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

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.

Source-space ICA for MEG source imaging.

PubMed

Jonmohamadi, Yaqub; Jones, Richard D

2016-02-01

One of the most widely used approaches in electroencephalography/magnetoencephalography (MEG) source imaging is application of an inverse technique (such as dipole modelling or sLORETA) on the component extracted by independent component analysis (ICA) (sensor-space ICA + inverse technique). The advantage of this approach over an inverse technique alone is that it can identify and localize multiple concurrent sources. Among inverse techniques, the minimum-variance beamformers offer a high spatial resolution. However, in order to have both high spatial resolution of beamformer and be able to take on multiple concurrent sources, sensor-space ICA + beamformer is not an ideal combination. We propose source-space ICA for MEG as a powerful alternative approach which can provide the high spatial resolution of the beamformer and handle multiple concurrent sources. The concept of source-space ICA for MEG is to apply the beamformer first and then singular value decomposition + ICA. In this paper we have compared source-space ICA with sensor-space ICA both in simulation and real MEG. The simulations included two challenging scenarios of correlated/concurrent cluster sources. Source-space ICA provided superior performance in spatial reconstruction of source maps, even though both techniques performed equally from a temporal perspective. Real MEG from two healthy subjects with visual stimuli were also used to compare performance of sensor-space ICA and source-space ICA. We have also proposed a new variant of minimum-variance beamformer called weight-normalized linearly-constrained minimum-variance with orthonormal lead-field. As sensor-space ICA-based source reconstruction is popular in EEG and MEG imaging, and given that source-space ICA has superior spatial performance, it is expected that source-space ICA will supersede its predecessor in many applications.

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.

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.

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

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.

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

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

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.

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.

Efficient charge-carrier extraction from Ag₂S quantum dots prepared by the SILAR method for utilization of multiple exciton generation.

PubMed

Zhang, Xiaoliang; Liu, Jianhua; Johansson, Erik M J

2015-01-28

The utilization of electron-hole pairs (EHPs) generated from multiple excitons in quantum dots (QDs) is of great interest toward efficient photovoltaic devices and other optoelectronic devices; however, extraction of charge carriers remains difficult. Herein, we extract photocharges from Ag2S QDs and investigate the dependence of the electric field on the extraction of charges from multiple exciton generation (MEG). Low toxic Ag2S QDs are directly grown on TiO2 mesoporous substrates by employing the successive ionic layer adsorption and reaction (SILAR) method. The contact between QDs is important for the initial charge separation after MEG and for the carrier transport, and the space between neighbor QDs decreases with more SILAR cycles, resulting in better charge extraction. At the optimal electric field for extraction of photocharges, the results suggest that the threshold energy (hνth) for MEG is 2.41Eg. The results reveal that Ag2S QD is a promising material for efficient extraction of charges from MEG and that QDs prepared by SILAR have an advantageous electrical contact facilitating charge separation and extraction.

Broadband ultrafast transient absorption of multiple exciton dynamics in lead sulfide nanocrystals

NASA Astrophysics Data System (ADS)

Gesuele, Felice; Wong, Chee Wei; Sfeir, Matthew; Misewich, James; Koh, Weonkyu; Murray, Christopher

2011-03-01

Multiple exciton generation (MEG) is under intense investigation as potential third-generation solar photovoltaics with efficiencies beyond the Shockley-Queisser limit. We examine PbS nanocrystals, dispersed and vigorously stirred in TCE solution, by means of supercontinuum femtosecond transient absorption (TA). TA spectra show the presence of first and second order bleaches for the 1Sh-Se and 1Ph-Pe excitonic transition while photoinduced absorption for the 1Sh,e-Ph,e transitions. We found evidence of carrier multiplication (MEG for single absorbed photon) from the analysis of the first and second order bleaches, in the limit of low number of absorbed photons (Nabs ~ 0.01), for energy three times and four times the Energy gap. The MEG efficiency, derived from the ratio between early-time to long-time TA signal, presents a strongly dispersive behavior with maximum red shifted respect the first absorption peak. Analysis of population dynamics shows that in presence of biexciton, the 1Sh-Se bleach peak is red-shifted indicating a positive binding energy. MEG efficiency estimation will be discussed with regards to spectral integration, correlated higher-order and first excitonic transitions, as well as the nanocrystal morphologies.

Extreme Ultraviolet Variability Experiment (EVE) Multiple EUV Grating Spectrographs (MEGS): Radiometric Calibrations and Results

NASA Technical Reports Server (NTRS)

Hock, R. A.; Woods, T. N.; Crotser, D.; Eparvier, F. G.; Woodraska, D. L.; Chamberlin, P. C.; Woods, E. C.

2010-01-01

The NASA Solar Dynamics Observatory (SDO), scheduled for launch in early 2010, incorporates a suite of instruments including the Extreme Ultraviolet Variability Experiment (EVE). EVE has multiple instruments including the Multiple Extreme ultraviolet Grating Spectrographs (MEGS) A, B, and P instruments, the Solar Aspect Monitor (SAM), and the Extreme ultraviolet SpectroPhotometer (ESP). The radiometric calibration of EVE, necessary to convert the instrument counts to physical units, was performed at the National Institute of Standards and Technology (NIST) Synchrotron Ultraviolet Radiation Facility (SURF III) located in Gaithersburg, Maryland. This paper presents the results and derived accuracy of this radiometric calibration for the MEGS A, B, P, and SAM instruments, while the calibration of the ESP instrument is addressed by Didkovsky et al. . In addition, solar measurements that were taken on 14 April 2008, during the NASA 36.240 sounding-rocket flight, are shown for the prototype EVE instruments.

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 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

Synaptic Plasticity Enables Adaptive Self-Tuning Critical Networks

PubMed Central

Stepp, Nigel; Plenz, Dietmar; Srinivasa, Narayan

2015-01-01

During rest, the mammalian cortex displays spontaneous neural activity. Spiking of single neurons during rest has been described as irregular and asynchronous. In contrast, recent in vivo and in vitro population measures of spontaneous activity, using the LFP, EEG, MEG or fMRI suggest that the default state of the cortex is critical, manifested by spontaneous, scale-invariant, cascades of activity known as neuronal avalanches. Criticality keeps a network poised for optimal information processing, but this view seems to be difficult to reconcile with apparently irregular single neuron spiking. Here, we simulate a 10,000 neuron, deterministic, plastic network of spiking neurons. We show that a combination of short- and long-term synaptic plasticity enables these networks to exhibit criticality in the face of intrinsic, i.e. self-sustained, asynchronous spiking. Brief external perturbations lead to adaptive, long-term modification of intrinsic network connectivity through long-term excitatory plasticity, whereas long-term inhibitory plasticity enables rapid self-tuning of the network back to a critical state. The critical state is characterized by a branching parameter oscillating around unity, a critical exponent close to -3/2 and a long tail distribution of a self-similarity parameter between 0.5 and 1. PMID:25590427

Automated Detection of Epileptic Biomarkers in Resting-State Interictal MEG Data

PubMed Central

Soriano, Miguel C.; Niso, Guiomar; Clements, Jillian; Ortín, Silvia; Carrasco, Sira; Gudín, María; Mirasso, Claudio R.; Pereda, Ernesto

2017-01-01

Certain differences between brain networks of healthy and epilectic subjects have been reported even during the interictal activity, in which no epileptic seizures occur. Here, magnetoencephalography (MEG) data recorded in the resting state is used to discriminate between healthy subjects and patients with either idiopathic generalized epilepsy or frontal focal epilepsy. Signal features extracted from interictal periods without any epileptiform activity are used to train a machine learning algorithm to draw a diagnosis. This is potentially relevant to patients without frequent or easily detectable spikes. To analyze the data, we use an up-to-date machine learning algorithm and explore the benefits of including different features obtained from the MEG data as inputs to the algorithm. We find that the relative power spectral density of the MEG time-series is sufficient to distinguish between healthy and epileptic subjects with a high prediction accuracy. We also find that a combination of features such as the phase-locked value and the relative power spectral density allow to discriminate generalized and focal epilepsy, when these features are calculated over a filtered version of the signals in certain frequency bands. Machine learning algorithms are currently being applied to the analysis and classification of brain signals. It is, however, less evident to identify the proper features of these signals that are prone to be used in such machine learning algorithms. Here, we evaluate the influence of the input feature selection on a clinical scenario to distinguish between healthy and epileptic subjects. Our results indicate that such distinction is possible with a high accuracy (86%), allowing the discrimination between idiopathic generalized and frontal focal epilepsy types. PMID:28713260

Frequency of gamma oscillations in humans is modulated by velocity of visual motion

PubMed Central

Butorina, Anna V.; Sysoeva, Olga V.; Prokofyev, Andrey O.; Nikolaeva, Anastasia Yu.; Stroganova, Tatiana A.

2015-01-01

Gamma oscillations are generated in networks of inhibitory fast-spiking (FS) parvalbumin-positive (PV) interneurons and pyramidal cells. In animals, gamma frequency is modulated by the velocity of visual motion; the effect of velocity has not been evaluated in humans. In this work, we have studied velocity-related modulations of gamma frequency in children using MEG/EEG. We also investigated whether such modulations predict the prominence of the “spatial suppression” effect (Tadin D, Lappin JS, Gilroy LA, Blake R. Nature 424: 312-315, 2003) that is thought to depend on cortical center-surround inhibitory mechanisms. MEG/EEG was recorded in 27 normal boys aged 8–15 yr while they watched high-contrast black-and-white annular gratings drifting with velocities of 1.2, 3.6, and 6.0°/s and performed a simple detection task. The spatial suppression effect was assessed in a separate psychophysical experiment. MEG gamma oscillation frequency increased while power decreased with increasing velocity of visual motion. In EEG, the effects were less reliable. The frequencies of the velocity-specific gamma peaks were 64.9, 74.8, and 87.1 Hz for the slow, medium, and fast motions, respectively. The frequency of the gamma response elicited during slow and medium velocity of visual motion decreased with subject age, whereas the range of gamma frequency modulation by velocity increased with age. The frequency modulation range predicted spatial suppression even after controlling for the effect of age. We suggest that the modulation of the MEG gamma frequency by velocity of visual motion reflects excitability of cortical inhibitory circuits and can be used to investigate their normal and pathological development in the human brain. PMID:25925324

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

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.

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

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.

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.

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

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

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

PubMed

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

2017-10-21

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

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.

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

Statistical technique for analysing functional connectivity of multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman

2011-03-15

A new statistical technique, the Cox method, used for analysing functional connectivity of simultaneously recorded multiple spike trains is presented. This method is based on the theory of modulated renewal processes and it estimates a vector of influence strengths from multiple spike trains (called reference trains) to the selected (target) spike train. Selecting another target spike train and repeating the calculation of the influence strengths from the reference spike trains enables researchers to find all functional connections among multiple spike trains. In order to study functional connectivity an "influence function" is identified. This function recognises the specificity of neuronal interactions and reflects the dynamics of postsynaptic potential. In comparison to existing techniques, the Cox method has the following advantages: it does not use bins (binless method); it is applicable to cases where the sample size is small; it is sufficiently sensitive such that it estimates weak influences; it supports the simultaneous analysis of multiple influences; it is able to identify a correct connectivity scheme in difficult cases of "common source" or "indirect" connectivity. The Cox method has been thoroughly tested using multiple sets of data generated by the neural network model of the leaky integrate and fire neurons with a prescribed architecture of connections. The results suggest that this method is highly successful for analysing functional connectivity of simultaneously recorded multiple spike trains. Copyright © 2011 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.

Plasmonically enhanced electromotive force of narrow bandgap PbS QD-based photovoltaics.

PubMed

Li, Xiaowei; McNaughter, Paul D; O'Brien, Paul; Minamimoto, Hiro; Murakoshi, Kei

2018-05-30

Electromotive force of photovoltaics is a key to define the output power density of photovoltaics. Multiple exciton generation (MEG) exhibited by semiconductor quantum dots (QDs) has great potential to enhance photovoltaic performance owing to the ability to generate more than one electron-hole pairs when absorbing a single photon. However, even in MEG-based photovoltaics, limitation of modifying the electromotive force exists due to the intrinsic electrochemical potential of the conduction band-edges of QDs. Here we report a pronouncedly improved photovoltaic performance by constructing a PbS QD-sensitized electrode that comprises plasmon-active Au nanoparticles embedded in a titanium dioxide thin film. Significant enhancement on electromotive force is characterized by the onset potential of photocurrent generation using MEG-effective PbS QDs with a narrow bandgap energy (Eg = 0.9 eV). By coupling with localized surface plasmon resonance (LSPR), such QDs exhibit improved photoresponses and the highest output power density over the other QDs with larger bandgap energies (Eg = 1.1 and 1.7 eV) under visible light irradiation. The wavelength-dependent onset potential and the output power density suggest effective electron injection owing to the enhanced density of electrons excited by energy overlapping between MEG and LSPR.

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.

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.

Genes with a spike expression are clustered in chromosome (sub)bands and spike (sub)bands have a powerful prognostic value in patients with multiple myeloma

PubMed Central

Kassambara, Alboukadel; Hose, Dirk; Moreaux, Jérôme; Walker, Brian A.; Protopopov, Alexei; Reme, Thierry; Pellestor, Franck; Pantesco, Véronique; Jauch, Anna; Morgan, Gareth; Goldschmidt, Hartmut; Klein, Bernard

2012-01-01

Background Genetic abnormalities are common in patients with multiple myeloma, and may deregulate gene products involved in tumor survival, proliferation, metabolism and drug resistance. In particular, translocations may result in a high expression of targeted genes (termed spike expression) in tumor cells. We identified spike genes in multiple myeloma cells of patients with newly-diagnosed myeloma and investigated their prognostic value. Design and Methods Genes with a spike expression in multiple myeloma cells were picked up using box plot probe set signal distribution and two selection filters. Results In a cohort of 206 newly diagnosed patients with multiple myeloma, 2587 genes/expressed sequence tags with a spike expression were identified. Some spike genes were associated with some transcription factors such as MAF or MMSET and with known recurrent translocations as expected. Spike genes were not associated with increased DNA copy number and for a majority of them, involved unknown mechanisms. Of spiked genes, 36.7% clustered significantly in 149 out of 862 documented chromosome (sub)bands, of which 53 had prognostic value (35 bad, 18 good). Their prognostic value was summarized with a spike band score that delineated 23.8% of patients with a poor median overall survival (27.4 months versus not reached, P<0.001) using the training cohort of 206 patients. The spike band score was independent of other gene expression profiling-based risk scores, t(4;14), or del17p in an independent validation cohort of 345 patients. Conclusions We present a new approach to identify spike genes and their relationship to patients’ survival. PMID:22102711

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.

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

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.

Source counting in MEG neuroimaging

NASA Astrophysics Data System (ADS)

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

2009-02-01

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

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.

Exceeding Conventional Photovoltaic Efficiency Limits Using Colloidal Quantum Dots

NASA Astrophysics Data System (ADS)

Pach, Gregory F.

Colloidal quantum dots (QDs) are a widely investigated field of research due to their highly tunable nature in which the optical and electronic properties of the nanocrystal can be manipulated by merely changing the nanocrystal's size. Specifically, colloidal quantum dot solar cells (QDSCs) have become a promising candidate for future generation photovoltaic technology. Quantum dots exhibit multiple exciton generation (MEG) in which multiple electron-hole pairs are generated from a single high-energy photon. This process is not observed in bulk-like semiconductors and allows for QDSCs to achieve theoretical efficiency limits above the standard single-junction Shockley-Queisser limit. However, the fast expanding field of QDSC research has lacked standardization of synthetic techniques and device design. Therefore, we sought to detail methodology for synthesizing PbS and PbSe QDs as well as photovoltaic device fabrication techniques as a fast track toward constructing high-performance solar cells. We show that these protocols lead toward consistently achieving efficiencies above 8% for PbS QDSCs. Using the same methodology for building single-junction photovoltaic devices, we incorporated PbS QDs as a bottom cell into a monolithic tandem architecture along with solution-processed CdTe nanocrystals. Modeling shows that near-peak tandem device efficiencies can be achieved across a wide range of bottom cell band gaps, and therefore the highly tunable band gap of lead-chalcogenide QDs lends well towards a bottom cell in a tandem architecture. A fully functioning monolithic tandem device is realized through the development of a ZnTe/ZnO recombination layer that appropriately combines the two subcells in series. Multiple recent reports have shown nanocrystalline heterostructures to undergo the MEG process more efficiency than several other nanostrucutres, namely lead-chalcogenide QDs. The final section of my thesis expands upon a recent publication by Zhang et. al., which details the synthesis of PbS/CdS heterostructures in which the PbS and CdS domains exist on opposite sides of the nanocrystal and are termed "Janus particles". Transient absorption spectroscopy shows MEG quantum yields above unity very the thermodynamic limit of 2Eg for PbS/CdS Janus particles. We further explain a mechanism for enhanced MEG using photoluminescence studies.

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

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.

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

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.

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.

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.

Uncovering Neuronal Networks Defined by Consistent Between-Neuron Spike Timing from Neuronal Spike Recordings

PubMed Central

2018-01-01

Abstract It is widely assumed that distributed neuronal networks are fundamental to the functioning of the brain. Consistent spike timing between neurons is thought to be one of the key principles for the formation of these networks. This can involve synchronous spiking or spiking with time delays, forming spike sequences when the order of spiking is consistent. Finding networks defined by their sequence of time-shifted spikes, denoted here as spike timing networks, is a tremendous challenge. As neurons can participate in multiple spike sequences at multiple between-spike time delays, the possible complexity of networks is prohibitively large. We present a novel approach that is capable of (1) extracting spike timing networks regardless of their sequence complexity, and (2) that describes their spiking sequences with high temporal precision. We achieve this by decomposing frequency-transformed neuronal spiking into separate networks, characterizing each network’s spike sequence by a time delay per neuron, forming a spike sequence timeline. These networks provide a detailed template for an investigation of the experimental relevance of their spike sequences. Using simulated spike timing networks, we show network extraction is robust to spiking noise, spike timing jitter, and partial occurrences of the involved spike sequences. Using rat multineuron recordings, we demonstrate the approach is capable of revealing real spike timing networks with sub-millisecond temporal precision. By uncovering spike timing networks, the prevalence, structure, and function of complex spike sequences can be investigated in greater detail, allowing us to gain a better understanding of their role in neuronal functioning. PMID:29789811

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.

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.

Spiking neural P systems with multiple channels.

PubMed

Peng, Hong; Yang, Jinyu; Wang, Jun; Wang, Tao; Sun, Zhang; Song, Xiaoxiao; Luo, Xiaohui; Huang, Xiangnian

2017-11-01

Spiking neural P systems (SNP systems, in short) are a class of distributed parallel computing systems inspired from the neurophysiological behavior of biological spiking neurons. In this paper, we investigate a new variant of SNP systems in which each neuron has one or more synaptic channels, called spiking neural P systems with multiple channels (SNP-MC systems, in short). The spiking rules with channel label are introduced to handle the firing mechanism of neurons, where the channel labels indicate synaptic channels of transmitting the generated spikes. The computation power of SNP-MC systems is investigated. Specifically, we prove that SNP-MC systems are Turing universal as both number generating and number accepting devices. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2018-06-19

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

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

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

Hu, Duanmin; Su, Cunjin; Jiang, Min

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

Accelerated spike resampling for accurate multiple testing controls.

PubMed

Harrison, Matthew T

2013-02-01

Controlling for multiple hypothesis tests using standard spike resampling techniques often requires prohibitive amounts of computation. Importance sampling techniques can be used to accelerate the computation. The general theory is presented, along with specific examples for testing differences across conditions using permutation tests and for testing pairwise synchrony and precise lagged-correlation between many simultaneously recorded spike trains using interval jitter.

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.

[A novel method of multi-channel feature extraction combining multivariate autoregression and multiple-linear principal component analysis].

PubMed

Wang, Jinjia; Zhang, Yanna

2015-02-01

Brain-computer interface (BCI) systems identify brain signals through extracting features from them. In view of the limitations of the autoregressive model feature extraction method and the traditional principal component analysis to deal with the multichannel signals, this paper presents a multichannel feature extraction method that multivariate autoregressive (MVAR) model combined with the multiple-linear principal component analysis (MPCA), and used for magnetoencephalography (MEG) signals and electroencephalograph (EEG) signals recognition. Firstly, we calculated the MVAR model coefficient matrix of the MEG/EEG signals using this method, and then reduced the dimensions to a lower one, using MPCA. Finally, we recognized brain signals by Bayes Classifier. The key innovation we introduced in our investigation showed that we extended the traditional single-channel feature extraction method to the case of multi-channel one. We then carried out the experiments using the data groups of IV-III and IV - I. The experimental results proved that the method proposed in this paper was feasible.

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.

Single-unit muscle sympathetic nervous activity and its relation to cardiac noradrenaline spillover

PubMed Central

Lambert, Elisabeth A; Schlaich, Markus P; Dawood, Tye; Sari, Carolina; Chopra, Reena; Barton, David A; Kaye, David M; Elam, Mikael; Esler, Murray D; Lambert, Gavin W

2011-01-01

Abstract Recent work using single-unit sympathetic nerve recording techniques has demonstrated aberrations in the firing pattern of sympathetic nerves in a variety of patient groups. We sought to examine whether nerve firing pattern is associated with increased noradrenaline release. Using single-unit muscle sympathetic nerve recording techniques coupled with direct cardiac catheterisation and noradrenaline isotope dilution methodology we examined the relationship between single-unit firing patterns and cardiac and whole body noradrenaline spillover to plasma. Participants comprised patients with hypertension (n = 6), depression (n = 7) and panic disorder (n = 9) who were drawn from our ongoing studies. The patient groups examined did not differ in their single-unit muscle sympathetic nerve firing characteristics nor in the rate of spillover of noradrenaline to plasma from the heart. The median incidence of multiple spikes per beat was 9%. Patients were stratified according to the firing pattern: low level of incidence (less than 9% incidence of multiple spikes per beat) and high level of incidence (greater than 9% incidence of multiple spikes per beat). High incidence of multiple spikes within a cardiac cycle was associated with higher firing rates (P < 0.0001) and increased probability of firing (P < 0.0001). Whole body noradrenaline spillover to plasma and (multi-unit) muscle sympathetic nerve activity in subjects with low incidence of multiple spikes was not different to that of those with high incidence of multiple spikes. In those with high incidence of multiple spikes there occurred a parallel activation of the sympathetic outflow to the heart, with cardiac noradrenaline spillover to plasma being two times that of subjects with low nerve firing rates (11.0 ± 1.5 vs. 22.0 ± 4.5 ng min−1, P < 0.05). This study indicates that multiple within-burst firing and increased single-unit firing rates of the sympathetic outflow to the skeletal muscle vasculature is associated with high cardiac noradrenaline spillover. PMID:21486790

Current and Emerging Potential of Magnetoencephalography in the Detection and Localization of High-Frequency Oscillations in Epilepsy

PubMed Central

Tamilia, Eleonora; Madsen, Joseph R.; Grant, Patricia Ellen; Pearl, Phillip L.; Papadelis, Christos

2017-01-01

Up to one-third of patients with epilepsy are medically intractable and need resective surgery. To be successful, epilepsy surgery requires a comprehensive preoperative evaluation to define the epileptogenic zone (EZ), the brain area that should be resected to achieve seizure freedom. Due to lack of tools and methods that measure the EZ directly, this area is defined indirectly based on concordant data from a multitude of presurgical non-invasive tests and intracranial recordings. However, the results of these tests are often insufficiently concordant or inconclusive. Thus, the presurgical evaluation of surgical candidates is frequently challenging or unsuccessful. To improve the efficacy of the surgical treatment, there is an overriding need for reliable biomarkers that can delineate the EZ. High-frequency oscillations (HFOs) have emerged over the last decade as new potential biomarkers for the delineation of the EZ. Multiple studies have shown that HFOs are spatially associated with the EZ. Despite the encouraging findings, there are still significant challenges for the translation of HFOs as epileptogenic biomarkers to the clinical practice. One of the major barriers is the difficulty to detect and localize them with non-invasive techniques, such as magnetoencephalography (MEG) or scalp electroencephalography (EEG). Although most literature has studied HFOs using invasive recordings, recent studies have reported the detection and localization of HFOs using MEG or scalp EEG. MEG seems to be particularly advantageous compared to scalp EEG due to its inherent advantages of being less affected by skull conductivity and less susceptible to contamination from muscular activity. The detection and localization of HFOs with MEG would largely expand the clinical utility of these new promising biomarkers to an earlier stage in the diagnostic process and to a wider range of patients with epilepsy. Here, we conduct a thorough critical review of the recent MEG literature that investigates HFOs in patients with epilepsy, summarizing the different methodological approaches and the main findings. Our goal is to highlight the emerging potential of MEG in the non-invasive detection and localization of HFOs for the presurgical evaluation of patients with medically refractory epilepsy (MRE). PMID:28194133

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

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

A model-based spike sorting algorithm for removing correlation artifacts in multi-neuron recordings.

PubMed

Pillow, Jonathan W; Shlens, Jonathon; Chichilnisky, E J; Simoncelli, Eero P

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call "binary pursuit". The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth.

A Model-Based Spike Sorting Algorithm for Removing Correlation Artifacts in Multi-Neuron Recordings

PubMed Central

Chichilnisky, E. J.; Simoncelli, Eero P.

2013-01-01

We examine the problem of estimating the spike trains of multiple neurons from voltage traces recorded on one or more extracellular electrodes. Traditional spike-sorting methods rely on thresholding or clustering of recorded signals to identify spikes. While these methods can detect a large fraction of the spikes from a recording, they generally fail to identify synchronous or near-synchronous spikes: cases in which multiple spikes overlap. Here we investigate the geometry of failures in traditional sorting algorithms, and document the prevalence of such errors in multi-electrode recordings from primate retina. We then develop a method for multi-neuron spike sorting using a model that explicitly accounts for the superposition of spike waveforms. We model the recorded voltage traces as a linear combination of spike waveforms plus a stochastic background component of correlated Gaussian noise. Combining this measurement model with a Bernoulli prior over binary spike trains yields a posterior distribution for spikes given the recorded data. We introduce a greedy algorithm to maximize this posterior that we call “binary pursuit”. The algorithm allows modest variability in spike waveforms and recovers spike times with higher precision than the voltage sampling rate. This method substantially corrects cross-correlation artifacts that arise with conventional methods, and substantially outperforms clustering methods on both real and simulated data. Finally, we develop diagnostic tools that can be used to assess errors in spike sorting in the absence of ground truth. PMID:23671583

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.

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

PubMed

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

2017-09-21

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

Good practice for conducting and reporting MEG research

PubMed Central

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

2013-01-01

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

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.

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.

Hierarchical Adaptive Means (HAM) clustering for hardware-efficient, unsupervised and real-time spike sorting.

PubMed

Paraskevopoulou, Sivylla E; Wu, Di; Eftekhar, Amir; Constandinou, Timothy G

2014-09-30

This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

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

PubMed

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

2009-05-01

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

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

PubMed

Puce, Aina; Hämäläinen, Matti S

2017-05-31

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

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

PubMed Central

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

2017-01-01

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

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.

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

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.

Neuromagnetic Evidence of Spatially Distributed Sources Underlying Epileptiform Spikes in the Human Brain

NASA Astrophysics Data System (ADS)

Barth, Daniel S.; Sutherling, William; Engle, Jerome; Beatty, Jackson

1984-01-01

Neuromagnetic measurements were performed on 17 subjects with focal seizure disorders. In all of the subjects, the interictal spike in the scalp electroencephalogram was associated with an orderly extracranial magnetic field pattern. In eight of these subjects, multiple current sources underlay the magnetic spike complex. The multiple sources within a given subject displayed a fixed chronological sequence of discharge, demonstrating a high degree of spatial and temporal organization within the interictal focus.

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.

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

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

PubMed Central

Puce, Aina; Hämäläinen, Matti S.

2017-01-01

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

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

PubMed

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

2013-01-01

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

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.

SPICODYN: A Toolbox for the Analysis of Neuronal Network Dynamics and Connectivity from Multi-Site Spike Signal Recordings.

PubMed

Pastore, Vito Paolo; Godjoski, Aleksandar; Martinoia, Sergio; Massobrio, Paolo

2018-01-01

We implemented an automated and efficient open-source software for the analysis of multi-site neuronal spike signals. The software package, named SPICODYN, has been developed as a standalone windows GUI application, using C# programming language with Microsoft Visual Studio based on .NET framework 4.5 development environment. Accepted input data formats are HDF5, level 5 MAT and text files, containing recorded or generated time series spike signals data. SPICODYN processes such electrophysiological signals focusing on: spiking and bursting dynamics and functional-effective connectivity analysis. In particular, for inferring network connectivity, a new implementation of the transfer entropy method is presented dealing with multiple time delays (temporal extension) and with multiple binary patterns (high order extension). SPICODYN is specifically tailored to process data coming from different Multi-Electrode Arrays setups, guarantying, in those specific cases, automated processing. The optimized implementation of the Delayed Transfer Entropy and the High-Order Transfer Entropy algorithms, allows performing accurate and rapid analysis on multiple spike trains from thousands of electrodes.

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.

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.

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

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.

Theoretical Efficiency of 3rd Generation Solar Cells: Comparison between Carrier Multiplication and Down-Conversion

DTIC Science & Technology

2012-01-01

rewrite this equation using a generalization of Eq. (6), for a given multiplicity mrM : ym Z 1 mEg E2dE eE=kTS1 Z 1 Eg E2dE eE=kTS1 ð13Þ Note that...vectorized quadrature algorithms . We used the quadgk function in Matlab to evaluate all function, since it is best at handling the pole at EqV¼0 in the

Action Potential Waveform Variability Limits Multi-Unit Separation in Freely Behaving Rats

PubMed Central

Stratton, Peter; Cheung, Allen; Wiles, Janet; Kiyatkin, Eugene; Sah, Pankaj; Windels, François

2012-01-01

Extracellular multi-unit recording is a widely used technique to study spontaneous and evoked neuronal activity in awake behaving animals. These recordings are done using either single-wire or mulitwire electrodes such as tetrodes. In this study we have tested the ability of single-wire electrodes to discriminate activity from multiple neurons under conditions of varying noise and neuronal cell density. Using extracellular single-unit recording, coupled with iontophoresis to drive cell activity across a wide dynamic range, we studied spike waveform variability, and explored systematic differences in single-unit spike waveform within and between brain regions as well as the influence of signal-to-noise ratio (SNR) on the similarity of spike waveforms. We also modelled spike misclassification for a range of cell densities based on neuronal recordings obtained at different SNRs. Modelling predictions were confirmed by classifying spike waveforms from multiple cells with various SNRs using a leading commercial spike-sorting system. Our results show that for single-wire recordings, multiple units can only be reliably distinguished under conditions of high recording SNR (≥4) and low neuronal density (≈20,000/ mm3). Physiological and behavioural changes, as well as technical limitations typical of awake animal preparations, reduce the accuracy of single-channel spike classification, resulting in serious classification errors. For SNR <4, the probability of misclassifying spikes approaches 100% in many cases. Our results suggest that in studies where the SNR is low or neuronal density is high, separation of distinct units needs to be evaluated with great caution. PMID:22719894

Advanced correlation grid: Analysis and visualisation of functional connectivity among multiple spike trains.

PubMed

Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz

2017-07-15

This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.

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

DTIC Science & Technology

2014-09-01

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

Magnetoencephalography signals are influenced by skull defects.

PubMed

Lau, S; Flemming, L; Haueisen, J

2014-08-01

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

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

PubMed Central

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

2016-01-01

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

Extracting information in spike time patterns with wavelets and information theory.

PubMed

Lopes-dos-Santos, Vítor; Panzeri, Stefano; Kayser, Christoph; Diamond, Mathew E; Quian Quiroga, Rodrigo

2015-02-01

We present a new method to assess the information carried by temporal patterns in spike trains. The method first performs a wavelet decomposition of the spike trains, then uses Shannon information to select a subset of coefficients carrying information, and finally assesses timing information in terms of decoding performance: the ability to identify the presented stimuli from spike train patterns. We show that the method allows: 1) a robust assessment of the information carried by spike time patterns even when this is distributed across multiple time scales and time points; 2) an effective denoising of the raster plots that improves the estimate of stimulus tuning of spike trains; and 3) an assessment of the information carried by temporally coordinated spikes across neurons. Using simulated data, we demonstrate that the Wavelet-Information (WI) method performs better and is more robust to spike time-jitter, background noise, and sample size than well-established approaches, such as principal component analysis, direct estimates of information from digitized spike trains, or a metric-based method. Furthermore, when applied to real spike trains from monkey auditory cortex and from rat barrel cortex, the WI method allows extracting larger amounts of spike timing information. Importantly, the fact that the WI method incorporates multiple time scales makes it robust to the choice of partly arbitrary parameters such as temporal resolution, response window length, number of response features considered, and the number of available trials. These results highlight the potential of the proposed method for accurate and objective assessments of how spike timing encodes information. Copyright © 2015 the American Physiological Society.

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.

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

Hurtado, Antonio, E-mail: antonio.hurtado@strath.ac.uk; Javaloyes, Julien

Multiple controllable spiking patterns are achieved in a 1310 nm Vertical-Cavity Surface Emitting Laser (VCSEL) in response to induced perturbations and for two different cases of polarized optical injection, namely, parallel and orthogonal. Furthermore, reproducible spiking responses are demonstrated experimentally at sub-nanosecond speed resolution and with a controlled number of spikes fired. This work opens therefore exciting research avenues for the use of VCSELs in ultrafast neuromorphic photonic systems for non-traditional computing applications, such as all-optical binary-to-spiking format conversion and spiking information encoding.

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

Resolving human object recognition in space and time

PubMed Central

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

2014-01-01

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

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

PubMed Central

Krumin, Michael; Shoham, Shy

2010-01-01

Recent years have seen the emergence of microelectrode arrays and optical methods allowing simultaneous recording of spiking activity from populations of neurons in various parts of the nervous system. The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis of continuous neural signals like EEG signals. However, those methods have not generally been well adapted to point processes. Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting ‘‘hidden” Multivariate Autoregressive models. We use this new framework to perform Granger causality analysis in order to extract the directed information flow pattern in networks of simulated spiking neurons. We discuss the relative merits and limitations of the new method. PMID:20454705

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

PubMed

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

2015-11-01

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

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

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

PubMed

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

2017-08-01

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

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.

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

PubMed

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

2010-02-01

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

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

PubMed

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

1989-10-01

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

Requirements for Coregistration Accuracy in On-Scalp MEG.

PubMed

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

2018-06-22

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

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

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.

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

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

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

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.

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

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.

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

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

PubMed Central

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

2014-01-01

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

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.

Air pollution and urinary n-acetyl-B-glucosaminidase levels in residents living near a cement plant.

PubMed

Jung, Min Soo; Kim, Jae Yoon; Lee, Hyun Seung; Lee, Chul Gab; Song, Han Soo

2016-01-01

To identify adverse renal effects due to air pollution derived from a cement plant in Korea. Urinary n-acetyl-B-glucosaminidase (U-NAG) levels in residents living near a cement plant were compared to those in a group who lived farther away from the plant. From June to August 2013 and from August to November 2014, laboratory tests for U-NAG and heavy metal were conducted on 547 study participants. Based on the level of air pollution exposure, subjects were divided into the "less exposed group," (LEG) which consisted of 66 persons who lived more than 5 km away from the cement plant, the "more exposed group from the rural area" (MEG-R), which consisted of 272 persons, and the "more exposed group from downtown area" (MEG-D), which consisted of 209 persons who lived within a 1 km radius of the cement plant. U-NAG levels >5.67 U/L were defined as "higher U-NAG" levels. We compared the prevalence of higher U-NAG levels and estimated the adjusted odds ratio (OR) by air pollution exposure using a chi-square test and multiple logistic regression analysis. Further, we estimated the interaction between air pollution exposure and heavy metal exposure in renal toxicity. The OR of higher U-NAG levels by MEG-D and MEG-R compared to LEG was 2.13 (95 % CI 0.86-4.96) and 4.79 (95 CI 1.65-10.01), respectively. Urinary cadmium (U-Cd), urinary mercury (U-Hg), age, occupation, hypertension, and diabetes had a significant association with higher U-NAG levels. However, blood lead (B-Pb), sex, and smoking were not associated with higher U-NAG. Especially, concurrent exposure to heavy metals (U-Hg or/and U-Cd) and air pollution had an additive adverse effect. In the group with both 4 th quartile heavy metal exposure (U-Cd or/and U-Hg) and air pollution exposure, the OR in MEG-R and MEG-D was 6.49 (95 % 1.42-29.65) and 8.12 (95 % CI 1.74-37.92), respectively, after adjustment for age, occupation, hypertension, diabetes. U-NAG levels seem to be affected by air pollution exposure as well as age, hypertension, diabetes, and even low levels of cadmium and low levels of mercury. Moreover, concurrent exposure to heavy metals and air pollution can have additive cytotoxic renal effects.

Intrinsic frequency biases and profiles across human cortex.

PubMed

Mellem, Monika S; Wohltjen, Sophie; Gotts, Stephen J; Ghuman, Avniel Singh; Martin, Alex

2017-11-01

Recent findings in monkeys suggest that intrinsic periodic spiking activity in selective cortical areas occurs at timescales that follow a sensory or lower order-to-higher order processing hierarchy (Murray JD, Bernacchia A, Freedman DJ, Romo R, Wallis JD, Cai X, Padoa-Schioppa C, Pasternak T, Seo H, Lee D, Wang XJ. Nat Neurosci 17: 1661-1663, 2014). It has not yet been fully explored if a similar timescale hierarchy is present in humans. Additionally, these measures in the monkey studies have not addressed findings that rhythmic activity within a brain area can occur at multiple frequencies. In this study we investigate in humans if regions may be biased toward particular frequencies of intrinsic activity and if a full cortical mapping still reveals an organization that follows this hierarchy. We examined the spectral power in multiple frequency bands (0.5-150 Hz) from task-independent data using magnetoencephalography (MEG). We compared standardized power across bands to find regional frequency biases. Our results demonstrate a mix of lower and higher frequency biases across sensory and higher order regions. Thus they suggest a more complex cortical organization that does not simply follow this hierarchy. Additionally, some regions do not display a bias for a single band, and a data-driven clustering analysis reveals a regional organization with high standardized power in multiple bands. Specifically, theta and beta are both high in dorsal frontal cortex, whereas delta and gamma are high in ventral frontal cortex and temporal cortex. Occipital and parietal regions are biased more narrowly toward alpha power, and ventral temporal lobe displays specific biases toward gamma. Thus intrinsic rhythmic neural activity displays a regional organization but one that is not necessarily hierarchical. NEW & NOTEWORTHY The organization of rhythmic neural activity is not well understood. Whereas it has been postulated that rhythms are organized in a hierarchical manner across brain regions, our novel analysis allows comparison of full cortical maps across different frequency bands, which demonstrate that the rhythmic organization is more complex. Additionally, data-driven methods show that rhythms of multiple frequencies or timescales occur within a particular region and that this nonhierarchical organization is widespread. Copyright © 2017 the American Physiological Society.

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

PubMed Central

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

2010-01-01

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

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

PubMed

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

2010-01-01

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

Large‐scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions

PubMed Central

Saiki, Akiko; Fujiwara‐Tsukamoto, Yoko; Sakai, Yutaka; Isomura, Yoshikazu

2016-01-01

Key points There have been few systematic population‐wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions.In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single‐unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task.The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony.Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions.The strength of spike synchrony between two neurons was statistically independent of the spike rate‐based preferences of the pair for behavioural functions. Abstract Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population‐wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular‐spiking (putatively excitatory) and fast‐spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single‐unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external‐trigger trials) or spontaneously without any cue (internal‐trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular‐spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population‐wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate‐based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large‐scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement. PMID:27488936

Large-scale analysis reveals populational contributions of cortical spike rate and synchrony to behavioural functions.

PubMed

Kimura, Rie; Saiki, Akiko; Fujiwara-Tsukamoto, Yoko; Sakai, Yutaka; Isomura, Yoshikazu

2017-01-01

There have been few systematic population-wide analyses of relationships between spike synchrony within a period of several milliseconds and behavioural functions. In this study, we obtained a large amount of spike data from > 23,000 neuron pairs by multiple single-unit recording from deep layer neurons in motor cortical areas in rats performing a forelimb movement task. The temporal changes of spike synchrony in the whole neuron pairs were statistically independent of behavioural changes during the task performance, although some neuron pairs exhibited correlated changes in spike synchrony. Mutual information analyses revealed that spike synchrony made a smaller contribution than spike rate to behavioural functions. The strength of spike synchrony between two neurons was statistically independent of the spike rate-based preferences of the pair for behavioural functions. Spike synchrony within a period of several milliseconds in presynaptic neurons enables effective integration of functional information in the postsynaptic neuron. However, few studies have systematically analysed the population-wide relationships between spike synchrony and behavioural functions. Here we obtained a sufficiently large amount of spike data among regular-spiking (putatively excitatory) and fast-spiking (putatively inhibitory) neuron subtypes (> 23,000 pairs) by multiple single-unit recording from deep layers in motor cortical areas (caudal forelimb area, rostral forelimb area) in rats performing a forelimb movement task. After holding a lever, rats pulled the lever either in response to a cue tone (external-trigger trials) or spontaneously without any cue (internal-trigger trials). Many neurons exhibited functional spike activity in association with forelimb movements, and the preference of regular-spiking neurons in the rostral forelimb area was more biased toward externally triggered movement than that in the caudal forelimb area. We found that a population of neuron pairs with spike synchrony does exist, and that some neuron pairs exhibit a dependence on movement phase during task performance. However, the population-wide analysis revealed that spike synchrony was statistically independent of the movement phase and the spike rate-based preferences of the pair for behavioural functions, whereas spike rates were clearly dependent on the movement phase. In fact, mutual information analyses revealed that the contribution of spike synchrony to the behavioural functions was small relative to the contribution of spike rate. Our large-scale analysis revealed that cortical spike rate, rather than spike synchrony, contributes to population coding for movement. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Spike-train communities: finding groups of similar spike trains.

PubMed

Humphries, Mark D

2011-02-09

Identifying similar spike-train patterns is a key element in understanding neural coding and computation. For single neurons, similar spike patterns evoked by stimuli are evidence of common coding. Across multiple neurons, similar spike trains indicate potential cell assemblies. As recording technology advances, so does the urgent need for grouping methods to make sense of large-scale datasets of spike trains. Existing methods require specifying the number of groups in advance, limiting their use in exploratory analyses. I derive a new method from network theory that solves this key difficulty: it self-determines the maximum number of groups in any set of spike trains, and groups them to maximize intragroup similarity. This method brings us revealing new insights into the encoding of aversive stimuli by dopaminergic neurons, and the organization of spontaneous neural activity in cortex. I show that the characteristic pause response of a rat's dopaminergic neuron depends on the state of the superior colliculus: when it is inactive, aversive stimuli invoke a single pattern of dopaminergic neuron spiking; when active, multiple patterns occur, yet the spike timing in each is reliable. In spontaneous multineuron activity from the cortex of anesthetized cat, I show the existence of neural ensembles that evolve in membership and characteristic timescale of organization during global slow oscillations. I validate these findings by showing that the method both is remarkably reliable at detecting known groups and can detect large-scale organization of dynamics in a model of the striatum.

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

Damtie, Fikeraddis A., E-mail: Fikeraddis.Damtie@teorfys.lu.se; Wacker, Andreas, E-mail: Andreas.Wacker@fysik.lu.se; Karki, Khadga J., E-mail: Khadga.Karki@chemphys.lu.se

Multiple exciton generation (MEG) is a process in which more than one electron hole pair is generated per absorbed photon. It allows us to increase the efficiency of solar energy harvesting. Experimental studies have shown the multiple exciton generation yield of 1.2 in isolated colloidal quantum dots. However real photoelectric devices require the extraction of electron hole pairs to electric contacts. We provide a systematic study of the corresponding quantum coherent processes including extraction and injection and show that a proper design of extraction and injection rates enhances the yield significantly up to values around 1.6.

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…

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.

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

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

PubMed

Nolte, Guido

2003-11-21

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

Exploring exciton relaxation and multiexciton generation in PbSe nanocrystals using hyperspectral near-IR probing.

PubMed

Gdor, Itay; Sachs, Hanan; Roitblat, Avishy; Strasfeld, David B; Bawendi, Moungi G; Ruhman, Sanford

2012-04-24

Hyperspectral femtosecond transient absorption spectroscopy is employed to record exciton relaxation and recombination in colloidal lead selenide (PbSe) nanocrystals in unprecedented detail. Results obtained with different pump wavelengths and fluences are scrutinized with regard to three issues: (1) early subpicosecond spectral features due to "hot" excitons are analyzed in terms of suggested underlying mechanisms; (2) global kinetic analysis facilitates separation of the transient difference spectra into single, double, and triple exciton state contributions, from which individual band assignments can be tested; and (3) the transient spectra are screened for signatures of multiexciton generation (MEG) by comparing experiments with excitation pulses both below and well above the theoretical threshold for multiplication. For the latter, a recently devised ultrafast pump-probe spectroscopic approach is employed. Scaling sample concentrations and pump pulse intensities inversely with the extinction coefficient at each excitation wavelength overcomes ambiguities due to direct multiphoton excitation, uncertainties of absolute absorption cross sections, and low signal levels. As observed in a recent application of this method to InAs core/shell/shell nanodots, no sign of MEG was detected in this sample up to photon energy 3.7 times the band gap. Accordingly, numerous reports of efficient MEG in other samples of PbSe suggest that the efficiency of this process varies from sample to sample and depends on factors yet to be determined.

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.

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.

A neuromorphic implementation of multiple spike-timing synaptic plasticity rules for large-scale neural networks

PubMed Central

Wang, Runchun M.; Hamilton, Tara J.; Tapson, Jonathan C.; van Schaik, André

2015-01-01

We present a neuromorphic implementation of multiple synaptic plasticity learning rules, which include both Spike Timing Dependent Plasticity (STDP) and Spike Timing Dependent Delay Plasticity (STDDP). We present a fully digital implementation as well as a mixed-signal implementation, both of which use a novel dynamic-assignment time-multiplexing approach and support up to 226 (64M) synaptic plasticity elements. Rather than implementing dedicated synapses for particular types of synaptic plasticity, we implemented a more generic synaptic plasticity adaptor array that is separate from the neurons in the neural network. Each adaptor performs synaptic plasticity according to the arrival times of the pre- and post-synaptic spikes assigned to it, and sends out a weighted or delayed pre-synaptic spike to the post-synaptic neuron in the neural network. This strategy provides great flexibility for building complex large-scale neural networks, as a neural network can be configured for multiple synaptic plasticity rules without changing its structure. We validate the proposed neuromorphic implementations with measurement results and illustrate that the circuits are capable of performing both STDP and STDDP. We argue that it is practical to scale the work presented here up to 236 (64G) synaptic adaptors on a current high-end FPGA platform. PMID:26041985

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.

Fractional-order leaky integrate-and-fire model with long-term memory and power law dynamics.

PubMed

Teka, Wondimu W; Upadhyay, Ranjit Kumar; Mondal, Argha

2017-09-01

Pyramidal neurons produce different spiking patterns to process information, communicate with each other and transform information. These spiking patterns have complex and multiple time scale dynamics that have been described with the fractional-order leaky integrate-and-Fire (FLIF) model. Models with fractional (non-integer) order differentiation that generalize power law dynamics can be used to describe complex temporal voltage dynamics. The main characteristic of FLIF model is that it depends on all past values of the voltage that causes long-term memory. The model produces spikes with high interspike interval variability and displays several spiking properties such as upward spike-frequency adaptation and long spike latency in response to a constant stimulus. We show that the subthreshold voltage and the firing rate of the fractional-order model make transitions from exponential to power law dynamics when the fractional order α decreases from 1 to smaller values. The firing rate displays different types of spike timing adaptation caused by changes on initial values. We also show that the voltage-memory trace and fractional coefficient are the causes of these different types of spiking properties. The voltage-memory trace that represents the long-term memory has a feedback regulatory mechanism and affects spiking activity. The results suggest that fractional-order models might be appropriate for understanding multiple time scale neuronal dynamics. Overall, a neuron with fractional dynamics displays history dependent activities that might be very useful and powerful for effective information processing. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2014-01-01

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

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

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2018-01-01

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

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.

Extreme Ultraviolet Variability Experiment (EVE) on the Solar Dynamics Observatory (SDO): Overview of Science Objectives, Instrument Design, Data Products, and Model Developments

NASA Technical Reports Server (NTRS)

Woods, T. N.; Eparvier, F. G.; Hock, R.; Jones, A. R.; Woodraska, D.; Judge, D.; Didkovsky, L.; Lean, J.; Mariska, J.; Warren, H.;

Water vapor δ17O measurements using an off-axis integrated cavity output spectrometer and seasonal variation in 17O-excess of precipitation in the east-central United States

NASA Astrophysics Data System (ADS)

Tian, C.; Wang, L.; Novick, K. A.

2016-12-01

High-precision triple oxygen isotope analysis can be used to improve our understanding of multiple hydrological and meteorological processes. Recent studies focus on understanding 17O-excess variation of tropical storms, high-latitude snow and ice-core as well as spatial distribution of meteoric water (tap water). The temporal scale of 17O-excess variation in middle-latitude precipitation is needed to better understand which processes control on the 17O-excess variations. This study focused on assessing how the accuracy and precision of vapor δ17O laser spectroscopy measurements depend on vapor concentration, delta range, and averaging-time. Meanwhile, we presented 17O-excess data from two-year, event based precipitation sampling in the east-central United States. A Triple Water Vapor Isotope Analyzer (T-WVIA) was used to evaluate the accuracy and precision of δ2H, δ18O and δ17O measurements. GISP and SLAP2 from IAEA and four working standards were used to evaluate the sensitivity in the three factors. Overall, the accuracy and precision of all isotope measurements were sensitive to concentration, with higher accuracy and precision generally observed under moderate vapor concentrations (i.e., 10000-15000 ppm) for all isotopes. Precision was also sensitive to the range of delta values, though the effect was not as large when compared to the sensitivity to concentration. The precision was much less sensitive to averaging time when compared with concentration and delta range effects. The preliminary results showed that 17O-excess variation was lower in summer (23±17 per meg) than in winter (34±16 per meg), whereas spring values (30±21 per meg) was similar to fall (29±13 per meg). That means kinetic fractionation influences the isotopic composition and 17O-excess in different seasons.

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.

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.

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.

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.

Cochlear spike synchronization and neuron coincidence detection model

NASA Astrophysics Data System (ADS)

Bader, Rolf

2018-02-01

Coincidence detection of a spike pattern fed from the cochlea into a single neuron is investigated using a physical Finite-Difference model of the cochlea and a physiologically motivated neuron model. Previous studies have shown experimental evidence of increased spike synchronization in the nucleus cochlearis and the trapezoid body [Joris et al., J. Neurophysiol. 71(3), 1022-1036 and 1037-1051 (1994)] and models show tone partial phase synchronization at the transition from mechanical waves on the basilar membrane into spike patterns [Ch. F. Babbs, J. Biophys. 2011, 435135]. Still the traveling speed of waves on the basilar membrane cause a frequency-dependent time delay of simultaneously incoming sound wavefronts up to 10 ms. The present model shows nearly perfect synchronization of multiple spike inputs as neuron outputs with interspike intervals (ISI) at the periodicity of the incoming sound for frequencies from about 30 to 300 Hz for two different amounts of afferent nerve fiber neuron inputs. Coincidence detection serves here as a fusion of multiple inputs into one single event enhancing pitch periodicity detection for low frequencies, impulse detection, or increased sound or speech intelligibility due to dereverberation.

Real-time separation of multineuron recordings with a DSP32C signal processor.

PubMed

Gädicke, R; Albus, K

1995-04-01

We have developed a hardware and software package for real-time discrimination of multiple-unit activities recorded simultaneously from multiple microelectrodes using a VME-Bus system. Compared with other systems cited in literature or commercially available, our system has the following advantages. (1) Each electrode is served by its own preprocessor (DSP32C); (2) On-line spike discrimination is performed independently for each electrode. (3) The VME-bus allows processing of data received from 16 electrodes. The digitized (62.5 kHz) spike form is itself used as the model spike; the algorithm allows for comparing and sorting complete wave forms in real time into 8 different models per electrode.

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

PubMed Central

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

2016-01-01

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

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

Multineuron spike train analysis with R-convolution linear combination kernel.

PubMed

Tezuka, Taro

2018-06-01

A spike train kernel provides an effective way of decoding information represented by a spike train. Some spike train kernels have been extended to multineuron spike trains, which are simultaneously recorded spike trains obtained from multiple neurons. However, most of these multineuron extensions were carried out in a kernel-specific manner. In this paper, a general framework is proposed for extending any single-neuron spike train kernel to multineuron spike trains, based on the R-convolution kernel. Special subclasses of the proposed R-convolution linear combination kernel are explored. These subclasses have a smaller number of parameters and make optimization tractable when the size of data is limited. The proposed kernel was evaluated using Gaussian process regression for multineuron spike trains recorded from an animal brain. It was compared with the sum kernel and the population Spikernel, which are existing ways of decoding multineuron spike trains using kernels. The results showed that the proposed approach performs better than these kernels and also other commonly used neural decoding methods. Copyright © 2018 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2018-01-01

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

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

DTIC Science & Technology

2015-05-22

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

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

PubMed

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

2018-06-11

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

Neighborhood and Family Environment of Expectant Mothers May Influence Prenatal Programming of Adult Cancer Risk: Discussion and an Illustrative Biomarker Example

PubMed Central

King, Katherine E.; Kane, Jennifer B.; Scarbrough, Peter; Hoyo, Cathrine; Murphy, Susan K.

2016-01-01

Objectives Childhood stressors including physical abuse predict adult cancer risk. Prior research portrays this finding as indirect through coping behaviors including adult smoking or through increased toxic exposures during childhood. Little is known about potential direct causal mechanisms between early-life stressors and adult cancer. Because prenatal conditions can affect gene expression by altering DNA methylation with implications for adult health, we hypothesize that maternal stress may program methylation of cancer-linked genes during gametogenesis. Methods To illustrate, we relate maternal social resources to methylation at the imprinted MEG3 differentially methylated regulatory region linked to multiple cancer types. Mothers (n=489) in umbilical cord blood of diverse birth cohort (Durham, North Carolina) provided newborn’s cord blood and completed a questionnaire. Results Newborns of currently-married mothers show lower (−0.321 SD, p<0.05) methylation vs. newborns of never-married mothers, who did not differ from those whose mothers are cohabiting and others (adjusted for demographics). MEG3 DNA methylation levels are also lower when maternal grandmothers co-reside before pregnancy (−0.314 SD, p<0.05). A 1-SD increase in prenatal neighborhood disadvantage also predicts higher methylation (−0.137 SD, p<0.05). Conclusions Maternal social resources may result in differential methylation of MEG3, which demonstrates a potential partial mechanism priming socially disadvantaged newborns for later risk of some cancers. PMID:27050035

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

PubMed

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

2015-05-15

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

A 20-channel magnetoencephalography system based on optically pumped magnetometers

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

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

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

A 20-channel magnetoencephalography system based on optically pumped magnetometers

DOE PAGES

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

2017-10-16

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

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

DTIC Science & Technology

2014-03-01

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

Marine Resiliency Study II

DTIC Science & Technology

2016-07-06

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

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

PubMed Central

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

2011-01-01

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

MEG-guided analysis of 7T-MRI in patients with epilepsy.

PubMed

Colon, A J; Osch, M J P van; Buijs, M; Grond, J V D; Hillebrand, A; Schijns, O; Wagner, G J; Ossenblok, P; Hofman, P; Buchem, M A V; Boon, P

2018-05-26

To study possible detection of structural abnormalities on 7T MRI that were not detected on 3T MRI and estimate the added value of MEG-guidance. For abnormalities found, analysis of convergence between clinical, MEG and 7T MRI localization of suspected epileptogenic foci. In adult patients with well-documented localization-related epilepsy in whom a previous 3T MRI did not demonstrate an epileptogenic lesion but MEG indicated a plausible epileptogenic focus, 7T MRI was performed. Based on semiologic data, visual analysis of the 7T images was performed as well as based on prior MEG results. Correlation with other data from the patient charts, for as far as these were available, was analysed. To establish the level of concordance between the three observers the generalized or Fleiss kappa was calculated. In 3/19 patients abnormalities that, based on semiology, could plausibly represent an epileptogenic lesion were detected using 7T MRI. In an additional 3/19 an abnormality was detected after MEG-guidance. However, in these later cases there was no concordance among the three observers with regard to the presence of a structural abnormality. In one of these three cases intracranial recording was performed, proving the possible abnormality on 7T MRI to be the epileptogenic focus. In 32% of patients 7T MRI showed abnormalities that could indicate an epileptogenic lesion whereas previous 3T MRI did not, especially when visual inspection was guided by the presence of focal interictal MEG abnormalities. Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Myricetin and methyl eugenol combination enhances the anticancer activity, cell cycle arrest and apoptosis induction of cis-platin against HeLa cervical cancer cell lines

PubMed Central

Yi, Jin-Ling; Shi, Song; Shen, Yan-Li; Wang, Ling; Chen, Hai-Yan; Zhu, Jun; Ding, Yan

2015-01-01

Drug combination therapies are common practice in the treatment of cancer. In this study, we evaluated the anticancer effects of myricetin (MYR), methyl eugenol (MEG) and cisplatin (CP) both separately as well as in combination against cervical cancer (HeLa) cells. To demonstrate whether MYR and MEG enhance the anticancer activity of CP against cervical cancer cells, we treated HeLa cells with MYR and MEG alone or in combination with cisplatin and evaluated cell growth and apoptosis using MTT (3 (4, 5 dimethyl thiazol 2yl) 2, 5 diphenyltetrazolium bromide) assay, LDH release assay, flow cytometry and fluorescence microscopy. The results revealed that, as compared to single drug treatment, the combination of MYR or MEG with CP resulted in greater effect in inhibiting cancer cell growth and inducing apoptosis. Cell apoptosis induction, Caspase-3 activity, cell cycle arrest and mitochondrial membrane potential loss were systematically studied to reveal the mechanisms of synergy between MYR, MEG and CP. Combination of MYR or MEG with CP resulted in more potent apoptosis induction as revealed by fluorescence microscopy using Hoechst 33258 and AO-ETBR staining. The combination treatment also increased the number of cells in G0/G1 phase dramatically as compared to single drug treatment. Mitochondrial membrane potential loss (ΛΨm) as well as Caspase-3 activity was much higher in combination treatment as compared to single drug treatment. Findings of this investigation suggest that MYR and MEG combined with cisplatin is a potential clinical chemotherapeutic approach in human cervical cancer. PMID:25972998

Reactive Melt Extrusion To Improve the Dissolution Performance and Physical Stability of Naproxen Amorphous Solid Dispersions.

PubMed

Liu, Xu; Zhou, Lin; Zhang, Feng

2017-03-06

The purpose of this study was to investigate the reaction between naproxen (NPX) and meglumine (MEG) at elevated temperature and to study the effect of this reaction on the physical stabilities and in vitro drug-release properties of melt-extruded naproxen amorphous solid dispersions (ASDs). Differential scanning calorimetry, hot-stage polarized light microscopy, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy analyses demonstrated that in situ salt formation with proton transfer between NPX and MEG occurred at elevated temperature during the melt extrusion process. The amorphous NPX-MEG salt was physically most stable when two components were present at a 1:1 molar ratio. Polymeric carriers, including povidone, copovidone, and SOLUPLUS, did not interfere with the reaction between NPX and MEG during melt extrusion. Compared to the traditional NPX ASDs consisting of NPX and polymer only, NPX-MEG ASDs were physically more stable and remained amorphous following four months storage at 40 °C and 75% RH (relative humidity). Based on nonsink dissolution testing and polarized light microscopy analyses, we concluded that the conventional NPX ASDs composed of NPX and polymers failed to improve the NPX dissolution rate due to the rapid recrystallization of NPX in contact with aqueous medium. The dissolution rate of NPX-MEG ASDs was two times greater than the corresponding physical mixtures and conventional NPX ASDs. This study demonstrated that the acid-base reaction between NPX and MEG during melt extrusion significantly improved the physical stability and the dissolution rate of NPX ASDs.

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

PubMed

Ding, Lei; Yuan, Han

2013-04-01

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

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.

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.

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.

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.

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

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.

Coincidence detection in the medial superior olive: mechanistic implications of an analysis of input spiking patterns

PubMed Central

Franken, Tom P.; Bremen, Peter; Joris, Philip X.

2014-01-01

Coincidence detection by binaural neurons in the medial superior olive underlies sensitivity to interaural time difference (ITD) and interaural correlation (ρ). It is unclear whether this process is akin to a counting of individual coinciding spikes, or rather to a correlation of membrane potential waveforms resulting from converging inputs from each side. We analyzed spike trains of axons of the cat trapezoid body (TB) and auditory nerve (AN) in a binaural coincidence scheme. ITD was studied by delaying “ipsi-” vs. “contralateral” inputs; ρ was studied by using responses to different noises. We varied the number of inputs; the monaural and binaural threshold and the coincidence window duration. We examined physiological plausibility of output “spike trains” by comparing their rate and tuning to ITD and ρ to those of binaural cells. We found that multiple inputs are required to obtain a plausible output spike rate. In contrast to previous suggestions, monaural threshold almost invariably needed to exceed binaural threshold. Elevation of the binaural threshold to values larger than 2 spikes caused a drastic decrease in rate for a short coincidence window. Longer coincidence windows allowed a lower number of inputs and higher binaural thresholds, but decreased the depth of modulation. Compared to AN fibers, TB fibers allowed higher output spike rates for a low number of inputs, but also generated more monaural coincidences. We conclude that, within the parameter space explored, the temporal patterns of monaural fibers require convergence of multiple inputs to achieve physiological binaural spike rates; that monaural coincidences have to be suppressed relative to binaural ones; and that the neuron has to be sensitive to single binaural coincidences of spikes, for a number of excitatory inputs per side of 10 or less. These findings suggest that the fundamental operation in the mammalian binaural circuit is coincidence counting of single binaural input spikes. PMID:24822037

Spiking Neurons in a Hierarchical Self-Organizing Map Model Can Learn to Develop Spatial and Temporal Properties of Entorhinal Grid Cells and Hippocampal Place Cells

PubMed Central

Pilly, Praveen K.; Grossberg, Stephen

2013-01-01

Medial entorhinal grid cells and hippocampal place cells provide neural correlates of spatial representation in the brain. A place cell typically fires whenever an animal is present in one or more spatial regions, or places, of an environment. A grid cell typically fires in multiple spatial regions that form a regular hexagonal grid structure extending throughout the environment. Different grid and place cells prefer spatially offset regions, with their firing fields increasing in size along the dorsoventral axes of the medial entorhinal cortex and hippocampus. The spacing between neighboring fields for a grid cell also increases along the dorsoventral axis. This article presents a neural model whose spiking neurons operate in a hierarchy of self-organizing maps, each obeying the same laws. This spiking GridPlaceMap model simulates how grid cells and place cells may develop. It responds to realistic rat navigational trajectories by learning grid cells with hexagonal grid firing fields of multiple spatial scales and place cells with one or more firing fields that match neurophysiological data about these cells and their development in juvenile rats. The place cells represent much larger spaces than the grid cells, which enable them to support navigational behaviors. Both self-organizing maps amplify and learn to categorize the most frequent and energetic co-occurrences of their inputs. The current results build upon a previous rate-based model of grid and place cell learning, and thus illustrate a general method for converting rate-based adaptive neural models, without the loss of any of their analog properties, into models whose cells obey spiking dynamics. New properties of the spiking GridPlaceMap model include the appearance of theta band modulation. The spiking model also opens a path for implementation in brain-emulating nanochips comprised of networks of noisy spiking neurons with multiple-level adaptive weights for controlling autonomous adaptive robots capable of spatial navigation. PMID:23577130

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

An Unsupervised Online Spike-Sorting Framework.

PubMed

Knieling, Simeon; Sridharan, Kousik S; Belardinelli, Paolo; Naros, Georgios; Weiss, Daniel; Mormann, Florian; Gharabaghi, Alireza

2016-08-01

Extracellular neuronal microelectrode recordings can include action potentials from multiple neurons. To separate spikes from different neurons, they can be sorted according to their shape, a procedure referred to as spike-sorting. Several algorithms have been reported to solve this task. However, when clustering outcomes are unsatisfactory, most of them are difficult to adjust to achieve the desired results. We present an online spike-sorting framework that uses feature normalization and weighting to maximize the distinctiveness between different spike shapes. Furthermore, multiple criteria are applied to either facilitate or prevent cluster fusion, thereby enabling experimenters to fine-tune the sorting process. We compare our method to established unsupervised offline (Wave_Clus (WC)) and online (OSort (OS)) algorithms by examining their performance in sorting various test datasets using two different scoring systems (AMI and the Adamos metric). Furthermore, we evaluate sorting capabilities on intra-operative recordings using established quality metrics. Compared to WC and OS, our algorithm achieved comparable or higher scores on average and produced more convincing sorting results for intra-operative datasets. Thus, the presented framework is suitable for both online and offline analysis and could substantially improve the quality of microelectrode-based data evaluation for research and clinical application.

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

Synchronous Spike Patterns in Macaque Motor Cortex during an Instructed-Delay Reach-to-Grasp Task

PubMed Central

Torre, Emiliano; Quaglio, Pietro; Denker, Michael; Brochier, Thomas; Riehle, Alexa

2016-01-01

The computational role of spike time synchronization at millisecond precision among neurons in the cerebral cortex is hotly debated. Studies performed on data of limited size provided experimental evidence that low-order correlations occur in relation to behavior. Advances in electrophysiological technology to record from hundreds of neurons simultaneously provide the opportunity to observe coordinated spiking activity of larger populations of cells. We recently published a method that combines data mining and statistical evaluation to search for significant patterns of synchronous spikes in massively parallel spike trains (Torre et al., 2013). The method solves the computational and multiple testing problems raised by the high dimensionality of the data. In the current study, we used our method on simultaneous recordings from two macaque monkeys engaged in an instructed-delay reach-to-grasp task to determine the emergence of spike synchronization in relation to behavior. We found a multitude of synchronous spike patterns aligned in both monkeys along a preferential mediolateral orientation in brain space. The occurrence of the patterns is highly specific to behavior, indicating that different behaviors are associated with the synchronization of different groups of neurons (“cell assemblies”). However, pooled patterns that overlap in neuronal composition exhibit no specificity, suggesting that exclusive cell assemblies become active during different behaviors, but can recruit partly identical neurons. These findings are consistent across multiple recording sessions analyzed across the two monkeys. SIGNIFICANCE STATEMENT Neurons in the brain communicate via electrical impulses called spikes. How spikes are coordinated to process information is still largely unknown. Synchronous spikes are effective in triggering a spike emission in receiving neurons and have been shown to occur in relation to behavior in a number of studies on simultaneous recordings of few neurons. We recently published a method to extend this type of investigation to larger data. Here, we apply it to simultaneous recordings of hundreds of neurons from the motor cortex of macaque monkeys performing a motor task. Our analysis reveals groups of neurons selectively synchronizing their activity in relation to behavior, which sheds new light on the role of synchrony in information processing in the cerebral cortex. PMID:27511007

Synchronous Spike Patterns in Macaque Motor Cortex during an Instructed-Delay Reach-to-Grasp Task.

PubMed

Torre, Emiliano; Quaglio, Pietro; Denker, Michael; Brochier, Thomas; Riehle, Alexa; Grün, Sonja

2016-08-10

The computational role of spike time synchronization at millisecond precision among neurons in the cerebral cortex is hotly debated. Studies performed on data of limited size provided experimental evidence that low-order correlations occur in relation to behavior. Advances in electrophysiological technology to record from hundreds of neurons simultaneously provide the opportunity to observe coordinated spiking activity of larger populations of cells. We recently published a method that combines data mining and statistical evaluation to search for significant patterns of synchronous spikes in massively parallel spike trains (Torre et al., 2013). The method solves the computational and multiple testing problems raised by the high dimensionality of the data. In the current study, we used our method on simultaneous recordings from two macaque monkeys engaged in an instructed-delay reach-to-grasp task to determine the emergence of spike synchronization in relation to behavior. We found a multitude of synchronous spike patterns aligned in both monkeys along a preferential mediolateral orientation in brain space. The occurrence of the patterns is highly specific to behavior, indicating that different behaviors are associated with the synchronization of different groups of neurons ("cell assemblies"). However, pooled patterns that overlap in neuronal composition exhibit no specificity, suggesting that exclusive cell assemblies become active during different behaviors, but can recruit partly identical neurons. These findings are consistent across multiple recording sessions analyzed across the two monkeys. Neurons in the brain communicate via electrical impulses called spikes. How spikes are coordinated to process information is still largely unknown. Synchronous spikes are effective in triggering a spike emission in receiving neurons and have been shown to occur in relation to behavior in a number of studies on simultaneous recordings of few neurons. We recently published a method to extend this type of investigation to larger data. Here, we apply it to simultaneous recordings of hundreds of neurons from the motor cortex of macaque monkeys performing a motor task. Our analysis reveals groups of neurons selectively synchronizing their activity in relation to behavior, which sheds new light on the role of synchrony in information processing in the cerebral cortex. Copyright © 2016 Torre, et al.

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.

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.

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

PubMed Central

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

2010-01-01

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

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

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.

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

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.

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

Regulation of RNA granule dynamics by phosphorylation of serine-rich, intrinsically disordered proteins in C. elegans

PubMed Central

Wang, Jennifer T; Smith, Jarrett; Chen, Bi-Chang; Schmidt, Helen; Rasoloson, Dominique; Paix, Alexandre; Lambrus, Bramwell G; Calidas, Deepika; Betzig, Eric; Seydoux, Geraldine

2014-01-01

RNA granules have been likened to liquid droplets whose dynamics depend on the controlled dissolution and condensation of internal components. The molecules and reactions that drive these dynamics in vivo are not well understood. In this study, we present evidence that a group of intrinsically disordered, serine-rich proteins regulate the dynamics of P granules in C. elegans embryos. The MEG (maternal-effect germline defective) proteins are germ plasm components that are required redundantly for fertility. We demonstrate that MEG-1 and MEG-3 are substrates of the kinase MBK-2/DYRK and the phosphatase PP2APPTR−½. Phosphorylation of the MEGs promotes granule disassembly and dephosphorylation promotes granule assembly. Using lattice light sheet microscopy on live embryos, we show that GFP-tagged MEG-3 localizes to a dynamic domain that surrounds and penetrates each granule. We conclude that, despite their liquid-like behavior, P granules are non-homogeneous structures whose assembly in embryos is regulated by phosphorylation. DOI: http://dx.doi.org/10.7554/eLife.04591.001 PMID:25535836

Interpretation of the MEG-MUSIC scan in biomagnetic source localization

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

Mosher, J.C.; Lewis, P.S.; Leahy, R.M.

1993-09-01

MEG-Music is a new approach to MEG source localization. MEG-Music is based on a spatio-temporal source model in which the observed biomagnetic fields are generated by a small number of current dipole sources with fixed positions/orientations and varying strengths. From the spatial covariance matrix of the observed fields, a signal subspace can be identified. The rank of this subspace is equal to the number of elemental sources present. This signal sub-space is used in a projection metric that scans the three dimensional head volume. Given a perfect signal subspace estimate and a perfect forward model, the metric will peak atmore » unity at each dipole location. In practice, the signal subspace estimate is contaminated by noise, which in turn yields MUSIC peaks which are less than unity. Previously we examined the lower bounds on localization error, independent of the choice of localization procedure. In this paper, we analyzed the effects of noise and temporal coherence on the signal subspace estimate and the resulting effects on the MEG-MUSIC peaks.« less

Distinct responses of Purkinje neurons and roles of simple spikes during associative motor learning in larval zebrafish

PubMed Central

Harmon, Thomas C; Magaram, Uri; McLean, David L; Raman, Indira M

2017-01-01

To study cerebellar activity during learning, we made whole-cell recordings from larval zebrafish Purkinje cells while monitoring fictive swimming during associative conditioning. Fish learned to swim in response to visual stimulation preceding tactile stimulation of the tail. Learning was abolished by cerebellar ablation. All Purkinje cells showed task-related activity. Based on how many complex spikes emerged during learned swimming, they were classified as multiple, single, or zero complex spike (MCS, SCS, ZCS) cells. With learning, MCS and ZCS cells developed increased climbing fiber (MCS) or parallel fiber (ZCS) input during visual stimulation; SCS cells fired complex spikes associated with learned swimming episodes. The categories correlated with location. Optogenetically suppressing simple spikes only during visual stimulation demonstrated that simple spikes are required for acquisition and early stages of expression of learned responses, but not their maintenance, consistent with a transient, instructive role for simple spikes during cerebellar learning in larval zebrafish. DOI: http://dx.doi.org/10.7554/eLife.22537.001 PMID:28541889

Electrical source imaging of interictal spikes using multiple sparse volumetric priors for presurgical epileptogenic focus localization

PubMed Central

Strobbe, Gregor; Carrette, Evelien; López, José David; Montes Restrepo, Victoria; Van Roost, Dirk; Meurs, Alfred; Vonck, Kristl; Boon, Paul; Vandenberghe, Stefaan; van Mierlo, Pieter

2016-01-01

Electrical source imaging of interictal spikes observed in EEG recordings of patients with refractory epilepsy provides useful information to localize the epileptogenic focus during the presurgical evaluation. However, the selection of the time points or time epochs of the spikes in order to estimate the origin of the activity remains a challenge. In this study, we consider a Bayesian EEG source imaging technique for distributed sources, i.e. the multiple volumetric sparse priors (MSVP) approach. The approach allows to estimate the time courses of the intensity of the sources corresponding with a specific time epoch of the spike. Based on presurgical averaged interictal spikes in six patients who were successfully treated with surgery, we estimated the time courses of the source intensities for three different time epochs: (i) an epoch starting 50 ms before the spike peak and ending at 50% of the spike peak during the rising phase of the spike, (ii) an epoch starting 50 ms before the spike peak and ending at the spike peak and (iii) an epoch containing the full spike time period starting 50 ms before the spike peak and ending 230 ms after the spike peak. To identify the primary source of the spike activity, the source with the maximum energy from 50 ms before the spike peak till 50% of the spike peak was subsequently selected for each of the time windows. For comparison, the activity at the spike peaks and at 50% of the peaks was localized using the LORETA inversion technique and an ECD approach. Both patient-specific spherical forward models and patient-specific 5-layered finite difference models were considered to evaluate the influence of the forward model. Based on the resected zones in each of the patients, extracted from post-operative MR images, we compared the distances to the resection border of the estimated activity. Using the spherical models, the distances to the resection border for the MSVP approach and each of the different time epochs were in the same range as the LORETA and ECD techniques. We found distances smaller than 23 mm, with robust results for all the patients. For the finite difference models, we found that the distances to the resection border for the MSVP inversions of the full spike time epochs were generally smaller compared to the MSVP inversions of the time epochs before the spike peak. The results also suggest that the inversions using the finite difference models resulted in slightly smaller distances to the resection border compared to the spherical models. The results we obtained are promising because the MSVP approach allows to study the network of the estimated source-intensities and allows to characterize the spatial extent of the underlying sources. PMID:26958464

Information recall using relative spike timing in a spiking neural network.

PubMed

Sterne, Philip

2012-08-01

We present a neural network that is capable of completing and correcting a spiking pattern given only a partial, noisy version. It operates in continuous time and represents information using the relative timing of individual spikes. The network is capable of correcting and recalling multiple patterns simultaneously. We analyze the network's performance in terms of information recall. We explore two measures of the capacity of the network: one that values the accurate recall of individual spike times and another that values only the presence or absence of complete patterns. Both measures of information are found to scale linearly in both the number of neurons and the period of the patterns, suggesting these are natural measures of network information. We show a smooth transition from encodings that provide precise spike times to flexible encodings that can encode many scenes. This makes it plausible that many diverse tasks could be learned with such an encoding.

Spike-like solitary waves in incompressible boundary layers driven by a travelling wave.

PubMed

Feng, Peihua; Zhang, Jiazhong; Wang, Wei

2016-06-01

Nonlinear waves produced in an incompressible boundary layer driven by a travelling wave are investigated, with damping considered as well. As one of the typical nonlinear waves, the spike-like wave is governed by the driven-damped Benjamin-Ono equation. The wave field enters a completely irregular state beyond a critical time, increasing the amplitude of the driving wave continuously. On the other hand, the number of spikes of solitary waves increases through multiplication of the wave pattern. The wave energy grows in a sequence of sharp steps, and hysteresis loops are found in the system. The wave energy jumps to different levels with multiplication of the wave, which is described by winding number bifurcation of phase trajectories. Also, the phenomenon of multiplication and hysteresis steps is found when varying the speed of driving wave as well. Moreover, the nature of the change of wave pattern and its energy is the stability loss of the wave caused by saddle-node bifurcation.

Multiple eigenmodes of the Rayleigh-Taylor instability observed for a fluid interface with smoothly varying density

NASA Astrophysics Data System (ADS)

Yu, C. X.; Xue, C.; Liu, J.; Hu, X. Y.; Liu, Y. Y.; Ye, W. H.; Wang, L. F.; Wu, J. F.; Fan, Z. F.

2018-01-01

In this article, multiple eigen-systems including linear growth rates and eigen-functions have been discovered for the Rayleigh-Taylor instability (RTI) by numerically solving the Sturm-Liouville eigen-value problem in the case of two-dimensional plane geometry. The system called the first mode has the maximal linear growth rate and is just extensively studied in literature. Higher modes have smaller eigen-values, but possess multi-peak eigen-functions which bring on multiple pairs of vortices in the vorticity field. A general fitting expression for the first four eigen-modes is presented. Direct numerical simulations show that high modes lead to appearances of multi-layered spike-bubble pairs, and lots of secondary spikes and bubbles are also generated due to the interactions between internal spikes and bubbles. The present work has potential applications in many research and engineering areas, e.g., in reducing the RTI growth during capsule implosions in inertial confinement fusion.

Dendritic sodium spikes are required for long-term potentiation at distal synapses on hippocampal pyramidal neurons

PubMed Central

Kim, Yujin; Hsu, Ching-Lung; Cembrowski, Mark S; Mensh, Brett D; Spruston, Nelson

2015-01-01

Dendritic integration of synaptic inputs mediates rapid neural computation as well as longer-lasting plasticity. Several channel types can mediate dendritically initiated spikes (dSpikes), which may impact information processing and storage across multiple timescales; however, the roles of different channels in the rapid vs long-term effects of dSpikes are unknown. We show here that dSpikes mediated by Nav channels (blocked by a low concentration of TTX) are required for long-term potentiation (LTP) in the distal apical dendrites of hippocampal pyramidal neurons. Furthermore, imaging, simulations, and buffering experiments all support a model whereby fast Nav channel-mediated dSpikes (Na-dSpikes) contribute to LTP induction by promoting large, transient, localized increases in intracellular calcium concentration near the calcium-conducting pores of NMDAR and L-type Cav channels. Thus, in addition to contributing to rapid neural processing, Na-dSpikes are likely to contribute to memory formation via their role in long-lasting synaptic plasticity. DOI: http://dx.doi.org/10.7554/eLife.06414.001 PMID:26247712

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...

Reconstruction of audio waveforms from spike trains of artificial cochlea models

PubMed Central

Zai, Anja T.; Bhargava, Saurabh; Mesgarani, Nima; Liu, Shih-Chii

2015-01-01

Spiking cochlea models describe the analog processing and spike generation process within the biological cochlea. Reconstructing the audio input from the artificial cochlea spikes is therefore useful for understanding the fidelity of the information preserved in the spikes. The reconstruction process is challenging particularly for spikes from the mixed signal (analog/digital) integrated circuit (IC) cochleas because of multiple non-linearities in the model and the additional variance caused by random transistor mismatch. This work proposes an offline method for reconstructing the audio input from spike responses of both a particular spike-based hardware model called the AEREAR2 cochlea and an equivalent software cochlea model. This method was previously used to reconstruct the auditory stimulus based on the peri-stimulus histogram of spike responses recorded in the ferret auditory cortex. The reconstructed audio from the hardware cochlea is evaluated against an analogous software model using objective measures of speech quality and intelligibility; and further tested in a word recognition task. The reconstructed audio under low signal-to-noise (SNR) conditions (SNR < –5 dB) gives a better classification performance than the original SNR input in this word recognition task. PMID:26528113

Maximum-likelihood estimation of channel-dependent trial-to-trial variability of auditory evoked brain responses in MEG

PubMed Central

2014-01-01

Background We propose a mathematical model for multichannel assessment of the trial-to-trial variability of auditory evoked brain responses in magnetoencephalography (MEG). Methods Following the work of de Munck et al., our approach is based on the maximum likelihood estimation and involves an approximation of the spatio-temporal covariance of the contaminating background noise by means of the Kronecker product of its spatial and temporal covariance matrices. Extending the work of de Munck et al., where the trial-to-trial variability of the responses was considered identical to all channels, we evaluate it for each individual channel. Results Simulations with two equivalent current dipoles (ECDs) with different trial-to-trial variability, one seeded in each of the auditory cortices, were used to study the applicability of the proposed methodology on the sensor level and revealed spatial selectivity of the trial-to-trial estimates. In addition, we simulated a scenario with neighboring ECDs, to show limitations of the method. We also present an illustrative example of the application of this methodology to real MEG data taken from an auditory experimental paradigm, where we found hemispheric lateralization of the habituation effect to multiple stimulus presentation. Conclusions The proposed algorithm is capable of reconstructing lateralization effects of the trial-to-trial variability of evoked responses, i.e. when an ECD of only one hemisphere habituates, whereas the activity of the other hemisphere is not subject to habituation. Hence, it may be a useful tool in paradigms that assume lateralization effects, like, e.g., those involving language processing. PMID:24939398

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.

Depression in pregnancy, infant birth weight and DNA methylation of imprint regulatory elements

PubMed Central

Liu, Ying; Murphy, Susan K.; Murtha, Amy P.; Fuemmeler, Bernard F.; Schildkraut, Joellen; Huang, Zhiqing; Overcash, Francine; Kurtzberg, Joanne; Jirtle, Randy; Iversen, Edwin S.; Forman, Michele R.; Hoyo, Cathrine

2012-01-01

Depressed mood in pregnancy has been linked to low birth weight (LBW, < 2,500 g), a risk factor for adult-onset chronic diseases in offspring. We examined maternal depressed mood in relation to birth weight and evaluated the role of DNA methylation at regulatory sequences of imprinted genes in this association. We measured depressed mood among 922 pregnant women using the CES-D scale and obtained birth weight data from hospital records. Using bisulfite pyrosequencing of cord blood DNA from 508 infants, we measured methylation at differentially methylated regions (DMRs) regulating imprinted genes IGF2/H19, DLK1/MEG3, MEST, PEG3, PEG10/SGCE, NNAT and PLAGL1. Multiple regression models were used to examine the relationship between depressed mood, birth weight and DMR methylation levels. Depressed mood was associated with a more that 3-fold higher risk of LBW, after adjusting for delivery mode, parity, education, cigarette smoking, folic acid use and preterm birth. The association may be more pronounced in offspring of black women and female infants. Compared with infants of women without depressed mood, infants born to women with severe depressed mood had a 2.4% higher methylation at the MEG3 DMR. Whereas LBW infants had 1.6% lower methylation at the IGF2 DMR, high birth weight (> 4,500 g) infants had 5.9% higher methylation at the PLAGL1 DMR compared with normal birth weight infants. Our findings confirm that severe maternal depressed mood in pregnancy is associated with LBW, and that MEG3 and IGF2 plasticity may play important roles. PMID:22677950

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

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

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

Anomalous temporal behaviour of broadband Lyα observations during solar flares from SDO/EVE

NASA Astrophysics Data System (ADS)

Milligan, Ryan O.; Chamberlin, Phillip C.

2016-03-01

Although it is the most prominent emission line in the solar spectrum, there has been a notable lack of studies devoted to variations in Lyα emission during solar flares in recent years. However, the few examples that do exist have shown Lyα emission to be a substantial radiator of the total energy budget of solar flares (of the order of 10%). It is also a known driver of fluctuations in the Earth's ionosphere. The EUV Variability Experiment (EVE) on board the Solar Dynamics Observatory now provides broadband, photometric Lyα data at 10 s cadence with its Multiple EUV Grating Spectrograph-Photometer (MEGS-P) component, and has observed scores of solar flares in the 5 years since it was launched. However, the MEGS-P time profiles appear to display a rise time of tens of minutes around the time of the flare onset. This is in stark contrast to the rapid, impulsive increase observed in other intrinsically chromospheric features (Hα, Lyβ, LyC, C III, etc.). Furthermore, the emission detected by MEGS-P peaks around the time of the peak of thermal soft X-ray emission and not during the impulsive phase when energy deposition in the chromosphere (often assumed to be in the form of non-thermal electrons) is greatest. The time derivative of Lyα lightcurves also appears to resemble that of the time derivative of soft X-rays, reminiscent of the Neupert effect. Given that spectrally-resolved Lyα observations during flares from SORCE/SOLSTICE peak during the impulsive phase as expected, this suggests that the atypical behaviour of MEGS-P data is a manifestation of the broadband nature of the observations. This could imply that other lines and/or continuum emission that becomes enhanced during flares could be contributing to the passband. Users are hereby urged to exercise caution when interpreting broadband Lyα observations of solar flares. Comparisons have also been made with other broadband Lyα photometers such as PROBA2/LYRA and GOES/EUVS-E.

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, ...

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.

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.

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.

Hyperspectral Probing of Exciton dynamics and Multiplication in PbSe Nanocrystals

NASA Astrophysics Data System (ADS)

Gdor, I.; Sachs, H.; Roitblat, A.; Strasfeld, D.; Bawendi, M. G.; Ruhman, S.

2013-03-01

Height time hyperspectral near IR probing providing broad-band coverage is employed on PbSe nanocrystals, uncovering spectral evolution following high energy photo-excitation due to hot exciton relaxation and recombination. Separation of single, double and triple exciton state contributions to these spectra is demonstrated, and the mechanisms underlying the course of spectral evolution are investigated. In addition no sign of MEG was detected in this sample up to a photon energy 3.7 times that of the band gap.

Versatile synchronized real-time MEG hardware controller for large-scale fast data acquisition.

PubMed

Sun, Limin; Han, Menglai; Pratt, Kevin; Paulson, Douglas; Dinh, Christoph; Esch, Lorenz; Okada, Yoshio; Hämäläinen, Matti

2017-05-01

Versatile controllers for accurate, fast, and real-time synchronized acquisition of large-scale data are useful in many areas of science, engineering, and technology. Here, we describe the development of a controller software based on a technique called queued state machine for controlling the data acquisition (DAQ) hardware, continuously acquiring a large amount of data synchronized across a large number of channels (>400) at a fast rate (up to 20 kHz/channel) in real time, and interfacing with applications for real-time data analysis and display of electrophysiological data. This DAQ controller was developed specifically for a 384-channel pediatric whole-head magnetoencephalography (MEG) system, but its architecture is useful for wide applications. This controller running in a LabVIEW environment interfaces with microprocessors in the MEG sensor electronics to control their real-time operation. It also interfaces with a real-time MEG analysis software via transmission control protocol/internet protocol, to control the synchronous acquisition and transfer of the data in real time from >400 channels to acquisition and analysis workstations. The successful implementation of this controller for an MEG system with a large number of channels demonstrates the feasibility of employing the present architecture in several other applications.

Versatile synchronized real-time MEG hardware controller for large-scale fast data acquisition

NASA Astrophysics Data System (ADS)

Sun, Limin; Han, Menglai; Pratt, Kevin; Paulson, Douglas; Dinh, Christoph; Esch, Lorenz; Okada, Yoshio; Hämäläinen, Matti

2017-05-01

Versatile controllers for accurate, fast, and real-time synchronized acquisition of large-scale data are useful in many areas of science, engineering, and technology. Here, we describe the development of a controller software based on a technique called queued state machine for controlling the data acquisition (DAQ) hardware, continuously acquiring a large amount of data synchronized across a large number of channels (>400) at a fast rate (up to 20 kHz/channel) in real time, and interfacing with applications for real-time data analysis and display of electrophysiological data. This DAQ controller was developed specifically for a 384-channel pediatric whole-head magnetoencephalography (MEG) system, but its architecture is useful for wide applications. This controller running in a LabVIEW environment interfaces with microprocessors in the MEG sensor electronics to control their real-time operation. It also interfaces with a real-time MEG analysis software via transmission control protocol/internet protocol, to control the synchronous acquisition and transfer of the data in real time from >400 channels to acquisition and analysis workstations. The successful implementation of this controller for an MEG system with a large number of channels demonstrates the feasibility of employing the present architecture in several other applications.

A three domain covariance framework for EEG/MEG data.

PubMed

Roś, Beata P; Bijma, Fetsje; de Gunst, Mathisca C M; de Munck, Jan C

2015-10-01

In this paper we introduce a covariance framework for the analysis of single subject EEG and MEG data that takes into account observed temporal stationarity on small time scales and trial-to-trial variations. We formulate a model for the covariance matrix, which is a Kronecker product of three components that correspond to space, time and epochs/trials, and consider maximum likelihood estimation of the unknown parameter values. An iterative algorithm that finds approximations of the maximum likelihood estimates is proposed. Our covariance model is applicable in a variety of cases where spontaneous EEG or MEG acts as source of noise and realistic noise covariance estimates are needed, such as in evoked activity studies, or where the properties of spontaneous EEG or MEG are themselves the topic of interest, like in combined EEG-fMRI experiments in which the correlation between EEG and fMRI signals is investigated. We use a simulation study to assess the performance of the estimator and investigate the influence of different assumptions about the covariance factors on the estimated covariance matrix and on its components. We apply our method to real EEG and MEG data sets. Copyright © 2015 Elsevier Inc. All rights reserved.

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

PubMed Central

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

2014-01-01

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

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

PubMed Central

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

2010-01-01

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

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.

Extending Transfer Entropy Improves Identification of Effective Connectivity in a Spiking Cortical Network Model

PubMed Central

Ito, Shinya; Hansen, Michael E.; Heiland, Randy; Lumsdaine, Andrew; Litke, Alan M.; Beggs, John M.

2011-01-01

Transfer entropy (TE) is an information-theoretic measure which has received recent attention in neuroscience for its potential to identify effective connectivity between neurons. Calculating TE for large ensembles of spiking neurons is computationally intensive, and has caused most investigators to probe neural interactions at only a single time delay and at a message length of only a single time bin. This is problematic, as synaptic delays between cortical neurons, for example, range from one to tens of milliseconds. In addition, neurons produce bursts of spikes spanning multiple time bins. To address these issues, here we introduce a free software package that allows TE to be measured at multiple delays and message lengths. To assess performance, we applied these extensions of TE to a spiking cortical network model (Izhikevich, 2006) with known connectivity and a range of synaptic delays. For comparison, we also investigated single-delay TE, at a message length of one bin (D1TE), and cross-correlation (CC) methods. We found that D1TE could identify 36% of true connections when evaluated at a false positive rate of 1%. For extended versions of TE, this dramatically improved to 73% of true connections. In addition, the connections correctly identified by extended versions of TE accounted for 85% of the total synaptic weight in the network. Cross correlation methods generally performed more poorly than extended TE, but were useful when data length was short. A computational performance analysis demonstrated that the algorithm for extended TE, when used on currently available desktop computers, could extract effective connectivity from 1 hr recordings containing 200 neurons in ∼5 min. We conclude that extending TE to multiple delays and message lengths improves its ability to assess effective connectivity between spiking neurons. These extensions to TE soon could become practical tools for experimentalists who record hundreds of spiking neurons. PMID:22102894

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.

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

Detection of changes of high-frequency activity by statistical time-frequency analysis in epileptic spikes

PubMed Central

Kobayashi, Katsuhiro; Jacobs, Julia; Gotman, Jean

2013-01-01

Objective A novel type of statistical time-frequency analysis was developed to elucidate changes of high-frequency EEG activity associated with epileptic spikes. Methods The method uses the Gabor Transform and detects changes of power in comparison to background activity using t-statistics that are controlled by the false discovery rate (FDR) to correct type I error of multiple testing. The analysis was applied to EEGs recorded at 2000 Hz from three patients with mesial temporal lobe epilepsy. Results Spike-related increase of high-frequency oscillations (HFOs) was clearly shown in the FDR-controlled t-spectra: it was most dramatic in spikes recorded from the hippocampus when the hippocampus was the seizure onset zone (SOZ). Depression of fast activity was observed immediately after the spikes, especially consistently in the discharges from the hippocampal SOZ. It corresponded to the slow wave part in case of spike-and-slow-wave complexes, but it was noted even in spikes without apparent slow waves. In one patient, a gradual increase of power above 200 Hz preceded spikes. Conclusions FDR-controlled t-spectra clearly detected the spike-related changes of HFOs that were unclear in standard power spectra. Significance We developed a promising tool to study the HFOs that may be closely linked to the pathophysiology of epileptogenesis. PMID:19394892

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...

Source localization of brain activity using helium-free interferometer

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

Dammers, Jürgen, E-mail: J.Dammers@fz-juelich.de; Chocholacs, Harald; Eich, Eberhard

2014-05-26

To detect extremely small magnetic fields generated by the human brain, currently all commercial magnetoencephalography (MEG) systems are equipped with low-temperature (low-T{sub c}) superconducting quantum interference device (SQUID) sensors that use liquid helium for cooling. The limited and increasingly expensive supply of helium, which has seen dramatic price increases recently, has become a real problem for such systems and the situation shows no signs of abating. MEG research in the long run is now endangered. In this study, we report a MEG source localization utilizing a single, highly sensitive SQUID cooled with liquid nitrogen only. Our findings confirm that localizationmore » of neuromagnetic activity is indeed possible using high-T{sub c} SQUIDs. We believe that our findings secure the future of this exquisitely sensitive technique and have major implications for brain research and the developments of cost-effective multi-channel, high-T{sub c} SQUID-based MEG systems.« less

Reduction of Werner Syndrome Protein Enhances G:C → A:T Transition by O6-Methylguanine in Human Cells.

PubMed

Suzuki, Tetsuya; Kuramoto, Yoshie; Kamiya, Hiroyuki

2018-05-21

O 6 -Methylguanine ( O 6 -MeG) is a damaged base produced by methylating reagents. The Werner syndrome protein (WRN) is a cancer-related human DNA helicase. The effects of WRN reduction on O 6 -MeG-caused mutagenesis were assessed by an siRNA-mediated knockdown in human U2OS cells, using a shuttle plasmid with a single O 6 -MeG base in the supF gene. The plasmid DNA was replicated in the cells, isolated, and electroporated into an Escherichia coli indicator strain. The lowered amount of WRN increased the frequency of mutations induced by O 6 -MeG, mainly G:C → A:T substitution. The increased mutation rate suggested that the cancer-related WRN suppresses the G:C → A:T substitution by O 6 -MeG in human cells.

Learning complex temporal patterns with resource-dependent spike timing-dependent plasticity.

PubMed

Hunzinger, Jason F; Chan, Victor H; Froemke, Robert C

2012-07-01

Studies of spike timing-dependent plasticity (STDP) have revealed that long-term changes in the strength of a synapse may be modulated substantially by temporal relationships between multiple presynaptic and postsynaptic spikes. Whereas long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength have been modeled as distinct or separate functional mechanisms, here, we propose a new shared resource model. A functional consequence of our model is fast, stable, and diverse unsupervised learning of temporal multispike patterns with a biologically consistent spiking neural network. Due to interdependencies between LTP and LTD, dendritic delays, and proactive homeostatic aspects of the model, neurons are equipped to learn to decode temporally coded information within spike bursts. Moreover, neurons learn spike timing with few exposures in substantial noise and jitter. Surprisingly, despite having only one parameter, the model also accurately predicts in vitro observations of STDP in more complex multispike trains, as well as rate-dependent effects. We discuss candidate commonalities in natural long-term plasticity mechanisms.

[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.

Multiscale analysis of neural spike trains.

PubMed

Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin

2014-01-30

This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. Copyright © 2013 John Wiley & Sons, Ltd.

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.

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

PubMed

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

2017-10-01

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

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

PubMed Central

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

2016-01-01

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

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.

Nonlinear Modeling of Causal Interrelationships in Neuronal Ensembles

PubMed Central

Zanos, Theodoros P.; Courellis, Spiros H.; Berger, Theodore W.; Hampson, Robert E.; Deadwyler, Sam A.; Marmarelis, Vasilis Z.

2009-01-01

The increasing availability of multiunit recordings gives new urgency to the need for effective analysis of “multidimensional” time-series data that are derived from the recorded activity of neuronal ensembles in the form of multiple sequences of action potentials—treated mathematically as point-processes and computationally as spike-trains. Whether in conditions of spontaneous activity or under conditions of external stimulation, the objective is the identification and quantification of possible causal links among the neurons generating the observed binary signals. A multiple-input/multiple-output (MIMO) modeling methodology is presented that can be used to quantify the neuronal dynamics of causal interrelationships in neuronal ensembles using spike-train data recorded from individual neurons. These causal interrelationships are modeled as transformations of spike-trains recorded from a set of neurons designated as the “inputs” into spike-trains recorded from another set of neurons designated as the “outputs.” The MIMO model is composed of a set of multiinput/single-output (MISO) modules, one for each output. Each module is the cascade of a MISO Volterra model and a threshold operator generating the output spikes. The Laguerre expansion approach is used to estimate the Volterra kernels of each MISO module from the respective input–output data using the least-squares method. The predictive performance of the model is evaluated with the use of the receiver operating characteristic (ROC) curve, from which the optimum threshold is also selected. The Mann–Whitney statistic is used to select the significant inputs for each output by examining the statistical significance of improvements in the predictive accuracy of the model when the respective inputs is included. Illustrative examples are presented for a simulated system and for an actual application using multiunit data recordings from the hippocampus of a behaving rat. PMID:18701382

Concizumab, an anti-tissue factor pathway inhibitor antibody, induces increased thrombin generation in plasma from haemophilia patients and healthy subjects measured by the thrombin generation assay.

PubMed

Waters, E K; Sigh, J; Friedrich, U; Hilden, I; Sørensen, B B

2017-09-01

Concizumab, a humanized monoclonal antibody against tissue factor pathway inhibitor (TFPI), is being developed as a subcutaneously (s.c.) administered treatment for haemophilia. It demonstrated a concentration-dependent procoagulant effect in functional TFPI assays; however, global haemostatic assays, such as the thrombin generation assay (TGA), offer a more complete picture of coagulation. We investigated how concizumab affects thrombin generation following ex vivo spiking in plasma from haemophilia patients using the TGA, and if the assay can detect the effect of multiple s.c. concizumab doses in healthy subjects. For the ex vivo spiking study, platelet-poor plasma (PPP) from 18 patients with severe haemophilia was spiked with 0.001-500 nm concizumab. For the multiple-dosing study, four healthy males received concizumab 250 μg kg -1 s.c. every other day for eight doses; blood was collected before and after dosing and processed into PPP. In both studies, thrombin generation was measured using a Calibrated Automated Thrombogram ® system with 1 pm tissue factor. In spiked samples from haemophilia patients, peak thrombin and endogenous thrombin potential (ETP) increased concentration dependently, reaching near-normal levels at concizumab concentrations >10 nm. Repeated s.c. doses of concizumab in healthy subjects increased both peak thrombin and ETP; these effects were sustained throughout the dosing interval. Thrombin generation assay demonstrated increased thrombin generation with concizumab after ex vivo spiking of haemophilia plasma and multiple s.c. doses in healthy subjects, supporting both the utility of the TGA in evaluating concizumab treatment and the potential of s.c. concizumab as a novel haemophilia therapy. © 2017 The Authors. Haemophilia Published by John Wiley & Sons Ltd.

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

Science.gov Websites

generation (MEG) in semiconductor nanocrystals, also called quantum dots, and recently found efficient MEG in silicon quantum dots. He shares the award with Stefan W. Glunz of the Fraunhofer Institute in Germany

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2010-08-11

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Shock Waves Mitigation at Blunt Bodies Using Needles and Shells Against a Supersonic Flow

NASA Technical Reports Server (NTRS)

Gilinsky, M.; Blankson, I. M.; Sakharov, V. I.; Shvets, A. I.

2004-01-01

The paper contains some experimental and numerical simulation test results on cylindrical blunt body drag reduction using thin spikes or shell mounted in front of a body against a supersonic flow. Experimental tests were conducted using the Aeromechanics and Gas Dynamics Laboratory facilities at the Institute of Mechanics of Moscow State University (IMMSU). Numerical simulations utilizing NASA and IM/MSU codes were conducted at the Hampton University Fluid Mechanics and Acoustics Laboratory. The main purpose of this research is to examine the efficiency of application of multiple spikes for drag reduction and flow stability at the front of a blunt body in different flight conditions, i.e. Mach number, angle of attack, etc. The principal conclusions of these test results are: multiple spike/needle application leads to decrease of drag reduction benefits by comparison with the case of one central mounted needle at the front of a blunt body, but increase lift benefits.

Through a glass darkly: some insights on change talk via magnetoencephalography.

PubMed

Houck, Jon M; Moyers, Theresa B; Tesche, Claudia D

2013-06-01

Motivational interviewing (MI) is a directive, client-centered therapeutic method employed in the treatment of substance abuse, with strong evidence of effectiveness. To date, the sole mechanism of action in MI with any consistent empirical support is "change talk" (CT), which is generally defined as client within-session speech in support of a behavior change. "Sustain talk" (ST) incorporates speech in support of the status quo. MI maintains that during treatment, clients essentially talk themselves into change. Multiple studies have now supported this theory, linking within-session speech to substance use outcomes. Although a causal chain has been established linking therapist behavior, client CT, and substance use outcome, the neural substrate of CT has been largely uncharted. We addressed this gap by measuring neural responses to clients' own CT using magnetoencephalography (MEG), a noninvasive neuroimaging technique with excellent spatial and temporal resolution. Following a recorded MI session, MEG was used to measure brain activity while participants heard multiple repetitions of their CT and ST utterances from that session, intermingled and presented in a random order. Results suggest that CT processing occurs in a right-hemisphere network that includes the inferior frontal gyrus, insula, and superior temporal cortex. These results support a representation of CT at the neural level, consistent with the role of these structures in self-perception. This suggests that during treatment sessions, clinicians who are able to evoke this special kind of language are tapping into neural circuitry that may be essential to behavior change. 2013 APA, all rights reserved

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.

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

Passemier, Damien; McKay, Matthew R.; Chen, Yang

2015-07-01

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

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

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.

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

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.

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

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.

Multiscale decoding for reliable brain-machine interface performance over time.

PubMed

Han-Lin Hsieh; Wong, Yan T; Pesaran, Bijan; Shanechi, Maryam M

2017-07-01

Recordings from invasive implants can degrade over time, resulting in a loss of spiking activity for some electrodes. For brain-machine interfaces (BMI), such a signal degradation lowers control performance. Achieving reliable performance over time is critical for BMI clinical viability. One approach to improve BMI longevity is to simultaneously use spikes and other recording modalities such as local field potentials (LFP), which are more robust to signal degradation over time. We have developed a multiscale decoder that can simultaneously model the different statistical profiles of multi-scale spike/LFP activity (discrete spikes vs. continuous LFP). This decoder can also run at multiple time-scales (millisecond for spikes vs. tens of milliseconds for LFP). Here, we validate the multiscale decoder for estimating the movement of 7 major upper-arm joint angles in a non-human primate (NHP) during a 3D reach-to-grasp task. The multiscale decoder uses motor cortical spike/LFP recordings as its input. We show that the multiscale decoder can improve decoding accuracy by adding information from LFP to spikes, while running at the fast millisecond time-scale of the spiking activity. Moreover, this improvement is achieved using relatively few LFP channels, demonstrating the robustness of the approach. These results suggest that using multiscale decoders has the potential to improve the reliability and longevity of BMIs.

Multiple Exciton Generation in Colloidal Nanocrystals

PubMed Central

Smith, Charles; Binks, David

2013-01-01

In a conventional solar cell, the energy of an absorbed photon in excess of the band gap is rapidly lost as heat, and this is one of the main reasons that the theoretical efficiency is limited to ~33%. However, an alternative process, multiple exciton generation (MEG), can occur in colloidal quantum dots. Here, some or all of the excess energy is instead used to promote one or more additional electrons to the conduction band, potentially increasing the photocurrent of a solar cell and thereby its output efficiency. This review will describe the development of this field over the decade since the first experimental demonstration of multiple exciton generation, including the controversies over experimental artefacts, comparison with similar effects in bulk materials, and the underlying mechanisms. We will also describe the current state-of-the-art and outline promising directions for further development. PMID:28348283

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task

PubMed Central

2017-01-01

Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP) are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making. PMID:28961245

Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks.

PubMed

Çakir, Yüksel

2016-01-01

Synchronization behaviors of bursting neurons coupled through electrical and dynamic chemical synapses are investigated. The Izhikevich model is used with random and small world network of bursting neurons. Various currents which consist of diffusive electrical and time-delayed dynamic chemical synapses are used in the simulations to investigate the influences of synaptic currents and couplings on synchronization behavior of bursting neurons. The effects of parameters, such as time delay, inhibitory synaptic strengths, and decay time on synchronization behavior are investigated. It is observed that in random networks with no delay, bursting synchrony is established with the electrical synapse alone, single spiking synchrony is observed with hybrid coupling. In small world network with no delay, periodic bursting behavior with multiple spikes is observed when only chemical and only electrical synapse exist. Single-spike and multiple-spike bursting are established with hybrid couplings. A decrease in the synchronization measure is observed with zero time delay, as the decay time is increased in random network. For synaptic delays which are above active phase period, synchronization measure increases with an increase in synaptic strength and time delay in small world network. However, in random network, it increases with only an increase in synaptic strength.

Application of modern tests for stationarity to single-trial MEG data: transferring powerful statistical tools from econometrics to neuroscience.

PubMed

Kipiński, Lech; König, Reinhard; Sielużycki, Cezary; Kordecki, Wojciech

2011-10-01

Stationarity is a crucial yet rarely questioned assumption in the analysis of time series of magneto- (MEG) or electroencephalography (EEG). One key drawback of the commonly used tests for stationarity of encephalographic time series is the fact that conclusions on stationarity are only indirectly inferred either from the Gaussianity (e.g. the Shapiro-Wilk test or Kolmogorov-Smirnov test) or the randomness of the time series and the absence of trend using very simple time-series models (e.g. the sign and trend tests by Bendat and Piersol). We present a novel approach to the analysis of the stationarity of MEG and EEG time series by applying modern statistical methods which were specifically developed in econometrics to verify the hypothesis that a time series is stationary. We report our findings of the application of three different tests of stationarity--the Kwiatkowski-Phillips-Schmidt-Schin (KPSS) test for trend or mean stationarity, the Phillips-Perron (PP) test for the presence of a unit root and the White test for homoscedasticity--on an illustrative set of MEG data. For five stimulation sessions, we found already for short epochs of duration of 250 and 500 ms that, although the majority of the studied epochs of single MEG trials were usually mean-stationary (KPSS test and PP test), they were classified as nonstationary due to their heteroscedasticity (White test). We also observed that the presence of external auditory stimulation did not significantly affect the findings regarding the stationarity of the data. We conclude that the combination of these tests allows a refined analysis of the stationarity of MEG and EEG time series.

Tracking neural coding of perceptual and semantic features of concrete nouns

PubMed Central

Sudre, Gustavo; Pomerleau, Dean; Palatucci, Mark; Wehbe, Leila; Fyshe, Alona; Salmelin, Riitta; Mitchell, Tom

2015-01-01

We present a methodological approach employing magnetoencephalography (MEG) and machine learning techniques to investigate the flow of perceptual and semantic information decodable from neural activity in the half second during which the brain comprehends the meaning of a concrete noun. Important information about the cortical location of neural activity related to the representation of nouns in the human brain has been revealed by past studies using fMRI. However, the temporal sequence of processing from sensory input to concept comprehension remains unclear, in part because of the poor time resolution provided by fMRI. In this study, subjects answered 20 questions (e.g. is it alive?) about the properties of 60 different nouns prompted by simultaneous presentation of a pictured item and its written name. Our results show that the neural activity observed with MEG encodes a variety of perceptual and semantic features of stimuli at different times relative to stimulus onset, and in different cortical locations. By decoding these features, our MEG-based classifier was able to reliably distinguish between two different concrete nouns that it had never seen before. The results demonstrate that there are clear differences between the time course of the magnitude of MEG activity and that of decodable semantic information. Perceptual features were decoded from MEG activity earlier in time than semantic features, and features related to animacy, size, and manipulability were decoded consistently across subjects. We also observed that regions commonly associated with semantic processing in the fMRI literature may not show high decoding results in MEG. We believe that this type of approach and the accompanying machine learning methods can form the basis for further modeling of the flow of neural information during language processing and a variety of other cognitive processes. PMID:22565201

Fast Neural Dynamics of Proactive Cognitive Control in a Task-Switching Analogue of the Wisconsin Card Sorting Test.

PubMed

Gema Díaz-Blancat; Juan García-Prieto; Fernando Maestú; Francisco Barceló

2018-05-01

One common assumption has been that prefrontal executive control is mostly required for target detection (Posner and Petersen in Ann Rev Neurosci 13:25-42, 1990). Alternatively, cognitive control has also been related to anticipatory updating of task-set (contextual) information, a view that highlights proactive control processes. Frontoparietal cortical networks contribute to both proactive control and reactive target detection, although their fast dynamics are still largely unexplored. To examine this, we analyzed rapid magnetoencephalographic (MEG) source activations elicited by task cues and target cards in a task-cueing analogue of the Wisconsin Card Sorting Test. A single-task (color sorting) condition with equivalent perceptual and motor demands was used as a control. Our results revealed fast, transient and largely switch-specific MEG activations across frontoparietal and cingulo-opercular regions in anticipation of target cards, including (1) early (100-200 ms) cue-locked MEG signals at visual, temporo-parietal and prefrontal cortices of the right hemisphere (i.e., calcarine sulcus, precuneus, inferior frontal gyrus, anterior insula and supramarginal gyrus); and (2) later cue-locked MEG signals at the right anterior and posterior insula (200-300 ms) and the left temporo-parietal junction (300-500 ms). In all cases larger MEG signal intensity was observed in switch relative to repeat cueing conditions. Finally, behavioral restart costs and test scores of working memory capacity (forward digit span) correlated with cue-locked MEG activations at key nodes of the frontoparietal network. Together, our findings suggest that proactive cognitive control of task rule updating can be fast and transiently implemented within less than a second and in anticipation of target detection.

Correlation between magnetoencephalography-based "clusterectomy" and postoperative seizure freedom.

PubMed

Vadera, Sumeet; Jehi, Lara; Burgess, Richard C; Shea, Katherine; Alexopoulos, Andreas V; Mosher, John; Gonzalez-Martinez, Jorge; Bingaman, William

2013-06-01

During the presurgical evaluation of patients with medically intractable focal epilepsy, a variety of noninvasive studies are performed to localize the hypothetical epileptogenic zone and guide the resection. Magnetoencephalography (MEG) is becoming increasingly used in the clinical realm for this purpose. No investigators have previously reported on coregisteration of MEG clusters with postoperative resection cavities to evaluate whether complete "clusterectomy" (resection of the area associated with MEG clusters) was performed or to compare these findings with postoperative seizure-free outcomes. The authors retrospectively reviewed the charts and imaging studies of 65 patients undergoing MEG followed by resective epilepsy surgery from 2009 until 2012 at the Cleveland Clinic. Preoperative MEG studies were fused with postoperative MRI studies to evaluate whether clusters were within the resected area. These data were then correlated with postoperative seizure freedom. Sixty-five patients were included in this study. The average duration of follow-up was 13.9 months, the mean age at surgery was 23.1 years, and the mean duration of epilepsy was 13.7 years. In 30 patients, the main cluster was located completely within the resection cavity, in 28 it was completely outside the resection cavity, and in 7 it was partially within the resection cavity. Seventy-four percent of patients were seizure free at 12 months after surgery, and this rate decreased to 60% at 24 months. Improved likelihood of seizure freedom was seen with complete clusterectomy in patients with localization outside the temporal lobe (extra-temporal lobe epilepsy) (p = 0.04). In patients with preoperative MEG studies that show clusters in surgically accessible areas outside the temporal lobe, we suggest aggressive resection to improve the chances for seizure freedom. When the cluster is found within the temporal lobe, further diagnostic testing may be required to better localize the epileptogenic zone.

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

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.

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

Altered modulation of gamma oscillation frequency by speed of visual motion in children with autism spectrum disorders.

PubMed

Stroganova, Tatiana A; Butorina, Anna V; Sysoeva, Olga V; Prokofyev, Andrey O; Nikolaeva, Anastasia Yu; Tsetlin, Marina M; Orekhova, Elena V

2015-01-01

Recent studies link autism spectrum disorders (ASD) with an altered balance between excitation and inhibition (E/I balance) in cortical networks. The brain oscillations in high gamma-band (50-120 Hz) are sensitive to the E/I balance and may appear useful biomarkers of certain ASD subtypes. The frequency of gamma oscillations is mediated by level of excitation of the fast-spiking inhibitory basket cells recruited by increasing strength of excitatory input. Therefore, the experimental manipulations affecting gamma frequency may throw light on inhibitory networks dysfunction in ASD. Here, we used magnetoencephalography (MEG) to investigate modulation of visual gamma oscillation frequency by speed of drifting annular gratings (1.2, 3.6, 6.0 °/s) in 21 boys with ASD and 26 typically developing boys aged 7-15 years. Multitaper method was used for analysis of spectra of gamma power change upon stimulus presentation and permutation test was applied for statistical comparisons. We also assessed in our participants visual orientation discrimination thresholds, which are thought to depend on excitability of inhibitory networks in the visual cortex. Although frequency of the oscillatory gamma response increased with increasing velocity of visual motion in both groups of participants, the velocity effect was reduced in a substantial proportion of children with ASD. The range of velocity-related gamma frequency modulation correlated inversely with the ability to discriminate oblique line orientation in the ASD group, while no such correlation has been observed in the group of typically developing participants. Our findings suggest that abnormal velocity-related gamma frequency modulation in ASD may constitute a potential biomarker for reduced excitability of fast-spiking inhibitory neurons in a subset of children with ASD.

[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.

Spiking Neural Network With Distributed Plasticity Reproduces Cerebellar Learning in Eye Blink Conditioning Paradigms.

PubMed

Antonietti, Alberto; Casellato, Claudia; Garrido, Jesús A; Luque, Niceto R; Naveros, Francisco; Ros, Eduardo; D' Angelo, Egidio; Pedrocchi, Alessandra

2016-01-01

In this study, we defined a realistic cerebellar model through the use of artificial spiking neural networks, testing it in computational simulations that reproduce associative motor tasks in multiple sessions of acquisition and extinction. By evolutionary algorithms, we tuned the cerebellar microcircuit to find out the near-optimal plasticity mechanism parameters that better reproduced human-like behavior in eye blink classical conditioning, one of the most extensively studied paradigms related to the cerebellum. We used two models: one with only the cortical plasticity and another including two additional plasticity sites at nuclear level. First, both spiking cerebellar models were able to well reproduce the real human behaviors, in terms of both "timing" and "amplitude", expressing rapid acquisition, stable late acquisition, rapid extinction, and faster reacquisition of an associative motor task. Even though the model with only the cortical plasticity site showed good learning capabilities, the model with distributed plasticity produced faster and more stable acquisition of conditioned responses in the reacquisition phase. This behavior is explained by the effect of the nuclear plasticities, which have slow dynamics and can express memory consolidation and saving. We showed how the spiking dynamics of multiple interactive neural mechanisms implicitly drive multiple essential components of complex learning processes.  This study presents a very advanced computational model, developed together by biomedical engineers, computer scientists, and neuroscientists. Since its realistic features, the proposed model can provide confirmations and suggestions about neurophysiological and pathological hypotheses and can be used in challenging clinical applications.

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.

Learning to Select Actions with Spiking Neurons in the Basal Ganglia

PubMed Central

Stewart, Terrence C.; Bekolay, Trevor; Eliasmith, Chris

2012-01-01

We expand our existing spiking neuron model of decision making in the cortex and basal ganglia to include local learning on the synaptic connections between the cortex and striatum, modulated by a dopaminergic reward signal. We then compare this model to animal data in the bandit task, which is used to test rodent learning in conditions involving forced choice under rewards. Our results indicate a good match in terms of both behavioral learning results and spike patterns in the ventral striatum. The model successfully generalizes to learning the utilities of multiple actions, and can learn to choose different actions in different states. The purpose of our model is to provide both high-level behavioral predictions and low-level spike timing predictions while respecting known neurophysiology and neuroanatomy. PMID:22319465

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.

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"…

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.

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.

Enhanced interlaminar excitation or reduced superficial layer inhibition in neocortex generates different spike-and-wave-like electrographic events in vitro

PubMed Central

Hall, Stephen P.; Traub, Roger D.; Adams, Natalie E.; Cunningham, Mark O.; Schofield, Ian; Jenkins, Alistair J.

2018-01-01

Acute in vitro models have revealed a great deal of information about mechanisms underlying many types of epileptiform activity. However, few examples exist that shed light on spike-and-wave (SpW) patterns of pathological activity. SpW are seen in many epilepsy syndromes, both generalized and focal, and manifest across the entire age spectrum. They are heterogeneous in terms of their severity, symptom burden, and apparent anatomical origin (thalamic, neocortical, or both), but any relationship between this heterogeneity and underlying pathology remains elusive. In this study we demonstrate that physiological delta-frequency rhythms act as an effective substrate to permit modeling of SpW of cortical origin and may help to address this issue. For a starting point of delta activity, multiple subtypes of SpW could be modeled computationally and experimentally by either enhancing the magnitude of excitatory synaptic events ascending from neocortical layer 5 to layers 2/3 or selectively modifying superficial layer GABAergic inhibition. The former generated SpW containing multiple field spikes with long interspike intervals, whereas the latter generated SpW with short-interval multiple field spikes. Both types had different laminar origins and each disrupted interlaminar cortical dynamics in a different manner. A small number of examples of human recordings from patients with different diagnoses revealed SpW subtypes with the same temporal signatures, suggesting that detailed quantification of the pattern of spikes in SpW discharges may be a useful indicator of disparate underlying epileptogenic pathologies. NEW & NOTEWORTHY Spike-and-wave-type discharges (SpW) are a common feature in many epilepsies. Their electrographic manifestation is highly varied, as are available genetic clues to associated underlying pathology. Using computational and in vitro models, we demonstrate that distinct subtypes of SpW are generated by lamina-selective disinhibition or enhanced interlaminar excitation. These subtypes could be detected in at least some noninvasive patient recordings, suggesting more detailed analysis of SpW may be useful in determining clinical pathology. PMID:28954894

Enhanced interlaminar excitation or reduced superficial layer inhibition in neocortex generates different spike-and-wave-like electrographic events in vitro.

PubMed

Hall, Stephen P; Traub, Roger D; Adams, Natalie E; Cunningham, Mark O; Schofield, Ian; Jenkins, Alistair J; Whittington, Miles A

2018-01-01

Acute in vitro models have revealed a great deal of information about mechanisms underlying many types of epileptiform activity. However, few examples exist that shed light on spike-and-wave (SpW) patterns of pathological activity. SpW are seen in many epilepsy syndromes, both generalized and focal, and manifest across the entire age spectrum. They are heterogeneous in terms of their severity, symptom burden, and apparent anatomical origin (thalamic, neocortical, or both), but any relationship between this heterogeneity and underlying pathology remains elusive. In this study we demonstrate that physiological delta-frequency rhythms act as an effective substrate to permit modeling of SpW of cortical origin and may help to address this issue. For a starting point of delta activity, multiple subtypes of SpW could be modeled computationally and experimentally by either enhancing the magnitude of excitatory synaptic events ascending from neocortical layer 5 to layers 2/3 or selectively modifying superficial layer GABAergic inhibition. The former generated SpW containing multiple field spikes with long interspike intervals, whereas the latter generated SpW with short-interval multiple field spikes. Both types had different laminar origins and each disrupted interlaminar cortical dynamics in a different manner. A small number of examples of human recordings from patients with different diagnoses revealed SpW subtypes with the same temporal signatures, suggesting that detailed quantification of the pattern of spikes in SpW discharges may be a useful indicator of disparate underlying epileptogenic pathologies. NEW & NOTEWORTHY Spike-and-wave-type discharges (SpW) are a common feature in many epilepsies. Their electrographic manifestation is highly varied, as are available genetic clues to associated underlying pathology. Using computational and in vitro models, we demonstrate that distinct subtypes of SpW are generated by lamina-selective disinhibition or enhanced interlaminar excitation. These subtypes could be detected in at least some noninvasive patient recordings, suggesting more detailed analysis of SpW may be useful in determining clinical pathology.

A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals.

PubMed

Kim, Yoon Jae; Park, Sung Woo; Yeom, Hong Gi; Bang, Moon Suk; Kim, June Sic; Chung, Chun Kee; Kim, Sungwan

2015-08-20

A brain-machine interface (BMI) should be able to help people with disabilities by replacing their lost motor functions. To replace lost functions, robot arms have been developed that are controlled by invasive neural signals. Although invasive neural signals have a high spatial resolution, non-invasive neural signals are valuable because they provide an interface without surgery. Thus, various researchers have developed robot arms driven by non-invasive neural signals. However, robot arm control based on the imagined trajectory of a human hand can be more intuitive for patients. In this study, therefore, an integrated robot arm-gripper system (IRAGS) that is driven by three-dimensional (3D) hand trajectories predicted from non-invasive neural signals was developed and verified. The IRAGS was developed by integrating a six-degree of freedom robot arm and adaptive robot gripper. The system was used to perform reaching and grasping motions for verification. The non-invasive neural signals, magnetoencephalography (MEG) and electroencephalography (EEG), were obtained to control the system. The 3D trajectories were predicted by multiple linear regressions. A target sphere was placed at the terminal point of the real trajectories, and the system was commanded to grasp the target at the terminal point of the predicted trajectories. The average correlation coefficient between the predicted and real trajectories in the MEG case was [Formula: see text] ([Formula: see text]). In the EEG case, it was [Formula: see text] ([Formula: see text]). The success rates in grasping the target plastic sphere were 18.75 and 7.50 % with MEG and EEG, respectively. The success rates of touching the target were 52.50 and 58.75 % respectively. A robot arm driven by 3D trajectories predicted from non-invasive neural signals was implemented, and reaching and grasping motions were performed. In most cases, the robot closely approached the target, but the success rate was not very high because the non-invasive neural signal is less accurate. However the success rate could be sufficiently improved for practical applications by using additional sensors. Robot arm control based on hand trajectories predicted from EEG would allow for portability, and the performance with EEG was comparable to that with MEG.

Anomalous Temporal Behaviour of Broadband Ly Alpha Observations During Solar Flares from SDO/EVE

NASA Technical Reports Server (NTRS)

Milligan, Ryan O.; Chamberlin, Phillip C.

2016-01-01

Although it is the most prominent emission line in the solar spectrum, there has been a notable lack of studies devoted to variations in Lyman-alpha (Ly-alpha) emission during solar flares in recent years. However, the few examples that do exist have shown Ly-alpha emission to be a substantial radiator of the total energy budget of solar flares (of the order of 10 percent). It is also a known driver of fluctuations in the Earth's ionosphere. The EUV (Extreme Ultra-Violet) Variability Experiment (EVE) on board the Solar Dynamics Observatory (SDO) now provides broadband, photometric Ly-alpha data at 10-second cadence with its Multiple EUV Grating Spectrograph-Photometer (MEGS-P) component, and has observed scores of solar flares in the 5 years since it was launched. However, the MEGS-P time profiles appear to display a rise time of tens of minutes around the time of the flare onset. This is in stark contrast to the rapid, impulsive increase observed in other intrinsically chromospheric features (H-alpha, Ly-beta, LyC, C III, etc.). Furthermore, the emission detected by MEGS-P peaks around the time of the peak of thermal soft X-ray emission and not during the impulsive phase when energy deposition in the chromosphere (often assumed to be in the form of non-thermal electrons) is greatest. The time derivative of Ly-alpha lightcurves also appears to resemble that of the time derivative of soft X-rays, reminiscent of the Neupert effect. Given that spectrally-resolved Ly-alpha observations during flares from SORCE / SOLSTICE (Solar Radiation and Climate Experiment / Solar Stellar Irradiance Comparison Experiment) peak during the impulsive phase as expected, this suggests that the atypical behaviour of MEGS-P data is a manifestation of the broadband nature of the observations. This could imply that other lines andor continuum emission that becomes enhanced during flares could be contributing to the passband. Users are hereby urged to exercise caution when interpreting broadband Ly-alpha observations of solar flares. Comparisons have also been made with other broadband Ly-alpha photometers such as PROBA2 (Project for On-Board Autonomy-2) / LYRA (Lyman Alpha Radiometer) and GOES (Geostationary Operational Environmental Satellite) / EUVE (Extreme Ultraviolet Explorer).

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…

A case for spiking neural network simulation based on configurable multiple-FPGA systems.

PubMed

Yang, Shufan; Wu, Qiang; Li, Renfa

2011-09-01

Recent neuropsychological research has begun to reveal that neurons encode information in the timing of spikes. Spiking neural network simulations are a flexible and powerful method for investigating the behaviour of neuronal systems. Simulation of the spiking neural networks in software is unable to rapidly generate output spikes in large-scale of neural network. An alternative approach, hardware implementation of such system, provides the possibility to generate independent spikes precisely and simultaneously output spike waves in real time, under the premise that spiking neural network can take full advantage of hardware inherent parallelism. We introduce a configurable FPGA-oriented hardware platform for spiking neural network simulation in this work. We aim to use this platform to combine the speed of dedicated hardware with the programmability of software so that it might allow neuroscientists to put together sophisticated computation experiments of their own model. A feed-forward hierarchy network is developed as a case study to describe the operation of biological neural systems (such as orientation selectivity of visual cortex) and computational models of such systems. This model demonstrates how a feed-forward neural network constructs the circuitry required for orientation selectivity and provides platform for reaching a deeper understanding of the primate visual system. In the future, larger scale models based on this framework can be used to replicate the actual architecture in visual cortex, leading to more detailed predictions and insights into visual perception phenomenon.

Predicting Spike Occurrence and Neuronal Responsiveness from LFPs in Primary Somatosensory Cortex

PubMed Central

Storchi, Riccardo; Zippo, Antonio G.; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E. M.

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role. PMID:22586452

Predicting spike occurrence and neuronal responsiveness from LFPs in primary somatosensory cortex.

PubMed

Storchi, Riccardo; Zippo, Antonio G; Caramenti, Gian Carlo; Valente, Maurizio; Biella, Gabriele E M

2012-01-01

Local Field Potentials (LFPs) integrate multiple neuronal events like synaptic inputs and intracellular potentials. LFP spatiotemporal features are particularly relevant in view of their applications both in research (e.g. for understanding brain rhythms, inter-areal neural communication and neuronal coding) and in the clinics (e.g. for improving invasive Brain-Machine Interface devices). However the relation between LFPs and spikes is complex and not fully understood. As spikes represent the fundamental currency of neuronal communication this gap in knowledge strongly limits our comprehension of neuronal phenomena underlying LFPs. We investigated the LFP-spike relation during tactile stimulation in primary somatosensory (S-I) cortex in the rat. First we quantified how reliably LFPs and spikes code for a stimulus occurrence. Then we used the information obtained from our analyses to design a predictive model for spike occurrence based on LFP inputs. The model was endowed with a flexible meta-structure whose exact form, both in parameters and structure, was estimated by using a multi-objective optimization strategy. Our method provided a set of nonlinear simple equations that maximized the match between models and true neurons in terms of spike timings and Peri Stimulus Time Histograms. We found that both LFPs and spikes can code for stimulus occurrence with millisecond precision, showing, however, high variability. Spike patterns were predicted significantly above chance for 75% of the neurons analysed. Crucially, the level of prediction accuracy depended on the reliability in coding for the stimulus occurrence. The best predictions were obtained when both spikes and LFPs were highly responsive to the stimuli. Spike reliability is known to depend on neuron intrinsic properties (i.e. on channel noise) and on spontaneous local network fluctuations. Our results suggest that the latter, measured through the LFP response variability, play a dominant role.

Nonlinear decoding of a complex movie from the mammalian retina

PubMed Central

Deny, Stéphane; Martius, Georg

2018-01-01

Retina is a paradigmatic system for studying sensory encoding: the transformation of light into spiking activity of ganglion cells. The inverse problem, where stimulus is reconstructed from spikes, has received less attention, especially for complex stimuli that should be reconstructed “pixel-by-pixel”. We recorded around a hundred neurons from a dense patch in a rat retina and decoded movies of multiple small randomly-moving discs. We constructed nonlinear (kernelized and neural network) decoders that improved significantly over linear results. An important contribution to this was the ability of nonlinear decoders to reliably separate between neural responses driven by locally fluctuating light signals, and responses at locally constant light driven by spontaneous-like activity. This improvement crucially depended on the precise, non-Poisson temporal structure of individual spike trains, which originated in the spike-history dependence of neural responses. We propose a general principle by which downstream circuitry could discriminate between spontaneous and stimulus-driven activity based solely on higher-order statistical structure in the incoming spike trains. PMID:29746463

Implementing Signature Neural Networks with Spiking Neurons

PubMed Central

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm—i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data—to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks. PMID:28066221

Implementing Signature Neural Networks with Spiking Neurons.

PubMed

Carrillo-Medina, José Luis; Latorre, Roberto

2016-01-01

Spiking Neural Networks constitute the most promising approach to develop realistic Artificial Neural Networks (ANNs). Unlike traditional firing rate-based paradigms, information coding in spiking models is based on the precise timing of individual spikes. It has been demonstrated that spiking ANNs can be successfully and efficiently applied to multiple realistic problems solvable with traditional strategies (e.g., data classification or pattern recognition). In recent years, major breakthroughs in neuroscience research have discovered new relevant computational principles in different living neural systems. Could ANNs benefit from some of these recent findings providing novel elements of inspiration? This is an intriguing question for the research community and the development of spiking ANNs including novel bio-inspired information coding and processing strategies is gaining attention. From this perspective, in this work, we adapt the core concepts of the recently proposed Signature Neural Network paradigm-i.e., neural signatures to identify each unit in the network, local information contextualization during the processing, and multicoding strategies for information propagation regarding the origin and the content of the data-to be employed in a spiking neural network. To the best of our knowledge, none of these mechanisms have been used yet in the context of ANNs of spiking neurons. This paper provides a proof-of-concept for their applicability in such networks. Computer simulations show that a simple network model like the discussed here exhibits complex self-organizing properties. The combination of multiple simultaneous encoding schemes allows the network to generate coexisting spatio-temporal patterns of activity encoding information in different spatio-temporal spaces. As a function of the network and/or intra-unit parameters shaping the corresponding encoding modality, different forms of competition among the evoked patterns can emerge even in the absence of inhibitory connections. These parameters also modulate the memory capabilities of the network. The dynamical modes observed in the different informational dimensions in a given moment are independent and they only depend on the parameters shaping the information processing in this dimension. In view of these results, we argue that plasticity mechanisms inside individual cells and multicoding strategies can provide additional computational properties to spiking neural networks, which could enhance their capacity and performance in a wide variety of real-world tasks.

A Simple Method to Simultaneously Detect and Identify Spikes from Raw Extracellular Recordings.

PubMed

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2015-01-01

The ability to track when and which neurons fire in the vicinity of an electrode, in an efficient and reliable manner can revolutionize the neuroscience field. The current bottleneck lies in spike sorting algorithms; existing methods for detecting and discriminating the activity of multiple neurons rely on inefficient, multi-step processing of extracellular recordings. In this work, we show that a single-step processing of raw (unfiltered) extracellular signals is sufficient for both the detection and identification of active neurons, thus greatly simplifying and optimizing the spike sorting approach. The efficiency and reliability of our method is demonstrated in both real and simulated data.

Recording large-scale neuronal ensembles with silicon probes in the anesthetized rat.

PubMed

Schjetnan, Andrea Gomez Palacio; Luczak, Artur

2011-10-19

Large scale electrophysiological recordings from neuronal ensembles offer the opportunity to investigate how the brain orchestrates the wide variety of behaviors from the spiking activity of its neurons. One of the most effective methods to monitor spiking activity from a large number of neurons in multiple local neuronal circuits simultaneously is by using silicon electrode arrays. Action potentials produce large transmembrane voltage changes in the vicinity of cell somata. These output signals can be measured by placing a conductor in close proximity of a neuron. If there are many active (spiking) neurons in the vicinity of the tip, the electrode records combined signal from all of them, where contribution of a single neuron is weighted by its 'electrical distance'. Silicon probes are ideal recording electrodes to monitor multiple neurons because of a large number of recording sites (+64) and a small volume. Furthermore, multiple sites can be arranged over a distance of millimeters, thus allowing for the simultaneous recordings of neuronal activity in the various cortical layers or in multiple cortical columns (Fig. 1). Importantly, the geometrically precise distribution of the recording sites also allows for the determination of the spatial relationship of the isolated single neurons. Here, we describe an acute, large-scale neuronal recording from the left and right forelimb somatosensory cortex simultaneously in an anesthetized rat with silicon probes (Fig. 2).

Recording Large-scale Neuronal Ensembles with Silicon Probes in the Anesthetized Rat

PubMed Central

Schjetnan, Andrea Gomez Palacio; Luczak, Artur

2011-01-01

Large scale electrophysiological recordings from neuronal ensembles offer the opportunity to investigate how the brain orchestrates the wide variety of behaviors from the spiking activity of its neurons. One of the most effective methods to monitor spiking activity from a large number of neurons in multiple local neuronal circuits simultaneously is by using silicon electrode arrays1-3. Action potentials produce large transmembrane voltage changes in the vicinity of cell somata. These output signals can be measured by placing a conductor in close proximity of a neuron. If there are many active (spiking) neurons in the vicinity of the tip, the electrode records combined signal from all of them, where contribution of a single neuron is weighted by its 'electrical distance'. Silicon probes are ideal recording electrodes to monitor multiple neurons because of a large number of recording sites (+64) and a small volume. Furthermore, multiple sites can be arranged over a distance of millimeters, thus allowing for the simultaneous recordings of neuronal activity in the various cortical layers or in multiple cortical columns (Fig. 1). Importantly, the geometrically precise distribution of the recording sites also allows for the determination of the spatial relationship of the isolated single neurons4. Here, we describe an acute, large-scale neuronal recording from the left and right forelimb somatosensory cortex simultaneously in an anesthetized rat with silicon probes (Fig. 2). PMID:22042361

MEG evidence that the central auditory system simultaneously encodes multiple temporal cues.

PubMed

Simpson, Michael I G; Barnes, Gareth R; Johnson, Sam R; Hillebrand, Arjan; Singh, Krish D; Green, Gary G R

2009-09-01

Speech contains complex amplitude modulations that have envelopes with multiple temporal cues. The processing of these complex envelopes is not well explained by the classical models of amplitude modulation processing. This may be because the evidence for the models typically comes from the use of simple sinusoidal amplitude modulations. In this study we used magnetoencephalography (MEG) to generate source space current estimates of the steady-state responses to simple one-component amplitude modulations and to a two-component amplitude modulation. A two-component modulation introduces the simplest form of modulation complexity into the waveform; the summation of the two-modulation rates introduces a beat-like modulation at the difference frequency between the two modulation rates. We compared the cortical representations of responses to the one-component and two-component modulations. In particular, we show that the temporal complexity in the two-component amplitude modulation stimuli was preserved at the cortical level. The method of stimulus normalization that we used also allows us to interpret these results as evidence that the important feature in sound modulations is the relative depth of one modulation rate with respect to another, rather than the absolute carrier-to-sideband modulation depth. More generally, this may be interpreted as evidence that modulation detection accurately preserves a representation of the modulation envelope. This is an important observation with respect to models of modulation processing, as it suggests that models may need a dynamic processing step to effectively model non-stationary stimuli. We suggest that the classic modulation filterbank model needs to be modified to take these findings into account.

Noise covariance incorporated MEG-MUSIC algorithm: a method for multiple-dipole estimation tolerant of the influence of background brain activity.

PubMed

Sekihara, K; Poeppel, D; Marantz, A; Koizumi, H; Miyashita, Y

1997-09-01

This paper proposes a method of localizing multiple current dipoles from spatio-temporal biomagnetic data. The method is based on the multiple signal classification (MUSIC) algorithm and is tolerant of the influence of background brain activity. In this method, the noise covariance matrix is estimated using a portion of the data that contains noise, but does not contain any signal information. Then, a modified noise subspace projector is formed using the generalized eigenvectors of the noise and measured-data covariance matrices. The MUSIC localizer is calculated using this noise subspace projector and the noise covariance matrix. The results from a computer simulation have verified the effectiveness of the method. The method was then applied to source estimation for auditory-evoked fields elicited by syllable speech sounds. The results strongly suggest the method's effectiveness in removing the influence of background activity.

Preserving information in neural transmission.

PubMed

Sincich, Lawrence C; Horton, Jonathan C; Sharpee, Tatyana O

2009-05-13

Along most neural pathways, the spike trains transmitted from one neuron to the next are altered. In the process, neurons can either achieve a more efficient stimulus representation, or extract some biologically important stimulus parameter, or succeed at both. We recorded the inputs from single retinal ganglion cells and the outputs from connected lateral geniculate neurons in the macaque to examine how visual signals are relayed from retina to cortex. We found that geniculate neurons re-encoded multiple temporal stimulus features to yield output spikes that carried more information about stimuli than was available in each input spike. The coding transformation of some relay neurons occurred with no decrement in information rate, despite output spike rates that averaged half the input spike rates. This preservation of transmitted information was achieved by the short-term summation of inputs that geniculate neurons require to spike. A reduced model of the retinal and geniculate visual responses, based on two stimulus features and their associated nonlinearities, could account for >85% of the total information available in the spike trains and the preserved information transmission. These results apply to neurons operating on a single time-varying input, suggesting that synaptic temporal integration can alter the temporal receptive field properties to create a more efficient representation of visual signals in the thalamus than the retina.

Design of Spiking Central Pattern Generators for Multiple Locomotion Gaits in Hexapod Robots by Christiansen Grammar Evolution

PubMed Central

Espinal, Andres; Rostro-Gonzalez, Horacio; Carpio, Martin; Guerra-Hernandez, Erick I.; Ornelas-Rodriguez, Manuel; Sotelo-Figueroa, Marco

2016-01-01

This paper presents a method to design Spiking Central Pattern Generators (SCPGs) to achieve locomotion at different frequencies on legged robots. It is validated through embedding its designs into a Field-Programmable Gate Array (FPGA) and implemented on a real hexapod robot. The SCPGs are automatically designed by means of a Christiansen Grammar Evolution (CGE)-based methodology. The CGE performs a solution for the configuration (synaptic weights and connections) for each neuron in the SCPG. This is carried out through the indirect representation of candidate solutions that evolve to replicate a specific spike train according to a locomotion pattern (gait) by measuring the similarity between the spike trains and the SPIKE distance to lead the search to a correct configuration. By using this evolutionary approach, several SCPG design specifications can be explicitly added into the SPIKE distance-based fitness function, such as looking for Spiking Neural Networks (SNNs) with minimal connectivity or a Central Pattern Generator (CPG) able to generate different locomotion gaits only by changing the initial input stimuli. The SCPG designs have been successfully implemented on a Spartan 6 FPGA board and a real time validation on a 12 Degrees Of Freedom (DOFs) hexapod robot is presented. PMID:27516737

Emergent properties of interacting populations of spiking neurons.

PubMed

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations.

Arcuate hypothalamic AgRP and putative POMC neurons show opposite changes in spiking across multiple timescales

PubMed Central

Mandelblat-Cerf, Yael; Ramesh, Rohan N; Burgess, Christian R; Patella, Paola; Yang, Zongfang; Lowell, Bradford B; Andermann, Mark L

2015-01-01

Agouti-related-peptide (AgRP) neurons—interoceptive neurons in the arcuate nucleus of the hypothalamus (ARC)—are both necessary and sufficient for driving feeding behavior. To better understand the functional roles of AgRP neurons, we performed optetrode electrophysiological recordings from AgRP neurons in awake, behaving AgRP-IRES-Cre mice. In free-feeding mice, we observed a fivefold increase in AgRP neuron firing with mounting caloric deficit in afternoon vs morning recordings. In food-restricted mice, as food became available, AgRP neuron firing dropped, yet remained elevated as compared to firing in sated mice. The rapid drop in spiking activity of AgRP neurons at meal onset may reflect a termination of the drive to find food, while residual, persistent spiking may reflect a sustained drive to consume food. Moreover, nearby neurons inhibited by AgRP neuron photostimulation, likely including satiety-promoting pro-opiomelanocortin (POMC) neurons, demonstrated opposite changes in spiking. Finally, firing of ARC neurons was also rapidly modulated within seconds of individual licks for liquid food. These findings suggest novel roles for antagonistic AgRP and POMC neurons in the regulation of feeding behaviors across multiple timescales. DOI: http://dx.doi.org/10.7554/eLife.07122.001 PMID:26159614

Measuring multiple spike train synchrony.

PubMed

Kreuz, Thomas; Chicharro, Daniel; Andrzejak, Ralph G; Haas, Julie S; Abarbanel, Henry D I

2009-10-15

Measures of multiple spike train synchrony are essential in order to study issues such as spike timing reliability, network synchronization, and neuronal coding. These measures can broadly be divided in multivariate measures and averages over bivariate measures. One of the most recent bivariate approaches, the ISI-distance, employs the ratio of instantaneous interspike intervals (ISIs). In this study we propose two extensions of the ISI-distance, the straightforward averaged bivariate ISI-distance and the multivariate ISI-diversity based on the coefficient of variation. Like the original measure these extensions combine many properties desirable in applications to real data. In particular, they are parameter-free, time scale independent, and easy to visualize in a time-resolved manner, as we illustrate with in vitro recordings from a cortical neuron. Using a simulated network of Hindemarsh-Rose neurons as a controlled configuration we compare the performance of our methods in distinguishing different levels of multi-neuron spike train synchrony to the performance of six other previously published measures. We show and explain why the averaged bivariate measures perform better than the multivariate ones and why the multivariate ISI-diversity is the best performer among the multivariate methods. Finally, in a comparison against standard methods that rely on moving window estimates, we use single-unit monkey data to demonstrate the advantages of the instantaneous nature of our methods.

Emergent Properties of Interacting Populations of Spiking Neurons

PubMed Central

Cardanobile, Stefano; Rotter, Stefan

2011-01-01

Dynamic neuronal networks are a key paradigm of increasing importance in brain research, concerned with the functional analysis of biological neuronal networks and, at the same time, with the synthesis of artificial brain-like systems. In this context, neuronal network models serve as mathematical tools to understand the function of brains, but they might as well develop into future tools for enhancing certain functions of our nervous system. Here, we present and discuss our recent achievements in developing multiplicative point processes into a viable mathematical framework for spiking network modeling. The perspective is that the dynamic behavior of these neuronal networks is faithfully reflected by a set of non-linear rate equations, describing all interactions on the population level. These equations are similar in structure to Lotka-Volterra equations, well known by their use in modeling predator-prey relations in population biology, but abundant applications to economic theory have also been described. We present a number of biologically relevant examples for spiking network function, which can be studied with the help of the aforementioned correspondence between spike trains and specific systems of non-linear coupled ordinary differential equations. We claim that, enabled by the use of multiplicative point processes, we can make essential contributions to a more thorough understanding of the dynamical properties of interacting neuronal populations. PMID:22207844

Auditory Habituation in the Fetus and Neonate: An fMEG Study

ERIC Educational Resources Information Center

Muenssinger, Jana; Matuz, Tamara; Schleger, Franziska; Kiefer-Schmidt, Isabelle; Goelz, Rangmar; Wacker-Gussmann, Annette; Birbaumer, Niels; Preissl, Hubert

2013-01-01

Habituation--the most basic form of learning--is used to evaluate central nervous system (CNS) maturation and to detect abnormalities in fetal brain development. In the current study, habituation, stimulus specificity and dishabituation of auditory evoked responses were measured in fetuses and newborns using fetal magnetoencephalography (fMEG). An…

Armed Deterrence: Countering Soft Target Attacks

DTIC Science & Technology

2016-02-06

Perspectives on Terrorism 9, no. 4 (August 2015): 14-30. 6 Ibid., 19. 7 Ibid., 16. 8 Ibid. 9 Ibid., 14. 10 Ibid., 27. 11 Meg Wagner and Rich...Wagner, Meg and Rich Schapiro. “Mastermind of Paris terror attack planned strikes on schools, mocked Europe’s open borders: report,” New York Daily

The Influence of Semantic Processing on Phonological Decisions in Children and Adults: A Magnetoencephalography (MEG) Study

ERIC Educational Resources Information Center

Wehner, Daniel T.; Ahlfors, Seppo P.; Mody, Maria

2007-01-01

Purpose: To examine the behavioral effects and neural activation patterns associated with implicit semantic processing influences on phonological judgments during reading in children and adults. Method: Whole-head magnetoencephalography (MEG) recordings were obtained from 2 groups, children (9-13 years) and adults, performing a homophone judgment…

An Extended Motor Network Generates Beta and Gamma Oscillatory Perturbations during Development

ERIC Educational Resources Information Center

Wilson, Tony W.; Slason, Erin; Asherin, Ryan; Kronberg, Eugene; Reite, Martin L.; Teale, Peter D.; Rojas, Donald C.

2010-01-01

This study examines the time course and neural generators of oscillatory beta and gamma motor responses in typically-developing children. Participants completed a unilateral flexion-extension task using each index finger as whole-head magnetoencephalography (MEG) data were acquired. These MEG data were imaged in the frequency-domain using spatial…

Removal of monoethylene glycol from wastewater by using Zr-metal organic frameworks.

PubMed

Zaboon, Sami; Abid, Hussein Rasool; Yao, Zhengxin; Gubner, Rolf; Wang, Shaobin; Barifcani, Ahmed

2018-08-01

Mono-ethylene glycol (MEG), used in the oil and gas industries as a gas hydrate inhibitor, is a hazardous chemical present in wastewater from those processes. Metal-organic frameworks (MOFs) (modified UiO-66 ∗ and UiO-66-2OH) were used for the effective removal of MEG waste from effluents of distillation columns (MEG recovery units). Batch contact adsorption method was used to study the adsorption behavior toward these types of MOFs. Adsorption experiments showed that these MOFs had very high affinity toward MEG. Significant adsorption capacity was demonstrated on UiO-66-2OH and modified UiO-66 at 1000 mg·g -1 and 800 mg·g -1 respectively. The adsorption kinetics were fitted to a pseudo first-order model. UiO-66-2OH showed a higher adsorption capacity due to the presence of hydroxyl groups in its structure. A Langmuir model gave the best fitting for isotherm of experimental data at pH = 7. Copyright © 2018 Elsevier Inc. All rights reserved.

Real Time Data Acquisition and Online Signal Processing for Magnetoencephalography

NASA Astrophysics Data System (ADS)

Rongen, H.; Hadamschek, V.; Schiek, M.

2006-06-01

To establish improved therapies for patients suffering from severe neurological and psychiatric diseases, a demand controlled and desynchronizing brain-pacemaker has been developed with techniques from statistical physics and nonlinear dynamics. To optimize the novel therapeutic approach, brain activity is investigated with a Magnetoencephalography (MEG) system prior to surgery. For this, a real time data acquisition system for a 148 channel MEG and online signal processing for artifact rejection, filtering, cross trial phase resetting analysis and three-dimensional (3-D) reconstruction of the cerebral current sources was developed. The developed PCI bus hardware is based on a FPGA and DSP design, using the benefits from both architectures. The reconstruction and visualization of the 3-D volume data is done by the PC which hosts the real time DAQ and pre-processing board. The framework of the MEG-online system is introduced and the architecture of the real time DAQ board and online reconstruction is described. In addition we show first results with the MEG-Online system for the investigation of dynamic brain activities in relation to external visual stimulation, based on test data sets.

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

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.

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.

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.

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.

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.

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.

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

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.

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.

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.

Understanding neurodynamical systems via Fuzzy Symbolic Dynamics.

PubMed

Dobosz, Krzysztof; Duch, Włodzisław

2010-05-01

Neurodynamical systems are characterized by a large number of signal streams, measuring activity of individual neurons, local field potentials, aggregated electrical (EEG) or magnetic potentials (MEG), oxygen use (fMRI) or activity of simulated neurons. Various basis set decomposition techniques are used to analyze such signals, trying to discover components that carry meaningful information, but these techniques tell us little about the global activity of the whole system. A novel technique called Fuzzy Symbolic Dynamics (FSD) is introduced to help in understanding of the multidimensional dynamical system's behavior. It is based on a fuzzy partitioning of the signal space that defines a non-linear mapping of the system's trajectory to the low-dimensional space of membership function activations. This allows for visualization of the trajectory showing various aspects of observed signals that may be difficult to discover looking at individual components, or to notice otherwise. FSD mapping can be applied to raw signals, transformed signals (for example, ICA components), or to signals defined in the time-frequency domain. To illustrate the method two FSD visualizations are presented: a model system with artificial radial oscillatory sources, and the output layer (50 neurons) of Respiratory Rhythm Generator (RRG) composed of 300 spiking neurons. 2009 Elsevier Ltd. All rights reserved.

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

Statistical evaluation of synchronous spike patterns extracted by frequent item set mining

PubMed Central

Torre, Emiliano; Picado-Muiño, David; Denker, Michael; Borgelt, Christian; Grün, Sonja

2013-01-01

We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of any superset (closed frequent item sets). The number of patterns found by FIM makes direct statistical tests infeasible due to severe multiple testing. To overcome this issue, we proposed to test the significance not of individual patterns, but instead of their signatures, defined as the pairs of pattern size z and support c. Here, we derive in detail a statistical test for the significance of the signatures under the null hypothesis of full independence (pattern spectrum filtering, PSF) by means of surrogate data. As a result, injected spike patterns that mimic assembly activity are well detected, yielding a low false negative rate. However, this approach is prone to additionally classify patterns resulting from chance overlap of real assembly activity and background spiking as significant. These patterns represent false positives with respect to the null hypothesis of having one assembly of given signature embedded in otherwise independent spiking activity. We propose the additional method of pattern set reduction (PSR) to remove these false positives by conditional filtering. By employing stochastic simulations of parallel spike trains with correlated activity in form of injected spike synchrony in subsets of the neurons, we demonstrate for a range of parameter settings that the analysis scheme composed of FIM, PSF and PSR allows to reliably detect active assemblies in massively parallel spike trains. PMID:24167487

Mental arithmetic leads to multiple discrete changes from baseline in the firing patterns of human thalamic neurons.

PubMed

Kim, J H; Ohara, S; Lenz, F A

2009-04-01

Primate thalamic action potential bursts associated with low-threshold spikes (LTS) occur during waking sensory and motor activity. We now test the hypothesis that different firing and LTS burst characteristics occur during quiet wakefulness (spontaneous condition) versus mental arithmetic (counting condition). This hypothesis was tested by thalamic recordings during the surgical treatment of tremor. Across all neurons and epochs, preburst interspike intervals (ISIs) were bimodal at median values, consistent with the duration of type A and type B gamma-aminobutyric acid inhibitory postsynaptic potentials. Neuronal spike trains (117 neurons) were categorized by joint ISI distributions into those firing as LTS bursts (G, grouped), firing as single spikes (NG, nongrouped), or firing as single spikes with sporadic LTS bursting (I, intermediate). During the spontaneous condition (46 neurons) only I spike trains changed category. Overall, burst rates (BRs) were lower and firing rates (FRs) were higher during the counting versus the spontaneous condition. Spike trains in the G category sometimes changed to I and NG categories at the transition from the spontaneous to the counting condition, whereas those in the I category often changed to NG. Among spike trains that did not change category by condition, G spike trains had lower BRs during counting, whereas NG spike trains had higher FRs. BRs were significantly greater than zero for G and I categories during wakefulness (both conditions). The changes between the spontaneous and counting conditions are most pronounced for the I category, which may be a transitional firing pattern between the bursting (G) and relay modes of thalamic firing (NG).

Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model

PubMed Central

Teka, Wondimu; Marinov, Toma M.; Santamaria, Fidel

2014-01-01

The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation. PMID:24675903

Role of Plasticity at Different Sites across the Time Course of Cerebellar Motor Learning

PubMed Central

Lisberger, Stephen G.

2014-01-01

Learning comprises multiple components that probably involve cellular and synaptic plasticity at multiple sites. Different neural sites may play their largest roles at different times during behavioral learning. We have used motor learning in smooth pursuit eye movements of monkeys to determine how and when different components of learning occur in a known cerebellar circuit. The earliest learning occurs when one climbing-fiber response to a learning instruction causes simple-spike firing rate of Purkinje cells in the floccular complex of the cerebellum to be depressed transiently at the time of the instruction on the next trial. Trial-over-trial depression and the associated learning in eye movement are forgotten in <6 s, but facilitate long-term behavioral learning over a time scale of ∼5 min. During 100 repetitions of a learning instruction, simple-spike firing rate becomes progressively depressed in Purkinje cells that receive climbing-fiber inputs from the instruction. In Purkinje cells that prefer the opposite direction of pursuit and therefore do not receive climbing-fiber inputs related to the instruction, simple-spike responses undergo potentiation, but more weakly and more slowly. Analysis of the relationship between the learned changes in simple-spike firing and learning in eye velocity suggests an orderly progression of plasticity: first on Purkinje cells with complex-spike (CS) responses to the instruction, later on Purkinje cells with CS responses to the opposite direction of instruction, and last in sites outside the cerebellar cortex. Climbing-fiber inputs appear to play a fast and primary, but nonexclusive, role in pursuit learning. PMID:24849344

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.

A biologically plausible computational model for auditory object recognition.

PubMed

Larson, Eric; Billimoria, Cyrus P; Sen, Kamal

2009-01-01

Object recognition is a task of fundamental importance for sensory systems. Although this problem has been intensively investigated in the visual system, relatively little is known about the recognition of complex auditory objects. Recent work has shown that spike trains from individual sensory neurons can be used to discriminate between and recognize stimuli. Multiple groups have developed spike similarity or dissimilarity metrics to quantify the differences between spike trains. Using a nearest-neighbor approach the spike similarity metrics can be used to classify the stimuli into groups used to evoke the spike trains. The nearest prototype spike train to the tested spike train can then be used to identify the stimulus. However, how biological circuits might perform such computations remains unclear. Elucidating this question would facilitate the experimental search for such circuits in biological systems, as well as the design of artificial circuits that can perform such computations. Here we present a biologically plausible model for discrimination inspired by a spike distance metric using a network of integrate-and-fire model neurons coupled to a decision network. We then apply this model to the birdsong system in the context of song discrimination and recognition. We show that the model circuit is effective at recognizing individual songs, based on experimental input data from field L, the avian primary auditory cortex analog. We also compare the performance and robustness of this model to two alternative models of song discrimination: a model based on coincidence detection and a model based on firing rate.

The Statistics and Mathematics of High Dimension Low Sample Size Asymptotics.

PubMed

Shen, Dan; Shen, Haipeng; Zhu, Hongtu; Marron, J S

2016-10-01

The aim of this paper is to establish several deep theoretical properties of principal component analysis for multiple-component spike covariance models. Our new results reveal an asymptotic conical structure in critical sample eigendirections under the spike models with distinguishable (or indistinguishable) eigenvalues, when the sample size and/or the number of variables (or dimension) tend to infinity. The consistency of the sample eigenvectors relative to their population counterparts is determined by the ratio between the dimension and the product of the sample size with the spike size. When this ratio converges to a nonzero constant, the sample eigenvector converges to a cone, with a certain angle to its corresponding population eigenvector. In the High Dimension, Low Sample Size case, the angle between the sample eigenvector and its population counterpart converges to a limiting distribution. Several generalizations of the multi-spike covariance models are also explored, and additional theoretical results are presented.

A Novel and Simple Spike Sorting Implementation.

PubMed

Petrantonakis, Panagiotis C; Poirazi, Panayiota

2017-04-01

Monitoring the activity of multiple, individual neurons that fire spikes in the vicinity of an electrode, namely perform a Spike Sorting (SS) procedure, comprises one of the most important tools for contemporary neuroscience in order to reverse-engineer the brain. As recording electrodes' technology rabidly evolves by integrating thousands of electrodes in a confined spatial setting, the algorithms that are used to monitor individual neurons from recorded signals have to become even more reliable and computationally efficient. In this work, we propose a novel framework of the SS approach in which a single-step processing of the raw (unfiltered) extracellular signal is sufficient for both the detection and sorting of the activity of individual neurons. Despite its simplicity, the proposed approach exhibits comparable performance with state-of-the-art approaches, especially for spike detection in noisy signals, and paves the way for a new family of SS algorithms with the potential for multi-recording, fast, on-chip implementations.

Determinants of Multiple Semantic Priming: A Meta-Analysis and Spike Frequency Adaptive Model of a Cortical Network

ERIC Educational Resources Information Center

Lavigne, Frederic; Dumercy, Laurent; Darmon, Nelly

2011-01-01

Recall and language comprehension while processing sequences of words involves multiple semantic priming between several related and/or unrelated words. Accounting for multiple and interacting priming effects in terms of underlying neuronal structure and dynamics is a challenge for current models of semantic priming. Further elaboration of current…

Synaptic input correlations leading to membrane potential decorrelation of spontaneous activity in cortex.

PubMed

Graupner, Michael; Reyes, Alex D

2013-09-18

Correlations in the spiking activity of neurons have been found in many regions of the cortex under multiple experimental conditions and are postulated to have important consequences for neural population coding. While there is a large body of extracellular data reporting correlations of various strengths, the subthreshold events underlying the origin and magnitude of signal-independent correlations (called noise or spike count correlations) are unknown. Here we investigate, using intracellular recordings, how synaptic input correlations from shared presynaptic neurons translate into membrane potential and spike-output correlations. Using a pharmacologically activated thalamocortical slice preparation, we perform simultaneous recordings from pairs of layer IV neurons in the auditory cortex of mice and measure synaptic potentials/currents, membrane potentials, and spiking outputs. We calculate cross-correlations between excitatory and inhibitory inputs to investigate correlations emerging from the network. We furthermore evaluate membrane potential correlations near resting potential to study how excitation and inhibition combine and affect spike-output correlations. We demonstrate directly that excitation is correlated with inhibition thereby partially canceling each other and resulting in weak membrane potential and spiking correlations between neurons. Our data suggest that cortical networks are set up to partially cancel correlations emerging from the connections between neurons. This active decorrelation is achieved because excitation and inhibition closely track each other. Our results suggest that the numerous shared presynaptic inputs do not automatically lead to increased spiking correlations.

Leaders and followers: quantifying consistency in spatio-temporal propagation patterns

NASA Astrophysics Data System (ADS)

Kreuz, Thomas; Satuvuori, Eero; Pofahl, Martin; Mulansky, Mario

2017-04-01

Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a synfire pattern. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed SPIKE-order and spike train order, that define the synfire indicator value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality.

Within- and between-session replicability of cognitive brain processes: An MEG study with an N-back task.

PubMed

Ahonen, L; Huotilainen, M; Brattico, E

2016-05-01

In the vast majority of electrophysiological studies on cognition, participants are only measured once during a single experimental session. The dearth of studies on test-retest reliability in magnetoencephalography (MEG) within and across experimental sessions is a preventing factor for longitudinal designs, imaging genetics studies, and clinical applications. From the recorded signals, it is not straightforward to draw robust and steady indices of brain activity that could directly be used in exploring behavioral effects or genetic associations. To study the variations in markers associated with cognitive functions, we extracted three event-related field (ERF) features from time-locked global field power (GFP) epochs using MEG while participants were performing a numerical N-back task in four consecutive measurements conducted during two different days separated by two weeks. We demonstrate that the latency of the M170, a neural correlate associated with cognitive functions such as working memory, was a stable parameter and did not show significant variations over time. In addition, the M170 peak amplitude and the mean amplitude of late positive component (LPP) also expressed moderate-to-strong reliability across multiple measures over time over many sensor spaces and between participants. The M170 amplitude varied more significantly between the measurements in some conditions but showed consistency over the participants over time. In addition we demonstrated significant correlation with the M170 and LPP parameters and cognitive load. The results are in line with the literature showing less within-subject fluctuation for the latency parameters and more consistency in between-subject comparisons for amplitude based features. The within-subject consistency was apparent also with longer delays between the measurements. We suggest that with a few limitations the ERF features show sufficient reliability and stability for longitudinal research designs and clinical applications for cognitive functions in single as well as cross-subject designs. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

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.

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.

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

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

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

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.

Development of multichannel MEG system at IGCAR

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

Armored long non-coding RNA MEG3 targeting EGFR based on recombinant MS2 bacteriophage virus-like particles against hepatocellular carcinoma.

PubMed

Chang, Le; Wang, Guojing; Jia, Tingting; Zhang, Lei; Li, Yulong; Han, Yanxi; Zhang, Kuo; Lin, Guigao; Zhang, Rui; Li, Jinming; Wang, Lunan

2016-04-26

Hepatocellular carcinoma (HCC) is one of the most frequently diagnosed cancers worldwide. However, the treatment of patients with HCC is particularly challenging. Long non-coding RNA maternally expressed gene 3 (MEG3) has been identified as a potential suppressor of several types of tumors, but the delivery of long RNA remains problematic, limiting its applications. In the present study, we designed a novel delivery system based on MS2 virus-like particles (VLPs) crosslinked with GE11 polypeptide. This vector was found to be fast, effective and safe for the targeted delivery of lncRNA MEG3 RNA to the epidermal growth factor receptor (EGFR)-positive HCC cell lines without the activation of EGFR downstream pathways, and significantly attenuated both in vitro and in vivo tumor cell growth. Our study also revealed that the targeted delivery was mainly dependent on clathrin-mediated endocytosis and MEG3 RNA suppresses tumor growth mainly via increasing the expression of p53 and its downstream gene GDF15, but decreasing the expression of MDM2. Thus, this vector is promising as a novel delivery system and may facilitate a new approach to lncRNA based cancer therapy.

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

PubMed

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

2008-02-01

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

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

PubMed

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

2011-01-01

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

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

PubMed Central

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

2011-01-01

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

Spectral changes in spontaneous MEG activity across the lifespan

NASA Astrophysics Data System (ADS)

Gómez, Carlos; Pérez-Macías, Jose M.; Poza, Jesús; Fernández, Alberto; Hornero, Roberto

2013-12-01

Objective. The aim of this study is to explore the spectral patterns of spontaneous magnetoencephalography (MEG) activity across the lifespan. Approach. Relative power (RP) in six frequency bands (delta, theta, alpha, beta-1, beta-2 and gamma) was calculated in a sample of 220 healthy subjects with ages ranging from 7 to 84 years. Main results. A significant RP decrease in low-frequency bands (i.e. delta and theta) and a significant increase in high bands (mainly beta-1 and beta-2) were found from childhood to adolescence. This trend was observed until the sixth decade of life, though only slight changes were found. Additionally, healthy aging was characterized by a power increase in low-frequency bands. Our results show that spectral changes across the lifespan may follow a quadratic relationship in delta, theta, alpha, beta-2 and gamma bands with peak ages being reached around the fifth or sixth decade of life. Significance. Our findings provide original insights into the definition of the ‘normal’ behavior of age-related MEG spectral patterns. Furthermore, our study can be useful for the forthcoming MEG research focused on the description of the abnormalities of different brain diseases in comparison to cognitive decline in normal aging.

Spatiotemporal signal space separation method for rejecting nearby interference in MEG measurements

NASA Astrophysics Data System (ADS)

Taulu, S.; Simola, J.

2006-04-01

Limitations of traditional magnetoencephalography (MEG) exclude some important patient groups from MEG examinations, such as epilepsy patients with a vagus nerve stimulator, patients with magnetic particles on the head or having magnetic dental materials that cause severe movement-related artefact signals. Conventional interference rejection methods are not able to remove the artefacts originating this close to the MEG sensor array. For example, the reference array method is unable to suppress interference generated by sources closer to the sensors than the reference array, about 20-40 cm. The spatiotemporal signal space separation method proposed in this paper recognizes and removes both external interference and the artefacts produced by these nearby sources, even on the scalp. First, the basic separation into brain-related and external interference signals is accomplished with signal space separation based on sensor geometry and Maxwell's equations only. After this, the artefacts from nearby sources are extracted by a simple statistical analysis in the time domain, and projected out. Practical examples with artificial current dipoles and interference sources as well as data from real patients demonstrate that the method removes the artefacts without altering the field patterns of the brain signals.

Anatomically constrained dipole adjustment (ANACONDA) for accurate MEG/EEG focal source localizations

NASA Astrophysics Data System (ADS)

Im, Chang-Hwan; Jung, Hyun-Kyo; Fujimaki, Norio

2005-10-01

This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG.

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.

Physical fatigue increases neural activation during eyes-closed state: a magnetoencephalography study.

PubMed

Tanaka, Masaaki; Ishii, Akira; Watanabe, Yasuyoshi

2015-11-05

Fatigue, defined as difficulty initiating or sustaining voluntary activities, can be classified as physical or mental. In this study, we use magnetoencephalography (MEG) to quantify the effect of physical fatigue on neural activity under the condition of simulated physical load. Thirteen healthy right-handed male volunteers participated in this study. The experiment consisted of one fatigue-inducing physical task session performed between two MEG sessions. During the 10-min physical task session, participants performed maximum-effort handgrips with the left hand lasting 1 s every 4 s; during MEG sessions, 3-min recordings were made during the eyes-closed state. MEG data were analyzed using narrow-band adaptive spatial filtering methods. Alpha-frequency band (8-13 Hz) power in the left postcentral gyrus, precentral gyrus, and middle frontal gyrus (Brodmann's areas 1, 2, 3, 4, 6, and 46) were decreased after performing the physical fatigue-inducing task. These results show that performing the physical fatigue-inducing task caused activation of the left sensorimotor and prefrontal areas, manifested as decreased alpha-frequency band power in these brain areas. Our results increase understanding of the neural mechanisms of physical fatigue.

Different propagation speeds of recalled sequences in plastic spiking neural networks

NASA Astrophysics Data System (ADS)

Huang, Xuhui; Zheng, Zhigang; Hu, Gang; Wu, Si; Rasch, Malte J.

2015-03-01

Neural networks can generate spatiotemporal patterns of spike activity. Sequential activity learning and retrieval have been observed in many brain areas, and e.g. is crucial for coding of episodic memory in the hippocampus or generating temporal patterns during song production in birds. In a recent study, a sequential activity pattern was directly entrained onto the neural activity of the primary visual cortex (V1) of rats and subsequently successfully recalled by a local and transient trigger. It was observed that the speed of activity propagation in coordinates of the retinotopically organized neural tissue was constant during retrieval regardless how the speed of light stimulation sweeping across the visual field during training was varied. It is well known that spike-timing dependent plasticity (STDP) is a potential mechanism for embedding temporal sequences into neural network activity. How training and retrieval speeds relate to each other and how network and learning parameters influence retrieval speeds, however, is not well described. We here theoretically analyze sequential activity learning and retrieval in a recurrent neural network with realistic synaptic short-term dynamics and STDP. Testing multiple STDP rules, we confirm that sequence learning can be achieved by STDP. However, we found that a multiplicative nearest-neighbor (NN) weight update rule generated weight distributions and recall activities that best matched the experiments in V1. Using network simulations and mean-field analysis, we further investigated the learning mechanisms and the influence of network parameters on recall speeds. Our analysis suggests that a multiplicative STDP rule with dominant NN spike interaction might be implemented in V1 since recall speed was almost constant in an NMDA-dominant regime. Interestingly, in an AMPA-dominant regime, neural circuits might exhibit recall speeds that instead follow the change in stimulus speeds. This prediction could be tested in experiments.

Real-time computing platform for spiking neurons (RT-spike).

PubMed

Ros, Eduardo; Ortigosa, Eva M; Agís, Rodrigo; Carrillo, Richard; Arnold, Michael

2006-07-01

A computing platform is described for simulating arbitrary networks of spiking neurons in real time. A hybrid computing scheme is adopted that uses both software and hardware components to manage the tradeoff between flexibility and computational power; the neuron model is implemented in hardware and the network model and the learning are implemented in software. The incremental transition of the software components into hardware is supported. We focus on a spike response model (SRM) for a neuron where the synapses are modeled as input-driven conductances. The temporal dynamics of the synaptic integration process are modeled with a synaptic time constant that results in a gradual injection of charge. This type of model is computationally expensive and is not easily amenable to existing software-based event-driven approaches. As an alternative we have designed an efficient time-based computing architecture in hardware, where the different stages of the neuron model are processed in parallel. Further improvements occur by computing multiple neurons in parallel using multiple processing units. This design is tested using reconfigurable hardware and its scalability and performance evaluated. Our overall goal is to investigate biologically realistic models for the real-time control of robots operating within closed action-perception loops, and so we evaluate the performance of the system on simulating a model of the cerebellum where the emulation of the temporal dynamics of the synaptic integration process is important.

Mouse Visual Neocortex Supports Multiple Stereotyped Patterns of Microcircuit Activity

PubMed Central

Sadovsky, Alexander J.

2014-01-01

Spiking correlations between neocortical neurons provide insight into the underlying synaptic connectivity that defines cortical microcircuitry. Here, using two-photon calcium fluorescence imaging, we observed the simultaneous dynamics of hundreds of neurons in slices of mouse primary visual cortex (V1). Consistent with a balance of excitation and inhibition, V1 dynamics were characterized by a linear scaling between firing rate and circuit size. Using lagged firing correlations between neurons, we generated functional wiring diagrams to evaluate the topological features of V1 microcircuitry. We found that circuit connectivity exhibited both cyclic graph motifs, indicating recurrent wiring, and acyclic graph motifs, indicating feedforward wiring. After overlaying the functional wiring diagrams onto the imaged field of view, we found properties consistent with Rentian scaling: wiring diagrams were topologically efficient because they minimized wiring with a modular architecture. Within single imaged fields of view, V1 contained multiple discrete circuits that were overlapping and highly interdigitated but were still distinct from one another. The majority of neurons that were shared between circuits displayed peri-event spiking activity whose timing was specific to the active circuit, whereas spike times for a smaller percentage of neurons were invariant to circuit identity. These data provide evidence that V1 microcircuitry exhibits balanced dynamics, is efficiently arranged in anatomical space, and is capable of supporting a diversity of multineuron spike firing patterns from overlapping sets of neurons. PMID:24899701

Phase Locking of Multiple Single Neurons to the Local Field Potential in Cat V1.

PubMed

Martin, Kevan A C; Schröder, Sylvia

2016-02-24

The local field potential (LFP) is thought to reflect a temporal reference for neuronal spiking, which may facilitate information coding and orchestrate the communication between neural populations. To explore this proposed role, we recorded the LFP and simultaneously the spike activity of one to three nearby neurons in V1 of anesthetized cats during the presentation of drifting sinusoidal gratings, binary dense noise stimuli, and natural movies. In all stimulus conditions and during spontaneous activity, the average LFP power at frequencies >20 Hz was higher when neurons were spiking versus not spiking. The spikes were weakly but significantly phase locked to all frequencies of the LFP. The average spike phase of the LFP was stable across high and low levels of LFP power, but the strength of phase locking at low frequencies (≤10 Hz) increased with increasing LFP power. In a next step, we studied how strong stimulus responses of single neurons are reflected in the LFP and the LFP-spike relationship. We found that LFP power was slightly increased and phase locking was slightly stronger during strong compared with weak stimulus-locked responses. In summary, the coupling strength between high frequencies of the LFP and spikes was not strongly modulated by LFP power, which is thought to reflect spiking synchrony, nor was it strongly influenced by how strongly the neuron was driven by the stimulus. Furthermore, a comparison between neighboring neurons showed no clustering of preferred LFP phase. We argue that hypotheses on the relevance of phase locking in their current form are inconsistent with our findings. Copyright © 2016 the authors 0270-6474/16/362494-09$15.00/0.

Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents

PubMed Central

Chagas, André M.; Theis, Lucas; Sengupta, Biswa; Stüttgen, Maik C.; Bethge, Matthias; Schwarz, Cornelius

2013-01-01

Sensory receptors determine the type and the quantity of information available for perception. Here, we quantified and characterized the information transferred by primary afferents in the rat whisker system using neural system identification. Quantification of “how much” information is conveyed by primary afferents, using the direct method (DM), a classical information theoretic tool, revealed that primary afferents transfer huge amounts of information (up to 529 bits/s). Information theoretic analysis of instantaneous spike-triggered kinematic stimulus features was used to gain functional insight on “what” is coded by primary afferents. Amongst the kinematic variables tested—position, velocity, and acceleration—primary afferent spikes encoded velocity best. The other two variables contributed to information transfer, but only if combined with velocity. We further revealed three additional characteristics that play a role in information transfer by primary afferents. Firstly, primary afferent spikes show preference for well separated multiple stimuli (i.e., well separated sets of combinations of the three instantaneous kinematic variables). Secondly, neurons are sensitive to short strips of the stimulus trajectory (up to 10 ms pre-spike time), and thirdly, they show spike patterns (precise doublet and triplet spiking). In order to deal with these complexities, we used a flexible probabilistic neuron model fitting mixtures of Gaussians to the spike triggered stimulus distributions, which quantitatively captured the contribution of the mentioned features and allowed us to achieve a full functional analysis of the total information rate indicated by the DM. We found that instantaneous position, velocity, and acceleration explained about 50% of the total information rate. Adding a 10 ms pre-spike interval of stimulus trajectory achieved 80–90%. The final 10–20% were found to be due to non-linear coding by spike bursts. PMID:24367295

MANTA--an open-source, high density electrophysiology recording suite for MATLAB.

PubMed

Englitz, B; David, S V; Sorenson, M D; Shamma, S A

2013-01-01

The distributed nature of nervous systems makes it necessary to record from a large number of sites in order to decipher the neural code, whether single cell, local field potential (LFP), micro-electrocorticograms (μECoG), electroencephalographic (EEG), magnetoencephalographic (MEG) or in vitro micro-electrode array (MEA) data are considered. High channel-count recordings also optimize the yield of a preparation and the efficiency of time invested by the researcher. Currently, data acquisition (DAQ) systems with high channel counts (>100) can be purchased from a limited number of companies at considerable prices. These systems are typically closed-source and thus prohibit custom extensions or improvements by end users. We have developed MANTA, an open-source MATLAB-based DAQ system, as an alternative to existing options. MANTA combines high channel counts (up to 1440 channels/PC), usage of analog or digital headstages, low per channel cost (<$90/channel), feature-rich display and filtering, a user-friendly interface, and a modular design permitting easy addition of new features. MANTA is licensed under the GPL and free of charge. The system has been tested by daily use in multiple setups for >1 year, recording reliably from 128 channels. It offers a growing list of features, including integrated spike sorting, PSTH and CSD display and fully customizable electrode array geometry (including 3D arrays), some of which are not available in commercial systems. MANTA runs on a typical PC and communicates via TCP/IP and can thus be easily integrated with existing stimulus generation/control systems in a lab at a fraction of the cost of commercial systems. With modern neuroscience developing rapidly, MANTA provides a flexible platform that can be rapidly adapted to the needs of new analyses and questions. Being open-source, the development of MANTA can outpace commercial solutions in functionality, while maintaining a low price-point.

MANTA—an open-source, high density electrophysiology recording suite for MATLAB

PubMed Central

Englitz, B.; David, S. V.; Sorenson, M. D.; Shamma, S. A.

2013-01-01

The distributed nature of nervous systems makes it necessary to record from a large number of sites in order to decipher the neural code, whether single cell, local field potential (LFP), micro-electrocorticograms (μECoG), electroencephalographic (EEG), magnetoencephalographic (MEG) or in vitro micro-electrode array (MEA) data are considered. High channel-count recordings also optimize the yield of a preparation and the efficiency of time invested by the researcher. Currently, data acquisition (DAQ) systems with high channel counts (>100) can be purchased from a limited number of companies at considerable prices. These systems are typically closed-source and thus prohibit custom extensions or improvements by end users. We have developed MANTA, an open-source MATLAB-based DAQ system, as an alternative to existing options. MANTA combines high channel counts (up to 1440 channels/PC), usage of analog or digital headstages, low per channel cost (<$90/channel), feature-rich display and filtering, a user-friendly interface, and a modular design permitting easy addition of new features. MANTA is licensed under the GPL and free of charge. The system has been tested by daily use in multiple setups for >1 year, recording reliably from 128 channels. It offers a growing list of features, including integrated spike sorting, PSTH and CSD display and fully customizable electrode array geometry (including 3D arrays), some of which are not available in commercial systems. MANTA runs on a typical PC and communicates via TCP/IP and can thus be easily integrated with existing stimulus generation/control systems in a lab at a fraction of the cost of commercial systems. With modern neuroscience developing rapidly, MANTA provides a flexible platform that can be rapidly adapted to the needs of new analyses and questions. Being open-source, the development of MANTA can outpace commercial solutions in functionality, while maintaining a low price-point. PMID:23653593

pH-induced conformational change of the rotavirus VP4 spike: implications for cell entry and antibody neutralization.

PubMed

Pesavento, Joseph B; Crawford, Sue E; Roberts, Ed; Estes, Mary K; Prasad, B V Venkataram

2005-07-01

The rotavirus spike protein, VP4, is a major determinant of infectivity and neutralization. Previously, we have shown that trypsin-enhanced infectivity of rotavirus involves a transformation of the VP4 spike from a flexible to a rigid bilobed structure. Here we show that at elevated pH the spike undergoes a drastic, irreversible conformational change and becomes stunted, with a pronounced trilobed appearance. These particles with altered spikes, at a normal pH of 7.5, despite the loss of infectivity and the ability to hemagglutinate, surprisingly exhibit sialic acid (SA)-independent cell binding in contrast to the SA-dependent cell binding exhibited by native virions. Remarkably, a neutralizing monoclonal antibody that remains bound to spikes throughout the pH changes (pH 7 to 11 and back to pH 7) completely prevents this conformational change, preserving the SA-dependent cell binding and hemagglutinating functions of the virion. A hypothesis that emerges from the present study is that high-pH treatment triggers a conformational change that mimics a post-SA-attachment step to expose an epitope recognized by a downstream receptor in the rotavirus cell entry process. This process involves sequential interactions with multiple receptors, and the mechanism by which the antibody neutralizes is by preventing this conformational change.

Standardized Methods to Generate Mock (Spiked) Clinical Specimens by Spiking Blood or Plasma with Cultured Pathogens

PubMed Central

Dong, Ming; Fisher, Carolyn; Añez, Germán; Rios, Maria; Nakhasi, Hira L.; Hobson, J. Peyton; Beanan, Maureen; Hockman, Donna; Grigorenko, Elena; Duncan, Robert

2016-01-01

Aims To demonstrate standardized methods for spiking pathogens into human matrices for evaluation and comparison among diagnostic platforms. Methods and Results This study presents detailed methods for spiking bacteria or protozoan parasites into whole blood and virus into plasma. Proper methods must start with a documented, reproducible pathogen source followed by steps that include standardized culture, preparation of cryopreserved aliquots, quantification of the aliquots by molecular methods, production of sufficient numbers of individual specimens and testing of the platform with multiple mock specimens. Results are presented following the described procedures that showed acceptable reproducibility comparing in-house real-time PCR assays to a commercially available multiplex molecular assay. Conclusions A step by step procedure has been described that can be followed by assay developers who are targeting low prevalence pathogens. Significance and Impact of Study The development of diagnostic platforms for detection of low prevalence pathogens such as biothreat or emerging agents is challenged by the lack of clinical specimens for performance evaluation. This deficit can be overcome using mock clinical specimens made by spiking cultured pathogens into human matrices. To facilitate evaluation and comparison among platforms, standardized methods must be followed in the preparation and application of spiked specimens. PMID:26835651

Reduced expression of CD45 Protein-Tyrosine Phosphatase Pr

DTIC Science & Technology

2009-05-08

H S /D T R A on A ugust 19, 2009 w w w .jbc.org D ow nloaded from PTP1B , CD45, TCPTP, LMPTP-A, LMPTP-B, MEG1, MEG2, HePTP, PTP), three belong to...the dual specificity phosphatase VHR or the protein-tyrosine phosphatase PTP1B . Given these FIGURE 5. Mice expressing intermediate CD45 levels survive

Why Understanding 1-3/4 divided by 1/2 Matters to Math Reform: ABE Teachers Learn the Math They Teach.

ERIC Educational Resources Information Center

Brover, Charles; Deagan, Denise; Farina, Solange

This paper explains the investigative attempts of The New York City Math Exchange Group (MEG) on elementary mathematics teachers' content knowledge in Adult Basic Education (ABE). The study is comparative in nature and took place in a workshop at the Adults Learning Maths Conference in Boston. The new members of the MEG professional development…

Progressive Presentations of Place-Based Identities in Meg Rosoff's "How I Live Now"

ERIC Educational Resources Information Center

Lockney, Karen

2013-01-01

This article provides a close reading of Meg Rosoff's award-winning novel "How I Live Now". It argues that an understanding of the text can be extended through an application of ideas found in contemporary spatial discourse concerning place. Reading the novel within this context allows a discussion of ways in which it draws on…

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

PubMed

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

1998-04-01

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

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.

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering

PubMed Central

2012-01-01

Background Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Results Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms. Conclusions This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces. PMID:22871125

Automatic online spike sorting with singular value decomposition and fuzzy C-mean clustering.

PubMed

Oliynyk, Andriy; Bonifazzi, Claudio; Montani, Fernando; Fadiga, Luciano

2012-08-08

Understanding how neurons contribute to perception, motor functions and cognition requires the reliable detection of spiking activity of individual neurons during a number of different experimental conditions. An important problem in computational neuroscience is thus to develop algorithms to automatically detect and sort the spiking activity of individual neurons from extracellular recordings. While many algorithms for spike sorting exist, the problem of accurate and fast online sorting still remains a challenging issue. Here we present a novel software tool, called FSPS (Fuzzy SPike Sorting), which is designed to optimize: (i) fast and accurate detection, (ii) offline sorting and (iii) online classification of neuronal spikes with very limited or null human intervention. The method is based on a combination of Singular Value Decomposition for fast and highly accurate pre-processing of spike shapes, unsupervised Fuzzy C-mean, high-resolution alignment of extracted spike waveforms, optimal selection of the number of features to retain, automatic identification the number of clusters, and quantitative quality assessment of resulting clusters independent on their size. After being trained on a short testing data stream, the method can reliably perform supervised online classification and monitoring of single neuron activity. The generalized procedure has been implemented in our FSPS spike sorting software (available free for non-commercial academic applications at the address: http://www.spikesorting.com) using LabVIEW (National Instruments, USA). We evaluated the performance of our algorithm both on benchmark simulated datasets with different levels of background noise and on real extracellular recordings from premotor cortex of Macaque monkeys. The results of these tests showed an excellent accuracy in discriminating low-amplitude and overlapping spikes under strong background noise. The performance of our method is competitive with respect to other robust spike sorting algorithms. This new software provides neuroscience laboratories with a new tool for fast and robust online classification of single neuron activity. This feature could become crucial in situations when online spike detection from multiple electrodes is paramount, such as in human clinical recordings or in brain-computer interfaces.

Models of utricular bouton afferents: role of afferent-hair cell connectivity in determining spike train regularity.

PubMed

Holmes, William R; Huwe, Janice A; Williams, Barbara; Rowe, Michael H; Peterson, Ellengene H

2017-05-01

Vestibular bouton afferent terminals in turtle utricle can be categorized into four types depending on their location and terminal arbor structure: lateral extrastriolar (LES), striolar, juxtastriolar, and medial extrastriolar (MES). The terminal arbors of these afferents differ in surface area, total length, collecting area, number of boutons, number of bouton contacts per hair cell, and axon diameter (Huwe JA, Logan CJ, Williams B, Rowe MH, Peterson EH. J Neurophysiol 113: 2420-2433, 2015). To understand how differences in terminal morphology and the resulting hair cell inputs might affect afferent response properties, we modeled representative afferents from each region, using reconstructed bouton afferents. Collecting area and hair cell density were used to estimate hair cell-to-afferent convergence. Nonmorphological features were held constant to isolate effects of afferent structure and connectivity. The models suggest that all four bouton afferent types are electrotonically compact and that excitatory postsynaptic potentials are two to four times larger in MES afferents than in other afferents, making MES afferents more responsive to low input levels. The models also predict that MES and LES terminal structures permit higher spontaneous firing rates than those in striola and juxtastriola. We found that differences in spike train regularity are not a consequence of differences in peripheral terminal structure, per se, but that a higher proportion of multiple contacts between afferents and individual hair cells increases afferent firing irregularity. The prediction that afferents having primarily one bouton contact per hair cell will fire more regularly than afferents making multiple bouton contacts per hair cell has implications for spike train regularity in dimorphic and calyx afferents. NEW & NOTEWORTHY Bouton afferents in different regions of turtle utricle have very different morphologies and afferent-hair cell connectivities. Highly detailed computational modeling provides insights into how morphology impacts excitability and also reveals a new explanation for spike train irregularity based on relative numbers of multiple bouton contacts per hair cell. This mechanism is independent of other proposed mechanisms for spike train irregularity based on ionic conductances and can explain irregularity in dimorphic units and calyx endings. Copyright © 2017 the American Physiological Society.

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.

Suppressive responses by visual food cues in postprandial activities of insular cortex as revealed by magnetoencephalography.

PubMed

Yoshikawa, Takahiro; Tanaka, Masaaki; Ishii, Akira; Watanabe, Yasuyoshi

2014-06-03

'Hara-Hachibu' in Japanese means a subjective sense by which we stop eating just before the motivation to eat is completely lost, a similar concept to caloric restriction (CR). Insular cortex is a critical platform which integrates sensory information into decision-making processes in eating behavior. We compared the responses of insular cortex, as assessed by magnetoencephalography (MEG), immediately after presentation of food images in the Fasting condition with those in the 'Hara-Hachibu' condition. Eleven healthy, right-handed males [age, 27.2±9.6 years; body mass index, 22.6±2.1kg/m(2) (mean±SD)] were enrolled in a randomized, two-crossover experiment (Fasting and 'Hara-Hachibu' conditions). Before the MEG recordings in the 'Hara-Hachibu' condition, the participants consumed rice balls as much as they judged themselves to have consumed shortly before reaching satiety. During the MEG recordings, they viewed food pictures projected on a screen. The intensities of MEG responses to viewing food pictures were significantly lower in the 'Hara-Hachibu' condition than those in the Fasting condition (P<0.05). The intensities of the MEG responses to the visual food stimuli in the 'Hara-Hachibu' condition was positively associated with the factor-3 (food tasted) (r=0.693, P=0.018) and aggregated scores (r=0.659, P=0.027) of the Power of Food Scale, a self-report measure of hedonic hunger. These findings may help to elucidate the neural basis of variability of appetite phenotypes under the condition of CR among individuals, and to develop possible strategies for the maintenance of adequate CR in daily life. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Thinking about the thoughts of others; temporal and spatial neural activation during false belief reasoning.

PubMed

Mossad, Sarah I; AuCoin-Power, Michelle; Urbain, Charline; Smith, Mary Lou; Pang, Elizabeth W; Taylor, Margot J

2016-07-01

Theory of Mind (ToM) is the ability to understand the perspectives, mental states and beliefs of others in order to anticipate their behaviour and is therefore crucial to social interactions. Although fMRI has been widely used to establish the neural networks implicated in ToM, little is known about the timing of ToM-related brain activity. We used magnetoencephalography (MEG) to measure the neural processes underlying ToM, as MEG provides very accurate timing and excellent spatial localization of brain processes. We recorded MEG activity during a false belief task, a reliable measure of ToM, in twenty young adults (10 females). MEG data were recorded in a 151 sensor CTF system (MISL, Coquitlam, BC) and data were co-registered to each participant's MRI (Siemens 3T) for source reconstruction. We found stronger right temporoparietal junction (rTPJ) activations in the false belief condition from 150ms to 225ms, in the right precuneus from 275ms to 375ms, in the right inferior frontal gyrus from 200ms to 300ms and the superior frontal gyrus from 300ms to 400ms. Our findings extend the literature by demonstrating the timing and duration of neural activity in the main regions involved in the "mentalizing" network, showing that activations related to false belief in adults are predominantly right lateralized and onset around 100ms. The sensitivity of MEG will allow us to determine spatial and temporal differences in the brain processes in ToM in younger populations or those who demonstrate deficits in this ability. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Quality by Design approach for an in situ gelling microemulsion of Lorazepam via intranasal route.

PubMed

Shah, Vidhi; Sharma, Mukesh; Pandya, Radhika; Parikh, Rajesh K; Bharatiya, Bhavesh; Shukla, Atindra; Tsai, Hsieh-Chih

2017-06-01

The present study illustrates the application of the concept of Quality by Design for development, optimization and evaluation of Lorazepam loaded microemulsion containing ion responsive In situ gelator gellan gum and carbopol 934. A novel approach involving interactions between surfactant and polymer was employed to achieve controlled drug release and reduced mucociliary clearance. Microemulsion formulated using preliminary solubility study and pseudo ternary phase diagrams showed significantly improved solubilization capacity of Lorazepam with 54.31±6.07nm droplets size. The effect of oil to surfactant/cosurfactant ratio and concentration of gelling agent on the drug release and viscosity of microemulsion gel (MEG) was evaluated using a 3 2 full factorial design. The gel of optimized formulation (MEG 1 ) showed a drug release up to 6h of 97.32±1.35% of total drug loaded. The change in shear-dependent viscosity for different formulations on interaction with Simulated Nasal Fluid depicts the crucial role of surfactant-polymer interactions on the gelation properties along with calcium ions binding on the polymer chains. It is proposed that the surfactant-polymer interactions in the form of a stoichiometric hydrogen bonding between oxyethylene and carboxylic groups of the polymers used, provides exceptional ME stability and adhesion properties. Compared with the marketed formulation, optimized MEG showed improved pharmacodynamic activity. Ex vivo diffusion studies revealed significantly higher release for MEG compared to microemulsion and drug solution. MEG showed higher flux and permeation across goat nasal mucosa. According to the study, it could be concluded that formulation would successfully provide the rapid onset of action, and decrease the mucociliary clearance due to formation of in situ gelling mucoadhesive system. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Combined MEG-EEG source localisation in patients with sub-acute sclerosing pan-encephalitis.

PubMed

Velmurugan, J; Sinha, Sanjib; Nagappa, Madhu; Mariyappa, N; Bindu, P S; Ravi, G S; Hazra, Nandita; Thennarasu, K; Ravi, V; Taly, A B; Satishchandra, P

2016-08-01

To study the genesis and propagation patterns of periodic complexes (PCs) associated with myoclonic jerks in sub-acute sclerosing pan-encephalitis (SSPE) using magnetoencephalography (MEG) and electroencephalography (EEG). Simultaneous recording of MEG (306 channels) and EEG (64 channels) in five patients of SSPE (M:F = 3:2; age 10.8 ± 3.2 years; symptom-duration 6.2 ± 10 months) was carried out using Elekta Neuromag(®) TRIUX™ system. Qualitative analysis of 80-160 PCs per patient was performed. Ten isomorphic classical PCs with significant field topography per patient were analysed at the 'onset' and at 'earliest significant peak' of the burst using discrete and distributed source imaging methods. MEG background was asymmetrical in 2 and slow in 3 patients. Complexes were periodic (3) or quasi-periodic (2), occurring every 4-16 s and varied in morphology among patients. Mean source localization at onset of bursts using discrete and distributed source imaging in magnetic source imaging (MSI) was in thalami and or insula (50 and 50 %, respectively) and in electric source imaging (ESI) was also in thalami and or insula (38 and 46 %, respectively). Mean source localization at the earliest rising phase of peak in MSI was in peri-central gyrus (49 and 42 %) and in ESI it was in frontal cortex (52 and 56 %). Further analysis revealed that PCs were generated in thalami and or insula and thereafter propagated to anterolateral surface of the cortices (viz. sensori-motor cortex and frontal cortex) to same side as that of the onset. This novel MEG-EEG based case series of PCs provides newer insights for understanding the plausible generators of myoclonus in SSPE and patterns of their propagation.

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

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.

Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.

PubMed

Pillow, Jonathan W; Ahmadian, Yashar; Paninski, Liam

2011-01-01

One of the central problems in systems neuroscience is to understand how neural spike trains convey sensory information. Decoding methods, which provide an explicit means for reading out the information contained in neural spike responses, offer a powerful set of tools for studying the neural coding problem. Here we develop several decoding methods based on point-process neural encoding models, or forward models that predict spike responses to stimuli. These models have concave log-likelihood functions, which allow efficient maximum-likelihood model fitting and stimulus decoding. We present several applications of the encoding model framework to the problem of decoding stimulus information from population spike responses: (1) a tractable algorithm for computing the maximum a posteriori (MAP) estimate of the stimulus, the most probable stimulus to have generated an observed single- or multiple-neuron spike train response, given some prior distribution over the stimulus; (2) a gaussian approximation to the posterior stimulus distribution that can be used to quantify the fidelity with which various stimulus features are encoded; (3) an efficient method for estimating the mutual information between the stimulus and the spike trains emitted by a neural population; and (4) a framework for the detection of change-point times (the time at which the stimulus undergoes a change in mean or variance) by marginalizing over the posterior stimulus distribution. We provide several examples illustrating the performance of these estimators with simulated and real neural data.

Understanding student use of mathematics in IPLS with the Math Epistemic Games Survey

NASA Astrophysics Data System (ADS)

Eichenlaub, Mark; Hemingway, Deborah; Redish, Edward F.

2017-01-01

We present the Math Epistemic Games Survey (MEGS), a new concept inventory on the use of mathematics in introductory physics for the life sciences. The survey asks questions that are often best-answered via techniques commonly-valued in physics instruction, including dimensional analysis, checking special or extreme cases, understanding scaling relationships, interpreting graphical representations, estimation, and mapping symbols onto physical meaning. MEGS questions are often rooted in quantitative biology. We present preliminary data on the validation and administration of the MEGS in a large, introductory physics for the life sciences course at the University of Maryland, as well as preliminary results on the clustering of questions and responses as a guide to student resource activation in problem solving. This material is based upon work supported by the US National Science Foundation under Award No. 15-04366.

NeuroGrid: recording action potentials from the surface of the brain.

PubMed

Khodagholy, Dion; Gelinas, Jennifer N; Thesen, Thomas; Doyle, Werner; Devinsky, Orrin; Malliaras, George G; Buzsáki, György

2015-02-01

Recording from neural networks at the resolution of action potentials is critical for understanding how information is processed in the brain. Here, we address this challenge by developing an organic material-based, ultraconformable, biocompatible and scalable neural interface array (the 'NeuroGrid') that can record both local field potentials(LFPs) and action potentials from superficial cortical neurons without penetrating the brain surface. Spikes with features of interneurons and pyramidal cells were simultaneously acquired by multiple neighboring electrodes of the NeuroGrid, allowing for the isolation of putative single neurons in rats. Spiking activity demonstrated consistent phase modulation by ongoing brain oscillations and was stable in recordings exceeding 1 week's duration. We also recorded LFP-modulated spiking activity intraoperatively in patients undergoing epilepsy surgery. The NeuroGrid constitutes an effective method for large-scale, stable recording of neuronal spikes in concert with local population synaptic activity, enhancing comprehension of neural processes across spatiotemporal scales and potentially facilitating diagnosis and therapy for brain disorders.

A Fully Automated Approach to Spike Sorting.

PubMed

Chung, Jason E; Magland, Jeremy F; Barnett, Alex H; Tolosa, Vanessa M; Tooker, Angela C; Lee, Kye Y; Shah, Kedar G; Felix, Sarah H; Frank, Loren M; Greengard, Leslie F

2017-09-13

Understanding the detailed dynamics of neuronal networks will require the simultaneous measurement of spike trains from hundreds of neurons (or more). Currently, approaches to extracting spike times and labels from raw data are time consuming, lack standardization, and involve manual intervention, making it difficult to maintain data provenance and assess the quality of scientific results. Here, we describe an automated clustering approach and associated software package that addresses these problems and provides novel cluster quality metrics. We show that our approach has accuracy comparable to or exceeding that achieved using manual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hundreds of electrodes. Moreover, a single choice of parameters in the algorithm is effective for a variety of electrode geometries and across multiple brain regions. This algorithm has the potential to enable reproducible and automated spike sorting of larger scale recordings than is currently possible. Copyright © 2017 Elsevier Inc. 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.

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

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.

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.

Cognitive inhibition of number/length interference in a Piaget-like task: evidence by combining ERP and MEG.

PubMed

Joliot, Marc; Leroux, Gaëlle; Dubal, Stéphanie; Tzourio-Mazoyer, Nathalie; Houdé, Olivier; Mazoyer, Bernard; Petit, Laurent

2009-08-01

We combined event-related potential (ERP) and magnetoencephalography (MEG) acquisition and analysis to investigate the electrophysiological markers of the inhibitory processes involved in the number/length interference in a Piaget-like numerical task. Eleven healthy subjects performed four gradually interfering conditions with the heuristic "length equals number" to be inhibited. Low resolution tomography reconstruction was performed on the combined grand averaged electromagnetic data at the early (N1, P1) and late (P2, N2, P3(early) and P3(late)) latencies. Every condition was analyzed at both scalp and regional brain levels. The inhibitory processes were visible on the late components of the electromagnetic brain activity. A right P2-related frontal orbital activation reflected the change of strategy in the inhibitory processes. N2-related SMA/cingulate activation revealed the first occurrence of the stimuli processing to be inhibited. Both P3 components revealed the working memory processes operating in a medial temporal complex and the mental imagery processes subtended by the precuneus. Simultaneous ERP and MEG signal acquisition and analysis allowed to describe the spatiotemporal patterns of neural networks involved in the inhibition of the "length equals number" interference. Combining ERP and MEG ensured a sensitivity which could be reached previously only through invasive intracortical recordings.

Advanced electronics for the CTF MEG system.

PubMed

McCubbin, J; Vrba, J; Spear, P; McKenzie, D; Willis, R; Loewen, R; Robinson, S E; Fife, A A

2004-11-30

Development of the CTF MEG system has been advanced with the introduction of a computer processing cluster between the data acquisition electronics and the host computer. The advent of fast processors, memory, and network interfaces has made this innovation feasible for large data streams at high sampling rates. We have implemented tasks including anti-alias filter, sample rate decimation, higher gradient balancing, crosstalk correction, and optional filters with a cluster consisting of 4 dual Intel Xeon processors operating on up to 275 channel MEG systems at 12 kHz sample rate. The architecture is expandable with additional processors to implement advanced processing tasks which may include e.g., continuous head localization/motion correction, optional display filters, coherence calculations, or real time synthetic channels (via beamformer). We also describe an electronics configuration upgrade to provide operator console access to the peripheral interface features such as analog signal and trigger I/O. This allows remote location of the acoustically noisy electronics cabinet and fitting of the cabinet with doors for improved EMI shielding. Finally, we present the latest performance results available for the CTF 275 channel MEG system including an unshielded SEF (median nerve electrical stimulation) measurement enhanced by application of an adaptive beamformer technique (SAM) which allows recognition of the nominal 20-ms response in the unaveraged signal.

Neuromagnetic Vistas into Typical and Atypical Development of Frontal Lobe Functions

PubMed Central

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

2014-01-01

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

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.

Pharmacokinetics of IDX184, a liver-targeted oral prodrug of 2'-methylguanosine-5'-monophosphate, in the monkey and formulation optimization for human exposure.

PubMed

Pan-Zhou, Xin-Ru; Mayes, Benjamin A; Rashidzadeh, Hassan; Gasparac, Rahela; Smith, Steven; Bhadresa, Sanjeev; Gupta, Kusum; Cohen, Marita Larsson; Bu, Charlie; Good, Steven S; Moussa, Adel; Rush, Roger

2016-10-01

IDX184 is a phosphoramidate prodrug of 2'-methylguanosine-5'-monophosphate, developed to treat patients infected with hepatitis C virus. A mass balance study of radiolabeled IDX184 and pharmacokinetic studies of IDX184 in portal vein-cannulated monkeys revealed relatively low IDX184 absorption but higher exposure of IDX184 in the portal vein than in the systemic circulation, indicating >90 % of the absorbed dose was subject to hepatic extraction. Systemic exposures to the main metabolite, 2'-methylguanosine (2'-MeG), were used as a surrogate for liver levels of the pharmacologically active entity 2'-MeG triphosphate, and accordingly, systemic levels of 2'-MeG in the monkey were used to optimize formulations for further clinical development of IDX184. Capsule formulations of IDX184 delivered acceptable levels of 2'-MeG in humans; however, the encapsulation process introduced low levels of the genotoxic impurity ethylene sulfide (ES), which necessitated formulation optimization. Animal pharmacokinetic data guided the development of a tablet with trace levels of ES and pharmacokinetic performance equal to that of the clinical capsule in the monkey. Under fed conditions in humans, the new tablet formulation showed similar exposure to the capsule used in prior clinical trials.

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.

Identification of interacting proteins of the TaFVE protein involved in spike development in bread wheat.

PubMed

Zheng, Yong-Sheng; Lu, Yu-Qing; Meng, Ying-Ying; Zhang, Rong-Zhi; Zhang, Han; Sun, Jia-Mei; Wang, Mu-Mu; Li, Li-Hui; Li, Ru-Yu

2017-05-01

WD-40 repeat-containing protein MSI4 (FVE)/MSI4 plays important roles in determining flowering time in Arabidopsis. However, its function is unexplored in wheat. In the present study, coimmunoprecipitation and nanoscale liquid chromatography coupled to MS/MS were used to identify FVE in wheat (TaFVE)-interacting or associated proteins. Altogether 89 differentially expressed proteins showed the same downregulated expression trends as TaFVE in wheat line 5660M. Among them, 62 proteins were further predicted to be involved in the interaction network of TaFVE and 11 proteins have been shown to be potential TaFVE interactors based on curated databases and experimentally determined in other species by the STRING. Both yeast two-hybrid assay and bimolecular fluorescence complementation assay showed that histone deacetylase 6 and histone deacetylase 15 directly interacted with TaFVE. Multiple chromatin-remodelling proteins and polycomb group proteins were also identified and predicted to interact with TaFVE. These results showed that TaFVE directly interacted with multiple proteins to form multiple complexes to regulate spike developmental process, e.g. histone deacetylate, chromatin-remodelling and polycomb repressive complex 2 complexes. In addition, multiple flower development regulation factors (e.g. flowering locus K homology domain, flowering time control protein FPA, FY, flowering time control protein FCA, APETALA 1) involved in floral transition were also identified in the present study. Taken together, these results further elucidate the regulatory functions of TaFVE and help reveal the genetic mechanisms underlying wheat spike differentiation. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Morphological Analyses of Spring Wheat (CIMMYT cv. PCYT-10) Somaclones

NASA Technical Reports Server (NTRS)

Campbell, W. F.; Carman, J. G.; Hashim, Z. N.

1990-01-01

The objectives of this study were to induce callus from single immature wheat embryos, produce multiple seedlings from the induced callus, and analyse the somaclonal regenerants for potential grain production in a space garden. Immature wheat, Triticum aestivum L. (cv. PCYT-10), embryos were excised 10 to 12 days post-anthesis and cultured on modified Murashige and Skoog's inorganic salts. Embryos cultured on medium containing kinetin (6-furfurylaminopurine) at 0.5mg/l plus 2 or 3mg/l dicamba (1-methoxy-3,6- dichlorobenzoic acid) or 0.2mg/l 2,4-dichlorophenoxyacetic acid produced calli from which 24, 35 and 39% of the explant tissue exhibited regenerants, respectively. The size of flag leaves, plant heights, tillers per plant, spike lengths, awn lengths, and seeds per spike were significantly different in regenerants of two-selfed recurrent generations (SC(sub 1), SC(sub 2)) than in parental controls. However, there were no significant differences in spikelets per spike between the SC(sub 2) and parental controls. Desirable characteristics that were obtained included longer spikes, more seeds per spike, supernumerary spikelets, and larger flag leaves, variants that should be useful in wheat improvement programs.

Common and Distinctive Patterns of Cognitive Dysfunction in Children With Benign Epilepsy Syndromes.

PubMed

Cheng, Dazhi; Yan, Xiuxian; Gao, Zhijie; Xu, Keming; Zhou, Xinlin; Chen, Qian

2017-07-01

Childhood absence epilepsy and benign childhood epilepsy with centrotemporal spikes are the most common forms of benign epilepsy syndromes. Although cognitive dysfunctions occur in children with both childhood absence epilepsy and benign childhood epilepsy with centrotemporal spikes, the similarity between their patterns of underlying cognitive impairments is not well understood. To describe these patterns, we examined multiple cognitive functions in children with childhood absence epilepsy and benign childhood epilepsy with centrotemporal spikes. In this study, 43 children with childhood absence epilepsy, 47 children with benign childhood epilepsy with centrotemporal spikes, and 64 control subjects were recruited; all received a standardized assessment (i.e., computerized test battery) assessing processing speed, spatial skills, calculation, language ability, intelligence, visual attention, and executive function. Groups were compared in these cognitive domains. Simple regression analysis was used to analyze the effects of epilepsy-related clinical variables on cognitive test scores. Compared with control subjects, children with childhood absence epilepsy and benign childhood epilepsy with centrotemporal spikes showed cognitive deficits in intelligence and executive function, but performed normally in language processing. Impairment in visual attention was specific to patients with childhood absence epilepsy, whereas impaired spatial ability was specific to the children with benign childhood epilepsy with centrotemporal spikes. Simple regression analysis showed syndrome-related clinical variables did not affect cognitive functions. This study provides evidence of both common and distinctive cognitive features underlying the relative cognitive difficulties in children with childhood absence epilepsy and benign childhood epilepsy with centrotemporal spikes. Our data suggest that clinicians should pay particular attention to the specific cognitive deficits in children with childhood absence epilepsy and benign childhood epilepsy with centrotemporal spikes, to allow for more discriminative and potentially more effective interventions. Copyright © 2017 Elsevier Inc. All rights reserved.

Distinguishing mechanisms of gamma frequency oscillations in human current source signals using a computational model of a laminar neocortical network

PubMed Central

Lee, Shane; Jones, Stephanie R.

2013-01-01

Gamma frequency rhythms have been implicated in numerous studies for their role in healthy and abnormal brain function. The frequency band has been described to encompass as broad a range as 30–150 Hz. Crucial to understanding the role of gamma in brain function is an identification of the underlying neural mechanisms, which is particularly difficult in the absence of invasive recordings in macroscopic human signals such as those from magnetoencephalography (MEG) and electroencephalography (EEG). Here, we studied features of current dipole (CD) signals from two distinct mechanisms of gamma generation, using a computational model of a laminar cortical circuit designed specifically to simulate CDs in a biophysically principled manner (Jones et al., 2007, 2009). We simulated spiking pyramidal interneuronal gamma (PING) whose period is regulated by the decay time constant of GABAA-mediated synaptic inhibition and also subthreshold gamma driven by gamma-periodic exogenous excitatory synaptic drive. Our model predicts distinguishable CD features created by spiking PING compared to subthreshold driven gamma that can help to disambiguate mechanisms of gamma oscillations in human signals. We found that gamma rhythms in neocortical layer 5 can obscure a simultaneous, independent gamma in layer 2/3. Further, we arrived at a novel interpretation of the origin of high gamma frequency rhythms (100–150 Hz), showing that they emerged from a specific temporal feature of CDs associated with single cycles of PING activity and did not reflect a separate rhythmic process. Last we show that the emergence of observable subthreshold gamma required highly coherent exogenous drive. Our results are the first to demonstrate features of gamma oscillations in human current source signals that distinguish cellular and circuit level mechanisms of these rhythms and may help to guide understanding of their functional role. PMID:24385958

A novel scheme for the validation of an automated classification method for epileptic spikes by comparison with multiple observers.

PubMed

Sharma, Niraj K; Pedreira, Carlos; Centeno, Maria; Chaudhary, Umair J; Wehner, Tim; França, Lucas G S; Yadee, Tinonkorn; Murta, Teresa; Leite, Marco; Vos, Sjoerd B; Ourselin, Sebastien; Diehl, Beate; Lemieux, Louis

2017-07-01

To validate the application of an automated neuronal spike classification algorithm, Wave_clus (WC), on interictal epileptiform discharges (IED) obtained from human intracranial EEG (icEEG) data. Five 10-min segments of icEEG recorded in 5 patients were used. WC and three expert EEG reviewers independently classified one hundred IED events into IED classes or non-IEDs. First, we determined whether WC-human agreement variability falls within inter-reviewer agreement variability by calculating the variation of information for each classifier pair and quantifying the overlap between all WC-reviewer and all reviewer-reviewer pairs. Second, we compared WC and EEG reviewers' spike identification and individual spike class labels visually and quantitatively. The overlap between all WC-human pairs and all human pairs was >80% for 3/5 patients and >58% for the other 2 patients demonstrating WC falling within inter-human variation. The average sensitivity of spike marking for WC was 91% and >87% for all three EEG reviewers. Finally, there was a strong visual and quantitative similarity between WC and EEG reviewers. WC performance is indistinguishable to that of EEG reviewers' suggesting it could be a valid clinical tool for the assessment of IEDs. WC can be used to provide quantitative analysis of epileptic spikes. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Intrinsic and synaptic properties of vertical cells of the mouse dorsal cochlear nucleus

PubMed Central

Kuo, Sidney P.; Lu, Hsin-Wei

2012-01-01

Multiple classes of inhibitory interneurons shape the activity of principal neurons of the dorsal cochlear nucleus (DCN), a primary target of auditory nerve fibers in the mammalian brain stem. Feedforward inhibition mediated by glycinergic vertical cells (also termed tuberculoventral or corn cells) is thought to contribute importantly to the sound-evoked response properties of principal neurons, but the cellular and synaptic properties that determine how vertical cells function are unclear. We used transgenic mice in which glycinergic neurons express green fluorescent protein (GFP) to target vertical cells for whole cell patch-clamp recordings in acute slices of DCN. We found that vertical cells express diverse intrinsic spiking properties and could fire action potentials at high, sustained spiking rates. Using paired recordings, we directly examined synapses made by vertical cells onto fusiform cells, a primary DCN principal cell type. Vertical cell synapses produced unexpectedly small-amplitude unitary currents in fusiform cells, and additional experiments indicated that multiple vertical cells must be simultaneously active to inhibit fusiform cell spike output. Paired recordings also revealed that a major source of inhibition to vertical cells comes from other vertical cells. PMID:22572947

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

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

Short-Range Temporal Interactions in Sleep; Hippocampal Spike Avalanches Support a Large Milieu of Sequential Activity Including Replay

PubMed Central

Mahoney, J. Matthew; Titiz, Ali S.; Hernan, Amanda E.; Scott, Rod C.

2016-01-01

Hippocampal neural systems consolidate multiple complex behaviors into memory. However, the temporal structure of neural firing supporting complex memory consolidation is unknown. Replay of hippocampal place cells during sleep supports the view that a simple repetitive behavior modifies sleep firing dynamics, but does not explain how multiple episodes could be integrated into associative networks for recollection during future cognition. Here we decode sequential firing structure within spike avalanches of all pyramidal cells recorded in sleeping rats after running in a circular track. We find that short sequences that combine into multiple long sequences capture the majority of the sequential structure during sleep, including replay of hippocampal place cells. The ensemble, however, is not optimized for maximally producing the behavior-enriched episode. Thus behavioral programming of sequential correlations occurs at the level of short-range interactions, not whole behavioral sequences and these short sequences are assembled into a large and complex milieu that could support complex memory consolidation. PMID:26866597

Synchronous neural interactions assessed by magnetoencephalography: a functional biomarker for brain disorders

NASA Astrophysics Data System (ADS)

Georgopoulos, Apostolos P.; Karageorgiou, Elissaios; Leuthold, Arthur C.; Lewis, Scott M.; Lynch, Joshua K.; Alonso, Aurelio A.; Aslam, Zaheer; Carpenter, Adam F.; Georgopoulos, Angeliki; Hemmy, Laura S.; Koutlas, Ioannis G.; Langheim, Frederick J. P.; Riley McCarten, J.; McPherson, Susan E.; Pardo, José V.; Pardo, Patricia J.; Parry, Gareth J.; Rottunda, Susan J.; Segal, Barbara M.; Sponheim, Scott R.; Stanwyck, John J.; Stephane, Massoud; Westermeyer, Joseph J.

2007-12-01

We report on a test to assess the dynamic brain function at high temporal resolution using magnetoencephalography (MEG). The essence of the test is the measurement of the dynamic synchronous neural interactions, an essential aspect of the brain function. MEG signals were recorded from 248 axial gradiometers while 142 human subjects fixated a spot of light for 45-60 s. After fitting an autoregressive integrative moving average (ARIMA) model and taking the stationary residuals, all pairwise, zero-lag, partial cross-correlations (PCCij0) and their z-transforms (zij0) between i and j sensors were calculated, providing estimates of the strength and sign (positive, negative) of direct synchronous coupling at 1 ms temporal resolution. We found that subsets of zij0 successfully classified individual subjects to their respective groups (multiple sclerosis, Alzheimer's disease, schizophrenia, Sjögren's syndrome, chronic alcoholism, facial pain, healthy controls) and gave excellent external cross-validation results. Contribution by the authors: Designed research (APG); acquired data (AAA, IGK, FJPL, ACL, SML, JJS); analyzed data (APG, EK, ACL, JKL); wrote the paper (APG, EK, ACL, SML); contributed subjects (AAA, ZA, AFC, AG, LSH, IGK, FJPL, SML, JRM, SEM, JVP, PJP, GJP, SJR, BMS, SRS, MS, JJS, JJW); discussed results (All); contributed equally (ZA, AFC, AG, LSH, FJPL, JRM, SEM, JVP, PJP, GJP, SJR, BMS, SRS, MS, JJS, JJW).

Minimum Requirements for Accurate and Efficient Real-Time On-Chip Spike Sorting

PubMed Central

Navajas, Joaquin; Barsakcioglu, Deren Y.; Eftekhar, Amir; Jackson, Andrew; Constandinou, Timothy G.; Quiroga, Rodrigo Quian

2014-01-01

Background Extracellular recordings are performed by inserting electrodes in the brain, relaying the signals to external power-demanding devices, where spikes are detected and sorted in order to identify the firing activity of different putative neurons. A main caveat of these recordings is the necessity of wires passing through the scalp and skin in order to connect intracortical electrodes to external amplifiers. The aim of this paper is to evaluate the feasibility of an implantable platform (i.e. a chip) with the capability to wirelessly transmit the neural signals and perform real-time on-site spike sorting. New Method We computationally modelled a two-stage implementation for online, robust, and efficient spike sorting. In the first stage, spikes are detected on-chip and streamed to an external computer where mean templates are created and sent back to the chip. In the second stage, spikes are sorted in real-time through template matching. Results We evaluated this procedure using realistic simulations of extracellular recordings and describe a set of specifications that optimise performance while keeping to a minimum the signal requirements and the complexity of the calculations. Comparison with Existing Methods A key bottleneck for the development of long-term BMIs is to find an inexpensive method for real-time spike sorting. Here, we simulated a solution to this problem that uses both offline and online processing of the data. Conclusions Hardware implementations of this method therefore enable low-power long-term wireless transmission of multiple site extracellular recordings, with application to wireless BMIs or closed-loop stimulation designs. PMID:24769170

A unified approach to the study of temporal, correlational, and rate coding.

PubMed

Panzeri, S; Schultz, S R

2001-06-01

We demonstrate that the information contained in the spike occurrence times of a population of neurons can be broken up into a series of terms, each reflecting something about potential coding mechanisms. This is possible in the coding regime in which few spikes are emitted in the relevant time window. This approach allows us to study the additional information contributed by spike timing beyond that present in the spike counts and to examine the contributions to the whole information of different statistical properties of spike trains, such as firing rates and correlation functions. It thus forms the basis for a new quantitative procedure for analyzing simultaneous multiple neuron recordings and provides theoretical constraints on neural coding strategies. We find a transition between two coding regimes, depending on the size of the relevant observation timescale. For time windows shorter than the timescale of the stimulus-induced response fluctuations, there exists a spike count coding phase, in which the purely temporal information is of third order in time. For time windows much longer than the characteristic timescale, there can be additional timing information of first order, leading to a temporal coding phase in which timing information may affect the instantaneous information rate. In this new framework, we study the relative contributions of the dynamic firing rate and correlation variables to the full temporal information, the interaction of signal and noise correlations in temporal coding, synergy between spikes and between cells, and the effect of refractoriness. We illustrate the utility of the technique by analyzing a few cells from the rat barrel cortex.

Spike timing precision of neuronal circuits.

PubMed

Kilinc, Deniz; Demir, Alper

2018-06-01

Spike timing is believed to be a key factor in sensory information encoding and computations performed by the neurons and neuronal circuits. However, the considerable noise and variability, arising from the inherently stochastic mechanisms that exist in the neurons and the synapses, degrade spike timing precision. Computational modeling can help decipher the mechanisms utilized by the neuronal circuits in order to regulate timing precision. In this paper, we utilize semi-analytical techniques, which were adapted from previously developed methods for electronic circuits, for the stochastic characterization of neuronal circuits. These techniques, which are orders of magnitude faster than traditional Monte Carlo type simulations, can be used to directly compute the spike timing jitter variance, power spectral densities, correlation functions, and other stochastic characterizations of neuronal circuit operation. We consider three distinct neuronal circuit motifs: Feedback inhibition, synaptic integration, and synaptic coupling. First, we show that both the spike timing precision and the energy efficiency of a spiking neuron are improved with feedback inhibition. We unveil the underlying mechanism through which this is achieved. Then, we demonstrate that a neuron can improve on the timing precision of its synaptic inputs, coming from multiple sources, via synaptic integration: The phase of the output spikes of the integrator neuron has the same variance as that of the sample average of the phases of its inputs. Finally, we reveal that weak synaptic coupling among neurons, in a fully connected network, enables them to behave like a single neuron with a larger membrane area, resulting in an improvement in the timing precision through cooperation.

Pleiotropic effects of the wheat domestication gene Q on yield and grain morphology.

PubMed

Xie, Quan; Li, Na; Yang, Yang; Lv, Yulong; Yao, Hongni; Wei, Rong; Sparkes, Debbie L; Ma, Zhengqiang

2018-05-01

Transformation from q to Q during wheat domestication functioned outside the boundary of threshability to increase yield, grains m -2 , grain weight and roundness, but to reduce grains per spike/spikelet. Mutation of the Q gene, well-known affecting wheat spike structure, represents a key domestication step in the formation of today's free-threshing, economically important wheats. In a previous study, multiple yield components and spike characteristics were associated with the Q gene interval in the bread wheat 'Forno' × European spelt 'Oberkulmer' recombinant inbred line population. Here, we reported that this interval was also associated with grain yield, grains m -2 , grain morphology, and spike dry weight at anthesis. To clarify the roles of Q in agronomic trait performance, a functional marker for the Q gene was developed. Analysis of allelic effects showed that the bread wheat Q allele conferred free-threshing habit, soft glumes, and short and compact spikes compared with q. In addition, the Q allele contributed to higher grain yield, more grains m -2 , and higher thousand grain weight, whereas q contributed to more grains per spike/spikelet likely resulting from increased preanthesis spike growth. For grain morphology, the Q allele was associated with reduced ratio of grain length to height, indicating a rounder grain. These results are supported by analysis of four Q mutant lines in the Chinese Spring background. Therefore, the transition from q to Q during wheat domestication had profound effects on grain yield and grain shape evolution as well, being a consequence of pleiotropy.

[SP600125-induced polyploidization of megakaryocytic leukemia cell lines by ribosomal protein S6 kinase 1 depends on the degree of cell differentiation].

PubMed

Wang, Lili; Yang, Jingang; Li, Changling; Xing, Sining; Yu, Ying; Liu, Shuo; Zhao, Song; Ma, Dongchu

2016-10-01

Objective To investigate regulatory role of ribosomal protein S6 kinase 1 (S6K1) in the polyploidization of different megakaryocytic leukemia cell lines at the different differentiation stages. Methods Megakaryocytic leukemia cell lines (Dami, Meg-01 and HEL cells) were induced towards polyploidization by SP600125, a c-Jun N-terminal kinase (JNK) inhibitor. The SP600125-inducing process was blocked by H-89, a cAMP-dependent protein kinase (PKA) inhibitor. The phenotype (CD41a, CD42a and CD42b) and DNA ploidy were detected by flow cytometry. The expression and phosphorylation of S6K1 and related proteins were detected by Western blotting. Results SP600125 induced polyploidization and increased the phosphorylation of eukaryotic initiation factor 4E binding protein 1 (4E-BP1) in Dami, Meg-01 and HEL cells. However, the effect of SP600125 on polyploidization of the three cell lines was different, with the strongest effect on Dami cells and the weakest on Meg-01 cells. Moreover, SP600125 increased the phosphorylation of S6K1 Thr421/Ser424 and decreased the phosphorylation of Thr389 in Dami cells. However, it only increased the phosphorylation of Thr389 in HEL cells and had no effect on the phosphorylation of S6K1 in Meg-01 cells. Interestingly, H-89 only partially blocked the polyploidization of Dami cells, although it decreased the phosphorylation of 4E-BP1 in all SP600125-induced three cell lines. Noticeably, H-89 decreased the phosphorylation of S6K1 Thr421/Ser424 and increased the phosphorylation of Thr389 in Dami cells. However, H-89 had no effect on the phosphorylation of Thr421/Ser424, although it increased the phosphorylation of Thr389 in Meg-01 and HEL cells. Phenotypic analysis showed that the three cell lines were at different levels of differentiation in megakaryocytic lineage, with the highest differentiation in Dami and the lowest in Meg-01 cells. Conclusion SP600125-induced polyploidization of megakaryocytic leukemia cell lines is dependent on the effect of SP600125 on phosphorylation of S6K1 in cell lines at the different differentiation stages.

Effects of Visual Complexity and Sublexical Information in the Occipitotemporal Cortex in the Reading of Chinese Phonograms: A Single-Trial Analysis with MEG

ERIC Educational Resources Information Center

Hsu, Chun-Hsien; Lee, Chia-Ying; Marantz, Alec

2011-01-01

We employ a linear mixed-effects model to estimate the effects of visual form and the linguistic properties of Chinese characters on M100 and M170 MEG responses from single-trial data of Chinese and English speakers in a Chinese lexical decision task. Cortically constrained minimum-norm estimation is used to compute the activation of M100 and M170…

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

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.

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.

Autoreject: Automated artifact rejection for MEG and EEG data.

PubMed

Jas, Mainak; Engemann, Denis A; Bekhti, Yousra; Raimondo, Federico; Gramfort, Alexandre

2017-10-01

We present an automated algorithm for unified rejection and repair of bad trials in magnetoencephalography (MEG) and electroencephalography (EEG) signals. Our method capitalizes on cross-validation in conjunction with a robust evaluation metric to estimate the optimal peak-to-peak threshold - a quantity commonly used for identifying bad trials in M/EEG. This approach is then extended to a more sophisticated algorithm which estimates this threshold for each sensor yielding trial-wise bad sensors. Depending on the number of bad sensors, the trial is then repaired by interpolation or by excluding it from subsequent analysis. All steps of the algorithm are fully automated thus lending itself to the name Autoreject. In order to assess the practical significance of the algorithm, we conducted extensive validation and comparisons with state-of-the-art methods on four public datasets containing MEG and EEG recordings from more than 200 subjects. The comparisons include purely qualitative efforts as well as quantitatively benchmarking against human supervised and semi-automated preprocessing pipelines. The algorithm allowed us to automate the preprocessing of MEG data from the Human Connectome Project (HCP) going up to the computation of the evoked responses. The automated nature of our method minimizes the burden of human inspection, hence supporting scalability and reliability demanded by data analysis in modern neuroscience. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

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

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.

Stability versus neuronal specialization for STDP: long-tail weight distributions solve the dilemma.

PubMed

Gilson, Matthieu; Fukai, Tomoki

2011-01-01

Spike-timing-dependent plasticity (STDP) modifies the weight (or strength) of synaptic connections between neurons and is considered to be crucial for generating network structure. It has been observed in physiology that, in addition to spike timing, the weight update also depends on the current value of the weight. The functional implications of this feature are still largely unclear. Additive STDP gives rise to strong competition among synapses, but due to the absence of weight dependence, it requires hard boundaries to secure the stability of weight dynamics. Multiplicative STDP with linear weight dependence for depression ensures stability, but it lacks sufficiently strong competition required to obtain a clear synaptic specialization. A solution to this stability-versus-function dilemma can be found with an intermediate parametrization between additive and multiplicative STDP. Here we propose a novel solution to the dilemma, named log-STDP, whose key feature is a sublinear weight dependence for depression. Due to its specific weight dependence, this new model can produce significantly broad weight distributions with no hard upper bound, similar to those recently observed in experiments. Log-STDP induces graded competition between synapses, such that synapses receiving stronger input correlations are pushed further in the tail of (very) large weights. Strong weights are functionally important to enhance the neuronal response to synchronous spike volleys. Depending on the input configuration, multiple groups of correlated synaptic inputs exhibit either winner-share-all or winner-take-all behavior. When the configuration of input correlations changes, individual synapses quickly and robustly readapt to represent the new configuration. We also demonstrate the advantages of log-STDP for generating a stable structure of strong weights in a recurrently connected network. These properties of log-STDP are compared with those of previous models. Through long-tail weight distributions, log-STDP achieves both stable dynamics for and robust competition of synapses, which are crucial for spike-based information processing.

Competitive STDP Learning of Overlapping Spatial Patterns.

PubMed

Krunglevicius, Dalius

2015-08-01

Spike-timing-dependent plasticity (STDP) is a set of Hebbian learning rules firmly based on biological evidence. It has been demonstrated that one of the STDP learning rules is suited for learning spatiotemporal patterns. When multiple neurons are organized in a simple competitive spiking neural network, this network is capable of learning multiple distinct patterns. If patterns overlap significantly (i.e., patterns are mutually inclusive), however, competition would not preclude trained neuron's responding to a new pattern and adjusting synaptic weights accordingly. This letter presents a simple neural network that combines vertical inhibition and Euclidean distance-dependent synaptic strength factor. This approach helps to solve the problem of pattern size-dependent parameter optimality and significantly reduces the probability of a neuron's forgetting an already learned pattern. For demonstration purposes, the network was trained for the first ten letters of the Braille alphabet.

Muscles innervated by a single motor neuron exhibit divergent synaptic properties on multiple time scales.

PubMed

Blitz, Dawn M; Pritchard, Amy E; Latimer, John K; Wakefield, Andrew T

2017-04-01

Adaptive changes in the output of neural circuits underlying rhythmic behaviors are relayed to muscles via motor neuron activity. Presynaptic and postsynaptic properties of neuromuscular junctions can impact the transformation from motor neuron activity to muscle response. Further, synaptic plasticity occurring on the time scale of inter-spike intervals can differ between multiple muscles innervated by the same motor neuron. In rhythmic behaviors, motor neuron bursts can elicit additional synaptic plasticity. However, it is unknown whether plasticity regulated by the longer time scale of inter-burst intervals also differs between synapses from the same neuron, and whether any such distinctions occur across a physiological activity range. To address these issues, we measured electrical responses in muscles innervated by a chewing circuit neuron, the lateral gastric (LG) motor neuron, in a well-characterized small motor system, the stomatogastric nervous system (STNS) of the Jonah crab, Cancer borealis In vitro and in vivo , sensory, hormonal and modulatory inputs elicit LG bursting consisting of inter-spike intervals of 50-250 ms and inter-burst intervals of 2-24 s. Muscles expressed similar facilitation measured with paired stimuli except at the shortest inter-spike interval. However, distinct decay time constants resulted in differences in temporal summation. In response to bursting activity, augmentation occurred to different extents and saturated at different inter-burst intervals. Further, augmentation interacted with facilitation, resulting in distinct intra-burst facilitation between muscles. Thus, responses of multiple target muscles diverge across a physiological activity range as a result of distinct synaptic properties sensitive to multiple time scales. © 2017. Published by The Company of Biologists Ltd.

Quantitation of iothalamate in urine and plasma using liquid chromatography electrospray tandem mass spectrometry (HPLC-ESI-MS/MS).

PubMed

Molinaro, Ross J; Ritchie, James C

2010-01-01

The following chapter describes a method to measure iothalamate in plasma and urine samples using high performance liquid chromatography combined with electrospray positive ionization tandem mass spectrometry (HPLC-ESI-MS/MS). Methanol and water are spiked with the internal standard (IS) iohexol. Iothalamate is isolated from plasma after IS spiked methanol extraction and from urine by IS spiked water addition and quick-spin filtration. The plasma extractions are dried under a stream of nitrogen. The residue is reconstituted in ammonium acetate-formic acid-water. The reconstituted plasma and filtered urine are injected into the HPLC-ESI-MS/MS. Iothalamate and iohexol show similar retention times in plasma and urine. Quantification of iothalamate in the samples is made by multiple reaction monitoring using the hydrogen adduct mass transitions, from a five-point calibration curve.

Spike-Nosed Bodies and Forward Injected Jets in Supersonic Flow

NASA Technical Reports Server (NTRS)

Gilinsky, M.; Washington, C.; Blankson, I. M.; Shvets, A. I.

2002-01-01

The paper contains new numerical simulation and experimental test results of blunt body drag reduction using thin spikes mounted in front of a body and one- or two-phase jets injected against a supersonic flow. Numerical simulations utilizing the NASA CFL3D code were conducted at the Hampton University Fluid Mechanics and Acoustics Laboratory (FM&AL) and experimental tests were conducted using the facilities of the IM/MSU Aeromechanics and Gas Dynamics Laboratory. Previous results were presented at the 37th AIAA/ASME/SAE/ASEE Joint Propulsion Conference. Those results were based on some experimental and numerical simulation tests for supersonic flow around spike-nosed or shell-nosed bodies, and numerical simulations were conducted only for a single spike-nosed or shell-nosed body at zero attack angle, alpha=0. In this paper, experimental test results of gas, liquid and solid particle jet injection against a supersonic flow are presented. In addition, numerical simulation results for supersonic flow around a multiple spike-nosed body with non-zero attack angles and with a gas and solid particle forward jet injection are included. Aerodynamic coefficients: drag, C(sub D), lift, C(sub L), and longitudinal momentum, M(sub z), obtained by numerical simulation and experimental tests are compared and show good agreement.

Spike-Nosed Bodies and Forward Injected Jets in Supersonic Flow

NASA Technical Reports Server (NTRS)

Gilinsky, M.; Washington, C.; Blankson, I. M.; Shvets, A. I.

2002-01-01

The paper contains new numerical simulation and experimental test results of blunt body drag reduction using thin spikes mounted in front of a body and one- or two-phase jets injected against a supersonic flow. Numerical simulations utilizing the NASA CFL3D code were conducted at the Hampton University Fluid Mechanics and Acoustics Laboratory (FM&AL) and experimental tests were conducted using the facilities of the IM/MSU Aeromechanics and Gas Dynamics Laboratory. Previous results were presented at the 37th AIAA/ASME/SAE/ASEE Joint Propulsion Conference. Those results were based on some experimental and numerical simulation tests for supersonic flow around spike-nosed or shell-nosed bodies, and numerical simulations were conducted only for a single spike-nosed or shell-nosed body at zero attack angle, alpha = 0 degrees. In this paper, experimental test results of gas, liquid and solid particle jet injection against a supersonic flow are presented. In addition, numerical simulation results for supersonic flow around a multiple spike-nosed body with non-zero attack angles and with a gas and solid particle forward jet injection are included. Aerodynamic coefficients: drag, C (sub D), lift, C(sub L), and longitudinal momentum, M(sub z), obtained by numerical simulation and experimental tests are compared and show good agreement.

Simultaneous determination of N7-alkylguanines in DNA by isotope-dilution LC-tandem MS coupled with automated solid-phase extraction and its application to a small fish model

PubMed Central

Chao, Mu-Rong; Wang, Chien-Jen; Yen, Cheng-Chieh; Yang, Hsi-Hsien; Lu, Yao-Cheng; Chang, Louis W.; Hu, Chiung-Wen

2006-01-01

In the present study, we report the development of a sensitive and selective assay based on LC (liquid chromatography)–MS/MS (tandem MS) to simultaneously measure N7-MeG (N7-methylguanine) and N7-EtG (N7-ethylguanine) in DNA hydrolysates. With the use of isotope internal standards (15N5-N7-MeG and 15N5-N7-EtG) and on-line SPE (solid-phase extraction), the detection limit of this method was estimated as 0.42 fmol and 0.17 fmol for N7-MeG and N7-EtG respectively. The high sensitivity achieved here makes this method applicable to small experimental animals. This method was applied to measure N7-alkylguanines in liver DNA from mosquito fish (Gambusia affinis) that were exposed to NDMA (N-nitrosodimethylamine) and NDEA (N-nitrosodiethylamine) alone or their combination over a wide range of concentrations (1–100 mg/l). Results showed that the background level of N7-MeG in liver of control fish was 7.89±1.38 μmol/mol of guanine, while N7-EtG was detectable in most of the control fish with a range of 0.05–0.19 μmol/mol of guanine. N7-MeG and N7-EtG were significantly induced by NDMA and NDEA respectively, at a concentration as low as 1 mg/l and increased in a dose-dependent manner. Taken together, this LC-MS/MS assay provides the sensitivity and high throughput required to evaluate the extent of alkylated DNA lesions in small animal models of cancer induced by alkylating agents. PMID:17134374

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.

Dietary butyrylated high-amylose starch reduces azoxymethane-induced colonic O(6)-methylguanine adducts in rats as measured by immunohistochemistry and high-pressure liquid chromatography.

PubMed

Le Leu, Richard K; Scherer, Benjamin L; Mano, Mark T; Winter, Jean M; Lannagan, Tamsin; Head, Richard J; Lockett, Trevor; Clarke, Julie M

2016-09-01

O(6)-methyl guanine (O(6)MeG) adducts are major toxic, promutagenic, and procarcinogenic adducts involved in colorectal carcinogenesis. Resistant starch and its colonic metabolite butyrate are known to protect against oncogenesis in the colon. In this study, we hypothesized that a dietary intervention that specifically delivers butyrate to the large bowel (notably butyrylated high-amylose maize starch [HAMSB]) would reduce colonic levels of O(6)MeG in rats shortly after exposure to the deoxyribonucleic acid (DNA) alkylating agent azoxymethane (AOM) when compared with a low-amylose maize starch (LAMS). A further objective was to validate an immunohistochemistry (IHC) method for quantifying O(6)MeG against a high-performance liquid chromatography method using fluorescence and diode array detection. Rats were fed either LAMS or HAMSB diets for 4 weeks followed by a single injection of AOM or saline and killed 6 hours later. After AOM exposure, both IHC and high-performance liquid chromatography method using fluorescence and diode array detection measured a substantially increased quantity of DNA adducts in the colon (P<.001). Both techniques demonstrated equally that consumption of HAMSB provided a protective effect by reducing colonic adduct load compared with the LAMS diet (P<.05). In addition, IHC allowed visualization of the O(6)MeG distribution, where adduct load was reduced in the lower third of the crypt compartment in HAMSB-fed rats (P=.036). The apoptotic response to AOM was higher in the HAMSB-fed rats (P=.002). In conclusion, the reduction in O(6)MeG levels and enhancement of the apoptotic response to DNA damage in the colonic epithelium through consumption of HAMSB provide mechanistic insights into how HAMSB protects against colorectal tumorigenesis. Copyright © 2016 Elsevier Inc. All rights reserved.

SPIKE – a database, visualization and analysis tool of cellular signaling pathways

PubMed Central

Elkon, Ran; Vesterman, Rita; Amit, Nira; Ulitsky, Igor; Zohar, Idan; Weisz, Mali; Mass, Gilad; Orlev, Nir; Sternberg, Giora; Blekhman, Ran; Assa, Jackie; Shiloh, Yosef; Shamir, Ron

2008-01-01

Background Biological signaling pathways that govern cellular physiology form an intricate web of tightly regulated interlocking processes. Data on these regulatory networks are accumulating at an unprecedented pace. The assimilation, visualization and interpretation of these data have become a major challenge in biological research, and once met, will greatly boost our ability to understand cell functioning on a systems level. Results To cope with this challenge, we are developing the SPIKE knowledge-base of signaling pathways. SPIKE contains three main software components: 1) A database (DB) of biological signaling pathways. Carefully curated information from the literature and data from large public sources constitute distinct tiers of the DB. 2) A visualization package that allows interactive graphic representations of regulatory interactions stored in the DB and superposition of functional genomic and proteomic data on the maps. 3) An algorithmic inference engine that analyzes the networks for novel functional interplays between network components. SPIKE is designed and implemented as a community tool and therefore provides a user-friendly interface that allows registered users to upload data to SPIKE DB. Our vision is that the DB will be populated by a distributed and highly collaborative effort undertaken by multiple groups in the research community, where each group contributes data in its field of expertise. Conclusion The integrated capabilities of SPIKE make it a powerful platform for the analysis of signaling networks and the integration of knowledge on such networks with omics data. PMID:18289391

Efficient Training of Supervised Spiking Neural Network via Accurate Synaptic-Efficiency Adjustment Method.

PubMed

Xie, Xiurui; Qu, Hong; Yi, Zhang; Kurths, Jurgen

2017-06-01

The spiking neural network (SNN) is the third generation of neural networks and performs remarkably well in cognitive tasks, such as pattern recognition. The temporal neural encode mechanism found in biological hippocampus enables SNN to possess more powerful computation capability than networks with other encoding schemes. However, this temporal encoding approach requires neurons to process information serially on time, which reduces learning efficiency significantly. To keep the powerful computation capability of the temporal encoding mechanism and to overcome its low efficiency in the training of SNNs, a new training algorithm, the accurate synaptic-efficiency adjustment method is proposed in this paper. Inspired by the selective attention mechanism of the primate visual system, our algorithm selects only the target spike time as attention areas, and ignores voltage states of the untarget ones, resulting in a significant reduction of training time. Besides, our algorithm employs a cost function based on the voltage difference between the potential of the output neuron and the firing threshold of the SNN, instead of the traditional precise firing time distance. A normalized spike-timing-dependent-plasticity learning window is applied to assigning this error to different synapses for instructing their training. Comprehensive simulations are conducted to investigate the learning properties of our algorithm, with input neurons emitting both single spike and multiple spikes. Simulation results indicate that our algorithm possesses higher learning performance than the existing other methods and achieves the state-of-the-art efficiency in the training of SNN.

Stimulus encoding and feature extraction by multiple sensory neurons.

PubMed

Krahe, Rüdiger; Kreiman, Gabriel; Gabbiani, Fabrizio; Koch, Christof; Metzner, Walter

2002-03-15

Neighboring cells in topographical sensory maps may transmit similar information to the next higher level of processing. How information transmission by groups of nearby neurons compares with the performance of single cells is a very important question for understanding the functioning of the nervous system. To tackle this problem, we quantified stimulus-encoding and feature extraction performance by pairs of simultaneously recorded electrosensory pyramidal cells in the hindbrain of weakly electric fish. These cells constitute the output neurons of the first central nervous stage of electrosensory processing. Using random amplitude modulations (RAMs) of a mimic of the fish's own electric field within behaviorally relevant frequency bands, we found that pyramidal cells with overlapping receptive fields exhibit strong stimulus-induced correlations. To quantify the encoding of the RAM time course, we estimated the stimuli from simultaneously recorded spike trains and found significant improvements over single spike trains. The quality of stimulus reconstruction, however, was still inferior to the one measured for single primary sensory afferents. In an analysis of feature extraction, we found that spikes of pyramidal cell pairs coinciding within a time window of a few milliseconds performed significantly better at detecting upstrokes and downstrokes of the stimulus compared with isolated spikes and even spike bursts of single cells. Coincident spikes can thus be considered "distributed bursts." Our results suggest that stimulus encoding by primary sensory afferents is transformed into feature extraction at the next processing stage. There, stimulus-induced coincident activity can improve the extraction of behaviorally relevant features from the stimulus.

The emergence of polychronization and feature binding in a spiking neural network model of the primate ventral visual system.

PubMed

Eguchi, Akihiro; Isbister, James B; Ahmad, Nasir; Stringer, Simon

2018-07-01

We present a hierarchical neural network model, in which subpopulations of neurons develop fixed and regularly repeating temporal chains of spikes (polychronization), which respond specifically to randomized Poisson spike trains representing the input training images. The performance is improved by including top-down and lateral synaptic connections, as well as introducing multiple synaptic contacts between each pair of pre- and postsynaptic neurons, with different synaptic contacts having different axonal delays. Spike-timing-dependent plasticity thus allows the model to select the most effective axonal transmission delay between neurons. Furthermore, neurons representing the binding relationship between low-level and high-level visual features emerge through visually guided learning. This begins to provide a way forward to solving the classic feature binding problem in visual neuroscience and leads to a new hypothesis concerning how information about visual features at every spatial scale may be projected upward through successive neuronal layers. We name this hypothetical upward projection of information the "holographic principle." (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Functional joint regeneration is achieved using reintegration mechanism in Xenopus laevis

PubMed Central

Yamada, Shigehito

2016-01-01

Abstract A functional joint requires integration of multiple tissues: the apposing skeletal elements should form an interlocking structure, and muscles should insert into skeletal tissues via tendons across the joint. Whereas newts can regenerate functional joints after amputation, Xenopus laevis regenerates a cartilaginous rod without joints, a “spike.” Previously we reported that the reintegration mechanism between the remaining and regenerated tissues has a significant effect on regenerating joint morphogenesis during elbow joint regeneration in newt. Based on this insight into the importance of reintegration, we amputated frogs’ limbs at the elbow joint and found that frogs could regenerate a functional elbow joint between the remaining tissues and regenerated spike. During regeneration, the regenerating cartilage was partially connected to the remaining articular cartilage to reform the interlocking structure of the elbow joint at the proximal end of the spike. Furthermore, the muscles of the remaining part inserted into the regenerated spike cartilage via tendons. This study might open up an avenue for analyzing molecular and cellular mechanisms of joint regeneration using Xenopus. PMID:27499877

Modeling somatic and dendritic spike mediated plasticity at the single neuron and network level.

PubMed

Bono, Jacopo; Clopath, Claudia

2017-09-26

Synaptic plasticity is thought to be the principal neuronal mechanism underlying learning. Models of plastic networks typically combine point neurons with spike-timing-dependent plasticity (STDP) as the learning rule. However, a point neuron does not capture the local non-linear processing of synaptic inputs allowed for by dendrites. Furthermore, experimental evidence suggests that STDP is not the only learning rule available to neurons. By implementing biophysically realistic neuron models, we study how dendrites enable multiple synaptic plasticity mechanisms to coexist in a single cell. In these models, we compare the conditions for STDP and for synaptic strengthening by local dendritic spikes. We also explore how the connectivity between two cells is affected by these plasticity rules and by different synaptic distributions. Finally, we show that how memory retention during associative learning can be prolonged in networks of neurons by including dendrites.Synaptic plasticity is the neuronal mechanism underlying learning. Here the authors construct biophysical models of pyramidal neurons that reproduce observed plasticity gradients along the dendrite and show that dendritic spike dependent LTP which is predominant in distal sections can prolong memory retention.

Feature extraction using first and second derivative extrema (FSDE) for real-time and hardware-efficient spike sorting.

PubMed

Paraskevopoulou, Sivylla E; Barsakcioglu, Deren Y; Saberi, Mohammed R; Eftekhar, Amir; Constandinou, Timothy G

2013-04-30

Next generation neural interfaces aspire to achieve real-time multi-channel systems by integrating spike sorting on chip to overcome limitations in communication channel capacity. The feasibility of this approach relies on developing highly efficient algorithms for feature extraction and clustering with the potential of low-power hardware implementation. We are proposing a feature extraction method, not requiring any calibration, based on first and second derivative features of the spike waveform. The accuracy and computational complexity of the proposed method are quantified and compared against commonly used feature extraction methods, through simulation across four datasets (with different single units) at multiple noise levels (ranging from 5 to 20% of the signal amplitude). The average classification error is shown to be below 7% with a computational complexity of 2N-3, where N is the number of sample points of each spike. Overall, this method presents a good trade-off between accuracy and computational complexity and is thus particularly well-suited for hardware-efficient implementation. Copyright © 2013 Elsevier B.V. All rights reserved.

Simultaneous determination of creatinine and creatine in human serum by double-spike isotope dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-mass spectrometry (GC-MS).

PubMed

Fernández-Fernández, Mario; Rodríguez-González, Pablo; Añón Álvarez, M Elena; Rodríguez, Felix; Menéndez, Francisco V Álvarez; García Alonso, J Ignacio

2015-04-07

This work describes the first multiple spiking isotope dilution procedure for organic compounds using (13)C labeling. A double-spiking isotope dilution method capable of correcting and quantifying the creatine-creatinine interconversion occurring during the analytical determination of both compounds in human serum is presented. The determination of serum creatinine may be affected by the interconversion between creatine and creatinine during sample preparation or by inefficient chemical separation of those compounds by solid phase extraction (SPE). The methodology is based on the use differently labeled (13)C analogues ((13)C1-creatinine and (13)C2-creatine), the measurement of the isotopic distribution of creatine and creatinine by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and the application of multiple linear regression. Five different lyophilized serum-based controls and two certified human serum reference materials (ERM-DA252a and ERM-DA253a) were analyzed to evaluate the accuracy and precision of the proposed double-spike LC-MS/MS method. The methodology was applied to study the creatine-creatinine interconversion during LC-MS/MS and gas chromatography-mass spectrometry (GC-MS) analyses and the separation efficiency of the SPE step required in the traditional gas chromatography-isotope dilution mass spectrometry (GC-IDMS) reference methods employed for the determination of serum creatinine. The analysis of real serum samples by GC-MS showed that creatine-creatinine separation by SPE can be a nonquantitative step that may induce creatinine overestimations up to 28% in samples containing high amounts of creatine. Also, a detectable conversion of creatine into creatinine was observed during sample preparation for LC-MS/MS. The developed double-spike LC-MS/MS improves the current state of the art for the determination of creatinine in human serum by isotope dilution mass spectrometry (IDMS), because corrections are made for all the possible errors derived from the sample preparation step.

Task-Dependent Changes in Cross-Level Coupling between Single Neurons and Oscillatory Activity in Multiscale Networks

PubMed Central

Canolty, Ryan T.; Ganguly, Karunesh; Carmena, Jose M.

2012-01-01

Understanding the principles governing the dynamic coordination of functional brain networks remains an important unmet goal within neuroscience. How do distributed ensembles of neurons transiently coordinate their activity across a variety of spatial and temporal scales? While a complete mechanistic account of this process remains elusive, evidence suggests that neuronal oscillations may play a key role in this process, with different rhythms influencing both local computation and long-range communication. To investigate this question, we recorded multiple single unit and local field potential (LFP) activity from microelectrode arrays implanted bilaterally in macaque motor areas. Monkeys performed a delayed center-out reach task either manually using their natural arm (Manual Control, MC) or under direct neural control through a brain-machine interface (Brain Control, BC). In accord with prior work, we found that the spiking activity of individual neurons is coupled to multiple aspects of the ongoing motor beta rhythm (10–45 Hz) during both MC and BC, with neurons exhibiting a diversity of coupling preferences. However, here we show that for identified single neurons, this beta-to-rate mapping can change in a reversible and task-dependent way. For example, as beta power increases, a given neuron may increase spiking during MC but decrease spiking during BC, or exhibit a reversible shift in the preferred phase of firing. The within-task stability of coupling, combined with the reversible cross-task changes in coupling, suggest that task-dependent changes in the beta-to-rate mapping play a role in the transient functional reorganization of neural ensembles. We characterize the range of task-dependent changes in the mapping from beta amplitude, phase, and inter-hemispheric phase differences to the spike rates of an ensemble of simultaneously-recorded neurons, and discuss the potential implications that dynamic remapping from oscillatory activity to spike rate and timing may hold for models of computation and communication in distributed functional brain networks. PMID:23284276

Secondary treatment of films of colloidal quantum dots for optoelectronics and devices produced thereby

DOEpatents

Semonin, Octavi Escala; Luther, Joseph M; Beard, Matthew C; Chen, Hsiang-Yu

2014-04-01

A method of forming an optoelectronic device. The method includes providing a deposition surface and contacting the deposition surface with a ligand exchange chemical and contacting the deposition surface with a quantum dot (QD) colloid. This initial process is repeated over one or more cycles to form an initial QD film on the deposition surface. The method further includes subsequently contacting the QD film with a secondary treatment chemical and optionally contacting the surface with additional QDs to form an enhanced QD layer exhibiting multiple exciton generation (MEG) upon absorption of high energy photons by the QD active layer. Devices having an enhanced QD active layer as described above are also disclosed.

Semiconductor quantum dot-sensitized solar cells.

PubMed

Tian, Jianjun; Cao, Guozhong

2013-10-31

Semiconductor quantum dots (QDs) have been drawing great attention recently as a material for solar energy conversion due to their versatile optical and electrical properties. The QD-sensitized solar cell (QDSC) is one of the burgeoning semiconductor QD solar cells that shows promising developments for the next generation of solar cells. This article focuses on recent developments in QDSCs, including 1) the effect of quantum confinement on QDSCs, 2) the multiple exciton generation (MEG) of QDs, 3) fabrication methods of QDs, and 4) nanocrystalline photoelectrodes for solar cells. We also make suggestions for future research on QDSCs. Although the efficiency of QDSCs is still low, we think there will be major breakthroughs in developing QDSCs in the future.

Experiences of CNES and SEP on space mechanisms rotating at low speed

NASA Technical Reports Server (NTRS)

Atlas, G.; Thomin, G.

1987-01-01

Some aspects of knowledge acquired in the field of space mechanisms by Societe Europeenne de Propulsion and Centre National d'Etudes Spatiales in International and French National space programs are described. The experience described centers on the development of these programs: The MEGS (Mechanisme d'Etrainement du Generateur Solaire), and the MOGS (Mechanisme d'Orientation de Generateur Solaire), both solar array drive mechanisms. Key design areas and the mechanism performance obtained are highlighted. Some test problems with the MEGS sliprings are discussed.

Evaluating the Aging of Multiple Emulsions Using Resonance-Enhanced Multiphoton Ionization Time-of-Flight Mass Spectrometry.

PubMed

Tsuda, Yukihiro; Uchimura, Tomohiro

2016-01-01

Resonance-enhanced multiphoton ionization time-of-flight mass spectrometry was applied to measurements of multiple emulsions with no pretreatment; a method for the quantitative evaluation of aging was proposed. We prepared water-in-oil-in-water (W/O/W) multiple emulsions containing toluene and m-phenylenediamine. The samples were measured immediately following both preparation and after having been stirred for 24 h. Time profiles of the peak areas for each analyte species were obtained, and several intense spikes for toluene could be detected from each sample after stirring, which suggests that the concentration of toluene in the middle phase had increased during stirring. On the other hand, in the case of a W/O/W multiple emulsion containing phenol and m-phenylenediamine, spikes for m-phenylenediamine, rather than phenol, were detected after stirring. In the present study, the time-profile data were converted into a scatter plot in order to quantitatively evaluate the aging. As a result, the ratio of the plots where strong signal intensities of toluene were detected increased from 8.4% before stirring to 33.2% after stirring for 24 h. The present method could be a powerful tool for evaluating multiple emulsions, such as studies on the kinetics of the encapsulation and release of active ingredients.

A compound memristive synapse model for statistical learning through STDP in spiking neural networks

PubMed Central

Bill, Johannes; Legenstein, Robert

2014-01-01

Memristors have recently emerged as promising circuit elements to mimic the function of biological synapses in neuromorphic computing. The fabrication of reliable nanoscale memristive synapses, that feature continuous conductance changes based on the timing of pre- and postsynaptic spikes, has however turned out to be challenging. In this article, we propose an alternative approach, the compound memristive synapse, that circumvents this problem by the use of memristors with binary memristive states. A compound memristive synapse employs multiple bistable memristors in parallel to jointly form one synapse, thereby providing a spectrum of synaptic efficacies. We investigate the computational implications of synaptic plasticity in the compound synapse by integrating the recently observed phenomenon of stochastic filament formation into an abstract model of stochastic switching. Using this abstract model, we first show how standard pulsing schemes give rise to spike-timing dependent plasticity (STDP) with a stabilizing weight dependence in compound synapses. In a next step, we study unsupervised learning with compound synapses in networks of spiking neurons organized in a winner-take-all architecture. Our theoretical analysis reveals that compound-synapse STDP implements generalized Expectation-Maximization in the spiking network. Specifically, the emergent synapse configuration represents the most salient features of the input distribution in a Mixture-of-Gaussians generative model. Furthermore, the network's spike response to spiking input streams approximates a well-defined Bayesian posterior distribution. We show in computer simulations how such networks learn to represent high-dimensional distributions over images of handwritten digits with high fidelity even in presence of substantial device variations and under severe noise conditions. Therefore, the compound memristive synapse may provide a synaptic design principle for future neuromorphic architectures. PMID:25565943

A Neuromorphic Architecture for Object Recognition and Motion Anticipation Using Burst-STDP

PubMed Central

Balduzzi, David; Tononi, Giulio

2012-01-01

In this work we investigate the possibilities offered by a minimal framework of artificial spiking neurons to be deployed in silico. Here we introduce a hierarchical network architecture of spiking neurons which learns to recognize moving objects in a visual environment and determine the correct motor output for each object. These tasks are learned through both supervised and unsupervised spike timing dependent plasticity (STDP). STDP is responsible for the strengthening (or weakening) of synapses in relation to pre- and post-synaptic spike times and has been described as a Hebbian paradigm taking place both in vitro and in vivo. We utilize a variation of STDP learning, called burst-STDP, which is based on the notion that, since spikes are expensive in terms of energy consumption, then strong bursting activity carries more information than single (sparse) spikes. Furthermore, this learning algorithm takes advantage of homeostatic renormalization, which has been hypothesized to promote memory consolidation during NREM sleep. Using this learning rule, we design a spiking neural network architecture capable of object recognition, motion detection, attention towards important objects, and motor control outputs. We demonstrate the abilities of our design in a simple environment with distractor objects, multiple objects moving concurrently, and in the presence of noise. Most importantly, we show how this neural network is capable of performing these tasks using a simple leaky-integrate-and-fire (LIF) neuron model with binary synapses, making it fully compatible with state-of-the-art digital neuromorphic hardware designs. As such, the building blocks and learning rules presented in this paper appear promising for scalable fully neuromorphic systems to be implemented in hardware chips. PMID:22615855

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

PubMed

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

2017-10-01

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

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

PubMed Central

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

2014-01-01

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