Relevant bibliographies by topics / EEG/MEG data

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'EEG/MEG data'

Author: Grafiati
Published: 7 December 2024

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Journal articles on the topic "EEG/MEG data"

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Litvak, Vladimir, Jérémie Mattout, Stefan Kiebel, et al. "EEG and MEG Data Analysis in SPM8." Computational Intelligence and Neuroscience 2011 (2011): 1–32. http://dx.doi.org/10.1155/2011/852961.

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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 analys
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Gramfort, Alexandre, Martin Luessi, Eric Larson, et al. "MNE software for processing MEG and EEG data." NeuroImage 86 (February 2014): 446–60. http://dx.doi.org/10.1016/j.neuroimage.2013.10.027.

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Hong, J., and S. C. Jun. "Single-trial Analysis for MEG/EEG spatiotemporal data." NeuroImage 47 (July 2009): S145. http://dx.doi.org/10.1016/s1053-8119(09)71470-3.

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Maris, Eric, and Robert Oostenveld. "Nonparametric statistical testing of EEG- and MEG-data." Journal of Neuroscience Methods 164, no. 1 (2007): 177–90. http://dx.doi.org/10.1016/j.jneumeth.2007.03.024.

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Gjini, Klevest, Susan M. Bowyer, Frank Wang, and Nash N. Boutros. "Deficit Versus Nondeficit Schizophrenia: An MEG-EEG Investigation of Resting State and Source Coherence—Preliminary Data." Clinical EEG and Neuroscience 51, no. 1 (2019): 34–44. http://dx.doi.org/10.1177/1550059419867561.

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This study investigated the magneto- and electroencephalography (MEG and EEG, respectively) resting state to identify the deviations closely associated with the deficit syndrome (DS) in schizophrenia patients. Ten subjects in each group (control, DS, and nondeficit schizophrenia [NDS]) were included. Subjects underwent MEG-EEG recordings during a resting state condition. MEG coherence source imaging (CSI) in source space and spectral analysis in sensor space were performed. Significant differences were found between the 2 patient groups: (1) MEG and EEG spectral analysis showed significantly h
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Zhang, Junpeng, Sarang S. Dalal, Srikantan S. Nagarajan, and Dezhong Yao. "COHERENT MEG/EEG SOURCE LOCALIZATION IN TRANSFORMED DATA SPACE." Biomedical Engineering: Applications, Basis and Communications 22, no. 05 (2010): 351–65. http://dx.doi.org/10.4015/s1016237210002110.

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In some cases, different brain regions give rise to strongly-coherent electrical neural activities. For example, pure tone evoked activations of the bilateral auditory cortices exhibit strong coherence. Conventional 2nd order statistics-based spatio-temporal algorithms, such as MUSIC (MUltiple SIgnal Classification) and beamforming encounter difficulties in localizing such activities. In this paper, we proposed a novel solution for this case. The key idea is to map the measurement data into a new data space through a transformation prior to the localization. The orthogonal complement of the le
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Jas, Mainak, Denis A. Engemann, Yousra Bekhti, Federico Raimondo, and Alexandre Gramfort. "Autoreject: Automated artifact rejection for MEG and EEG data." NeuroImage 159 (October 2017): 417–29. http://dx.doi.org/10.1016/j.neuroimage.2017.06.030.

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Trujillo-Barreto, N. J., E. Martínez-Montes, P. A. Valdés-Sosa, and L. Melie-García. "Bayesian model for EEG/MEG and fMRI data fusion." NeuroImage 13, no. 6 (2001): 270. http://dx.doi.org/10.1016/s1053-8119(01)91613-1.

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Roś, Beata P., Fetsje Bijma, Mathisca C. M. de Gunst, and Jan C. de Munck. "A three domain covariance framework for EEG/MEG data." NeuroImage 119 (October 2015): 305–15. http://dx.doi.org/10.1016/j.neuroimage.2015.06.020.

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Kozinska, D., F. Carducci, and K. Nowinski. "Automatic alignment of EEG/MEG and MRI data sets." Clinical Neurophysiology 112, no. 8 (2001): 1553–61. http://dx.doi.org/10.1016/s1388-2457(01)00556-9.

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Dissertations / Theses on the topic "EEG/MEG data"

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Zaremba, Wojciech. "Modeling the variability of EEG/MEG data through statistical machine learning." Habilitation à diriger des recherches, Ecole Polytechnique X, 2012. http://tel.archives-ouvertes.fr/tel-00803958.

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Brain neural activity generates electrical discharges, which manifest as electrical and magnetic potentials around the scalp. Those potentials can be registered with magnetoencephalography (MEG) and electroencephalography (EEG) devices. Data acquired by M/EEG is extremely difficult to work with due to the inherent complexity of underlying brain processes and low signal-to-noise ratio (SNR). Machine learning techniques have to be employed in order to reveal the underlying structure of the signal and to understand the brain state. This thesis explores a diverse range of machine learning techniqu
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Molins, Jiménez Antonio. "Multimodal integration of EEG and MEG data using minimum ℓ₂-norm estimates". Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40528.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.<br>Includes bibliographical references (leaves 69-74).<br>The aim of this thesis was to study the effects of multimodal integration of electroencephalography (EEG) and magnetoencephalography (MEG) data on the minimum ℓ₂-norm estimates of cortical current densities. We investigated analytically the effect of including EEG recordings in MEG studies versus the addition of new MEG channels. To further confirm these results, clinical datasets comprising concurrent MEG/EEG acquisitions w
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Papadopoulo, Théodore. "Contributions and perspectives to computer vision, image processing and EEG/MEG data analysis." Habilitation à diriger des recherches, Université Nice Sophia Antipolis, 2011. http://tel.archives-ouvertes.fr/tel-00847782.

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Dans une première partie, j'illustrerai quelques uns de mes travaux en visio n par ordinateur et traitement d'images. Ceux-ci portent notamment sur la géométrie multi-vues, l'utilisation du raisonnement géométrique pour intégrer des contraintes sur la scène, l'appariement et la segmentation d'images. Sans forcément rentrer dans les détails, j'exposerai les idées fondamentales qui sous-tendent ces travaux qui ont maintenant quelques années et proposerai quelques perspectives sur des extensions possibles. Une deuxième partie abordera certains problèmes liés à l'électro- et la magnéto-encéphalogr
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Zavala, Fernandez Heriberto. "Evaluation and comparsion of the independent components of simultaneously measured MEG and EEG data /." Berlin : Univ.-Verl. der TU, 2009. http://www.ub.tu-berlin.de/index.php?id=2260#c9917.

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Ablin, Pierre. "Exploration of multivariate EEG /MEG signals using non-stationary models." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLT051.

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L'Analyse en Composantes Indépendantes (ACI) modèle un ensemble de signaux comme une combinaison linéaire de sources indépendantes. Cette méthode joue un rôle clé dans le traitement des signaux de magnétoencéphalographie (MEG) et électroencéphalographie (EEG). L'ACI de tels signaux permet d'isoler des sources de cerveau intéressantes, de les localiser, et de les séparer d'artefacts. L'ACI fait partie de la boite à outils de nombreux neuroscientifiques, et est utilisée dans de nombreux articles de recherche en neurosciences. Cependant, les algorithmes d'ACI les plus utilisés ont été développés
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Abbasi, Omid [Verfasser], Georg [Gutachter] Schmitz, and Markus [Gutachter] Butz. "Retrieving neurophysiological information from strongly distorted EEG and MEG data / Omid Abbasi ; Gutachter: Georg Schmitz, Markus Butz." Bochum : Ruhr-Universität Bochum, 2017. http://d-nb.info/1140223119/34.

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Dubarry, Anne-Sophie. "Linking neurophysiological data to cognitive functions : methodological developments and applications." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM5017.

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Un des enjeux majeurs de la Psychologie Cognitive est de décrire les grandes fonctions mentales, notamment chez l’humain. Du point de vue neuroscientifique, il s’agit de modéliser l’activité cérébrale pour en extraire les éléments et mécanismes spatio-temporels susceptibles d’être mis en correspondance avec les opérations cognitives. Le travail de cette thèse a consisté à définir et mettre en œuvre des stratégies originales permettant de confronter les modèles cognitifs existants à des données issues d’enregistrements neurophysiologiques chez l’humain. Dans une première étude nous avons démont
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Ewald, Arne Verfasser], Klaus-Robert [Akademischer Betreuer] [Müller, Andreas [Akademischer Betreuer] Daffertshofer, and Guido [Akademischer Betreuer] Nolte. "Novel multivariate data analysis techniques to determine functionally connected networks within the brain from EEG or MEG data / Arne Ewald. Gutachter: Klaus-Robert Müller ; Andreas Daffertshofer ; Guido Nolte." Berlin : Technische Universität Berlin, 2014. http://d-nb.info/1067387773/34.

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Ewald, Arne [Verfasser], Klaus-Robert [Akademischer Betreuer] Müller, Andreas [Akademischer Betreuer] Daffertshofer, and Guido [Akademischer Betreuer] Nolte. "Novel multivariate data analysis techniques to determine functionally connected networks within the brain from EEG or MEG data / Arne Ewald. Gutachter: Klaus-Robert Müller ; Andreas Daffertshofer ; Guido Nolte." Berlin : Technische Universität Berlin, 2014. http://d-nb.info/1067387773/34.

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Carrara, Igor. "Méthodes avancées de traitement des BCI-EEG pour améliorer la performance et la reproductibilité de la classification." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4033.

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L'électroencéphalographie (EEG) mesure de manière non invasive l'activité électrique du cerveau par le biais de champs électromagnétiques générés par l'activité synchronisée de millions de neurones. Cela permet de collecter des données temporelles multivariées qui constituent une trace de l'activité électrique du cerveau mesurée au niveau du cuir chevelu. À tout instant, les mesures enregistrées par ces capteurs sont des combinaisons linéaires des activités électriques provenant d'un ensemble de sources sous-jacentes situées dans le cortex cérébral. Ces sources interagissent entre elles selon
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Books on the topic "EEG/MEG data"

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Giebels, Ludy. Jacob Israël de Haan in het Palestijnse labyrint, 1919-1924. Amsterdam University Press, 2024. http://dx.doi.org/10.5117/9789048563838.

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Jacob Israël de Haan was romanschrijver, dichter en jurist. In Nederland was hij bekend als schrijver van Pijpelijntjes (1904), een roman waarin openlijk homoseksualiteit werd beschreven. Hij bekeerde zich tot het zionisme en emigreerde in 1919 naar Palestina als correspondent voor het Algemeen Handelsblad. Zijn feuilletons schetsen een levendig beeld van de politieke situatie en het leven van alledag in het nieuwe Joods Nationaal Tehuis, dat zich dankzij de Balfour Declaratie in Palestina ontwikkelde. In Jeruzalem sloot hij zich echter al snel aan bij de anti- zionistische ultraorthodoxe geme
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Hari, MD, PhD, Riitta, and Aina Puce, PhD. MEG-EEG Primer. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190497774.001.0001.

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This book provides newcomers and more experienced researchers with the very basics of magnetoencephalography (MEG) and electroencephalography (EEG)—two noninvasive methods that can inform about the neurodynamics of the human brain on a millisecond scale. These two closely related methods are addressed side by side, starting from their physical and physiological bases and then advancing to methods of data acquisition, analysis, visualization, and interpretation. Special attention is paid to careful experimentation, guiding the readers to differentiate brain signals from various biological and n
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Hamalainen, Matti, Risto Ilmoniemi, and Lauri Parkkonen. Fundamentals of MEG and EEG: Biophysics, Instrumentation, and Data Analysis. Elsevier Science & Technology Books, 2020.

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Butkov, Nic. Polysomnography. Edited by Sudhansu Chokroverty, Luigi Ferini-Strambi, and Christopher Kennard. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199682003.003.0007.

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This chapter provides an overview of the sleep recording process, including the application of electrodes and sensors to the patient, instrumentation, signal processing, digital polysomnography (PSG), and artifact recognition. Topics discussed include indications for PSG, standard recording parameters, patient preparation, electrode placement for recording the electroencephalogram (EEG), electrooculogram (EOG), electromyogram (EMG), and electrocardiogram (ECG), the use of respiratory transducers, oximetry, signal processing, filters, digital data display, electrical safety, and patient monitor
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Kam, Julia W. Y., and Todd C. Handy. Electroencephalogram Recording in Humans. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199939800.003.0006.

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This chapter provides an elementary introduction to the theory and practical application of electroencephalogram (EEG) recording for the purpose of studying neurocognitive processes. It is aimed at readers who have had little or no experience in EEG data collection, and would like to gain a better understanding of scientific papers employing this methodology or start their own EEG experiment. We begin with a definition of EEG, and a summary of the strengths and limitations of EEG-based techniques. Following this is a description of the basic theory concerning the cellular mechanisms underlying
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Sutter, Raoul, Peter W. Kaplan, and Donald L. Schomer. Historical Aspects of Electroencephalography. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0001.

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Electroencephalography (EEG), a dynamic real-time recording of electrical neocortical brain activity, began in the 1600s with the discovery of electrical phenomena and the concept of an “action current.” The galvanometer was introduced in the 1800s and the first bioelectrical observations of human brain signals were made in the 1900s. Certain EEG patterns were associated with brain disorders, increasing the clinical and scientific use of EEG. In the 1980s, technical advances allowed EEGs to be digitized and linked with videotape recording. In the 1990s, digital data storage increased and compu
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Thomas, James, and Tanya Monaghan. Clinical data interpretation. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780199593972.003.0019.

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Vanhatalo, Sampsa, and J. Matias Palva. Infraslow EEG Activity. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0032.

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Infraslow electroencephalographic (EEG) activity refers to frequencies below the conventional clinical EEG range that starts at about 0.5 Hz. Evidence suggests that salient EEG signals in the infraslow range are essential parts of many physiological and pathological conditions. In addition, brain is known to exhibit multitude of infraslow processes, which may be observed directly as fluctuations in the EEG signal amplitude, as infraslow fluctuations or intermittency in other neurophysiological signals, or as fluctuations in behavioural performance. Both physiological and pathological EEG activ
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Osman, Gamaleldin M., James J. Riviello, and Lawrence J. Hirsch. EEG in the Intensive Care Unit. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0022.

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The field of continuous electroencephalographic monitoring (cEEG) in the intensive care unit has dramatically expanded over the past two decades. Expansion of cEEG programs led to recognition of the frequent occurrence of electrographic seizures, and complex rhythmic and periodic patterns in various critically ill populations. The majority of electrographic seizures are of nonconvulsive nature, hence the need for cEEG for their identification. Guidelines on when and how to perform cEEG and standardized nomenclature for description of rhythmic and periodic patterns are now available. Quantitati
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Vespa, Paul M. Electroencephalogram monitoring in the critically ill. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0221.

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Electroencephalography monitoring provides a method for monitoring brain function, which can complement other forms of monitoring, such as monitoring of intracranial pressure and derived parameters, such as cerebral perfusion pressure. Continuous electroencephalogram (EEG) monitoring can be helpful in seizure detection after brain injury and coma. Seizures can be detected by visual inspection of the raw EEG and/or processed EEG data. Treatment of status epilepticus can be improved by rapid identification and abolition of seizures using continuous EEG. Quantitative EEG can also be used to detec
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Book chapters on the topic "EEG/MEG data"

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Iversen, John R., and Scott Makeig. "MEG/EEG Data Analysis Using EEGLAB." In Magnetoencephalography. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-62657-4_8-1.

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Iversen, John R., and Scott Makeig. "MEG/EEG Data Analysis Using EEGLAB." In Magnetoencephalography. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-33045-2_8.

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Iversen, John R., and Scott Makeig. "MEG/EEG Data Analysis Using EEGLAB." In Magnetoencephalography. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00087-5_8.

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Sorrentino, Alberto, and Michele Piana. "Inverse Modeling for MEG/EEG Data." In Mathematical and Theoretical Neuroscience. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-68297-6_15.

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Sellers, Kristin K., Joline M. Fan, Leighton B. N. Hinkley, and Heidi E. Kirsch. "Preprocessing Electrophysiological Data: EEG, iEEG, and MEG Data." In Statistical Methods in Epilepsy. Chapman and Hall/CRC, 2024. http://dx.doi.org/10.1201/9781003254515-2.

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Pflieger, M. E., G. V. Simpson, S. P. Ahlfors, and R. J. Ilmoniemi. "Superadditive Information from Simultaneous MEG/EEG Data." In Biomag 96. Springer New York, 2000. http://dx.doi.org/10.1007/978-1-4612-1260-7_282.

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Pitolli, Francesca. "Neuroelectric Current Localization from Combined EEG/MEG Data." In Curves and Surfaces. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27413-8_37.

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Louis, Alfred K., Uwe Schmitt, Felix Darvas, Helmut Büchner, and Manfred Fuchs. "Spatio-Temporal Current Density Reconstruction from EEG-/MEG-Data." In Mathematics — Key Technology for the Future. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-642-55753-8_38.

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Esch, Lorenz, Christoph Dinh, Eric Larson, et al. "MNE: Software for Acquiring, Processing,and Visualizing MEG/EEG Data." In Magnetoencephalography. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-62657-4_59-1.

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Esch, Lorenz, Christoph Dinh, Eric Larson, et al. "MNE: Software for Acquiring, Processing, and Visualizing MEG/EEG Data." In Magnetoencephalography. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-00087-5_59.

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Conference papers on the topic "EEG/MEG data"

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Vlasenko, Daniil, Alexey Zaikin, and Denis Zakharov. "Ensemble methods for representation of fMRI, EEG/MEG data in graph form for classification of brain states." In 2024 8th Scientific School Dynamics of Complex Networks and their Applications (DCNA). IEEE, 2024. http://dx.doi.org/10.1109/dcna63495.2024.10718443.

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Cai, Chang, Mithun Diwakar, Kensuke Sekihara, and Srikantan S. Nagarajan. "Robust Bayesian algorithm for distributed source reconstructions MEG/EEG data." In 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2019. http://dx.doi.org/10.1109/ner.2019.8716990.

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Gramfort, Alexandre, and Maureen Clerc. "Low Dimensional Representations of MEG/EEG Data Using Laplacian Eigenmaps." In 2007 Joint Meeting of the 6th International Symposium on Noninvasive Functional Source Imaging of the Brain and Heart and the International Conference on Functional Biomedical Imaging. IEEE, 2007. http://dx.doi.org/10.1109/nfsi-icfbi.2007.4387717.

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NOLTE, G. "DETECTING AND LOCALIZING TRUE BRAIN INTERACTIONS FROM EEG/MEG DATA." In Proceedings of the Seventh International Workshop. WORLD SCIENTIFIC, 2006. http://dx.doi.org/10.1142/9789812773197_0036.

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Ardila Franco, Camilo Ernesto, Jose David Lopez Hincapie, and Jairo Jose Espinosa. "Neural activity reconstruction with MEG/EEG data considering noise regularization." In 2012 XVII Symposium of Image, Signal Processing, and Artificial Vision (STSIVA). IEEE, 2012. http://dx.doi.org/10.1109/stsiva.2012.6340551.

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Huang, Gan, and Zhiguo Zhang. "Improving sensitivity of cluster-based permutation test for EEG/MEG data." In 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER). IEEE, 2017. http://dx.doi.org/10.1109/ner.2017.8008279.

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Lopez, Jose David, Angela Sucerquia, and Gareth Barnes. "Simultaneous estimation of brain structure and function with MEG/EEG data." In 2017 International Conference on Innovations in Electrical Engineering and Computational Technologies (ICIEECT). IEEE, 2017. http://dx.doi.org/10.1109/icieect.2017.7916582.

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Belaoucha, Brahim, and Theodore Papadopoulo. "Large brain effective network from EEG/MEG data and dMR information." In 2017 International Workshop on Pattern Recognition in Neuroimaging (PRNI). IEEE, 2017. http://dx.doi.org/10.1109/prni.2017.7981511.

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Gutiérrez, David, Gerardo Herrera Corral, and Luis Manuel Montaño Zentina. "Using EEG∕MEG Data of Cognitive Processes in Brain-Computer Interfaces." In MEDICAL PHYSICS: Tenth Mexican Symposium on Medical Physics. AIP, 2008. http://dx.doi.org/10.1063/1.2979300.

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Jia, Wenyan, Robert J. Sclabassi, Lin-Sen Pon, Mark L. Scheuer, and Mingui Sun. "Spike Separation from EEG/MEG Data Using Morphological Filter and Wavelet Transform." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.259695.

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Reports on the topic "EEG/MEG data"

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Mosher, J. C., M. Huang, R. M. Leahy, and M. E. Spencer. Modeling versus accuracy in EEG and MEG data. Office of Scientific and Technical Information (OSTI), 1997. http://dx.doi.org/10.2172/554813.

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Van der Maas, Peter, Jesse Wagenaar, Ilse Ubels, and Anne Helbig. Circulair water in de wijk : verkennend onderzoek naar de potenties en belemmering van decentrale systemen voor behandeling en hergebruik van afvalwater en regenwater in woonwijken. Hogeschool van Hall Larenstein, 2024. http://dx.doi.org/10.31715/2024.6.

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In Nederland en omringende landen zijn in de afgelopen jaren en decennia verschillende projecten gerealiseerd rond decentrale innovatieve concepten voor afvalwaterbehandeling en gebruik van re-genwater. Om gemeenten, waterschappen en andere belanghebbenden een rationele grondslag te bieden voor keuzes m.b.t. de inrichting van de stedelijke waterketen (wel of niet decentraal, wel of niet brongescheiden), is in dit KIEM project de potentie en beperkingen onderzocht van nieuwe en circulaire sanitatieconcepten, zoals brongescheiden sanitatie en lokaal (her)gebruik van regenwater op woonwijk schaal
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3

Agrawal, Asha Weinstein, Evelyn Blumenberg, Anastasia Loukaitou-Sideris, and Brittney Lu. Understanding Workforce Diversity in the Transit Industry: Establishing a Baseline of Diversity Demographics. Mineta Transportation Institute, 2024. http://dx.doi.org/10.31979/mti.2024.2213.

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This study provides baseline data on the status of the racial/ethnic and gender diversity of the transit agency workforce in the U.S. and identifies potential barriers and promising practices for diversifying this workforce. Public transit agencies function best when the diversity of their workforce represents the communities they serve, yet previous research finds an underrepresentation of women and minorities in senior and managerial roles, along with an overconcentration of men and workers of color—particularly Black workers—in operational roles (e.g., drivers, janitors). The study updates
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4

Guérin, Laurence, Patrick Sins, Lida Klaver, and Juliette Walma van der Molen. Onderzoeksrapport Samen werken aan Bèta Burgerschap. Saxion, 2021. http://dx.doi.org/10.14261/ff0c6282-93e2-41a7-b60ab9bceb2a4328.

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In het TechYourfuture project ‘Samen werken aan Bèta Burgerschap’, dat plaats vond in de periode maart 2015 - maart 2020, gaven de onderzoekers samen met scholen en bedrijven concreet invulling aan burgerschapsonderwijs. De maatschappij en maatschappelijke vraagstukken worden steeds complexer. Politieke, technologische, economische, sociaal-culturele of ecologische aspecten van een vraagstuk zijn met elkaar verweven. Daarnaast spelen ook globale en lokale dimensies een rol. Er zijn alleen hierdoor al meerdere antwoorden mogelijk op een vraagstuk. Gedurende het project hebben basisschoolleerlin
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5

Blankestijn, Wouter, Walter Verspui, Jan Fliervoet, and Loes Witteveen. Motivaties rondom Tuinvergroening onderzoek Tuinverhalen : resultaten enquête onder deelnemers van het project Pientere Tuinen. Lectoraat Communicatie, Participatie & Sociaal-Ecologisch Leren (CoPSEL), 2024. http://dx.doi.org/10.31715/2024.3.

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In dit rapport worden de resultaten gepresenteerd van de enquête die in december 2023 is uitgezet bij de deelnemers van Pientere Tuinen, een participatief en burgerwetenschappelijk project met als doel meer Nederlandse tuinen te vergroenen. Deze enquête is onderdeel van het onderzoek Tuinverhalen dat in samenwerking met Pientere Tuinen wordt uitgevoerd door het lectoraat Communicatie, Participatie en Sociaal-Ecologisch Leren (CoPSEL) bij Hogeschool Van Hall Larenstein. Binnen dit onderzoek worden de motivaties en belemmeringen die tuineigenaren ervaren om veranderingen op het gebied van vergro
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6

Strietman, W. J., M. J. van den Heuvel-Greve, A. M. van den Brink, et al. Resultaten bronanalyse zwerfafval Griend : Resultaten van een gedetailleerde bronanalyse van zwerfafval dat op het Waddeneiland Griend verzameld is en samen met lokale stakeholders tijdens een Litter-ID-sessie in oktober 2019 onderzocht is. Wageningen Economic Research, 2020. http://dx.doi.org/10.18174/528599.

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7

Nelson, Gena. A Systematic Review of the Quality of Reporting in Mathematics Meta-Analyses for Students with or at Risk of Disabilities Coding Protocol. Boise State University, 2021. http://dx.doi.org/10.18122/sped138.boisestate.

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The purpose of this document is to provide readers with the coding protocol that authors used to code 22 meta-analyses focused on mathematics interventions for students with or at-risk of disabilities. The purpose of the systematic review was to evaluate reporting quality in meta-analyses focused on mathematics interventions for students with or at risk of disabilities. To identify meta-analyses for inclusion, we considered peer-reviewed literature published between 2000 and 2020; we searched five education-focused electronic databases, scanned the table of contents of six special education jo
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Nelson, Gena. A Systematic Review of the Quality of Reporting in Mathematics Meta-Analyses for Students with or at Risk of Disabilities Coding Protocol. Boise State University, Albertsons Library, 2021. http://dx.doi.org/10.18122/sped.138.boisestate.

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The purpose of this document is to provide readers with the coding protocol that authors used to code 22 meta-analyses focused on mathematics interventions for students with or at-risk of disabilities. The purpose of the systematic review was to evaluate reporting quality in meta-analyses focused on mathematics interventions for students with or at risk of disabilities. To identify meta-analyses for inclusion, we considered peer-reviewed literature published between 2000 and 2020; we searched five education-focused electronic databases, scanned the table of contents of six special education jo
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9

Rupke, Andrew, and Taylor Boden. Lithium Brine Analytical Database of Utah: Second Edition. Utah Geological Survey, 2023. http://dx.doi.org/10.34191/ofr-758.

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The accompanying database is a compilation of analytical data from brine or water samples in Utah that includes lithium concentrations. The data were collected from published and unpublished sources. This second edition is an update that includes data from the first edition (Rupke and Boden, 2020) and adds additional records. We also added some minor detail to previous records, particularly in relation to how units (e.g., ppm or mg/L) were recorded in source documents. Our intent is to continue to add additional analyses to this database as time allows and more data are discovered or become av
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Sloan, Steven, Shelby Peterie, Richard Miller, Julian Ivanov, J. Schwenk, and Jason McKenna. Detecting clandestine tunnels by using near-surface seismic techniques. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40419.

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Geophysical detection of clandestine tunnels is a complex problem that has been met with limited success. Multiple methods have been applied spanning several decades, but a reliable solution has yet to be found. This report presents shallow seismic data collected at a tunnel test site representative of geologic settings found along the southwestern U.S. border. Results demonstrate the capability of using compressional wave diffraction and surface-wave backscatter techniques to detect a purpose-built subterranean tunnel. Near-surface seismic data were also collected at multiple sites in Afghani
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