diagnostic value of two noninvasive approaches, magnetoencephalography (MEG) and ictal single-photon emission computed tomography (SPECT), in patients with failed epilepsy surgery. We retrospectively included a consecutive cohort of patients who failed prior resective epilepsy surgery, underwent re-evaluation including MEG and ictal SPECT, and had another surgery after the re-evaluation. The relationship between resection and localization from each test was determined, and their association with seizure outcomes was analyzed. A total of 46 patients were included; 21 (46%) were seizure-free at 1-year followup after reoperation. Twenty-seven (58%) had a positive MEG and 31 (67%) had a positive ictal SPECT. The resection of MEG foci was significantly associated with seizure-free outcome (p = 0.002). Overlap of ictal SPECT hyperperfusion zones with resection was significantly associated with seizure-free outcome in the subgroup of patients with injection time ≤20 seconds(p = 0.03), but did not show significant association in the overall cohort (p = 0.46) although all injections were ictal. Patients whose MEG and ictal SPECT were concordant on a sublobar level had a significantly higher chance of seizure freedom (p = 0.05). MEG alone achieved successful localization in patients with failed epilepsy surgery with a statistical significance. Only ictal SPECT with early injection (≤20 seconds) had good localization value. Sublobar concordance between both tests was significantly associated with seizure freedom. SPECT can provide essential information in MEG-negative cases and vice versa. Our results emphasize the importance of considering a multimodal presurgical evaluation including MEG and SPECT in all patients with a previous failed epilepsy surgery. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Resistance of Salmonella typhimurium TA 1535 to O6-guanine methylation and mutagenesis induced by low doses of N-methyl-N'-nitro-N-nitrosoguanidine: an apparent constitutive repair activity.

PubMed

Guttenplan, J B; Milstein, S

1982-01-01

Salmonella tester strains which are reverted by base-pair substitution mutagens are relatively insensitive to the mutagenic effects of N-methyl-N-nitroso compounds. One reason for this insensitivity is the ability of these strains to withstand low doses of these compounds before they become sensitive to their mutagenic effects. In this report it is shown that mutagenesis induced by treatment of Salmonella typhimurium TA 1535 with N-methyl-N'-nitro-N-nitroso-guanidine (MNNG) in buffer is biphasic with a low sensitivity range at low doses where little mutagenesis occurs, followed by a high sensitivity range whose onset begins after an apparent threshold dose has been exceeded. levels of O6-methylguanine (O6-MeG) in the DNA extracted from the bacteria follow a similar dose-response curve suggesting a dependency of mutagenesis on O6-MeG. In contrast, levels of 7-methylguanine (7-MeG) in the DNA increase linearly with dose. O6-MeG was undetectable at the lowest dose of MNNG whereas 7-MeG was readily detectable. Although such resistance to O6-alkylation has been demonstrated in MNNG- pretreated (adapted) E. coli, it has not been reported in unpretreated cells. Then isolated DNA was treated with MNNG a linear dose-response in the generation of O6-MeG was observed. The lack of O6-MeG in DNA isolated from MNNG treated cells after low doses is attributed to a saturable, constitutive repair activity in the bacteria. An attempt to observe the removal of O6-MeG from the bacteria after exposure to a short challenge dose of N-nitroso-N-methylurea (NMU) followed by a subsequent incubation in buffer was unsuccessful, probably because all the repair occurred within the time necessary to treat and lyse the cells.

Abnormal Brain Dynamics Underlie Speech Production in Children with Autism Spectrum Disorder.

PubMed

Pang, Elizabeth W; Valica, Tatiana; MacDonald, Matt J; Taylor, Margot J; Brian, Jessica; Lerch, Jason P; Anagnostou, Evdokia

2016-02-01

A large proportion of children with autism spectrum disorder (ASD) have speech and/or language difficulties. While a number of structural and functional neuroimaging methods have been used to explore the brain differences in ASD with regards to speech and language comprehension and production, the neurobiology of basic speech function in ASD has not been examined. Magnetoencephalography (MEG) is a neuroimaging modality with high spatial and temporal resolution that can be applied to the examination of brain dynamics underlying speech as it can capture the fast responses fundamental to this function. We acquired MEG from 21 children with high-functioning autism (mean age: 11.43 years) and 21 age- and sex-matched controls as they performed a simple oromotor task, a phoneme production task and a phonemic sequencing task. Results showed significant differences in activation magnitude and peak latencies in primary motor cortex (Brodmann Area 4), motor planning areas (BA 6), temporal sequencing and sensorimotor integration areas (BA 22/13) and executive control areas (BA 9). Our findings of significant functional brain differences between these two groups on these simple oromotor and phonemic tasks suggest that these deficits may be foundational and could underlie the language deficits seen in ASD. © 2015 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research.

Multimodal Approach to Testing the Acute Effects of Mild Traumatic Brain Injury (mTBI)

DTIC Science & Technology

2015-03-01

included several key staff changes, a major instrument acquisition, repairs and upgrades to the MEG , combined with substantial progress with patient...patients to non-head trauma controls in the first days after injury. Multiple modalities of behavioral, electrophysiological, and most strikingly, MEG ...changes were found. The MEG of all mTBI patients had delta activity in the frontal lobes that was absent in all controls. A scientific abstract on

The brain’s resting state activity is shaped by synchronized cross frequency coupling of neural oscillations (Author’s Manuscript)

DTIC Science & Technology

2015-02-11

uncovered. Using magnetoencephalography ( MEG ) imaging during rest in 12 healthy subjects we analyse the resting state networks and their underlying...across the whole brain of the resting state is generated. Human magnetoencephalography ( MEG ) of the whole brain emphasized the contribution of...frequency oscillations coordinate long-range communication (Stein, Chiang, and König, 2000). However, these MEG findings do not align entirely with

Feasibility of clinical magnetoencephalography (MEG) functional mapping in the presence of dental artefacts.

PubMed

Hillebrand, A; Fazio, P; de Munck, J C; van Dijk, B W

2013-01-01

To evaluate the viability of MEG source reconstruction in the presence of large interference due to orthodontic material. We recorded the magnetic fields following a simple hand movement and following electrical stimulation of the median nerve (somatosensory evoked field -SEF). These two tasks were performed twice, once with and once without artificial dental artefacts. Temporal Signal Space Separation (tSSS) was applied to spatially filter the data and source reconstruction was performed according to standard procedures for pre-surgical mapping of eloquent cortex, applying dipole fitting to the SEF data and beamforming to the hand movement data. Comparing the data with braces to the data without braces, the observed distances between the activations following hand movement in the two conditions were on average 6.4 and 4.5 mm for the left and right hand, respectively, whereas the dipole localisation errors for the SEF were 4.1 and 5.4 mm, respectively. Without tSSS it was generally not possible to obtain reliable dipole fit or beamforming results when wearing braces. We confirm that tSSS is a required and effective pre-processing step for data recorded with the Elekta-MEG system. Moreover, we have shown that even the presence of large interference from orthodontic material does not significantly alter the results from dipole localisation or beamformer analysis, provided the data are spatially filtered by tSSS. State-of-the-art signal processing techniques enable the use of MEG for pre-surgical evaluation in a much larger clinical population than previously thought possible. Copyright © 2012 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Rodlike Supramolecular Nanoassemblies of Degradable Poly(Aspartic Acid) Derivatives and Hydroxyl-Rich Polycations for Effective Delivery of Versatile Tumor-Suppressive ncRNAs.

PubMed

Song, Hai-Qing; Pan, Wenting; Li, Rui-Quan; Yu, Bingran; Liu, Wenjuan; Yang, Ming; Xu, Fu-Jian

2018-03-01

The delivery of tumor-suppressive noncoding RNAs (ncRNAs) including short ncRNAs (i.e., miRNAs) and long ncRNAs (lncRNAs) is put forward to treat tumors. In this work, novel rodlike supramolecular nanoassemblies (CNC @CB[8] @ PGEA) of degradable poly(aspartic acid) (PAsp) derivatives-grafted cellulose nanocrystals (CNCs) and hydroxyl-rich polycations (ethanolamine-functionalized poly(glycidyl methacrylate), PGEA) are proposed via typical cucurbit[8]uril (CB[8])-based host-guest interactions for delivery of different ncRNAs to treat hepatocellular carcinoma (HCC). Spindly CNCs, one kind of natural polysaccharide nanoparticles, possess good biocompatibility and unique physico-chemical properties. PGEA with abundant hydroxyl groups is one promising gene carrier with low cytotoxicity. PAsp can benefit the disassembly and degradability of nanoassemblies within cells. CNC @ CB[8]@PGEA combines the different unique properties of CNC, PGEA, and PAsp. CNC @ CB[8] @ PGEA effectively complexes the expression constructs of miR-101 (plasmid pc3.0-miR-101) and lncRNA MEG3 (plasmid pc3.0-MEG3). CNC @ CB[8] @ PGEA produces much better transfection performances than PGEA-containing assembly units. In addition, the codelivery system of CNC @ CB[8] @ PGEA/(pc3.0-MEG3+pc3.0-miR-101) nanocomplexes demonstrates better efficacy in suppressing HCC than CNC @ CB[8] @ PGEA/pc3.0-MEG3 or CNC @ CB[8] @ PGEA/pc3.0-miR-101 nanocomplexes alone. Such rodlike supramolecular nanoassemblies will provide a promising means to produce efficient delivery vectors of versatile tumor-suppressive nucleic acids. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Male veterans with PTSD exhibit aberrant neural dynamics during working memory processing: an MEG study

PubMed Central

McDermott, Timothy J.; Badura-Brack, Amy S.; Becker, Katherine M.; Ryan, Tara J.; Khanna, Maya M.; Heinrichs-Graham, Elizabeth; Wilson, Tony W.

2016-01-01

Background Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory. In this study, we examined the neural dynamics of working memory processing in veterans with PTSD and a matched healthy control sample using magnetoencephalography (MEG). Methods Our sample of recent combat veterans with PTSD and demographically matched participants without PTSD completed a working memory task during a 306-sensor MEG recording. The MEG data were preprocessed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach to identify spatiotemporal dynamics. Results Fifty-one men were included in our analyses: 27 combat veterans with PTSD and 24 controls. Across all participants, a dynamic wave of neural activity spread from posterior visual cortices to left frontotemporal regions during encoding, consistent with a verbal working memory task, and was sustained throughout maintenance. Differences related to PTSD emerged during early encoding, with patients exhibiting stronger α oscillatory responses than controls in the right inferior frontal gyrus (IFG). Differences spread to the right supramarginal and temporal cortices during later encoding where, along with the right IFG, they persisted throughout the maintenance period. Limitations This study focused on men with combat-related PTSD using a verbal working memory task. Future studies should evaluate women and the impact of various traumatic experiences using diverse tasks. Conclusion Posttraumatic stress disorder is associated with neurophysiological abnormalities during working memory encoding and maintenance. Veterans with PTSD engaged a bilateral network, including the inferior prefrontal cortices and supramarginal gyri. Right hemispheric neural activity likely reflects compensatory processing, as veterans with PTSD work to maintain accurate performance despite known cognitive deficits associated with the disorder. PMID:26645740

Colour or shape: examination of neural processes underlying mental flexibility in posttraumatic stress disorder.

PubMed

Pang, E W; Sedge, P; Grodecki, R; Robertson, A; MacDonald, M J; Jetly, R; Shek, P N; Taylor, M J

2014-08-05

Posttraumatic stress disorder (PTSD) is a mental disorder that stems from exposure to one or more traumatic events. While PTSD is thought to result from a dysregulation of emotional neurocircuitry, neurocognitive difficulties are frequently reported. Mental flexibility is a core executive function that involves the ability to shift and adapt to new information. It is essential for appropriate social-cognitive behaviours. Magnetoencephalography (MEG), a neuroimaging modality with high spatial and temporal resolution, has been used to track the progression of brain activation during tasks of mental flexibility called set-shifting. We hypothesized that the sensitivity of MEG would be able to capture the abnormal neurocircuitry implicated in PTSD and this would negatively impact brain regions involved in set-shifting. Twenty-two soldiers with PTSD and 24 matched control soldiers completed a colour-shape set-shifting task. MEG data were recorded and source localized to identify significant brain regions involved in the task. Activation latencies were obtained by analysing the time course of activation in each region. The control group showed a sequence of activity that involved dorsolateral frontal cortex, insula and posterior parietal cortices. The soldiers with PTSD showed these activations but they were interrupted by activations in paralimbic regions. This is consistent with models of PTSD that suggest dysfunctional neurocircuitry is driven by hyper-reactive limbic areas that are not appropriately modulated by prefrontal cortical control regions. This is the first study identifying the timing and location of atypical neural responses in PTSD with set-shifting and supports the model that hyperactive limbic structures negatively impact cognitive function.

The Discontinuous Galerkin Finite Element Method for Solving the MEG and the Combined MEG/EEG Forward Problem

PubMed Central

Piastra, Maria Carla; Nüßing, Andreas; Vorwerk, Johannes; Bornfleth, Harald; Oostenveld, Robert; Engwer, Christian; Wolters, Carsten H.

2018-01-01

In Electro- (EEG) and Magnetoencephalography (MEG), one important requirement of source reconstruction is the forward model. The continuous Galerkin finite element method (CG-FEM) has become one of the dominant approaches for solving the forward problem over the last decades. Recently, a discontinuous Galerkin FEM (DG-FEM) EEG forward approach has been proposed as an alternative to CG-FEM (Engwer et al., 2017). It was shown that DG-FEM preserves the property of conservation of charge and that it can, in certain situations such as the so-called skull leakages, be superior to the standard CG-FEM approach. In this paper, we developed, implemented, and evaluated two DG-FEM approaches for the MEG forward problem, namely a conservative and a non-conservative one. The subtraction approach was used as source model. The validation and evaluation work was done in statistical investigations in multi-layer homogeneous sphere models, where an analytic solution exists, and in a six-compartment realistically shaped head volume conductor model. In agreement with the theory, the conservative DG-FEM approach was found to be superior to the non-conservative DG-FEM implementation. This approach also showed convergence with increasing resolution of the hexahedral meshes. While in the EEG case, in presence of skull leakages, DG-FEM outperformed CG-FEM, in MEG, DG-FEM achieved similar numerical errors as the CG-FEM approach, i.e., skull leakages do not play a role for the MEG modality. In particular, for the finest mesh resolution of 1 mm sources with a distance of 1.59 mm from the brain-CSF surface, DG-FEM yielded mean topographical errors (relative difference measure, RDM%) of 1.5% and mean magnitude errors (MAG%) of 0.1% for the magnetic field. However, if the goal is a combined source analysis of EEG and MEG data, then it is highly desirable to employ the same forward model for both EEG and MEG data. Based on these results, we conclude that the newly presented conservative DG-FEM can at least complement and in some scenarios even outperform the established CG-FEM approaches in EEG or combined MEG/EEG source analysis scenarios, which motivates a further evaluation of DG-FEM for applications in bioelectromagnetism. PMID:29456487

Building Blocks of Fetal Cognition: Emotion and Language

ERIC Educational Resources Information Center

Huotilainen, Minna

2010-01-01

Magnetoencephalography (MEG) can be effectively used to record fetal and neonatal cognitive abilities/functions by recording completely non-invasively the magnetic fields produced by the active neurons in the brain. During the last trimester and the first months of life, the cognitive capabilities related to emotion recognition and language…

Source-space ICA for MEG source imaging.

PubMed

Jonmohamadi, Yaqub; Jones, Richard D

2016-02-01

One of the most widely used approaches in electroencephalography/magnetoencephalography (MEG) source imaging is application of an inverse technique (such as dipole modelling or sLORETA) on the component extracted by independent component analysis (ICA) (sensor-space ICA + inverse technique). The advantage of this approach over an inverse technique alone is that it can identify and localize multiple concurrent sources. Among inverse techniques, the minimum-variance beamformers offer a high spatial resolution. However, in order to have both high spatial resolution of beamformer and be able to take on multiple concurrent sources, sensor-space ICA + beamformer is not an ideal combination. We propose source-space ICA for MEG as a powerful alternative approach which can provide the high spatial resolution of the beamformer and handle multiple concurrent sources. The concept of source-space ICA for MEG is to apply the beamformer first and then singular value decomposition + ICA. In this paper we have compared source-space ICA with sensor-space ICA both in simulation and real MEG. The simulations included two challenging scenarios of correlated/concurrent cluster sources. Source-space ICA provided superior performance in spatial reconstruction of source maps, even though both techniques performed equally from a temporal perspective. Real MEG from two healthy subjects with visual stimuli were also used to compare performance of sensor-space ICA and source-space ICA. We have also proposed a new variant of minimum-variance beamformer called weight-normalized linearly-constrained minimum-variance with orthonormal lead-field. As sensor-space ICA-based source reconstruction is popular in EEG and MEG imaging, and given that source-space ICA has superior spatial performance, it is expected that source-space ICA will supersede its predecessor in many applications.

Combined EEG/MEG Can Outperform Single Modality EEG or MEG Source Reconstruction in Presurgical Epilepsy Diagnosis

PubMed Central

Aydin, Ümit; Vorwerk, Johannes; Dümpelmann, Matthias; Küpper, Philipp; Kugel, Harald; Heers, Marcel; Wellmer, Jörg; Kellinghaus, Christoph; Haueisen, Jens; Rampp, Stefan; Stefan, Hermann; Wolters, Carsten H.

2015-01-01

We investigated two important means for improving source reconstruction in presurgical epilepsy diagnosis. The first investigation is about the optimal choice of the number of epileptic spikes in averaging to (1) sufficiently reduce the noise bias for an accurate determination of the center of gravity of the epileptic activity and (2) still get an estimation of the extent of the irritative zone. The second study focuses on the differences in single modality EEG (80-electrodes) or MEG (275-gradiometers) and especially on the benefits of combined EEG/MEG (EMEG) source analysis. Both investigations were validated with simultaneous stereo-EEG (sEEG) (167-contacts) and low-density EEG (ldEEG) (21-electrodes). To account for the different sensitivity profiles of EEG and MEG, we constructed a six-compartment finite element head model with anisotropic white matter conductivity, and calibrated the skull conductivity via somatosensory evoked responses. Our results show that, unlike single modality EEG or MEG, combined EMEG uses the complementary information of both modalities and thereby allows accurate source reconstructions also at early instants in time (epileptic spike onset), i.e., time points with low SNR, which are not yet subject to propagation and thus supposed to be closer to the origin of the epileptic activity. EMEG is furthermore able to reveal the propagation pathway at later time points in agreement with sEEG, while EEG or MEG alone reconstructed only parts of it. Subaveraging provides important and accurate information about both the center of gravity and the extent of the epileptogenic tissue that neither single nor grand-averaged spike localizations can supply. PMID:25761059

Brain activity is related to individual differences in the number of items stored in auditory short-term memory for pitch: evidence from magnetoencephalography.

PubMed

Grimault, Stephan; Nolden, Sophie; Lefebvre, Christine; Vachon, François; Hyde, Krista; Peretz, Isabelle; Zatorre, Robert; Robitaille, Nicolas; Jolicoeur, Pierre

2014-07-01

We used magnetoencephalography (MEG) to examine brain activity related to the maintenance of non-verbal pitch information in auditory short-term memory (ASTM). We focused on brain activity that increased with the number of items effectively held in memory by the participants during the retention interval of an auditory memory task. We used very simple acoustic materials (i.e., pure tones that varied in pitch) that minimized activation from non-ASTM related systems. MEG revealed neural activity in frontal, temporal, and parietal cortices that increased with a greater number of items effectively held in memory by the participants during the maintenance of pitch representations in ASTM. The present results reinforce the functional role of frontal and temporal cortices in the retention of pitch information in ASTM. This is the first MEG study to provide both fine spatial localization and temporal resolution on the neural mechanisms of non-verbal ASTM for pitch in relation to individual differences in the capacity of ASTM. This research contributes to a comprehensive understanding of the mechanisms mediating the representation and maintenance of basic non-verbal auditory features in the human brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Effects of phonological contrast on auditory word discrimination in children with and without reading disability: A magnetoencephalography (MEG) study

PubMed Central

Wehner, Daniel T.; Ahlfors, Seppo P.; Mody, Maria

2007-01-01

Poor readers perform worse than their normal reading peers on a variety of speech perception tasks, which may be linked to their phonological processing abilities. The purpose of the study was to compare the brain activation patterns of normal and impaired readers on speech perception to better understand the phonological basis in reading disability. Whole-head magnetoencephalography (MEG) was recorded as good and poor readers, 7-13 years of age, performed an auditory word discrimination task. We used an auditory oddball paradigm in which the ‘deviant’ stimuli (/bat/, /kat/, /rat/) differed in the degree of phonological contrast (1 vs. 3 features) from a repeated standard word (/pat/). Both good and poor readers responded more slowly to deviants that were phonologically similar compared to deviants that were phonologically dissimilar to the standard word. Source analysis of the MEG data using Minimum Norm Estimation (MNE) showed that compared to good readers, poor readers had reduced left-hemisphere activation to the most demanding phonological condition reflecting their difficulties with phonological processing. Furthermore, unlike good readers, poor readers did not show differences in activation as a function of the degree of phonological contrast. These results are consistent with a phonological account of reading disability. PMID:17675109

Beamspace dual signal space projection (bDSSP): a method for selective detection of deep sources in MEG measurements.

PubMed

Sekihara, Kensuke; Adachi, Yoshiaki; Kubota, Hiroshi K; Cai, Chang; Nagarajan, Srikantan S

2018-06-01

Magnetoencephalography (MEG) has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in MEG measurements. The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources. The proposed algorithm first derives the basis vectors that span a local region just covering the locations of the deep sources. It then estimates the time-domain signal subspace of the superficial sources by using the projector composed of these basis vectors. Signals from the deep sources are extracted by projecting the row space of the data matrix onto the direction orthogonal to the signal subspace of the superficial sources. Compared with the previously proposed beamspace signal space separation (SSS) method, the proposed algorithm is capable of suppressing much stronger interference from superficial sources. This capability is demonstrated in our computer simulation as well as experiments using phantom data. The proposed bDSSP algorithm can be a powerful tool in studies of physiological functions of midbrain and deep brain structures.

Beamspace dual signal space projection (bDSSP): a method for selective detection of deep sources in MEG measurements

NASA Astrophysics Data System (ADS)

Sekihara, Kensuke; Adachi, Yoshiaki; Kubota, Hiroshi K.; Cai, Chang; Nagarajan, Srikantan S.

2018-06-01

Objective. Magnetoencephalography (MEG) has a well-recognized weakness at detecting deeper brain activities. This paper proposes a novel algorithm for selective detection of deep sources by suppressing interference signals from superficial sources in MEG measurements. Approach. The proposed algorithm combines the beamspace preprocessing method with the dual signal space projection (DSSP) interference suppression method. A prerequisite of the proposed algorithm is prior knowledge of the location of the deep sources. The proposed algorithm first derives the basis vectors that span a local region just covering the locations of the deep sources. It then estimates the time-domain signal subspace of the superficial sources by using the projector composed of these basis vectors. Signals from the deep sources are extracted by projecting the row space of the data matrix onto the direction orthogonal to the signal subspace of the superficial sources. Main results. Compared with the previously proposed beamspace signal space separation (SSS) method, the proposed algorithm is capable of suppressing much stronger interference from superficial sources. This capability is demonstrated in our computer simulation as well as experiments using phantom data. Significance. The proposed bDSSP algorithm can be a powerful tool in studies of physiological functions of midbrain and deep brain structures.

Dynamic Modulation of Sensory Cortex by Top-Down Spatial Attention

DTIC Science & Technology

2015-04-15

yet only in recent decades has the neural basis for these benefits begun to be studied. The studies presented here use EEG and MEG to identify patterns...presented here use EEG and MEG to identify patterns of neural activity related to the deployment of attention in extrapersonal space, and examine the...we use simultaneously recorded EEG/ MEG to examine the interaction of these top-down signals with neural responses evoked by attended and unattended

Dynamic reorganization of Eg5 in the mammalian spindle throughout mitosis requires dynein and TPX2

PubMed Central

Gable, Alyssa; Qiu, Minhua; Titus, Janel; Balchand, Sai; Ferenz, Nick P.; Ma, Nan; Collins, Elizabeth S.; Fagerstrom, Carey; Ross, Jennifer L.; Yang, Ge; Wadsworth, Patricia

2012-01-01

Kinesin-5 is an essential mitotic motor. However, how its spatial–temporal distribution is regulated in mitosis remains poorly understood. We expressed localization and affinity purification–tagged Eg5 from a mouse bacterial artificial chromosome (this construct was called mEg5) and found its distribution to be tightly regulated throughout mitosis. Fluorescence recovery after photobleaching analysis showed rapid Eg5 turnover throughout mitosis, which cannot be accounted for by microtubule turnover. Total internal reflection fluorescence microscopy and high-resolution, single-particle tracking revealed that mEg5 punctae on both astral and midzone microtubules rapidly bind and unbind. mEg5 punctae on midzone microtubules moved transiently both toward and away from spindle poles. In contrast, mEg5 punctae on astral microtubules moved transiently toward microtubule minus ends during early mitosis but switched to plus end–directed motion during anaphase. These observations explain the poleward accumulation of Eg5 in early mitosis and its redistribution in anaphase. Inhibition of dynein blocked mEg5 movement on astral microtubules, whereas depletion of the Eg5-binding protein TPX2 resulted in plus end–directed mEg5 movement. However, motion of Eg5 on midzone microtubules was not altered. Our results reveal differential and precise spatial and temporal regulation of Eg5 in the spindle mediated by dynein and TPX2. PMID:22337772

Differences between magnetoencephalographic (MEG) spectral profiles of drugs acting on GABA at synaptic and extrasynaptic sites: a study in healthy volunteers.

PubMed

Nutt, David; Wilson, Sue; Lingford-Hughes, Anne; Myers, Jim; Papadopoulos, Andreas; Muthukumaraswamy, Suresh

2015-01-01

A range of medications target different aspects of the GABA system; understanding their effects is important to inform further drug development. Effects on the waking EEG comparing these mechanisms have not been reported; in this study we compare the effects on resting MEG spectra of the benzodiazepine receptor agonist zolpidem, the delta sub-unit selective agonist gaboxadol (also known as THIP) and the GABA reuptake inhibitor tiagabine. These were two randomised, single-blind, placebo-controlled, crossover studies in healthy volunteers, one using zolpidem 10 mg, gaboxadol 15 mg and placebo, and the other tiagabine 15 mg and placebo. Whole head MEG recordings and individual MEG spectra were divided into frequency bands. Baseline spectra were subtracted from each post-intervention spectra and then differences between intervention and placebo compared. After zolpidem there were significant increases in beta frequencies and reduction in alpha frequency power; after gaboxadol and tiagabine there were significant increases in power at all frequencies up to beta. Enhancement of tonic inhibition via extrasynaptic receptors by gaboxadol gives rise to a very different MEG signature from the synaptic action of zolpidem. Tiagabine theoretically can affect both types of receptor; from these MEG results it is likely that the latter is the more prominent effect here. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Regulation of RNA granule dynamics by phosphorylation of serine-rich, intrinsically disordered proteins in C. elegans

PubMed Central

Wang, Jennifer T; Smith, Jarrett; Chen, Bi-Chang; Schmidt, Helen; Rasoloson, Dominique; Paix, Alexandre; Lambrus, Bramwell G; Calidas, Deepika; Betzig, Eric; Seydoux, Geraldine

2014-01-01

RNA granules have been likened to liquid droplets whose dynamics depend on the controlled dissolution and condensation of internal components. The molecules and reactions that drive these dynamics in vivo are not well understood. In this study, we present evidence that a group of intrinsically disordered, serine-rich proteins regulate the dynamics of P granules in C. elegans embryos. The MEG (maternal-effect germline defective) proteins are germ plasm components that are required redundantly for fertility. We demonstrate that MEG-1 and MEG-3 are substrates of the kinase MBK-2/DYRK and the phosphatase PP2APPTR−½. Phosphorylation of the MEGs promotes granule disassembly and dephosphorylation promotes granule assembly. Using lattice light sheet microscopy on live embryos, we show that GFP-tagged MEG-3 localizes to a dynamic domain that surrounds and penetrates each granule. We conclude that, despite their liquid-like behavior, P granules are non-homogeneous structures whose assembly in embryos is regulated by phosphorylation. DOI: http://dx.doi.org/10.7554/eLife.04591.001 PMID:25535836

Interpretation of the MEG-MUSIC scan in biomagnetic source localization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mosher, J.C.; Lewis, P.S.; Leahy, R.M.

1993-09-01

MEG-Music is a new approach to MEG source localization. MEG-Music is based on a spatio-temporal source model in which the observed biomagnetic fields are generated by a small number of current dipole sources with fixed positions/orientations and varying strengths. From the spatial covariance matrix of the observed fields, a signal subspace can be identified. The rank of this subspace is equal to the number of elemental sources present. This signal sub-space is used in a projection metric that scans the three dimensional head volume. Given a perfect signal subspace estimate and a perfect forward model, the metric will peak atmore » unity at each dipole location. In practice, the signal subspace estimate is contaminated by noise, which in turn yields MUSIC peaks which are less than unity. Previously we examined the lower bounds on localization error, independent of the choice of localization procedure. In this paper, we analyzed the effects of noise and temporal coherence on the signal subspace estimate and the resulting effects on the MEG-MUSIC peaks.« less

76 FR 75797 - Transportation Conformity Rule: MOVES Regional Grace Period Extension

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-05

... INFORMATION CONTACT: Meg Patulski, State Measures and Transportation Planning Center, Environmental Protection...) 214-4052; email address: patulski.meg@epa.gov . SUPPLEMENTARY INFORMATION: Because EPA received...

MEG/EEG Source Reconstruction, Statistical Evaluation, and Visualization with NUTMEG

PubMed Central

Dalal, Sarang S.; Zumer, Johanna M.; Guggisberg, Adrian G.; Trumpis, Michael; Wong, Daniel D. E.; Sekihara, Kensuke; Nagarajan, Srikantan S.

2011-01-01

NUTMEG is a source analysis toolbox geared towards cognitive neuroscience researchers using MEG and EEG, including intracranial recordings. Evoked and unaveraged data can be imported to the toolbox for source analysis in either the time or time-frequency domains. NUTMEG offers several variants of adaptive beamformers, probabilistic reconstruction algorithms, as well as minimum-norm techniques to generate functional maps of spatiotemporal neural source activity. Lead fields can be calculated from single and overlapping sphere head models or imported from other software. Group averages and statistics can be calculated as well. In addition to data analysis tools, NUTMEG provides a unique and intuitive graphical interface for visualization of results. Source analyses can be superimposed onto a structural MRI or headshape to provide a convenient visual correspondence to anatomy. These results can also be navigated interactively, with the spatial maps and source time series or spectrogram linked accordingly. Animations can be generated to view the evolution of neural activity over time. NUTMEG can also display brain renderings and perform spatial normalization of functional maps using SPM's engine. As a MATLAB package, the end user may easily link with other toolboxes or add customized functions. PMID:21437174

MEG/EEG source reconstruction, statistical evaluation, and visualization with NUTMEG.

PubMed

Dalal, Sarang S; Zumer, Johanna M; Guggisberg, Adrian G; Trumpis, Michael; Wong, Daniel D E; Sekihara, Kensuke; Nagarajan, Srikantan S

2011-01-01

NUTMEG is a source analysis toolbox geared towards cognitive neuroscience researchers using MEG and EEG, including intracranial recordings. Evoked and unaveraged data can be imported to the toolbox for source analysis in either the time or time-frequency domains. NUTMEG offers several variants of adaptive beamformers, probabilistic reconstruction algorithms, as well as minimum-norm techniques to generate functional maps of spatiotemporal neural source activity. Lead fields can be calculated from single and overlapping sphere head models or imported from other software. Group averages and statistics can be calculated as well. In addition to data analysis tools, NUTMEG provides a unique and intuitive graphical interface for visualization of results. Source analyses can be superimposed onto a structural MRI or headshape to provide a convenient visual correspondence to anatomy. These results can also be navigated interactively, with the spatial maps and source time series or spectrogram linked accordingly. Animations can be generated to view the evolution of neural activity over time. NUTMEG can also display brain renderings and perform spatial normalization of functional maps using SPM's engine. As a MATLAB package, the end user may easily link with other toolboxes or add customized functions.

Absence of Auditory M100 Source Asymmetry in Schizophrenia and Bipolar Disorder: A MEG Study

PubMed Central

Wang, Ying; Feng, Yigang; Jia, Yanbin; Xie, Yanping; Wang, Wensheng; Guan, Yufang; Zhong, Shuming; Zhu, Dan; Huang, Li

2013-01-01

Background Whether schizophrenia and bipolar disorder are the clinical outcomes of discrete or shared causative processes is much debated in psychiatry. Several studies have demonstrated anomalous structural and functional superior temporal gyrus (STG) symmetries in schizophrenia. We examined bipolar patients to determine if they also have altered STG asymmetry. Methods Whole-head magnetoencephalography (MEG) recordings of auditory evoked fields were obtained for 20 subjects with schizophrenia, 20 with bipolar disorder, and 20 control subjects. Neural generators of the M100 auditory response were modeled using a single equivalent current dipole for each hemisphere. The source location of the M100 response was used as a measure of functional STG asymmetry. Results Control subjects showed the typical M100 asymmetrical pattern with more anterior sources in the right STG. In contrast, both schizophrenia and bipolar disorder patients displayed a symmetrical M100 source pattern. There was no significant difference in the M100 latency and strength in bilateral hemispheres within three groups. Conclusions Our results indicate that disturbed asymmetry of temporal lobe function may reflect a common deviance present in schizophrenia and bipolar disorder, suggesting the two disorders might share etiological and pathophysiological factors. PMID:24340052

Improving the Nulling Beamformer Using Subspace Suppression.

PubMed

Rana, Kunjan D; Hämäläinen, Matti S; Vaina, Lucia M

2018-01-01

Magnetoencephalography (MEG) captures the magnetic fields generated by neuronal current sources with sensors outside the head. In MEG analysis these current sources are estimated from the measured data to identify the locations and time courses of neural activity. Since there is no unique solution to this so-called inverse problem, multiple source estimation techniques have been developed. The nulling beamformer (NB), a modified form of the linearly constrained minimum variance (LCMV) beamformer, is specifically used in the process of inferring interregional interactions and is designed to eliminate shared signal contributions, or cross-talk, between regions of interest (ROIs) that would otherwise interfere with the connectivity analyses. The nulling beamformer applies the truncated singular value decomposition (TSVD) to remove small signal contributions from a ROI to the sensor signals. However, ROIs with strong crosstalk will have high separating power in the weaker components, which may be removed by the TSVD operation. To address this issue we propose a new method, the nulling beamformer with subspace suppression (NBSS). This method, controlled by a tuning parameter, reweights the singular values of the gain matrix mapping from source to sensor space such that components with high overlap are reduced. By doing so, we are able to measure signals between nearby source locations with limited cross-talk interference, allowing for reliable cortical connectivity analysis between them. In two simulations, we demonstrated that NBSS reduces cross-talk while retaining ROIs' signal power, and has higher separating power than both the minimum norm estimate (MNE) and the nulling beamformer without subspace suppression. We also showed that NBSS successfully localized the auditory M100 event-related field in primary auditory cortex, measured from a subject undergoing an auditory localizer task, and suppressed cross-talk in a nearby region in the superior temporal sulcus.

Combination of brain-computer interface training and goal-directed physical therapy in chronic stroke: a case report.

PubMed

Broetz, Doris; Braun, Christoph; Weber, Cornelia; Soekadar, Surjo R; Caria, Andrea; Birbaumer, Niels

2010-09-01

There is no accepted and efficient rehabilitation strategy to reduce focal impairments for patients with chronic stroke who lack residual movements. A 67-year-old hemiplegic patient with no active finger extension was trained with a brain-computer interface (BCI) combined with a specific daily life-oriented physiotherapy. The BCI used electrical brain activity (EEG) and magnetic brain activity (MEG) to drive an orthosis and a robot affixed to the patient's affected upper extremity, which enabled him to move the paralyzed arm and hand driven by voluntary modulation of micro-rhythm activity. In addition, the patient practiced goal-directed physiotherapy training. Over 1 year, he completed 3 training blocks. Arm motor function, gait capacities (using Fugl-Meyer Assessment, Wolf Motor Function Test, Modified Ashworth Scale, 10-m walk speed, and goal attainment score), and brain reorganization (functional MRI, MEG) were repeatedly assessed. The ability of hand and arm movements as well as speed and safety of gait improved significantly (mean 46.6%). Improvement of motor function was associated with increased micro-oscillations in the ipsilesional motor cortex. This proof-of-principle study suggests that the combination of BCI training with goal-directed, active physical therapy may improve the motor abilities of chronic stroke patients despite apparent initial paralysis.

Neural correlates of the LSD experience revealed by multimodal neuroimaging.

PubMed

Carhart-Harris, Robin L; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T; Williams, Tim M; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I; Nichols, David; Hellyer, Peter J; Hobden, Peter; Evans, John; Singh, Krish D; Wise, Richard G; Curran, H Valerie; Feilding, Amanda; Nutt, David J

2016-04-26

Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD's marked effects on the visual cortex did not significantly correlate with the drug's other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of "ego-dissolution" and "altered meaning," implying the importance of this particular circuit for the maintenance of "self" or "ego" and its processing of "meaning." Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others.

Neural correlates of the LSD experience revealed by multimodal neuroimaging

PubMed Central

Carhart-Harris, Robin L.; Muthukumaraswamy, Suresh; Roseman, Leor; Kaelen, Mendel; Droog, Wouter; Murphy, Kevin; Tagliazucchi, Enzo; Schenberg, Eduardo E.; Nest, Timothy; Orban, Csaba; Leech, Robert; Williams, Luke T.; Williams, Tim M.; Bolstridge, Mark; Sessa, Ben; McGonigle, John; Sereno, Martin I.; Nichols, David; Hobden, Peter; Evans, John; Singh, Krish D.; Wise, Richard G.; Curran, H. Valerie; Feilding, Amanda; Nutt, David J.

2016-01-01

Lysergic acid diethylamide (LSD) is the prototypical psychedelic drug, but its effects on the human brain have never been studied before with modern neuroimaging. Here, three complementary neuroimaging techniques: arterial spin labeling (ASL), blood oxygen level-dependent (BOLD) measures, and magnetoencephalography (MEG), implemented during resting state conditions, revealed marked changes in brain activity after LSD that correlated strongly with its characteristic psychological effects. Increased visual cortex cerebral blood flow (CBF), decreased visual cortex alpha power, and a greatly expanded primary visual cortex (V1) functional connectivity profile correlated strongly with ratings of visual hallucinations, implying that intrinsic brain activity exerts greater influence on visual processing in the psychedelic state, thereby defining its hallucinatory quality. LSD’s marked effects on the visual cortex did not significantly correlate with the drug’s other characteristic effects on consciousness, however. Rather, decreased connectivity between the parahippocampus and retrosplenial cortex (RSC) correlated strongly with ratings of “ego-dissolution” and “altered meaning,” implying the importance of this particular circuit for the maintenance of “self” or “ego” and its processing of “meaning.” Strong relationships were also found between the different imaging metrics, enabling firmer inferences to be made about their functional significance. This uniquely comprehensive examination of the LSD state represents an important advance in scientific research with psychedelic drugs at a time of growing interest in their scientific and therapeutic value. The present results contribute important new insights into the characteristic hallucinatory and consciousness-altering properties of psychedelics that inform on how they can model certain pathological states and potentially treat others. PMID:27071089

Dynamics of hemispheric dominance for language assessed by magnetoencephalographic imaging.

PubMed

Findlay, Anne M; Ambrose, Josiah B; Cahn-Weiner, Deborah A; Houde, John F; Honma, Susanne; Hinkley, Leighton B N; Berger, Mitchel S; Nagarajan, Srikantan S; Kirsch, Heidi E

2012-05-01

The goal of the current study was to examine the dynamics of language lateralization using magnetoencephalographic (MEG) imaging, to determine the sensitivity and specificity of MEG imaging, and to determine whether MEG imaging can become a viable alternative to the intracarotid amobarbital procedure (IAP), the current gold standard for preoperative language lateralization in neurosurgical candidates. MEG was recorded during an auditory verb generation task and imaging analysis of oscillatory activity was initially performed in 21 subjects with epilepsy, brain tumor, or arteriovenous malformation who had undergone IAP and MEG. Time windows and brain regions of interest that best discriminated between IAP-determined left or right dominance for language were identified. Parameters derived in the retrospective analysis were applied to a prospective cohort of 14 patients and healthy controls. Power decreases in the beta frequency band were consistently observed following auditory stimulation in inferior frontal, superior temporal, and parietal cortices; similar power decreases were also seen in inferior frontal cortex prior to and during overt verb generation. Language lateralization was clearly observed to be a dynamic process that is bilateral for several hundred milliseconds during periods of auditory perception and overt speech production. Correlation with the IAP was seen in 13 of 14 (93%) prospective patients, with the test demonstrating a sensitivity of 100% and specificity of 92%. Our results demonstrate excellent correlation between MEG imaging findings and the IAP for language lateralization, and provide new insights into the spatiotemporal dynamics of cortical speech processing. Copyright © 2012 American Neurological Association.

Response Inhibition in Adults and Teenagers: Spatiotemporal Differences in the Prefrontal Cortex

ERIC Educational Resources Information Center

Vidal, Julie; Mills, Travis; Pang, Elizabeth W.; Taylor, Margot J.

2012-01-01

Inhibition is a core executive function reliant on the frontal lobes that shows protracted maturation through to adulthood. We investigated the spatiotemporal characteristics of response inhibition during a visual go/no-go task in 14 teenagers and 14 adults using magnetoencephalography (MEG) and a contrast between two no-go experimental conditions…

Unconscious Learning versus Visual Perception: Dissociable Roles for Gamma Oscillations Revealed in MEG

ERIC Educational Resources Information Center

Chaumon, Maximilien; Schwartz, Denis; Tallon-Baudry, Catherine

2009-01-01

Oscillatory synchrony in the gamma band (30-120 Hz) has been involved in various cognitive functions including conscious perception and learning. Explicit memory encoding, in particular, relies on enhanced gamma oscillations. Does this finding extend to unconscious memory encoding? Can we dissociate gamma oscillations related to unconscious…

Prestimulus oscillatory activity in the alpha band predicts visual discrimination ability.

PubMed

van Dijk, Hanneke; Schoffelen, Jan-Mathijs; Oostenveld, Robert; Jensen, Ole

2008-02-20

Although the resting and baseline states of the human electroencephalogram and magnetoencephalogram (MEG) are dominated by oscillations in the alpha band (approximately 10 Hz), the functional role of these oscillations remains unclear. In this study we used MEG to investigate how spontaneous oscillations in humans presented before visual stimuli modulate visual perception. Subjects had to report if there was a subtle difference in gray levels between two superimposed presented discs. We then compared the prestimulus brain activity for correctly (hits) versus incorrectly (misses) identified stimuli. We found that visual discrimination ability decreased with an increase in prestimulus alpha power. Given that reaction times did not vary systematically with prestimulus alpha power changes in vigilance are not likely to explain the change in discrimination ability. Source reconstruction using spatial filters allowed us to identify the brain areas accounting for this effect. The dominant sources modulating visual perception were localized around the parieto-occipital sulcus. We suggest that the parieto-occipital alpha power reflects functional inhibition imposed by higher level areas, which serves to modulate the gain of the visual stream.

Versatile synchronized real-time MEG hardware controller for large-scale fast data acquisition.

PubMed

Sun, Limin; Han, Menglai; Pratt, Kevin; Paulson, Douglas; Dinh, Christoph; Esch, Lorenz; Okada, Yoshio; Hämäläinen, Matti

2017-05-01

Versatile controllers for accurate, fast, and real-time synchronized acquisition of large-scale data are useful in many areas of science, engineering, and technology. Here, we describe the development of a controller software based on a technique called queued state machine for controlling the data acquisition (DAQ) hardware, continuously acquiring a large amount of data synchronized across a large number of channels (>400) at a fast rate (up to 20 kHz/channel) in real time, and interfacing with applications for real-time data analysis and display of electrophysiological data. This DAQ controller was developed specifically for a 384-channel pediatric whole-head magnetoencephalography (MEG) system, but its architecture is useful for wide applications. This controller running in a LabVIEW environment interfaces with microprocessors in the MEG sensor electronics to control their real-time operation. It also interfaces with a real-time MEG analysis software via transmission control protocol/internet protocol, to control the synchronous acquisition and transfer of the data in real time from >400 channels to acquisition and analysis workstations. The successful implementation of this controller for an MEG system with a large number of channels demonstrates the feasibility of employing the present architecture in several other applications.

Versatile synchronized real-time MEG hardware controller for large-scale fast data acquisition

NASA Astrophysics Data System (ADS)

Sun, Limin; Han, Menglai; Pratt, Kevin; Paulson, Douglas; Dinh, Christoph; Esch, Lorenz; Okada, Yoshio; Hämäläinen, Matti

2017-05-01

Versatile controllers for accurate, fast, and real-time synchronized acquisition of large-scale data are useful in many areas of science, engineering, and technology. Here, we describe the development of a controller software based on a technique called queued state machine for controlling the data acquisition (DAQ) hardware, continuously acquiring a large amount of data synchronized across a large number of channels (>400) at a fast rate (up to 20 kHz/channel) in real time, and interfacing with applications for real-time data analysis and display of electrophysiological data. This DAQ controller was developed specifically for a 384-channel pediatric whole-head magnetoencephalography (MEG) system, but its architecture is useful for wide applications. This controller running in a LabVIEW environment interfaces with microprocessors in the MEG sensor electronics to control their real-time operation. It also interfaces with a real-time MEG analysis software via transmission control protocol/internet protocol, to control the synchronous acquisition and transfer of the data in real time from >400 channels to acquisition and analysis workstations. The successful implementation of this controller for an MEG system with a large number of channels demonstrates the feasibility of employing the present architecture in several other applications.

A three domain covariance framework for EEG/MEG data.

PubMed

Roś, Beata P; Bijma, Fetsje; de Gunst, Mathisca C M; de Munck, Jan C

2015-10-01

In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG-fMRI experiments in which the correlation between EEG and fMRI signals is investigated. We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets. Copyright © 2015 Elsevier Inc. All rights reserved.

Application of Multiple Regression and Design of Experiments for Modelling the Effect of Monoethylene Glycol in the Calcium Carbonate Scaling Process.

PubMed

Kartnaller, Vinicius; Venâncio, Fabrício; F do Rosário, Francisca; Cajaiba, João

2018-04-10

To avoid gas hydrate formation during oil and gas production, companies usually employ thermodynamic inhibitors consisting of hydroxyl compounds, such as monoethylene glycol (MEG). However, these inhibitors may cause other types of fouling during production such as inorganic salt deposits (scale). Calcium carbonate is one of the main scaling salts and is a great concern, especially for the new pre-salt wells being explored in Brazil. Hence, it is important to understand how using inhibitors to control gas hydrate formation may be interacting with the scale formation process. Multiple regression and design of experiments were used to mathematically model the calcium carbonate scaling process and its evolution in the presence of MEG. It was seen that MEG, although inducing the precipitation by increasing the supersaturation ratio, actually works as a scale inhibitor for calcium carbonate in concentrations over 40%. This effect was not due to changes in the viscosity, as suggested in the literature, but possibly to the binding of MEG to the CaCO₃ particles' surface. The interaction of the MEG inhibition effect with the system's variables was also assessed, when temperature' and calcium concentration were more relevant.

Liquid xenon calorimeter for MEG II experiment with VUV-sensitive MPPCs

NASA Astrophysics Data System (ADS)

Ogawa, Shinji; MEG II Collaboration

2017-02-01

The MEG II experiment is an upgrade of the MEG experiment to search for the charged lepton flavor violating decay of muon, μ+ →e+ γ . The MEG II experiment is expected to reach a branching ratio sensitivity of 4 ×10-14 , which is one order of magnitude better than the sensitivity of the current MEG experiment. The performance of the liquid xenon (LXe) γ-ray detector will be greatly improved with a highly granular scintillation readout realized by replacing 216 photomultiplier tubes (PMTs) on the γ-ray entrance face with 4092 Multi-Pixel Photon Counters (MPPCs). For this purpose, we have developed a new type of MPPC which is sensitive to the LXe scintillation light in vacuum ultraviolet (VUV) range, in collaboration with Hamamatsu Photonics K.K. We have measured the performance of the MPPC in LXe, and an excellent performance has been confirmed including high photon detection efficiency (> 15 %) for LXe scintillation light. An excellent performance of the LXe detector has been confirmed by Monte Carlo simulations based on the measured properties of the MPPC. The construction of the detector is in progress, aiming to start physics data taking in 2017.

Frequency specific patterns of resting-state networks development from childhood to adolescence: A magnetoencephalography study.

PubMed

Meng, Lu; Xiang, Jing

2016-11-01

The present study investigated frequency dependent developmental patterns of the brain resting-state networks from childhood to adolescence. Magnetoencephalography (MEG) data were recorded from 20 healthy subjects at resting-state with eyes-open. The resting-state networks (RSNs) was analyzed at source-level. Brain network organization was characterized by mean clustering coefficient and average path length. The correlations between brain network measures and subjects' age during development from childhood to adolescence were statistically analyzed in delta (1-4Hz), theta (4-8Hz), alpha (8-12Hz), and beta (12-30Hz) frequency bands. A significant positive correlation between functional connectivity with age was found in alpha and beta frequency bands. A significant negative correlation between average path lengths with age was found in beta frequency band. The results suggest that there are significant developmental changes of resting-state networks from childhood to adolescence, which matures from a lattice network to a small-world network. Copyright © 2016 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.

Within- and between-session replicability of cognitive brain processes: An MEG study with an N-back task.

PubMed

Ahonen, L; Huotilainen, M; Brattico, E

2016-05-01

In the vast majority of electrophysiological studies on cognition, participants are only measured once during a single experimental session. The dearth of studies on test-retest reliability in magnetoencephalography (MEG) within and across experimental sessions is a preventing factor for longitudinal designs, imaging genetics studies, and clinical applications. From the recorded signals, it is not straightforward to draw robust and steady indices of brain activity that could directly be used in exploring behavioral effects or genetic associations. To study the variations in markers associated with cognitive functions, we extracted three event-related field (ERF) features from time-locked global field power (GFP) epochs using MEG while participants were performing a numerical N-back task in four consecutive measurements conducted during two different days separated by two weeks. We demonstrate that the latency of the M170, a neural correlate associated with cognitive functions such as working memory, was a stable parameter and did not show significant variations over time. In addition, the M170 peak amplitude and the mean amplitude of late positive component (LPP) also expressed moderate-to-strong reliability across multiple measures over time over many sensor spaces and between participants. The M170 amplitude varied more significantly between the measurements in some conditions but showed consistency over the participants over time. In addition we demonstrated significant correlation with the M170 and LPP parameters and cognitive load. The results are in line with the literature showing less within-subject fluctuation for the latency parameters and more consistency in between-subject comparisons for amplitude based features. The within-subject consistency was apparent also with longer delays between the measurements. We suggest that with a few limitations the ERF features show sufficient reliability and stability for longitudinal research designs and clinical applications for cognitive functions in single as well as cross-subject designs. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of action observation therapy and mirror therapy after stroke on rehabilitation outcomes and neural mechanisms by MEG: study protocol for a randomized controlled trial.

PubMed

Shih, Tsai-Yu; Wu, Ching-Yi; Lin, Keh-Chung; Cheng, Chia-Hsiung; Hsieh, Yu-Wei; Chen, Chia-Ling; Lai, Chih-Jou; Chen, Chih-Chi

2017-10-04

Loss of upper-extremity motor function is one of the most debilitating deficits following stroke. Two promising treatment approaches, action observation therapy (AOT) and mirror therapy (MT), aim to enhance motor learning and promote neural reorganization in patients through different afferent inputs and patterns of visual feedback. Both approaches involve different patterns of motor observation, imitation, and execution but share some similar neural bases of the mirror neuron system. AOT and MT used in stroke rehabilitation may confer differential benefits and neural activities that remain to be determined. This clinical trial aims to investigate and compare treatment effects and neural activity changes of AOT and MT with those of the control intervention in patients with subacute stroke. An estimated total of 90 patients with subacute stroke will be recruited for this study. All participants will be randomly assigned to receive AOT, MT, or control intervention for a 3-week training period (15 sessions). Outcome measurements will be taken at baseline, immediately after treatment, and at the 3-month follow-up. For the magnetoencephalography (MEG) study, we anticipate that we will recruit 12 to 15 patients per group. The primary outcome will be the Fugl-Meyer Assessment score. Secondary outcomes will include the modified Rankin Scale, the Box and Block Test, the ABILHAND questionnaire, the Questionnaire Upon Mental Imagery, the Functional Independence Measure, activity monitors, the Stroke Impact Scale version 3.0, and MEG signals. This clinical trial will provide scientific evidence of treatment effects on motor, functional outcomes, and neural activity mechanisms after AOT and MT in patients with subacute stroke. Further application and use of AOT and MT may include telerehabilitation or home-based rehabilitation through web-based or video teaching. ClinicalTrials.gov, ID: NCT02871700 . Registered on 1 August 2016.

Simultaneous transcranial direct current stimulation (tDCS) and whole-head magnetoencephalography (MEG): assessing the impact of tDCS on slow cortical magnetic fields.

PubMed

Garcia-Cossio, Eliana; Witkowski, Matthias; Robinson, Stephen E; Cohen, Leonardo G; Birbaumer, Niels; Soekadar, Surjo R

2016-10-15

Transcranial direct current stimulation (tDCS) can influence cognitive, affective or motor brain functions. Whereas previous imaging studies demonstrated widespread tDCS effects on brain metabolism, direct impact of tDCS on electric or magnetic source activity in task-related brain areas could not be confirmed due to the difficulty to record such activity simultaneously during tDCS. The aim of this proof-of-principal study was to demonstrate the feasibility of whole-head source localization and reconstruction of neuromagnetic brain activity during tDCS and to confirm the direct effect of tDCS on ongoing neuromagnetic activity in task-related brain areas. Here we show for the first time that tDCS has an immediate impact on slow cortical magnetic fields (SCF, 0-4Hz) of task-related areas that are identical with brain regions previously described in metabolic neuroimaging studies. 14 healthy volunteers performed a choice reaction time (RT) task while whole-head magnetoencephalography (MEG) was recorded. Task-related source-activity of SCFs was calculated using synthetic aperture magnetometry (SAM) in absence of stimulation and while anodal, cathodal or sham tDCS was delivered over the right primary motor cortex (M1). Source reconstruction revealed task-related SCF modulations in brain regions that precisely matched prior metabolic neuroimaging studies. Anodal and cathodal tDCS had a polarity-dependent impact on RT and SCF in primary sensorimotor and medial centro-parietal cortices. Combining tDCS and whole-head MEG is a powerful approach to investigate the direct effects of transcranial electric currents on ongoing neuromagnetic source activity, brain function and behavior. Copyright © 2015 Elsevier Inc. All rights reserved.

Simultaneous transcranial direct current stimulation (tDCS) and whole-head magnetoencephalography (MEG): assessing the impact of tDCS on slow cortical magnetic fields

PubMed Central

Garcia-Cossio, Eliana; Witkowski, Matthias; Robinson, Stephen E.; Cohen, Leonardo G.; Birbaumer, Niels; Soekadar, Surjo R.

2016-01-01

Transcranial direct current stimulation (tDCS) can influence cognitive, affective or motor brain functions. Whereas previous imaging studies demonstrated widespread tDCS effects on brain metabolism, direct impact of tDCS on electric or magnetic source activity in task-related brain areas could not be confirmed due to the difficulty to record such activity simultaneously during tDCS. The aim of this proof-of-principal study was to demonstrate the feasibility of whole-head source localization and reconstruction of neuromagnetic brain activity during tDCS and to confirm the direct effect of tDCS on ongoing neuromagnetic activity in task-related brain areas. Here we show for the first time that tDCS has an immediate impact on slow cortical magnetic fields (SCF, 0–4 Hz) of task-related areas that are identical with brain regions previously described in metabolic neuroimaging studies. 14 healthy volunteers performed a choice reaction time (RT) task while whole-head magnetoencephalography (MEG) was recorded. Task-related source-activity of SCFs was calculated using synthetic aperture magnetometry (SAM) in absence of stimulation and while anodal, cathodal or sham tDCS was delivered over the right primary motor cortex (M1). Source reconstruction revealed task-related SCF modulations in brain regions that precisely matched prior metabolic neuroimaging studies. Anodal and cathodal tDCS had a polarity-dependent impact on RT and SCF in primary sensorimotor and medial centro-parietal cortices. Combining tDCS and whole-head MEG is a powerful approach to investigate the direct effects of transcranial electric currents on ongoing neuromagnetic source activity, brain function and behavior. PMID:26455796

Magnetocardiography and magnetoencephalography measurements at room temperature using tunnel magneto-resistance sensors

NASA Astrophysics Data System (ADS)

Fujiwara, Kosuke; Oogane, Mikihiko; Kanno, Akitake; Imada, Masahiro; Jono, Junichi; Terauchi, Takashi; Okuno, Tetsuo; Aritomi, Yuuji; Morikawa, Masahiro; Tsuchida, Masaaki; Nakasato, Nobukazu; Ando, Yasuo

2018-02-01

Magnetocardiography (MCG) and magnetoencephalography (MEG) signals were detected at room temperature using tunnel magneto-resistance (TMR) sensors. TMR sensors developed with low-noise amplifier circuits detected the MCG R wave without averaging, and the QRS complex was clearly observed with averaging at a high signal-to-noise ratio. Spatial mapping of the MCG was also achieved. Averaging of MEG signals triggered by electroencephalography (EEG) clearly observed the phase inversion of the alpha rhythm with a correlation coefficient as high as 0.7 between EEG and MEG.

The design of the MEG II experiment

NASA Astrophysics Data System (ADS)

Baldini, A. M.; Baracchini, E.; Bemporad, C.; Berg, F.; Biasotti, M.; Boca, G.; Cattaneo, P. W.; Cavoto, G.; Cei, F.; Chiappini, M.; Chiarello, G.; Chiri, C.; Cocciolo, G.; Corvaglia, A.; de Bari, A.; De Gerone, M.; D'Onofrio, A.; Francesconi, M.; Fujii, Y.; Galli, L.; Gatti, F.; Grancagnolo, F.; Grassi, M.; Grigoriev, D. N.; Hildebrandt, M.; Hodge, Z.; Ieki, K.; Ignatov, F.; Iwai, R.; Iwamoto, T.; Kaneko, D.; Kasami, K.; Kettle, P.-R.; Khazin, B. I.; Khomutov, N.; Korenchenko, A.; Kravchuk, N.; Libeiro, T.; Maki, M.; Matsuzawa, N.; Mihara, S.; Milgie, M.; Molzon, W.; Mori, Toshinori; Morsani, F.; Mtchedilishvili, A.; Nakao, M.; Nakaura, S.; Nicolò, D.; Nishiguchi, H.; Nishimura, M.; Ogawa, S.; Ootani, W.; Panareo, M.; Papa, A.; Pepino, A.; Piredda, G.; Popov, A.; Raffaelli, F.; Renga, F.; Ripiccini, E.; Ritt, S.; Rossella, M.; Rutar, G.; Sawada, R.; Signorelli, G.; Simonetta, M.; Tassielli, G. F.; Uchiyama, Y.; Usami, M.; Venturini, M.; Voena, C.; Yoshida, K.; Yudin, Yu. V.; Zhang, Y.

2018-05-01

The MEG experiment, designed to search for the {μ ^+ → e^+ γ } decay, completed data-taking in 2013 reaching a sensitivity level of {5.3× 10^{-13}} for the branching ratio. In order to increase the sensitivity reach of the experiment by an order of magnitude to the level of 6× 10^{-14}, a total upgrade, involving substantial changes to the experiment, has been undertaken, known as MEG II. We present both the motivation for the upgrade and a detailed overview of the design of the experiment and of the expected detector performance.

BabySQUID: A mobile, high-resolution multichannel magnetoencephalography system for neonatal brain assessment

NASA Astrophysics Data System (ADS)

Okada, Yoshio; Pratt, Kevin; Atwood, Christopher; Mascarenas, Anthony; Reineman, Richard; Nurminen, Jussi; Paulson, Douglas

2006-02-01

We developed a prototype of a mobile, high-resolution, multichannel magnetoencephalography (MEG) system, called babySQUID, for assessing brain functions in newborns and infants. Unlike electroencephalography, MEG signals are not distorted by the scalp or the fontanels and sutures in the skull. Thus, brain activity can be measured and localized with MEG as if the sensors were above an exposed brain. The babySQUID is housed in a moveable cart small enough to be transported from one room to another. To assess brain functions, one places the baby on the bed of the cart and the head on its headrest with MEG sensors just below. The sensor array consists of 76 first-order axial gradiometers, each with a pickup coil diameter of 6mm and a baseline of 30mm, in a high-density array with a spacing of 12-14mm center-to-center. The pickup coils are 6±1mm below the outer surface of the headrest. The short gap provides unprecedented sensitivity since the scalp and skull are thin (as little as 3-4mm altogether) in babies. In an electromagnetically unshielded room in a hospital, the field sensitivity at 1kHz was ˜17fT/√Hz. The noise was reduced from ˜400to200fT/√Hz at 1Hz using a reference cancellation technique and further to ˜40fT/√Hz using a gradient common mode rejection technique. Although the residual environmental magnetic noise interfered with the operation of the babySQUID, the instrument functioned sufficiently well to detect spontaneous brain signals from babies with a signal to noise ratio (SNR) of as much as 7.6:1. In a magnetically shielded room, the field sensitivity was 17fT/√Hz at 20Hz and 30fT/√Hz at 1Hz without implementation of reference or gradient cancellation. The sensitivity was sufficiently high to detect spontaneous brain activity from a 7month old baby with a SNR as much as 40:1 and evoked somatosensory responses with a 50Hz bandwidth after as little as four averages. We expect that both the noise and the sensor gap can be reduced further by approximately half with a gain in SNR of about four. Thus, we conclude from the performance of the prototype that it should be feasible to improve the babySQUID to detect cortical activity in infants in real time with high spatial resolution.

Comparing Features for Classification of MEG Responses to Motor Imagery.

PubMed

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio-spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system.

Adsorption and regeneration of expanded graphite modified by CTAB-KBr/H3PO4 for marine oil pollution.

PubMed

Xu, Congbin; Jiao, Chunlei; Yao, Ruihua; Lin, Aijun; Jiao, Wentao

2018-02-01

The cleaning-up of viscous oil spilled in ocean is a global challenge, especially in Bohai, due to its slow current movement and poor self-purification capacity. Frequent oil-spill accidents not only cause severe and long-term damages to marine ecosystems, but also lead to a great loss of valuable resources. To eliminate the environmental pollution of oil spills, an efficient and environment-friendly oil-recovery approach is necessary. In this study, 1 expanded graphite (EG) modified by CTAB-KBr/H 3 PO 4 was synthesized via composite intercalation agents of CTAB-KBr and natural flake graphite, followed by the activation of phosphoric acid at low temperature. The resultant modified expanded graphite (M-EG) obtained an interconnected and continuous open microstructure with lower polarity surface, more and larger pores, and increased surface hydrophobicity. Due to these characteristics, M-EG exhibited a superior adsorption capacity towards marine oil. The saturated adsorption capacities of M-EG were as large as 7.44  g/g for engine oil, 6.12 g/g for crude oil, 5.34 g/g for diesel oil and 4.10 g/g for gasoline oil in 120min, exceeding the capacity of pristine EG. Furthermore, M-EG maintained good removal efficiency under different adsorption conditions, such as temperature, oil types, and sodium salt concentration. In addition, oils sorbed into M-EG could be recovered either by a simple compression or filtration-drying treatment with a recovery ratio of 58-83%. However, filtration-drying treatment shows better performance in preserving microstructures of M-EG, which ensures the adsorbents can be recycled several times. High removal capability, fast adsorption efficiency, excellent stability and good recycling performance make M-EG an ideal candidate for treating marine oil pollution in practical application. Copyright © 2017 Elsevier Ltd. All rights reserved.

Synergistic hydrate inhibition of monoethylene glycol with poly(vinylcaprolactam) in thermodynamically underinhibited system.

PubMed

Kim, Jakyung; Shin, Kyuchul; Seo, Yutaek; Cho, Seong Jun; Lee, Ju Dong

2014-07-31

This study investigates the hydrate inhibition performance of monoethylene glycol (MEG) with poly(vinylcaprolactam) (PVCap) for retarding the hydrate onset as well as preventing the agglomeration of hydrate particles. A high-pressure autoclave was used to determine the hydrate onset time, subcooling temperature, hydrate fraction in the liquid phase, and torque changes during hydrate formation in pure water, 0.2 wt % PVCap solution, and 20 and 30 wt % MEG solutions. In comparison to water with no inhibitors, the addition of PVCap delays the hydrate onset time but cannot reduce the hydrate fraction, leading to a sharp increase in torque. The 20 and 30 wt % MEG solutions also delay the hydrate onset time slightly and reduce the hydrate fraction to 0.15. The addition of 0.2 wt % PVCap to the 20 wt % MEG solution, however, delays the hydrate onset time substantially, and the hydrate fraction was less than 0.19. The torque changes were negligible during the hydrate formation, suggesting the homogeneous dispersion of hydrate particles in the liquid phase. The well-dispersed hydrate particles do not agglomerate or deposit under stirring. Moreover, when 0.2 wt % PVCap was added to the 30 wt % MEG solution, no hydrate formation was observed for at least 24 h. These results suggest that mixing of MEG with a small amount of PVCap in underinhibited conditions will induce the synergistic inhibition of hydrate by delaying the hydrate onset time as well as preventing the agglomeration and deposition of hydrate particles. Decreasing the hydrate fraction in the liquid phase might be the reason for negligible torque changes during the hydrate formation in the 0.2 wt % PVCap and 20 wt % MEG solution. Simple structure II was confirmed by in situ Raman spectroscopy for the synergistic inhibition system, while coexisting structures I and II are observed in 0.2 wt % PVCap solution.

Magnetoencephalographic imaging of deep corticostriatal network activity during a rewards paradigm.

PubMed

Kanal, Eliezer Y; Sun, Mingui; Ozkurt, Tolga E; Jia, Wenyan; Sclabassi, Robert

2009-01-01

The human rewards network is a complex system spanning both cortical and subcortical regions. While much is known about the functions of the various components of the network, research on the behavior of the network as a whole has been stymied due to an inability to detect signals at a high enough temporal resolution from both superficial and deep network components simultaneously. In this paper, we describe the application of magnetoencephalographic imaging (MEG) combined with advanced signal processing techniques to this problem. Using data collected while subjects performed a rewards-related gambling paradigm demonstrated to activate the rewards network, we were able to identify neural signals which correspond to deep network activity. We also show that this signal was not observable prior to filtration. These results suggest that MEG imaging may be a viable tool for the detection of deep neural activity.

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... the price volatility for purified terephthalic acid (PTA) and monoethylene glycol (MEG) used in the... adjustment to its cost of manufacturing information which accounts for purchases of PTA and MEG from...

Multiple exciton generation for photoelectrochemical hydrogen evolution reactions with quantum yields exceeding 100%

DOE PAGES

Yan, Yong; Crisp, Ryan W.; Gu, Jing; ...

2017-04-03

Multiple exciton generation (MEG) in quantum dots (QDs) has the potential to greatly increase the power conversion efficiency in solar cells and in solar-fuel production. During the MEG process, two electron-hole pairs (excitons) are created from the absorption of one high-energy photon, bypassing hot-carrier cooling via phonon emission. Here we demonstrate that extra carriers produced via MEG can be used to drive a chemical reaction with quantum efficiency above 100%. We developed a lead sulfide (PbS) QD photoelectrochemical cell that is able to drive hydrogen evolution from aqueous Na 2S solution with a peak external quantum efficiency exceeding 100%. QDmore » photoelectrodes that were measured all demonstrated MEG when the incident photon energy was larger than 2.7 times the bandgap energy. Finally, our results demonstrate a new direction in exploring high-efficiency approaches to solar fuels.« less

Source localization of brain activity using helium-free interferometer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dammers, Jürgen, E-mail: J.Dammers@fz-juelich.de; Chocholacs, Harald; Eich, Eberhard

2014-05-26

To detect extremely small magnetic fields generated by the human brain, currently all commercial magnetoencephalography (MEG) systems are equipped with low-temperature (low-T{sub c}) superconducting quantum interference device (SQUID) sensors that use liquid helium for cooling. The limited and increasingly expensive supply of helium, which has seen dramatic price increases recently, has become a real problem for such systems and the situation shows no signs of abating. MEG research in the long run is now endangered. In this study, we report a MEG source localization utilizing a single, highly sensitive SQUID cooled with liquid nitrogen only. Our findings confirm that localizationmore » of neuromagnetic activity is indeed possible using high-T{sub c} SQUIDs. We believe that our findings secure the future of this exquisitely sensitive technique and have major implications for brain research and the developments of cost-effective multi-channel, high-T{sub c} SQUID-based MEG systems.« less

Reduction of Werner Syndrome Protein Enhances G:C → A:T Transition by O6-Methylguanine in Human Cells.

PubMed

Suzuki, Tetsuya; Kuramoto, Yoshie; Kamiya, Hiroyuki

2018-05-21

O 6 -Methylguanine ( O 6 -MeG) is a damaged base produced by methylating reagents. The Werner syndrome protein (WRN) is a cancer-related human DNA helicase. The effects of WRN reduction on O 6 -MeG-caused mutagenesis were assessed by an siRNA-mediated knockdown in human U2OS cells, using a shuttle plasmid with a single O 6 -MeG base in the supF gene. The plasmid DNA was replicated in the cells, isolated, and electroporated into an Escherichia coli indicator strain. The lowered amount of WRN increased the frequency of mutations induced by O 6 -MeG, mainly G:C → A:T substitution. The increased mutation rate suggested that the cancer-related WRN suppresses the G:C → A:T substitution by O 6 -MeG in human cells.

Deficits in auditory processing contribute to impairments in vocal affect recognition in autism spectrum disorders: A MEG study.

PubMed

Demopoulos, Carly; Hopkins, Joyce; Kopald, Brandon E; Paulson, Kim; Doyle, Lauren; Andrews, Whitney E; Lewine, Jeffrey David

2015-11-01

The primary aim of this study was to examine whether there is an association between magnetoencephalography-based (MEG) indices of basic cortical auditory processing and vocal affect recognition (VAR) ability in individuals with autism spectrum disorder (ASD). MEG data were collected from 25 children/adolescents with ASD and 12 control participants using a paired-tone paradigm to measure quality of auditory physiology, sensory gating, and rapid auditory processing. Group differences were examined in auditory processing and vocal affect recognition ability. The relationship between differences in auditory processing and vocal affect recognition deficits was examined in the ASD group. Replicating prior studies, participants with ASD showed longer M1n latencies and impaired rapid processing compared with control participants. These variables were significantly related to VAR, with the linear combination of auditory processing variables accounting for approximately 30% of the variability after controlling for age and language skills in participants with ASD. VAR deficits in ASD are typically interpreted as part of a core, higher order dysfunction of the "social brain"; however, these results suggest they also may reflect basic deficits in auditory processing that compromise the extraction of socially relevant cues from the auditory environment. As such, they also suggest that therapeutic targeting of sensory dysfunction in ASD may have additional positive implications for other functional deficits. (c) 2015 APA, all rights reserved).

Quality assessment of MEG-to-MRI coregistrations

NASA Astrophysics Data System (ADS)

Sonntag, Hermann; Haueisen, Jens; Maess, Burkhard

2018-04-01

For high precision in source reconstruction of magnetoencephalography (MEG) or electroencephalography data, high accuracy of the coregistration of sources and sensors is mandatory. Usually, the source space is derived from magnetic resonance imaging (MRI). In most cases, however, no quality assessment is reported for sensor-to-MRI coregistrations. If any, typically root mean squares (RMS) of point residuals are provided. It has been shown, however, that RMS of residuals do not correlate with coregistration errors. We suggest using target registration error (TRE) as criterion for the quality of sensor-to-MRI coregistrations. TRE measures the effect of uncertainty in coregistrations at all points of interest. In total, 5544 data sets with sensor-to-head and 128 head-to-MRI coregistrations, from a single MEG laboratory, were analyzed. An adaptive Metropolis algorithm was used to estimate the optimal coregistration and to sample the coregistration parameters (rotation and translation). We found an average TRE between 1.3 and 2.3 mm at the head surface. Further, we observed a mean absolute difference in coregistration parameters between the Metropolis and iterative closest point algorithm of (1.9 +/- 15){\\hspace{0pt}}\\circ and (1.1 +/- 9) m. A paired sample t-test indicated a significant improvement in goal function minimization by using the Metropolis algorithm. The sampled parameters allowed computation of TRE on the entire grid of the MRI volume. Hence, we recommend the Metropolis algorithm for head-to-MRI coregistrations.

[Magneto-encephalographic (MEG) brain recordings during traumatic memory recall in women with post-traumatic stress disorder: A pilot study].

PubMed

Cottraux, J; Lecaignard, F; Yao, S-N; De Mey-Guillard, C; Haour, F; Delpuech, C; Servan-Schreiber, D

2015-06-01

The experiment studied the effects of a short duration exposure to traumatic memories using magneto-encephalography (MEG). Nine right-handed DSM-4 PTSD patients were recruited from a unit for anxiety disorders and an organisation supporting victims of violence. In order to have a homogeneous sample, we included only women who suffered from civilian PTSD. Exclusion criteria were co-morbid major medical illness, metallic dental prostheses that would interfere in the magnetic measurement, and current drug treatment. All participants were free from neurological disease and had normal hearing. They signed a written informed consent form. An ethics committee accepted the study. A tape-recorded voice administered a script-driven imagery. The patients had to imagine, successively, a neutral image, a traumatic memory and rest, while MEG measured brain activities across delta, theta, alpha and beta bands. Each condition lasted three minutes. Heart rate (HR), anxiety and the vividness of mental images were recorded at the end of each phase. MEG power analysis was carried out with Statistical Parametric Mapping (SPM) 8. The signals were averaged for each of the three conditions of threeminutes duration. The dependent variable was a subtracted value: (trauma - rest) - (neutral - rest). The significance threshold was set at P<0.01. Anxiety and HR significantly increased during the trauma condition and returned to the neutral level during rest. The vividness of the mental imagery remained stable across the three conditions. The left-brain demonstrated a statistically significant power decrease in the secondary visual cortex (BA 18-19) in the delta band, the insula (BA13) in the beta band, the insula (BA13), premotor cortex (BA 6), Broca area (BA 44), and BA 43, in the alpha band. The symptom provocation protocol was successful in eliciting subjective anxiety and HR response in relation to traumatic memories. Our MEG results are in keeping with previous neuro-imagery studies showing decreased activities in the insula and Broca area during PTSD symptom provocation. However, we did not replicate the activation in the amygdala and the cingulate and prefrontal cortex found in some studies. Moreover, the within-group design, the small sample, and the inclusion of only female patients with milder dissociative symptoms limit our conclusions. The MEG protocol we used may also explain some partial discrepancies with previous MEG studies. However, our aim was to provoke a specific autobiographic recall of a traumatic event unfolding several sequential mental images along three minutes as in exposure therapy for PTSD. Despite its limitations, this pilot study is the first to provide MEG data during trauma recall. It suggests that recalling a specific traumatic event along three minutes results in hypo-activations of the brain regions regulating language and emotions. This paves the way to recording whole sessions of specific therapies for PTSD, with MEG using the millisecond resolution. MEG might be of interest to study the suppression of traumatic memories and their activation and habituation through prolonged graduated exposure in imagination across several sessions. MEG could also be used to study the effects of medication on PTSD symptoms. A controlled replication in a larger sample including male and female patients with various traumatic experiences is needed. Copyright © 2014 L’Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

Performance of the Helium Circulation System on a Commercialized MEG

NASA Astrophysics Data System (ADS)

T, Takeda; M, Okamoto; T, Miyazaki; K, Katagiri

2012-12-01

We report the performance of a helium circulation system (HCS) mounted on a MEG (Magnetoencephalography) at Nagoya University, Japan. This instrument is the first commercialized version of an HCS. The HCS collects warm helium gas at approximately 300 K and then cools it to approximately 40 K. The gas is returned to the neck tube of a Dewar of the MEG to keep it cold. It also collects helium gas in the region just above the liquid helium surface while it is still cold, re-liquefies the gas and returns it to the Dewar. A special transfer tube (TT) of approximately 3 m length was developed to allow for dual helium streams. This tube separates the HCS using a MEG to reduce magnetic noise. A refiner was incorporated to effectively collect contaminating gases by freezing them. The refiner was equipped with an electric heater to remove the frozen contaminants as gases into the air. A gas flow controller was also developed, which automatically controlled the heater and electric valves to clean up contamination. The developed TT exhibited a very low heat inflow of less than 0.1 W/m to the liquid helium, ensuring efficient operation. The insert tube diameter, which was 1.5 in. was reduced to a standard 0.5 in. size. This dimensional change enabled the HCS to mount onto any commercialized MEG without any modifications to the MEG. The HCS can increase liquid helium in the Dewar by at least 3 liters/Day using two GM cryocoolers (SRDK-415D, Sumitomo Heavy Industries, Ltd.). The noise levels were virtually the same as before this installation.

Source-reconstruction of the sensorimotor network from resting-state macaque electrocorticography.

PubMed

Hindriks, R; Micheli, C; Bosman, C A; Oostenveld, R; Lewis, C; Mantini, D; Fries, P; Deco, G

2018-06-07

The discovery of hemodynamic (BOLD-fMRI) resting-state networks (RSNs) has brought about a fundamental shift in our thinking about the role of intrinsic brain activity. The electrophysiological underpinnings of RSNs remain largely elusive and it has been shown only recently that electric cortical rhythms are organized into the same RSNs as hemodynamic signals. Most electrophysiological studies into RSNs use magnetoencephalography (MEG) or scalp electroencephalography (EEG), which limits the spatial resolution with which electrophysiological RSNs can be observed. Due to their close proximity to the cortical surface, electrocorticographic (ECoG) recordings can potentially provide a more detailed picture of the functional organization of resting-state cortical rhythms, albeit at the expense of spatial coverage. In this study we propose using source-space spatial independent component analysis (spatial ICA) for identifying generators of resting-state cortical rhythms as recorded with ECoG and for reconstructing their functional connectivity. Network structure is assessed by two kinds of connectivity measures: instantaneous correlations between band-limited amplitude envelopes and oscillatory phase-locking. By simulating rhythmic cortical generators, we find that the reconstruction of oscillatory phase-locking is more challenging than that of amplitude correlations, particularly for low signal-to-noise levels. Specifically, phase-lags can both be over- and underestimated, which troubles the interpretation of lag-based connectivity measures. We illustrate the methodology on somatosensory beta rhythms recorded from a macaque monkey using ECoG. The methodology decomposes the resting-state sensorimotor network into three cortical generators, distributed across primary somatosensory and primary and higher-order motor areas. The generators display significant and reproducible amplitude correlations and phase-locking values with non-zero lags. Our findings illustrate the level of spatial detail attainable with source-projected ECoG and motivates wider use of the methodology for studying resting-state as well as event-related cortical dynamics in macaque and human. Copyright © 2018. Published by Elsevier Inc.

Senior Research Fellow Wins Major International Science Award | News | NREL

Science.gov Websites

generation (MEG) in semiconductor nanocrystals, also called quantum dots, and recently found efficient MEG in silicon quantum dots. He shares the award with Stefan W. Glunz of the Fraunhofer Institute in Germany

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Neural source dynamics of brain responses to continuous stimuli: Speech processing from acoustics to comprehension.

PubMed

Brodbeck, Christian; Presacco, Alessandro; Simon, Jonathan Z

2018-05-15

Human experience often involves continuous sensory information that unfolds over time. This is true in particular for speech comprehension, where continuous acoustic signals are processed over seconds or even minutes. We show that brain responses to such continuous stimuli can be investigated in detail, for magnetoencephalography (MEG) data, by combining linear kernel estimation with minimum norm source localization. Previous research has shown that the requirement to average data over many trials can be overcome by modeling the brain response as a linear convolution of the stimulus and a kernel, or response function, and estimating a kernel that predicts the response from the stimulus. However, such analysis has been typically restricted to sensor space. Here we demonstrate that this analysis can also be performed in neural source space. We first computed distributed minimum norm current source estimates for continuous MEG recordings, and then computed response functions for the current estimate at each source element, using the boosting algorithm with cross-validation. Permutation tests can then assess the significance of individual predictor variables, as well as features of the corresponding spatio-temporal response functions. We demonstrate the viability of this technique by computing spatio-temporal response functions for speech stimuli, using predictor variables reflecting acoustic, lexical and semantic processing. Results indicate that processes related to comprehension of continuous speech can be differentiated anatomically as well as temporally: acoustic information engaged auditory cortex at short latencies, followed by responses over the central sulcus and inferior frontal gyrus, possibly related to somatosensory/motor cortex involvement in speech perception; lexical frequency was associated with a left-lateralized response in auditory cortex and subsequent bilateral frontal activity; and semantic composition was associated with bilateral temporal and frontal brain activity. We conclude that this technique can be used to study the neural processing of continuous stimuli in time and anatomical space with the millisecond temporal resolution of MEG. This suggests new avenues for analyzing neural processing of naturalistic stimuli, without the necessity of averaging over artificially short or truncated stimuli. Copyright © 2018 Elsevier Inc. All rights reserved.

Functional source separation and hand cortical representation for a brain–computer interface feature extraction

PubMed Central

Tecchio, Franca; Porcaro, Camillo; Barbati, Giulia; Zappasodi, Filippo

2007-01-01

A brain–computer interface (BCI) can be defined as any system that can track the person's intent which is embedded in his/her brain activity and, from it alone, translate the intention into commands of a computer. Among the brain signal monitoring systems best suited for this challenging task, electroencephalography (EEG) and magnetoencephalography (MEG) are the most realistic, since both are non-invasive, EEG is portable and MEG could provide more specific information that could be later exploited also through EEG signals. The first two BCI steps require set up of the appropriate experimental protocol while recording the brain signal and then to extract interesting features from the recorded cerebral activity. To provide information useful in these BCI stages, our aim is to provide an overview of a new procedure we recently developed, named functional source separation (FSS). As it comes from the blind source separation algorithms, it exploits the most valuable information provided by the electrophysiological techniques, i.e. the waveform signal properties, remaining blind to the biophysical nature of the signal sources. FSS returns the single trial source activity, estimates the time course of a neuronal pool along different experimental states on the basis of a specific functional requirement in a specific time period, and uses the simulated annealing as the optimization procedure allowing the exploit of functional constraints non-differentiable. Moreover, a minor section is included, devoted to information acquired by MEG in stroke patients, to guide BCI applications aiming at sustaining motor behaviour in these patients. Relevant BCI features – spatial and time-frequency properties – are in fact altered by a stroke in the regions devoted to hand control. Moreover, a method to investigate the relationship between sensory and motor hand cortical network activities is described, providing information useful to develop BCI feedback control systems. This review provides a description of the FSS technique, a promising tool for the BCI community for online electrophysiological feature extraction, and offers interesting information to develop BCI applications to sustain hand control in stroke patients. PMID:17331989

A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals.

PubMed

Kim, Yoon Jae; Park, Sung Woo; Yeom, Hong Gi; Bang, Moon Suk; Kim, June Sic; Chung, Chun Kee; Kim, Sungwan

2015-08-20

A brain-machine interface (BMI) should be able to help people with disabilities by replacing their lost motor functions. To replace lost functions, robot arms have been developed that are controlled by invasive neural signals. Although invasive neural signals have a high spatial resolution, non-invasive neural signals are valuable because they provide an interface without surgery. Thus, various researchers have developed robot arms driven by non-invasive neural signals. However, robot arm control based on the imagined trajectory of a human hand can be more intuitive for patients. In this study, therefore, an integrated robot arm-gripper system (IRAGS) that is driven by three-dimensional (3D) hand trajectories predicted from non-invasive neural signals was developed and verified. The IRAGS was developed by integrating a six-degree of freedom robot arm and adaptive robot gripper. The system was used to perform reaching and grasping motions for verification. The non-invasive neural signals, magnetoencephalography (MEG) and electroencephalography (EEG), were obtained to control the system. The 3D trajectories were predicted by multiple linear regressions. A target sphere was placed at the terminal point of the real trajectories, and the system was commanded to grasp the target at the terminal point of the predicted trajectories. The average correlation coefficient between the predicted and real trajectories in the MEG case was [Formula: see text] ([Formula: see text]). In the EEG case, it was [Formula: see text] ([Formula: see text]). The success rates in grasping the target plastic sphere were 18.75 and 7.50 % with MEG and EEG, respectively. The success rates of touching the target were 52.50 and 58.75 % respectively. A robot arm driven by 3D trajectories predicted from non-invasive neural signals was implemented, and reaching and grasping motions were performed. In most cases, the robot closely approached the target, but the success rate was not very high because the non-invasive neural signal is less accurate. However the success rate could be sufficiently improved for practical applications by using additional sensors. Robot arm control based on hand trajectories predicted from EEG would allow for portability, and the performance with EEG was comparable to that with MEG.

Head movement compensation in real-time magnetoencephalographic recordings.

PubMed

Little, Graham; Boe, Shaun; Bardouille, Timothy

2014-01-01

Neurofeedback- and brain-computer interface (BCI)-based interventions can be implemented using real-time analysis of magnetoencephalographic (MEG) recordings. Head movement during MEG recordings, however, can lead to inaccurate estimates of brain activity, reducing the efficacy of the intervention. Most real-time applications in MEG have utilized analyses that do not correct for head movement. Effective means of correcting for head movement are needed to optimize the use of MEG in such applications. Here we provide preliminary validation of a novel analysis technique, real-time source estimation (rtSE), that measures head movement and generates corrected current source time course estimates in real-time. rtSE was applied while recording a calibrated phantom to determine phantom position localization accuracy and source amplitude estimation accuracy under stationary and moving conditions. Results were compared to off-line analysis methods to assess validity of the rtSE technique. The rtSE method allowed for accurate estimation of current source activity at the source-level in real-time, and accounted for movement of the source due to changes in phantom position. The rtSE technique requires modifications and specialized analysis of the following MEG work flow steps.•Data acquisition•Head position estimation•Source localization•Real-time source estimation This work explains the technical details and validates each of these steps.

Magnetoencephalography as a Tool in Psychiatric Research: Current Status and Perspective.

PubMed

Uhlhaas, Peter J; Liddle, Peter; Linden, David E J; Nobre, Anna C; Singh, Krish D; Gross, Joachim

2017-04-01

The application of neuroimaging to provide mechanistic insights into circuit dysfunctions in major psychiatric conditions and the development of biomarkers are core challenges in current psychiatric research. We propose that recent technological and analytic advances in magnetoencephalography (MEG), a technique that allows measurement of neuronal events directly and noninvasively with millisecond resolution, provides novel opportunities to address these fundamental questions. Because of its potential in delineating normal and abnormal brain dynamics, we propose that MEG provides a crucial tool to advance our understanding of pathophysiological mechanisms of major neuropsychiatric conditions, such as schizophrenia, autism spectrum disorders, and the dementias. We summarize the mechanisms underlying the generation of MEG signals and the tools available to reconstruct generators and underlying networks using advanced source-reconstruction techniques. We then surveyed recent studies that have used MEG to examine aberrant rhythmic activity in neuropsychiatric disorders. This was followed by links with preclinical research that has highlighted possible neurobiological mechanisms, such as disturbances in excitation/inhibition parameters, that could account for measured changes in neural oscillations. Finally, we discuss challenges as well as novel methodological developments that could pave the way for widespread application of MEG in translational research with the aim of developing biomarkers for early detection and diagnosis.

Analysis of simultaneous MEG and intracranial LFP recordings during Deep Brain Stimulation: a protocol and experimental validation

PubMed Central

Oswal, Ashwini; Jha, Ashwani; Neal, Spencer; Reid, Alphonso; Bradbury, David; Aston, Peter; Limousin, Patricia; Foltynie, Tom; Zrinzo, Ludvic; Brown, Peter; Litvak, Vladimir

2016-01-01

Background Deep Brain Stimulation (DBS) is an effective treatment for several neurological and psychiatric disorders. In order to gain insights into the therapeutic mechanisms of DBS and to advance future therapies a better understanding of the effects of DBS on large-scale brain networks is required. New method In this paper, we describe an experimental protocol and analysis pipeline for simultaneously performing DBS and intracranial local field potential (LFP) recordings at a target brain region during concurrent magnetoencephalography (MEG) measurement. Firstly we describe a phantom setup that allowed us to precisely characterise the MEG artefacts that occurred during DBS at clinical settings. Results Using the phantom recordings we demonstrate that with MEG beamforming it is possible to recover oscillatory activity synchronised to a reference channel, despite the presence of high amplitude artefacts evoked by DBS. Finally, we highlight the applicability of these methods by illustrating in a single patient with Parkinson's disease (PD), that changes in cortical-subthalamic nucleus coupling can be induced by DBS. Comparison with existing approaches To our knowledge this paper provides the first technical description of a recording and analysis pipeline for combining simultaneous cortical recordings using MEG, with intracranial LFP recordings of a target brain nucleus during DBS. PMID:26698227

Convergence of circuit dysfunction in ASD: a common bridge between diverse genetic and environmental risk factors and common clinical electrophysiology.

PubMed

Port, Russell G; Gandal, Michael J; Roberts, Timothy P L; Siegel, Steven J; Carlson, Gregory C

2014-01-01

Most recent estimates indicate that 1 in 68 children are affected by an autism spectrum disorder (ASD). Though decades of research have uncovered much about these disorders, the pathological mechanism remains unknown. Hampering efforts is the seeming inability to integrate findings over the micro to macro scales of study, from changes in molecular, synaptic and cellular function to large-scale brain dysfunction impacting sensory, communicative, motor and cognitive activity. In this review, we describe how studies focusing on neuronal circuit function provide unique context for identifying common neurobiological disease mechanisms of ASD. We discuss how recent EEG and MEG studies in subjects with ASD have repeatedly shown alterations in ensemble population recordings (both in simple evoked related potential latencies and specific frequency subcomponents). Because these disease-associated electrophysiological abnormalities have been recapitulated in rodent models, studying circuit differences in these models may provide access to abnormal circuit function found in ASD. We then identify emerging in vivo and ex vivo techniques, focusing on how these assays can characterize circuit level dysfunction and determine if these abnormalities underlie abnormal clinical electrophysiology. Such circuit level study in animal models may help us understand how diverse genetic and environmental risks can produce a common set of EEG, MEG and anatomical abnormalities found in ASD.

Application of modern tests for stationarity to single-trial MEG data: transferring powerful statistical tools from econometrics to neuroscience.

PubMed

Kipiński, Lech; König, Reinhard; Sielużycki, Cezary; Kordecki, Wojciech

2011-10-01

Stationarity is a crucial yet rarely questioned assumption in the analysis of time series of magneto- (MEG) or electroencephalography (EEG). One key drawback of the commonly used tests for stationarity of encephalographic time series is the fact that conclusions on stationarity are only indirectly inferred either from the Gaussianity (e.g. the Shapiro-Wilk test or Kolmogorov-Smirnov test) or the randomness of the time series and the absence of trend using very simple time-series models (e.g. the sign and trend tests by Bendat and Piersol). We present a novel approach to the analysis of the stationarity of MEG and EEG time series by applying modern statistical methods which were specifically developed in econometrics to verify the hypothesis that a time series is stationary. We report our findings of the application of three different tests of stationarity--the Kwiatkowski-Phillips-Schmidt-Schin (KPSS) test for trend or mean stationarity, the Phillips-Perron (PP) test for the presence of a unit root and the White test for homoscedasticity--on an illustrative set of MEG data. For five stimulation sessions, we found already for short epochs of duration of 250 and 500 ms that, although the majority of the studied epochs of single MEG trials were usually mean-stationary (KPSS test and PP test), they were classified as nonstationary due to their heteroscedasticity (White test). We also observed that the presence of external auditory stimulation did not significantly affect the findings regarding the stationarity of the data. We conclude that the combination of these tests allows a refined analysis of the stationarity of MEG and EEG time series.

Tracking neural coding of perceptual and semantic features of concrete nouns

PubMed Central

Sudre, Gustavo; Pomerleau, Dean; Palatucci, Mark; Wehbe, Leila; Fyshe, Alona; Salmelin, Riitta; Mitchell, Tom

2015-01-01

We present a methodological approach employing magnetoencephalography (MEG) and machine learning techniques to investigate the flow of perceptual and semantic information decodable from neural activity in the half second during which the brain comprehends the meaning of a concrete noun. Important information about the cortical location of neural activity related to the representation of nouns in the human brain has been revealed by past studies using fMRI. However, the temporal sequence of processing from sensory input to concept comprehension remains unclear, in part because of the poor time resolution provided by fMRI. In this study, subjects answered 20 questions (e.g. is it alive?) about the properties of 60 different nouns prompted by simultaneous presentation of a pictured item and its written name. Our results show that the neural activity observed with MEG encodes a variety of perceptual and semantic features of stimuli at different times relative to stimulus onset, and in different cortical locations. By decoding these features, our MEG-based classifier was able to reliably distinguish between two different concrete nouns that it had never seen before. The results demonstrate that there are clear differences between the time course of the magnitude of MEG activity and that of decodable semantic information. Perceptual features were decoded from MEG activity earlier in time than semantic features, and features related to animacy, size, and manipulability were decoded consistently across subjects. We also observed that regions commonly associated with semantic processing in the fMRI literature may not show high decoding results in MEG. We believe that this type of approach and the accompanying machine learning methods can form the basis for further modeling of the flow of neural information during language processing and a variety of other cognitive processes. PMID:22565201

Fast Neural Dynamics of Proactive Cognitive Control in a Task-Switching Analogue of the Wisconsin Card Sorting Test.

PubMed

Gema Díaz-Blancat; Juan García-Prieto; Fernando Maestú; Francisco Barceló

2018-05-01

One common assumption has been that prefrontal executive control is mostly required for target detection (Posner and Petersen in Ann Rev Neurosci 13:25-42, 1990). Alternatively, cognitive control has also been related to anticipatory updating of task-set (contextual) information, a view that highlights proactive control processes. Frontoparietal cortical networks contribute to both proactive control and reactive target detection, although their fast dynamics are still largely unexplored. To examine this, we analyzed rapid magnetoencephalographic (MEG) source activations elicited by task cues and target cards in a task-cueing analogue of the Wisconsin Card Sorting Test. A single-task (color sorting) condition with equivalent perceptual and motor demands was used as a control. Our results revealed fast, transient and largely switch-specific MEG activations across frontoparietal and cingulo-opercular regions in anticipation of target cards, including (1) early (100-200 ms) cue-locked MEG signals at visual, temporo-parietal and prefrontal cortices of the right hemisphere (i.e., calcarine sulcus, precuneus, inferior frontal gyrus, anterior insula and supramarginal gyrus); and (2) later cue-locked MEG signals at the right anterior and posterior insula (200-300 ms) and the left temporo-parietal junction (300-500 ms). In all cases larger MEG signal intensity was observed in switch relative to repeat cueing conditions. Finally, behavioral restart costs and test scores of working memory capacity (forward digit span) correlated with cue-locked MEG activations at key nodes of the frontoparietal network. Together, our findings suggest that proactive cognitive control of task rule updating can be fast and transiently implemented within less than a second and in anticipation of target detection.

Correlation between magnetoencephalography-based "clusterectomy" and postoperative seizure freedom.

PubMed

Vadera, Sumeet; Jehi, Lara; Burgess, Richard C; Shea, Katherine; Alexopoulos, Andreas V; Mosher, John; Gonzalez-Martinez, Jorge; Bingaman, William

2013-06-01

During the presurgical evaluation of patients with medically intractable focal epilepsy, a variety of noninvasive studies are performed to localize the hypothetical epileptogenic zone and guide the resection. Magnetoencephalography (MEG) is becoming increasingly used in the clinical realm for this purpose. No investigators have previously reported on coregisteration of MEG clusters with postoperative resection cavities to evaluate whether complete "clusterectomy" (resection of the area associated with MEG clusters) was performed or to compare these findings with postoperative seizure-free outcomes. The authors retrospectively reviewed the charts and imaging studies of 65 patients undergoing MEG followed by resective epilepsy surgery from 2009 until 2012 at the Cleveland Clinic. Preoperative MEG studies were fused with postoperative MRI studies to evaluate whether clusters were within the resected area. These data were then correlated with postoperative seizure freedom. Sixty-five patients were included in this study. The average duration of follow-up was 13.9 months, the mean age at surgery was 23.1 years, and the mean duration of epilepsy was 13.7 years. In 30 patients, the main cluster was located completely within the resection cavity, in 28 it was completely outside the resection cavity, and in 7 it was partially within the resection cavity. Seventy-four percent of patients were seizure free at 12 months after surgery, and this rate decreased to 60% at 24 months. Improved likelihood of seizure freedom was seen with complete clusterectomy in patients with localization outside the temporal lobe (extra-temporal lobe epilepsy) (p = 0.04). In patients with preoperative MEG studies that show clusters in surgically accessible areas outside the temporal lobe, we suggest aggressive resection to improve the chances for seizure freedom. When the cluster is found within the temporal lobe, further diagnostic testing may be required to better localize the epileptogenic zone.

Combining EEG and MEG for the Reconstruction of Epileptic Activity Using a Calibrated Realistic Volume Conductor Model

PubMed Central

Aydin, Ümit; Vorwerk, Johannes; Küpper, Philipp; Heers, Marcel; Kugel, Harald; Galka, Andreas; Hamid, Laith; Wellmer, Jörg; Kellinghaus, Christoph; Rampp, Stefan; Wolters, Carsten Hermann

2014-01-01

To increase the reliability for the non-invasive determination of the irritative zone in presurgical epilepsy diagnosis, we introduce here a new experimental and methodological source analysis pipeline that combines the complementary information in EEG and MEG, and apply it to data from a patient, suffering from refractory focal epilepsy. Skull conductivity parameters in a six compartment finite element head model with brain anisotropy, constructed from individual MRI data, are estimated in a calibration procedure using somatosensory evoked potential (SEP) and field (SEF) data. These data are measured in a single run before acquisition of further runs of spontaneous epileptic activity. Our results show that even for single interictal spikes, volume conduction effects dominate over noise and need to be taken into account for accurate source analysis. While cerebrospinal fluid and brain anisotropy influence both modalities, only EEG is sensitive to skull conductivity and conductivity calibration significantly reduces the difference in especially depth localization of both modalities, emphasizing its importance for combining EEG and MEG source analysis. On the other hand, localization differences which are due to the distinct sensitivity profiles of EEG and MEG persist. In case of a moderate error in skull conductivity, combined source analysis results can still profit from the different sensitivity profiles of EEG and MEG to accurately determine location, orientation and strength of the underlying sources. On the other side, significant errors in skull modeling are reflected in EEG reconstruction errors and could reduce the goodness of fit to combined datasets. For combined EEG and MEG source analysis, we therefore recommend calibrating skull conductivity using additionally acquired SEP/SEF data. PMID:24671208

Multivariate matching pursuit in optimal Gabor dictionaries: theory and software with interface for EEG/MEG via Svarog

PubMed Central

2013-01-01

Background Matching pursuit algorithm (MP), especially with recent multivariate extensions, offers unique advantages in analysis of EEG and MEG. Methods We propose a novel construction of an optimal Gabor dictionary, based upon the metrics introduced in this paper. We implement this construction in a freely available software for MP decomposition of multivariate time series, with a user friendly interface via the Svarog package (Signal Viewer, Analyzer and Recorder On GPL, http://braintech.pl/svarog), and provide a hands-on introduction to its application to EEG. Finally, we describe numerical and mathematical optimizations used in this implementation. Results Optimal Gabor dictionaries, based on the metric introduced in this paper, for the first time allowed for a priori assessment of maximum one-step error of the MP algorithm. Variants of multivariate MP, implemented in the accompanying software, are organized according to the mathematical properties of the algorithms, relevant in the light of EEG/MEG analysis. Some of these variants have been successfully applied to both multichannel and multitrial EEG and MEG in previous studies, improving preprocessing for EEG/MEG inverse solutions and parameterization of evoked potentials in single trials; we mention also ongoing work and possible novel applications. Conclusions Mathematical results presented in this paper improve our understanding of the basics of the MP algorithm. Simple introduction of its properties and advantages, together with the accompanying stable and user-friendly Open Source software package, pave the way for a widespread and reproducible analysis of multivariate EEG and MEG time series and novel applications, while retaining a high degree of compatibility with the traditional, visual analysis of EEG. PMID:24059247

Multiple-region directed functional connectivity based on phase delays.

PubMed

Goelman, Gadi; Dan, Rotem

2017-03-01

Network analysis is increasingly advancing the field of neuroimaging. Neural networks are generally constructed from pairwise interactions with an assumption of linear relations between them. Here, a high-order statistical framework to calculate directed functional connectivity among multiple regions, using wavelet analysis and spectral coherence has been presented. The mathematical expression for 4 regions was derived and used to characterize a quartet of regions as a linear, combined (nonlinear), or disconnected network. Phase delays between regions were used to obtain network's temporal hierarchy and directionality. The validity of the mathematical derivation along with the effects of coupling strength and noise on its outcomes were studied by computer simulations of the Kuramoto model. The simulations demonstrated correct directionality for a large range of coupling strength and low sensitivity to Gaussian noise compared with pairwise coherences. The analysis was applied to resting-state fMRI data of 40 healthy young subjects to characterize the ventral visual system, motor system and default mode network (DMN). It was shown that the ventral visual system was predominantly composed of linear networks while the motor system and the DMN were composed of combined (nonlinear) networks. The ventral visual system exhibits its known temporal hierarchy, the motor system exhibits center ↔ out hierarchy and the DMN has dorsal ↔ ventral and anterior ↔ posterior organizations. The analysis can be applied in different disciplines such as seismology, or economy and in a variety of brain data including stimulus-driven fMRI, electrophysiology, EEG, and MEG, thus open new horizons in brain research. Hum Brain Mapp 38:1374-1386, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A new methodology for automated diagnosis of mild cognitive impairment (MCI) using magnetoencephalography (MEG).

PubMed

Amezquita-Sanchez, Juan P; Adeli, Anahita; Adeli, Hojjat

2016-05-15

Mild cognitive impairment (MCI) is a cognitive disorder characterized by memory impairment, greater than expected by age. A new methodology is presented to identify MCI patients during a working memory task using MEG signals. The methodology consists of four steps: In step 1, the complete ensemble empirical mode decomposition (CEEMD) is used to decompose the MEG signal into a set of adaptive sub-bands according to its contained frequency information. In step 2, a nonlinear dynamics measure based on permutation entropy (PE) analysis is employed to analyze the sub-bands and detect features to be used for MCI detection. In step 3, an analysis of variation (ANOVA) is used for feature selection. In step 4, the enhanced probabilistic neural network (EPNN) classifier is applied to the selected features to distinguish between MCI and healthy patients. The usefulness and effectiveness of the proposed methodology are validated using the sensed MEG data obtained experimentally from 18 MCI and 19 control patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Photoinduced Single- and Multiple-Electron Dynamics Processes Enhanced by Quantum Confinement in Lead Halide Perovskite Quantum Dots

DOE PAGES

Vogel, Dayton J.; Kryjevski, Andrei; Inerbaev, Talgat; ...

2017-03-21

Methylammonium lead iodide perovskite (MAPbI 3) is a promising material for photovoltaic devices. A modification of MAPbI 3 into confined nanostructures is expected to further increase efficiency of solar energy conversion. Photoexcited dynamic processes in a MAPbI3 quantum dot (QD) have been modeled by many-body perturbation theory and nonadiabatic dynamics. A photoexcitation is followed by either exciton cooling (EC), its radiative (RR) or nonradiative recombination (NRR), or multiexciton generation (MEG) processes. Computed times of these processes fall in the order of MEG < EC < RR < NRR, where MEG is on the order of a few femtoseconds, EC ismore » in the picosecond range, while RR and NRR are on the order of nanoseconds. Computed time scales indicate which electronic transition pathways can contribute to increase in charge collection efficiency. Simulated mechanisms of relaxation and their rates show that quantum confinement promotes MEG in MAPbI 3 QDs.« less

Comparing Features for Classification of MEG Responses to Motor Imagery

PubMed Central

Halme, Hanna-Leena; Parkkonen, Lauri

2016-01-01

Background Motor imagery (MI) with real-time neurofeedback could be a viable approach, e.g., in rehabilitation of cerebral stroke. Magnetoencephalography (MEG) noninvasively measures electric brain activity at high temporal resolution and is well-suited for recording oscillatory brain signals. MI is known to modulate 10- and 20-Hz oscillations in the somatomotor system. In order to provide accurate feedback to the subject, the most relevant MI-related features should be extracted from MEG data. In this study, we evaluated several MEG signal features for discriminating between left- and right-hand MI and between MI and rest. Methods MEG was measured from nine healthy participants imagining either left- or right-hand finger tapping according to visual cues. Data preprocessing, feature extraction and classification were performed offline. The evaluated MI-related features were power spectral density (PSD), Morlet wavelets, short-time Fourier transform (STFT), common spatial patterns (CSP), filter-bank common spatial patterns (FBCSP), spatio—spectral decomposition (SSD), and combined SSD+CSP, CSP+PSD, CSP+Morlet, and CSP+STFT. We also compared four classifiers applied to single trials using 5-fold cross-validation for evaluating the classification accuracy and its possible dependence on the classification algorithm. In addition, we estimated the inter-session left-vs-right accuracy for each subject. Results The SSD+CSP combination yielded the best accuracy in both left-vs-right (mean 73.7%) and MI-vs-rest (mean 81.3%) classification. CSP+Morlet yielded the best mean accuracy in inter-session left-vs-right classification (mean 69.1%). There were large inter-subject differences in classification accuracy, and the level of the 20-Hz suppression correlated significantly with the subjective MI-vs-rest accuracy. Selection of the classification algorithm had only a minor effect on the results. Conclusions We obtained good accuracy in sensor-level decoding of MI from single-trial MEG data. Feature extraction methods utilizing both the spatial and spectral profile of MI-related signals provided the best classification results, suggesting good performance of these methods in an online MEG neurofeedback system. PMID:27992574

Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer's disease.

PubMed

Nakamura, Akinori; Cuesta, Pablo; Fernández, Alberto; Arahata, Yutaka; Iwata, Kaori; Kuratsubo, Izumi; Bundo, Masahiko; Hattori, Hideyuki; Sakurai, Takashi; Fukuda, Koji; Washimi, Yukihiko; Endo, Hidetoshi; Takeda, Akinori; Diers, Kersten; Bajo, Ricardo; Maestú, Fernando; Ito, Kengo; Kato, Takashi

2018-05-01

Biomarkers useful for the predementia stages of Alzheimer's disease are needed. Electroencephalography and magnetoencephalography (MEG) are expected to provide potential biomarker candidates for evaluating the predementia stages of Alzheimer's disease. However, the physiological relevance of EEG/MEG signal changes and their role in pathophysiological processes such as amyloid-β deposition and neurodegeneration need to be elucidated. We evaluated 28 individuals with mild cognitive impairment and 38 cognitively normal individuals, all of whom were further classified into amyloid-β-positive mild cognitive impairment (n = 17, mean age 74.7 ± 5.4 years, nine males), amyloid-β-negative mild cognitive impairment (n = 11, mean age 73.8 ± 8.8 years, eight males), amyloid-β-positive cognitively normal (n = 13, mean age 71.8 ± 4.4 years, seven males), and amyloid-β-negative cognitively normal (n = 25, mean age 72.5 ± 3.4 years, 11 males) individuals using Pittsburgh compound B-PET. We measured resting state MEG for 5 min with the eyes closed, and investigated regional spectral patterns of MEG signals using atlas-based region of interest analysis. Then, the relevance of the regional spectral patterns and their associations with pathophysiological backgrounds were analysed by integrating information from Pittsburgh compound B-PET, fluorodeoxyglucose-PET, structural MRI, and cognitive tests. The results demonstrated that regional spectral patterns of resting state activity could be separated into several types of MEG signatures as follows: (i) the effects of amyloid-β deposition were expressed as the alpha band power augmentation in medial frontal areas; (ii) the delta band power increase in the same region was associated with disease progression within the Alzheimer's disease continuum and was correlated with entorhinal atrophy and an Alzheimer's disease-like regional decrease in glucose metabolism; and (iii) the global theta power augmentation, which was previously considered to be an Alzheimer's disease-related EEG/MEG signature, was associated with general cognitive decline and hippocampal atrophy, but was not specific to Alzheimer's disease because these changes could be observed in the absence of amyloid-β deposition. The results suggest that these MEG signatures may be useful as unique biomarkers for the predementia stages of Alzheimer's disease.

Annotation: What Electrical Brain Activity Tells Us about Brain Function that Other Techniques Cannot Tell Us--A Child Psychiatric Perspective

ERIC Educational Resources Information Center

Banaschewski, Tobias; Brandeis, Daniel

2007-01-01

Background: Monitoring brain processes in real time requires genuine subsecond resolution to follow the typical timing and frequency of neural events. Non-invasive recordings of electric (EEG/ERP) and magnetic (MEG) fields provide this time resolution. They directly measure neural activations associated with a wide variety of brain states and…

Charting the Functional Relevance of Broca's Area for Visual Word Recognition and Picture Naming in Dutch Using fMRI-Guided TMS

ERIC Educational Resources Information Center

Wheat, Katherine L.; Cornelissen, Piers L.; Sack, Alexander T.; Schuhmann, Teresa; Goebel, Rainer; Blomert, Leo

2013-01-01

Magnetoencephalography (MEG) has shown pseudohomophone priming effects at Broca's area (specifically pars opercularis of left inferior frontal gyrus and precentral gyrus; LIFGpo/PCG) within [approximately]100 ms of viewing a word. This is consistent with Broca's area involvement in fast phonological access during visual word recognition. Here we…

A variational Bayes spatiotemporal model for electromagnetic brain mapping.

PubMed

Nathoo, F S; Babul, A; Moiseev, A; Virji-Babul, N; Beg, M F

2014-03-01

In this article, we present a new variational Bayes approach for solving the neuroelectromagnetic inverse problem arising in studies involving electroencephalography (EEG) and magnetoencephalography (MEG). This high-dimensional spatiotemporal estimation problem involves the recovery of time-varying neural activity at a large number of locations within the brain, from electromagnetic signals recorded at a relatively small number of external locations on or near the scalp. Framing this problem within the context of spatial variable selection for an underdetermined functional linear model, we propose a spatial mixture formulation where the profile of electrical activity within the brain is represented through location-specific spike-and-slab priors based on a spatial logistic specification. The prior specification accommodates spatial clustering in brain activation, while also allowing for the inclusion of auxiliary information derived from alternative imaging modalities, such as functional magnetic resonance imaging (fMRI). We develop a variational Bayes approach for computing estimates of neural source activity, and incorporate a nonparametric bootstrap for interval estimation. The proposed methodology is compared with several alternative approaches through simulation studies, and is applied to the analysis of a multimodal neuroimaging study examining the neural response to face perception using EEG, MEG, and fMRI. © 2013, The International Biometric Society.

Four-channel optically pumped atomic magnetometer for magnetoencephalography

PubMed Central

Colombo, Anthony P.; Carter, Tony R.; Borna, Amir; Jau, Yuan-Yu; Johnson, Cort N.; Dagel, Amber L.; Schwindt, Peter D. D.

2016-01-01

We have developed a four-channel optically pumped atomic magnetometer for magnetoencephalography (MEG) that incorporates a passive diffractive optical element (DOE). The DOE allows us to achieve a long, 18-mm gradiometer baseline in a compact footprint on the head. Using gradiometry, the sensitivities of the channels are < 5 fT/Hz1/2, and the 3-dB bandwidths are approximately 90 Hz, which are both sufficient to perform MEG. Additionally, the channels are highly uniform, which offers the possibility of employing standard MEG post-processing techniques. This module will serve as a building block of an array for magnetic source localization. PMID:27410816

Four-channel optically pumped atomic magnetometer for magnetoencephalography

DOE PAGES

Colombo, Anthony P.; Carter, Tony R.; Borna, Amir; ...

2016-06-29

We have developed a four-channel optically pumped atomic magnetometer for magnetoencephalography (MEG) that incorporates a passive diffractive optical element (DOE). The DOE allows us to achieve a long, 18-mm gradiometer baseline in a compact footprint on the head. Using gradiometry, the sensitivities of the channels are < 5 fT/Hz 1/2, and the 3-dB bandwidths are approximately 90 Hz, which are both sufficient to perform MEG. Additionally, the channels are highly uniform, which offers the possibility of employing standard MEG post-processing techniques. As a result, this module will serve as a building block of an array for magnetic source localization.

Theoretical Efficiency of 3rd Generation Solar Cells: Comparison between Carrier Multiplication and Down-Conversion

DTIC Science & Technology

2012-01-01

rewrite this equation using a generalization of Eq. (6), for a given multiplicity mrM : ym Z 1 mEg E2dE eE=kTS1 Z 1 Eg E2dE eE=kTS1 ð13Þ Note that...vectorized quadrature algorithms . We used the quadgk function in Matlab to evaluate all function, since it is best at handling the pole at EqV¼0 in the

Malagasy Backward Object Control

ERIC Educational Resources Information Center

Potsdam, Eric

2009-01-01

Backward control is an obligatory interpretational dependency between an overt controller and a nonovert controllee in which the controllee is structurally superior to the controller: "Meg persuaded [Delta]i" ["Roni to give up"]. It contrasts with ordinary forward control, in which the controller is structurally higher: "Meg persuaded Roni"…

Estimation of the velocity and trajectory of three-dimensional reaching movements from non-invasive magnetoencephalography signals

NASA Astrophysics Data System (ADS)

Yeom, Hong Gi; Sic Kim, June; Chung, Chun Kee

2013-04-01

Objective. Studies on the non-invasive brain-machine interface that controls prosthetic devices via movement intentions are at their very early stages. Here, we aimed to estimate three-dimensional arm movements using magnetoencephalography (MEG) signals with high accuracy. Approach. Whole-head MEG signals were acquired during three-dimensional reaching movements (center-out paradigm). For movement decoding, we selected 68 MEG channels in motor-related areas, which were band-pass filtered using four subfrequency bands (0.5-8, 9-22, 25-40 and 57-97 Hz). After the filtering, the signals were resampled, and 11 data points preceding the current data point were used as features for estimating velocity. Multiple linear regressions were used to estimate movement velocities. Movement trajectories were calculated by integrating estimated velocities. We evaluated our results by calculating correlation coefficients (r) between real and estimated velocities. Main results. Movement velocities could be estimated from the low-frequency MEG signals (0.5-8 Hz) with significant and considerably high accuracy (p <0.001, mean r > 0.7). We also showed that preceding (60-140 ms) MEG signals are important to estimate current movement velocities and the intervals of brain signals of 200-300 ms are sufficient for movement estimation. Significance. These results imply that disabled people will be able to control prosthetic devices without surgery in the near future.

Estimation of hyper-parameters for a hierarchical model of combined cortical and extra-brain current sources in the MEG inverse problem.

PubMed

Morishige, Ken-ichi; Yoshioka, Taku; Kawawaki, Dai; Hiroe, Nobuo; Sato, Masa-aki; Kawato, Mitsuo

2014-11-01

One of the major obstacles in estimating cortical currents from MEG signals is the disturbance caused by magnetic artifacts derived from extra-cortical current sources such as heartbeats and eye movements. To remove the effect of such extra-brain sources, we improved the hybrid hierarchical variational Bayesian method (hyVBED) proposed by Fujiwara et al. (NeuroImage, 2009). hyVBED simultaneously estimates cortical and extra-brain source currents by placing dipoles on cortical surfaces as well as extra-brain sources. This method requires EOG data for an EOG forward model that describes the relationship between eye dipoles and electric potentials. In contrast, our improved approach requires no EOG and less a priori knowledge about the current variance of extra-brain sources. We propose a new method, "extra-dipole," that optimally selects hyper-parameter values regarding current variances of the cortical surface and extra-brain source dipoles. With the selected parameter values, the cortical and extra-brain dipole currents were accurately estimated from the simulated MEG data. The performance of this method was demonstrated to be better than conventional approaches, such as principal component analysis and independent component analysis, which use only statistical properties of MEG signals. Furthermore, we applied our proposed method to measured MEG data during covert pursuit of a smoothly moving target and confirmed its effectiveness. Copyright © 2014 Elsevier Inc. All rights reserved.

Attention training improves aberrant neural dynamics during working memory processing in veterans with PTSD.

PubMed

McDermott, Timothy J; Badura-Brack, Amy S; Becker, Katherine M; Ryan, Tara J; Bar-Haim, Yair; Pine, Daniel S; Khanna, Maya M; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2016-12-01

Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory (WM). Recent studies suggest that attention training reduces PTSD symptomatology, but the underlying neural mechanisms are unknown. We used high-density magnetoencephalography (MEG) to evaluate whether attention training modulates brain regions serving WM processing in PTSD. Fourteen veterans with PTSD completed a WM task during a 306-sensor MEG recording before and after 8 sessions of attention training treatment. A matched comparison sample of 12 combat-exposed veterans without PTSD completed the same WM task during a single MEG session. To identify the spatiotemporal dynamics, each group's data were transformed into the time-frequency domain, and significant oscillatory brain responses were imaged using a beamforming approach. All participants exhibited activity in left hemispheric language areas consistent with a verbal WM task. Additionally, veterans with PTSD and combat-exposed healthy controls each exhibited oscillatory responses in right hemispheric homologue regions (e.g., right Broca's area); however, these responses were in opposite directions. Group differences in oscillatory activity emerged in the theta band (4-8 Hz) during encoding and in the alpha band (9-12 Hz) during maintenance and were significant in right prefrontal and right supramarginal and inferior parietal regions. Importantly, following attention training, these significant group differences were reduced or eliminated. This study provides initial evidence that attention training improves aberrant neural activity in brain networks serving WM processing.

Time course of gamma-band oscillation associated with face processing in the inferior occipital gyrus and fusiform gyrus: A combined fMRI and MEG study.

PubMed

Uono, Shota; Sato, Wataru; Kochiyama, Takanori; Kubota, Yasutaka; Sawada, Reiko; Yoshimura, Sayaka; Toichi, Motomi

2017-04-01

Debate continues over whether the inferior occipital gyrus (IOG) or the fusiform gyrus (FG) represents the first stage of face processing and what role these brain regions play. We investigated this issue by combining functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG) in normal adults. Participants passively observed upright and inverted faces and houses. First, we identified the IOG and FG as face-specific regions using fMRI. We applied beamforming source reconstruction and time-frequency analysis to MEG source signals to reveal the time course of gamma-band activations in these regions. The results revealed that the right IOG showed higher gamma-band activation in response to upright faces than to upright houses at 100 ms from the stimulus onset. Subsequently, the right FG showed greater gamma-band response to upright faces versus upright houses at around 170 ms. The gamma-band activation in the right IOG and right FG was larger in response to inverted faces than to upright faces at the later time window. These results suggest that (1) the gamma-band activities occurs rapidly first in the IOG and next in the FG and (2) the gamma-band activity in the right IOG at later time stages is involved in configuration processing for faces. Hum Brain Mapp 38:2067-2079, 2017. © 2017 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Environmental distribution of two widespread uncultured freshwater Euryarchaeota clades unveiled by specific primers and quantitative PCR.

PubMed

Restrepo-Ortiz, Claudia X; Casamayor, Emilio O

2013-12-01

Quantitative environmental distribution of two widely distributed uncultured freshwater Euryarchaeota with unknown functional role was explored by newly designed quantitative PCR primers targeting the 16S rRNA gene of clades Miscellaneous Euryarchaeota Group (MEG, containing the groups pMC2A384 and VALII/Eury4) and Deep-Sea Euryarchaeotal Groups (DSEG, targeting the cluster named VALIII containing the DHVE-3/DSEG, BC07-2A-27/DSEG-3 and DSEG-2 groups), respectively. The summer surface plankton of 28 lakes was analysed, and one additional dimictic deep alpine lake, Lake Redon, was temporally and vertically surveyed covering seasonal limnological variability. A trophic range between 0.2 and 5.2 μg l(-1) Chl a, and pH span from 3.8 to 9.5 was explored at altitudes between 632 and 2590 m above sea level. The primers showed to be highly selective with c. 85% coverage and 100% specificity. Only pH significantly explained the changes observed in gene abundances and environment. In Lake Redon, DSEG bloomed in deep stratified waters both in summer and early spring, and MEG at intermediate depths during the ice-cover period. Overall, MEG and DSEG showed a differential ecological distribution although correlational analyses indicated lack of coupling of both Euryarchaeota with phytoplankton (chlorophyll a). However, an intriguing positive and significant relationship was found between DSEG and putative ammonia oxidizing thaumarchaeota. © 2013 John Wiley & Sons Ltd and Society for Applied Microbiology.

Spatiotemporal imaging of complexity

PubMed Central

Robinson, Stephen E.; Mandell, Arnold J.; Coppola, Richard

2013-01-01

What are the functional neuroimaging measurements required for more fully characterizing the events and locations of neocortical activity? A prime assumption has been that modulation of cortical activity will inevitably be reflected in changes in energy utilization (for the most part) changes of glucose and oxygen consumption. Are such a measures complete and sufficient? More direct measures of cortical electrophysiological activity show event or task-related modulation of amplitude or band-limited oscillatory power. Using magnetoencephalography (MEG), these measures have been shown to correlate well with energy utilization sensitive BOLD fMRI. In this paper, we explore the existence of state changes in electrophysiological cortical activity that can occur independently of changes in averaged amplitude, source power or indices of metabolic rates. In addition, we demonstrate that such state changes can be described by applying a new measure of complexity, rank vector entropy (RVE), to source waveform estimates from beamformer-processed MEG. RVE is a non-parametric symbolic dynamic informational entropy measure that accommodates the wide dynamic range of measured brain signals while resolving its temporal variations. By representing the measurements by their rank values, RVE overcomes the problem of defining embedding space partitions without resorting to signal compression. This renders RVE-independent of absolute signal amplitude. In addition, this approach is robust, being relatively free of tunable parameters. We present examples of task-free and task-dependent MEG demonstrating that RVE provides new information by uncovering hidden dynamical structure in the apparent turbulent (or chaotic) dynamics of spontaneous cortical activity. PMID:23355820

Masked Repetition Priming Using Magnetoencephalography

ERIC Educational Resources Information Center

Monahan, Philip J.; Fiorentino, Robert; Poeppel, David

2008-01-01

Masked priming is used in psycholinguistic studies to assess questions about lexical access and representation. We present two masked priming experiments using MEG. If the MEG signal elicited by words reflects specific aspects of lexical retrieval, then one expects to identify specific neural correlates of retrieval that are sensitive to priming.…

MEG Evidence for Incremental Sentence Composition in the Anterior Temporal Lobe

ERIC Educational Resources Information Center

Brennan, Jonathan R.; Pylkkänen, Liina

2017-01-01

Research investigating the brain basis of language comprehension has associated the left anterior temporal lobe (ATL) with sentence-level combinatorics. Using magnetoencephalography (MEG), we test the parsing strategy implemented in this brain region. The number of incremental parse steps from a predictive left-corner parsing strategy that is…

MULTIMEDIA ENVIRONMENTAL GOALS FOR ENVIRONMENTAL ASSESSMENT: VOLUME III. MEG CHARTS AND BACKGROUND INFORMATION SUMMARIES (CATEGORIES 1-12)

EPA Science Inventory

Multimedia Environmental Goals (MEG's) are levels of significant contaminants or degradents (in ambient air, water, or land or in emissions of effluents conveyed to the ambient media) that are judged to be (1) appropriate for preventing certain negative effects in the surrounding...

Semantic and Phonological Task-Set Priming and Stimulus Processing Investigated Using Magnetoencephalography (MEG)

ERIC Educational Resources Information Center

McNab, F.; Rippon, G.; Hillebrand, A.; Singh, K. D.; Swithenby, S. J.

2007-01-01

In this study the neural substrates of semantic and phonological task priming and task performance were investigated using single word task-primes. Magnetoencephalography (MEG) data were analysed using Synthetic Aperture Magnetometry (SAM) to determine the spatiotemporal and spectral characteristics of cortical responses. Comparisons were made…

SQUIDs in biomagnetism: a roadmap towards improved healthcare

NASA Astrophysics Data System (ADS)

Körber, Rainer; Storm, Jan-Hendrik; Seton, Hugh; Mäkelä, Jyrki P.; Paetau, Ritva; Parkkonen, Lauri; Pfeiffer, Christoph; Riaz, Bushra; Schneiderman, Justin F.; Dong, Hui; Hwang, Seong-min; You, Lixing; Inglis, Ben; Clarke, John; Espy, Michelle A.; Ilmoniemi, Risto J.; Magnelind, Per E.; Matlashov, Andrei N.; Nieminen, Jaakko O.; Volegov, Petr L.; Zevenhoven, Koos C. J.; Höfner, Nora; Burghoff, Martin; Enpuku, Keiji; Yang, S. Y.; Chieh, Jen-Jei; Knuutila, Jukka; Laine, Petteri; Nenonen, Jukka

2016-11-01

Globally, the demand for improved health care delivery while managing escalating costs is a major challenge. Measuring the biomagnetic fields that emanate from the human brain already impacts the treatment of epilepsy, brain tumours and other brain disorders. This roadmap explores how superconducting technologies are poised to impact health care. Biomagnetism is the study of magnetic fields of biological origin. Biomagnetic fields are typically very weak, often in the femtotesla range, making their measurement challenging. The earliest in vivo human measurements were made with room-temperature coils. In 1963, Baule and McFee (1963 Am. Heart J. 55 95-6) reported the magnetic field produced by electric currents in the heart (‘magnetocardiography’), and in 1968, Cohen (1968 Science 161 784-6) described the magnetic field generated by alpha-rhythm currents in the brain (‘magnetoencephalography’). Subsequently, in 1970, Cohen et al (1970 Appl. Phys. Lett. 16 278-80) reported the recording of a magnetocardiogram using a Superconducting QUantum Interference Device (SQUID). Just two years later, in 1972, Cohen (1972 Science 175 664-6) described the use of a SQUID in magnetoencephalography. These last two papers set the scene for applications of SQUIDs in biomagnetism, the subject of this roadmap. The SQUID is a combination of two fundamental properties of superconductors. The first is flux quantization—the fact that the magnetic flux Φ in a closed superconducting loop is quantized in units of the magnetic flux quantum, Φ0 ≡ h/2e, ≈ 2.07 × 10-15 Tm2 (Deaver and Fairbank 1961 Phys. Rev. Lett. 7 43-6, Doll R and Näbauer M 1961 Phys. Rev. Lett. 7 51-2). Here, h is the Planck constant and e the elementary charge. The second property is the Josephson effect, predicted in 1962 by Josephson (1962 Phys. Lett. 1 251-3) and observed by Anderson and Rowell (1963 Phys. Rev. Lett. 10 230-2) in 1963. The Josephson junction consists of two weakly coupled superconductors separated by a tunnel barrier or other weak link. A tiny electric current is able to flow between the superconductors as a supercurrent, without developing a voltage across them. At currents above the ‘critical current’ (maximum supercurrent), however, a voltage is developed. In 1964, Jaklevic et al (1964 Phys. Rev. Lett. 12 159-60) observed quantum interference between two Josephson junctions connected in series on a superconducting loop, giving birth to the dc SQUID. The essential property of the SQUID is that a steady increase in the magnetic flux threading the loop causes the critical current to oscillate with a period of one flux quantum. In today’s SQUIDs, using conventional semiconductor readout electronics, one can typically detect a change in Φ corresponding to 10-6 Φ0 in one second. Although early practical SQUIDs were usually made from bulk superconductors, for example, niobium or Pb-Sn solder blobs, today’s devices are invariably made from thin superconducting films patterned with photolithography or even electron lithography. An extensive description of SQUIDs and their applications can be found in the SQUID Handbooks (Clarke and Braginski 2004 Fundamentals and Technology of SQUIDs and SQUID Systems vol I (Weinheim, Germany: Wiley-VCH), Clarke and Braginski 2006 Applications of SQUIDs and SQUID Systems vol II (Weinheim, Germany: Wiley-VCH)). The roadmap begins (chapter 1) with a brief review of the state-of-the-art of SQUID-based magnetometers and gradiometers for biomagnetic measurements. The magnetic field noise referred to the pick-up loop is typically a few fT Hz-1/2, often limited by noise in the metallized thermal insulation of the dewar rather than by intrinsic SQUID noise. The authors describe a pathway to achieve an intrinsic magnetic field noise as low as 0.1 fT Hz-1/2, approximately the Nyquist noise of the human body. They also descibe a technology to defeat dewar noise. Chapter 2 reviews the neuroscientific and clinical use of magnetoencephalography (MEG), by far the most widespread application of biomagnetism with systems containing typically 300 sensors cooled to liquid-helium temperature, 4.2 K. Two important clinical applications are presurgical mapping of focal epilepsy and of eloquent cortex in brain-tumor patients. Reducing the sensor-to-brain separation and the system noise level would both improve spatial resolution. The very recent commercial innovation that replaces the need for frequent manual transfer of liquid helium with an automated system that collects and liquefies the gas and transfers the liquid to the dewar will make MEG systems more accessible. A highly promising means of placing the sensors substantially closer to the scalp for MEG is to use high-transition-temperature (high-T c) SQUID sensors and flux transformers (chapter 3). Operation of these devices at liquid-nitrogen temperature, 77 K, enables one to minimize or even omit metallic thermal insulation between the sensors and the dewar. Noise levels of a few fT Hz-1/2 have already been achieved, and lower values are likely. The dewars can be made relatively flexible, and thus able to be placed close to the skull irrespective of the size of the head, potentially providing higher spatial resolution than liquid-helium based systems. The successful realization of a commercial high-T c MEG system would have a major commercial impact. Chapter 4 introduces the concept of SQUID-based ultra-low-field magnetic resonance imaging (ULF MRI) operating at typically several kHz, some four orders of magnitude lower than conventional, clinical MRI machines. Potential advantages of ULF MRI include higher image contrast than for conventional MRI, enabling methodologies not currently available. Examples include screening for cancer without a contrast agent, imaging traumatic brain injury (TBI) and degenerative diseases such as Alzheimer’s, and determining the elapsed time since a stroke. The major current problem with ULF MRI is that its signal-to-noise ratio (SNR) is low compared with high-field MRI. Realistic solutions to this problem are proposed, including implementing sensors with a noise level of 0.1 fT Hz-1/2. A logical and exciting prospect (chapter 5) is to combine MEG and ULF MRI into a single system in which both signal sources are detected with the same array of SQUIDs. A prototype system is described. The combination of MEG and ULF MRI allows one to obtain structural images of the head concurrently with the recording of brain activity. Since all MEG images require an MRI to determine source locations underlying the MEG signal, the combined modality would give a precise registration of the two images; the combination of MEG with high-field MRI can produce registration errors as large as 5 mm. The use of multiple sensors for ULF MRI increases both the SNR and the field of view. Chapter 6 describes another potentially far-reaching application of ULF MRI, namely neuronal current imaging (NCI) of the brain. Currently available neuronal imaging techniques include MEG, which is fast but has relatively poor spatial resolution, perhaps 10 mm, and functional MRI (fMRI) which has a millimeter resolution but is slow, on the order of seconds, and furthermore does not directly measure neuronal signals. NCI combines the ability of direct measurement of MEG with the spatial precision of MRI. In essence, the magnetic fields generated by neural currents shift the frequency of the magnetic resonance signal at a location that is imaged by the three-dimensional magnetic field gradients that form the basis of MRI. The currently achieved sensitivity of NCI is not quite sufficient to realize its goal, but it is close. The realization of NCI would represent a revolution in functional brain imaging. Improved techniques for immunoassay are always being sought, and chapter 7 introduces an entirely new topic, magnetic nanoparticles for immunoassay. These particles are bio-funtionalized, for example with a specific antibody which binds to its corresponding antigen, if it is present. Any resulting changes in the properties of the nanoparticles are detected with a SQUID. For liquid-phase detection, there are three basic methods: AC susceptibility, magnetic relaxation and remanence measurement. These methods, which have been successfully implemented for both in vivo and ex vivo applications, are highly sensitive and, although further development is required, it appears highly likely that at least some of them will be commercialized. Chapter 8 concludes the roadmap with an assessment of the commercial market for MEG systems. Despite the huge advances that have been realized since MEG was first introduced, the number of commercial systems deployed around the world remains small, around 250 units employing about 50 000 SQUIDs. The slow adoption of this technology is undoubtedly in part due to the high cost, not least because of the need to surround the entire system in an expensive magnetically shielded room. Nonetheless, the recent introduction of automatically refilling liquid-helium systems, the ongoing reduction in sensor noise, the potential availability of high-T c SQUID systems, the availability of new and better software and the combination of MEG with ULF MRI all have the potential to increase the market size in the not-so-distant future. In particular, there is a great and growing need for better noninvasive technologies to measure brain function. There are hundreds of millions of people in the world who suffer from brain disorders such as epilepsy, stroke, dementia or depression. The enormous cost to society of these diseases can be reduced by earlier and more accurate detection and diagnosis. Once the challenges outlined in this roadmap have been met and the outstanding problems have been solved, the potential demand for SQUID-based health technology can be expected to increase by ten- if not hundred-fold.

[A magnetoencephalographic study of generalised developmental disorders. A new proposal for their classification].

PubMed

Muñoz Yunta, J A; Palau Baduell, M; Salvado Salvado, B; Amo, C; Fernandez Lucas, A; Maestu, F; Ortiz, T

2004-02-01

Autistic spectrum disorders (ASD) is a term that is not included in DSM IV or in ICD 10, which are the diagnostic tools most commonly used by clinical professionals but can offer problems in research when it comes to finding homogenous groups. From a neuropaediatric point of view, there is a need for a classification of the generalised disorders affecting development and for this purpose we used Wing's triad, which defines the continuum of the autistic spectrum, and the information provided by magnetoencephalography (MEG) as grouping elements. Specific generalised developmental disorders were taken as being those syndromes that partially expressed some autistic trait, but with their own personality so that they could be considered to be a specific disorder. ASD were classified as being primary, cryptogenic or secondary. The primary disorders, in turn, express a continuum that ranges from Savant syndrome to Asperger's syndrome and the different degrees of early infantile autism. MEG is a functional neuroimaging technique that has enabled us to back up this classification.

Performance evaluation of the Champagne source reconstruction algorithm on simulated and real M/EEG data.

PubMed

Owen, Julia P; Wipf, David P; Attias, Hagai T; Sekihara, Kensuke; Nagarajan, Srikantan S

2012-03-01

In this paper, we present an extensive performance evaluation of a novel source localization algorithm, Champagne. It is derived in an empirical Bayesian framework that yields sparse solutions to the inverse problem. It is robust to correlated sources and learns the statistics of non-stimulus-evoked activity to suppress the effect of noise and interfering brain activity. We tested Champagne on both simulated and real M/EEG data. The source locations used for the simulated data were chosen to test the performance on challenging source configurations. In simulations, we found that Champagne outperforms the benchmark algorithms in terms of both the accuracy of the source localizations and the correct estimation of source time courses. We also demonstrate that Champagne is more robust to correlated brain activity present in real MEG data and is able to resolve many distinct and functionally relevant brain areas with real MEG and EEG data. Copyright © 2011 Elsevier Inc. All rights reserved.

Convergence of circuit dysfunction in ASD: a common bridge between diverse genetic and environmental risk factors and common clinical electrophysiology

PubMed Central

Port, Russell G.; Gandal, Michael J.; Roberts, Timothy P. L.; Siegel, Steven J.; Carlson, Gregory C.

2014-01-01

Most recent estimates indicate that 1 in 68 children are affected by an autism spectrum disorder (ASD). Though decades of research have uncovered much about these disorders, the pathological mechanism remains unknown. Hampering efforts is the seeming inability to integrate findings over the micro to macro scales of study, from changes in molecular, synaptic and cellular function to large-scale brain dysfunction impacting sensory, communicative, motor and cognitive activity. In this review, we describe how studies focusing on neuronal circuit function provide unique context for identifying common neurobiological disease mechanisms of ASD. We discuss how recent EEG and MEG studies in subjects with ASD have repeatedly shown alterations in ensemble population recordings (both in simple evoked related potential latencies and specific frequency subcomponents). Because these disease-associated electrophysiological abnormalities have been recapitulated in rodent models, studying circuit differences in these models may provide access to abnormal circuit function found in ASD. We then identify emerging in vivo and ex vivo techniques, focusing on how these assays can characterize circuit level dysfunction and determine if these abnormalities underlie abnormal clinical electrophysiology. Such circuit level study in animal models may help us understand how diverse genetic and environmental risks can produce a common set of EEG, MEG and anatomical abnormalities found in ASD. PMID:25538564

Abnormal hippocampal functioning and impaired spatial navigation in depressed individuals: evidence from whole-head magnetoencephalography.

PubMed

Cornwell, Brian R; Salvadore, Giacomo; Colon-Rosario, Veronica; Latov, David R; Holroyd, Tom; Carver, Frederick W; Coppola, Richard; Manji, Husseini K; Zarate, Carlos A; Grillon, Christian

2010-07-01

Dysfunction of the hippocampus has long been suspected to be a key component of the pathophysiology of major depressive disorder. Despite evidence of hippocampal structural abnormalities in depressed patients, abnormal hippocampal functioning has not been demonstrated. The authors aimed to link spatial navigation deficits previously documented in depressed patients to abnormal hippocampal functioning using a virtual reality navigation task. Whole-head magnetoencephalography (MEG) recordings were collected while participants (19 patients diagnosed with major depressive disorder and 19 healthy subjects matched by gender and age) navigated a virtual Morris water maze to find a hidden platform; navigation to a visible platform served as a control condition. Behavioral measures were obtained to assess navigation performance. Theta oscillatory activity (4-8 Hz) was mapped across the brain on a voxel-wise basis using a spatial-filtering MEG source analysis technique. Depressed patients performed worse than healthy subjects in navigating to the hidden platform. Robust group differences in theta activity were observed in right medial temporal cortices during navigation, with patients exhibiting less engagement of the anterior hippocampus and parahippocampal cortices relative to comparison subjects. Left posterior hippocampal theta activity was positively correlated with individual performance within each group. Consistent with previous findings, depressed patients showed impaired spatial navigation. Dysfunction of right anterior hippocampus and parahippocampal cortices may underlie this deficit and stem from structural abnormalities commonly found in depressed patients.

Synchronous neural interactions assessed by magnetoencephalography: a functional biomarker for brain disorders

NASA Astrophysics Data System (ADS)

Georgopoulos, Apostolos P.; Karageorgiou, Elissaios; Leuthold, Arthur C.; Lewis, Scott M.; Lynch, Joshua K.; Alonso, Aurelio A.; Aslam, Zaheer; Carpenter, Adam F.; Georgopoulos, Angeliki; Hemmy, Laura S.; Koutlas, Ioannis G.; Langheim, Frederick J. P.; Riley McCarten, J.; McPherson, Susan E.; Pardo, José V.; Pardo, Patricia J.; Parry, Gareth J.; Rottunda, Susan J.; Segal, Barbara M.; Sponheim, Scott R.; Stanwyck, John J.; Stephane, Massoud; Westermeyer, Joseph J.

2007-12-01

We report on a test to assess the dynamic brain function at high temporal resolution using magnetoencephalography (MEG). The essence of the test is the measurement of the dynamic synchronous neural interactions, an essential aspect of the brain function. MEG signals were recorded from 248 axial gradiometers while 142 human subjects fixated a spot of light for 45-60 s. After fitting an autoregressive integrative moving average (ARIMA) model and taking the stationary residuals, all pairwise, zero-lag, partial cross-correlations (PCCij0) and their z-transforms (zij0) between i and j sensors were calculated, providing estimates of the strength and sign (positive, negative) of direct synchronous coupling at 1 ms temporal resolution. We found that subsets of zij0 successfully classified individual subjects to their respective groups (multiple sclerosis, Alzheimer's disease, schizophrenia, Sjögren's syndrome, chronic alcoholism, facial pain, healthy controls) and gave excellent external cross-validation results. Contribution by the authors: Designed research (APG); acquired data (AAA, IGK, FJPL, ACL, SML, JJS); analyzed data (APG, EK, ACL, JKL); wrote the paper (APG, EK, ACL, SML); contributed subjects (AAA, ZA, AFC, AG, LSH, IGK, FJPL, SML, JRM, SEM, JVP, PJP, GJP, SJR, BMS, SRS, MS, JJS, JJW); discussed results (All); contributed equally (ZA, AFC, AG, LSH, FJPL, JRM, SEM, JVP, PJP, GJP, SJR, BMS, SRS, MS, JJS, JJW).

Brain noise is task dependent and region specific.

PubMed

Misić, Bratislav; Mills, Travis; Taylor, Margot J; McIntosh, Anthony R

2010-11-01

The emerging organization of anatomical and functional connections during human brain development is thought to facilitate global integration of information. Recent empirical and computational studies have shown that this enhanced capacity for information processing enables a diversified dynamic repertoire that manifests in neural activity as irregularity and noise. However, transient functional networks unfold over multiple time, scales and the embedding of a particular region depends not only on development, but also on the manner in which sensory and cognitive systems are engaged. Here we show that noise is a facet of neural activity that is also sensitive to the task context and is highly region specific. Children (6-16 yr) and adults (20-41 yr) performed a one-back face recognition task with inverted and upright faces. Neuromagnetic activity was estimated at several hundred sources in the brain by applying a beamforming technique to the magnetoencephalogram (MEG). During development, neural activity became more variable across the whole brain, with most robust increases in medial parietal regions, such as the precuneus and posterior cingulate cortex. For young children and adults, activity evoked by upright faces was more variable and noisy compared with inverted faces, and this effect was reliable only in the right fusiform gyrus. These results are consistent with the notion that upright faces engender a variety of integrative neural computations, such as the relations among facial features and their holistic constitution. This study shows that transient changes in functional integration modulated by task demand are evident in the variability of regional neural activity.

Auditory Habituation in the Fetus and Neonate: An fMEG Study

ERIC Educational Resources Information Center

Muenssinger, Jana; Matuz, Tamara; Schleger, Franziska; Kiefer-Schmidt, Isabelle; Goelz, Rangmar; Wacker-Gussmann, Annette; Birbaumer, Niels; Preissl, Hubert

2013-01-01

Habituation--the most basic form of learning--is used to evaluate central nervous system (CNS) maturation and to detect abnormalities in fetal brain development. In the current study, habituation, stimulus specificity and dishabituation of auditory evoked responses were measured in fetuses and newborns using fetal magnetoencephalography (fMEG). An…

Armed Deterrence: Countering Soft Target Attacks

DTIC Science & Technology

2016-02-06

Perspectives on Terrorism 9, no. 4 (August 2015): 14-30. 6 Ibid., 19. 7 Ibid., 16. 8 Ibid. 9 Ibid., 14. 10 Ibid., 27. 11 Meg Wagner and Rich...Wagner, Meg and Rich Schapiro. “Mastermind of Paris terror attack planned strikes on schools, mocked Europe’s open borders: report,” New York Daily

The Influence of Semantic Processing on Phonological Decisions in Children and Adults: A Magnetoencephalography (MEG) Study

ERIC Educational Resources Information Center

Wehner, Daniel T.; Ahlfors, Seppo P.; Mody, Maria

2007-01-01

Purpose: To examine the behavioral effects and neural activation patterns associated with implicit semantic processing influences on phonological judgments during reading in children and adults. Method: Whole-head magnetoencephalography (MEG) recordings were obtained from 2 groups, children (9-13 years) and adults, performing a homophone judgment…

An Extended Motor Network Generates Beta and Gamma Oscillatory Perturbations during Development

ERIC Educational Resources Information Center

Wilson, Tony W.; Slason, Erin; Asherin, Ryan; Kronberg, Eugene; Reite, Martin L.; Teale, Peter D.; Rojas, Donald C.

2010-01-01

This study examines the time course and neural generators of oscillatory beta and gamma motor responses in typically-developing children. Participants completed a unilateral flexion-extension task using each index finger as whole-head magnetoencephalography (MEG) data were acquired. These MEG data were imaged in the frequency-domain using spatial…

Truncated RAP-MUSIC (TRAP-MUSIC) for MEG and EEG source localization.

PubMed

Mäkelä, Niko; Stenroos, Matti; Sarvas, Jukka; Ilmoniemi, Risto J

2018-02-15

Electrically active brain regions can be located applying MUltiple SIgnal Classification (MUSIC) on magneto- or electroencephalographic (MEG; EEG) data. We introduce a new MUSIC method, called truncated recursively-applied-and-projected MUSIC (TRAP-MUSIC). It corrects a hidden deficiency of the conventional RAP-MUSIC algorithm, which prevents estimation of the true number of brain-signal sources accurately. The correction is done by applying a sequential dimension reduction to the signal-subspace projection. We show that TRAP-MUSIC significantly improves the performance of MUSIC-type localization; in particular, it successfully and robustly locates active brain regions and estimates their number. We compare TRAP-MUSIC and RAP-MUSIC in simulations with varying key parameters, e.g., signal-to-noise ratio, correlation between source time-courses, and initial estimate for the dimension of the signal space. In addition, we validate TRAP-MUSIC with measured MEG data. We suggest that with the proposed TRAP-MUSIC method, MUSIC-type localization could become more reliable and suitable for various online and offline MEG and EEG applications. Copyright © 2017 Elsevier Inc. All rights reserved.

Removal of monoethylene glycol from wastewater by using Zr-metal organic frameworks.

PubMed

Zaboon, Sami; Abid, Hussein Rasool; Yao, Zhengxin; Gubner, Rolf; Wang, Shaobin; Barifcani, Ahmed

2018-08-01

Mono-ethylene glycol (MEG), used in the oil and gas industries as a gas hydrate inhibitor, is a hazardous chemical present in wastewater from those processes. Metal-organic frameworks (MOFs) (modified UiO-66 ∗ and UiO-66-2OH) were used for the effective removal of MEG waste from effluents of distillation columns (MEG recovery units). Batch contact adsorption method was used to study the adsorption behavior toward these types of MOFs. Adsorption experiments showed that these MOFs had very high affinity toward MEG. Significant adsorption capacity was demonstrated on UiO-66-2OH and modified UiO-66 at 1000 mg·g -1 and 800 mg·g -1 respectively. The adsorption kinetics were fitted to a pseudo first-order model. UiO-66-2OH showed a higher adsorption capacity due to the presence of hydroxyl groups in its structure. A Langmuir model gave the best fitting for isotherm of experimental data at pH = 7. Copyright © 2018 Elsevier Inc. All rights reserved.

Real Time Data Acquisition and Online Signal Processing for Magnetoencephalography

NASA Astrophysics Data System (ADS)

Rongen, H.; Hadamschek, V.; Schiek, M.

2006-06-01

To establish improved therapies for patients suffering from severe neurological and psychiatric diseases, a demand controlled and desynchronizing brain-pacemaker has been developed with techniques from statistical physics and nonlinear dynamics. To optimize the novel therapeutic approach, brain activity is investigated with a Magnetoencephalography (MEG) system prior to surgery. For this, a real time data acquisition system for a 148 channel MEG and online signal processing for artifact rejection, filtering, cross trial phase resetting analysis and three-dimensional (3-D) reconstruction of the cerebral current sources was developed. The developed PCI bus hardware is based on a FPGA and DSP design, using the benefits from both architectures. The reconstruction and visualization of the 3-D volume data is done by the PC which hosts the real time DAQ and pre-processing board. The framework of the MEG-online system is introduced and the architecture of the real time DAQ board and online reconstruction is described. In addition we show first results with the MEG-Online system for the investigation of dynamic brain activities in relation to external visual stimulation, based on test data sets.

Dual drug encapsulated thermo-sensitive fibrinogen-graft-poly (N-isopropyl acrylamide) nanogels for breast cancer therapy.

PubMed

Rejinold, N Sanoj; Baby, Thejus; Chennazhi, K P; Jayakumar, R

2014-02-01

5-FU/Megestrol acetate loaded fibrinogen-graft-PNIPAAm Nanogels (5-FU/Meg-fib-graft-PNIPAAm NGs) were prepared for thermo responsive drug delivery toward α5β1-integrins expressing breast cancer cells in vitro (MCF-7 cells). The 60-100 nm sized fib-graft-PNIPAAm nanogels (LCST=35 °C) were prepared by CaCl2 cross-linker. 5-FU/Meg-fib-graft-PNIPAAm NGs showed particle size of 165-195 nm size. The drug loading efficiency with 5-FU was 60% and 70% for Meg. "Drug release was greater above the lower critical solution temperature (LCST). Above LCST, drug release system triggers apopotosis and enhance toxicity to MCF-7 cells when compared to the equivalent dose of the free drug. This effect was due to the greater uptake of the drug by MCF-7 cells". 5-FU/Meg-fib-graft-PNIPAAm NGs is portrayed here as a new combinatorial thermo-responsive drug delivery agent for breast cancer therapy. Copyright © 2013 Elsevier B.V. All rights reserved.

Control of Multiple Exciton Generation and Electron-Phonon Coupling by Interior Nanospace in Hyperstructured Quantum Dot Superlattice.

PubMed

Chang, I-Ya; Kim, DaeGwi; Hyeon-Deuk, Kim

2017-09-20

The possibility of precisely manipulating interior nanospace, which can be adjusted by ligand-attaching down to the subnanometer regime, in a hyperstructured quantum dot (QD) superlattice (QDSL) induces a new kind of collective resonant coupling among QDs and opens up new opportunities for developing advanced optoelectric and photovoltaic devices. Here, we report the first real-time dynamics simulations of the multiple exciton generation (MEG) in one-, two-, and three-dimensional (1D, 2D, and 3D) hyperstructured H-passivated Si QDSLs, accounting for thermally fluctuating band energies and phonon dynamics obtained by finite-temperature ab initio molecular dynamics simulations. We computationally demonstrated that the MEG was significantly accelerated, especially in the 3D QDSL compared to the 1D and 2D QDSLs. The MEG acceleration in the 3D QDSL was almost 1.9 times the isolated QD case. The dimension-dependent MEG acceleration was attributed not only to the static density of states but also to the dynamical electron-phonon couplings depending on the dimensionality of the hyperstructured QDSL, which is effectively controlled by the interior nanospace. Such dimension-dependent modifications originated from the short-range quantum resonance among component QDs and were intrinsic to the hyperstructured QDSL. We propose that photoexcited dynamics including the MEG process can be effectively controlled by only manipulating the interior nanospace of the hyperstructured QDSL without changing component QD size, shape, compositions, ligand, etc.

Neurophysiological Studies of Auditory Verbal Hallucinations

PubMed Central

Ford, Judith M.; Dierks, Thomas; Fisher, Derek J.; Herrmann, Christoph S.; Hubl, Daniela; Kindler, Jochen; Koenig, Thomas; Mathalon, Daniel H.; Spencer, Kevin M.; Strik, Werner; van Lutterveld, Remko

2012-01-01

We discuss 3 neurophysiological approaches to study auditory verbal hallucinations (AVH). First, we describe “state” (or symptom capture) studies where periods with and without hallucinations are compared “within” a patient. These studies take 2 forms: passive studies, where brain activity during these states is compared, and probe studies, where brain responses to sounds during these states are compared. EEG (electroencephalography) and MEG (magnetoencephalography) data point to frontal and temporal lobe activity, the latter resulting in competition with external sounds for auditory resources. Second, we discuss “trait” studies where EEG and MEG responses to sounds are recorded from patients who hallucinate and those who do not. They suggest a tendency to hallucinate is associated with competition for auditory processing resources. Third, we discuss studies addressing possible mechanisms of AVH, including spontaneous neural activity, abnormal self-monitoring, and dysfunctional interregional communication. While most studies show differences in EEG and MEG responses between patients and controls, far fewer show symptom relationships. We conclude that efforts to understand the pathophysiology of AVH using EEG and MEG have been hindered by poor anatomical resolution of the EEG and MEG measures, poor assessment of symptoms, poor understanding of the phenomenon, poor models of the phenomenon, decoupling of the symptoms from the neurophysiology due to medications and comorbidites, and the possibility that the schizophrenia diagnosis breeds truer than the symptoms it comprises. These problems are common to studies of other psychiatric symptoms and should be considered when attempting to understand the basic neural mechanisms responsible for them. PMID:22368236

Multireaction equilibrium geothermometry: A sensitivity analysis using data from the Lower Geyser Basin, Yellowstone National Park, USA

USGS Publications Warehouse

King, Jonathan M.; Hurwitz, Shaul; Lowenstern, Jacob B.; Nordstrom, D. Kirk; McCleskey, R. Blaine

2016-01-01

A multireaction chemical equilibria geothermometry (MEG) model applicable to high-temperature geothermal systems has been developed over the past three decades. Given sufficient data, this model provides more constraint on calculated reservoir temperatures than classical chemical geothermometers that are based on either the concentration of silica (SiO2), or the ratios of cation concentrations. A set of 23 chemical analyses from Ojo Caliente Spring and 22 analyses from other thermal features in the Lower Geyser Basin of Yellowstone National Park are used to examine the sensitivity of calculated reservoir temperatures using the GeoT MEG code (Spycher et al. 2013, 2014) to quantify the effects of solute concentrations, degassing, and mineral assemblages on calculated reservoir temperatures. Results of our analysis demonstrate that the MEG model can resolve reservoir temperatures within approximately ±15°C, and that natural variation in fluid compositions represents a greater source of variance in calculated reservoir temperatures than variations caused by analytical uncertainty (assuming ~5% for major elements). The analysis also suggests that MEG calculations are particularly sensitive to variations in silica concentration, the concentrations of the redox species Fe(II) and H2S, and that the parameters defining steam separation and CO2 degassing from the liquid may be adequately determined by numerical optimization. Results from this study can provide guidance for future applications of MEG models, and thus provide more reliable information on geothermal energy resources during exploration.

Self-awareness and the subconscious effect of personal pronouns on word encoding: a magnetoencephalography (MEG) study.

PubMed

Walla, Peter; Greiner, Katharina; Duregger, Cornelia; Deecke, Lüder; Thurner, Stefan

2007-03-02

The effect of personal pronouns such as "ein" (German for "a"), "mein" (German for "my") and "sein" (German for "his") on the processing of associated nouns was investigated using MEG. Three different encoding strategies were provided in order to vary the level of consciousness involved in verbal information processing. A shallow (alphabetic), a deep (semantic) and a very deep (contextual) encoding instruction related to visual word presentation were given to all study participants. After the encoding of pronoun-noun pairs, recognition performances of nouns only were tested. The number of correctly recognized nouns previously associated with "sein" was significantly lower than the number of correctly recognized nouns previously associated with "ein" in the shallow encoding condition. The same trend was found for "mein" associated nouns which were also less accurately recognized compared to "ein" associated nouns. Magnetic field distributions recorded during the encoding phases revealed two significant effects, one between about 200 and 400ms after stimulus onset and the other between about 500 and 800ms. The earlier effect was found over occipito-parietal sensors, whereas the later effect occurred over left frontal sensors. Within both time ranges, brain activation varied significantly as a function of associated pronoun independent of depth of word processing. In the respective areas of both time ranges, conditions including personal pronouns ("mein" and "sein") showed higher magnetic field components compared to the control condition of no personal pronouns ("ein"). Evidence is shown that early stage processing is able to distinguish between no personal and personal information, whereas later stage processing is able to distinguish between information related to oneself and to another person (self and non-self). Along with other previous reports our MEG findings support the notion that particular human brain functions involved in processing neurophysiological correlates of self and non-self can be identified.

Thalamocortical interactions underlying visual fear conditioning in humans.

PubMed

Lithari, Chrysa; Moratti, Stephan; Weisz, Nathan

2015-11-01

Despite a strong focus on the role of the amygdala in fear conditioning, recent works point to a more distributed network supporting fear conditioning. We aimed to elucidate interactions between subcortical and cortical regions in fear conditioning in humans. To do this, we used two fearful faces as conditioned stimuli (CS) and an electrical stimulation at the left hand, paired with one of the CS, as unconditioned stimulus (US). The luminance of the CS was rhythmically modulated leading to "entrainment" of brain oscillations at a predefined modulation frequency. Steady-state responses (SSR) were recorded by MEG. In addition to occipital regions, spectral analysis of SSR revealed increased power during fear conditioning particularly for thalamus and cerebellum contralateral to the upcoming US. Using thalamus and amygdala as seed-regions, directed functional connectivity was calculated to capture the modulation of interactions that underlie fear conditioning. Importantly, this analysis showed that the thalamus drives the fusiform area during fear conditioning, while amygdala captures the more general effect of fearful faces perception. This study confirms ideas from the animal literature, and demonstrates for the first time the central role of the thalamus in fear conditioning in humans. © 2015 Wiley Periodicals, Inc.

Localizing on-scalp MEG sensors using an array of magnetic dipole coils.

PubMed

Pfeiffer, Christoph; Andersen, Lau M; Lundqvist, Daniel; Hämäläinen, Matti; Schneiderman, Justin F; Oostenveld, Robert

2018-01-01

Accurate estimation of the neural activity underlying magnetoencephalography (MEG) signals requires co-registration i.e., determination of the position and orientation of the sensors with respect to the head. In modern MEG systems, an array of hundreds of low-Tc SQUID sensors is used to localize a set of small, magnetic dipole-like (head-position indicator, HPI) coils that are attached to the subject's head. With accurate prior knowledge of the positions and orientations of the sensors with respect to one another, the HPI coils can be localized with high precision, and thereby the positions of the sensors in relation to the head. With advances in magnetic field sensing technologies, e.g., high-Tc SQUIDs and optically pumped magnetometers (OPM), that require less extreme operating temperatures than low-Tc SQUID sensors, on-scalp MEG is on the horizon. To utilize the full potential of on-scalp MEG, flexible sensor arrays are preferable. Conventional co-registration is impractical for such systems as the relative positions and orientations of the sensors to each other are subject-specific and hence not known a priori. Herein, we present a method for co-registration of on-scalp MEG sensors. We propose to invert the conventional co-registration approach and localize the sensors relative to an array of HPI coils on the subject's head. We show that given accurate prior knowledge of the positions of the HPI coils with respect to one another, the sensors can be localized with high precision. We simulated our method with realistic parameters and layouts for sensor and coil arrays. Results indicate co-registration is possible with sub-millimeter accuracy, but the performance strongly depends upon a number of factors. Accurate calibration of the coils and precise determination of the positions and orientations of the coils with respect to one another are crucial. Finally, we propose methods to tackle practical challenges to further improve the method.

MEG predicts outcome following surgery for intractable epilepsy in children with normal or nonfocal MRI findings.

PubMed

RamachandranNair, Rajesh; Otsubo, Hiroshi; Shroff, Manohar M; Ochi, Ayako; Weiss, Shelly K; Rutka, James T; Snead, O Carter

2007-01-01

To identify the predictors of postsurgical seizure freedom in children with refractory epilepsy and normal or nonfocal MRI findings. We analyzed 22 children with normal or subtle and nonfocal MRI findings, who underwent surgery for intractable epilepsy following extraoperative intracranial EEG. We compared clinical profiles, neurophysiological data (scalp EEG, magnetoencephalography (MEG) and intracranial EEG), completeness of surgical resection and pathology to postoperative seizure outcomes. Seventeen children (77%) had a good postsurgical outcome (defined as Engel class IIIA or better), which included eight (36%) seizure-free children. All children with postsurgical seizure freedom had an MEG cluster in the final resection area. Postsurgical seizure freedom was obtained in none of the children who had bilateral MEG dipole clusters (3) or only scattered dipoles (1). All five children in whom ictal onset zones were confined to < or = 5 adjacent intracranial electrodes achieved seizure freedom compared to three of 17 children with ictal onset zones that extended over >5 electrodes (p = 0.002). None of six children with more than one type of seizure became seizure-free, compared to eight of 16 children with a single seizure type (p = 0.04). Complete resection of the preoperatively localized epileptogenic zone resulted in seizure remission in 63% (5/8) and incomplete resections, in 21% (3/14) (p = 0.06). Age of onset, duration of epilepsy, number of lobes involved in resection, and pathology failed to correlate with seizure freedom. Surgery for intractable epilepsy in children with normal MRI findings provided good postsurgical outcomes in the majority of our patients. As well, restricted ictal onset zone predicted postoperative seizure freedom. Postoperative seizure freedom was less likely to occur in children with bilateral MEG dipole clusters or only scattered dipoles, multiple seizure types and incomplete resection of the proposed epileptogenic zone. Seizure freedom was most likely to occur when there was concordance between EEG and MEG localization and least likely to occur when these results were divergent.

Automated detection of epileptic ripples in MEG using beamformer-based virtual sensors

NASA Astrophysics Data System (ADS)

Migliorelli, Carolina; Alonso, Joan F.; Romero, Sergio; Nowak, Rafał; Russi, Antonio; Mañanas, Miguel A.

2017-08-01

Objective. In epilepsy, high-frequency oscillations (HFOs) are expressively linked to the seizure onset zone (SOZ). The detection of HFOs in the noninvasive signals from scalp electroencephalography (EEG) and magnetoencephalography (MEG) is still a challenging task. The aim of this study was to automate the detection of ripples in MEG signals by reducing the high-frequency noise using beamformer-based virtual sensors (VSs) and applying an automatic procedure for exploring the time-frequency content of the detected events. Approach. Two-hundred seconds of MEG signal and simultaneous iEEG were selected from nine patients with refractory epilepsy. A two-stage algorithm was implemented. Firstly, beamforming was applied to the whole head to delimitate the region of interest (ROI) within a coarse grid of MEG-VS. Secondly, a beamformer using a finer grid in the ROI was computed. The automatic detection of ripples was performed using the time-frequency response provided by the Stockwell transform. Performance was evaluated through comparisons with simultaneous iEEG signals. Main results. ROIs were located within the seizure-generating lobes in the nine subjects. Precision and sensitivity values were 79.18% and 68.88%, respectively, by considering iEEG-detected events as benchmarks. A higher number of ripples were detected inside the ROI compared to the same region in the contralateral lobe. Significance. The evaluation of interictal ripples using non-invasive techniques can help in the delimitation of the epileptogenic zone and guide placement of intracranial electrodes. This is the first study that automatically detects ripples in MEG in the time domain located within the clinically expected epileptic area taking into account the time-frequency characteristics of the events through the whole signal spectrum. The algorithm was tested against intracranial recordings, the current gold standard. Further studies should explore this approach to enable the localization of noninvasively recorded HFOs to help during pre-surgical planning and to reduce the need for invasive diagnostics.

Localizing on-scalp MEG sensors using an array of magnetic dipole coils

PubMed Central

Andersen, Lau M.; Lundqvist, Daniel; Hämäläinen, Matti; Schneiderman, Justin F.; Oostenveld, Robert

2018-01-01

Accurate estimation of the neural activity underlying magnetoencephalography (MEG) signals requires co-registration i.e., determination of the position and orientation of the sensors with respect to the head. In modern MEG systems, an array of hundreds of low-Tc SQUID sensors is used to localize a set of small, magnetic dipole-like (head-position indicator, HPI) coils that are attached to the subject’s head. With accurate prior knowledge of the positions and orientations of the sensors with respect to one another, the HPI coils can be localized with high precision, and thereby the positions of the sensors in relation to the head. With advances in magnetic field sensing technologies, e.g., high-Tc SQUIDs and optically pumped magnetometers (OPM), that require less extreme operating temperatures than low-Tc SQUID sensors, on-scalp MEG is on the horizon. To utilize the full potential of on-scalp MEG, flexible sensor arrays are preferable. Conventional co-registration is impractical for such systems as the relative positions and orientations of the sensors to each other are subject-specific and hence not known a priori. Herein, we present a method for co-registration of on-scalp MEG sensors. We propose to invert the conventional co-registration approach and localize the sensors relative to an array of HPI coils on the subject’s head. We show that given accurate prior knowledge of the positions of the HPI coils with respect to one another, the sensors can be localized with high precision. We simulated our method with realistic parameters and layouts for sensor and coil arrays. Results indicate co-registration is possible with sub-millimeter accuracy, but the performance strongly depends upon a number of factors. Accurate calibration of the coils and precise determination of the positions and orientations of the coils with respect to one another are crucial. Finally, we propose methods to tackle practical challenges to further improve the method. PMID:29746486

The population genomic landscape of human genetic structure, admixture history and local adaptation in Peninsular Malaysia.

PubMed

Deng, Lian; Hoh, Boon Peng; Lu, Dongsheng; Fu, Ruiqing; Phipps, Maude E; Li, Shilin; Nur-Shafawati, Ab Rajab; Hatin, Wan Isa; Ismail, Endom; Mokhtar, Siti Shuhada; Jin, Li; Zilfalil, Bin Alwi; Marshall, Christian R; Scherer, Stephen W; Al-Mulla, Fahd; Xu, Shuhua

2014-09-01

Peninsular Malaysia is a strategic region which might have played an important role in the initial peopling and subsequent human migrations in Asia. However, the genetic diversity and history of human populations--especially indigenous populations--inhabiting this area remain poorly understood. Here, we conducted a genome-wide study using over 900,000 single nucleotide polymorphisms (SNPs) in four major Malaysian ethnic groups (MEGs; Malay, Proto-Malay, Senoi and Negrito), and made comparisons of 17 world-wide populations. Our data revealed that Peninsular Malaysia has greater genetic diversity corresponding to its role as a contact zone of both early and recent human migrations in Asia. However, each single Orang Asli (indigenous) group was less diverse with a smaller effective population size (N(e)) than a European or an East Asian population, indicating a substantial isolation of some duration for these groups. All four MEGs were genetically more similar to Asian populations than to other continental groups, and the divergence time between MEGs and East Asian populations (12,000--6,000 years ago) was also much shorter than that between East Asians and Europeans. Thus, Malaysian Orang Asli groups, despite their significantly different features, may share a common origin with the other Asian groups. Nevertheless, we identified traces of recent gene flow from non-Asians to MEGs. Finally, natural selection signatures were detected in a batch of genes associated with immune response, human height, skin pigmentation, hair and facial morphology and blood pressure in MEGs. Notable examples include SYN3 which is associated with human height in all Orang Asli groups, a height-related gene (PNPT1) and two blood pressure-related genes (CDH13 and PAX5) in Negritos. We conclude that a long isolation period, subsequent gene flow and local adaptations have jointly shaped the genetic architectures of MEGs, and this study provides insight into the peopling and human migration history in Southeast Asia.

Electromagnetic signatures of the preclinical and prodromal stages of Alzheimer’s disease

PubMed Central

Cuesta, Pablo; Fernández, Alberto; Arahata, Yutaka; Iwata, Kaori; Kuratsubo, Izumi; Bundo, Masahiko; Hattori, Hideyuki; Sakurai, Takashi; Fukuda, Koji; Washimi, Yukihiko; Endo, Hidetoshi; Takeda, Akinori; Diers, Kersten; Bajo, Ricardo; Maestú, Fernando; Ito, Kengo; Kato, Takashi

2018-01-01

Abstract Biomarkers useful for the predementia stages of Alzheimer’s disease are needed. Electroencephalography and magnetoencephalography (MEG) are expected to provide potential biomarker candidates for evaluating the predementia stages of Alzheimer’s disease. However, the physiological relevance of EEG/MEG signal changes and their role in pathophysiological processes such as amyloid-β deposition and neurodegeneration need to be elucidated. We evaluated 28 individuals with mild cognitive impairment and 38 cognitively normal individuals, all of whom were further classified into amyloid-β-positive mild cognitive impairment (n = 17, mean age 74.7 ± 5.4 years, nine males), amyloid-β-negative mild cognitive impairment (n = 11, mean age 73.8 ± 8.8 years, eight males), amyloid-β-positive cognitively normal (n = 13, mean age 71.8 ± 4.4 years, seven males), and amyloid-β-negative cognitively normal (n = 25, mean age 72.5 ± 3.4 years, 11 males) individuals using Pittsburgh compound B-PET. We measured resting state MEG for 5 min with the eyes closed, and investigated regional spectral patterns of MEG signals using atlas-based region of interest analysis. Then, the relevance of the regional spectral patterns and their associations with pathophysiological backgrounds were analysed by integrating information from Pittsburgh compound B-PET, fluorodeoxyglucose-PET, structural MRI, and cognitive tests. The results demonstrated that regional spectral patterns of resting state activity could be separated into several types of MEG signatures as follows: (i) the effects of amyloid-β deposition were expressed as the alpha band power augmentation in medial frontal areas; (ii) the delta band power increase in the same region was associated with disease progression within the Alzheimer’s disease continuum and was correlated with entorhinal atrophy and an Alzheimer’s disease-like regional decrease in glucose metabolism; and (iii) the global theta power augmentation, which was previously considered to be an Alzheimer’s disease-related EEG/MEG signature, was associated with general cognitive decline and hippocampal atrophy, but was not specific to Alzheimer’s disease because these changes could be observed in the absence of amyloid-β deposition. The results suggest that these MEG signatures may be useful as unique biomarkers for the predementia stages of Alzheimer’s disease. PMID:29522156

Abnormal early dynamic individual patterns of functional networks in low gamma band for depression recognition.

PubMed

Bi, Kun; Chattun, Mahammad Ridwan; Liu, Xiaoxue; Wang, Qiang; Tian, Shui; Zhang, Siqi; Lu, Qing; Yao, Zhijian

2018-06-13

The functional networks are associated with emotional processing in depression. The mapping of dynamic spatio-temporal brain networks is used to explore individual performance during early negative emotional processing. However, the dysfunctions of functional networks in low gamma band and their discriminative potentialities during early period of emotional face processing remain to be explored. Functional brain networks were constructed from the MEG recordings of 54 depressed patients and 54 controls in low gamma band (30-48 Hz). Dynamic connectivity regression (DCR) algorithm analyzed the individual change points of time series in response to emotional stimuli and constructed individualized spatio-temporal patterns. The nodal characteristics of patterns were calculated and fed into support vector machine (SVM). Performance of the classification algorithm in low gamma band was validated by dynamic topological characteristics of individual patterns in comparison to alpha and beta band. The best discrimination accuracy of individual spatio-temporal patterns was 91.01% in low gamma band. Individual temporal patterns had better results compared to group-averaged temporal patterns in all bands. The most important discriminative networks included affective network (AN) and fronto-parietal network (FPN) in low gamma band. The sample size is relatively small. High gamma band was not considered. The abnormal dynamic functional networks in low gamma band during early emotion processing enabled depression recognition. The individual information processing is crucial in the discovery of abnormal spatio-temporal patterns in depression during early negative emotional processing. Individual spatio-temporal patterns may reflect the real dynamic function of subjects while group-averaged data may neglect some individual information. Copyright © 2018. Published by Elsevier B.V.

Neural Connectivity in Epilepsy as Measured by Granger Causality.

PubMed

Coben, Robert; Mohammad-Rezazadeh, Iman

2015-01-01

Epilepsy is a chronic neurological disorder characterized by repeated seizures or excessive electrical discharges in a group of brain cells. Prevalence rates include about 50 million people worldwide and 10% of all people have at least one seizure at one time in their lives. Connectivity models of epilepsy serve to provide a deeper understanding of the processes that control and regulate seizure activity. These models have received initial support and have included measures of EEG, MEG, and MRI connectivity. Preliminary findings have shown regions of increased connectivity in the immediate regions surrounding the seizure foci and associated low connectivity in nearby regions and pathways. There is also early evidence to suggest that these patterns change during ictal events and that these changes may even by related to the occurrence or triggering of seizure events. We present data showing how Granger causality can be used with EEG data to measure connectivity across brain regions involved in ictal events and their resolution. We have provided two case examples as a demonstration of how to obtain and interpret such data. EEG data of ictal events are processed, converted to independent components and their dipole localizations, and these are used to measure causality and connectivity between these locations. Both examples have shown hypercoupling near the seizure foci and low causality across nearby and associated neuronal pathways. This technique also allows us to track how these measures change over time and during the ictal and post-ictal periods. Areas for further research into this technique, its application to epilepsy, and the formation of more effective therapeutic interventions are recommended.

Selective impairment of hippocampus and posterior hub areas in Alzheimer's disease: an MEG-based multiplex network study.

PubMed

Yu, Meichen; Engels, Marjolein M A; Hillebrand, Arjan; van Straaten, Elisabeth C W; Gouw, Alida A; Teunissen, Charlotte; van der Flier, Wiesje M; Scheltens, Philip; Stam, Cornelis J

2017-05-01

Although frequency-specific network analyses have shown that functional brain networks are altered in patients with Alzheimer's disease, the relationships between these frequency-specific network alterations remain largely unknown. Multiplex network analysis is a novel network approach to study complex systems consisting of subsystems with different types of connectivity patterns. In this study, we used magnetoencephalography to integrate five frequency-band specific brain networks in a multiplex framework. Previous structural and functional brain network studies have consistently shown that hub brain areas are selectively disrupted in Alzheimer's disease. Accordingly, we hypothesized that hub regions in the multiplex brain networks are selectively targeted in patients with Alzheimer's disease in comparison to healthy control subjects. Eyes-closed resting-state magnetoencephalography recordings from 27 patients with Alzheimer's disease (60.6 ± 5.4 years, 12 females) and 26 controls (61.8 ± 5.5 years, 14 females) were projected onto atlas-based regions of interest using beamforming. Subsequently, source-space time series for both 78 cortical and 12 subcortical regions were reconstructed in five frequency bands (delta, theta, alpha 1, alpha 2 and beta band). Multiplex brain networks were constructed by integrating frequency-specific magnetoencephalography networks. Functional connections between all pairs of regions of interests were quantified using a phase-based coupling metric, the phase lag index. Several multiplex hub and heterogeneity metrics were computed to capture both overall importance of each brain area and heterogeneity of the connectivity patterns across frequency-specific layers. Different nodal centrality metrics showed consistently that several hub regions, particularly left hippocampus, posterior parts of the default mode network and occipital regions, were vulnerable in patients with Alzheimer's disease compared to control subjects. Of note, these detected vulnerable hubs in Alzheimer's disease were absent in each individual frequency-specific network, thus showing the value of integrating the networks. The connectivity patterns of these vulnerable hub regions in the patients were heterogeneously distributed across layers. Perturbed cognitive function and abnormal cerebrospinal fluid amyloid-β42 levels correlated positively with the vulnerability of the hub regions in patients with Alzheimer's disease. Our analysis therefore demonstrates that the magnetoencephalography-based multiplex brain networks contain important information that cannot be revealed by frequency-specific brain networks. Furthermore, this indicates that functional networks obtained in different frequency bands do not act as independent entities. Overall, our multiplex network study provides an effective framework to integrate the frequency-specific networks with different frequency patterns and reveal neuropathological mechanism of hub disruption in Alzheimer's disease. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Disambiguating Form and Lexical Frequency Effects in MEG Responses Using Homonyms

ERIC Educational Resources Information Center

Simon, Dylan Alexander; Lewis, Gwyneth; Marantz, Alec

2012-01-01

We present an MEG study of homonym recognition in reading, identifying effects of a semantic measure of homonym ambiguity. This measure sheds light on two competing theories of lexical access: the "early access" theory, which entails that lexical access occurs at early (pre 200 ms) stages of processing; and the "late access" theory, which…

The Precise Time Course of Lexical Activation: MEG Measurements of the Effects of Frequency, Probability, and Density in Lexical Decision

ERIC Educational Resources Information Center

Stockall, Linnaea; Stringfellow, Andrew; Marantz, Alec

2004-01-01

Visually presented letter strings consistently yield three MEG response components: the M170, associated with letter-string processing (Tarkiainen, Helenius, Hansen, Cornelissen, & Salmelin, 1999); the M250, affected by phonotactic probability, (Pylkkanen, Stringfellow, & Marantz, 2002); and the M350, responsive to lexical frequency (Embick,…

Exceeding Conventional Photovoltaic Efficiency Limits Using Colloidal Quantum Dots

NASA Astrophysics Data System (ADS)

Pach, Gregory F.

Colloidal quantum dots (QDs) are a widely investigated field of research due to their highly tunable nature in which the optical and electronic properties of the nanocrystal can be manipulated by merely changing the nanocrystal's size. Specifically, colloidal quantum dot solar cells (QDSCs) have become a promising candidate for future generation photovoltaic technology. Quantum dots exhibit multiple exciton generation (MEG) in which multiple electron-hole pairs are generated from a single high-energy photon. This process is not observed in bulk-like semiconductors and allows for QDSCs to achieve theoretical efficiency limits above the standard single-junction Shockley-Queisser limit. However, the fast expanding field of QDSC research has lacked standardization of synthetic techniques and device design. Therefore, we sought to detail methodology for synthesizing PbS and PbSe QDs as well as photovoltaic device fabrication techniques as a fast track toward constructing high-performance solar cells. We show that these protocols lead toward consistently achieving efficiencies above 8% for PbS QDSCs. Using the same methodology for building single-junction photovoltaic devices, we incorporated PbS QDs as a bottom cell into a monolithic tandem architecture along with solution-processed CdTe nanocrystals. Modeling shows that near-peak tandem device efficiencies can be achieved across a wide range of bottom cell band gaps, and therefore the highly tunable band gap of lead-chalcogenide QDs lends well towards a bottom cell in a tandem architecture. A fully functioning monolithic tandem device is realized through the development of a ZnTe/ZnO recombination layer that appropriately combines the two subcells in series. Multiple recent reports have shown nanocrystalline heterostructures to undergo the MEG process more efficiency than several other nanostrucutres, namely lead-chalcogenide QDs. The final section of my thesis expands upon a recent publication by Zhang et. al., which details the synthesis of PbS/CdS heterostructures in which the PbS and CdS domains exist on opposite sides of the nanocrystal and are termed "Janus particles". Transient absorption spectroscopy shows MEG quantum yields above unity very the thermodynamic limit of 2Eg for PbS/CdS Janus particles. We further explain a mechanism for enhanced MEG using photoluminescence studies.

Search for the lepton flavour violating decay $$\\mu ^+ \\rightarrow \\mathrm {e}^+ \\gamma $$ with the full dataset of the MEG experiment: MEG Collaboration

DOE PAGES

Baldini, A. M.; Bao, Y.; Baracchini, E.; ...

2016-08-03

Our final results of the search for the lepton flavour violating decay μ+→e+γ based on the full dataset collected by the MEG experiment at the Paul Scherrer Institut in the period 2009–2013 and totalling 7.5×1014 stopped muons on target are presented. Furthermore, there was not a significant excess of events observed in the dataset with respect to the expected background and a new upper limit on the branching ratio of this decay of B(μ+→e+γ)<4.2×10-13 (90 % confidence level) is established, which represents the most stringent limit on the existence of this decay to date.

Automatic Semantic Facilitation in Anterior Temporal Cortex Revealed through Multimodal Neuroimaging

PubMed Central

Gramfort, Alexandre; Hämäläinen, Matti S.; Kuperberg, Gina R.

2013-01-01

A core property of human semantic processing is the rapid, facilitatory influence of prior input on extracting the meaning of what comes next, even under conditions of minimal awareness. Previous work has shown a number of neurophysiological indices of this facilitation, but the mapping between time course and localization—critical for separating automatic semantic facilitation from other mechanisms—has thus far been unclear. In the current study, we used a multimodal imaging approach to isolate early, bottom-up effects of context on semantic memory, acquiring a combination of electroencephalography (EEG), magnetoencephalography (MEG), and functional magnetic resonance imaging (fMRI) measurements in the same individuals with a masked semantic priming paradigm. Across techniques, the results provide a strikingly convergent picture of early automatic semantic facilitation. Event-related potentials demonstrated early sensitivity to semantic association between 300 and 500 ms; MEG localized the differential neural response within this time window to the left anterior temporal cortex, and fMRI localized the effect more precisely to the left anterior superior temporal gyrus, a region previously implicated in semantic associative processing. However, fMRI diverged from early EEG/MEG measures in revealing semantic enhancement effects within frontal and parietal regions, perhaps reflecting downstream attempts to consciously access the semantic features of the masked prime. Together, these results provide strong evidence that automatic associative semantic facilitation is realized as reduced activity within the left anterior superior temporal cortex between 300 and 500 ms after a word is presented, and emphasize the importance of multimodal neuroimaging approaches in distinguishing the contributions of multiple regions to semantic processing. PMID:24155321

In situ Observation of Direct Electron Transfer Reaction of Cytochrome c Immobilized on ITO Electrode Modified with 11-{2-[2-(2-Methoxyethoxy)ethoxy]ethoxy}undecylphosphonic Acid Self-assembled Monolayer Film by Electrochemical Slab Optical Waveguide Spectroscopy.

PubMed

Matsuda, Naoki; Okabe, Hirotaka; Omura, Ayako; Nakano, Miki; Miyake, Koji

2017-01-01

To immobilize cytochrome c (cyt.c) on an ITO electrode while keeping its direct electron transfer (DET) functionality, the ITO electrode surface was modified with 11-{2-[2-(2-methoxyethoxy)ethoxy]ethoxy}undecylphosphonic acid (CH 3 O (CH 2 CH 2 O) 3 C 11 H 22 PO(OH) 2 , M-EG 3 -UPA) self-assembled monolayer (SAM) film. After a 100-times washing process to exchange a phosphate buffer saline solution surrounding cyt.c and ITO electrode to a fresh one, an in situ observation of visible absorption spectral change with slab optical waveguide (SOWG) spectroscopy showed that 87.7% of the cyt.c adsorbed on the M-EG 3 -UPA modified ITO electrode remained on the ITO electrode. The SOWG absorption spectra corresponding to oxidized and reduced cyt.c were observed with setting the ITO electrode potential at 0.3 and -0.3 V vs. Ag/AgCl, respectively, while probing the DET reaction between cyt.c and ITO electrode occurred. The amount of cyt.c was evaluated to be about 19.4% of a monolayer coverage based on the coulomb amount in oxidation and reduction peaks on cyclic voltammetry (CV) data. The CV peak current maintained to be 83.4% compared with the initial value for a M-EG 3 -UPA modified ITO electrode after 60 min continuous scan with 0.1 V/s between 0.3 and -0.3 V vs. Ag/AgCl.

Discriminative analysis with a limited number of MEG trials in depression.

PubMed

Lu, Qing; Jiang, Haiteng; Bi, Kun; Liu, Chu; Yao, Zhijian

2014-01-01

In studies when exploring distinct patterns of functional abnormalities inherent in depression, experiments are generally repeated over many trials, and then the data are averaged across those trials in order to improve the signal to noise ratio. Repeated stimuli will lead to unpredictable impairment on signals, due to material familiarity or subjects׳ fatigue. In this consideration, signal processing tools powerful on small numbers of trials are expected to alleviate the work load on subjects, especially for mental disease studies. Forty-four subjects, half-depressed patients and half-healthy subjects, were recruited for MEG scanning in response to sad facial stimuli. Multichannel matching pursuit (MMP) was implemented to manage the limited number of trials. The post-MMP MEG signals were utilized to calculate the power topography over the whole brain, as inputs for a Support Vector Machine (SVM) classifier. Standard ICA and conventional ensemble averaging plus Butterworth filtering were employed as well as benchmark studies for performance comparison. A limited number of trials were required via MMP to discriminate the depressive. Post-MMP discriminative analysis revealed a deficit theta pattern and an excessive alpha/beta pattern. The small sample size may impair the stability of the reported findings. The transient tiny variance of the signal was excluded from exploration. The deficit theta pattern together with the excessive alpha/beta pattern in depression may indicate the dysfunction of the limbic-cortical circuit in a 'top-down' process. The post-MMP discrimination helps alleviate the scanning burden, facilitating the possibility for neuroimaging supporting the affective disorder clinical diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

Cortical recovery of swallowing function in wound botulism

PubMed Central

Teismann, Inga K; Steinstraeter, Olaf; Warnecke, Tobias; Zimmermann, Julian; Ringelstein, Erich B; Pantev, Christo; Dziewas, Rainer

2008-01-01

Background Botulism is a rare disease caused by intoxication leading to muscle weakness and rapidly progressive dysphagia. With adequate therapy signs of recovery can be observed within several days. In the last few years, brain imaging studies carried out in healthy subjects showed activation of the sensorimotor cortex and the insula during volitional swallowing. However, little is known about cortical changes and compensation mechanisms accompanying swallowing pathology. Methods In this study, we applied whole-head magnetoencephalography (MEG) in order to study changes in cortical activation in a 27-year-old patient suffering from wound botulism during recovery from dysphagia. An age-matched group of healthy subjects served as control group. A self-paced swallowing paradigm was performed and data were analyzed using synthetic aperture magnetometry (SAM). Results The first MEG measurement, carried out when the patient still demonstrated severe dysphagia, revealed strongly decreased activation of the somatosensory cortex but a strong activation of the right insula and marked recruitment of the left posterior parietal cortex (PPC). In the second measurement performed five days later after clinical recovery from dysphagia we found a decreased activation in these two areas and a bilateral cortical activation of the primary and secondary sensorimotor cortex comparable to the results seen in a healthy control group. Conclusion These findings indicate parallel development to normalization of swallowing related cortical activation and clinical recovery from dysphagia and highlight the importance of the insula and the PPC for the central coordination of swallowing. The results suggest that MEG examination of swallowing can reflect short-term changes in patients suffering from neurogenic dysphagia. PMID:18462489

Cortical recovery of swallowing function in wound botulism.

PubMed

Teismann, Inga K; Steinstraeter, Olaf; Warnecke, Tobias; Zimmermann, Julian; Ringelstein, Erich B; Pantev, Christo; Dziewas, Rainer

2008-05-07

Botulism is a rare disease caused by intoxication leading to muscle weakness and rapidly progressive dysphagia. With adequate therapy signs of recovery can be observed within several days. In the last few years, brain imaging studies carried out in healthy subjects showed activation of the sensorimotor cortex and the insula during volitional swallowing. However, little is known about cortical changes and compensation mechanisms accompanying swallowing pathology. In this study, we applied whole-head magnetoencephalography (MEG) in order to study changes in cortical activation in a 27-year-old patient suffering from wound botulism during recovery from dysphagia. An age-matched group of healthy subjects served as control group. A self-paced swallowing paradigm was performed and data were analyzed using synthetic aperture magnetometry (SAM). The first MEG measurement, carried out when the patient still demonstrated severe dysphagia, revealed strongly decreased activation of the somatosensory cortex but a strong activation of the right insula and marked recruitment of the left posterior parietal cortex (PPC). In the second measurement performed five days later after clinical recovery from dysphagia we found a decreased activation in these two areas and a bilateral cortical activation of the primary and secondary sensorimotor cortex comparable to the results seen in a healthy control group. These findings indicate parallel development to normalization of swallowing related cortical activation and clinical recovery from dysphagia and highlight the importance of the insula and the PPC for the central coordination of swallowing. The results suggest that MEG examination of swallowing can reflect short-term changes in patients suffering from neurogenic dysphagia.

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning.

PubMed

Kia, Seyed Mostafa; Pedregosa, Fabian; Blumenthal, Anna; Passerini, Andrea

2017-06-15

The use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. To facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. Our experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. We compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. These results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models. Copyright © 2017 Elsevier B.V. All rights reserved.

Chaos in the brain: imaging via chaoticity of EEG/MEG signals

NASA Astrophysics Data System (ADS)

Kowalik, Zbigniew J.; Elbert, Thomas; Rockstroh, Brigitte; Hoke, Manfried

1995-03-01

Brain electro- (EEG) or magnetoencephalogram (MEG) can be analyzed by using methods of the nonlinear system theory. We show that even for very short and nonstationary time series it is possible to functionally differentiate various brain activities. Usually the analysis assumes that the analyzed signals are both long and stationary, so that the classic spectral methods can be used. Even more convincing results can be obtained under these circumstances when the dimensional analysis or estimation of the Kolmogorov entropy or the Lyapunov exponent are performed. When measuring the spontaneous activity of a human brain the assumption of stationarity is questionable and `static' methods (correlation dimension, entropy, etc.) are then not adequate. In this case `dynamic' methods like pointwise-D2 dimension or chaoticity measures should be applied. Predictability measures in the form of local Lyapunov exponents are capable of revealing directly the chaoticity of a given process, and can practically be applied for functional differentiation of brain activity. We exemplify these in cases of apallic syndrome, tinnitus and schizophrenia. We show that: the average chaoticity in apallic syndrome differentiates brain states both in space and time, chaoticity changes temporally in case of schizophrenia (critical jumps of chaoticity), chaoticity changes locally in space, i.e., in the cortex plane in case of tinnitus.

Glutamatergic Signaling Drives Ketamine-Mediated Response in Depression: Evidence from Dynamic Causal Modeling.

PubMed

Gilbert, Jessica R; Yarrington, Julia S; Wills, Kathleen E; Nugent, Allison C; Zarate, Carlos A

2018-04-13

The glutamatergic modulator ketamine has rapid antidepressant effects in individuals with major depressive disorder (MDD) and bipolar depression. Thus, modulating glutamatergic transmission may be critical to effectively treating depression, though the mechanisms by which this occurs are not fully understood. This double-blind, crossover, placebo-controlled study analyzed data from 18 drug-free MDD subjects and 18 heathy controls who received a single intravenous infusion of ketamine hydrochloride (0.5 mg/kg) as well as an intravenous saline placebo. Magnetoencephalographic (MEG) recordings were collected prior to the first infusion and six to nine hours after both ketamine and placebo infusions. During scanning, participants passively received tactile stimulation to the right index finger. Antidepressant response was assessed across timepoints using the Montgomery-Asberg Depression Rating Scale (MADRS). Dynamic causal modeling (DCM) was used to measure changes in -amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA)- and N-methyl-D-aspartate (NMDA)-mediated connectivity estimates in MDD subjects and controls using a simple model of somatosensory evoked responses. Both MDD and healthy subjects showed ketamine-mediated NMDA-blockade sensitization, with MDD subjects showing enhanced NMDA connectivity estimates in backward connections, and controls showing enhanced NMDA connectivity estimates in forward connections in our model. Within our MDD subject group, ketamine efficacy-as measured by improved mood ratings-correlated with reduced NMDA and AMPA connectivity estimates in discrete extrinsic connections within the somatosensory cortical network. These findings suggest that AMPA- and NMDA-mediated glutamatergic signaling play a key role in antidepressant response to ketamine and, further, that DCM is a powerful tool for modeling AMPA- and NMDA-mediated connectivity in vivo. NCT#00088699.

Single trial discrimination of individual finger movements on one hand: A combined MEG and EEG study☆

PubMed Central

Quandt, F.; Reichert, C.; Hinrichs, H.; Heinze, H.J.; Knight, R.T.; Rieger, J.W.

2012-01-01

It is crucial to understand what brain signals can be decoded from single trials with different recording techniques for the development of Brain-Machine Interfaces. A specific challenge for non-invasive recording methods are activations confined to small spatial areas on the cortex such as the finger representation of one hand. Here we study the information content of single trial brain activity in non-invasive MEG and EEG recordings elicited by finger movements of one hand. We investigate the feasibility of decoding which of four fingers of one hand performed a slight button press. With MEG we demonstrate reliable discrimination of single button presses performed with the thumb, the index, the middle or the little finger (average over all subjects and fingers 57%, best subject 70%, empirical guessing level: 25.1%). EEG decoding performance was less robust (average over all subjects and fingers 43%, best subject 54%, empirical guessing level 25.1%). Spatiotemporal patterns of amplitude variations in the time series provided best information for discriminating finger movements. Non-phase-locked changes of mu and beta oscillations were less predictive. Movement related high gamma oscillations were observed in average induced oscillation amplitudes in the MEG but did not provide sufficient information about the finger's identity in single trials. Importantly, pre-movement neuronal activity provided information about the preparation of the movement of a specific finger. Our study demonstrates the potential of non-invasive MEG to provide informative features for individual finger control in a Brain-Machine Interface neuroprosthesis. PMID:22155040

Magnetoencephalographic recording of auditory mismatch negativity in response to duration and frequency deviants in a single session in patients with schizophrenia.

PubMed

Suga, Motomu; Nishimura, Yukika; Kawakubo, Yuki; Yumoto, Masato; Kasai, Kiyoto

2016-07-01

Auditory mismatch negativity (MMN) and its magnetoencephalographic (MEG) counterpart (MMNm) are an established biological index in schizophrenia research. MMN in response to duration and frequency deviants may have differential relevance to the pathophysiology and clinical stages of schizophrenia. MEG has advantage in that it almost purely detects MMNm arising from the auditory cortex. However, few previous MEG studies on schizophrenia have simultaneously assessed MMNm in response to duration and frequency deviants or examined the effect of chronicity on the group difference. Forty-two patients with chronic schizophrenia and 74 matched control subjects participated in the study. Using a whole-head MEG, MMNm in response to duration and frequency deviants of tones was recorded while participants passively listened to an auditory sequence. Compared to healthy subjects, patients with schizophrenia exhibited significantly reduced powers of MMNm in response to duration deviant in both hemispheres, whereas MMNm in response to frequency deviant did not differ between the two groups. These results did not change according to the chronicity of the illness. These results, obtained by using a sequence-enabling simultaneous assessment of both types of MMNm, suggest that MEG recording of MMN in response to duration deviant may be a more sensitive biological marker of schizophrenia than MMN in response to frequency deviant. Our findings represent an important first step towards establishment of MMN as a biomarker for schizophrenia in real-world clinical psychiatry settings. © 2016 The Authors. Psychiatry and Clinical Neurosciences © 2016 Japanese Society of Psychiatry and Neurology.

Ellipsoidal head model for fetal magnetoencephalography: forward and inverse solutions

NASA Astrophysics Data System (ADS)

Gutiérrez, David; Nehorai, Arye; Preissl, Hubert

2005-05-01

Fetal magnetoencephalography (fMEG) is a non-invasive technique where measurements of the magnetic field outside the maternal abdomen are used to infer the source location and signals of the fetus' neural activity. There are a number of aspects related to fMEG modelling that must be addressed, such as the conductor volume, fetal position and orientation, gestation period, etc. We propose a solution to the forward problem of fMEG based on an ellipsoidal head geometry. This model has the advantage of highlighting special characteristics of the field that are inherent to the anisotropy of the human head, such as the spread and orientation of the field in relationship with the localization and position of the fetal head. Our forward solution is presented in the form of a kernel matrix that facilitates the solution of the inverse problem through decoupling of the dipole localization parameters from the source signals. Then, we use this model and the maximum likelihood technique to solve the inverse problem assuming the availability of measurements from multiple trials. The applicability and performance of our methods are illustrated through numerical examples based on a real 151-channel SQUID fMEG measurement system (SARA). SARA is an MEG system especially designed for fetal assessment and is currently used for heart and brain studies. Finally, since our model requires knowledge of the best-fitting ellipsoid's centre location and semiaxes lengths, we propose a method for estimating these parameters through a least-squares fit on anatomical information obtained from three-dimensional ultrasound images.

Close similarity between spatiotemporal frequency tunings of human cortical responses and involuntary manual following responses to visual motion.

PubMed

Amano, Kaoru; Kimura, Toshitaka; Nishida, Shin'ya; Takeda, Tsunehiro; Gomi, Hiroaki

2009-02-01

Human brain uses visual motion inputs not only for generating subjective sensation of motion but also for directly guiding involuntary actions. For instance, during arm reaching, a large-field visual motion is quickly and involuntarily transformed into a manual response in the direction of visual motion (manual following response, MFR). Previous attempts to correlate motion-evoked cortical activities, revealed by brain imaging techniques, with conscious motion perception have resulted only in partial success. In contrast, here we show a surprising degree of similarity between the MFR and the population neural activity measured by magnetoencephalography (MEG). We measured the MFR and MEG induced by the same motion onset of a large-field sinusoidal drifting grating with changing the spatiotemporal frequency of the grating. The initial transient phase of these two responses had very similar spatiotemporal tunings. Specifically, both the MEG and MFR amplitudes increased as the spatial frequency was decreased to, at most, 0.05 c/deg, or as the temporal frequency was increased to, at least, 10 Hz. We also found in peak latency a quantitative agreement (approximately 100-150 ms) and correlated changes against spatiotemporal frequency changes between MEG and MFR. In comparison with these two responses, conscious visual motion detection is known to be most sensitive (i.e., have the lowest detection threshold) at higher spatial frequencies and have longer and more variable response latencies. Our results suggest a close relationship between the properties of involuntary motor responses and motion-evoked cortical activity as reflected by the MEG.

Post-movement beta rebound abnormality as indicator of mirror neuron system dysfunction in autistic spectrum disorder: an MEG study.

PubMed

Honaga, Eiko; Ishii, Ryouhei; Kurimoto, Ryu; Canuet, Leonides; Ikezawa, Koji; Takahashi, Hidetoshi; Nakahachi, Takayuki; Iwase, Masao; Mizuta, Ichiro; Yoshimine, Toshiki; Takeda, Masatoshi

2010-07-12

The mu rhythm is regarded as a physiological indicator of the human mirror neuron system (MNS). The dysfunctional MNS hypothesis in patients with autistic spectrum disorder (ASD) has often been tested using EEG and MEG, targeting mu rhythm suppression during action observation/execution, although with controversial results. We explored neural activity related to the MNS in patients with ASD, focusing on power increase in the beta frequency band after observation and execution of movements, known as post-movement beta rebound (PMBR). Multiple source beamformer (MSBF) and BrainVoyager QX were used for MEG source imaging and statistical group analysis, respectively. Seven patients with ASD and ten normal subjects participated in this study. During the MEG recordings, the subjects were asked to observe and later execute object-related hand actions performed by an experimenter. We found that both groups exhibited pronounced PMBR exceeding 20% when observing and executing actions with a similar topographic distribution of maximal activity. However, significantly reduced PMBR was found only during the observation condition in the patients relative to controls in cortical regions within the MNS, namely the sensorimotor area, premotor cortex and superior temporal gyrus. Reduced PMBR during the observation condition was also found in the medial prefrontal cortex. These results support the notion of a dysfunctional execution/observation matching system related to MNS impairment in patients with ASD, and the feasibility of using MEG to detect neural activity, in particular PMBR abnormalities, as an index of MNS dysfunction during performance of motor or cognitive tasks. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.

Tracking the Speech Signal--Time-Locked MEG Signals during Perception of Ultra-Fast and Moderately Fast Speech in Blind and in Sighted Listeners

ERIC Educational Resources Information Center

Hertrich, Ingo; Dietrich, Susanne; Ackermann, Hermann

2013-01-01

Blind people can learn to understand speech at ultra-high syllable rates (ca. 20 syllables/s), a capability associated with hemodynamic activation of the central-visual system. To further elucidate the neural mechanisms underlying this skill, magnetoencephalographic (MEG) measurements during listening to sentence utterances were cross-correlated…

Auditory Evoked Responses in Neonates by MEG

NASA Astrophysics Data System (ADS)

Hernandez-Pavon, J. C.; Sosa, M.; Lutter, W. J.; Maier, M.; Wakai, R. T.

2008-08-01

Magnetoencephalography is a biomagnetic technique with outstanding potential for neurodevelopmental studies. In this work, we have used MEG to determinate if newborns can discriminate between different stimuli during the first few months of life. Five neonates were stimulated during several minutes with auditory stimulation. The results suggest that the newborns are able to discriminate between different stimuli despite their early age.

Auditory Evoked Responses in Neonates by MEG

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hernandez-Pavon, J. C.; Department of Medical Physics, University of Wisconsin Madison, Wisconsin; Sosa, M.

2008-08-11

Magnetoencephalography is a biomagnetic technique with outstanding potential for neurodevelopmental studies. In this work, we have used MEG to determinate if newborns can discriminate between different stimuli during the first few months of life. Five neonates were stimulated during several minutes with auditory stimulation. The results suggest that the newborns are able to discriminate between different stimuli despite their early age.

Lexical Access in Early Stages of Visual Word Processing: A Single-Trial Correlational MEG Study of Heteronym Recognition

ERIC Educational Resources Information Center

Solomyak, Olla; Marantz, Alec

2009-01-01

We present an MEG study of heteronym recognition, aiming to distinguish between two theories of lexical access: the "early access" theory, which entails that lexical access occurs at early (pre 200 ms) stages of processing, and the "late access" theory, which interprets this early activity as orthographic word-form identification rather than…

The Effects of Sweet, Bitter, Salty and Sour Stimuli on Alpha Rhythm. A Meg Study.

PubMed

Kotini, Athanasia; Anninos, Photios; Gemousakakis, Triandafillos; Adamopoulos, Adam

2016-09-01

the possible diff erences in processing gustatory stimuli in healthy subjects was investigated by magnetoencephalography (meg). meg recordings were evaluated for 10 healthy volunteers (3 men within the age range 20-46 years, 7 women within the age range 10-28 years), with four diff erent gustatory stimuli: sweet, bi" er, sour and salty. Fast fourier transform was performed on meg epochs recorded for the above conditions and the eff ect of each kind of stimuli on alpha rhythm was examined. A significant higher percent of alpha power was found irrespective of hemispheric side in all gustatory states located mainly at the occipital, le$ and right parietal lobes. One female volunteer experienced no statistically signifi cance when comparing normal with salty and sour taste respectively. Two female volunteers exhibited no statistically signifi cance when comparing their normal with their salty taste. One male volunteer experienced no statistically signifi cance when comparing the normalbitter and normal-salty states correspondingly. All the other subjects showed statistically signifi cant changes in alpha power for the 4 gustatory stimuli. The pattern of activation caused by the four stimuli indicated elevated gustatory processing mechanisms. This cortical activation might have applicability in modulation of brain status.

Efficient charge-carrier extraction from Ag₂S quantum dots prepared by the SILAR method for utilization of multiple exciton generation.

PubMed

Zhang, Xiaoliang; Liu, Jianhua; Johansson, Erik M J

2015-01-28

The utilization of electron-hole pairs (EHPs) generated from multiple excitons in quantum dots (QDs) is of great interest toward efficient photovoltaic devices and other optoelectronic devices; however, extraction of charge carriers remains difficult. Herein, we extract photocharges from Ag2S QDs and investigate the dependence of the electric field on the extraction of charges from multiple exciton generation (MEG). Low toxic Ag2S QDs are directly grown on TiO2 mesoporous substrates by employing the successive ionic layer adsorption and reaction (SILAR) method. The contact between QDs is important for the initial charge separation after MEG and for the carrier transport, and the space between neighbor QDs decreases with more SILAR cycles, resulting in better charge extraction. At the optimal electric field for extraction of photocharges, the results suggest that the threshold energy (hνth) for MEG is 2.41Eg. The results reveal that Ag2S QD is a promising material for efficient extraction of charges from MEG and that QDs prepared by SILAR have an advantageous electrical contact facilitating charge separation and extraction.

Armored long non-coding RNA MEG3 targeting EGFR based on recombinant MS2 bacteriophage virus-like particles against hepatocellular carcinoma.

PubMed

Chang, Le; Wang, Guojing; Jia, Tingting; Zhang, Lei; Li, Yulong; Han, Yanxi; Zhang, Kuo; Lin, Guigao; Zhang, Rui; Li, Jinming; Wang, Lunan

2016-04-26

Hepatocellular carcinoma (HCC) is one of the most frequently diagnosed cancers worldwide. However, the treatment of patients with HCC is particularly challenging. Long non-coding RNA maternally expressed gene 3 (MEG3) has been identified as a potential suppressor of several types of tumors, but the delivery of long RNA remains problematic, limiting its applications. In the present study, we designed a novel delivery system based on MS2 virus-like particles (VLPs) crosslinked with GE11 polypeptide. This vector was found to be fast, effective and safe for the targeted delivery of lncRNA MEG3 RNA to the epidermal growth factor receptor (EGFR)-positive HCC cell lines without the activation of EGFR downstream pathways, and significantly attenuated both in vitro and in vivo tumor cell growth. Our study also revealed that the targeted delivery was mainly dependent on clathrin-mediated endocytosis and MEG3 RNA suppresses tumor growth mainly via increasing the expression of p53 and its downstream gene GDF15, but decreasing the expression of MDM2. Thus, this vector is promising as a novel delivery system and may facilitate a new approach to lncRNA based cancer therapy.

Spectral changes in spontaneous MEG activity across the lifespan

NASA Astrophysics Data System (ADS)

Gómez, Carlos; Pérez-Macías, Jose M.; Poza, Jesús; Fernández, Alberto; Hornero, Roberto

2013-12-01

Objective. The aim of this study is to explore the spectral patterns of spontaneous magnetoencephalography (MEG) activity across the lifespan. Approach. Relative power (RP) in six frequency bands (delta, theta, alpha, beta-1, beta-2 and gamma) was calculated in a sample of 220 healthy subjects with ages ranging from 7 to 84 years. Main results. A significant RP decrease in low-frequency bands (i.e. delta and theta) and a significant increase in high bands (mainly beta-1 and beta-2) were found from childhood to adolescence. This trend was observed until the sixth decade of life, though only slight changes were found. Additionally, healthy aging was characterized by a power increase in low-frequency bands. Our results show that spectral changes across the lifespan may follow a quadratic relationship in delta, theta, alpha, beta-2 and gamma bands with peak ages being reached around the fifth or sixth decade of life. Significance. Our findings provide original insights into the definition of the ‘normal’ behavior of age-related MEG spectral patterns. Furthermore, our study can be useful for the forthcoming MEG research focused on the description of the abnormalities of different brain diseases in comparison to cognitive decline in normal aging.

Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements

NASA Astrophysics Data System (ADS)

Taulu, S.; Simola, J.

2006-04-01

Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.

Anatomically constrained dipole adjustment (ANACONDA) for accurate MEG/EEG focal source localizations

NASA Astrophysics Data System (ADS)

Im, Chang-Hwan; Jung, Hyun-Kyo; Fujimaki, Norio

2005-10-01

This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG.

Plasmonically enhanced electromotive force of narrow bandgap PbS QD-based photovoltaics.

PubMed

Li, Xiaowei; McNaughter, Paul D; O'Brien, Paul; Minamimoto, Hiro; Murakoshi, Kei

2018-05-30

Electromotive force of photovoltaics is a key to define the output power density of photovoltaics. Multiple exciton generation (MEG) exhibited by semiconductor quantum dots (QDs) has great potential to enhance photovoltaic performance owing to the ability to generate more than one electron-hole pairs when absorbing a single photon. However, even in MEG-based photovoltaics, limitation of modifying the electromotive force exists due to the intrinsic electrochemical potential of the conduction band-edges of QDs. Here we report a pronouncedly improved photovoltaic performance by constructing a PbS QD-sensitized electrode that comprises plasmon-active Au nanoparticles embedded in a titanium dioxide thin film. Significant enhancement on electromotive force is characterized by the onset potential of photocurrent generation using MEG-effective PbS QDs with a narrow bandgap energy (Eg = 0.9 eV). By coupling with localized surface plasmon resonance (LSPR), such QDs exhibit improved photoresponses and the highest output power density over the other QDs with larger bandgap energies (Eg = 1.1 and 1.7 eV) under visible light irradiation. The wavelength-dependent onset potential and the output power density suggest effective electron injection owing to the enhanced density of electrons excited by energy overlapping between MEG and LSPR.

Differentiability of simulated MEG hippocampal, medial temporal and neocortical temporal epileptic spike activity.

PubMed

Stephen, Julia M; Ranken, Doug M; Aine, Cheryl J; Weisend, Michael P; Shih, Jerry J

2005-12-01

Previous studies have shown that magnetoencephalography (MEG) can measure hippocampal activity, despite the cylindrical shape and deep location in the brain. The current study extended this work by examining the ability to differentiate the hippocampal subfields, parahippocampal cortex, and neocortical temporal sources using simulated interictal epileptic activity. A model of the hippocampus was generated on the MRIs of five subjects. CA1, CA3, and dentate gyrus of the hippocampus were activated as well as entorhinal cortex, presubiculum, and neocortical temporal cortex. In addition, pairs of sources were activated sequentially to emulate various hypotheses of mesial temporal lobe seizure generation. The simulated MEG activity was added to real background brain activity from the five subjects and modeled using a multidipole spatiotemporal modeling technique. The waveforms and source locations/orientations for hippocampal and parahippocampal sources were differentiable from neocortical temporal sources. In addition, hippocampal and parahippocampal sources were differentiated to varying degrees depending on source. The sequential activation of hippocampal and parahippocampal sources was adequately modeled by a single source; however, these sources were not resolvable when they overlapped in time. These results suggest that MEG has the sensitivity to distinguish parahippocampal and hippocampal spike generators in mesial temporal lobe epilepsy.

Broadband ultrafast transient absorption of multiple exciton dynamics in lead sulfide nanocrystals

NASA Astrophysics Data System (ADS)

Gesuele, Felice; Wong, Chee Wei; Sfeir, Matthew; Misewich, James; Koh, Weonkyu; Murray, Christopher

2011-03-01

Multiple exciton generation (MEG) is under intense investigation as potential third-generation solar photovoltaics with efficiencies beyond the Shockley-Queisser limit. We examine PbS nanocrystals, dispersed and vigorously stirred in TCE solution, by means of supercontinuum femtosecond transient absorption (TA). TA spectra show the presence of first and second order bleaches for the 1Sh-Se and 1Ph-Pe excitonic transition while photoinduced absorption for the 1Sh,e-Ph,e transitions. We found evidence of carrier multiplication (MEG for single absorbed photon) from the analysis of the first and second order bleaches, in the limit of low number of absorbed photons (Nabs ~ 0.01), for energy three times and four times the Energy gap. The MEG efficiency, derived from the ratio between early-time to long-time TA signal, presents a strongly dispersive behavior with maximum red shifted respect the first absorption peak. Analysis of population dynamics shows that in presence of biexciton, the 1Sh-Se bleach peak is red-shifted indicating a positive binding energy. MEG efficiency estimation will be discussed with regards to spectral integration, correlated higher-order and first excitonic transitions, as well as the nanocrystal morphologies.

Physical fatigue increases neural activation during eyes-closed state: a magnetoencephalography study.

PubMed

Tanaka, Masaaki; Ishii, Akira; Watanabe, Yasuyoshi

2015-11-05

Fatigue, defined as difficulty initiating or sustaining voluntary activities, can be classified as physical or mental. In this study, we use magnetoencephalography (MEG) to quantify the effect of physical fatigue on neural activity under the condition of simulated physical load. Thirteen healthy right-handed male volunteers participated in this study. The experiment consisted of one fatigue-inducing physical task session performed between two MEG sessions. During the 10-min physical task session, participants performed maximum-effort handgrips with the left hand lasting 1 s every 4 s; during MEG sessions, 3-min recordings were made during the eyes-closed state. MEG data were analyzed using narrow-band adaptive spatial filtering methods. Alpha-frequency band (8-13 Hz) power in the left postcentral gyrus, precentral gyrus, and middle frontal gyrus (Brodmann's areas 1, 2, 3, 4, 6, and 46) were decreased after performing the physical fatigue-inducing task. These results show that performing the physical fatigue-inducing task caused activation of the left sensorimotor and prefrontal areas, manifested as decreased alpha-frequency band power in these brain areas. Our results increase understanding of the neural mechanisms of physical fatigue.

Frequency-following and connectivity of different visual areas in response to contrast-reversal stimulation.

PubMed

Stephen, Julia M; Ranken, Doug F; Aine, Cheryl J

2006-01-01

The sensitivity of visual areas to different temporal frequencies, as well as the functional connections between these areas, was examined using magnetoencephalography (MEG). Alternating circular sinusoids (0, 3.1, 8.7 and 14 Hz) were presented to foveal and peripheral locations in the visual field to target ventral and dorsal stream structures, respectively. It was hypothesized that higher temporal frequencies would preferentially activate dorsal stream structures. To determine the effect of frequency on the cortical response we analyzed the late time interval (220-770 ms) using a multi-dipole spatio-temporal analysis approach to provide source locations and timecourses for each condition. As an exploratory aspect, we performed cross-correlation analysis on the source timecourses to determine which sources responded similarly within conditions. Contrary to predictions, dorsal stream areas were not activated more frequently during high temporal frequency stimulation. However, across cortical sources the frequency-following response showed a difference, with significantly higher power at the second harmonic for the 3.1 and 8.7 Hz stimulation and at the first and second harmonics for the 14 Hz stimulation with this pattern seen robustly in area V1. Cross-correlations of the source timecourses showed that both low- and high-order visual areas, including dorsal and ventral stream areas, were significantly correlated in the late time interval. The results imply that frequency information is transferred to higher-order visual areas without translation. Despite the less complex waveforms seen in the late interval of time, the cross-correlation results show that visual, temporal and parietal cortical areas are intricately involved in late-interval visual processing.

The Virtual Brain: a simulator of primate brain network dynamics.

PubMed

Sanz Leon, Paula; Knock, Stuart A; Woodman, M Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications.

The Virtual Brain: a simulator of primate brain network dynamics

PubMed Central

Sanz Leon, Paula; Knock, Stuart A.; Woodman, M. Marmaduke; Domide, Lia; Mersmann, Jochen; McIntosh, Anthony R.; Jirsa, Viktor

2013-01-01

We present The Virtual Brain (TVB), a neuroinformatics platform for full brain network simulations using biologically realistic connectivity. This simulation environment enables the model-based inference of neurophysiological mechanisms across different brain scales that underlie the generation of macroscopic neuroimaging signals including functional MRI (fMRI), EEG and MEG. Researchers from different backgrounds can benefit from an integrative software platform including a supporting framework for data management (generation, organization, storage, integration and sharing) and a simulation core written in Python. TVB allows the reproduction and evaluation of personalized configurations of the brain by using individual subject data. This personalization facilitates an exploration of the consequences of pathological changes in the system, permitting to investigate potential ways to counteract such unfavorable processes. The architecture of TVB supports interaction with MATLAB packages, for example, the well known Brain Connectivity Toolbox. TVB can be used in a client-server configuration, such that it can be remotely accessed through the Internet thanks to its web-based HTML5, JS, and WebGL graphical user interface. TVB is also accessible as a standalone cross-platform Python library and application, and users can interact with the scientific core through the scripting interface IDLE, enabling easy modeling, development and debugging of the scientific kernel. This second interface makes TVB extensible by combining it with other libraries and modules developed by the Python scientific community. In this article, we describe the theoretical background and foundations that led to the development of TVB, the architecture and features of its major software components as well as potential neuroscience applications. PMID:23781198

Brain structure and verbal function across adulthood while controlling for cerebrovascular risks.

PubMed

Sanfratello, L; Lundy, S L; Qualls, C; Knoefel, J E; Adair, J C; Caprihan, A; Stephen, J M; Aine, C J

2017-04-08

The development and decline of brain structure and function throughout adulthood is a complex issue, with cognitive aging trajectories influenced by a host of factors including cerebrovascular risk. Neuroimaging studies of age-related cognitive decline typically reveal a linear decrease in gray matter (GM) volume/density in frontal regions across adulthood. However, white matter (WM) tracts mature later than GM, particularly in regions necessary for executive functions and memory. Therefore, it was predicted that a middle-aged group (MC: 35-45 years) would perform best on a verbal working memory task and reveal greater regional WM integrity, compared with both young (YC: 18-25 years) and elder groups (EC: 60+ years). Diffusion tensor imaging (DTI) and magnetoencephalography (MEG) were obtained from 80 healthy participants. Objective measures of cerebrovascular risk and cognition were also obtained. As predicted, MC revealed best verbal working memory accuracy overall indicating some maturation of brain function between YC and MC. However, contrary to the prediction fractional anisotropy values (FA), a measure of WM integrity, were not greater in MC (i.e., there were no significant differences in FA between YC and MC but both groups showed greater FA than EC). An overall multivariate model for MEG ROIs showed greater peak amplitudes for MC and YC, compared with EC. Subclinical cerebrovascular risk factors (systolic blood pressure and blood glucose) were negatively associated with FA in frontal callosal, limbic, and thalamic radiation regions which correlated with executive dysfunction and slower processing speed, suggesting their contribution to age-related cognitive decline. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Haptic contents of a movie dynamically engage the spectator's sensorimotor cortex

PubMed Central

Smeds, Eero; Tikka, Pia; Pihko, Elina; Hari, Riitta; Koskinen, Miika

2016-01-01

Abstract Observation of another person's actions and feelings activates brain areas that support similar functions in the observer, thereby facilitating inferences about the other's mental and bodily states. In real life, events eliciting this kind of vicarious brain activations are intermingled with other complex, ever‐changing stimuli in the environment. One practical approach to study the neural underpinnings of real‐life vicarious perception is to image brain activity during movie viewing. Here the goal was to find out how observed haptic events in a silent movie would affect the spectator's sensorimotor cortex. The functional state of the sensorimotor cortex was monitored by analyzing, in 16 healthy subjects, magnetoencephalographic (MEG) responses to tactile finger stimuli that were presented once per second throughout the session. Using canonical correlation analysis and spatial filtering, consistent single‐trial responses across subjects were uncovered, and their waveform changes throughout the movie were quantified. The long‐latency (85–175 ms) parts of the responses were modulated in concordance with the participants’ average moment‐by‐moment ratings of own engagement in the haptic content of the movie (correlation r = 0.49; ratings collected after the MEG session). The results, obtained by using novel signal‐analysis approaches, demonstrate that the functional state of the human sensorimotor cortex fluctuates in a fine‐grained manner even during passive observation of temporally varying haptic events. Hum Brain Mapp 37:4061–4068, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:27364184

Reduced expression of CD45 Protein-Tyrosine Phosphatase Pr

DTIC Science & Technology

2009-05-08

H S /D T R A on A ugust 19, 2009 w w w .jbc.org D ow nloaded from PTP1B , CD45, TCPTP, LMPTP-A, LMPTP-B, MEG1, MEG2, HePTP, PTP), three belong to...the dual specificity phosphatase VHR or the protein-tyrosine phosphatase PTP1B . Given these FIGURE 5. Mice expressing intermediate CD45 levels survive

Why Understanding 1-3/4 divided by 1/2 Matters to Math Reform: ABE Teachers Learn the Math They Teach.

ERIC Educational Resources Information Center

Brover, Charles; Deagan, Denise; Farina, Solange

This paper explains the investigative attempts of The New York City Math Exchange Group (MEG) on elementary mathematics teachers' content knowledge in Adult Basic Education (ABE). The study is comparative in nature and took place in a workshop at the Adults Learning Maths Conference in Boston. The new members of the MEG professional development…

Progressive Presentations of Place-Based Identities in Meg Rosoff's "How I Live Now"

ERIC Educational Resources Information Center

Lockney, Karen

2013-01-01

This article provides a close reading of Meg Rosoff's award-winning novel "How I Live Now". It argues that an understanding of the text can be extended through an application of ideas found in contemporary spatial discourse concerning place. Reading the novel within this context allows a discussion of ways in which it draws on…

Short-Term Repeatability of Magnetic Resonance Elastography at 3.0T: Effects of Motion-Encoding Gradient Direction, Slice Position, and Meal Ingestion.

PubMed

Zhang, Jiming; Arena, Claudio; Pednekar, Amol; Lambert, Brenda; Dees, Debra; Lee, Vei Vei; Muthupillai, Raja

2016-03-01

Magnetic resonance elastography (MRE) can estimate liver stiffness (LS) noninvasively. We prospectively assessed whether motion-encoding gradient (MEG) direction, slice position, or high-caloric food intake affects the repeatability of MRE measurements of LS. Twenty healthy volunteers (8 women, 12 men; age, 48 ± 12 years) were imaged in a 3.0T scanner at four timepoints: twice after overnight fasting (B1 , B2 ) and twice after consuming a 1050-calorie standardized meal (A1 , A2 ; after 30 and 60 min, respectively). Each session comprised sequential MRE acquisitions in which MEG was applied in three orthogonal directions with three slices positioned over the liver for each. Between sessions, the participants were repositioned to assess test-retest reproducibility. The LS measurements before/after food intake were 3.36 ± 1.31 kPa/3.22 ± 1.03 kPa, 2.04 ± 0.33 kPa/2.27 ± 0.38 kPa, and 2.47 ± 0.50 kPa/2.64 ± 0.76 kPa for MEG superimposed along the anterior-posterior (AP), foot-head (FH), and right-left (RL) directions, respectively. Before and after food intake, LS estimates were lower and more reproducible (<10% coefficient of variation) when the MEG was in the FH direction, not the AP or RL direction. Liver stiffness estimates were significantly elevated after meal consumption when the MEG was in the FH direction (P < 0.05 for B1 vs. A1 , B1 vs. A2 , B2 vs. A1 , and B2 vs. A2 ). MRE estimates of LS were highly reproducible, particularly when MEG was applied in the FH direction, suggesting that this method could be used for long-term monitoring of antifibrotic therapy without repeated biopsies. High-caloric food intake resulted in slightly elevated LS on MRE. © 2015 Wiley Periodicals, Inc.

Current and Emerging Potential of Magnetoencephalography in the Detection and Localization of High-Frequency Oscillations in Epilepsy

PubMed Central

Tamilia, Eleonora; Madsen, Joseph R.; Grant, Patricia Ellen; Pearl, Phillip L.; Papadelis, Christos

2017-01-01

Up to one-third of patients with epilepsy are medically intractable and need resective surgery. To be successful, epilepsy surgery requires a comprehensive preoperative evaluation to define the epileptogenic zone (EZ), the brain area that should be resected to achieve seizure freedom. Due to lack of tools and methods that measure the EZ directly, this area is defined indirectly based on concordant data from a multitude of presurgical non-invasive tests and intracranial recordings. However, the results of these tests are often insufficiently concordant or inconclusive. Thus, the presurgical evaluation of surgical candidates is frequently challenging or unsuccessful. To improve the efficacy of the surgical treatment, there is an overriding need for reliable biomarkers that can delineate the EZ. High-frequency oscillations (HFOs) have emerged over the last decade as new potential biomarkers for the delineation of the EZ. Multiple studies have shown that HFOs are spatially associated with the EZ. Despite the encouraging findings, there are still significant challenges for the translation of HFOs as epileptogenic biomarkers to the clinical practice. One of the major barriers is the difficulty to detect and localize them with non-invasive techniques, such as magnetoencephalography (MEG) or scalp electroencephalography (EEG). Although most literature has studied HFOs using invasive recordings, recent studies have reported the detection and localization of HFOs using MEG or scalp EEG. MEG seems to be particularly advantageous compared to scalp EEG due to its inherent advantages of being less affected by skull conductivity and less susceptible to contamination from muscular activity. The detection and localization of HFOs with MEG would largely expand the clinical utility of these new promising biomarkers to an earlier stage in the diagnostic process and to a wider range of patients with epilepsy. Here, we conduct a thorough critical review of the recent MEG literature that investigates HFOs in patients with epilepsy, summarizing the different methodological approaches and the main findings. Our goal is to highlight the emerging potential of MEG in the non-invasive detection and localization of HFOs for the presurgical evaluation of patients with medically refractory epilepsy (MRE). PMID:28194133

Muon polarization in the MEG experiment: predictions and measurements

DOE PAGES

Baldini, A. M.; Bao, Y.; Baracchini, E.; ...

2016-04-22

The MEG experiment makes use of one of the world’s most intense low energy muon beams, in order to search for the lepton flavour violating process μ +→e +γ. We determined the residual beam polarization at the thin stopping target, by measuring the asymmetry of the angular distribution of Michel decay positrons as a function of energy. The initial muon beam polarization at the production is predicted to be P μ=-1 by the Standard Model (SM) with massless neutrinos. We estimated our residual muon polarization to be P μ= -0.86 ± 0.02 (stat)more » $$+0.05\\atop{-0.06}$$ (syst) at the stopping target, which is consistent with the SM predictions when the depolarizing effects occurring during the muon production, propagation and moderation in the target are taken into account. The knowledge of beam polarization is of fundamental importance in order to model the background of our μ +→e +γ search induced by the muon radiative decay: μ +→e +$$\\bar{v}$$ μν eγ.« less

Magnetoencephalographic Signals Identify Stages in Real-Life Decision Processes

PubMed Central

Braeutigam, Sven; Stins, John F.; Rose, Steven P. R.; Swithenby, Stephen J.; Ambler, Tim

2001-01-01

We used magnetoencephalography (MEG) to study the dynamics of neural responses in eight subjects engaged in shopping for day-to-day items from supermarket shelves. This behavior not only has personal and economic importance but also provides an example of an experience that is both personal and shared between individuals. The shopping experience enables the exploration of neural mechanisms underlying choice based on complex memories. Choosing among different brands of closely related products activated a robust sequence of signals within the first second after the presentation of the choice images. This sequence engaged first the visual cortex (80-100 ms), then as the images were analyzed, predominantly the left temporal regions (310-340 ms). At longer latency, characteristic neural activetion was found in motor speech areas (500-520 ms) for images requiring low salience choices with respect to previous (brand) memory, and in right parietal cortex for high salience choices (850-920 ms). We argue that the neural processes associated with the particular brand-choice stimulus can be separated into identifiable stages through observation of MEG responses and knowledge of functional anatomy. PMID:12018772

Context-dependent lexical ambiguity resolution: MEG evidence for the time-course of activity in left inferior frontal gyrus and posterior middle temporal gyrus.

PubMed

Mollo, Giovanna; Jefferies, Elizabeth; Cornelissen, Piers; Gennari, Silvia P

An MEG study investigated the role of context in semantic interpretation by examining the comprehension of ambiguous words in contexts leading to different interpretations. We compared high-ambiguity words in minimally different contexts (to bowl, the bowl) to low-ambiguity counterparts (the tray, to flog). Whole brain beamforming revealed the engagement of left inferior frontal gyrus (LIFG) and posterior middle temporal gyrus (LPMTG). Points of interest analyses showed that both these sites showed a stronger response to verb-contexts by 200 ms post-stimulus and displayed overlapping ambiguity effects that were sustained from 300 ms onwards. The effect of context was stronger for high-ambiguity words than for low-ambiguity words at several different time points, including within the first 100 ms post-stimulus. Unlike LIFG, LPMTG also showed stronger responses to verb than noun contexts in low-ambiguity trials. We argue that different functional roles previously attributed to LIFG and LPMTG are in fact played out at different periods during processing. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

Differential neural responses to acupuncture revealed by MEG using wavelet-based time-frequency analysis: a pilot study.

PubMed

You, Youbo; Bai, Lijun; Dai, Ruwei; Xue, Ting; Zhong, Chongguang; Feng, Yuanyuan; Wang, Hu; Liu, Zhenyu; Tian, Jie

2011-01-01

Acupoint specificity, lying at the core of the Traditional Chinese Medicine, still faces many controversies. As previous neuroimaging studies on acupuncture mainly adopted relatively low time-resolution functional magnetic resonance imaging (fMRI) technology and inappropriate block-designed experimental paradigm due to sustained effect, in the current study, we employed a single block-designed paradigm together with high temporal-resolution magnetoencephalography (MEG) technology. We applied time-frequency analysis based upon Morlet wavelet transforming approach to detect differential oscillatory brain dynamics induced by acupuncture at Stomach Meridian 36 (ST36) using a nearby nonacupoint (NAP) as control condition. We observed that frequency power changes were mainly restricted to delta band for both ST36 group and NAP group. Consistently increased delta band power in contralateral temporal regions and decreased power in the counterparts of ipsilateral hemisphere were detected following stimulation at ST36 on the right leg. Compared with ST36, no significant delta ranges were found in temporal regions in NAP group, illustrating different oscillatory brain patterns. Our results may provide additional evidence to support the specificity of acupuncture modulation effects.

Suppressive responses by visual food cues in postprandial activities of insular cortex as revealed by magnetoencephalography.

PubMed

Yoshikawa, Takahiro; Tanaka, Masaaki; Ishii, Akira; Watanabe, Yasuyoshi

2014-06-03

'Hara-Hachibu' in Japanese means a subjective sense by which we stop eating just before the motivation to eat is completely lost, a similar concept to caloric restriction (CR). Insular cortex is a critical platform which integrates sensory information into decision-making processes in eating behavior. We compared the responses of insular cortex, as assessed by magnetoencephalography (MEG), immediately after presentation of food images in the Fasting condition with those in the 'Hara-Hachibu' condition. Eleven healthy, right-handed males [age, 27.2±9.6 years; body mass index, 22.6±2.1kg/m(2) (mean±SD)] were enrolled in a randomized, two-crossover experiment (Fasting and 'Hara-Hachibu' conditions). Before the MEG recordings in the 'Hara-Hachibu' condition, the participants consumed rice balls as much as they judged themselves to have consumed shortly before reaching satiety. During the MEG recordings, they viewed food pictures projected on a screen. The intensities of MEG responses to viewing food pictures were significantly lower in the 'Hara-Hachibu' condition than those in the Fasting condition (P<0.05). The intensities of the MEG responses to the visual food stimuli in the 'Hara-Hachibu' condition was positively associated with the factor-3 (food tasted) (r=0.693, P=0.018) and aggregated scores (r=0.659, P=0.027) of the Power of Food Scale, a self-report measure of hedonic hunger. These findings may help to elucidate the neural basis of variability of appetite phenotypes under the condition of CR among individuals, and to develop possible strategies for the maintenance of adequate CR in daily life. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Thinking about the thoughts of others; temporal and spatial neural activation during false belief reasoning.

PubMed

Mossad, Sarah I; AuCoin-Power, Michelle; Urbain, Charline; Smith, Mary Lou; Pang, Elizabeth W; Taylor, Margot J

2016-07-01

Theory of Mind (ToM) is the ability to understand the perspectives, mental states and beliefs of others in order to anticipate their behaviour and is therefore crucial to social interactions. Although fMRI has been widely used to establish the neural networks implicated in ToM, little is known about the timing of ToM-related brain activity. We used magnetoencephalography (MEG) to measure the neural processes underlying ToM, as MEG provides very accurate timing and excellent spatial localization of brain processes. We recorded MEG activity during a false belief task, a reliable measure of ToM, in twenty young adults (10 females). MEG data were recorded in a 151 sensor CTF system (MISL, Coquitlam, BC) and data were co-registered to each participant's MRI (Siemens 3T) for source reconstruction. We found stronger right temporoparietal junction (rTPJ) activations in the false belief condition from 150ms to 225ms, in the right precuneus from 275ms to 375ms, in the right inferior frontal gyrus from 200ms to 300ms and the superior frontal gyrus from 300ms to 400ms. Our findings extend the literature by demonstrating the timing and duration of neural activity in the main regions involved in the "mentalizing" network, showing that activations related to false belief in adults are predominantly right lateralized and onset around 100ms. The sensitivity of MEG will allow us to determine spatial and temporal differences in the brain processes in ToM in younger populations or those who demonstrate deficits in this ability. Copyright © 2016 Elsevier Inc. All rights reserved.

Quality by Design approach for an in situ gelling microemulsion of Lorazepam via intranasal route.

PubMed

Shah, Vidhi; Sharma, Mukesh; Pandya, Radhika; Parikh, Rajesh K; Bharatiya, Bhavesh; Shukla, Atindra; Tsai, Hsieh-Chih

2017-06-01

The present study illustrates the application of the concept of Quality by Design for development, optimization and evaluation of Lorazepam loaded microemulsion containing ion responsive In situ gelator gellan gum and carbopol 934. A novel approach involving interactions between surfactant and polymer was employed to achieve controlled drug release and reduced mucociliary clearance. Microemulsion formulated using preliminary solubility study and pseudo ternary phase diagrams showed significantly improved solubilization capacity of Lorazepam with 54.31±6.07nm droplets size. The effect of oil to surfactant/cosurfactant ratio and concentration of gelling agent on the drug release and viscosity of microemulsion gel (MEG) was evaluated using a 3 2 full factorial design. The gel of optimized formulation (MEG 1 ) showed a drug release up to 6h of 97.32±1.35% of total drug loaded. The change in shear-dependent viscosity for different formulations on interaction with Simulated Nasal Fluid depicts the crucial role of surfactant-polymer interactions on the gelation properties along with calcium ions binding on the polymer chains. It is proposed that the surfactant-polymer interactions in the form of a stoichiometric hydrogen bonding between oxyethylene and carboxylic groups of the polymers used, provides exceptional ME stability and adhesion properties. Compared with the marketed formulation, optimized MEG showed improved pharmacodynamic activity. Ex vivo diffusion studies revealed significantly higher release for MEG compared to microemulsion and drug solution. MEG showed higher flux and permeation across goat nasal mucosa. According to the study, it could be concluded that formulation would successfully provide the rapid onset of action, and decrease the mucociliary clearance due to formation of in situ gelling mucoadhesive system. Copyright © 2017 Elsevier B.V. All rights reserved.

Combined MEG-EEG source localisation in patients with sub-acute sclerosing pan-encephalitis.

PubMed

Velmurugan, J; Sinha, Sanjib; Nagappa, Madhu; Mariyappa, N; Bindu, P S; Ravi, G S; Hazra, Nandita; Thennarasu, K; Ravi, V; Taly, A B; Satishchandra, P

2016-08-01

To study the genesis and propagation patterns of periodic complexes (PCs) associated with myoclonic jerks in sub-acute sclerosing pan-encephalitis (SSPE) using magnetoencephalography (MEG) and electroencephalography (EEG). Simultaneous recording of MEG (306 channels) and EEG (64 channels) in five patients of SSPE (M:F = 3:2; age 10.8 ± 3.2 years; symptom-duration 6.2 ± 10 months) was carried out using Elekta Neuromag(®) TRIUX™ system. Qualitative analysis of 80-160 PCs per patient was performed. Ten isomorphic classical PCs with significant field topography per patient were analysed at the 'onset' and at 'earliest significant peak' of the burst using discrete and distributed source imaging methods. MEG background was asymmetrical in 2 and slow in 3 patients. Complexes were periodic (3) or quasi-periodic (2), occurring every 4-16 s and varied in morphology among patients. Mean source localization at onset of bursts using discrete and distributed source imaging in magnetic source imaging (MSI) was in thalami and or insula (50 and 50 %, respectively) and in electric source imaging (ESI) was also in thalami and or insula (38 and 46 %, respectively). Mean source localization at the earliest rising phase of peak in MSI was in peri-central gyrus (49 and 42 %) and in ESI it was in frontal cortex (52 and 56 %). Further analysis revealed that PCs were generated in thalami and or insula and thereafter propagated to anterolateral surface of the cortices (viz. sensori-motor cortex and frontal cortex) to same side as that of the onset. This novel MEG-EEG based case series of PCs provides newer insights for understanding the plausible generators of myoclonus in SSPE and patterns of their propagation.