EEG-MEG Integration Enhances the Characterization of Functional and Effective Connectivity in the Resting State Network

PubMed Central

Mideksa, Kidist Gebremariam; Anwar, Abdul Rauf; Stephani, Ulrich; Deuschl, Günther; Freitag, Christine M.; Siniatchkin, Michael

2015-01-01

At the sensor level many aspects, such as spectral power, functional and effective connectivity as well as relative-power-ratio ratio (RPR) and spatial resolution have been comprehensively investigated through both electroencephalography (EEG) and magnetoencephalography (MEG). Despite this, differences between both modalities have not yet been systematically studied by direct comparison. It remains an open question as to whether the integration of EEG and MEG data would improve the information obtained from the above mentioned parameters. Here, EEG (64-channel system) and MEG (275 sensor system) were recorded simultaneously in conditions with eyes open (EO) and eyes closed (EC) in 29 healthy adults. Spectral power, functional and effective connectivity, RPR, and spatial resolution were analyzed at five different frequency bands (delta, theta, alpha, beta and gamma). Networks of functional and effective connectivity were described using a spatial filter approach called the dynamic imaging of coherent sources (DICS) followed by the renormalized partial directed coherence (RPDC). Absolute mean power at the sensor level was significantly higher in EEG than in MEG data in both EO and EC conditions. At the source level, there was a trend towards a better performance of the combined EEG+MEG analysis compared with separate EEG or MEG analyses for the source mean power, functional correlation, effective connectivity for both EO and EC. The network of coherent sources and the spatial resolution were similar for both the EEG and MEG data if they were analyzed separately. Results indicate that the combined approach has several advantages over the separate analyses of both EEG and MEG. Moreover, by a direct comparison of EEG and MEG, EEG was characterized by significantly higher values in all measured parameters in both sensor and source level. All the above conclusions are specific to the resting state task and the specific analysis used in this study to have general conclusion multi-center studies would be helpful. PMID:26509448

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals

PubMed Central

Xiang, Jing; Luo, Qian; Kotecha, Rupesh; Korman, Abraham; Zhang, Fawen; Luo, Huan; Fujiwara, Hisako; Hemasilpin, Nat; Rose, Douglas F.

2014-01-01

Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstation's memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2–3 days and used 1–2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory. PMID:24904402

Accumulated source imaging of brain activity with both low and high-frequency neuromagnetic signals.

PubMed

Xiang, Jing; Luo, Qian; Kotecha, Rupesh; Korman, Abraham; Zhang, Fawen; Luo, Huan; Fujiwara, Hisako; Hemasilpin, Nat; Rose, Douglas F

2014-01-01

Recent studies have revealed the importance of high-frequency brain signals (>70 Hz). One challenge of high-frequency signal analysis is that the size of time-frequency representation of high-frequency brain signals could be larger than 1 terabytes (TB), which is beyond the upper limits of a typical computer workstation's memory (<196 GB). The aim of the present study is to develop a new method to provide greater sensitivity in detecting high-frequency magnetoencephalography (MEG) signals in a single automated and versatile interface, rather than the more traditional, time-intensive visual inspection methods, which may take up to several days. To address the aim, we developed a new method, accumulated source imaging, defined as the volumetric summation of source activity over a period of time. This method analyzes signals in both low- (1~70 Hz) and high-frequency (70~200 Hz) ranges at source levels. To extract meaningful information from MEG signals at sensor space, the signals were decomposed to channel-cross-channel matrix (CxC) representing the spatiotemporal patterns of every possible sensor-pair. A new algorithm was developed and tested by calculating the optimal CxC and source location-orientation weights for volumetric source imaging, thereby minimizing multi-source interference and reducing computational cost. The new method was implemented in C/C++ and tested with MEG data recorded from clinical epilepsy patients. The results of experimental data demonstrated that accumulated source imaging could effectively summarize and visualize MEG recordings within 12.7 h by using approximately 10 GB of computer memory. In contrast to the conventional method of visually identifying multi-frequency epileptic activities that traditionally took 2-3 days and used 1-2 TB storage, the new approach can quantify epileptic abnormalities in both low- and high-frequency ranges at source levels, using much less time and computer memory.

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

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.

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

The Iterative Reweighted Mixed-Norm Estimate for Spatio-Temporal MEG/EEG Source Reconstruction.

PubMed

Strohmeier, Daniel; Bekhti, Yousra; Haueisen, Jens; Gramfort, Alexandre

2016-10-01

Source imaging based on magnetoencephalography (MEG) and electroencephalography (EEG) allows for the non-invasive analysis of brain activity with high temporal and good spatial resolution. As the bioelectromagnetic inverse problem is ill-posed, constraints are required. For the analysis of evoked brain activity, spatial sparsity of the neuronal activation is a common assumption. It is often taken into account using convex constraints based on the l 1 -norm. The resulting source estimates are however biased in amplitude and often suboptimal in terms of source selection due to high correlations in the forward model. In this work, we demonstrate that an inverse solver based on a block-separable penalty with a Frobenius norm per block and a l 0.5 -quasinorm over blocks addresses both of these issues. For solving the resulting non-convex optimization problem, we propose the iterative reweighted Mixed Norm Estimate (irMxNE), an optimization scheme based on iterative reweighted convex surrogate optimization problems, which are solved efficiently using a block coordinate descent scheme and an active set strategy. We compare the proposed sparse imaging method to the dSPM and the RAP-MUSIC approach based on two MEG data sets. We provide empirical evidence based on simulations and analysis of MEG data that the proposed method improves on the standard Mixed Norm Estimate (MxNE) in terms of amplitude bias, support recovery, and stability.

Localization Accuracy of Distributed Inverse Solutions for Electric and Magnetic Source Imaging of Interictal Epileptic Discharges in Patients with Focal Epilepsy.

PubMed

Heers, Marcel; Chowdhury, Rasheda A; Hedrich, Tanguy; Dubeau, François; Hall, Jeffery A; Lina, Jean-Marc; Grova, Christophe; Kobayashi, Eliane

2016-01-01

Distributed inverse solutions aim to realistically reconstruct the origin of interictal epileptic discharges (IEDs) from noninvasively recorded electroencephalography (EEG) and magnetoencephalography (MEG) signals. Our aim was to compare the performance of different distributed inverse solutions in localizing IEDs: coherent maximum entropy on the mean (cMEM), hierarchical Bayesian implementations of independent identically distributed sources (IID, minimum norm prior) and spatially coherent sources (COH, spatial smoothness prior). Source maxima (i.e., the vertex with the maximum source amplitude) of IEDs in 14 EEG and 19 MEG studies from 15 patients with focal epilepsy were analyzed. We visually compared their concordance with intracranial EEG (iEEG) based on 17 cortical regions of interest and their spatial dispersion around source maxima. Magnetic source imaging (MSI) maxima from cMEM were most often confirmed by iEEG (cMEM: 14/19, COH: 9/19, IID: 8/19 studies). COH electric source imaging (ESI) maxima co-localized best with iEEG (cMEM: 8/14, COH: 11/14, IID: 10/14 studies). In addition, cMEM was less spatially spread than COH and IID for ESI and MSI (p < 0.001 Bonferroni-corrected post hoc t test). Highest positive predictive values for cortical regions with IEDs in iEEG could be obtained with cMEM for MSI and with COH for ESI. Additional realistic EEG/MEG simulations confirmed our findings. Accurate spatially extended sources, as found in cMEM (ESI and MSI) and COH (ESI) are desirable for source imaging of IEDs because this might influence surgical decision. Our simulations suggest that COH and IID overestimate the spatial extent of the generators compared to cMEM.

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.

Imaging of neural oscillations with embedded inferential and group prevalence statistics.

PubMed

Donhauser, Peter W; Florin, Esther; Baillet, Sylvain

2018-02-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience.

Imaging of neural oscillations with embedded inferential and group prevalence statistics

PubMed Central

2018-01-01

Magnetoencephalography and electroencephalography (MEG, EEG) are essential techniques for studying distributed signal dynamics in the human brain. In particular, the functional role of neural oscillations remains to be clarified. For that reason, imaging methods need to identify distinct brain regions that concurrently generate oscillatory activity, with adequate separation in space and time. Yet, spatial smearing and inhomogeneous signal-to-noise are challenging factors to source reconstruction from external sensor data. The detection of weak sources in the presence of stronger regional activity nearby is a typical complication of MEG/EEG source imaging. We propose a novel, hypothesis-driven source reconstruction approach to address these methodological challenges. The imaging with embedded statistics (iES) method is a subspace scanning technique that constrains the mapping problem to the actual experimental design. A major benefit is that, regardless of signal strength, the contributions from all oscillatory sources, which activity is consistent with the tested hypothesis, are equalized in the statistical maps produced. We present extensive evaluations of iES on group MEG data, for mapping 1) induced oscillations using experimental contrasts, 2) ongoing narrow-band oscillations in the resting-state, 3) co-modulation of brain-wide oscillatory power with a seed region, and 4) co-modulation of oscillatory power with peripheral signals (pupil dilation). Along the way, we demonstrate several advantages of iES over standard source imaging approaches. These include the detection of oscillatory coupling without rejection of zero-phase coupling, and detection of ongoing oscillations in deeper brain regions, where signal-to-noise conditions are unfavorable. We also show that iES provides a separate evaluation of oscillatory synchronization and desynchronization in experimental contrasts, which has important statistical advantages. The flexibility of iES allows it to be adjusted to many experimental questions in systems neuroscience. PMID:29408902

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

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

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

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.

EEG and MEG data analysis in SPM8.

PubMed

Litvak, Vladimir; Mattout, Jérémie; Kiebel, Stefan; Phillips, Christophe; Henson, Richard; Kilner, James; Barnes, Gareth; Oostenveld, Robert; Daunizeau, Jean; Flandin, Guillaume; Penny, Will; Friston, Karl

2011-01-01

SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools.

EEG and MEG Data Analysis in SPM8

PubMed Central

Litvak, Vladimir; Mattout, Jérémie; Kiebel, Stefan; Phillips, Christophe; Henson, Richard; Kilner, James; Barnes, Gareth; Oostenveld, Robert; Daunizeau, Jean; Flandin, Guillaume; Penny, Will; Friston, Karl

2011-01-01

SPM is a free and open source software written in MATLAB (The MathWorks, Inc.). In addition to standard M/EEG preprocessing, we presently offer three main analysis tools: (i) statistical analysis of scalp-maps, time-frequency images, and volumetric 3D source reconstruction images based on the general linear model, with correction for multiple comparisons using random field theory; (ii) Bayesian M/EEG source reconstruction, including support for group studies, simultaneous EEG and MEG, and fMRI priors; (iii) dynamic causal modelling (DCM), an approach combining neural modelling with data analysis for which there are several variants dealing with evoked responses, steady state responses (power spectra and cross-spectra), induced responses, and phase coupling. SPM8 is integrated with the FieldTrip toolbox , making it possible for users to combine a variety of standard analysis methods with new schemes implemented in SPM and build custom analysis tools using powerful graphical user interface (GUI) and batching tools. PMID:21437221

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.

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.

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.

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.

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.

MEG (Magnetoencephalography) multipolar modeling of distributed sources using RAP-MUSIC (Recursively Applied and Projected Multiple Signal Characterization)

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

Mosher, J. C.; Baillet, S.; Jerbi, K.

2001-01-01

We describe the use of truncated multipolar expansions for producing dynamic images of cortical neural activation from measurements of the magnetoencephalogram. We use a signal-subspace method to find the locations of a set of multipolar sources, each of which represents a region of activity in the cerebral cortex. Our method builds up an estimate of the sources in a recursive manner, i.e. we first search for point current dipoles, then magnetic dipoles, and finally first order multipoles. The dynamic behavior of these sources is then computed using a linear fit to the spatiotemporal data. The final step in the proceduremore » is to map each of the multipolar sources into an equivalent distributed source on the cortical surface. The method is illustrated through an application to epileptic interictal MEG data.« less

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

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.

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.

Zoomed MRI Guided by Combined EEG/MEG Source Analysis: A Multimodal Approach for Optimizing Presurgical Epilepsy Work-up and its Application in a Multi-focal Epilepsy Patient Case Study.

PubMed

Aydin, Ü; Rampp, S; Wollbrink, A; Kugel, H; Cho, J -H; Knösche, T R; Grova, C; Wellmer, J; Wolters, C H

2017-07-01

In recent years, the use of source analysis based on electroencephalography (EEG) and magnetoencephalography (MEG) has gained considerable attention in presurgical epilepsy diagnosis. However, in many cases the source analysis alone is not used to tailor surgery unless the findings are confirmed by lesions, such as, e.g., cortical malformations in MRI. For many patients, the histology of tissue resected from MRI negative epilepsy shows small lesions, which indicates the need for more sensitive MR sequences. In this paper, we describe a technique to maximize the synergy between combined EEG/MEG (EMEG) source analysis and high resolution MRI. The procedure has three main steps: (1) construction of a detailed and calibrated finite element head model that considers the variation of individual skull conductivities and white matter anisotropy, (2) EMEG source analysis performed on averaged interictal epileptic discharges (IED), (3) high resolution (0.5 mm) zoomed MR imaging, limited to small areas centered at the EMEG source locations. The proposed new diagnosis procedure was then applied in a particularly challenging case of an epilepsy patient: EMEG analysis at the peak of the IED coincided with a right frontal focal cortical dysplasia (FCD), which had been detected at standard 1 mm resolution MRI. Of higher interest, zoomed MR imaging (applying parallel transmission, 'ZOOMit') guided by EMEG at the spike onset revealed a second, fairly subtle, FCD in the left fronto-central region. The evaluation revealed that this second FCD, which had not been detectable with standard 1 mm resolution, was the trigger of the seizures.

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

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.

Magnetoencephalography recording and analysis.

PubMed

Velmurugan, Jayabal; Sinha, Sanjib; Satishchandra, Parthasarathy

2014-03-01

Magnetoencephalography (MEG) non-invasively measures the magnetic field generated due to the excitatory postsynaptic electrical activity of the apical dendritic pyramidal cells. Such a tiny magnetic field is measured with the help of the biomagnetometer sensors coupled with the Super Conducting Quantum Interference Device (SQUID) inside the magnetically shielded room (MSR). The subjects are usually screened for the presence of ferromagnetic materials, and then the head position indicator coils, electroencephalography (EEG) electrodes (if measured simultaneously), and fiducials are digitized using a 3D digitizer, which aids in movement correction and also in transferring the MEG data from the head coordinates to the device and voxel coordinates, thereby enabling more accurate co-registration and localization. MEG data pre-processing involves filtering the data for environmental and subject interferences, artefact identification, and rejection. Magnetic resonance Imaging (MRI) is processed for correction and identifying fiducials. After choosing and computing for the appropriate head models (spherical or realistic; boundary/finite element model), the interictal/ictal epileptiform discharges are selected and modeled by an appropriate source modeling technique (clinically and commonly used - single equivalent current dipole - ECD model). The equivalent current dipole (ECD) source localization of the modeled interictal epileptiform discharge (IED) is considered physiologically valid or acceptable based on waveform morphology, isofield pattern, and dipole parameters (localization, dipole moment, confidence volume, goodness of fit). Thus, MEG source localization can aid clinicians in sublobar localization, lateralization, and grid placement, by evoking the irritative/seizure onset zone. It also accurately localizes the eloquent cortex-like visual, language areas. MEG also aids in diagnosing and delineating multiple novel findings in other neuropsychiatric disorders, including Alzheimer's disease, Parkinsonism, Traumatic brain injury, autistic disorders, and so oon.

Current Source Mapping by Spontaneous MEG and ECoG in Piglets Model

PubMed Central

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

2016-01-01

The previous research reveals the presence of relatively strong spatial correlations from spontaneous activity over cortex in Electroencephalography (EEG) and Magnetoencephalography (MEG) measurement. A critical obstacle in MEG current source mapping is that strong background activity masks the relatively weak local information. In this paper, the hypothesis is that the dominant components of this background activity can be captured by the first Principal Component (PC) after employing Principal Component Analysis (PCA), thus discarding the first PC before the back projection would enhance the exposure of the information carried by a subset of sensors that reflects the local neuronal activity. By detecting MEG signals densely (one measurement per 2×2 mm2) in three piglets neocortical models over an area of 18×26 mm2 with a special shape of lesion by means of a μSQUID, this basic idea was demonstrated by the fact that a strong activity could be imaged in the lesion region after removing the first PC in Delta, Theta and Alpha band, while the original recordings did not show such activity clearly. Thus, the PCA decomposition can be employed to expose the local activity, which is around the lesion in the piglets’ neocortical models, by removing the dominant components of the background activity. PMID:27570537

A time-frequency analysis of the dynamics of cortical networks of sleep spindles from MEG-EEG recordings

PubMed Central

Zerouali, Younes; Lina, Jean-Marc; Sekerovic, Zoran; Godbout, Jonathan; Dube, Jonathan; Jolicoeur, Pierre; Carrier, Julie

2014-01-01

Sleep spindles are a hallmark of NREM sleep. They result from a widespread thalamo-cortical loop and involve synchronous cortical networks that are still poorly understood. We investigated whether brain activity during spindles can be characterized by specific patterns of functional connectivity among cortical generators. For that purpose, we developed a wavelet-based approach aimed at imaging the synchronous oscillatory cortical networks from simultaneous MEG-EEG recordings. First, we detected spindles on the EEG and extracted the corresponding frequency-locked MEG activity under the form of an analytic ridge signal in the time-frequency plane (Zerouali et al., 2013). Secondly, we performed source reconstruction of the ridge signal within the Maximum Entropy on the Mean framework (Amblard et al., 2004), yielding a robust estimate of the cortical sources producing observed oscillations. Lastly, we quantified functional connectivity among cortical sources using phase-locking values. The main innovations of this methodology are (1) to reveal the dynamic behavior of functional networks resolved in the time-frequency plane and (2) to characterize functional connectivity among MEG sources through phase interactions. We showed, for the first time, that the switch from fast to slow oscillatory mode during sleep spindles is required for the emergence of specific patterns of connectivity. Moreover, we show that earlier synchrony during spindles was associated with mainly intra-hemispheric connectivity whereas later synchrony was associated with global long-range connectivity. We propose that our methodology can be a valuable tool for studying the connectivity underlying neural processes involving sleep spindles, such as memory, plasticity or aging. PMID:25389381

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.

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.

Alterations of Intrinsic Brain Connectivity Patterns in Depression and Bipolar Disorders: A Critical Assessment of Magnetoencephalography-Based Evidence

PubMed Central

Alamian, Golnoush; Hincapié, Ana-Sofía; Combrisson, Etienne; Thiery, Thomas; Martel, Véronique; Althukov, Dmitrii; Jerbi, Karim

2017-01-01

Despite being the object of a thriving field of clinical research, the investigation of intrinsic brain network alterations in psychiatric illnesses is still in its early days. Because the pathological alterations are predominantly probed using functional magnetic resonance imaging (fMRI), many questions about the electrophysiological bases of resting-state alterations in psychiatric disorders, particularly among mood disorder patients, remain unanswered. Alongside important research using electroencephalography (EEG), the specific recent contributions and future promise of magnetoencephalography (MEG) in this field are not fully recognized and valued. Here, we provide a critical review of recent findings from MEG resting-state connectivity within major depressive disorder (MDD) and bipolar disorder (BD). The clinical MEG resting-state results are compared with those previously reported with fMRI and EEG. Taken together, MEG appears to be a promising but still critically underexploited technique to unravel the neurophysiological mechanisms that mediate abnormal (both hyper- and hypo-) connectivity patterns involved in MDD and BD. In particular, a major strength of MEG is its ability to provide source-space estimations of neuromagnetic long-range rhythmic synchronization at various frequencies (i.e., oscillatory coupling). The reviewed literature highlights the relevance of probing local and interregional rhythmic synchronization to explore the pathophysiological underpinnings of each disorder. However, before we can fully take advantage of MEG connectivity analyses in psychiatry, several limitations inherent to MEG connectivity analyses need to be understood and taken into account. Thus, we also discuss current methodological challenges and outline paths for future research. MEG resting-state studies provide an important window onto perturbed spontaneous oscillatory brain networks and hence supply an important complement to fMRI-based resting-state measurements in psychiatric populations. PMID:28367127

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

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.

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.

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.

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

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.

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.

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.

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.

Magnetoencephalography - a noninvasive brain imaging method with 1 ms time resolution

NASA Astrophysics Data System (ADS)

DelGratta, Cosimo; Pizzella, Vittorio; Tecchio, Franca; Luca Romani, Gian

2001-12-01

The basics of magnetoencephalography (MEG), i.e. the measurement and the analysis of the tiny magnetic fields generated outside the scalp by the working human brain, are reviewed. Three main topics are discussed: (1) the relationship between the magnetic field and its generators, including on one hand the neurophysiological basis and the physical theory of magnetic field generation, and on the other hand the techniques for the estimation of the sources from the magnetic field measurements; (2) the instrumental techniques and the laboratory practice of neuromagnetic field measurement and (3) the main applications of MEG in basic neurophysiology as well as in clinical neurology.

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.

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

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

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.

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.

Comparison of imaging modalities and source-localization algorithms in locating the induced activity during deep brain stimulation of the STN.

PubMed

Mideksa, K G; Singh, A; Hoogenboom, N; Hellriegel, H; Krause, H; Schnitzler, A; Deuschl, G; Raethjen, J; Schmidt, G; Muthuraman, M

2016-08-01

One of the most commonly used therapy to treat patients with Parkinson's disease (PD) is deep brain stimulation (DBS) of the subthalamic nucleus (STN). Identifying the most optimal target area for the placement of the DBS electrodes have become one of the intensive research area. In this study, the first aim is to investigate the capabilities of different source-analysis techniques in detecting deep sources located at the sub-cortical level and validating it using the a-priori information about the location of the source, that is, the STN. Secondly, we aim at an investigation of whether EEG or MEG is best suited in mapping the DBS-induced brain activity. To do this, simultaneous EEG and MEG measurement were used to record the DBS-induced electromagnetic potentials and fields. The boundary-element method (BEM) have been used to solve the forward problem. The position of the DBS electrodes was then estimated using the dipole (moving, rotating, and fixed MUSIC), and current-density-reconstruction (CDR) (minimum-norm and sLORETA) approaches. The source-localization results from the dipole approaches demonstrated that the fixed MUSIC algorithm best localizes deep focal sources, whereas the moving dipole detects not only the region of interest but also neighboring regions that are affected by stimulating the STN. The results from the CDR approaches validated the capability of sLORETA in detecting the STN compared to minimum-norm. Moreover, the source-localization results using the EEG modality outperformed that of the MEG by locating the DBS-induced activity in the STN.

Increased Functional MEG Connectivity as a Hallmark of MRI-Negative Focal and Generalized Epilepsy.

PubMed

Li Hegner, Yiwen; Marquetand, Justus; Elshahabi, Adham; Klamer, Silke; Lerche, Holger; Braun, Christoph; Focke, Niels K

2018-05-15

Epilepsy is one of the most prevalent neurological diseases with a high morbidity. Accumulating evidence has shown that epilepsy is an archetypical neural network disorder. Here we developed a non-invasive cortical functional connectivity analysis based on magnetoencephalography (MEG) to assess commonalities and differences in the network phenotype in different epilepsy syndromes (non-lesional/cryptogenic focal and idiopathic/genetic generalized epilepsy). Thirty-seven epilepsy patients with normal structural brain anatomy underwent a 30-min resting state MEG measurement with eyes closed. We only analyzed interictal epochs without epileptiform discharges. The imaginary part of coherency was calculated as an indicator of cortical functional connectivity in five classical frequency bands. This connectivity measure was computed between all sources on individually reconstructed cortical surfaces that were surface-aligned to a common template. In comparison to healthy controls, both focal and generalized epilepsy patients showed widespread increased functional connectivity in several frequency bands, demonstrating the potential of elevated functional connectivity as a common pathophysiological hallmark in different epilepsy types. Furthermore, the comparison between focal and generalized epilepsies revealed increased network connectivity in bilateral mesio-frontal and motor regions specifically for the generalized epilepsy patients. Our study indicated that the surface-based normalization of MEG sources of individual brains enables the comparison of imaging findings across subjects and groups on a united platform, which leads to a straightforward and effective disclosure of pathological network characteristics in epilepsy. This approach may allow for the definition of more specific markers of different epilepsy syndromes, and increased MEG-based resting-state functional connectivity seems to be a common feature in MRI-negative epilepsy syndromes.

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.

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.

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.

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

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…

A comparative study of minimum norm inverse methods for MEG imaging

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

Leahy, R.M.; Mosher, J.C.; Phillips, J.W.

1996-07-01

The majority of MEG imaging techniques currently in use fall into the general class of (weighted) minimum norm methods. The minimization of a norm is used as the basis for choosing one from a generally infinite set of solutions that provide an equally good fit to the data. This ambiguity in the solution arises from the inherent non- uniqueness of the continuous inverse problem and is compounded by the imbalance between the relatively small number of measurements and the large number of source voxels. Here we present a unified view of the minimum norm methods and describe how we canmore » use Tikhonov regularization to avoid instabilities in the solutions due to noise. We then compare the performance of regularized versions of three well known linear minimum norm methods with the non-linear iteratively reweighted minimum norm method and a Bayesian approach.« less

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

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.

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.

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.

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.

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.

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.

Group Analysis in FieldTrip of Time-Frequency Responses: A Pipeline for Reproducibility at Every Step of Processing, Going From Individual Sensor Space Representations to an Across-Group Source Space Representation.

PubMed

Andersen, Lau M

2018-01-01

An important aim of an analysis pipeline for magnetoencephalographic (MEG) data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer his or her questions. The example question being answered here is whether the so-called beta rebound differs between novel and repeated stimulations. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The data analyzed are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. The processing steps covered for the first analysis are MaxFiltering the raw data, defining, preprocessing and epoching the data, cleaning the data, finding and removing independent components related to eye blinks, eye movements and heart beats, calculating participants' individual evoked responses by averaging over epoched data and subsequently removing the average response from single epochs, calculating a time-frequency representation and baselining it with non-stimulation trials and finally calculating a grand average, an across-group sensor space representation. The second analysis starts from the grand average sensor space representation and after identification of the beta rebound the neural origin is imaged using beamformer source reconstruction. This analysis covers reading in co-registered magnetic resonance images, segmenting the data, creating a volume conductor, creating a forward model, cutting out MEG data of interest in the time and frequency domains, getting Fourier transforms and estimating source activity with a beamformer model where power is expressed relative to MEG data measured during periods of non-stimulation. Finally, morphing the source estimates onto a common template and performing group-level statistics on the data are covered. Functions for saving relevant figures in an automated and structured manner are also included. The protocol presented here can be applied to any research protocol where the emphasis is on source reconstruction of induced responses where the underlying sources are not coherent.

Craniux: A LabVIEW-Based Modular Software Framework for Brain-Machine Interface Research

DTIC Science & Technology

2011-01-01

open-source BMI software solu- tions are currently available, we feel that the Craniux software package fills a specific need in the realm of BMI...data, such as cortical source imaging using EEG or MEG recordings. It is with these characteristics in mind that we feel the Craniux software package...S. Adee, “Dean Kamen’s ‘luke arm’ prosthesis readies for clinical trials,” IEEE Spectrum, February 2008, http://spectrum .ieee.org/biomedical

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

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.

From Structure to Circuits: The Contribution of MEG Connectivity Studies to Functional Neurosurgery.

PubMed

Pang, Elizabeth W; Snead Iii, O C

2016-01-01

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

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

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

Measuring functional connectivity using MEG: Methodology and comparison with fcMRI

PubMed Central

Brookes, Matthew J.; Hale, Joanne R.; Zumer, Johanna M.; Stevenson, Claire M.; Francis, Susan T.; Barnes, Gareth R.; Owen, Julia P.; Morris, Peter G.; Nagarajan, Srikantan S.

2011-01-01

Functional connectivity (FC) between brain regions is thought to be central to the way in which the brain processes information. Abnormal connectivity is thought to be implicated in a number of diseases. The ability to study FC is therefore a key goal for neuroimaging. Functional connectivity (fc) MRI has become a popular tool to make connectivity measurements but the technique is limited by its indirect nature. A multimodal approach is therefore an attractive means to investigate the electrodynamic mechanisms underlying hemodynamic connectivity. In this paper, we investigate resting state FC using fcMRI and magnetoencephalography (MEG). In fcMRI, we exploit the advantages afforded by ultra high magnetic field. In MEG we apply envelope correlation and coherence techniques to source space projected MEG signals. We show that beamforming provides an excellent means to measure FC in source space using MEG data. However, care must be taken when interpreting these measurements since cross talk between voxels in source space can potentially lead to spurious connectivity and this must be taken into account in all studies of this type. We show good spatial agreement between FC measured independently using MEG and fcMRI; FC between sensorimotor cortices was observed using both modalities, with the best spatial agreement when MEG data are filtered into the β band. This finding helps to reduce the potential confounds associated with each modality alone: while it helps reduce the uncertainties in spatial patterns generated by MEG (brought about by the ill posed inverse problem), addition of electrodynamic metric confirms the neural basis of fcMRI measurements. Finally, we show that multiple MEG based FC metrics allow the potential to move beyond what is possible using fcMRI, and investigate the nature of electrodynamic connectivity. Our results extend those from previous studies and add weight to the argument that neural oscillations are intimately related to functional connectivity and the BOLD response. PMID:21352925

Reliability of MEG source imaging of anterior temporal spikes: analysis of an intracranially characterized spike focus.

PubMed

Wennberg, Richard; Cheyne, Douglas

2014-05-01

To assess the reliability of MEG source imaging (MSI) of anterior temporal spikes through detailed analysis of the localization and orientation of source solutions obtained for a large number of spikes that were separately confirmed by intracranial EEG to be focally generated within a single, well-characterized spike focus. MSI was performed on 64 identical right anterior temporal spikes from an anterolateral temporal neocortical spike focus. The effects of different volume conductors (sphere and realistic head model), removal of noise with low frequency filters (LFFs) and averaging multiple spikes were assessed in terms of the reliability of the source solutions. MSI of single spikes resulted in scattered dipole source solutions that showed reasonable reliability for localization at the lobar level, but only for solutions with a goodness-of-fit exceeding 80% using a LFF of 3 Hz. Reliability at a finer level of intralobar localization was limited. Spike averaging significantly improved the reliability of source solutions and averaging 8 or more spikes reduced dependency on goodness-of-fit and data filtering. MSI performed on topographically identical individual spikes from an intracranially defined classical anterior temporal lobe spike focus was limited by low reliability (i.e., scattered source solutions) in terms of fine, sublobar localization within the ipsilateral temporal lobe. Spike averaging significantly improved reliability. MSI performed on individual anterior temporal spikes is limited by low reliability. Reduction of background noise through spike averaging significantly improves the reliability of MSI solutions. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Multimodal description of whole brain connectivity: A comparison of resting state MEG, fMRI, and DWI.

PubMed

Garcés, Pilar; Pereda, Ernesto; Hernández-Tamames, Juan A; Del-Pozo, Francisco; Maestú, Fernando; Pineda-Pardo, José Ángel

2016-01-01

Structural and functional connectivity (SC and FC) have received much attention over the last decade, as they offer unique insight into the coordination of brain functioning. They are often assessed independently with three imaging modalities: SC using diffusion-weighted imaging (DWI), FC using functional magnetic resonance imaging (fMRI), and magnetoencephalography/electroencephalography (MEG/EEG). DWI provides information about white matter organization, allowing the reconstruction of fiber bundles. fMRI uses blood-oxygenation level-dependent (BOLD) contrast to indirectly map neuronal activation. MEG and EEG are direct measures of neuronal activity, as they are sensitive to the synchronous inputs in pyramidal neurons. Seminal studies have targeted either the electrophysiological substrate of BOLD or the anatomical basis of FC. However, multimodal comparisons have been scarcely performed, and the relation between SC, fMRI-FC, and MEG-FC is still unclear. Here we present a systematic comparison of SC, resting state fMRI-FC, and MEG-FC between cortical regions, by evaluating their similarities at three different scales: global network, node, and hub distribution. We obtained strong similarities between the three modalities, especially for the following pairwise combinations: SC and fMRI-FC; SC and MEG-FC at theta, alpha, beta and gamma bands; and fMRI-FC and MEG-FC in alpha and beta. Furthermore, highest node similarity was found for regions of the default mode network and primary motor cortex, which also presented the highest hubness score. Distance was partially responsible for these similarities since it biased all three connectivity estimates, but not the unique contributor, since similarities remained after controlling for distance. © 2015 Wiley Periodicals, Inc.

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, ...

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

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.

Measuring electrophysiological connectivity by power envelope correlation: a technical review on MEG methods

NASA Astrophysics Data System (ADS)

O'Neill, George C.; Barratt, Eleanor L.; Hunt, Benjamin A. E.; Tewarie, Prejaas K.; Brookes, Matthew J.

2015-11-01

The human brain can be divided into multiple areas, each responsible for different aspects of behaviour. Healthy brain function relies upon efficient connectivity between these areas and, in recent years, neuroimaging has been revolutionised by an ability to estimate this connectivity. In this paper we discuss measurement of network connectivity using magnetoencephalography (MEG), a technique capable of imaging electrophysiological brain activity with good (~5 mm) spatial resolution and excellent (~1 ms) temporal resolution. The rich information content of MEG facilitates many disparate measures of connectivity between spatially separate regions and in this paper we discuss a single metric known as power envelope correlation. We review in detail the methodology required to measure power envelope correlation including (i) projection of MEG data into source space, (ii) removing confounds introduced by the MEG inverse problem and (iii) estimation of connectivity itself. In this way, we aim to provide researchers with a description of the key steps required to assess envelope based functional networks, which are thought to represent an intrinsic mode of coupling in the human brain. We highlight the principal findings of the techniques discussed, and furthermore, we show evidence that this method can probe how the brain forms and dissolves multiple transient networks on a rapid timescale in order to support current processing demand. Overall, power envelope correlation offers a unique and verifiable means to gain novel insights into network coordination and is proving to be of significant value in elucidating the neural dynamics of the human connectome in health and disease.

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.

Optimizing estimation of hemispheric dominance for language using magnetic source imaging

PubMed Central

Passaro, Antony D.; Rezaie, Roozbeh; Moser, Dana C.; Li, Zhimin; Dias, Nadeeka; Papanicolaou, Andrew C.

2011-01-01

The efficacy of magnetoencephalography (MEG) as an alternative to invasive methods for investigating the cortical representation of language has been explored in several studies. Recently, studies comparing MEG to the gold standard Wada procedure have found inconsistent and often less-than accurate estimates of laterality across various MEG studies. Here we attempted to address this issue among normal right-handed adults (N=12) by supplementing a well-established MEG protocol involving word recognition and the single dipole method with a sentence comprehension task and a beamformer approach localizing neural oscillations. Beamformer analysis of word recognition and sentence comprehension tasks revealed a desynchronization in the 10–18 Hz range, localized to the temporo-parietal cortices. Inspection of individual profiles of localized desynchronization (10–18 Hz) revealed left hemispheric dominance in 91.7% and 83.3% of individuals during the word recognition and sentence comprehension tasks, respectively. In contrast, single dipole analysis yielded lower estimates, such that activity in temporal language regions was left-lateralized in 66.7% and 58.3% of individuals during word recognition and sentence comprehension, respectively. The results obtained from the word recognition task and localization of oscillatory activity using a beamformer appear to be in line with general estimates of left hemispheric dominance for language in normal right-handed individuals. Furthermore, the current findings support the growing notion that changes in neural oscillations underlie critical components of linguistic processing. PMID:21890118

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 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.

Source analysis of MEG activities during sleep (abstract)

NASA Astrophysics Data System (ADS)

Ueno, S.; Iramina, K.

1991-04-01

The present study focuses on magnetic fields of the brain activities during sleep, in particular on K-complexes, vertex waves, and sleep spindles in human subjects. We analyzed these waveforms based on both topographic EEG (electroencephalographic) maps and magnetic fields measurements, called MEGs (magnetoencephalograms). The components of magnetic fields perpendicular to the surface of the head were measured using a dc SQUID magnetometer with a second derivative gradiometer. In our computer simulation, the head is assumed to be a homogeneous spherical volume conductor, with electric sources of brain activity modeled as current dipoles. Comparison of computer simulations with the measured data, particularly the MEG, suggests that the source of K-complexes can be modeled by two current dipoles. A source for the vertex wave is modeled by a single current dipole which orients along the body axis out of the head. By again measuring the simultaneous MEG and EEG signals, it is possible to uniquely determine the orientation of this dipole, particularly when it is tilted slightly off-axis. In sleep stage 2, fast waves of magnetic fields consistently appeared, but EEG spindles appeared intermittently. The results suggest that there exist sources which are undetectable by electrical measurement but are detectable by magnetic-field measurement. Such source can be described by a pair of opposing dipoles of which directions are oppositely oriented.

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

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

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

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

[Magnetoencephalography in the presurgical evaluation of patients with drug-resistant epilepsy].

PubMed

Koptelova, A M; Arkhipova, N A; Golovteev, A L; Chadaev, V A; Grinenko, O A; Kozlova, A B; Novikova, S I; Stepanenko, A Iu; Melikian, A G; Stroganova, T A

2013-01-01

Magnetoencephalography (MEG) in combination with structural MRI (magnetic source imaging, MSI) plays an increasingly important role as one of the tools for presurgical evaluation of medically intractable focal epilepsy. The aim of the study was to compare the MSI and commonly used video EEG monitoring method (vEEG) in their sensitivity to interictal epileptic discharges (IED) in 22 patients with drug resistant epilepsy. Furthermore, the detection and localization results obtained by both methods were verified using the data of electrocorticography (ECoG) and postsurgical outcome in 13 patients who underwent invasive EEG monitoring and surgery. The results showed that MSI was superior to vEEC in terms of sensitivity to IED with difference in sensitivity of 22%. The data also suggested that MSI superiority to vEEG in detecting epileptic discharges might, at least partly, arise from better MEG responsiveness to epileptic events coming from the medial, opercular and basal aspects of cortical lobes. MSI localization estimates were in the same cortical lobe and at the same lobar aspects as the epileptic foci detected by ECoG in all patients. Thus, magnetic source imaging can provide critical localization information that is not available when other noninvasive methods, such as vEEG and MRI, are used.

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 simple method for MR elastography: a gradient-echo type multi-echo sequence.

PubMed

Numano, Tomokazu; Mizuhara, Kazuyuki; Hata, Junichi; Washio, Toshikatsu; Homma, Kazuhiro

2015-01-01

To demonstrate the feasibility of a novel MR elastography (MRE) technique based on a conventional gradient-echo type multi-echo MR sequence which does not need additional bipolar magnetic field gradients (motion encoding gradient: MEG), yet is sensitive to vibration. In a gradient-echo type multi-echo MR sequence, several images are produced from each echo of the train with different echo times (TEs). If these echoes are synchronized with the vibration, each readout's gradient lobes achieve a MEG-like effect, and the later generated echo causes a greater MEG-like effect. The sequence was tested for the tissue-mimicking agarose gel phantoms and the psoas major muscles of healthy volunteers. It was confirmed that the readout gradient lobes caused an MEG-like effect and the later TE images had higher sensitivity to vibrations. The magnitude image of later generated echo suffered the T2 decay and the susceptibility artifacts, but the wave image and elastogram of later generated echo were unaffected by these effects. In in vivo experiments, this method was able to measure the mean shear modulus of the psoas major muscle. From the results of phantom experiments and volunteer studies, it was shown that this method has clinical application potential. Copyright © 2014 Elsevier Inc. All rights reserved.

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

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.

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.

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

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.

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

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.

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.

Optimizing estimation of hemispheric dominance for language using magnetic source imaging.

PubMed

Passaro, Antony D; Rezaie, Roozbeh; Moser, Dana C; Li, Zhimin; Dias, Nadeeka; Papanicolaou, Andrew C

2011-10-06

The efficacy of magnetoencephalography (MEG) as an alternative to invasive methods for investigating the cortical representation of language has been explored in several studies. Recently, studies comparing MEG to the gold standard Wada procedure have found inconsistent and often less-than accurate estimates of laterality across various MEG studies. Here we attempted to address this issue among normal right-handed adults (N=12) by supplementing a well-established MEG protocol involving word recognition and the single dipole method with a sentence comprehension task and a beamformer approach localizing neural oscillations. Beamformer analysis of word recognition and sentence comprehension tasks revealed a desynchronization in the 10-18Hz range, localized to the temporo-parietal cortices. Inspection of individual profiles of localized desynchronization (10-18Hz) revealed left hemispheric dominance in 91.7% and 83.3% of individuals during the word recognition and sentence comprehension tasks, respectively. In contrast, single dipole analysis yielded lower estimates, such that activity in temporal language regions was left-lateralized in 66.7% and 58.3% of individuals during word recognition and sentence comprehension, respectively. The results obtained from the word recognition task and localization of oscillatory activity using a beamformer appear to be in line with general estimates of left hemispheric dominance for language in normal right-handed individuals. Furthermore, the current findings support the growing notion that changes in neural oscillations underlie critical components of linguistic processing. Published by Elsevier B.V.

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.

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.

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

MEG Evidence for Dynamic Amygdala Modulations by Gaze and Facial Emotions

PubMed Central

Dumas, Thibaud; Dubal, Stéphanie; Attal, Yohan; Chupin, Marie; Jouvent, Roland; Morel, Shasha; George, Nathalie

2013-01-01

Background Amygdala is a key brain region for face perception. While the role of amygdala in the perception of facial emotion and gaze has been extensively highlighted with fMRI, the unfolding in time of amydgala responses to emotional versus neutral faces with different gaze directions is scarcely known. Methodology/Principal Findings Here we addressed this question in healthy subjects using MEG combined with an original source imaging method based on individual amygdala volume segmentation and the localization of sources in the amygdala volume. We found an early peak of amygdala activity that was enhanced for fearful relative to neutral faces between 130 and 170 ms. The effect of emotion was again significant in a later time range (310–350 ms). Moreover, the amygdala response was greater for direct relative averted gaze between 190 and 350 ms, and this effect was selective of fearful faces in the right amygdala. Conclusion Altogether, our results show that the amygdala is involved in the processing and integration of emotion and gaze cues from faces in different time ranges, thus underlining its role in multiple stages of face perception. PMID:24040190

MEG dual scanning: a procedure to study real-time auditory interaction between two persons

PubMed Central

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

2012-01-01

Social interactions fill our everyday life and put strong demands on our brain function. However, the possibilities for studying the brain basis of social interaction are still technically limited, and even modern brain imaging studies of social cognition typically monitor just one participant at a time. We present here a method to connect and synchronize two faraway neuromagnetometers. With this method, two participants at two separate sites can interact with each other through a stable real-time audio connection with minimal delay and jitter. The magnetoencephalographic (MEG) and audio recordings of both laboratories are accurately synchronized for joint offline analysis. The concept can be extended to connecting multiple MEG devices around the world. As a proof of concept of the MEG-to-MEG link, we report the results of time-sensitive recordings of cortical evoked responses to sounds delivered at laboratories separated by 5 km. PMID:22514530

Advanced dynamic statistical parametric mapping with MEG in localizing epileptogenicity of the bottom of sulcus dysplasia.

PubMed

Nakajima, Midori; Wong, Simeon; Widjaja, Elysa; Baba, Shiro; Okanishi, Tohru; Takada, Lynne; Sato, Yosuke; Iwata, Hiroki; Sogabe, Maya; Morooka, Hikaru; Whitney, Robyn; Ueda, Yuki; Ito, Tomoshiro; Yagyu, Kazuyori; Ochi, Ayako; Carter Snead, O; Rutka, James T; Drake, James M; Doesburg, Sam; Takeuchi, Fumiya; Shiraishi, Hideaki; Otsubo, Hiroshi

2018-06-01

To investigate whether advanced dynamic statistical parametric mapping (AdSPM) using magnetoencephalography (MEG) can better localize focal cortical dysplasia at bottom of sulcus (FCDB). We analyzed 15 children with diagnosis of FCDB in surgical specimen and 3 T MRI by using MEG. Using AdSPM, we analyzed a ±50 ms epoch relative to each single moving dipole (SMD) and applied summation technique to estimate the source activity. The most active area in AdSPM was defined as the location of AdSPM spike source. We compared spatial congruence between MRI-visible FCDB and (1) dipole cluster in SMD method; and (2) AdSPM spike source. AdSPM localized FCDB in 12 (80%) of 15 children whereas dipole cluster localized six (40%). AdSPM spike source was concordant within seizure onset zone in nine (82%) of 11 children with intracranial video EEG. Eleven children with resective surgery achieved seizure freedom with follow-up period of 1.9 ± 1.5 years. Ten (91%) of them had an AdSPM spike source in the resection area. AdSPM can noninvasively and neurophysiologically localize epileptogenic FCDB, whether it overlaps with the dipole cluster or not. This is the first study to localize epileptogenic FCDB using MEG. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

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.

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…

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

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

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.

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.

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.

Temporal and spatial localization of prediction-error signals in the visual brain.

PubMed

Johnston, Patrick; Robinson, Jonathan; Kokkinakis, Athanasios; Ridgeway, Samuel; Simpson, Michael; Johnson, Sam; Kaufman, Jordy; Young, Andrew W

2017-04-01

It has been suggested that the brain pre-empts changes in the environment through generating predictions, although real-time electrophysiological evidence of prediction violations in the domain of visual perception remain elusive. In a series of experiments we showed participants sequences of images that followed a predictable implied sequence or whose final image violated the implied sequence. Through careful design we were able to use the same final image transitions across predictable and unpredictable conditions, ensuring that any differences in neural responses were due only to preceding context and not to the images themselves. EEG and MEG recordings showed that early (N170) and mid-latency (N300) visual evoked potentials were robustly modulated by images that violated the implied sequence across a range of types of image change (expression deformations, rigid-rotations and visual field location). This modulation occurred irrespective of stimulus object category. Although the stimuli were static images, MEG source reconstruction of the early latency signal (N/M170) localized expectancy violation signals to brain areas associated with motion perception. Our findings suggest that the N/M170 can index mismatches between predicted and actual visual inputs in a system that predicts trajectories based on ongoing context. More generally we suggest that the N/M170 may reflect a "family" of brain signals generated across widespread regions of the visual brain indexing the resolution of top-down influences and incoming sensory data. This has important implications for understanding the N/M170 and investigating how the brain represents context to generate perceptual predictions. Copyright © 2017 Elsevier B.V. All rights reserved.

[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.

Investigating Causality Between Interacting Brain Areas with Multivariate Autoregressive Models of MEG Sensor Data

PubMed Central

Michalareas, George; Schoffelen, Jan-Mathijs; Paterson, Gavin; Gross, Joachim

2013-01-01

Abstract In this work, we investigate the feasibility to estimating causal interactions between brain regions based on multivariate autoregressive models (MAR models) fitted to magnetoencephalographic (MEG) sensor measurements. We first demonstrate the theoretical feasibility of estimating source level causal interactions after projection of the sensor-level model coefficients onto the locations of the neural sources. Next, we show with simulated MEG data that causality, as measured by partial directed coherence (PDC), can be correctly reconstructed if the locations of the interacting brain areas are known. We further demonstrate, if a very large number of brain voxels is considered as potential activation sources, that PDC as a measure to reconstruct causal interactions is less accurate. In such case the MAR model coefficients alone contain meaningful causality information. The proposed method overcomes the problems of model nonrobustness and large computation times encountered during causality analysis by existing methods. These methods first project MEG sensor time-series onto a large number of brain locations after which the MAR model is built on this large number of source-level time-series. Instead, through this work, we demonstrate that by building the MAR model on the sensor-level and then projecting only the MAR coefficients in source space, the true casual pathways are recovered even when a very large number of locations are considered as sources. The main contribution of this work is that by this methodology entire brain causality maps can be efficiently derived without any a priori selection of regions of interest. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc. PMID:22328419

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.

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.

Spatiotemporal mapping of interictal epileptiform discharges in human absence epilepsy: A MEG study.

PubMed

Rozendaal, Yvonne J W; van Luijtelaar, Gilles; Ossenblok, Pauly P W

2016-01-01

Although absence epilepsy is considered to be a prototypic type of generalized epilepsy, it is still under debate whether generalized 3 Hz spike-and-wave discharges (SWDs) might have a cortical focal origin. Here it is investigated whether focal interictal epileptiform discharges (IEDs), which typically occur in the electro- (EEG) and magnetoencephalogram (MEG) in case of focal epilepsy, are present in the MEG of children with absence epilepsy. Next, the location of the sources of the IEDs is established, and it is investigated whether the location is concordant to the earlier established focal cortical regions involved in the generalized SWDs of these children. Whole head MEG recordings of seven children with absence epilepsy were reviewed with respect to the presence of IEDs (spikes and sharp waves). These IEDs were grouped into distinct clusters, in which each contribution to a cluster yields a comparable magnetic field distribution. Source localization was then performed onto the average signal of each cluster using an equivalent current dipole model and a realistic head model of the cortical surface. IEDs were detected in 6 out of 7 patients. Source reconstruction indicated most often frontal, central or parietal origins of the IED in either the left and or right hemisphere. Spatiotemporal assessment of the IEDs indicated a stable location of the averages of these discharges, indicating a single underlying cortical source. The outcome of this pilot study shows that MEG is well suited for the detection of IEDs and suggests that their estimated sources coincide rather well with the cortical regions involved during the spikes of the SWDs. It is discussed whether the presence of IEDs, classically seen as a marker of focal epilepsies, indicate that absence epilepsy should be considered as a focal type of epilepsy, in which changes in the network are evolving rapidly. Copyright © 2015 Elsevier B.V. All rights reserved.

Distributed Source Modeling of Language with Magnetoencephalography: Application to Patients with Intractable Epilepsy

PubMed Central

McDonald, Carrie R.; Thesen, Thomas; Hagler, Donald J.; Carlson, Chad; Devinksy, Orrin; Kuzniecky, Rubin; Barr, William; Gharapetian, Lusineh; Trongnetrpunya, Amy; Dale, Anders M.; Halgren, Eric

2009-01-01

Purpose To examine distributed patterns of language processing in healthy controls and patients with epilepsy using magnetoencephalography (MEG), and to evaluate the concordance between laterality of distributed MEG sources and language laterality as determined by the intracarotid amobarbitol procedure (IAP). Methods MEG was performed in ten healthy controls using an anatomically-constrained, noise-normalized distributed source solution (dSPM). Distributed source modeling of language was then applied to eight patients with intractable epilepsy. Average source strengths within temporoparietal and frontal lobe regions of interest (ROIs) were calculated and the laterality of activity within ROIs during discrete time windows was compared to results from the IAP. Results In healthy controls, dSPM revealed activity in visual cortex bilaterally from ~80-120ms in response to novel words and sensory control stimuli (i.e., false fonts). Activity then spread to fusiform cortex ~160-200ms, and was dominated by left hemisphere activity in response to novel words. From ~240-450ms, novel words produced activity that was left-lateralized in frontal and temporal lobe regions, including anterior and inferior temporal, temporal pole, and pars opercularis, as well as bilaterally in posterior superior temporal cortex. Analysis of patient data with dSPM demonstrated that from 350-450ms, laterality of temporoparietal sources agreed with the IAP 75% of the time, whereas laterality of frontal MEG sources agreed with the IAP in all eight patients. Discussion Our results reveal that dSPM can unveil the timing and spatial extent of language processes in patients with epilepsy and may enhance knowledge of language lateralization and localization for use in preoperative planning. PMID:19552656

MEG source localization of spatially extended generators of epileptic activity: comparing entropic and hierarchical bayesian approaches.

PubMed

Chowdhury, Rasheda Arman; Lina, Jean Marc; Kobayashi, Eliane; Grova, Christophe

2013-01-01

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm(2) to 30 cm(2), whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered.

MEG Source Localization of Spatially Extended Generators of Epileptic Activity: Comparing Entropic and Hierarchical Bayesian Approaches

PubMed Central

Chowdhury, Rasheda Arman; Lina, Jean Marc; Kobayashi, Eliane; Grova, Christophe

2013-01-01

Localizing the generators of epileptic activity in the brain using Electro-EncephaloGraphy (EEG) or Magneto-EncephaloGraphy (MEG) signals is of particular interest during the pre-surgical investigation of epilepsy. Epileptic discharges can be detectable from background brain activity, provided they are associated with spatially extended generators. Using realistic simulations of epileptic activity, this study evaluates the ability of distributed source localization methods to accurately estimate the location of the generators and their sensitivity to the spatial extent of such generators when using MEG data. Source localization methods based on two types of realistic models have been investigated: (i) brain activity may be modeled using cortical parcels and (ii) brain activity is assumed to be locally smooth within each parcel. A Data Driven Parcellization (DDP) method was used to segment the cortical surface into non-overlapping parcels and diffusion-based spatial priors were used to model local spatial smoothness within parcels. These models were implemented within the Maximum Entropy on the Mean (MEM) and the Hierarchical Bayesian (HB) source localization frameworks. We proposed new methods in this context and compared them with other standard ones using Monte Carlo simulations of realistic MEG data involving sources of several spatial extents and depths. Detection accuracy of each method was quantified using Receiver Operating Characteristic (ROC) analysis and localization error metrics. Our results showed that methods implemented within the MEM framework were sensitive to all spatial extents of the sources ranging from 3 cm2 to 30 cm2, whatever were the number and size of the parcels defining the model. To reach a similar level of accuracy within the HB framework, a model using parcels larger than the size of the sources should be considered. PMID:23418485

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

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

[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.

Synchronization Tomography: Modeling and Exploring Complex Brain Dynamics

NASA Astrophysics Data System (ADS)

Fieseler, Thomas

2002-03-01

Phase synchronization (PS) plays an important role both under physiological and pathological conditions. With standard averaging techniques of MEG data, it is difficult to reliably detect cortico-cortical and cortico-muscular PS processes that are not time-locked to an external stimulus. For this reason, novel synchronization analysis techniques were developed and directly applied to MEG signals. Of course, due to the lack of an inverse modeling (i.e. source localization), the spatial resolution of this approach was limited. To detect and localize cerebral PS, we here present the synchronization tomography (ST): For this, we first estimate the cerebral current source density by means of the magnetic field tomography (MFT). We then apply the single-run PS analysis to the current source density in each voxel of the reconstruction space. In this way we study simulated PS, voxel by voxel in order to determine the spatio-temporal resolution of the ST. To this end different generators of ongoing rhythmic cerebral activity are simulated by current dipoles at different locations and directions, which are modeled by slightly detuned chaotic oscillators. MEG signals for these generators are simulated for a spherical head model and a whole-head MEG system. MFT current density solutions are calculated from these simulated signals within a hemispherical source space. We compare the spatial resolution of the ST with that of the MFT. Our results show that adjacent sources which are indistinguishable for the MFT, can nevertheless be separated with the ST, provided they are not strongly phase synchronized. This clearly demonstrates the potential of combining spatial information (i.e. source localization) with temporal information for the anatomical localization of phase synchronization in the human brain.

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

Wavelet-based localization of oscillatory sources from magnetoencephalography data.

PubMed

Lina, J M; Chowdhury, R; Lemay, E; Kobayashi, E; Grova, C

2014-08-01

Transient brain oscillatory activities recorded with Eelectroencephalography (EEG) or magnetoencephalography (MEG) are characteristic features in physiological and pathological processes. This study is aimed at describing, evaluating, and illustrating with clinical data a new method for localizing the sources of oscillatory cortical activity recorded by MEG. The method combines time-frequency representation and an entropic regularization technique in a common framework, assuming that brain activity is sparse in time and space. Spatial sparsity relies on the assumption that brain activity is organized among cortical parcels. Sparsity in time is achieved by transposing the inverse problem in the wavelet representation, for both data and sources. We propose an estimator of the wavelet coefficients of the sources based on the maximum entropy on the mean (MEM) principle. The full dynamics of the sources is obtained from the inverse wavelet transform, and principal component analysis of the reconstructed time courses is applied to extract oscillatory components. This methodology is evaluated using realistic simulations of single-trial signals, combining fast and sudden discharges (spike) along with bursts of oscillating activity. The method is finally illustrated with a clinical application using MEG data acquired on a patient with a right orbitofrontal epilepsy.

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.

Spatio-temporal Reconstruction of Neural Sources Using Indirect Dominant Mode Rejection.

PubMed

Jafadideh, Alireza Talesh; Asl, Babak Mohammadzadeh

2018-04-27

Adaptive minimum variance based beamformers (MVB) have been successfully applied to magnetoencephalogram (MEG) and electroencephalogram (EEG) data to localize brain activities. However, the performance of these beamformers falls down in situations where correlated or interference sources exist. To overcome this problem, we propose indirect dominant mode rejection (iDMR) beamformer application in brain source localization. This method by modifying measurement covariance matrix makes MVB applicable in source localization in the presence of correlated and interference sources. Numerical results on both EEG and MEG data demonstrate that presented approach accurately reconstructs time courses of active sources and localizes those sources with high spatial resolution. In addition, the results of real AEF data show the good performance of iDMR in empirical situations. Hence, iDMR can be reliably used for brain source localization especially when there are correlated and interference sources.

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.

Influence of metallic artifact filtering on MEG signals for source localization during interictal epileptiform activity

NASA Astrophysics Data System (ADS)

Migliorelli, Carolina; Alonso, Joan F.; Romero, Sergio; Mañanas, Miguel A.; Nowak, Rafał; Russi, Antonio

2016-04-01

Objective. Medical intractable epilepsy is a common condition that affects 40% of epileptic patients that generally have to undergo resective surgery. Magnetoencephalography (MEG) has been increasingly used to identify the epileptogenic foci through equivalent current dipole (ECD) modeling, one of the most accepted methods to obtain an accurate localization of interictal epileptiform discharges (IEDs). Modeling requires that MEG signals are adequately preprocessed to reduce interferences, a task that has been greatly improved by the use of blind source separation (BSS) methods. MEG recordings are highly sensitive to metallic interferences originated inside the head by implanted intracranial electrodes, dental prosthesis, etc and also coming from external sources such as pacemakers or vagal stimulators. To reduce these artifacts, a BSS-based fully automatic procedure was recently developed and validated, showing an effective reduction of metallic artifacts in simulated and real signals (Migliorelli et al 2015 J. Neural Eng. 12 046001). The main objective of this study was to evaluate its effects in the detection of IEDs and ECD modeling of patients with focal epilepsy and metallic interference. Approach. A comparison between the resulting positions of ECDs was performed: without removing metallic interference; rejecting only channels with large metallic artifacts; and after BSS-based reduction. Measures of dispersion and distance of ECDs were defined to analyze the results. Main results. The relationship between the artifact-to-signal ratio and ECD fitting showed that higher values of metallic interference produced highly scattered dipoles. Results revealed a significant reduction on dispersion using the BSS-based reduction procedure, yielding feasible locations of ECDs in contrast to the other two approaches. Significance. The automatic BSS-based method can be applied to MEG datasets affected by metallic artifacts as a processing step to improve the localization of epileptic foci.

Measuring MEG closer to the brain: Performance of on-scalp sensor arrays

PubMed Central

Iivanainen, Joonas; Stenroos, Matti; Parkkonen, Lauri

2017-01-01

Optically-pumped magnetometers (OPMs) have recently reached sensitivity levels required for magnetoencephalography (MEG). OPMs do not need cryogenics and can thus be placed within millimetres from the scalp into an array that adapts to the invidual head size and shape, thereby reducing the distance from cortical sources to the sensors. Here, we quantified the improvement in recording MEG with hypothetical on-scalp OPM arrays compared to a 306-channel state-of-the-art SQUID array (102 magnetometers and 204 planar gradiometers). We simulated OPM arrays that measured either normal (nOPM; 102 sensors), tangential (tOPM; 204 sensors), or all components (aOPM; 306 sensors) of the magnetic field. We built forward models based on magnetic resonance images of 10 adult heads; we employed a three-compartment boundary element model and distributed current dipoles evenly across the cortical mantle. Compared to the SQUID magnetometers, nOPM and tOPM yielded 7.5 and 5.3 times higher signal power, while the correlations between the field patterns of source dipoles were reduced by factors of 2.8 and 3.6, respectively. Values of the field-pattern correlations were similar across nOPM, tOPM and SQUID gradiometers. Volume currents reduced the signals of primary currents on average by 10%, 72% and 15% in nOPM, tOPM and SQUID magnetometers, respectively. The information capacities of the OPM arrays were clearly higher than that of the SQUID array. The dipole-localization accuracies of the arrays were similar while the minimum-norm-based point-spread functions were on average 2.4 and 2.5 times more spread for the SQUID array compared to nOPM and tOPM arrays, respectively. PMID:28007515

Cortical localization of phase and amplitude dynamics predicting access to somatosensory awareness.

PubMed

Hirvonen, Jonni; Palva, Satu

2016-01-01

Neural dynamics leading to conscious sensory perception have remained enigmatic in despite of large interest. Human functional magnetic resonance imaging (fMRI) studies have revealed that a co-activation of sensory and frontoparietal areas is crucial for conscious sensory perception in the several second time-scale of BOLD signal fluctuations. Electrophysiological recordings with magneto- and electroencephalography (MEG and EEG) and intracranial EEG (iEEG) have shown that event related responses (ERs), phase-locking of neuronal activity, and oscillation amplitude modulations in sub-second timescales are greater for consciously perceived than for unperceived stimuli. The cortical sources of ER and oscillation dynamics predicting the conscious perception have, however, remained unclear because these prior studies have utilized MEG/EEG sensor-level analyses or iEEG with limited neuroanatomical coverage. We used a somatosensory detection task, magnetoencephalography (MEG), and cortically constrained source reconstruction to identify the cortical areas where ERs, local poststimulus amplitudes and phase-locking of neuronal activity are predictive of the conscious access of somatosensory information. We show here that strengthened ERs, phase-locking to stimulus onset (SL), and induced oscillations amplitude modulations all predicted conscious somatosensory perception, but the most robust and widespread of these was SL that was sustained in low-alpha (6-10 Hz) band. The strength of SL and to a lesser extent that of ER predicted conscious perception in the somatosensory, lateral and medial frontal, posterior parietal, and in the cingulate cortex. These data suggest that a rapid phase-reorganization and concurrent oscillation amplitude modulations in these areas play an instrumental role in the emergence of a conscious percept. © 2015 Wiley Periodicals, Inc.

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.

Localized N20 Component of Somatosensory Evoked Magnetic Fields in Frontoparietal Brain Tumor Patients Using Noise-Normalized Approaches.

PubMed

Elaina, Nor Safira; Malik, Aamir Saeed; Shams, Wafaa Khazaal; Badruddin, Nasreen; Abdullah, Jafri Malin; Reza, Mohammad Faruque

2018-06-01

To localize sensorimotor cortical activation in 10 patients with frontoparietal tumors using quantitative magnetoencephalography (MEG) with noise-normalized approaches. Somatosensory evoked magnetic fields (SEFs) were elicited in 10 patients with somatosensory tumors and in 10 control participants using electrical stimulation of the median nerve via the right and left wrists. We localized the N20m component of the SEFs using dynamic statistical parametric mapping (dSPM) and standardized low-resolution brain electromagnetic tomography (sLORETA) combined with 3D magnetic resonance imaging (MRI). The obtained coordinates were compared between groups. Finally, we statistically evaluated the N20m parameters across hemispheres using non-parametric statistical tests. The N20m sources were accurately localized to Brodmann area 3b in all members of the control group and in seven of the patients; however, the sources were shifted in three patients relative to locations outside the primary somatosensory cortex (SI). Compared with the affected (tumor) hemispheres in the patient group, N20m amplitudes and the strengths of the current sources were significantly lower in the unaffected hemispheres and in both hemispheres of the control group. These results were consistent for both dSPM and sLORETA approaches. Tumors in the sensorimotor cortex lead to cortical functional reorganization and an increase in N20m amplitude and current-source strengths. Noise-normalized approaches for MEG analysis that are integrated with MRI show accurate and reliable localization of sensorimotor function.

Direct imaging of neural currents using ultra-low field magnetic resonance techniques

DOEpatents

Volegov, Petr L [Los Alamos, NM; Matlashov, Andrei N [Los Alamos, NM; Mosher, John C [Los Alamos, NM; Espy, Michelle A [Los Alamos, NM; Kraus, Jr., Robert H.

2009-08-11

Using resonant interactions to directly and tomographically image neural activity in the human brain using magnetic resonance imaging (MRI) techniques at ultra-low field (ULF), the present inventors have established an approach that is sensitive to magnetic field distributions local to the spin population in cortex at the Larmor frequency of the measurement field. Because the Larmor frequency can be readily manipulated (through varying B.sub.m), one can also envision using ULF-DNI to image the frequency distribution of the local fields in cortex. Such information, taken together with simultaneous acquisition of MEG and ULF-NMR signals, enables non-invasive exploration of the correlation between local fields induced by neural activity in cortex and more `distant` measures of brain activity such as MEG and EEG.

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.

Test-retest reliability of resting-state magnetoencephalography power in sensor and source space.

PubMed

Martín-Buro, María Carmen; Garcés, Pilar; Maestú, Fernando

2016-01-01

Several studies have reported changes in spontaneous brain rhythms that could be used as clinical biomarkers or in the evaluation of neuropsychological and drug treatments in longitudinal studies using magnetoencephalography (MEG). There is an increasing necessity to use these measures in early diagnosis and pathology progression; however, there is a lack of studies addressing how reliable they are. Here, we provide the first test-retest reliability estimate of MEG power in resting-state at sensor and source space. In this study, we recorded 3 sessions of resting-state MEG activity from 24 healthy subjects with an interval of a week between each session. Power values were estimated at sensor and source space with beamforming for classical frequency bands: delta (2-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), low beta (13-20 Hz), high beta (20-30 Hz), and gamma (30-45 Hz). Then, test-retest reliability was evaluated using the intraclass correlation coefficient (ICC). We also evaluated the relation between source power and the within-subject variability. In general, ICC of theta, alpha, and low beta power was fairly high (ICC > 0.6) while in delta and gamma power was lower. In source space, fronto-posterior alpha, frontal beta, and medial temporal theta showed the most reliable profiles. Signal-to-noise ratio could be partially responsible for reliability as low signal intensity resulted in high within-subject variability, but also the inherent nature of some brain rhythms in resting-state might be driving these reliability patterns. In conclusion, our results described the reliability of MEG power estimates in each frequency band, which could be considered in disease characterization or clinical trials. © 2015 Wiley Periodicals, Inc.

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.

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

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

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.

Use of multidimensional, multimodal imaging and PACS to support neurological diagnoses

NASA Astrophysics Data System (ADS)

Wong, Stephen T. C.; Knowlton, Robert C.; Hoo, Kent S.; Huang, H. K.

1995-05-01

Technological advances in brain imaging have revolutionized diagnosis in neurology and neurological surgery. Major imaging techniques include magnetic resonance imaging (MRI) to visualize structural anatomy, positron emission tomography (PET) to image metabolic function and cerebral blood flow, magnetoencephalography (MEG) to visualize the location of physiologic current sources, and magnetic resonance spectroscopy (MRS) to measure specific biochemicals. Each of these techniques studies different biomedical aspects of the brain, but there lacks an effective means to quantify and correlate the disparate imaging datasets in order to improve clinical decision making processes. This paper describes several techniques developed in a UNIX-based neurodiagnostic workstation to aid the noninvasive presurgical evaluation of epilepsy patients. These techniques include online access to the picture archiving and communication systems (PACS) multimedia archive, coregistration of multimodality image datasets, and correlation and quantitation of structural and functional information contained in the registered images. For illustration, we describe the use of these techniques in a patient case of nonlesional neocortical epilepsy. We also present out future work based on preliminary studies.

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.

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.

Localization from near-source quasi-static electromagnetic fields

NASA Astrophysics Data System (ADS)

Mosher, J. C.

1993-09-01

A wide range of research has been published on the problem of estimating the parameters of electromagnetic and acoustical sources from measurements of signals measured at an array of sensors. In the quasi-static electromagnetic cases examined here, the signal variation from a point source is relatively slow with respect to the signal propagation and the spacing of the array of sensors. As such, the location of the point sources can only be determined from the spatial diversity of the received signal across the array. The inverse source localization problem is complicated by unknown model order and strong local minima. The nonlinear optimization problem is posed for solving for the parameters of the quasi-static source model. The transient nature of the sources can be exploited to allow subspace approaches to separate out the signal portion of the spatial correlation matrix. Decomposition techniques are examined for improved processing, and an adaptation of MUltiple SIgnal Characterization (MUSIC) is presented for solving the source localization problem. Recent results on calculating the Cramer-Rao error lower bounds are extended to the multidimensional problem here. This thesis focuses on the problem of source localization in magnetoencephalography (MEG), with a secondary application to thunderstorm source localization. Comparisons are also made between MEG and its electrical equivalent, electroencephalography (EEG). The error lower bounds are examined in detail for several MEG and EEG configurations, as well as localizing thunderstorm cells over Cape Canaveral and Kennedy Space Center. Time-eigenspectrum is introduced as a parsing technique for improving the performance of the optimization problem.

Localization from near-source quasi-static electromagnetic fields

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

Mosher, John Compton

1993-09-01

A wide range of research has been published on the problem of estimating the parameters of electromagnetic and acoustical sources from measurements of signals measured at an array of sensors. In the quasi-static electromagnetic cases examined here, the signal variation from a point source is relatively slow with respect to the signal propagation and the spacing of the array of sensors. As such, the location of the point sources can only be determined from the spatial diversity of the received signal across the array. The inverse source localization problem is complicated by unknown model order and strong local minima. Themore » nonlinear optimization problem is posed for solving for the parameters of the quasi-static source model. The transient nature of the sources can be exploited to allow subspace approaches to separate out the signal portion of the spatial correlation matrix. Decomposition techniques are examined for improved processing, and an adaptation of MUtiple SIgnal Characterization (MUSIC) is presented for solving the source localization problem. Recent results on calculating the Cramer-Rao error lower bounds are extended to the multidimensional problem here. This thesis focuses on the problem of source localization in magnetoencephalography (MEG), with a secondary application to thunderstorm source localization. Comparisons are also made between MEG and its electrical equivalent, electroencephalography (EEG). The error lower bounds are examined in detail for several MEG and EEG configurations, as well as localizing thunderstorm cells over Cape Canaveral and Kennedy Space Center. Time-eigenspectrum is introduced as a parsing technique for improving the performance of the optimization problem.« less

Optimising experimental design for MEG resting state functional connectivity measurement.

PubMed

Liuzzi, Lucrezia; Gascoyne, Lauren E; Tewarie, Prejaas K; Barratt, Eleanor L; Boto, Elena; Brookes, Matthew J

2017-07-15

The study of functional connectivity using magnetoencephalography (MEG) is an expanding area of neuroimaging, and adds an extra dimension to the more common assessments made using fMRI. The importance of such metrics is growing, with recent demonstrations of their utility in clinical research, however previous reports suggest that whilst group level resting state connectivity is robust, single session recordings lack repeatability. Such robustness is critical if MEG measures in individual subjects are to prove clinically valuable. In the present paper, we test how practical aspects of experimental design affect the intra-subject repeatability of MEG findings; specifically we assess the effect of co-registration method and data recording duration. We show that the use of a foam head-cast, which is known to improve co-registration accuracy, increased significantly the between session repeatability of both beamformer reconstruction and connectivity estimation. We also show that recording duration is a critical parameter, with large improvements in repeatability apparent when using ten minute, compared to five minute recordings. Further analyses suggest that the origin of this latter effect is not underpinned by technical aspects of source reconstruction, but rather by a genuine effect of brain state; short recordings are simply inefficient at capturing the canonical MEG network in a single subject. Our results provide important insights on experimental design and will prove valuable for future MEG connectivity studies. Copyright © 2016. Published by Elsevier Inc.

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).

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.

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.

Language-motor interference reflected in MEG beta oscillations.

PubMed

Klepp, Anne; Niccolai, Valentina; Buccino, Giovanni; Schnitzler, Alfons; Biermann-Ruben, Katja

2015-04-01

The involvement of the brain's motor system in action-related language processing can lead to overt interference with simultaneous action execution. The aim of the current study was to find evidence for this behavioural interference effect and to investigate its neurophysiological correlates using oscillatory MEG analysis. Subjects performed a semantic decision task on single action verbs, describing actions executed with the hands or the feet, and abstract verbs. Right hand button press responses were given for concrete verbs only. Therefore, longer response latencies for hand compared to foot verbs should reflect interference. We found interference effects to depend on verb imageability: overall response latencies for hand verbs did not differ significantly from foot verbs. However, imageability interacted with effector: while response latencies to hand and foot verbs with low imageability were equally fast, those for highly imageable hand verbs were longer than for highly imageable foot verbs. The difference is reflected in motor-related MEG beta band power suppression, which was weaker for highly imageable hand verbs compared with highly imageable foot verbs. This provides a putative neuronal mechanism for language-motor interference where the involvement of cortical hand motor areas in hand verb processing interacts with the typical beta suppression seen before movements. We found that the facilitatory effect of higher imageability on action verb processing time is perturbed when verb and motor response relate to the same body part. Importantly, this effect is accompanied by neurophysiological effects in beta band oscillations. The attenuated power suppression around the time of movement, reflecting decreased cortical excitability, seems to result from motor simulation during action-related language processing. This is in line with embodied cognition theories. Copyright © 2015. Published by Elsevier Inc.

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.

Multimodal Classification of Schizophrenia Patients with MEG and fMRI Data Using Static and Dynamic Connectivity Measures

PubMed Central

Cetin, Mustafa S.; Houck, Jon M.; Rashid, Barnaly; Agacoglu, Oktay; Stephen, Julia M.; Sui, Jing; Canive, Jose; Mayer, Andy; Aine, Cheryl; Bustillo, Juan R.; Calhoun, Vince D.

2016-01-01

Mental disorders like schizophrenia are currently diagnosed by physicians/psychiatrists through clinical assessment and their evaluation of patient's self-reported experiences as the illness emerges. There is great interest in identifying biological markers of prognosis at the onset of illness, rather than relying on the evolution of symptoms across time. Functional network connectivity, which indicates a subject's overall level of “synchronicity” of activity between brain regions, demonstrates promise in providing individual subject predictive power. Many previous studies reported functional connectivity changes during resting-state using only functional magnetic resonance imaging (fMRI). Nevertheless, exclusive reliance on fMRI to generate such networks may limit the inference of the underlying dysfunctional connectivity, which is hypothesized to be a factor in patient symptoms, as fMRI measures connectivity via hemodynamics. Therefore, combination of connectivity assessments using fMRI and magnetoencephalography (MEG), which more directly measures neuronal activity, may provide improved classification of schizophrenia than either modality alone. Moreover, recent evidence indicates that metrics of dynamic connectivity may also be critical for understanding pathology in schizophrenia. In this work, we propose a new framework for extraction of important disease related features and classification of patients with schizophrenia based on using both fMRI and MEG to investigate functional network components in the resting state. Results of this study show that the integration of fMRI and MEG provides important information that captures fundamental characteristics of functional network connectivity in schizophrenia and is helpful for prediction of schizophrenia patient group membership. Combined fMRI/MEG methods, using static functional network connectivity analyses, improved classification accuracy relative to use of fMRI or MEG methods alone (by 15 and 12.45%, respectively), while combined fMRI/MEG methods using dynamic functional network connectivity analyses improved classification up to 5.12% relative to use of fMRI alone and up to 17.21% relative to use of MEG alone. PMID:27807403

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.

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.

The temporal evolution of electromagnetic markers sensitive to the capacity limits of visual short-term memory.

PubMed

Mitchell, Daniel J; Cusack, Rhodri

2011-01-01

An electroencephalographic (EEG) marker of the limited contents of human visual short-term memory (VSTM) has previously been described. Termed contralateral delay activity, this consists of a sustained, posterior, negative potential that correlates with memory load and is greatest contralateral to the remembered hemifield. The current investigation replicates this finding and uses magnetoencephalography (MEG) to characterize its magnetic counterparts and their neural generators as they evolve throughout the memory delay. A parametric manipulation of memory load, within and beyond capacity limits, allows separation of signals that asymptote with behavioral VSTM performance from additional responses that contribute to a linear increase with set-size. Both EEG and MEG yielded bilateral signals that track the number of objects held in memory, and contralateral signals that are independent of memory load. In MEG, unlike EEG, the contralateral interaction between hemisphere and item load is much weaker, suggesting that bilateral and contralateral markers of memory load reflect distinct sources to which EEG and MEG are differentially sensitive. Nonetheless, source estimation allowed both the bilateral and the weaker contralateral capacity-limited responses to be localized, along with a load-independent contralateral signal. Sources of global and hemisphere-specific signals all localized to the posterior intraparietal sulcus during the early delay. However the bilateral load response peaked earlier and its generators shifted later in the delay. Therefore the hemifield-specific response may be more closely tied to memory maintenance while the global load response may be involved in initial processing of a limited number of attended objects, such as their individuation or consolidation into memory.

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

Amplitude modulation of alpha-band rhythm caused by mimic collision: MEG study.

PubMed

Yokosawa, Koichi; Watanabe, Tatsuya; Kikuzawa, Daichi; Aoyama, Gakuto; Takahashi, Makoto; Kuriki, Shinya

2013-01-01

Detection of a collision risk and avoiding the collision are important for survival. We have been investigating neural responses when humans anticipate a collision or intend to take evasive action by applying collision-simulating images in a predictable manner. Collision-simulating images and control images were presented in random order to 9 healthy male volunteers. A cue signal was also given visually two seconds before each stimulus to enable each participant to anticipate the upcoming stimulus. Magnetoencephalograms (MEG) were recorded with a 76-ch helmet system. The amplitude of alpha band (8-13 Hz) rhythm when anticipating the upcoming collision-simulating image was significantly smaller than that when anticipating control images even just after the cue signal. This result demonstrates that anticipating a negative (dangerous) event induced event-related desynchronization (ERD) of alpha band activity, probably caused by attention. The results suggest the feasibility of detecting endogenous brain activities by monitoring alpha band rhythm and its possible applications to engineering systems, such as an automatic collision evasion system for automobiles.

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.

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.

Interictal High Frequency Oscillations Detected with Simultaneous Magnetoencephalography and Electroencephalography as Biomarker of Pediatric Epilepsy

PubMed Central

Papadelis, Christos; Tamilia, Eleonora; Stufflebeam, Steven; Grant, Patricia E.; Madsen, Joseph R.; Pearl, Phillip L.; Tanaka, Naoaki

2016-01-01

Crucial to the success of epilepsy surgery is the availability of a robust biomarker that identifies the Epileptogenic Zone (EZ). High Frequency Oscillations (HFOs) have emerged as potential presurgical biomarkers for the identification of the EZ in addition to Interictal Epileptiform Discharges (IEDs) and ictal activity. Although they are promising to localize the EZ, they are not yet suited for the diagnosis or monitoring of epilepsy in clinical practice. Primary barriers remain: the lack of a formal and global definition for HFOs; the consequent heterogeneity of methodological approaches used for their study; and the practical difficulties to detect and localize them noninvasively from scalp recordings. Here, we present a methodology for the recording, detection, and localization of interictal HFOs from pediatric patients with refractory epilepsy. We report representative data of HFOs detected noninvasively from interictal scalp EEG and MEG from two children undergoing surgery. The underlying generators of HFOs were localized by solving the inverse problem and their localization was compared to the Seizure Onset Zone (SOZ) as this was defined by the epileptologists. For both patients, Interictal Epileptogenic Discharges (IEDs) and HFOs were localized with source imaging at concordant locations. For one patient, intracranial EEG (iEEG) data were also available. For this patient, we found that the HFOs localization was concordant between noninvasive and invasive methods. The comparison of iEEG with the results from scalp recordings served to validate these findings. To our best knowledge, this is the first study that presents the source localization of scalp HFOs from simultaneous EEG and MEG recordings comparing the results with invasive recordings. These findings suggest that HFOs can be reliably detected and localized noninvasively with scalp EEG and MEG. We conclude that the noninvasive localization of interictal HFOs could significantly improve the presurgical evaluation for pediatric patients with epilepsy. PMID:28060325

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

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.

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

Use of multidimensional, multimodal imaging and PACS to support neurological diagnoses

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

Wong, S.T.C.; Knowlton, R.; Hoo, K.S.

1995-12-31

Technological advances in brain imaging have revolutionized diagnosis in neurology and neurological surgery. Major imaging techniques include magnetic resonance imaging (MRI) to visualize structural anatomy, positron emission tomography (PET) to image metabolic function and cerebral blood flow, magnetoencephalography (MEG) to visualize the location of physiologic current sources, and magnetic resonance spectroscopy (MRS) to measure specific biochemicals. Each of these techniques studies different biomedical aspects of the grain, but there lacks an effective means to quantify and correlate the disparate imaging datasets in order to improve clinical decision making processes. This paper describes several techniques developed in a UNIX-based neurodiagnostic workstationmore » to aid the non-invasive presurgical evaluation of epilepsy patients. These techniques include on-line access to the picture archiving and communication systems (PACS) multimedia archive, coregistration of multimodality image datasets, and correlation and quantitative of structural and functional information contained in the registered images. For illustration, the authors describe the use of these techniques in a patient case of non-lesional neocortical epilepsy. They also present the future work based on preliminary studies.« less

EEG and MEG source localization using recursively applied (RAP) MUSIC

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

Mosher, J.C.; Leahy, R.M.

1996-12-31

The multiple signal characterization (MUSIC) algorithm locates multiple asynchronous dipolar sources from electroencephalography (EEG) and magnetoencephalography (MEG) data. A signal subspace is estimated from the data, then the algorithm scans a single dipole model through a three-dimensional head volume and computes projections onto this subspace. To locate the sources, the user must search the head volume for local peaks in the projection metric. Here we describe a novel extension of this approach which we refer to as RAP (Recursively APplied) MUSIC. This new procedure automatically extracts the locations of the sources through a recursive use of subspace projections, which usesmore » the metric of principal correlations as a multidimensional form of correlation analysis between the model subspace and the data subspace. The dipolar orientations, a form of `diverse polarization,` are easily extracted using the associated principal vectors.« less

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.

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.

DC magnetic fields from the human body generally: a historical overview.

PubMed

Cohen, D

2004-11-30

A review is presented of the earliest dc magnetic field (dcMF) measurements, made between 1969 and 1983, due to natural currents in the body. The measurements were essentially a mapping over the whole body, except for the brain (dcMEG), which was omitted because of interfering non-neural sources in the head. This mapping can be useful today in interpreting new measurements over the body, especially dcMEG data, where the new authors assume only a neural source in the head; our mapping suggests that this assumption may be in error. Briefly, in our mapping, dcMFs were found over almost the entire body; they were larger over the limbs and head than over the torso proper except over the abdomen, where it was usually the largest in the body Some of the sources were: 1. A strong and complicated reflex in the abdomen due to drinking cold water, suggesting that other dcMF reflexes might be common in the body. 2. Long muscle fibers in the limbs, suggesting sources also in scalp muscles. 3. Hair follicles due to touching the scalp; these sources could also exist, unrecognized, in recent dcMEG whole-head measurements. 4. Injury currents from the ischemic human heart, suggesting dcMFs could arise from injured muscle in the body generally. One major mechanism for producing dcMFs appeared to be a change in the potassium ion concentration in the vicinity of long excitable fibers. Overall, we concluded that the dcMFs were complicated, and it may be difficult to identify each source, especially in the head.

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.

The role of visual representations during the lexical access of spoken words

PubMed Central

Lewis, Gwyneth; Poeppel, David

2015-01-01

Do visual representations contribute to spoken word recognition? We examine, using MEG, the effects of sublexical and lexical variables at superior temporal (ST) areas and the posterior middle temporal gyrus (pMTG) compared with that of word imageability at visual cortices. Embodied accounts predict early modulation of visual areas by imageability - concurrently with or prior to modulation of pMTG by lexical variables. Participants responded to speech stimuli varying continuously in imageability during lexical decision with simultaneous MEG recording. We employed the linguistic variables in a new type of correlational time course analysis to assess trial-by-trial activation in occipital, ST, and pMTG regions of interest (ROIs). The linguistic variables modulated the ROIs during different time windows. Critically, visual regions reflected an imageability effect prior to effects of lexicality on pMTG. This surprising effect supports a view on which sensory aspects of a lexical item are not a consequence of lexical activation. PMID:24814579

The role of visual representations during the lexical access of spoken words.

PubMed

Lewis, Gwyneth; Poeppel, David

2014-07-01

Do visual representations contribute to spoken word recognition? We examine, using MEG, the effects of sublexical and lexical variables at superior temporal (ST) areas and the posterior middle temporal gyrus (pMTG) compared with that of word imageability at visual cortices. Embodied accounts predict early modulation of visual areas by imageability--concurrently with or prior to modulation of pMTG by lexical variables. Participants responded to speech stimuli varying continuously in imageability during lexical decision with simultaneous MEG recording. We employed the linguistic variables in a new type of correlational time course analysis to assess trial-by-trial activation in occipital, ST, and pMTG regions of interest (ROIs). The linguistic variables modulated the ROIs during different time windows. Critically, visual regions reflected an imageability effect prior to effects of lexicality on pMTG. This surprising effect supports a view on which sensory aspects of a lexical item are not a consequence of lexical activation. Copyright © 2014 Elsevier Inc. All rights reserved.

Independence of Early Speech Processing from Word Meaning

PubMed Central

Travis, Katherine E.; Leonard, Matthew K.; Chan, Alexander M.; Torres, Christina; Sizemore, Marisa L.; Qu, Zhe; Eskandar, Emad; Dale, Anders M.; Elman, Jeffrey L.; Cash, Sydney S.; Halgren, Eric

2013-01-01

We combined magnetoencephalography (MEG) with magnetic resonance imaging and electrocorticography to separate in anatomy and latency 2 fundamental stages underlying speech comprehension. The first acoustic-phonetic stage is selective for words relative to control stimuli individually matched on acoustic properties. It begins ∼60 ms after stimulus onset and is localized to middle superior temporal cortex. It was replicated in another experiment, but is strongly dissociated from the response to tones in the same subjects. Within the same task, semantic priming of the same words by a related picture modulates cortical processing in a broader network, but this does not begin until ∼217 ms. The earlier onset of acoustic-phonetic processing compared with lexico-semantic modulation was significant in each individual subject. The MEG source estimates were confirmed with intracranial local field potential and high gamma power responses acquired in 2 additional subjects performing the same task. These recordings further identified sites within superior temporal cortex that responded only to the acoustic-phonetic contrast at short latencies, or the lexico-semantic at long. The independence of the early acoustic-phonetic response from semantic context suggests a limited role for lexical feedback in early speech perception. PMID:22875868

Optimal Measurement Conditions for Spatiotemporal EEG/MEG Source Analysis.

ERIC Educational Resources Information Center

Huizenga, Hilde M.; Heslenfeld, Dirk J.; Molenaar, Peter C. M.

2002-01-01

Developed a method to determine the required number and position of sensors for human brain electromagnetic source analysis. Studied the method through a simulation study and an empirical study on visual evoked potentials in one adult male. Results indicate the method is fast and reliable and improves source precision. (SLD)

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.

The role of biomarkers and MEG-based imaging markers in the diagnosis of post-traumatic stress disorder and blast-induced mild traumatic brain injury.

PubMed

Huang, Mingxiong; Risling, Mårten; Baker, Dewleen G

2016-01-01

Pervasive use of improvised explosive devices (IEDs), rocket-propelled grenades, and land mines in the recent conflicts in Iraq and Afghanistan has brought traumatic brain injury (TBI) and its impact on health outcomes into public awareness. Blast injuries have been deemed signature wounds of these wars. War-related TBI is not new, having become prevalent during WWI and remaining medically relevant in WWII and beyond. Medicine's past attempts to accurately diagnose and disentangle the pathophysiology of war-related TBI parallels current lines of inquiry and highlights limitations in methodology and attribution of symptom etiology, be it organic, psychological, or behavioral. New approaches and biomarkers are needed. Serological biomarkers and biomarkers of injury obtained with imaging techniques represent cornerstones in the translation between experimental data and clinical observations. Experimental models for blast related TBI and PTSD can generate critical data on injury threshold, for example for white matter injury from acceleration. Carefully verified and validated models can be evaluated with gene expression arrays and proteomics to identify new candidates for serological biomarkers. Such models can also be analyzed with diffusion MRI and microscopy in order to identify criteria for detection of diffuse white matter injuries, such as DAI (diffuse axonal injury). The experimental models can also be analyzed with focus on injury outcome in brain stem regions, such as locus coeruleus or nucleus raphe magnus that can be involved in response to anxiety changes. Mild (and some moderate) TBI can be difficult to diagnose because the injuries are often not detectable on conventional MRI or CT. There is accumulating evidence that injured brain tissues in TBI patients generate abnormal low-frequency magnetic activity (ALFMA, peaked at 1-4Hz) that can be measured and localized by magnetoencephalography (MEG). MEG imaging detects TBI abnormalities at the rates of 87% for the mild TBI, group (blast-induced plus non-blast causes) and 100% for the moderate group. Among the mild TBI patients, the rates of abnormalities are 96% and 77% for the blast and non-blast TBI groups, respectively. There is emerging evidence based on fMRI and MEG studies showing hyper-activity in the amygdala and hypo-activity in pre-frontal cortex in individuals with PTSD. MEG signal may serve as a sensitive imaging marker for mTBI, distinguishable from abnormalities generated in association with PTSD. More work is needed to fully describe physiological mechanisms of post-concussive symptoms. Published by Elsevier Ltd.

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

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.

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

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.

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.

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

Measurement of the radiative decay of polarized muons in the MEG experiment

DOE PAGES

Baldini, A. M.; Bao, Y.; Baracchini, E.; ...

2016-02-29

Here, we studied the radiative muon decay μ + → e +νν¯γ by using for the first time an almost fully polarized muon source. We identified a large sample (~13,000) of these decays in a total sample of 1.8×10 14 positive muon decays collected in the MEG experiment in the years 2009–2010 and measured the branching ratio B(μ → eνν¯γ)=(6.03 ± 0.14(stat.) ± 0.53(sys.))×10 –8 for E e > 45 MeV and E γ > 40 MeV, consistent with the Standard Model prediction. The precise measurement of this decay mode provides a basic tool for the timing calibration, a normalizationmore » channel, and a strong quality check of the complete MEG experiment in the search for μ+→e+γ process.« less

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.

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.

Harmony: EEG/MEG Linear Inverse Source Reconstruction in the Anatomical Basis of Spherical Harmonics

PubMed Central

Petrov, Yury

2012-01-01

EEG/MEG source localization based on a “distributed solution” is severely underdetermined, because the number of sources is much larger than the number of measurements. In particular, this makes the solution strongly affected by sensor noise. A new way to constrain the problem is presented. By using the anatomical basis of spherical harmonics (or spherical splines) instead of single dipoles the dimensionality of the inverse solution is greatly reduced without sacrificing the quality of the data fit. The smoothness of the resulting solution reduces the surface bias and scatter of the sources (incoherency) compared to the popular minimum-norm algorithms where single-dipole basis is used (MNE, depth-weighted MNE, dSPM, sLORETA, LORETA, IBF) and allows to efficiently reduce the effect of sensor noise. This approach, termed Harmony, performed well when applied to experimental data (two exemplars of early evoked potentials) and showed better localization precision and solution coherence than the other tested algorithms when applied to realistically simulated data. PMID:23071497

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.

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

Morphological and Compositional (S)TEM Analysis of Multiple Exciton Generation Solar Cells

NASA Astrophysics Data System (ADS)

Wisnivesky-Rocca-Rivarola, F.; Davis, N. J. L. K.; Bohm, M.; Ducati, C.

2015-10-01

Quantum confinement of charge carriers in semiconductor nanocrystals produces optical and electronic properties that have the potential to enhance the power conversion efficiency of solar cells. One of these properties is the efficient formation of more than one electron-hole pair from a single absorbed photon, in a process called multiple exciton generation (MEG). In this work we studied the morphology of nanocrystal multilayers of PbSe treated with CdCl2 using complementary imaging and spectroscopy techniques to characterise the chemical composition and morphology of full MEG devices made with PbSe nanorods (NRs). IN the scanning TEM (STEM), plan view images and chemical maps were obtained of the nanocrystal layers, which allowed for the analysis of crystal structure and orientation, as well as size distribution and aspect ratio. These results were complemented by cross-sectional images of full devices, which allowed accessing the structure of each layer that composes the device, including the nanorod packing in the active nanocrystal layer.

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.

Fast Room Temperature Very Low Field-Magnetic Resonance Imaging System Compatible with MagnetoEncephaloGraphy Environment

PubMed Central

Galante, Angelo; Sinibaldi, Raffaele; Conti, Allegra; De Luca, Cinzia; Catallo, Nadia; Sebastiani, Piero; Pizzella, Vittorio; Romani, Gian Luca; Sotgiu, Antonello; Della Penna, Stefania

2015-01-01

In recent years, ultra-low field (ULF)-MRI is being given more and more attention, due to the possibility of integrating ULF-MRI and Magnetoencephalography (MEG) in the same device. Despite the signal-to-noise ratio (SNR) reduction, there are several advantages to operating at ULF, including increased tissue contrast, reduced cost and weight of the scanners, the potential to image patients that are not compatible with clinical scanners, and the opportunity to integrate different imaging modalities. The majority of ULF-MRI systems are based, until now, on magnetic field pulsed techniques for increasing SNR, using SQUID based detectors with Larmor frequencies in the kHz range. Although promising results were recently obtained with such systems, it is an open question whether similar SNR and reduced acquisition time can be achieved with simpler devices. In this work a room-temperature, MEG-compatible very-low field (VLF)-MRI device working in the range of several hundred kHz without sample pre-polarization is presented. This preserves many advantages of ULF-MRI, but for equivalent imaging conditions and SNR we achieve reduced imaging time based on preliminary results using phantoms and ex-vivo rabbits heads. PMID:26630172

Early Parallel Activation of Semantics and Phonology in Picture Naming: Evidence from a Multiple Linear Regression MEG Study

PubMed Central

Miozzo, Michele; Pulvermüller, Friedemann; Hauk, Olaf

2015-01-01

The time course of brain activation during word production has become an area of increasingly intense investigation in cognitive neuroscience. The predominant view has been that semantic and phonological processes are activated sequentially, at about 150 and 200–400 ms after picture onset. Although evidence from prior studies has been interpreted as supporting this view, these studies were arguably not ideally suited to detect early brain activation of semantic and phonological processes. We here used a multiple linear regression approach to magnetoencephalography (MEG) analysis of picture naming in order to investigate early effects of variables specifically related to visual, semantic, and phonological processing. This was combined with distributed minimum-norm source estimation and region-of-interest analysis. Brain activation associated with visual image complexity appeared in occipital cortex at about 100 ms after picture presentation onset. At about 150 ms, semantic variables became physiologically manifest in left frontotemporal regions. In the same latency range, we found an effect of phonological variables in the left middle temporal gyrus. Our results demonstrate that multiple linear regression analysis is sensitive to early effects of multiple psycholinguistic variables in picture naming. Crucially, our results suggest that access to phonological information might begin in parallel with semantic processing around 150 ms after picture onset. PMID:25005037

Optimized Geometry for Superconducting Sensing Coils

NASA Technical Reports Server (NTRS)

Eom, Byeong Ho; Pananen, Konstantin; Hahn, Inseob

2008-01-01

An optimized geometry has been proposed for superconducting sensing coils that are used in conjunction with superconducting quantum interference devices (SQUIDs) in magnetic resonance imaging (MRI), magnetoencephalography (MEG), and related applications in which magnetic fields of small dipoles are detected. In designing a coil of this type, as in designing other sensing coils, one seeks to maximize the sensitivity of the detector of which the coil is a part, subject to geometric constraints arising from the proximity of other required equipment. In MRI or MEG, the main benefit of maximizing the sensitivity would be to enable minimization of measurement time. In general, to maximize the sensitivity of a detector based on a sensing coil coupled with a SQUID sensor, it is necessary to maximize the magnetic flux enclosed by the sensing coil while minimizing the self-inductance of this coil. Simply making the coil larger may increase its self-inductance and does not necessarily increase sensitivity because it also effectively increases the distance from the sample that contains the source of the signal that one seeks to detect. Additional constraints on the size and shape of the coil and on the distance from the sample arise from the fact that the sample is at room temperature but the coil and the SQUID sensor must be enclosed within a cryogenic shield to maintain superconductivity.

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.

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.

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

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

Aging changes and gender differences in response to median nerve stimulation measured with MEG.

PubMed

Stephen, Julia M; Ranken, Doug; Best, Elaine; Adair, John; Knoefel, Janice; Kovacevic, Sanja; Padilla, Denise; Hart, Blaine; Aine, Cheryl J

2006-01-01

The current study uses magnetoencephalography (MEG) to characterize age-related changes and gender differences in the amplitudes and timing of cortical sources evoked by median nerve stimulation. Thirty-four healthy subjects from two age groups: 20-29 and >64 years of age were examined. After measuring the MEG responses, we modeled the data using a spatio-temporal multi-dipole modeling approach to determine the source locations and their associated timecourses. We found early, large amplitude responses in the elderly in primary somatosensory (approximately 20 ms) and pre-central sulcus timecourses (approximately 22 ms) and lower amplitude responses in the elderly later in primary somatosensory (approximately 32 ms) and contralateral secondary somatosensory timecourses (approximately 90 ms). In addition, females had larger peak amplitude responses than males in the contralateral secondary somatosensory timecourse (approximately 28 and 51 ms). These results show that the median nerve stimulation paradigm provides considerable sensitivity to age- and gender-related differences. The results are consistent with the theory that increased amplitudes identified in the elderly may be associated with decreased inhibition. The results emphasize that an examination of two discrete age groups, collapsed across gender, cannot provide a complete understanding of the fundamental changes that occur in the brain across the lifetime.

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.

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

Development of a bio-magnetic measurement system and sensor configuration analysis for rats

NASA Astrophysics Data System (ADS)

Kim, Ji-Eun; Kim, In-Seon; Kim, Kiwoong; Lim, Sanghyun; Kwon, Hyukchan; Kang, Chan Seok; Ahn, San; Yu, Kwon Kyu; Lee, Yong-Ho

2017-04-01

Magnetoencephalography (MEG) based on superconducting quantum interference devices enables the measurement of very weak magnetic fields (10-1000 fT) generated from the human or animal brain. In this article, we introduce a small MEG system that we developed specifically for use with rats. Our system has the following characteristics: (1) variable distance between the pick-up coil and outer Dewar bottom (˜5 mm), (2) small pick-up coil (4 mm) for high spatial resolution, (3) good field sensitivity (45 ˜ 80 fT /cm/√{Hz} ) , (4) the sensor interval satisfies the Nyquist spatial sampling theorem, and (5) small source localization error for the region to be investigated. To reduce source localization error, it is necessary to establish an optimal sensor layout. To this end, we simulated confidence volumes at each point on a grid on the surface of a virtual rat head. In this simulation, we used locally fitted spheres as model rat heads. This enabled us to consider more realistic volume currents. We constrained the model such that the dipoles could have only four possible orientations: the x- and y-axes from the original coordinates, and two tangentially layered dipoles (local x- and y-axes) in the locally fitted spheres. We considered the confidence volumes according to the sensor layout and dipole orientation and positions. We then conducted a preliminary test with a 4-channel MEG system prior to manufacturing the multi-channel system. Using the 4-channel MEG system, we measured rat magnetocardiograms. We obtained well defined P-, QRS-, and T-waves in rats with a maximum value of 15 pT/cm. Finally, we measured auditory evoked fields and steady state auditory evoked fields with maximum values 400 fT/cm and 250 fT/cm, respectively.

Automated model selection in covariance estimation and spatial whitening of MEG and EEG signals.

PubMed

Engemann, Denis A; Gramfort, Alexandre

2015-03-01

Magnetoencephalography and electroencephalography (M/EEG) measure non-invasively the weak electromagnetic fields induced by post-synaptic neural currents. The estimation of the spatial covariance of the signals recorded on M/EEG sensors is a building block of modern data analysis pipelines. Such covariance estimates are used in brain-computer interfaces (BCI) systems, in nearly all source localization methods for spatial whitening as well as for data covariance estimation in beamformers. The rationale for such models is that the signals can be modeled by a zero mean Gaussian distribution. While maximizing the Gaussian likelihood seems natural, it leads to a covariance estimate known as empirical covariance (EC). It turns out that the EC is a poor estimate of the true covariance when the number of samples is small. To address this issue the estimation needs to be regularized. The most common approach downweights off-diagonal coefficients, while more advanced regularization methods are based on shrinkage techniques or generative models with low rank assumptions: probabilistic PCA (PPCA) and factor analysis (FA). Using cross-validation all of these models can be tuned and compared based on Gaussian likelihood computed on unseen data. We investigated these models on simulations, one electroencephalography (EEG) dataset as well as magnetoencephalography (MEG) datasets from the most common MEG systems. First, our results demonstrate that different models can be the best, depending on the number of samples, heterogeneity of sensor types and noise properties. Second, we show that the models tuned by cross-validation are superior to models with hand-selected regularization. Hence, we propose an automated solution to the often overlooked problem of covariance estimation of M/EEG signals. The relevance of the procedure is demonstrated here for spatial whitening and source localization of MEG signals. Copyright © 2015 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.

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.

Online and offline tools for head movement compensation in MEG.

PubMed

Stolk, Arjen; Todorovic, Ana; Schoffelen, Jan-Mathijs; Oostenveld, Robert

2013-03-01

Magnetoencephalography (MEG) is measured above the head, which makes it sensitive to variations of the head position with respect to the sensors. Head movements blur the topography of the neuronal sources of the MEG signal, increase localization errors, and reduce statistical sensitivity. Here we describe two novel and readily applicable methods that compensate for the detrimental effects of head motion on the statistical sensitivity of MEG experiments. First, we introduce an online procedure that continuously monitors head position. Second, we describe an offline analysis method that takes into account the head position time-series. We quantify the performance of these methods in the context of three different experimental settings, involving somatosensory, visual and auditory stimuli, assessing both individual and group-level statistics. The online head localization procedure allowed for optimal repositioning of the subjects over multiple sessions, resulting in a 28% reduction of the variance in dipole position and an improvement of up to 15% in statistical sensitivity. Offline incorporation of the head position time-series into the general linear model resulted in improvements of group-level statistical sensitivity between 15% and 29%. These tools can substantially reduce the influence of head movement within and between sessions, increasing the sensitivity of many cognitive neuroscience experiments. Copyright © 2012 Elsevier Inc. All rights reserved.

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.

Categorical discrimination of human body parts by magnetoencephalography

PubMed Central

Nakamura, Misaki; Yanagisawa, Takufumi; Okamura, Yumiko; Fukuma, Ryohei; Hirata, Masayuki; Araki, Toshihiko; Kamitani, Yukiyasu; Yorifuji, Shiro

2015-01-01

Humans recognize body parts in categories. Previous studies have shown that responses in the fusiform body area (FBA) and extrastriate body area (EBA) are evoked by the perception of the human body, when presented either as whole or as isolated parts. These responses occur approximately 190 ms after body images are visualized. The extent to which body-sensitive responses show specificity for different body part categories remains to be largely clarified. We used a decoding method to quantify neural responses associated with the perception of different categories of body parts. Nine subjects underwent measurements of their brain activities by magnetoencephalography (MEG) while viewing 14 images of feet, hands, mouths, and objects. We decoded categories of the presented images from the MEG signals using a support vector machine (SVM) and calculated their accuracy by 10-fold cross-validation. For each subject, a response that appeared to be a body-sensitive response was observed and the MEG signals corresponding to the three types of body categories were classified based on the signals in the occipitotemporal cortex. The accuracy in decoding body-part categories (with a peak at approximately 48%) was above chance (33.3%) and significantly higher than that for random categories. According to the time course and location, the responses are suggested to be body-sensitive and to include information regarding the body-part category. Finally, this non-invasive method can decode category information of a visual object with high temporal and spatial resolution and this result may have a significant impact in the field of brain–machine interface research. PMID:26582986

Categorical discrimination of human body parts by magnetoencephalography.

PubMed

Nakamura, Misaki; Yanagisawa, Takufumi; Okamura, Yumiko; Fukuma, Ryohei; Hirata, Masayuki; Araki, Toshihiko; Kamitani, Yukiyasu; Yorifuji, Shiro

2015-01-01

Humans recognize body parts in categories. Previous studies have shown that responses in the fusiform body area (FBA) and extrastriate body area (EBA) are evoked by the perception of the human body, when presented either as whole or as isolated parts. These responses occur approximately 190 ms after body images are visualized. The extent to which body-sensitive responses show specificity for different body part categories remains to be largely clarified. We used a decoding method to quantify neural responses associated with the perception of different categories of body parts. Nine subjects underwent measurements of their brain activities by magnetoencephalography (MEG) while viewing 14 images of feet, hands, mouths, and objects. We decoded categories of the presented images from the MEG signals using a support vector machine (SVM) and calculated their accuracy by 10-fold cross-validation. For each subject, a response that appeared to be a body-sensitive response was observed and the MEG signals corresponding to the three types of body categories were classified based on the signals in the occipitotemporal cortex. The accuracy in decoding body-part categories (with a peak at approximately 48%) was above chance (33.3%) and significantly higher than that for random categories. According to the time course and location, the responses are suggested to be body-sensitive and to include information regarding the body-part category. Finally, this non-invasive method can decode category information of a visual object with high temporal and spatial resolution and this result may have a significant impact in the field of brain-machine interface research.

Current use of imaging and electromagnetic source localization procedures in epilepsy surgery centers across Europe.

PubMed

Mouthaan, Brian E; Rados, Matea; Barsi, Péter; Boon, Paul; Carmichael, David W; Carrette, Evelien; Craiu, Dana; Cross, J Helen; Diehl, Beate; Dimova, Petia; Fabo, Daniel; Francione, Stefano; Gaskin, Vladislav; Gil-Nagel, Antonio; Grigoreva, Elena; Guekht, Alla; Hirsch, Edouard; Hecimovic, Hrvoje; Helmstaedter, Christoph; Jung, Julien; Kalviainen, Reetta; Kelemen, Anna; Kimiskidis, Vasilios; Kobulashvili, Teia; Krsek, Pavel; Kuchukhidze, Giorgi; Larsson, Pål G; Leitinger, Markus; Lossius, Morten I; Luzin, Roman; Malmgren, Kristina; Mameniskiene, Ruta; Marusic, Petr; Metin, Baris; Özkara, Cigdem; Pecina, Hrvoje; Quesada, Carlos M; Rugg-Gunn, Fergus; Rydenhag, Bertil; Ryvlin, Philippe; Scholly, Julia; Seeck, Margitta; Staack, Anke M; Steinhoff, Bernhard J; Stepanov, Valentin; Tarta-Arsene, Oana; Trinka, Eugen; Uzan, Mustafa; Vogt, Viola L; Vos, Sjoerd B; Vulliémoz, Serge; Huiskamp, Geertjan; Leijten, Frans S S; Van Eijsden, Pieter; Braun, Kees P J

2016-05-01

In 2014 the European Union-funded E-PILEPSY project was launched to improve awareness of, and accessibility to, epilepsy surgery across Europe. We aimed to investigate the current use of neuroimaging, electromagnetic source localization, and imaging postprocessing procedures in participating centers. A survey on the clinical use of imaging, electromagnetic source localization, and postprocessing methods in epilepsy surgery candidates was distributed among the 25 centers of the consortium. A descriptive analysis was performed, and results were compared to existing guidelines and recommendations. Response rate was 96%. Standard epilepsy magnetic resonance imaging (MRI) protocols are acquired at 3 Tesla by 15 centers and at 1.5 Tesla by 9 centers. Three centers perform 3T MRI only if indicated. Twenty-six different MRI sequences were reported. Six centers follow all guideline-recommended MRI sequences with the proposed slice orientation and slice thickness or voxel size. Additional sequences are used by 22 centers. MRI postprocessing methods are used in 16 centers. Interictal positron emission tomography (PET) is available in 22 centers; all using 18F-fluorodeoxyglucose (FDG). Seventeen centers perform PET postprocessing. Single-photon emission computed tomography (SPECT) is used by 19 centers, of which 15 perform postprocessing. Four centers perform neither PET nor SPECT in children. Seven centers apply magnetoencephalography (MEG) source localization, and nine apply electroencephalography (EEG) source localization. Fourteen combinations of inverse methods and volume conduction models are used. We report a large variation in the presurgical diagnostic workup among epilepsy surgery centers across Europe. This diversity underscores the need for high-quality systematic reviews, evidence-based recommendations, and harmonization of available diagnostic presurgical methods. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

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

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.

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.

Digestion, milk production, milk composition, and blood composition of dairy cows fed whole flaxseed.

PubMed

Petit, Helene V

2002-06-01

A total of 90 lactating Holstein cows averaging 628 kg (SE = 8) of body weight (BW) were allotted at calving to 30 groups of three cows blocked for similar calving dates to determine the effects of feeding whole untreated flaxseed on milk production and composition, fatty acid composition of blood and milk, and digestibility, and to determine whether flaxseed could substitute for other sources of fat such as Megalac and micronized soybeans. Cows were fed a total mixed diet based on grass and corn silage and fat supplements for ad libitum intake. The experiment was carried out from calving up to wk 16 of lactation. Cows within each block were assigned to one of the three isonitrogenous, isoenergetic, and isolipidic supplements based on either whole flaxseed (FLA), Megalac (MEG), or micronized soybeans (SOY). Intake of dry matter and change in BW were similar among diets. Cows fed FLA had greater milk yield than those fed MEG (35.7 vs. 33.5 kg/d) and there was no difference between cows fed FLA and those fed SOY (34.4 kg/d). Fat percentage was higher in the milk of cows fed MEG (4.14%) than in the milk of those fed FLA (3.81%) or SOY (3.70%), but milk protein percentage was higher for cows fed FLA (2.98%) than for those fed MEG (2.86%) and SOY (2.87%). Digestibilities of acid detergent fiber, neutral detergent fiber, and ether extract were lower for cows fed FLA than for those fed SOY and MEG. Retention of N was similar among diets. Feeding FLA resulted in the lowest omega-6-to-omega-3-fatty-acids ratio, which would improve the nutritive value of milk from a human health point of view. The data suggest that micronized soybeans and Megalac can be completely substituted by whole untreated flaxseed as the fat source in the diet of early lactating cows without any adverse effect on production and that flaxseed increased milk protein percentage and its omega-6-to-omega-3-fatty-acids ratio.

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.

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.

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.

Preliminary differences in resting state MEG functional connectivity pre- and post-ketamine in major depressive disorder.

PubMed

Nugent, Allison C; Robinson, Stephen E; Coppola, Richard; Zarate, Carlos A

2016-08-30

Functional neuroimaging techniques including magnetoencephalography (MEG) have demonstrated that the brain is organized into networks displaying correlated activity. Group connectivity differences between healthy controls and participants with major depressive disorder (MDD) can be detected using temporal independent components analysis (ICA) on beta-bandpass filtered Hilbert envelope MEG data. However, the response of these networks to treatment is unknown. Ketamine, an N-methyl-D-aspartate (NMDA) receptor antagonist, exerts rapid antidepressant effects. We obtained MEG recordings before and after open-label infusion of 0.5mg/kg ketamine in MDD subjects (N=13) and examined networks previously shown to differ between healthy individuals and those with MDD. Connectivity between the amygdala and an insulo-temporal component decreased post-ketamine in MDD subjects towards that observed in control subjects at baseline. Decreased baseline connectivity of the subgenual anterior cingulate cortex (sgACC) with a bilateral precentral network had previously been observed in MDD compared to healthy controls, and the change in connectivity post-ketamine was proportional to the change in sgACC glucose metabolism in a subset (N=8) of subjects receiving [11F]FDG-PET imaging. Ketamine appeared to reduce connectivity, regardless of whether connectivity was abnormally high or low compared to controls at baseline. These preliminary findings suggest that sgACC connectivity may be directly related to glutamate levels. Published by Elsevier Ireland Ltd.

tDCS Modulates Visual Gamma Oscillations and Basal Alpha Activity in Occipital Cortices: Evidence from MEG.

PubMed

Wilson, Tony W; McDermott, Timothy J; Mills, Mackenzie S; Coolidge, Nathan M; Heinrichs-Graham, Elizabeth

2018-05-01

Transcranial direct-current stimulation (tDCS) is now a widely used method for modulating the human brain, but the resulting physiological effects are not understood. Recent studies have combined magnetoencephalography (MEG) with simultaneous tDCS to evaluate online changes in occipital alpha and gamma oscillations, but no study to date has quantified the offline (i.e., after tDCS) alterations in these responses. Thirty-five healthy adults received active or sham anodal tDCS to the occipital cortices, and then completed a visual stimulation paradigm during MEG that is known to elicit robust gamma and alpha oscillations. The resulting MEG data were imaged and peak voxel time series were extracted to evaluate tDCS effects. We found that tDCS to the occipital increased the amplitude of local gamma oscillations, and basal alpha levels during the baseline. tDCS was also associated with network-level effects, including increased gamma oscillations in the prefrontal cortex, parietal, and other visual attention regions. Finally, although tDCS did not modulate peak gamma frequency, this variable was inversely correlated with gamma amplitude, which is consistent with a GABA-gamma link. In conclusion, tDCS alters gamma oscillations and basal alpha levels. The net offline effects on gamma activity are consistent with the view that anodal tDCS decreases local GABA.

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

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

Magnetoencephalography with temporal spread imaging to visualize propagation of epileptic activity.

PubMed

Shibata, Sumiya; Matsuhashi, Masao; Kunieda, Takeharu; Yamao, Yukihiro; Inano, Rika; Kikuchi, Takayuki; Imamura, Hisaji; Takaya, Shigetoshi; Matsumoto, Riki; Ikeda, Akio; Takahashi, Ryosuke; Mima, Tatsuya; Fukuyama, Hidenao; Mikuni, Nobuhiro; Miyamoto, Susumu

2017-05-01

We describe temporal spread imaging (TSI) that can identify the spatiotemporal pattern of epileptic activity using Magnetoencephalography (MEG). A three-dimensional grid of voxels covering the brain is created. The array-gain minimum-variance spatial filter is applied to an interictal spike to estimate the magnitude of the source and the time (Ta) when the magnitude exceeds a predefined threshold at each voxel. This calculation is performed through all spikes. Each voxel has the mean Ta () and spike number (N sp ), which is the number of spikes whose source exceeds the threshold. Then, a random resampling method is used to determine the cutoff value of N sp for the statistically reproducible pattern of the activity. Finally, all the voxels where the source exceeds the threshold reproducibly shown on the MRI with a color scale representing . Four patients with intractable mesial temporal lobe epilepsy (MTLE) were analyzed. In three patients, the common pattern of the overlap between the propagation and the hypometabolism shown by fluorodeoxyglucose-positron emission tomography (FDG-PET) was identified. TSI can visualize statistically reproducible patterns of the temporal and spatial spread of epileptic activity. TSI can assess the statistical significance of the spatiotemporal pattern based on its reproducibility. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Reducing Sensor Noise in MEG and EEG Recordings Using Oversampled Temporal Projection.

PubMed

Larson, Eric; Taulu, Samu

2018-05-01

Here, we review the theory of suppression of spatially uncorrelated, sensor-specific noise in electro- and magentoencephalography (EEG and MEG) arrays, and introduce a novel method for suppression. Our method requires only that the signals of interest are spatially oversampled, which is a reasonable assumption for many EEG and MEG systems. Our method is based on a leave-one-out procedure using overlapping temporal windows in a mathematical framework to project spatially uncorrelated noise in the temporal domain. This method, termed "oversampled temporal projection" (OTP), has four advantages over existing methods. First, sparse channel-specific artifacts are suppressed while limiting mixing with other channels, whereas existing linear, time-invariant spatial operators can spread such artifacts to other channels with a spatial distribution which can be mistaken for one produced by an electrophysiological source. Second, OTP minimizes distortion of the spatial configuration of the data. During source localization (e.g., dipole fitting), many spatial methods require corresponding modification of the forward model to avoid bias, while OTP does not. Third, noise suppression factors at the sensor level are maintained during source localization, whereas bias compensation removes the denoising benefit for spatial methods that require such compensation. Fourth, OTP uses a time-window duration parameter to control the tradeoff between noise suppression and adaptation to time-varying sensor characteristics. OTP efficiently optimizes noise suppression performance while controlling for spatial bias of the signal of interest. This is important in applications where sensor noise significantly limits the signal-to-noise ratio, such as high-frequency brain oscillations.

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.

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.

Similarities and differences between on-scalp and conventional in-helmet magnetoencephalography recordings

PubMed Central

Pfeiffer, Christoph; Ruffieux, Silvia; Jousmäki, Veikko; Hämäläinen, Matti; Schneiderman, Justin F.; Lundqvist, Daniel

2017-01-01

The development of new magnetic sensor technologies that promise sensitivities approaching that of conventional MEG technology while operating at far lower operating temperatures has catalysed the growing field of on-scalp MEG. The feasibility of on-scalp MEG has been demonstrated via benchmarking of new sensor technologies performing neuromagnetic recordings in close proximity to the head surface against state-of-the-art in-helmet MEG sensor technology. However, earlier work has provided little information about how these two approaches compare, or about the reliability of observed differences. Herein, we present such a comparison, based on recordings of the N20m component of the somatosensory evoked field as elicited by electric median nerve stimulation. As expected from the proximity differences between the on-scalp and in-helmet sensors, the magnitude of the N20m activation as recorded with the on-scalp sensor was higher than that of the in-helmet sensors. The dipole pattern of the on-scalp recordings was also more spatially confined than that of the conventional recordings. Our results furthermore revealed unexpected temporal differences in the peak of the N20m component. An analysis protocol was therefore developed for assessing the reliability of this observed difference. We used this protocol to examine our findings in terms of differences in sensor sensitivity between the two types of MEG recordings. The measurements and subsequent analysis raised attention to the fact that great care has to be taken in measuring the field close to the zero-line crossing of the dipolar field, since it is heavily dependent on the orientation of sensors. Taken together, our findings provide reliable evidence that on-scalp and in-helmet sensors measure neural sources in mostly similar ways. PMID:28742118

Whole-Brain Source-Reconstructed MEG-Data Reveal Reduced Long-Range Synchronization in Chronic Schizophrenia.

PubMed

Hirvonen, Jonni; Wibral, Michael; Palva, J Matias; Singer, Wolf; Uhlhaas, Peter; Palva, Satu

2017-01-01

Current theories of schizophrenia (ScZ) posit that the symptoms and cognitive dysfunctions arise from a dysconnection syndrome. However, studies that have examined this hypothesis with physiological data at realistic time scales are so far scarce. The current study employed a state-of-the-art approach using Magnetoencephalography (MEG) to test alterations in large-scale phase synchronization in a sample of n = 16 chronic ScZ patients, 10 males and n = 19 healthy participants, 10 males, during a perceptual closure task. We identified large-scale networks from source reconstructed MEG data using data-driven analyses of neuronal synchronization. Oscillation amplitudes and interareal phase-synchronization in the 3-120 Hz frequency range were estimated for 400 cortical parcels and correlated with clinical symptoms and neuropsychological scores. ScZ patients were characterized by a reduction in γ-band (30-120 Hz) oscillation amplitudes that was accompanied by a pronounced deficit in large-scale synchronization at γ-band frequencies. Synchronization was reduced within visual regions as well as between visual and frontal cortex and the reduction of synchronization correlated with elevated clinical disorganization. Accordingly, these data highlight that ScZ is associated with a profound disruption of transient synchronization, providing critical support for the notion that core aspect of the pathophysiology arises from an impairment in coordination of distributed neural activity.

Whole-Brain Source-Reconstructed MEG-Data Reveal Reduced Long-Range Synchronization in Chronic Schizophrenia

PubMed Central

Hirvonen, Jonni; Palva, J. Matias; Singer, Wolf; Uhlhaas, Peter

2017-01-01

Abstract Current theories of schizophrenia (ScZ) posit that the symptoms and cognitive dysfunctions arise from a dysconnection syndrome. However, studies that have examined this hypothesis with physiological data at realistic time scales are so far scarce. The current study employed a state-of-the-art approach using Magnetoencephalography (MEG) to test alterations in large-scale phase synchronization in a sample of n = 16 chronic ScZ patients, 10 males and n = 19 healthy participants, 10 males, during a perceptual closure task. We identified large-scale networks from source reconstructed MEG data using data-driven analyses of neuronal synchronization. Oscillation amplitudes and interareal phase-synchronization in the 3–120 Hz frequency range were estimated for 400 cortical parcels and correlated with clinical symptoms and neuropsychological scores. ScZ patients were characterized by a reduction in γ-band (30–120 Hz) oscillation amplitudes that was accompanied by a pronounced deficit in large-scale synchronization at γ-band frequencies. Synchronization was reduced within visual regions as well as between visual and frontal cortex and the reduction of synchronization correlated with elevated clinical disorganization. Accordingly, these data highlight that ScZ is associated with a profound disruption of transient synchronization, providing critical support for the notion that core aspect of the pathophysiology arises from an impairment in coordination of distributed neural activity. PMID:29085902

Donders is dead: cortical traveling waves and the limits of mental chronometry in cognitive neuroscience.

PubMed

Alexander, David M; Trengove, Chris; van Leeuwen, Cees

2015-11-01

An assumption nearly all researchers in cognitive neuroscience tacitly adhere to is that of space-time separability. Historically, it forms the basis of Donders' difference method, and to date, it underwrites all difference imaging and trial-averaging of cortical activity, including the customary techniques for analyzing fMRI and EEG/MEG data. We describe the assumption and how it licenses common methods in cognitive neuroscience; in particular, we show how it plays out in signal differencing and averaging, and how it misleads us into seeing the brain as a set of static activity sources. In fact, rather than being static, the domains of cortical activity change from moment to moment: Recent research has suggested the importance of traveling waves of activation in the cortex. Traveling waves have been described at a range of different spatial scales in the cortex; they explain a large proportion of the variance in phase measurements of EEG, MEG and ECoG, and are important for understanding cortical function. Critically, traveling waves are not space-time separable. Their prominence suggests that the correct frame of reference for analyzing cortical activity is the dynamical trajectory of the system, rather than the time and space coordinates of measurements. We illustrate what the failure of space-time separability implies for cortical activation, and what consequences this should have for cognitive neuroscience.

Recording Brain Electromagnetic Activity During the Administration of the Gaseous Anesthetic Agents Xenon and Nitrous Oxide in Healthy Volunteers.

PubMed

Pelentritou, Andria; Kuhlmann, Levin; Cormack, John; Woods, Will; Sleigh, Jamie; Liley, David

2018-01-13

Anesthesia arguably provides one of the only systematic ways to study the neural correlates of global consciousness/unconsciousness. However to date most neuroimaging or neurophysiological investigations in humans have been confined to the study of γ-Amino-Butyric-Acid-(GABA)-receptor-agonist-based anesthetics, while the effects of dissociative N-Methyl-D-Aspartate-(NMDA)-receptor-antagonist-based anesthetics ketamine, nitrous oxide (N2O) and xenon (Xe) are largely unknown. This paper describes the methods underlying the simultaneous recording of magnetoencephalography (MEG) and electroencephalography (EEG) from healthy males during inhalation of the gaseous anesthetic agents N2O and Xe. Combining MEG and EEG data enables the assessment of electromagnetic brain activity during anesthesia at high temporal, and moderate spatial, resolution. Here we describe a detailed protocol, refined over multiple recording sessions, that includes subject recruitment, anesthesia equipment setup in the MEG scanner room, data collection and basic data analysis. In this protocol each participant is exposed to varying levels of Xe and N2O in a repeated measures cross-over design. Following relevant baseline recordings participants are exposed to step-wise increasing inspired concentrations of Xe and N2O of 8, 16, 24 and 42%, and 16, 32 and 47% respectively, during which their level of responsiveness is tracked with an auditory continuous performance task (aCPT). Results are presented for a number of recordings to highlight the sensor-level properties of the raw data, the spectral topography, the minimization of head movements, and the unequivocal level dependent effects on the auditory evoked responses. This paradigm describes a general approach to the recording of electromagnetic signals associated with the action of different kinds of gaseous anesthetics, which can be readily adapted to be used with volatile and intravenous anesthetic agents. It is expected that the method outlined can contribute to the understanding of the macro-scale mechanisms of anesthesia by enabling methodological extensions involving source space imaging and functional network analysis.

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

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.

Bayesian analysis of multimodal data and brain imaging

NASA Astrophysics Data System (ADS)

Assadi, Amir H.; Eghbalnia, Hamid; Backonja, Miroslav; Wakai, Ronald T.; Rutecki, Paul; Haughton, Victor

2000-06-01

It is often the case that information about a process can be obtained using a variety of methods. Each method is employed because of specific advantages over the competing alternatives. An example in medical neuro-imaging is the choice between fMRI and MEG modes where fMRI can provide high spatial resolution in comparison to the superior temporal resolution of MEG. The combination of data from varying modes provides the opportunity to infer results that may not be possible by means of any one mode alone. We discuss a Bayesian and learning theoretic framework for enhanced feature extraction that is particularly suited to multi-modal investigations of massive data sets from multiple experiments. In the following Bayesian approach, acquired knowledge (information) regarding various aspects of the process are all directly incorporated into the formulation. This information can come from a variety of sources. In our case, it represents statistical information obtained from other modes of data collection. The information is used to train a learning machine to estimate a probability distribution, which is used in turn by a second machine as a prior, in order to produce a more refined estimation of the distribution of events. The computational demand of the algorithm is handled by proposing a distributed parallel implementation on a cluster of workstations that can be scaled to address real-time needs if required. We provide a simulation of these methods on a set of synthetically generated MEG and EEG data. We show how spatial and temporal resolutions improve by using prior distributions. The method on fMRI signals permits one to construct the probability distribution of the non-linear hemodynamics of the human brain (real data). These computational results are in agreement with biologically based measurements of other labs, as reported to us by researchers from UK. We also provide preliminary analysis involving multi-electrode cortical recording that accompanies behavioral data in pain experiments on freely moving mice subjected to moderate heat delivered by an electric bulb. Summary of new or breakthrough ideas: (1) A new method to estimate probability distribution for measurement of nonlinear hemodynamics of brain from a multi- modal neuronal data. This is the first time that such an idea is tried, to our knowledge. (2) Breakthrough in improvement of time resolution of fMRI signals using (1) above.

Spatio-temporal dynamics and laterality effects of face inversion, feature presence and configuration, and face outline

PubMed Central

Marinkovic, Ksenija; Courtney, Maureen G.; Witzel, Thomas; Dale, Anders M.; Halgren, Eric

2014-01-01

Although a crucial role of the fusiform gyrus (FG) in face processing has been demonstrated with a variety of methods, converging evidence suggests that face processing involves an interactive and overlapping processing cascade in distributed brain areas. Here we examine the spatio-temporal stages and their functional tuning to face inversion, presence and configuration of inner features, and face contour in healthy subjects during passive viewing. Anatomically-constrained magnetoencephalography (aMEG) combines high-density whole-head MEG recordings and distributed source modeling with high-resolution structural MRI. Each person's reconstructed cortical surface served to constrain noise-normalized minimum norm inverse source estimates. The earliest activity was estimated to the occipital cortex at ~100 ms after stimulus onset and was sensitive to an initial coarse level visual analysis. Activity in the right-lateralized ventral temporal area (inclusive of the FG) peaked at ~160 ms and was largest to inverted faces. Images containing facial features in the veridical and rearranged configuration irrespective of the facial outline elicited intermediate level activity. The M160 stage may provide structural representations necessary for downstream distributed areas to process identity and emotional expression. However, inverted faces additionally engaged the left ventral temporal area at ~180 ms and were uniquely subserved by bilateral processing. This observation is consistent with the dual route model and spared processing of inverted faces in prosopagnosia. The subsequent deflection, peaking at ~240 ms in the anterior temporal areas bilaterally, was largest to normal, upright faces. It may reflect initial engagement of the distributed network subserving individuation and familiarity. These results support dynamic models suggesting that processing of unfamiliar faces in the absence of a cognitive task is subserved by a distributed and interactive neural circuit. PMID:25426044

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.

The Application of Electro- and Magneto-Encephalography in Tinnitus Research – Methods and Interpretations

PubMed Central

Adjamian, Peyman

2014-01-01

In recent years, there has been a significant increase in the use of electroencephalography (EEG) and magnetoencephalography (MEG) to investigate changes in oscillatory brain activity associated with tinnitus with many conflicting results. Current view of the underlying mechanism of tinnitus is that it results from changes in brain activity in various structures of the brain as a consequence of sensory deprivation. This in turn gives rise to increased spontaneous activity and/or synchrony in the auditory centers but also involves modulation from non-auditory processes from structures of the limbic and paralimbic system. Some of the neural changes associated with tinnitus may be assessed non-invasively in human beings with MEG and EEG (M/EEG) in ways, which are superior to animal studies and other non-invasive imaging techniques. However, both MEG and EEG have their limitations and research results can be misinterpreted without appropriate consideration of these limitations. In this article, I intend to provide a brief review of these techniques, describe what the recorded signals reflect in terms of the underlying neural activity, and their strengths and limitations. I also discuss some pertinent methodological issues involved in tinnitus-related studies and conclude with suggestions to minimize possible discrepancies between results. The overall message is that while MEG and EEG are extremely useful techniques, the interpretation of results from tinnitus studies requires much caution given the individual variability in oscillatory activity and the limits of these techniques. PMID:25431567

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.

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

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

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.

Robotics in neurosurgery: which tools for what?

PubMed

Benabid, A L; Hoffmann, D; Seigneuret, E; Chabardes, S

2006-01-01

Robots are the tools for taking advantage of the skills of computers in achieving complicated tasks. This has been made possible owing to the "numerical image explosion" which allowed us to easily obtain spatial coordinates, three dimensional reconstruction, multimodality imaging including digital subtraction angiography (DSA), computed tomography (CT), magnetic resonance imaging (MRI) and magneto encephalography (MEG), with high resolution in space, time, and tissue density. Neurosurgical robots currently available at the operating level are being described. Future evolutions, indications and ethical aspects are examined.

Localization of extended brain sources from EEG/MEG: the ExSo-MUSIC approach.

PubMed

Birot, Gwénaël; Albera, Laurent; Wendling, Fabrice; Merlet, Isabelle

2011-05-01

We propose a new MUSIC-like method, called 2q-ExSo-MUSIC (q ≥ 1). This method is an extension of the 2q-MUSIC (q ≥ 1) approach for solving the EEG/MEG inverse problem, when spatially-extended neocortical sources ("ExSo") are considered. It introduces a novel ExSo-MUSIC principle. The novelty is two-fold: i) the parameterization of the spatial source distribution that leads to an appropriate metric in the context of distributed brain sources and ii) the introduction of an original, efficient and low-cost way of optimizing this metric. In 2q-ExSo-MUSIC, the possible use of higher order statistics (q ≥ 2) offers a better robustness with respect to Gaussian noise of unknown spatial coherence and modeling errors. As a result we reduced the penalizing effects of both the background cerebral activity that can be seen as a Gaussian and spatially correlated noise, and the modeling errors induced by the non-exact resolution of the forward problem. Computer results on simulated EEG signals obtained with physiologically-relevant models of both the sources and the volume conductor show a highly increased performance of our 2q-ExSo-MUSIC method as compared to the classical 2q-MUSIC algorithms. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

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

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

PubMed

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.

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.

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

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…

Absolute Power Spectral Density Changes in the Magnetoencephalographic Activity During the Transition from Childhood to Adulthood.

PubMed

Gómez, Carlos M; Rodríguez-Martínez, Elena I; Fernández, Alberto; Maestú, Fernando; Poza, Jesús; Gómez, Carlos

2017-01-01

The aim of this study was to define the pattern of reduction in absolute power spectral density (PSD) of magnetoencephalography (MEG) signals throughout development. Specifically, we wanted to explore whether the human skull's high permeability for electromagnetic fields would allow us to question whether the pattern of absolute PSD reduction observed in the human electroencephalogram is due to an increase in the skull's resistive properties with age. Furthermore, the topography of the MEG signals during maturation was explored, providing additional insights about the areas and brain rhythms related to late maturation in the human brain. To attain these goals, spontaneous MEG activity was recorded from 148 sensors in a sample of 59 subjects divided into three age groups: children/adolescents (7-14 years), young adults (17-20 years) and adults (21-26 years). Statistical testing was carried out by means of an analysis of variance (ANOVA), with "age group" as between-subject factor and "sensor group" as within-subject factor. Additionally, correlations of absolute PSD with age were computed to assess the influence of age on the spectral content of MEG signals. Results showed a broadband PSD decrease in frontal areas, which suggests the late maturation of this region, but also a mild increase in high frequency PSD with age in posterior areas. These findings suggest that the intensity of the neural sources during spontaneous brain activity decreases with age, which may be related to synaptic pruning.

Latency of modality-specific reactivation of auditory and visual information during episodic memory retrieval.

PubMed

Ueno, Daisuke; Masumoto, Kouhei; Sutani, Kouichi; Iwaki, Sunao

2015-04-15

This study used magnetoencephalography (MEG) to examine the latency of modality-specific reactivation in the visual and auditory cortices during a recognition task to determine the effects of reactivation on episodic memory retrieval. Nine right-handed healthy young adults participated in the experiment. The experiment consisted of a word-encoding phase and two recognition phases. Three encoding conditions were included: encoding words alone (word-only) and encoding words presented with either related pictures (visual) or related sounds (auditory). The recognition task was conducted in the MEG scanner 15 min after the completion of the encoding phase. After the recognition test, a source-recognition task was given, in which participants were required to choose whether each recognition word was not presented or was presented with which information during the encoding phase. Word recognition in the auditory condition was higher than that in the word-only condition. Confidence-of-recognition scores (d') and the source-recognition test showed superior performance in both the visual and the auditory conditions compared with the word-only condition. An equivalent current dipoles analysis of MEG data indicated that higher equivalent current dipole amplitudes in the right fusiform gyrus occurred during the visual condition and in the superior temporal auditory cortices during the auditory condition, both 450-550 ms after onset of the recognition stimuli. Results suggest that reactivation of visual and auditory brain regions during recognition binds language with modality-specific information and that reactivation enhances confidence in one's recognition performance.

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.

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

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

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.

Whole-brain MEG connectivity-based analyses reveals critical hubs in childhood absence epilepsy.

PubMed

Youssofzadeh, Vahab; Agler, William; Tenney, Jeffrey R; Kadis, Darren S

2018-06-04

Absence seizures are thought to be linked to abnormal interplays between regions of a thalamocortical network. However, the complexity of this widespread network makes characterizing the functional interactions among various brain regions challenging. Using whole-brain functional connectivity and network analysis of magnetoencephalography (MEG) data, we explored pre-treatment brain hubs ("highly connected nodes") of patients aged 6 to 12 years with childhood absence epilepsy. We analyzed ictal MEG data of 74 seizures from 16 patients. We employed a time-domain beamformer technique to estimate MEG sources in broadband (1-40 Hz) where the greatest power changes between ictal and preictal periods were identified. A phase synchrony measure, phase locking value, and a graph theory metric, eigenvector centrality (EVC), were utilized to quantify voxel-level connectivity and network hubs of ictal > preictal periods, respectively. A volumetric atlas containing 116 regions of interests (ROIs) was utilized to summarize the network measures. ROIs with EVC (z-score) > 1.96 were reported as critical hubs. ROIs analysis revealed functional-anatomical hubs in a widespread network containing bilateral precuneus (right/left, z = 2.39, 2.18), left thalamus (z = 2.28), and three anterior cerebellar subunits of lobule "IV-V" (z = 3.9), vermis "IV-V" (z = 3.57), and lobule "III" (z = 2.03). Findings suggest that highly connected brain areas or hubs are present in focal cortical, subcortical, and cerebellar regions during absence seizures. Hubs in thalami, precuneus and cingulate cortex generally support a theory of rapidly engaging and bilaterally distributed networks of cortical and subcortical regions responsible for seizures generation, whereas hubs in anterior cerebellar regions may be linked to terminating motor automatisms frequently seen during typical absence seizures. Whole-brain network connectivity is a powerful analytic tool to reveal focal components of absence seizures in MEG. Our investigations can lead to a better understanding of the pathophysiology of CAE. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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.

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

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.

Neural Mechanisms Underlying Action Observation in Adults with Down Syndrome

ERIC Educational Resources Information Center

Virji-Babul, Naznin; Moiseev, Alexander; Cheung, Teresa; Weeks, Daniel J.; Cheyne, Douglas; Ribary, Urs

2010-01-01

Results of a magnetoencephalography (MEG) brain imaging study conducted to examine the cortical responses during action execution and action observation in 10 healthy adults and 8 age-matched adults with Down syndrome are reported. During execution, the motor responses were strongly lateralized on the ipsilateral rather than the contralateral side…

A MEG investigation of somatosensory processing in the rhesus monkey

PubMed Central

Wilson, Tony W.; Godwin, Dwayne W.; Czoty, Paul W.; Nader, Michael A.; Kraft, Robert A.; Buchheimer, Nancy C.; Daunais, James B.

2009-01-01

The use of minimally and non-invasive neuroimaging methods in animal models has sharply increased over the past decade. Such studies have enhanced understanding of the neural basis of the physical signals quantified by these tools, and have addressed an assortment of fundamental and otherwise intractable questions in neurobiology. To date, these studies have almost exclusively utilized positron-emission tomography or variants of magnetic resonance based imaging. These methods provide largely indirect measures of brain activity and are strongly reliant on intact vasculature and normal blood flow, which is known to be compromised in many clinical conditions. The current study provides the first demonstration of whole-head magnetoencephalography (MEG), a non-invasive and direct measure of neuronal activity, in a rhesus monkey, and in the process supplies the initial data on systems-level dynamics in somatosensory cortices. An adult rhesus monkey underwent three separate studies of tactile stimulation on the pad of the right second or fifth digit as whole-head MEG data were acquired. The neural generators of the primary neuromagnetic components were localized using an equivalent-current-dipole model. Second digit stimulation produced an initial cortical response peaking ∼16 ms after stimulus onset in the contralateral somatosensory cortices, with a later response at ∼96 ms in an overlapping or nearby neural area with a roughly orthogonal orientation. Stimulation of the fifth digit produced similar results, the main exception being a substantially weaker later response. We believe the 16ms response is likely the monkey homologue of the human M50 response, as both are the earliest cortical response and localize to the contralateral primary somatosensory area. Thus, these data suggest that mechanoreception in nonhuman primates operates substantially faster than that in adult humans. More broadly, these results demonstrate that it is feasible to use current human whole-head MEG instrumentation to record neuromagnetic responses in adult rhesus monkeys. Nonhuman primate models of human disease provide the closest phylogenetic link to humans. The present, non-invasive imaging study could promote exciting links between invasive animal studies and non-invasive human studies, allowing experimentally induced deficits and pharmacological treatments to be interpreted in light of resulting brain network interactions. PMID:19306931

MEG Frequency Analysis Depicts the Impaired Neurophysiological Condition of Ischemic Brain

PubMed Central

Ikeda, Hidetoshi; Tsuyuguchi, Naohiro; Uda, Takehiro; Okumura, Eiichi; Asakawa, Takashi; Haruta, Yasuhiro; Nishiyama, Hideki; Okada, Toyoji; Kamada, Hajime; Ohata, Kenji; Miki, Yukio

2016-01-01

Purpose Quantitative imaging of neuromagnetic fields based on automated region of interest (ROI) setting was analyzed to determine the characteristics of cerebral neural activity in ischemic areas. Methods Magnetoencephalography (MEG) was used to evaluate spontaneous neuromagnetic fields in the ischemic areas of 37 patients with unilateral internal carotid artery (ICA) occlusive disease. Voxel-based time-averaged intensity of slow waves was obtained in two frequency bands (0.3–4 Hz and 4–8 Hz) using standardized low-resolution brain electromagnetic tomography (sLORETA) modified for a quantifiable method (sLORETA-qm). ROIs were automatically applied to the anterior cerebral artery (ACA), anterior middle cerebral artery (MCAa), posterior middle cerebral artery (MCAp), and posterior cerebral artery (PCA) using statistical parametric mapping (SPM). Positron emission tomography with 15O-gas inhalation (15O-PET) was also performed to evaluate cerebral blood flow (CBF) and oxygen extraction fraction (OEF). Statistical analyses were performed using laterality index of MEG and 15O-PET in each ROI with respect to distribution and intensity. Results MEG revealed statistically significant laterality in affected MCA regions, including 4–8 Hz waves in MCAa, and 0.3–4 Hz and 4–8 Hz waves in MCAp (95% confidence interval: 0.020–0.190, 0.030–0.207, and 0.034–0.213), respectively. We found that 0.3–4 Hz waves in MCAp were highly correlated with CBF in MCAa and MCAp (r = 0.74, r = 0.68, respectively), whereas 4–8 Hz waves were moderately correlated with CBF in both the MCAa and MCAp (r = 0.60, r = 0.63, respectively). We also found that 4–8 Hz waves in MCAp were statistically significant for misery perfusion identified on 15O-PET (p<0.05). Conclusions Quantitatively imaged spontaneous neuromagnetic fields using the automated ROI setting enabled clear depiction of cerebral ischemic areas. Frequency analysis may reveal unique neural activity that is distributed in the impaired vascular metabolic territory, in which the cerebral infarction has not yet been completed. PMID:27992543

Neuroimaging in pediatric traumatic head injury: diagnostic considerations and relationships to neurobehavioral outcome.

PubMed

Bigler, E D

1999-08-01

Contemporary neuorimaging techniques in child traumatic brain injury are reviewed, with an emphasis on computerized tomography (CT) and magnetic resonance (MR) imaging. A brief overview of MR spectroscopy (MRS), functional MR imaging (fMRI), single-photon emission computed tomography (SPECT), and magnetoencephalography (MEG) is also provided because these techniques will likely constitute important neuroimaging techniques of the future. Numerous figures are provided to illustrate the multifaceted manner in which traumatic deficits can be imaged and the role of neuroimaging information as it relates to TBI outcome.

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.

Emerging imaging tools for use with traumatic brain injury research.

PubMed

Hunter, Jill V; Wilde, Elisabeth A; Tong, Karen A; Holshouser, Barbara A

2012-03-01

This article identifies emerging neuroimaging measures considered by the inter-agency Pediatric Traumatic Brain Injury (TBI) Neuroimaging Workgroup. This article attempts to address some of the potential uses of more advanced forms of imaging in TBI as well as highlight some of the current considerations and unresolved challenges of using them. We summarize emerging elements likely to gain more widespread use in the coming years, because of 1) their utility in diagnosis, prognosis, and understanding the natural course of degeneration or recovery following TBI, and potential for evaluating treatment strategies; 2) the ability of many centers to acquire these data with scanners and equipment that are readily available in existing clinical and research settings; and 3) advances in software that provide more automated, readily available, and cost-effective analysis methods for large scale data image analysis. These include multi-slice CT, volumetric MRI analysis, susceptibility-weighted imaging (SWI), diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), arterial spin tag labeling (ASL), functional MRI (fMRI), including resting state and connectivity MRI, MR spectroscopy (MRS), and hyperpolarization scanning. However, we also include brief introductions to other specialized forms of advanced imaging that currently do require specialized equipment, for example, single photon emission computed tomography (SPECT), positron emission tomography (PET), encephalography (EEG), and magnetoencephalography (MEG)/magnetic source imaging (MSI). Finally, we identify some of the challenges that users of the emerging imaging CDEs may wish to consider, including quality control, performing multi-site and longitudinal imaging studies, and MR scanning in infants and children.

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.

Multimodal imaging of temporal processing in typical and atypical language development.

PubMed

Kovelman, Ioulia; Wagley, Neelima; Hay, Jessica S F; Ugolini, Margaret; Bowyer, Susan M; Lajiness-O'Neill, Renee; Brennan, Jonathan

2015-03-01

New approaches to understanding language and reading acquisition propose that the human brain's ability to synchronize its neural firing rate to syllable-length linguistic units may be important to children's ability to acquire human language. Yet, little evidence from brain imaging studies has been available to support this proposal. Here, we summarize three recent brain imaging (functional near-infrared spectroscopy (fNIRS), functional magnetic resonance imaging (fMRI), and magnetoencephalography (MEG)) studies from our laboratories with young English-speaking children (aged 6-12 years). In the first study (fNIRS), we used an auditory beat perception task to show that, in children, the left superior temporal gyrus (STG) responds preferentially to rhythmic beats at 1.5 Hz. In the second study (fMRI), we found correlations between children's amplitude rise-time sensitivity, phonological awareness, and brain activation in the left STG. In the third study (MEG), typically developing children outperformed children with autism spectrum disorder in extracting words from rhythmically rich foreign speech and displayed different brain activation during the learning phase. The overall findings suggest that the efficiency with which left temporal regions process slow temporal (rhythmic) information may be important for gains in language and reading proficiency. These findings carry implications for better understanding of the brain's mechanisms that support language and reading acquisition during both typical and atypical development. © 2014 New York Academy of Sciences.

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

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

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.

A comparative study of a theoretical neural net model with MEG data from epileptic patients and normal individuals.

PubMed

Kotini, A; Anninos, P; Anastasiadis, A N; Tamiolakis, D

2005-09-07

The aim of this study was to compare a theoretical neural net model with MEG data from epileptic patients and normal individuals. Our experimental study population included 10 epilepsy sufferers and 10 healthy subjects. The recordings were obtained with a one-channel biomagnetometer SQUID in a magnetically shielded room. Using the method of x2-fitting it was found that the MEG amplitudes in epileptic patients and normal subjects had Poisson and Gauss distributions respectively. The Poisson connectivity derived from the theoretical neural model represents the state of epilepsy, whereas the Gauss connectivity represents normal behavior. The MEG data obtained from epileptic areas had higher amplitudes than the MEG from normal regions and were comparable with the theoretical magnetic fields from Poisson and Gauss distributions. Furthermore, the magnetic field derived from the theoretical model had amplitudes in the same order as the recorded MEG from the 20 participants. The approximation of the theoretical neural net model with real MEG data provides information about the structure of the brain function in epileptic and normal states encouraging further studies to be conducted.

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

Non-linear Parameter Estimates from Non-stationary MEG Data

PubMed Central

Martínez-Vargas, Juan D.; López, Jose D.; Baker, Adam; Castellanos-Dominguez, German; Woolrich, Mark W.; Barnes, Gareth

2016-01-01

We demonstrate a method to estimate key electrophysiological parameters from resting state data. In this paper, we focus on the estimation of head-position parameters. The recovery of these parameters is especially challenging as they are non-linearly related to the measured field. In order to do this we use an empirical Bayesian scheme to estimate the cortical current distribution due to a range of laterally shifted head-models. We compare different methods of approaching this problem from the division of M/EEG data into stationary sections and performing separate source inversions, to explaining all of the M/EEG data with a single inversion. We demonstrate this through estimation of head position in both simulated and empirical resting state MEG data collected using a head-cast. PMID:27597815

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

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.

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.

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.

Filling in the gaps: Anticipatory control of eye movements in chronic mild traumatic brain injury.

PubMed

Diwakar, Mithun; Harrington, Deborah L; Maruta, Jun; Ghajar, Jamshid; El-Gabalawy, Fady; Muzzatti, Laura; Corbetta, Maurizio; Huang, Ming-Xiong; Lee, Roland R

2015-01-01

A barrier in the diagnosis of mild traumatic brain injury (mTBI) stems from the lack of measures that are adequately sensitive in detecting mild head injuries. MRI and CT are typically negative in mTBI patients with persistent symptoms of post-concussive syndrome (PCS), and characteristic difficulties in sustaining attention often go undetected on neuropsychological testing, which can be insensitive to momentary lapses in concentration. Conversely, visual tracking strongly depends on sustained attention over time and is impaired in chronic mTBI patients, especially when tracking an occluded target. This finding suggests deficient internal anticipatory control in mTBI, the neural underpinnings of which are poorly understood. The present study investigated the neuronal bases for deficient anticipatory control during visual tracking in 25 chronic mTBI patients with persistent PCS symptoms and 25 healthy control subjects. The task was performed while undergoing magnetoencephalography (MEG), which allowed us to examine whether neural dysfunction associated with anticipatory control deficits was due to altered alpha, beta, and/or gamma activity. Neuropsychological examinations characterized cognition in both groups. During MEG recordings, subjects tracked a predictably moving target that was either continuously visible or randomly occluded (gap condition). MEG source-imaging analyses tested for group differences in alpha, beta, and gamma frequency bands. The results showed executive functioning, information processing speed, and verbal memory deficits in the mTBI group. Visual tracking was impaired in the mTBI group only in the gap condition. Patients showed greater error than controls before and during target occlusion, and were slower to resynchronize with the target when it reappeared. Impaired tracking concurred with abnormal beta activity, which was suppressed in the parietal cortex, especially the right hemisphere, and enhanced in left caudate and frontal-temporal areas. Regional beta-amplitude demonstrated high classification accuracy (92%) compared to eye-tracking (65%) and neuropsychological variables (80%). These findings show that deficient internal anticipatory control in mTBI is associated with altered beta activity, which is remarkably sensitive given the heterogeneity of injuries.

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

Conversation Effects on Neural Mechanisms Underlying Reaction Time to Visual Events while Viewing a Driving Scene using MEG

PubMed Central

Bowyer, Susan M.; Hsieh, Li; Moran, John E.; Young, Richard A.; Manoharan, Arun; Liao, Chia-cheng Jason; Malladi, Kiran; Yu, Ya-Ju; Chiang, Yow-Ren; Tepley, Norman

2009-01-01

Magnetoencephalography (MEG) imaging examined the neural mechanisms that modulate reaction times to visual events while viewing a driving video, with and without a conversation. Twenty-four subjects ages 18–65 were monitored by whole-head MEG. The primary tasks were to monitor a driving video and to depress a foot pedal in response to a small red light presented to the left or below the driving scene at unpredictable times. The behavioral reaction time (RT) to the lights was recorded. The secondary task was a hands-free conversation. The subject pressed a button to answer a ring tone, and then covertly answered pre-recorded non-emotional questions such as “What is your birth date?” RTs for the conversation task (1043ms, SE=65ms) were slightly longer than for the primary task (baseline no conversation (944ms, SE=48ms). During the primary task RTs were inversely related to the amount of brain activity detected by MEG in the right superior parietal lobe (Brodmann’s Area 7). Brain activity was seen in the 200 to 300 ms range after the onset of the red light and in the visual cortex (BA 19) about 85 ms after the red light. Conversation reduced the strengths of these regression relationships and increased mean RT. Conversation may contribute to increased reaction times by (1) damping brain activation in specific regions during specific time windows, or (2) reducing facilitation from attention inputs into those areas. These laboratory findings should not be interpreted as indicative of real-world driving, without on-road validation, and comparison to other in-vehicle tasks. PMID:18992728

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

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.

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.

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.

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

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

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.

Magnetoencephalographic accuracy profiles for the detection of auditory pathway sources.

PubMed

Bauer, Martin; Trahms, Lutz; Sander, Tilmann

2015-04-01

The detection limits for cortical and brain stem sources associated with the auditory pathway are examined in order to analyse brain responses at the limits of the audible frequency range. The results obtained from this study are also relevant to other issues of auditory brain research. A complementary approach consisting of recordings of magnetoencephalographic (MEG) data and simulations of magnetic field distributions is presented in this work. A biomagnetic phantom consisting of a spherical volume filled with a saline solution and four current dipoles is built. The magnetic fields outside of the phantom generated by the current dipoles are then measured for a range of applied electric dipole moments with a planar multichannel SQUID magnetometer device and a helmet MEG gradiometer device. The inclusion of a magnetometer system is expected to be more sensitive to brain stem sources compared with a gradiometer system. The same electrical and geometrical configuration is simulated in a forward calculation. From both the measured and the simulated data, the dipole positions are estimated using an inverse calculation. Results are obtained for the reconstruction accuracy as a function of applied electric dipole moment and depth of the current dipole. We found that both systems can localize cortical and subcortical sources at physiological dipole strength even for brain stem sources. Further, we found that a planar magnetometer system is more suitable if the position of the brain source can be restricted in a limited region of the brain. If this is not the case, a helmet-shaped sensor system offers more accurate source estimation.

Techniques for detection and localization of weak hippocampal and medial frontal sources using beamformers in MEG.

PubMed

Mills, Travis; Lalancette, Marc; Moses, Sandra N; Taylor, Margot J; Quraan, Maher A

2012-07-01

Magnetoencephalography provides precise information about the temporal dynamics of brain activation and is an ideal tool for investigating rapid cognitive processing. However, in many cognitive paradigms visual stimuli are used, which evoke strong brain responses (typically 40-100 nAm in V1) that may impede the detection of weaker activations of interest. This is particularly a concern when beamformer algorithms are used for source analysis, due to artefacts such as "leakage" of activation from the primary visual sources into other regions. We have previously shown (Quraan et al. 2011) that we can effectively reduce leakage patterns and detect weak hippocampal sources by subtracting the functional images derived from the experimental task and a control task with similar stimulus parameters. In this study we assess the performance of three different subtraction techniques. In the first technique we follow the same post-localization subtraction procedures as in our previous work. In the second and third techniques, we subtract the sensor data obtained from the experimental and control paradigms prior to source localization. Using simulated signals embedded in real data, we show that when beamformers are used, subtraction prior to source localization allows for the detection of weaker sources and higher localization accuracy. The improvement in localization accuracy exceeded 10 mm at low signal-to-noise ratios, and sources down to below 5 nAm were detected. We applied our techniques to empirical data acquired with two different paradigms designed to evoke hippocampal and frontal activations, and demonstrated our ability to detect robust activations in both regions with substantial improvements over image subtraction. We conclude that removal of the common-mode dominant sources through data subtraction prior to localization further improves the beamformer's ability to project the n-channel sensor-space data to reveal weak sources of interest and allows more accurate localization.

Rapid neural discrimination of communicative gestures

PubMed Central

Carlson, Thomas A.

2015-01-01

Humans are biased toward social interaction. Behaviorally, this bias is evident in the rapid effects that self-relevant communicative signals have on attention and perceptual systems. The processing of communicative cues recruits a wide network of brain regions, including mentalizing systems. Relatively less work, however, has examined the timing of the processing of self-relevant communicative cues. In the present study, we used multivariate pattern analysis (decoding) approach to the analysis of magnetoencephalography (MEG) to study the processing dynamics of social-communicative actions. Twenty-four participants viewed images of a woman performing actions that varied on a continuum of communicative factors including self-relevance (to the participant) and emotional valence, while their brain activity was recorded using MEG. Controlling for low-level visual factors, we found early discrimination of emotional valence (70 ms) and self-relevant communicative signals (100 ms). These data offer neural support for the robust and rapid effects of self-relevant communicative cues on behavior. PMID:24958087

Magnetoencephalography Phantom Comparison and Validation: Hospital Universiti Sains Malaysia (HUSM) Requisite.

PubMed

Omar, Hazim; Ahmad, Alwani Liyan; Hayashi, Noburo; Idris, Zamzuri; Abdullah, Jafri Malin

2015-12-01

Magnetoencephalography (MEG) has been extensively used to measure small-scale neuronal brain activity. Although it is widely acknowledged as a sensitive tool for deciphering brain activity and source localisation, the accuracy of the MEG system must be critically evaluated. Typically, on-site calibration with the provided phantom (Local phantom) is used. However, this method is still questionable due to the uncertainty that may originate from the phantom itself. Ideally, the validation of MEG data measurements would require cross-site comparability. A simple method of phantom testing was used twice in addition to a measurement taken with a calibrated reference phantom (RefPhantom) obtained from Elekta Oy of Helsinki, Finland. The comparisons of two main aspects were made in terms of the dipole moment (Qpp) and the difference in the dipole distance from the origin (d) after the tests of statistically equal means and variance were confirmed. The result of Qpp measurements for the LocalPhantom and RefPhantom were 978 (SD24) nAm and 988 (SD32) nAm, respectively, and were still optimally within the accepted range of 900 to 1100 nAm. Moreover, the shifted d results for the LocalPhantom and RefPhantom were 1.84 mm (SD 0.53) and 2.14 mm (SD 0.78), respectively, and these values were below the maximum acceptance range of within 5.0 mm of the nominal dipole location. The Local phantom seems to outperform the reference phantom as indicated by the small standard error of the former (SE 0.094) compared with the latter (SE 0.138). The result indicated that HUSM MEG system was in excellent working condition in terms of the dipole magnitude and localisation measurements as these values passed the acceptance limits criteria of the phantom test.

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

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

Emerging Imaging Tools for Use with Traumatic Brain Injury Research

PubMed Central

Wilde, Elisabeth A.; Tong, Karen A.; Holshouser, Barbara A.

2012-01-01

Abstract This article identifies emerging neuroimaging measures considered by the inter-agency Pediatric Traumatic Brain Injury (TBI) Neuroimaging Workgroup. This article attempts to address some of the potential uses of more advanced forms of imaging in TBI as well as highlight some of the current considerations and unresolved challenges of using them. We summarize emerging elements likely to gain more widespread use in the coming years, because of 1) their utility in diagnosis, prognosis, and understanding the natural course of degeneration or recovery following TBI, and potential for evaluating treatment strategies; 2) the ability of many centers to acquire these data with scanners and equipment that are readily available in existing clinical and research settings; and 3) advances in software that provide more automated, readily available, and cost-effective analysis methods for large scale data image analysis. These include multi-slice CT, volumetric MRI analysis, susceptibility-weighted imaging (SWI), diffusion tensor imaging (DTI), magnetization transfer imaging (MTI), arterial spin tag labeling (ASL), functional MRI (fMRI), including resting state and connectivity MRI, MR spectroscopy (MRS), and hyperpolarization scanning. However, we also include brief introductions to other specialized forms of advanced imaging that currently do require specialized equipment, for example, single photon emission computed tomography (SPECT), positron emission tomography (PET), encephalography (EEG), and magnetoencephalography (MEG)/magnetic source imaging (MSI). Finally, we identify some of the challenges that users of the emerging imaging CDEs may wish to consider, including quality control, performing multi-site and longitudinal imaging studies, and MR scanning in infants and children. PMID:21787167

Atypical spatiotemporal signatures of working memory brain processes in autism.

PubMed

Urbain, C M; Pang, E W; Taylor, M J

2015-08-11

Working memory (WM) impairments may contribute to the profound behavioural manifestations in children with autism spectrum disorder (ASD). However, previous behavioural results are discrepant as are the few functional magnetic resonance imaging (fMRI) results collected in adults and adolescents with ASD. Here we investigate the precise temporal dynamics of WM-related brain activity using magnetoencephalography (MEG) in 20 children with ASD and matched controls during an n-back WM task across different load levels (1-back vs 2-back). Although behavioural results were similar between ASD and typically developing (TD) children, the between-group comparison performed on functional brain activity showed atypical WM-related brain processes in children with ASD compared with TD children. These atypical responses were observed in the ASD group from 200 to 600 ms post stimulus in both the low- (1-back) and high- (2-back) memory load conditions. During the 1-back condition, children with ASD showed reduced WM-related activations in the right hippocampus and the cingulate gyrus compared with TD children who showed more activation in the left dorso-lateral prefrontal cortex and the insulae. In the 2-back condition, children with ASD showed less activity in the left insula and midcingulate gyrus and more activity in the left precuneus than TD children. In addition, reduced activity in the anterior cingulate cortex was correlated with symptom severity in children with ASD. Thus, this MEG study identified the precise timing and sources of atypical WM-related activity in frontal, temporal and parietal regions in children with ASD. The potential impacts of such atypicalities on social deficits of autism are discussed.

The role of cortical beta oscillations in time estimation.

PubMed

Kulashekhar, Shrikanth; Pekkola, Johanna; Palva, Jaakko Matias; Palva, Satu

2016-09-01

Estimation of time is central to perception, action, and cognition. Human functional magnetic resonance imaging (fMRI) and positron emission topography (PET) have revealed a positive correlation between the estimation of multi-second temporal durations and neuronal activity in a circuit of sensory and motor areas, prefrontal and temporal cortices, basal ganglia, and cerebellum. The systems-level mechanisms coordinating the collective neuronal activity in these areas have remained poorly understood. Synchronized oscillations regulate communication in neuronal networks and could hence serve such coordination, but their role in the estimation and maintenance of multi-second time intervals has remained largely unknown. We used source-reconstructed magnetoencephalography (MEG) to address the functional significance of local neuronal synchronization, as indexed by the amplitudes of cortical oscillations, in time-estimation. MEG was acquired during a working memory (WM) task where the subjects first estimated and then memorized the durations, or in the contrast condition, the colors of dynamic visual stimuli. Time estimation was associated with stronger beta (β, 14 - 30 Hz) band oscillations than color estimation in sensory regions and attentional cortical structures that earlier have been associated with time processing. In addition, the encoding of duration information was associated with strengthened gamma- (γ, 30 - 120 Hz), and the retrieval and maintenance with alpha- (α, 8 - 14 Hz) band oscillations. These data suggest that β oscillations may provide a mechanism for estimating short temporal durations, while γ and α oscillations support their encoding, retrieval, and maintenance in memory. Hum Brain Mapp 37:3262-3281, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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.

Verbal memory and verbal fluency tasks used for language localization and lateralization during magnetoencephalography.

PubMed

Pirmoradi, Mona; Jemel, Boutheina; Gallagher, Anne; Tremblay, Julie; D'Hondt, Fabien; Nguyen, Dang Khoa; Béland, Renée; Lassonde, Maryse

2016-01-01

The aim of this study was to develop a presurgical magnetoencephalography (MEG) protocol to localize and lateralize expressive and receptive language function as well as verbal memory in patients with epilepsy. Two simple language tasks and a different analytical procedure were developed. Ten healthy participants and 13 epileptic patients completed two language tasks during MEG recording: a verbal memory task and a verbal fluency task. As a first step, principal component analyses (PCA) were performed on source data from the group of healthy participants to identify spatiotemporal factors that were relevant to these paradigms. Averaged source data were used to localize areas activated during each task and a laterality index (LI) was computed on an individual basis for both groups, healthy participants and patients, using sensor data. PCA revealed activation in the left temporal lobe (300 ms) during the verbal memory task, and from the frontal lobe (210 ms) to the temporal lobe (500 ms) during the verbal fluency task in healthy participants. Averaged source data showed activity in the left hemisphere (250-750 ms), in Wernicke's area, for all participants. Left hemisphere dominance was demonstrated better using the verbal memory task than the verbal fluency task (F1,19=4.41, p=0.049). Cohen's kappa statistic revealed 93% agreement (k=0.67, p=0.002) between LIs obtained from MEG sensor data and fMRI, the IAT, electrical cortical stimulation or handedness with the verbal memory task for all participants. At 74%, agreement results for the verbal fluency task did not reach statistical significance. Analysis procedures yielded interesting findings with both tasks and localized language-related activation. However, based on source localization and laterality indices, the verbal memory task yielded better results in the context of the presurgical evaluation of epileptic patients. The verbal fluency task did not add any further information to the verbal memory task as regards language localization and lateralization for most patients and healthy participants that would facilitate decision making prior to surgery. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

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

The Brain Computer Interface Future: Time for a Strategy

DTIC Science & Technology

2013-02-14

electrophysiological activity can be measured by electroencepholography ( EEG ), electrocorticography (ECoG), magnetoencephalography (MEG), or signal activity...magnetic resonance imaging (MRI) or near infrared spectroscopy. Currently EEG is most the most widely used BCI interface due to high temporal...resolution, less user risk, and lower costs.12 EEG technology has been widely available for many decades but has significantly expanded as researchers

Artificial neural network detects human uncertainty

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Frolov, Nikita S.; Maksimenko, Vladimir A.; Makarov, Vladimir V.; Koronovskii, Alexey A.; Garcia-Prieto, Juan; Antón-Toro, Luis Fernando; Maestú, Fernando; Pisarchik, Alexander N.

2018-03-01

Artificial neural networks (ANNs) are known to be a powerful tool for data analysis. They are used in social science, robotics, and neurophysiology for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience, ANNs allow the recognition of specific forms of brain activity from multichannel EEG or MEG data. This makes the ANN an efficient computational core for brain-machine systems. However, despite significant achievements of artificial intelligence in recognition and classification of well-reproducible patterns of neural activity, the use of ANNs for recognition and classification of patterns in neural networks still requires additional attention, especially in ambiguous situations. According to this, in this research, we demonstrate the efficiency of application of the ANN for classification of human MEG trials corresponding to the perception of bistable visual stimuli with different degrees of ambiguity. We show that along with classification of brain states associated with multistable image interpretations, in the case of significant ambiguity, the ANN can detect an uncertain state when the observer doubts about the image interpretation. With the obtained results, we describe the possible application of ANNs for detection of bistable brain activity associated with difficulties in the decision-making process.

An evaluation of kurtosis beamforming in magnetoencephalography to localize the epileptogenic zone in drug resistant epilepsy patients.

PubMed

Hall, Michael B H; Nissen, Ida A; van Straaten, Elisabeth C W; Furlong, Paul L; Witton, Caroline; Foley, Elaine; Seri, Stefano; Hillebrand, Arjan

2018-06-01

Kurtosis beamforming is a useful technique for analysing magnetoencephalograpy (MEG) data containing epileptic spikes. However, the implementation varies and few studies measure concordance with subsequently resected areas. We evaluated kurtosis beamforming as a means of localizing spikes in drug-resistant epilepsy patients. We retrospectively applied kurtosis beamforming to MEG recordings of 22 epilepsy patients that had previously been analysed using equivalent current dipole (ECD) fitting. Virtual electrodes were placed in the kurtosis volumetric peaks and visually inspected to select a candidate source. The candidate sources were compared to the ECD localizations and resection areas. The kurtosis beamformer produced interpretable localizations in 18/22 patients, of which the candidate source coincided with the resection lobe in 9/13 seizure-free patients and in 3/5 patients with persistent seizures. The sublobar accuracy of the kurtosis beamformer with respect to the resection zone was higher than ECD (56% and 50%, respectively), however, ECD resulted in a higher lobar accuracy (75%, 67%). Kurtosis beamforming may provide additional value when spikes are not clearly discernible on the sensors and support ECD localizations when dipoles are scattered. Kurtosis beamforming should be integrated with existing clinical protocols to assist in localizing the epileptogenic zone. Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Magnetoencephalography for the Detection of Intervention Effects of a Specific Nutrient Combination in Patients with Mild Alzheimer’s Disease: Results from an Exploratory Double-Blind, Randomized, Controlled Study

PubMed Central

van Straaten, Elisabeth C. W.; de Waal, Hanneke; Lansbergen, Marieke M.; Scheltens, Philip; Maestu, Fernando; Nowak, Rafal; Hillebrand, Arjan; Stam, Cornelis J.

2016-01-01

Synaptic loss is an early pathological finding in Alzheimer’s disease (AD) and correlates with memory impairment. Changes in macroscopic brain activity measured with electro- and magnetoencephalography (EEG and MEG) in AD indicate synaptic changes and may therefore serve as markers of intervention effects in clinical trials. EEG peak frequency and functional networks have shown, in addition to improved memory performance, to be sensitive to detect an intervention effect in mild AD patients of the medical food Souvenaid containing the specific nutrient combination Fortasyn® Connect, which is designed to enhance synapse formation and function. Here, we explore the value of MEG, with higher spatial resolution than EEG, in identifying intervention effects of the nutrient combination by comparing MEG spectral measures, functional connectivity, and networks between an intervention and a control group. Quantitative markers describing spectral properties, functional connectivity, and graph theoretical aspects of MEG from the exploratory 24-week, double-blind, randomized, controlled Souvenir II MEG sub-study (NTR1975, http://www.trialregister.nl) in drug naïve patients with mild AD were compared between a test group (n = 27), receiving Souvenaid, and a control group (n = 28), receiving an isocaloric control product. The groups were unbalanced at screening with respect to Mini-Mental State Examination. Peak frequencies of MEG were compared with EEG peak frequencies, recorded in the same patients at similar time points, were compared with respect to sensitivity to intervention effects. No consistent statistically significant intervention effects were detected. In addition, we found no difference in sensitivity between MEG and EEG peak frequency. This exploratory study could not unequivocally establish the value of MEG in detecting interventional effects on brain activity, possibly due to small sample size and unbalanced study groups. We found no indication that the difference could be attributed to a lack of sensitivity of MEG compared with EEG. MEG in randomized controlled trials is feasible but its value to disclose intervention effects of Souvenaid in mild AD patients needs to be studied further. PMID:27799918

Magnetoencephalography for the Detection of Intervention Effects of a Specific Nutrient Combination in Patients with Mild Alzheimer's Disease: Results from an Exploratory Double-Blind, Randomized, Controlled Study.

PubMed

van Straaten, Elisabeth C W; de Waal, Hanneke; Lansbergen, Marieke M; Scheltens, Philip; Maestu, Fernando; Nowak, Rafal; Hillebrand, Arjan; Stam, Cornelis J

2016-01-01

Synaptic loss is an early pathological finding in Alzheimer's disease (AD) and correlates with memory impairment. Changes in macroscopic brain activity measured with electro- and magnetoencephalography (EEG and MEG) in AD indicate synaptic changes and may therefore serve as markers of intervention effects in clinical trials. EEG peak frequency and functional networks have shown, in addition to improved memory performance, to be sensitive to detect an intervention effect in mild AD patients of the medical food Souvenaid containing the specific nutrient combination Fortasyn ® Connect, which is designed to enhance synapse formation and function. Here, we explore the value of MEG, with higher spatial resolution than EEG, in identifying intervention effects of the nutrient combination by comparing MEG spectral measures, functional connectivity, and networks between an intervention and a control group. Quantitative markers describing spectral properties, functional connectivity, and graph theoretical aspects of MEG from the exploratory 24-week, double-blind, randomized, controlled Souvenir II MEG sub-study (NTR1975, http://www.trialregister.nl) in drug naïve patients with mild AD were compared between a test group ( n  = 27), receiving Souvenaid, and a control group ( n  = 28), receiving an isocaloric control product. The groups were unbalanced at screening with respect to Mini-Mental State Examination. Peak frequencies of MEG were compared with EEG peak frequencies, recorded in the same patients at similar time points, were compared with respect to sensitivity to intervention effects. No consistent statistically significant intervention effects were detected. In addition, we found no difference in sensitivity between MEG and EEG peak frequency. This exploratory study could not unequivocally establish the value of MEG in detecting interventional effects on brain activity, possibly due to small sample size and unbalanced study groups. We found no indication that the difference could be attributed to a lack of sensitivity of MEG compared with EEG. MEG in randomized controlled trials is feasible but its value to disclose intervention effects of Souvenaid in mild AD patients needs to be studied further.

Localization of MEG pathologic gamma oscillations in adult epilepsy patients with focal cortical dysplasia☆

PubMed Central

Jeong, Woorim; Kim, June Sic; Chung, Chun Kee

2013-01-01

We aimed to evaluate the clinical value of gamma oscillations in MEG for intractable neocortical epilepsy patients with cortical dysplasia by comparing gamma and interictal spike events. A retrospective analysis of MEG recordings of 30 adult neocortical epilepsy patients was performed. Gamma (30–70 Hz) and interictal spike events were independently identified, their independent or concurrent presence determined, and their source localization rates compared. Of 30 patients, gamma activities were detected in 28 patients and interictal spikes in 24 patients. Gamma events alone appeared in 5 patients, interictal spikes alone in 1 patient, and no events in 1 patient. Gamma co-occurred with interictal spikes in 20.1 ± 22.1% and interictal spikes co-occurred with gamma in 15.0 ± 19.2%. Rates of event localization within the resection cavity were significantly different (p = 0.042) between gamma (63.3 ± 32.6%) and interictal spike (47.0 ± 41.3%) events. In 4 of the 5 gamma-only patients the mean localization rate was 42.5%. Compared with the interictal spike localization rate, 4 of 9 seizure-free patients had higher gamma localization rates, 4 had the same rate, and 1 had a lower rate. Individual gamma events can be detected independently from interictal spike presence. Gamma can be localized to the resection cavity at least comparably to or more frequently than that from interictal spikes. Even when interictal spikes were undetected, gamma sources were localized to the resection cavity. Gamma oscillations may be a useful indicator of epileptogenic focus. PMID:24273733

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.

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.

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…

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.

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

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.

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.

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

Language in Context: MEG Evidence for Modality-General and -Specific Responses to Reference Resolution

PubMed Central

2016-01-01

Abstract Successful language comprehension critically depends on our ability to link linguistic expressions to the entities they refer to. Without reference resolution, newly encountered language cannot be related to previously acquired knowledge. The human experience includes many different types of referents, some visual, some auditory, some very abstract. Does the neural basis of reference resolution depend on the nature of the referents, or do our brains use a modality-general mechanism for linking meanings to referents? Here we report evidence for both. Using magnetoencephalography (MEG), we varied both the modality of referents, which consisted either of visual or auditory objects, and the point at which reference resolution was possible within sentences. Source-localized MEG responses revealed brain activity associated with reference resolution that was independent of the modality of the referents, localized to the medial parietal lobe and starting ∼415 ms after the onset of reference resolving words. A modality-specific response to reference resolution in auditory domains was also found, in the vicinity of auditory cortex. Our results suggest that referential language processing cannot be reduced to processing in classical language regions and representations of the referential domain in modality-specific neural systems. Instead, our results suggest that reference resolution engages medial parietal cortex, which supports a mechanism for referential processing regardless of the content modality. PMID:28058272

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

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

Delays in auditory processing identified in preschool children with FASD

PubMed Central

Stephen, Julia M.; Kodituwakku, Piyadasa W.; Kodituwakku, Elizabeth L.; Romero, Lucinda; Peters, Amanda M.; Sharadamma, Nirupama Muniswamy; Caprihan, Arvind; Coffman, Brian A.

2012-01-01

Background Both sensory and cognitive deficits have been associated with prenatal exposure to alcohol; however, very few studies have focused on sensory deficits in preschool aged children. Since sensory skills develop early, characterization of sensory deficits using novel imaging methods may reveal important neural markers of prenatal alcohol exposure. Materials and Methods Participants in this study were 10 children with a fetal alcohol spectrum disorder (FASD) and 15 healthy control children aged 3-6 years. All participants had normal hearing as determined by clinical screens. We measured their neurophysiological responses to auditory stimuli (1000 Hz, 72 dB tone) using magnetoencephalography (MEG). We used a multi-dipole spatio-temporal modeling technique (CSST – Ranken et al. 2002) to identify the location and timecourse of cortical activity in response to the auditory tones. The timing and amplitude of the left and right superior temporal gyrus sources associated with activation of left and right primary/secondary auditory cortices were compared across groups. Results There was a significant delay in M100 and M200 latencies for the FASD children relative to the HC children (p = 0.01), when including age as a covariate. The within-subjects effect of hemisphere was not significant. A comparable delay in M100 and M200 latencies was observed in children across the FASD subtypes. Discussion Auditory delay revealed by MEG in children with FASD may prove to be a useful neural marker of information processing difficulties in young children with prenatal alcohol exposure. The fact that delayed auditory responses were observed across the FASD spectrum suggests that it may be a sensitive measure of alcohol-induced brain damage. Therefore, this measure in conjunction with other clinical tools may prove useful for early identification of alcohol affected children, particularly those without dysmorphia. PMID:22458372

Differential Phonological and Semantic Modulation of Neurophysiological Responses to Visual Word Recognition.

PubMed

Drakesmith, Mark; El-Deredy, Wael; Welbourne, Stephen

2015-01-01

Reading words for meaning relies on orthographic, phonological and semantic processing. The triangle model implicates a direct orthography-to-semantics pathway and a phonologically mediated orthography-to-semantics pathway, which interact with each other. The temporal evolution of processing in these routes is not well understood, although theoretical evidence predicts early phonological processing followed by interactive phonological and semantic processing. This study used electroencephalography-event-related potential (ERP) analysis and magnetoencephalography (MEG) source localisation to identify temporal markers and the corresponding neural generators of these processes in early (∼200 ms) and late (∼400 ms) neurophysiological responses to visual words, pseudowords and consonant strings. ERP showed an effect of phonology but not semantics in both time windows, although at ∼400 ms there was an effect of stimulus familiarity. Phonological processing at ~200 ms was localised to the left occipitotemporal cortex and the inferior frontal gyrus. At 400 ms, there was continued phonological processing in the inferior frontal gyrus and additional semantic processing in the anterior temporal cortex. There was also an area in the left temporoparietal junction which was implicated in both phonological and semantic processing. In ERP, the semantic response at ∼400 ms appeared to be masked by concurrent processes relating to familiarity, while MEG successfully differentiated these processes. The results support the prediction of early phonological processing followed by an interaction of phonological and semantic processing during word recognition. Neuroanatomical loci of these processes are consistent with previous neuropsychological and functional magnetic resonance imaging studies. The results also have implications for the classical interpretation of N400-like responses as markers for semantic processing.

Delays in auditory processing identified in preschool children with FASD.

PubMed

Stephen, Julia M; Kodituwakku, Piyadasa W; Kodituwakku, Elizabeth L; Romero, Lucinda; Peters, Amanda M; Sharadamma, Nirupama M; Caprihan, Arvind; Coffman, Brian A

2012-10-01

Both sensory and cognitive deficits have been associated with prenatal exposure to alcohol; however, very few studies have focused on sensory deficits in preschool-aged children. As sensory skills develop early, characterization of sensory deficits using novel imaging methods may reveal important neural markers of prenatal alcohol exposure. Participants in this study were 10 children with a fetal alcohol spectrum disorder (FASD) and 15 healthy control (HC) children aged 3 to 6 years. All participants had normal hearing as determined by clinical screens. We measured their neurophysiological responses to auditory stimuli (1,000 Hz, 72 dB tone) using magnetoencephalography (MEG). We used a multidipole spatio-temporal modeling technique to identify the location and timecourse of cortical activity in response to the auditory tones. The timing and amplitude of the left and right superior temporal gyrus sources associated with activation of left and right primary/secondary auditory cortices were compared across groups. There was a significant delay in M100 and M200 latencies for the FASD children relative to the HC children (p = 0.01), when including age as a covariate. The within-subjects effect of hemisphere was not significant. A comparable delay in M100 and M200 latencies was observed in children across the FASD subtypes. Auditory delay revealed by MEG in children with FASDs may prove to be a useful neural marker of information processing difficulties in young children with prenatal alcohol exposure. The fact that delayed auditory responses were observed across the FASD spectrum suggests that it may be a sensitive measure of alcohol-induced brain damage. Therefore, this measure in conjunction with other clinical tools may prove useful for early identification of alcohol affected children, particularly those without dysmorphia. Copyright © 2012 by the Research Society on Alcoholism.

A Low-Cost System Based on Image Analysis for Monitoring the Crystal Growth Process.

PubMed

Venâncio, Fabrício; Rosário, Francisca F do; Cajaiba, João

2017-05-31

Many techniques are used to monitor one or more of the phenomena involved in the crystallization process. One of the challenges in crystal growth monitoring is finding techniques that allow direct interpretation of the data. The present study used a low-cost system, composed of a commercial webcam and a simple white LED (Light Emitting Diode) illuminator, to follow the calcium carbonate crystal growth process. The experiments were followed with focused beam reflectance measurement (FBRM), a common technique for obtaining information about the formation and growth of crystals. The images obtained in real time were treated with the red, blue, and green (RGB) system. The results showed a qualitative response of the system to crystal formation and growth processes, as there was an observed decrease in the signal as the growth process occurred. Control of the crystal growth was managed by increasing the viscosity of the test solution with the addition of monoethylene glycol (MEG) at 30% and 70% in a mass to mass relationship, providing different profiles of the RGB average curves. The decrease in the average RGB value became slower as the concentration of MEG was increased; this reflected a lag in the growth process that was proven by the FBRM.

Diffusion-weighted imaging for evaluating inflammatory activity in Crohn's disease: comparison with histopathology, conventional MRI activity scores, and faecal calprotectin.

PubMed

Pendsé, D A; Makanyanga, J C; Plumb, A A; Bhatnagar, G; Atkinson, D; Rodriguez-Justo, Manuel; Halligan, S; Taylor, S A

2017-01-01

To evaluate whether the extent of enteric diffusion-weighted imaging (DWI) signal abnormality reflects inflammatory burden in Crohn's disease (CD), and to compare qualitative and quantitative grading. 69 CD patients (35 male, age 16-78) undergoing MR enterography with DWI (MRE-D) and the same-day faecal calprotectin (cohort 1) were supplemented by 29 patients (19 male, age 16-70) undergoing MRE-D and terminal ileal biopsy (cohort 2). Global (cohort 1) and terminal ileal (cohort 2) DWI signal was graded (0 to 3) by 2 radiologists and segmental apparent diffusion coefficient (ADC) calculated. Data were compared to calprotectin and a validated MRI activity score [MEGS] (cohort 1), and a histopathological activity score (eAIS) (cohort 2) using nonparametric testing and rank correlation. Patients with normal (grades 0 and 1) DWI signal had lower calprotectin and MEGS than those with abnormal signal (grades 2 and 3) (160 vs. 492 μg/l, p = 0.0004, and 3.3 vs. 21, p < 0.0001), respectively. Calprotectin was lower if abnormal DWI affected <10 cm of small bowel compared to diffuse small and large bowel abnormality (236 vs. 571 μg, p = 0.009). The sensitivity and specificity for active disease (calprotectin > 120 μg/l) were 83% and 52%, respectively. There was a negative correlation between ileal MEGS and ADC (r = -0.41, p = 0.017). There was no significant difference in eAIS between qualitative DWI scores (p = 0.42). Mean ADC was not different in those with and without histological inflammation (2077 vs. 1622 × 10 -6 mm 2 /s, p = 0.10) CONCLUSIONS: Qualitative grading of DWI signal has utility in defining the burden of CD activity. Quantitative ADC measurements have poor discriminatory ability for segmental disease activity.

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

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks

PubMed Central

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

2017-01-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100 ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250 ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. PMID:27039703

Rapid neural discrimination of communicative gestures.

PubMed

Redcay, Elizabeth; Carlson, Thomas A

2015-04-01

Humans are biased toward social interaction. Behaviorally, this bias is evident in the rapid effects that self-relevant communicative signals have on attention and perceptual systems. The processing of communicative cues recruits a wide network of brain regions, including mentalizing systems. Relatively less work, however, has examined the timing of the processing of self-relevant communicative cues. In the present study, we used multivariate pattern analysis (decoding) approach to the analysis of magnetoencephalography (MEG) to study the processing dynamics of social-communicative actions. Twenty-four participants viewed images of a woman performing actions that varied on a continuum of communicative factors including self-relevance (to the participant) and emotional valence, while their brain activity was recorded using MEG. Controlling for low-level visual factors, we found early discrimination of emotional valence (70 ms) and self-relevant communicative signals (100 ms). These data offer neural support for the robust and rapid effects of self-relevant communicative cues on behavior. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Neuroimaging Techniques: a Conceptual Overview of Physical Principles, Contribution and History

NASA Astrophysics Data System (ADS)

Minati, Ludovico

2006-06-01

This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Given the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.

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

Minati, Ludovico

This paper is meant to provide a brief overview of the techniques currently used to image the brain and to study non-invasively its anatomy and function. After a historical summary in the first section, general aspects are outlined in the second section. The subsequent six sections survey, in order, computed tomography (CT), morphological magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), diffusion-tensor magnetic resonance imaging (DWI/DTI), positron emission tomography (PET), and electro- and magneto-encephalography (EEG/MEG) based imaging. Underlying physical principles, modelling and data processing approaches, as well as clinical and research relevance are briefly outlined for each technique. Givenmore » the breadth of the scope, there has been no attempt to be comprehensive. The ninth and final section outlines some aspects of active research in neuroimaging.« 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.

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.

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.

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

Functional Brain Imaging

PubMed Central

2006-01-01

Executive Summary Objective The objective of this analysis is to review a spectrum of functional brain imaging technologies to identify whether there are any imaging modalities that are more effective than others for various brain pathology conditions. This evidence-based analysis reviews magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) for the diagnosis or surgical management of the following conditions: Alzheimer’s disease (AD), brain tumours, epilepsy, multiple sclerosis (MS), and Parkinson’s disease (PD). Clinical Need: Target Population and Condition Alzheimer’s disease is a progressive, degenerative, neurologic condition characterized by cognitive impairment and memory loss. The Canadian Study on Health and Aging estimated that there will be 97,000 incident cases (about 60,000 women) of dementia (including AD) in Canada in 2006. In Ontario, there will be an estimated 950 new cases and 580 deaths due to brain cancer in 2006. Treatments for brain tumours include surgery and radiation therapy. However, one of the limitations of radiation therapy is that it damages tissue though necrosis and scarring. Computed tomography (CT) and magnetic resonance imaging (MRI) may not distinguish between radiation effects and resistant tissue, creating a potential role for functional brain imaging. Epilepsy is a chronic disorder that provokes repetitive seizures. In Ontario, the rate of epilepsy is estimated to be 5 cases per 1,000 people. Most people with epilepsy are effectively managed with drug therapy; but about 50% do not respond to drug therapy. Surgical resection of the seizure foci may be considered in these patients, and functional brain imaging may play a role in localizing the seizure foci. Multiple sclerosis is a progressive, inflammatory, demyelinating disease of the central nervous system (CNS). The cause of MS is unknown; however, it is thought to be due to a combination of etiologies, including genetic and environmental components. The prevalence of MS in Canada is 240 cases per 100,000 people. Parkinson’s disease is the most prevalent movement disorder; it affects an estimated 100,000 Canadians. Currently, the standard for measuring disease progression is through the use of scales, which are subjective measures of disease progression. Functional brain imaging may provide an objective measure of disease progression, differentiation between parkinsonian syndromes, and response to therapy. The Technology Being Reviewed Functional Brain Imaging Functional brain imaging technologies measure blood flow and metabolism. The results of these tests are often used in conjunction with structural imaging (e.g., MRI or CT). Positron emission tomography and MRS identify abnormalities in brain tissues. The former measures abnormalities through uptake of radiotracers in the brain, while the latter measures chemical shifts in metabolite ratios to identify abnormalities. The potential role of functional MRI (fMRI) is to identify the areas of the brain responsible for language, sensory and motor function (sensorimotor cortex), rather than identifying abnormalities in tissues. Magnetoencephalography measures magnetic fields of the electric currents in the brain, identifying aberrant activity. Magnetoencephalography may have the potential to localize seizure foci and to identify the sensorimotor cortex, visual cortex and auditory cortex. In terms of regulatory status, MEG and PET are licensed by Health Canada. Both MRS and fMRI use a MRI platform; thus, they do not have a separate licence from Health Canada. The radiotracers used in PET scanning are not licensed by Health Canada for general use but can be used through a Clinical Trials Application. Review Strategy The literature published up to September 2006 was searched in the following databases: MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Cochrane Database of Systematic Reviews, CENTRAL, and International Network of Agencies for Health Technology Assessment (INAHTA). The database search was supplemented with a search of relevant Web sites and a review of the bibliographies of selected papers. General inclusion criteria were applied to all conditions. Those criteria included the following: Full reports of systematic reviews, randomized controlled trials (RCTs), cohort-control studies, prospective cohort studies (PCS’), and retrospective studies. Sample sizes of at least 20 patients (≥ 10 with condition being reviewed). English-language studies. Human studies. Any age. Studying at least one of the following: fMRI, PET, MRS, or MEG. Functional brain imaging modality must be compared with a clearly defined reference standard. Must report at least one of the following outcomes: sensitivity, specificity, accuracy, positive predictive value (PPV), receiver operating characteristic curve, outcome measuring impact on diagnostic testing, treatment, patient health, or cost. Summary of Findings There is evidence to indicate that PET can accurately diagnose AD; however, at this time, there is no evidence to suggest that a diagnosis of AD with PET alters the clinical outcomes of patients. The addition of MRS or O-(2-18F-Fluoroethyl)-L-Tyrosine (FET)-PET to gadolinium (Gd)-enhanced MRI for distinguishing malignant from benign tumours during primary diagnosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients to distinguish malignant from benign tumours is unclear, because patients with a suspected brain tumour will likely undergo a biopsy despite additional imaging results. The addition of MRS, FET-PET, or MRI T2 to Gd-enhanced MRI for the differentiation of recurrence from radiation necrosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients with a suspected recurrence is in the monitoring of patients. Based on the evidence available, it is unclear if one of the imaging modalities (MRS, FET-PET, or MRI T2) offers significantly improved specificity over another. There may be a role for fMRI in the identification of surgical candidates for tumour resection; however, this requires further research. Based on the studies available, it is unclear if MEG has similar accuracy in localizing seizure foci to intracranial electroencephalogram (ICEEG). More high-quality research is needed to establish whether there is a difference in accuracy between MEG and ICEEG. The results of the studies comparing PET to noninvasive electroencephalogram (EEG) did not demonstrate that PET was more accurate at localizing seizure foci; however, there may be some specific conditions, such as tuberous sclerosis, where PET may be more accurate than noninvasive EEG. There may be some clinical utility for MEG or fMRI in presurgical functional mapping; however, this needs further investigation involving comparisons with other modalities. The clinical utility of MRS has yet to be established for patients with epilepsy. Positron emission tomography has high sensitivity and specificity in the diagnosis of PD and the differential diagnosis of parkinsonian syndromes; however, it is unclear at this time if the addition of PET in the diagnosis of these conditions contributes to the treatment and clinical outcomes of patients. There is limited clinical utility of functional brain imaging in the management of patients with MS at this time. Diagnosis of MS is established through clinical history, evoked potentials, and MRI. Magnetic resonance imaging can identify the multifocal white lesions and other structural characteristics of MS. PMID:23074493

Functional brain imaging: an evidence-based analysis.

PubMed

2006-01-01

The objective of this analysis is to review a spectrum of functional brain imaging technologies to identify whether there are any imaging modalities that are more effective than others for various brain pathology conditions. This evidence-based analysis reviews magnetoencephalography (MEG), magnetic resonance spectroscopy (MRS), positron emission tomography (PET), and functional magnetic resonance imaging (fMRI) for the diagnosis or surgical management of the following conditions: Alzheimer's disease (AD), brain tumours, epilepsy, multiple sclerosis (MS), and Parkinson's disease (PD). TARGET POPULATION AND CONDITION Alzheimer's disease is a progressive, degenerative, neurologic condition characterized by cognitive impairment and memory loss. The Canadian Study on Health and Aging estimated that there will be 97,000 incident cases (about 60,000 women) of dementia (including AD) in Canada in 2006. In Ontario, there will be an estimated 950 new cases and 580 deaths due to brain cancer in 2006. Treatments for brain tumours include surgery and radiation therapy. However, one of the limitations of radiation therapy is that it damages tissue though necrosis and scarring. Computed tomography (CT) and magnetic resonance imaging (MRI) may not distinguish between radiation effects and resistant tissue, creating a potential role for functional brain imaging. Epilepsy is a chronic disorder that provokes repetitive seizures. In Ontario, the rate of epilepsy is estimated to be 5 cases per 1,000 people. Most people with epilepsy are effectively managed with drug therapy; but about 50% do not respond to drug therapy. Surgical resection of the seizure foci may be considered in these patients, and functional brain imaging may play a role in localizing the seizure foci. Multiple sclerosis is a progressive, inflammatory, demyelinating disease of the central nervous system (CNS). The cause of MS is unknown; however, it is thought to be due to a combination of etiologies, including genetic and environmental components. The prevalence of MS in Canada is 240 cases per 100,000 people. Parkinson's disease is the most prevalent movement disorder; it affects an estimated 100,000 Canadians. Currently, the standard for measuring disease progression is through the use of scales, which are subjective measures of disease progression. Functional brain imaging may provide an objective measure of disease progression, differentiation between parkinsonian syndromes, and response to therapy. FUNCTIONAL BRAIN IMAGING: Functional brain imaging technologies measure blood flow and metabolism. The results of these tests are often used in conjunction with structural imaging (e.g., MRI or CT). Positron emission tomography and MRS identify abnormalities in brain tissues. The former measures abnormalities through uptake of radiotracers in the brain, while the latter measures chemical shifts in metabolite ratios to identify abnormalities. The potential role of functional MRI (fMRI) is to identify the areas of the brain responsible for language, sensory and motor function (sensorimotor cortex), rather than identifying abnormalities in tissues. Magnetoencephalography measures magnetic fields of the electric currents in the brain, identifying aberrant activity. Magnetoencephalography may have the potential to localize seizure foci and to identify the sensorimotor cortex, visual cortex and auditory cortex. In terms of regulatory status, MEG and PET are licensed by Health Canada. Both MRS and fMRI use a MRI platform; thus, they do not have a separate licence from Health Canada. The radiotracers used in PET scanning are not licensed by Health Canada for general use but can be used through a Clinical Trials Application. The literature published up to September 2006 was searched in the following databases: MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, Cochrane Database of Systematic Reviews, CENTRAL, and International Network of Agencies for Health Technology Assessment (INAHTA). The database search was supplemented with a search of relevant Web sites and a review of the bibliographies of selected papers. General inclusion criteria were applied to all conditions. Those criteria included the following: Full reports of systematic reviews, randomized controlled trials (RCTs), cohort-control studies, prospective cohort studies (PCS'), and retrospective studies.Sample sizes of at least 20 patients (≥ 10 with condition being reviewed).English-language studies.Human studies.Any age.STUDYING AT LEAST ONE OF THE FOLLOWING: fMRI, PET, MRS, or MEG.Functional brain imaging modality must be compared with a clearly defined reference standard.MUST REPORT AT LEAST ONE OF THE FOLLOWING OUTCOMES: sensitivity, specificity, accuracy, positive predictive value (PPV), receiver operating characteristic curve, outcome measuring impact on diagnostic testing, treatment, patient health, or cost. There is evidence to indicate that PET can accurately diagnose AD; however, at this time, there is no evidence to suggest that a diagnosis of AD with PET alters the clinical outcomes of patients. The addition of MRS or O-(2-(18)F-Fluoroethyl)-L-Tyrosine (FET)-PET to gadolinium (Gd)-enhanced MRI for distinguishing malignant from benign tumours during primary diagnosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients to distinguish malignant from benign tumours is unclear, because patients with a suspected brain tumour will likely undergo a biopsy despite additional imaging results. The addition of MRS, FET-PET, or MRI T2 to Gd-enhanced MRI for the differentiation of recurrence from radiation necrosis may provide a higher specificity than Gd-enhanced MRI alone. The clinical utility of additional imaging in patients with a suspected recurrence is in the monitoring of patients. Based on the evidence available, it is unclear if one of the imaging modalities (MRS, FET-PET, or MRI T2) offers significantly improved specificity over another. There may be a role for fMRI in the identification of surgical candidates for tumour resection; however, this requires further research. Based on the studies available, it is unclear if MEG has similar accuracy in localizing seizure foci to intracranial electroencephalogram (ICEEG). More high-quality research is needed to establish whether there is a difference in accuracy between MEG and ICEEG. The results of the studies comparing PET to noninvasive electroencephalogram (EEG) did not demonstrate that PET was more accurate at localizing seizure foci; however, there may be some specific conditions, such as tuberous sclerosis, where PET may be more accurate than noninvasive EEG. There may be some clinical utility for MEG or fMRI in presurgical functional mapping; however, this needs further investigation involving comparisons with other modalities. The clinical utility of MRS has yet to be established for patients with epilepsy. Positron emission tomography has high sensitivity and specificity in the diagnosis of PD and the differential diagnosis of parkinsonian syndromes; however, it is unclear at this time if the addition of PET in the diagnosis of these conditions contributes to the treatment and clinical outcomes of patients. There is limited clinical utility of functional brain imaging in the management of patients with MS at this time. Diagnosis of MS is established through clinical history, evoked potentials, and MRI. Magnetic resonance imaging can identify the multifocal white lesions and other structural characteristics of MS.

Diffuse Optical Tomography for Brain Imaging: Theory

NASA Astrophysics Data System (ADS)

Yuan, Zhen; Jiang, Huabei

Diffuse optical tomography (DOT) is a noninvasive, nonionizing, and inexpensive imaging technique that uses near-infrared light to probe tissue optical properties. Regional variations in oxy- and deoxy-hemoglobin concentrations as well as blood flow and oxygen consumption can be imaged by monitoring spatiotemporal variations in the absorption spectra. For brain imaging, this provides DOT unique abilities to directly measure the hemodynamic, metabolic, and neuronal responses to cells (neurons), and tissue and organ activations with high temporal resolution and good tissue penetration. DOT can be used as a stand-alone modality or can be integrated with other imaging modalities such as fMRI/MRI, PET/CT, and EEG/MEG in studying neurophysiology and pathology. This book chapter serves as an introduction to the basic theory and principles of DOT for neuroimaging. It covers the major aspects of advances in neural optical imaging including mathematics, physics, chemistry, reconstruction algorithm, instrumentation, image-guided spectroscopy, neurovascular and neurometabolic coupling, and clinical applications.

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.

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

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.

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.

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

GALA: group analysis leads to accuracy, a novel approach for solving the inverse problem in exploratory analysis of group MEG recordings

PubMed Central

Kozunov, Vladimir V.; Ossadtchi, Alexei

2015-01-01

Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping of cortical regions consistently active across subjects. In practice the first step often leads to a set of active cortical regions whose location and timecourses display a great amount of interindividual variability hindering the subsequent group analysis. We propose Group Analysis Leads to Accuracy (GALA)—a solution that combines the two steps into one. GALA takes advantage of individual variations of cortical geometry and sensor locations. It exploits the ensuing variability in electromagnetic forward model as a source of additional information. We assume that for different subjects functionally identical cortical regions are located in close proximity and partially overlap and their timecourses are correlated. This relaxed similarity constraint on the inverse solution can be expressed within a probabilistic framework, allowing for an iterative algorithm solving the inverse problem jointly for all subjects. A systematic simulation study showed that GALA, as compared with the standard min-norm approach, improves accuracy of true activity recovery, when accuracy is assessed both in terms of spatial proximity of the estimated and true activations and correct specification of spatial extent of the activated regions. This improvement obtained without using any noise normalization techniques for both solutions, preserved for a wide range of between-subject variations in both spatial and temporal features of regional activation. The corresponding activation timecourses exhibit significantly higher similarity across subjects. Similar results were obtained for a real MEG dataset of face-specific evoked responses. PMID:25954141

Effects of distraction on magnetoencephalographic responses ascending through C-fibers in humans.

PubMed

Qiu, Yunhai; Inui, Koji; Wang, Xiaohong; Nguyen, Binh Thi; Tran, Tuan Diep; Kakigi, Ryusuke

2004-03-01

Using magnetoencephalography (MEG), we evaluated the cerebral regions relating to second pain perception ascending through C-fibers and investigated the effect of distraction on each region. Thirteen normal subjects participated in this study. CO2 laser pulses were delivered to the dorsum of the left hand to selectively activate C-fibers. The MEG responses were analyzed using a multi-dipole model. (1) primary somatosensory cortex (SI), and (2) secondary somatosensory cortex (SII)--insula were the main generators for the primary component, 1M, whose mean peak latency was 744 ms. In addition to (1) and (2), (3) cingulate cortex and (4) medial temporal area (MT) were also activated for the subsequent component, 2M, whose mean peak latency was 947 ms. During a mental calculation task (Distraction), all 6 sources were significantly reduced in amplitude, but the SII-insula (P < 0.01) and cingulate cortex (P < 0.001) were more sensitive than the SI (P < 0.05) and MT (P < 0.05). We confirmed that SI in the contralateral hemisphere and SII-insula, cingulate cortex and MT in bilateral hemispheres play a major role in second pain perception, and all sites were much affected by a change of attention, indicating that these regions are related to the cognitive aspect of second pain perception. The SI, SII, cingulate and MT were activated during the C-fiber-related MEG response, and responses in these regions were significantly diminished during mental distraction.

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...

MNE Scan: Software for real-time processing of electrophysiological data.

PubMed

Esch, Lorenz; Sun, Limin; Klüber, Viktor; Lew, Seok; Baumgarten, Daniel; Grant, P Ellen; Okada, Yoshio; Haueisen, Jens; Hämäläinen, Matti S; Dinh, Christoph

2018-06-01

Magnetoencephalography (MEG) and Electroencephalography (EEG) are noninvasive techniques to study the electrophysiological activity of the human brain. Thus, they are well suited for real-time monitoring and analysis of neuronal activity. Real-time MEG/EEG data processing allows adjustment of the stimuli to the subject's responses for optimizing the acquired information especially by providing dynamically changing displays to enable neurofeedback. We introduce MNE Scan, an acquisition and real-time analysis software based on the multipurpose software library MNE-CPP. MNE Scan allows the development and application of acquisition and novel real-time processing methods in both research and clinical studies. The MNE Scan development follows a strict software engineering process to enable approvals required for clinical software. We tested the performance of MNE Scan in several device-independent use cases, including, a clinical epilepsy study, real-time source estimation, and Brain Computer Interface (BCI) application. Compared to existing tools we propose a modular software considering clinical software requirements expected by certification authorities. At the same time the software is extendable and freely accessible. We conclude that MNE Scan is the first step in creating a device-independent open-source software to facilitate the transition from basic neuroscience research to both applied sciences and clinical applications. Copyright © 2018 Elsevier B.V. All rights reserved.

Functional Imaging and Related Techniques: An Introduction for Rehabilitation Researchers

PubMed Central

Crosson, Bruce; Ford, Anastasia; McGregor, Keith M.; Meinzer, Marcus; Cheshkov, Sergey; Li, Xiufeng; Walker-Batson, Delaina; Briggs, Richard W.

2010-01-01

Functional neuroimaging and related neuroimaging techniques are becoming important tools for rehabilitation research. Functional neuroimaging techniques can be used to determine the effects of brain injury or disease on brain systems related to cognition and behavior and to determine how rehabilitation changes brain systems. These techniques include: functional magnetic resonance imaging (fMRI), positron emission tomography (PET), electroencephalography (EEG), magnetoencephalography (MEG), near infrared spectroscopy (NIRS), and transcranial magnetic stimulation (TMS). Related diffusion weighted magnetic resonance imaging techniques (DWI), including diffusion tensor imaging (DTI) and high angular resolution diffusion imaging (HARDI), can quantify white matter integrity. With the proliferation of these imaging techniques in rehabilitation research, it is critical that rehabilitation researchers, as well as consumers of rehabilitation research, become familiar with neuroimaging techniques, what they can offer, and their strengths and weaknesses The purpose to this review is to provide such an introduction to these neuroimaging techniques. PMID:20593321

Brain development during the preschool years

PubMed Central

Brown, Timothy T.; Jernigan, Terry L.

2012-01-01

The preschool years represent a time of expansive psychological growth, with the initial expression of many psychological abilities that will continue to be refined into young adulthood. Likewise, brain development during this age is characterized by its “blossoming” nature, showing some of its most dynamic and elaborative anatomical and physiological changes. In this article, we review human brain development during the preschool years, sampling scientific evidence from a variety of sources. First, we cover neurobiological foundations of early postnatal development, explaining some of the primary mechanisms seen at a larger scale within neuroimaging studies. Next, we review evidence from both structural and functional imaging studies, which now accounts for a large portion of our current understanding of typical brain development. Within anatomical imaging, we focus on studies of developing brain morphology and tissue properties, including diffusivity of white matter fiber tracts. We also present new data on changes during the preschool years in cortical area, thickness, and volume. Physiological brain development is then reviewed, touching on influential results from several different functional imaging and recording modalities in the preschool and early school-age years, including positron emission tomography (PET), electroencephalography (EEG) and event-related potentials (ERP), functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), and near-infrared spectroscopy (NIRS). Here, more space is devoted to explaining some of the key methodological factors that are required for interpretation. We end with a section on multimodal and multidimensional imaging approaches, which we believe will be critical for increasing our understanding of brain development and its relationship to cognitive and behavioral growth in the preschool years and beyond. PMID:23007644

Potential applications of microtesla magnetic resonance imaging detected using a superconducting quantum interference device

NASA Astrophysics Data System (ADS)

Myers, Whittier Ryan

This dissertation describes magnetic resonance imaging (MRI) of protons performed in a precession field of 132 muT. In order to increase the signal-to-noise ratio (SNR), a pulsed 40-300 mT magnetic field prepolarizes the sample spins and an untuned second-order superconducting gradiometer coupled to a low transition temperature superconducting quantum interference device (SQUID) detects the subsequent 5.6-kHz spin precession. Imaging sequences including multiple echoes and partial Fourier reconstruction are developed. Calculating the SNR of prepolarized SQUID-detected MRI shows that three-dimensional Fourier imaging yields higher SNR than slice-selection imaging. An experimentally demonstrated field-cycling pulse sequence and post-processing algorithm mitigate image artifacts caused by concomitant gradients in low-field MRI. The magnetic field noise of SQUID untuned detection is compared to the noise of SQUID tuned detection, conventional Faraday detection, and the Nyquist noise generated by conducting biological samples. A second-generation microtesla MRI system employing a low-noise SQUID is constructed to increase SNR. A 2.4-m cubic, eddy-current shield with 6-mm thick aluminum walls encloses the experiment to attenuate external noise. The measured noise is 0.75 fT Hz 1/2 referred to the bottom gradiometer loop. Solenoids wound from 30-strand braided wire to decrease Nyquist noise and cooled by either liquid nitrogen or water polarize the spins. Copper wire coils wound on wooden supports produce the imaging magnetic fields and field gradients. Water phantom images with 0.8 x 0.8 x 10 mm3 resolution have a SNR of 6. Three-dimensional 1.6 x 1.9 x 14 mm3 images of bell peppers and 3 x 3 x 26 mm3 in vivo images of the human arm are presented. Since contrast based on the transverse spin relaxation rate (T1 ) is enhanced at low magnetic fields, microtesla MRI could potentially be used for tumor imaging. The measured T1 of ex vivo normal and cancerous prostate tissue differ significantly at 132 muT. A single-sided MRI system designed for prostate imaging could achieve 3 x 3 x 5 mm3 resolution in 8 minutes. Existing SQUID-based magnetoencephalography (MEG) systems could be used as microtesla MRI detectors. A commercial 275-channel MEG system could acquire 6-minute brain images with (4 mm)3 resolution and SNR 16.

Distinguished Neuropsychologist Award Lecture 1999. The lesion(s) in traumatic brain injury: implications for clinical neuropsychology.

PubMed

Bigler, E D

2001-02-01

This paper overviews the current status of neuroimaging in neuropsychological outcome in traumatic brain injury (TBI). The pathophysiology of TBI is reviewed and integrated with expected neuroimaging and neuropsychological findings. The integration of clinical and quantitative magnetic resonance (QMR) imaging is the main topic of review, but these findings are integrated with single photon emission computed tomography (SPECT) and magnetoencephalography (MEG). Various clinical caveats are offered for the clinician.

Hybrid Molecule-Nanocrystal Photon Upconversion Across the Visible and Near-Infrared

DTIC Science & Technology

2015-07-10

applications in solar energy, biological imaging , and data storage. In this Letter, CdSe and PbSe semiconductor nanocrystals are combined with molecular...Goldschmidt, J. C. Absolute Upconversion Quantum Yield of β-NaYF4 Doped with Er3+ and External Quantum Efficiency of Upconverter Solar Cell Devices...C. Peak External Photocurrent Quantum Efficiency Exceeding 100% via MEG in a Quantum Dot Solar Cell . Science 2011, 334, 1530−1533. (37) Choi, J.-H

Neuroergonomics Deep Dive Literature Review, Volume 1: Neuroergonomics and Cognitive State

DTIC Science & Technology

2010-11-01

Neurophysiology, 108, 1-16. This paper compares TMS to TDCS . TDCS has very mild side effects when compared to those produced by TMS . Larger...use make it a good alternative to TMS . DC polarization can change the efficiency of cognitive processes without side effects. TDCS can alter verbal...with TMS and tDCS to better understand the effects of the stimulation. New imaging technologies such as DSI and MEG are also being considered

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.

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.

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.

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.

Alpha-band rhythm modulation under the condition of subliminal face presentation: MEG study.

PubMed

Sakuraba, Satoshi; Kobayashi, Hana; Sakai, Shinya; Yokosawa, Koichi

2013-01-01

The human brain has two streams to process visual information: a dorsal stream and a ventral stream. Negative potential N170 or its magnetic counterpart M170 is known as the face-specific signal originating from the ventral stream. It is possible to present a visual image unconsciously by using continuous flash suppression (CFS), which is a visual masking technique adopting binocular rivalry. In this work, magnetoencephalograms were recorded during presentation of the three invisible images: face images, which are processed by the ventral stream; tool images, which could be processed by the dorsal stream, and a blank image. Alpha-band activities detected by sensors that are sensitive to M170 were compared. The alpha-band rhythm was suppressed more during presentation of face images than during presentation of the blank image (p=.028). The suppression remained for about 1 s after ending presentations. However, no significant difference was observed between tool and other images. These results suggest that alpha-band rhythm can be modulated also by unconscious visual images.

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.

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.

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.

A different pattern of lateralised brain activity during processing of loved faces in men and women: a MEG study.

PubMed

Tiedt, Hannes O; Beier, Klaus M; Lueschow, Andreas; Pauls, Alfred; Weber, Joachim E

2014-12-01

Viewing personally familiar and loved faces evokes a distinct pattern of brain activity as demonstrated by research employing imaging and electrophysiological methods. The aim of the current investigation was to study the perception of loved faces combined with recalling past emotional experiences using whole-head magnetoencephalograpy (MEG). Twenty-eight participants (fourteen female) viewed photographs of their romantic partner as well as of two long-term friends while imagining a positive emotional encounter with the respective person. Face-stimuli evoked a slow and sustained shift of magnetic activity from 300ms post-stimulus onwards which differentiated loved from friends' faces in female participants and left-sided sensors only. This late-latency evoked magnetic field resembled (as its magnetic counterpart) ERP-modulations by affective content and memory, most notably the late positive potential (LPP). We discuss our findings in the light of studies suggesting greater responsiveness to affective cues in women as well as sex differences in autobiographical and emotional memory. Copyright © 2014 Elsevier B.V. All rights reserved.

Dynamics of scene representations in the human brain revealed by magnetoencephalography and deep neural networks.

PubMed

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

2017-06-01

Human scene recognition is a rapid multistep process evolving over time from single scene image to spatial layout processing. We used multivariate pattern analyses on magnetoencephalography (MEG) data to unravel the time course of this cortical process. Following an early signal for lower-level visual analysis of single scenes at ~100ms, we found a marker of real-world scene size, i.e. spatial layout processing, at ~250ms indexing neural representations robust to changes in unrelated scene properties and viewing conditions. For a quantitative model of how scene size representations may arise in the brain, we compared MEG data to a deep neural network model trained on scene classification. Representations of scene size emerged intrinsically in the model, and resolved emerging neural scene size representation. Together our data provide a first description of an electrophysiological signal for layout processing in humans, and suggest that deep neural networks are a promising framework to investigate how spatial layout representations emerge in the human brain. Copyright © 2017 The Authors. 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.

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.

Neural correlation of successful cognitive behaviour therapy for spider phobia: a magnetoencephalography study.

PubMed

Wright, Barry; Alderson-Day, Ben; Prendergast, Garreth; Kennedy, Juliette; Bennett, Sophie; Docherty, Mary; Whitton, Clare; Manea, Laura; Gouws, Andre; Tomlinson, Heather; Green, Gary

2013-12-30

Cognitive behavioural therapy (CBT) can be an effective treatment for spider phobia, but the underlying neural correlates of therapeutic change are yet to be specified. The present study used magnetoencephalography (MEG) to study responses within the first half second, to phobogenic stimuli in a group of individuals with spider phobia prior to treatment (n=12) and then in nine of them following successful CBT (where they could touch and manage live large common house spiders) at least 9 months later. We also compared responses to a group of age-matched healthy control participants (n=11). Participants viewed static photographs of real spiders, other fear-inducing images (e.g. snakes, sharks) and neutral stimuli (e.g. kittens). Beamforming methods were used to localise sources of significant power changes in response to stimuli. Prior to treatment, participants with spider phobia showed a significant maximum response in the right frontal pole when viewing images of real spiders specifically. No significant frontal response was observed for either control participants or participants with spider phobia post-treatment. In addition, participants' subjective ratings of spider stimuli significantly predicted peak responses in right frontal regions. The implications for understanding brain-based effects of cognitive therapies are discussed. © 2013 Published by Elsevier Ireland Ltd.

77 FR 32503 - Certain Polyester Staple Fiber From Taiwan: Preliminary Results of Antidumping Duty...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-06-01

... 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

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.

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

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.

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.

Frequency-dependent changes in sensorimotor and pain affective systems induced by empathy for pain.

PubMed

Motoyama, Yoshimasa; Ogata, Katsuya; Hoka, Sumio; Tobimatsu, Shozo

2017-01-01

Empathy for pain helps us to understand the pain of others indirectly. To better comprehend the processing of empathic pain, we report the frequency-dependent modulation of cortical oscillations induced by watching movies depicting pain using high-density electroencephalography (EEG), magnetoencephalography (MEG), and motor evoked potentials (MEP). Event-related desynchronization of EEG and MEG was assessed while participants viewed videos of painful (needle) or neutral (cotton swab) situations. The amplitudes of MEPs were also compared between the needle and cotton swab conditions. The degree of suppression in α/β band power was significantly increased, whereas that of γ band power was significantly decreased, in the needle condition compared with the cotton swab condition. EEG revealed that significant differences in α/β band were distributed in the right frontocentral and left parietooccipital regions, whereas significant γ band differences were distributed predominantly over the right hemisphere, which were confirmed by source estimation using MEG. There was a significant positive correlation between the difference in γ power of the two conditions and the visual analog scale subjective rating of aversion, but not in the α/β band. The amplitude of MEPs decreased in the needle condition, which confirmed the inhibition of the primary motor cortex. MEP suppression supports that modulation of cortical oscillations by viewing movies depicting pain involves sensorimotor processing. Our results suggest that α/β oscillations underlie the sensory qualities of others' pain, whereas the γ band reflects the cognitive aspect. Therefore, α/β and γ band oscillations are differentially involved in empathic pain processing under the condition of motor cortical suppression.

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.

Senior Research Fellow Wins Major International Science Award | News | NREL

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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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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

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

Enhanced Early Neuronal Processing of Food Pictures in Anorexia Nervosa: A Magnetoencephalography Study

PubMed Central

Scaife, Jessica C.; Park, Rebecca J.

2016-01-01

Neuroimaging studies in Anorexia Nervosa (AN) have shown increased activation in reward and cognitive control regions in response to food, and a behavioral attentional bias (AB) towards food stimuli is reported. This study aimed to further investigate the neural processing of food using magnetoencephalography (MEG). Participants were 13 females with restricting-type AN, 14 females recovered from restricting-type AN, and 15 female healthy controls. MEG data was acquired whilst participants viewed high- and low-calorie food pictures. Attention was assessed with a reaction time task and eye tracking. Time-series analysis suggested increased neural activity in response to both calorie conditions in the AN groups, consistent with an early AB. Increased activity was observed at 150 ms in the current AN group. Neuronal activity at this latency was at normal level in the recovered group; however, this group exhibited enhanced activity at 320 ms after stimulus. Consistent with previous studies, analysis in source space and behavioral data suggested enhanced attention and cognitive control processes in response to food stimuli in AN. This may enable avoidance of salient food stimuli and maintenance of dietary restraint in AN. A later latency of increased activity in the recovered group may reflect a reversal of this avoidance, with source space and behavioral data indicating increased visual and cognitive processing of food stimuli. PMID:27525258

Global Neuromagnetic Cortical Fields Have Non-Zero Velocity

PubMed Central

Alexander, David M.; Nikolaev, Andrey R.; Jurica, Peter; Zvyagintsev, Mikhail; Mathiak, Klaus; van Leeuwen, Cees

2016-01-01

Globally coherent patterns of phase can be obscured by analysis techniques that aggregate brain activity measures across-trials, whether prior to source localization or for estimating inter-areal coherence. We analyzed, at single-trial level, whole head MEG recorded during an observer-triggered apparent motion task. Episodes of globally coherent activity occurred in the delta, theta, alpha and beta bands of the signal in the form of large-scale waves, which propagated with a variety of velocities. Their mean speed at each frequency band was proportional to temporal frequency, giving a range of 0.06 to 4.0 m/s, from delta to beta. The wave peaks moved over the entire measurement array, during both ongoing activity and task-relevant intervals; direction of motion was more predictable during the latter. A large proportion of the cortical signal, measurable at the scalp, exists as large-scale coherent motion. We argue that the distribution of observable phase velocities in MEG is dominated by spatial filtering considerations in combination with group velocity of cortical activity. Traveling waves may index processes involved in global coordination of cortical activity. PMID:26953886

Cross-modal interactions during perception of audiovisual speech and nonspeech signals: an fMRI study.

PubMed

Hertrich, Ingo; Dietrich, Susanne; Ackermann, Hermann

2011-01-01

During speech communication, visual information may interact with the auditory system at various processing stages. Most noteworthy, recent magnetoencephalography (MEG) data provided first evidence for early and preattentive phonetic/phonological encoding of the visual data stream--prior to its fusion with auditory phonological features [Hertrich, I., Mathiak, K., Lutzenberger, W., & Ackermann, H. Time course of early audiovisual interactions during speech and non-speech central-auditory processing: An MEG study. Journal of Cognitive Neuroscience, 21, 259-274, 2009]. Using functional magnetic resonance imaging, the present follow-up study aims to further elucidate the topographic distribution of visual-phonological operations and audiovisual (AV) interactions during speech perception. Ambiguous acoustic syllables--disambiguated to /pa/ or /ta/ by the visual channel (speaking face)--served as test materials, concomitant with various control conditions (nonspeech AV signals, visual-only and acoustic-only speech, and nonspeech stimuli). (i) Visual speech yielded an AV-subadditive activation of primary auditory cortex and the anterior superior temporal gyrus (STG), whereas the posterior STG responded both to speech and nonspeech motion. (ii) The inferior frontal and the fusiform gyrus of the right hemisphere showed a strong phonetic/phonological impact (differential effects of visual /pa/ vs. /ta/) upon hemodynamic activation during presentation of speaking faces. Taken together with the previous MEG data, these results point at a dual-pathway model of visual speech information processing: On the one hand, access to the auditory system via the anterior supratemporal “what" path may give rise to direct activation of "auditory objects." On the other hand, visual speech information seems to be represented in a right-hemisphere visual working memory, providing a potential basis for later interactions with auditory information such as the McGurk effect.

Veterans with post-traumatic stress disorder exhibit altered emotional processing and attentional control during an emotional Stroop task.

PubMed

Khanna, M M; Badura-Brack, A S; McDermott, T J; Embury, C M; Wiesman, A I; Shepherd, A; Ryan, T J; Heinrichs-Graham, E; Wilson, T W

2017-08-01

Post-traumatic stress disorder (PTSD) is often associated with attention allocation and emotional regulation difficulties, but the brain dynamics underlying these deficits are unknown. The emotional Stroop task (EST) is an ideal means to monitor these difficulties, because participants are asked to attend to non-emotional aspects of the stimuli. In this study, we used magnetoencephalography (MEG) and the EST to monitor attention allocation and emotional regulation during the processing of emotionally charged stimuli in combat veterans with and without PTSD. A total of 31 veterans with PTSD and 20 without PTSD performed the EST during MEG. Three categories of stimuli were used, including combat-related, generally threatening and neutral words. MEG data were imaged in the time-frequency domain and the network dynamics were probed for differences in processing threatening and non-threatening words. Behaviorally, veterans with PTSD were significantly slower in responding to combat-related relative to neutral and generally threatening words. Veterans without PTSD exhibited no significant differences in responding to the three different word types. Neurophysiologically, we found a significant three-way interaction between group, word type and time period across multiple brain regions. Follow-up testing indicated stronger theta-frequency (4-8 Hz) responses in the right ventral prefrontal (0.4-0.8 s) and superior temporal cortices (0.6-0.8 s) of veterans without PTSD compared with those with PTSD during the processing of combat-related words. Our data indicated that veterans with PTSD exhibited deficits in attention allocation and emotional regulation when processing trauma cues, while those without PTSD were able to regulate emotion by directing attention away from threat.

Evaluation of MERIS products from Baltic Sea coastal waters rich in CDOM

NASA Astrophysics Data System (ADS)

Beltrán-Abaunza, J. M.; Kratzer, S.; Brockmann, C.

2013-11-01

In this study, retrievals of the medium resolution imaging spectrometer (MERIS) reflectances and water quality products using 4 different coastal processing algorithms freely available are assessed by comparison against sea-truthing data. The study is based on a pair-wise comparison using processor-dependent quality flags for the retrieval of valid common macro-pixels. This assessment is required in order to ensure the reliability of monitoring systems based on MERIS data, such as the Swedish coastal and lake monitoring system (http.vattenkvalitet.se). The results show that the pre-processing with the Improved Contrast between Ocean and Land (ICOL) processor, correcting for adjacency effects, improve the retrieval of spectral reflectance for all processors, Therefore, it is recommended that the ICOL processor should be applied when Baltic coastal waters are investigated. Chlorophyll was retrieved best using the FUB (Free University of Berlin) processing algorithm, although overestimations in the range 18-26.5%, dependent on the compared pairs, were obtained. At low chlorophyll concentrations (< 2.5 mg m-3), random errors dominated in the retrievals with the MEGS (MERIS ground segment processor) processor. The lowest bias and random errors were obtained with MEGS for suspended particulate matter, for which overestimations in te range of 8-16% were found. Only the FUB retrieved CDOM (Coloured Dissolved Organic Matter) correlate with in situ values. However, a large systematic underestimation appears in the estimates that nevertheless may be corrected for by using a~local correction factor. The MEGS has the potential to be used as an operational processing algorithm for the Himmerfjärden bay and adjacent areas, but it requires further improvement of the atmospheric correction for the blue bands and better definition at relatively low chlorophyll concentrations in presence of high CDOM attenuation.

Evaluation of MERIS products from Baltic Sea coastal waters rich in CDOM

NASA Astrophysics Data System (ADS)

Beltrán-Abaunza, J. M.; Kratzer, S.; Brockmann, C.

2014-05-01

In this study, retrievals of the medium resolution imaging spectrometer (MERIS) reflectances and water quality products using four different coastal processing algorithms freely available are assessed by comparison against sea-truthing data. The study is based on a pair-wise comparison using processor-dependent quality flags for the retrieval of valid common macro-pixels. This assessment is required in order to ensure the reliability of monitoring systems based on MERIS data, such as the Swedish coastal and lake monitoring system (http://vattenkvalitet.se). The results show that the pre-processing with the Improved Contrast between Ocean and Land (ICOL) processor, correcting for adjacency effects, improves the retrieval of spectral reflectance for all processors. Therefore, it is recommended that the ICOL processor should be applied when Baltic coastal waters are investigated. Chlorophyll was retrieved best using the FUB (Free University of Berlin) processing algorithm, although overestimations in the range 18-26.5%, dependent on the compared pairs, were obtained. At low chlorophyll concentrations (< 2.5 mg m-3), data dispersion dominated in the retrievals with the MEGS (MERIS ground segment processor) processor. The lowest bias and data dispersion were obtained with MEGS for suspended particulate matter, for which overestimations in the range of 8-16% were found. Only the FUB retrieved CDOM (coloured dissolved organic matter) correlate with in situ values. However, a large systematic underestimation appears in the estimates that nevertheless may be corrected for by using a local correction factor. The MEGS has the potential to be used as an operational processing algorithm for the Himmerfjärden bay and adjacent areas, but it requires further improvement of the atmospheric correction for the blue bands and better definition at relatively low chlorophyll concentrations in the presence of high CDOM attenuation.

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

Connectivity in MEG resting-state networks increases after resective surgery for low-grade glioma and correlates with improved cognitive performance☆

PubMed Central

van Dellen, E.; de Witt Hamer, P.C.; Douw, L.; Klein, M.; Heimans, J.J.; Stam, C.J.; Reijneveld, J.C.; Hillebrand, A.

2012-01-01

Purpose Low-grade glioma (LGG) patients often have cognitive deficits. Several disease- and treatment related factors affect cognitive processing. Cognitive outcome of resective surgery is unpredictable, both for improvement and deterioration, especially for complex domains such as attention and executive functioning. MEG analysis of resting-state networks (RSNs) is a good candidate for presurgical prediction of cognitive outcome. In this study, we explore the relation between alterations in connectivity of RSNs and changes in cognitive processing after resective surgery, as a stepping stone to ultimately predict postsurgical cognitive outcome. Methods Ten patients with LGG were included, who had no adjuvant therapy. MEG recording and neuropsychological assessment were obtained before and after resective surgery. MEG data were recorded during a no-task eyes-closed condition, and projected to the anatomical space of the AAL atlas. Alterations in functional connectivity, as characterized by the phase lag index (PLI), within the default mode network (DMN), executive control network (ECN), and left- and right-sided frontoparietal networks (FPN) were compared to cognitive changes. Results Lower alpha band DMN connectivity was increased after surgery, and this increase was related to improved verbal memory functioning. Similarly, right FPN connectivity was increased after resection in the upper alpha band, which correlated with improved attention, working memory and executive functioning. Discussion Increased alpha band RSN functional connectivity in MEG recordings correlates with improved cognitive outcome after resective surgery. The mechanisms resulting in functional connectivity alterations after resection remain to be elucidated. Importantly, our findings indicate that connectivity of MEG RSNs may be used for presurgical prediction of cognitive outcome in future studies. PMID:24179752

[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.

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.

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.

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.

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"…

Improved method for retinotopy constrained source estimation of visual evoked responses

PubMed Central

Hagler, Donald J.; Dale, Anders M.

2011-01-01

Retinotopy constrained source estimation (RCSE) is a method for non-invasively measuring the time courses of activation in early visual areas using magnetoencephalography (MEG) or electroencephalography (EEG). Unlike conventional equivalent current dipole or distributed source models, the use of multiple, retinotopically-mapped stimulus locations to simultaneously constrain the solutions allows for the estimation of independent waveforms for visual areas V1, V2, and V3, despite their close proximity to each other. We describe modifications that improve the reliability and efficiency of this method. First, we find that increasing the number and size of visual stimuli results in source estimates that are less susceptible to noise. Second, to create a more accurate forward solution, we have explicitly modeled the cortical point spread of individual visual stimuli. Dipoles are represented as extended patches on the cortical surface, which take into account the estimated receptive field size at each location in V1, V2, and V3 as well as the contributions from contralateral, ipsilateral, dorsal, and ventral portions of the visual areas. Third, we implemented a map fitting procedure to deform a template to match individual subject retinotopic maps derived from functional magnetic resonance imaging (fMRI). This improves the efficiency of the overall method by allowing automated dipole selection, and it makes the results less sensitive to physiological noise in fMRI retinotopy data. Finally, the iteratively reweighted least squares (IRLS) method was used to reduce the contribution from stimulus locations with high residual error for robust estimation of visual evoked responses. PMID:22102418

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.

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.

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

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.

Language in context: Characterizing the comprehension of referential expressions with MEG.

PubMed

Brodbeck, Christian; Pylkkänen, Liina

2017-02-15

A critical component of comprehending language in context is identifying the entities that individual linguistic expressions refer to. While previous research has shown that language comprehenders resolve reference quickly and incrementally, little is currently known about the neural basis of successful reference resolution. Using source localized MEG, we provide evidence across 3 experiments and 2 languages that successful reference resolution in simple visual displays is associated with increased activation in the medial parietal lobe. In each trial, participants saw a simple visual display containing three objects which constituted the referential domain. Target referential expressions were embedded in questions about the displays. By varying the displays, we manipulated referential status while keeping the linguistic expressions constant. Follow-up experiments addressed potential interactions of reference resolution with linguistic predictiveness and pragmatic plausibility. Notably, we replicated the effect in Arabic, a language that differs in a structurally informative way from English while keeping referential aspects parallel to our two English studies. Distributed minimum norm estimates of MEG data consistently indicated that reference resolution is associated with increased activity in the medial parietal lobe. With one exception, the timing of the onset of the medial parietal response fell into a mid-latency time-window at 350-500ms after the onset of the resolving word. Through concurrent EEG recordings on a subset of subjects we also describe the EEG topography of the effect of reference resolution, which makes the result available for comparison with a larger existing literature. Our results extend previous reports that medial parietal lobe is involved in referential language processing, indicating that it is relevant for reference resolution to individual referents, and suggests avenues for future research. Copyright © 2016 Elsevier Inc. All rights reserved.

Frequency-dependent changes in sensorimotor and pain affective systems induced by empathy for pain

PubMed Central

Motoyama, Yoshimasa; Ogata, Katsuya; Hoka, Sumio; Tobimatsu, Shozo

2017-01-01

Background Empathy for pain helps us to understand the pain of others indirectly. To better comprehend the processing of empathic pain, we report the frequency-dependent modulation of cortical oscillations induced by watching movies depicting pain using high-density electroencephalography (EEG), magnetoencephalography (MEG), and motor evoked potentials (MEP). Methods Event-related desynchronization of EEG and MEG was assessed while participants viewed videos of painful (needle) or neutral (cotton swab) situations. The amplitudes of MEPs were also compared between the needle and cotton swab conditions. Results The degree of suppression in α/β band power was significantly increased, whereas that of γ band power was significantly decreased, in the needle condition compared with the cotton swab condition. EEG revealed that significant differences in α/β band were distributed in the right frontocentral and left parietooccipital regions, whereas significant γ band differences were distributed predominantly over the right hemisphere, which were confirmed by source estimation using MEG. There was a significant positive correlation between the difference in γ power of the two conditions and the visual analog scale subjective rating of aversion, but not in the α/β band. The amplitude of MEPs decreased in the needle condition, which confirmed the inhibition of the primary motor cortex. Conclusion MEP suppression supports that modulation of cortical oscillations by viewing movies depicting pain involves sensorimotor processing. Our results suggest that α/β oscillations underlie the sensory qualities of others’ pain, whereas the γ band reflects the cognitive aspect. Therefore, α/β and γ band oscillations are differentially involved in empathic pain processing under the condition of motor cortical suppression. PMID:28615963

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…

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.

PIV/HPIV Film Analysis Software Package

NASA Technical Reports Server (NTRS)

Blackshire, James L.

1997-01-01

A PIV/HPIV film analysis software system was developed that calculates the 2-dimensional spatial autocorrelations of subregions of Particle Image Velocimetry (PIV) or Holographic Particle Image Velocimetry (HPIV) film recordings. The software controls three hardware subsystems including (1) a Kodak Megaplus 1.4 camera and EPIX 4MEG framegrabber subsystem, (2) an IEEE/Unidex 11 precision motion control subsystem, and (3) an Alacron I860 array processor subsystem. The software runs on an IBM PC/AT host computer running either the Microsoft Windows 3.1 or Windows 95 operating system. It is capable of processing five PIV or HPIV displacement vectors per second, and is completely automated with the exception of user input to a configuration file prior to analysis execution for update of various system parameters.

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…

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.

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.

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.

Early visual responses predict conscious face perception within and between subjects during binocular rivalry

PubMed Central

Sandberg, Kristian; Bahrami, Bahador; Kanai, Ryota; Barnes, Gareth Robert; Overgaard, Morten; Rees, Geraint

2014-01-01

Previous studies indicate that conscious face perception may be related to neural activity in a large time window around 170-800ms after stimulus presentation, yet in the majority of these studies changes in conscious experience are confounded with changes in physical stimulation. Using multivariate classification on MEG data recorded when participants reported changes in conscious perception evoked by binocular rivalry between a face and a grating, we showed that only MEG signals in the 120-320ms time range, peaking at the M170 around 180ms and the P2m at around 260ms, reliably predicted conscious experience. Conscious perception could not only be decoded significantly better than chance from the sensors that showed the largest average difference, as previous studies suggest, but also from patterns of activity across groups of occipital sensors that individually were unable to predict perception better than chance. Additionally, source space analyses showed that sources in the early and late visual system predicted conscious perception more accurately than frontal and parietal sites, although conscious perception could also be decoded there. Finally, the patterns of neural activity associated with conscious face perception generalized from one participant to another around the times of maximum prediction accuracy. Our work thus demonstrates that the neural correlates of particular conscious contents (here, faces) are highly consistent in time and space within individuals and that these correlates are shared to some extent between individuals. PMID:23281780

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.

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

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.

Active Region Soft X-Ray Spectra as Observed Using Sounding Rocket Measurements from the Solar Aspect Monitor (SAM), - a Modified SDO/EVE Instrument

NASA Astrophysics Data System (ADS)

Wieman, S. R.; Didkovsky, L. V.; Woods, T. N.; Jones, A. R.; Caspi, A.; Warren, H. P.

2015-12-01

Observations of solar active regions (ARs) in the soft x-ray spectral range (0.5 to 3.0 nm) were made on sounding rocket flight NASA 36.290 using a modified Solar Aspect Monitor (SAM), a pinhole camera on the EUV Variability Experiment (EVE) sounding rocket instrument. The suite of EVE rocket instruments is designed for under-flight calibrations of the orbital EVE on SDO. While the sounding rocket EVE instrument is for the most part a duplicate of the EVE on SDO, the SAM channel on the rocket version was modified in 2012 to include a free-standing transmission grating so that it could provide spectrally resolved images of the solar disk with the best signal to noise ratio for the brightest features on it, such as ARs. Calibrations of the EVE sounding rocket instrument at the National Institute of Standards and Technology Synchrotron Ultraviolet Radiation Facility (NIST SURF) have provided a measurement of the SAM absolute spectral response function and a mapping of wavelength separation in the grating diffraction pattern. For solar observations, this spectral separation is on a similar scale to the spatial size of the AR on the CCD, so dispersed AR images associated with emission lines of similar wavelength tend to overlap. Furthermore, SAM shares a CCD detector with MEGS-A, a separate EVE spectrometer channel, and artifacts of the MEGS-A signal (a set of bright spectral lines) appear in the SAM images. For these reasons some processing and analysis of the solar images obtained by SAM must be performed in order to determine spectra of the observed ARs. We present a method for determining AR spectra from the SAM rocket images and report initial soft X-ray spectra for two of the major active regions (AR11877 and AR11875) observed on flight 36.290 on 21 October 2013 at about 18:30 UT. We also compare our results with concurrent measurements from other solar soft x-ray instrumentation.

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

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.

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.

Xenomelia: a new right parietal lobe syndrome.

PubMed

McGeoch, Paul D; Brang, David; Song, Tao; Lee, Roland R; Huang, Mingxiong; Ramachandran, V S

2011-12-01

Damage to the right parietal lobe has long been associated with various disorders of body image. The authors have recently suggested that an unusual behavioural condition in which otherwise rational individuals desire the amputation of a healthy limb might also arise from right parietal dysfunction. Four subjects who desired the amputation of healthy legs (two right, one left and one, at first, bilateral and then left only) were recruited and underwent magnetoencephalography (MEG) scans during tactile stimulation of sites above and below the desired amputation line. Regions of interest (ROIs) in each hemisphere (superior parietal lobule (SPL), inferior parietal lobule, S1, M1, insula, premotor cortex and precuneus) were defined using FreeSurfer software. Analysis of average MEG activity across the 40-140 ms post-stimulation timeframe was carried out using an unpaired t test. This revealed significantly reduced activation only in the right SPL ROI for the subjects' affected legs when compared with both subjects' unaffected legs and that of controls. The right SPL is a cortical area that appears ideally placed to unify disparate sensory inputs to create a coherent sense of having a body. The authors propose that inadequate activation of the right SPL leads to the unnatural situation in which the sufferers can feel the limb in question being touched without it actually incorporating into their body image, with a resulting desire for amputation. The authors introduce the term 'xenomelia' as a more appropriate name than apotemnophilia or body integrity identity disorder, for what appears to be an unrecognised right parietal lobe syndrome.

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.

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.

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,…

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.

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

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

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.

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

BA3b and BA1 activate in a serial fashion after median nerve stimulation: direct evidence from combining source analysis of evoked fields and cytoarchitectonic probabilistic maps.

PubMed

Papadelis, Christos; Eickhoff, Simon B; Zilles, Karl; Ioannides, Andreas A

2011-01-01

This study combines source analysis imaging data for early somatosensory processing and the probabilistic cytoarchitectonic maps (PCMs). Human somatosensory evoked fields (SEFs) were recorded by stimulating left and right median nerves. Filtering the recorded responses in different frequency ranges identified the most responsive frequency band. The short-latency averaged SEFs were analyzed using a single equivalent current dipole (ECD) model and magnetic field tomography (MFT). The identified foci of activity were superimposed with PCMs. Two major components of opposite polarity were prominent around 21 and 31 ms. A weak component around 25 ms was also identified. For the most responsive frequency band (50-150 Hz) ECD and MFT revealed one focal source at the contralateral Brodmann area 3b (BA3b) at the peak of N20. The component ~25 ms was localised in Brodmann area 1 (BA1) in 50-150 Hz. By using ECD, focal generators around 28-30 ms located initially in BA3b and 2 ms later to BA1. MFT also revealed two focal sources - one in BA3b and one in BA1 for these latencies. Our results provide direct evidence that the earliest cortical response after median nerve stimulation is generated within the contralateral BA3b. BA1 activation few milliseconds later indicates a serial mode of somatosensory processing within cytoarchitectonic SI subdivisions. Analysis of non-invasive magnetoencephalography (MEG) data and the use of PCMs allow unambiguous and quantitative (probabilistic) interpretation of cytoarchitectonic identity of activated areas following median nerve stimulation, even with the simple ECD model, but only when the model fits the data extremely well. Copyright © 2010 Elsevier Inc. All rights reserved.

Exploration Review

USGS Publications Warehouse

Wilburn, D.R.; Stanley, K.A.

2013-01-01

This summary of international mineral exploration activities for 2012 draws upon information from industry sources, published literature and U.S. Geological Survey (USGS) specialists. The summary provides data on exploration budgets by region and mineral commodity, identifies significant mineral discoveries and areas of mineral exploration, discusses government programs affecting the mineral exploration industry and presents analyses of exploration activities performed by the mineral industry. Three sources of information are reported and analyzed in this annual review of international exploration for 2012: 1) budgetary statistics expressed in U.S. nominal dollars provided by SNL Metals Economics Group (MEG) of Halifax, Nova Scotia; 2) regional and site-specific exploration activities that took place in 2012 as compiled by the USGS and 3) regional events including economic, social and political conditions that affected exploration activities, which were derived from published sources and unpublished discussions with USGS and industry specialists.

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.