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152. Benchmarking for On-Scalp MEG Sensors

Author

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

Published
2017
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157. Academic Software Toolboxes for the Analysis of MEG Data

Author

Baillet, Sylvain, Leahy, Richard, Tadel, François, Mosher, John, Delorme, Arnaud, Makeig, Scott, Oostenveld, Robert, Hämäläinen, Matti, Dalal, Sarang, Zumer, J., Clerc, Maureen, Wolters, Carsten, Kiebel, Stefan, Jensen, Ole, Department of Neurology [Milwaukee], Medical College of Wisconsin, University of South California (USC), Neuroimaging group, Cleveland Clinic, Centre de recherche cerveau et cognition (CERCO), Institut des sciences du cerveau de Toulouse. (ISCT), Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Swartz Center for Computational Neuroscience, University of California [San Diego] (UC San Diego), University of California-University of California, Donders Institute for Brain, Cognition and Behaviour, Radboud university [Nijmegen], Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS), Dynamique Cérébrale et Cognition, Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM), School of Physics and Astronomy [Nottingham], University of Nottingham, UK (UON), Computational Imaging of the Central Nervous System (ATHENA), Inria Sophia Antipolis - Méditerranée (CRISAM), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institute for Biomagnetism and Biosignal Analysis, Westfälische Wilhelms-Universität Münster (WWU), Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Max-Planck-Gesellschaft, S. Supek, Supek, Selma and Susac, Ana, University of Southern California (USC), Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Université de Toulouse (UT)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Toulouse - Jean Jaurès (UT2J), Université de Toulouse (UT)-Centre Hospitalier Universitaire de Toulouse (CHU Toulouse)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), University of California (UC)-University of California (UC), Radboud University [Nijmegen], Harvard Medical School [Boston] (HMS)-Massachusetts General Hospital [Boston], Westfälische Wilhelms-Universität Münster = University of Münster (WWU), Clerc, Maureen, and Supek, Selma and Susac, Ana

Subjects
MEG, [SCCO.COMP] Cognitive science/Computer science, connectivity, data analysis, imaging, [SCCO.COMP]Cognitive science/Computer science, source analysis, mapping, forward modeling
Abstract

International audience; Free MEG and EEG data analysis software packages springing from academic research are now widely used in published work. These toolboxes and applications are typically developed by or in close contact with researchers addressing cognitive or clinical neuroscience questions. Thus they often contain the latest methodological developments from the research community. It is therefore vital to educate MEG researchers and make them aware of the new possibilities offered by these toolboxes. The aim of this paper is to illustrate the characteristics and advantages of the various toolboxes to users and developers alike. We present each toolbox with their key features and target audience.

Published
2010

161. Stimulus repetition modulates gamma-band synchronization in primate visual cortex

Author

McGovern Institute for Brain Research at MIT, Desimone, Robert, Brunet, Nicolas M., Bosman, Conrado A., Vinck, Martin, Roberts, Mark, Oostenveld, Robert, De Weerd, Peter, Fries, Pascal, McGovern Institute for Brain Research at MIT, Desimone, Robert, Brunet, Nicolas M., Bosman, Conrado A., Vinck, Martin, Roberts, Mark, Oostenveld, Robert, De Weerd, Peter, and Fries, Pascal

Abstract

When a sensory stimulus repeats, neuronal firing rate and functional MRI blood oxygen level-dependent responses typically decline, yet perception and behavioral performance either stay constant or improve. An additional aspect of neuronal activity is neuronal synchronization, which can enhance the impact of neurons onto their postsynaptic targets independent of neuronal firing rates. We show that stimulus repetition leads to profound changes of neuronal gamma-band (∼40–90 Hz) synchronization. Electrocorticographic recordings in two awake macaque monkeys demonstrated that repeated presentations of a visual grating stimulus resulted in a steady increase of visually induced gamma-band activity in area V1, gamma-band synchronization between areas V1 and V4, and gamma-band activity in area V4. Microelectrode recordings in area V4 of two additional monkeys under the same stimulation conditions allowed a direct comparison of firing rates and gamma-band synchronization strengths for multiunit activity (MUA), as well as for isolated single units, sorted into putative pyramidal cells and putative interneurons. MUA and putative interneurons showed repetition-related decreases in firing rate, yet increases in gamma-band synchronization. Putative pyramidal cells showed no repetition-related firing rate change, but a decrease in gamma-band synchronization for weakly stimulus-driven units and constant gamma-band synchronization for strongly driven units. We propose that the repetition-related changes in gamma-band synchronization maintain the interareal stimulus signaling and sharpen the stimulus representation by gamma-synchronized pyramidal cell spikes., Human Frontier Science Program (Strasbourg, France) (Organization Grant RGP0070/2003), Volkswagen Foundation (Grant I/79876), European Science Foundation (European Young Investigator Award Program), European Union (HEALTH-F2-2008-200728 Grant), State Offensive for Development of Scientific and Economic Excellence (program grant “Neuronale Koordination Forschungsschwerpunkt Frankfurt”), Netherlands. Ministry of Economic Affairs (Smart Mix Programme), Netherlands. Ministry of Education, Culture, and Science (BrainGain), Netherlands Organization for Scientific Research (Grant 452-03-344)

Published
2014

163. fNIRS is sensitive to leg activity in the primary motor cortex after systemic artifact correction.

Author

Cockx, Helena, Oostenveld, Robert, Tabor, Merel, Savenco, Ecaterina, van Setten, Arne, Cameron, Ian, and van Wezel, Richard

Subjects
*MOTOR cortex, *MOVEMENT sequences, *NEAR infrared spectroscopy, *HEART beat, *BLOOD pressure, *SHORT selling (Securities)
Abstract

• fNIRS can distinguish between finger and leg movements in the primary motor cortex. • Effect sizes of leg activity are smaller than effect sizes of finger activity. • Leg movements induce systemic fluctuations that should be removed by short channels. • Correlation between tasks and systemic fluctuations results in multicollinearity. • We share a fully-open dataset in BIDS format, including 3D optode positions. functional near-infrared spectroscopy (fNIRS) is an increasingly popular tool to study cortical activity during movement and gait that requires further validation. This study aimed to assess (1) whether fNIRS can detect the difficult-to-measure leg area of the primary motor cortex (M1) and distinguish it from the hand area; and (2) whether fNIRS can differentiate between automatic (i.e., not requiring one's attention) and non-automatic movement processes. Special attention was attributed to systemic artifacts (i.e., changes in blood pressure, heart rate, breathing) which were assessed and corrected by short channels, i.e., fNIRS channels which are mainly sensitive to superficial scalp hemodynamics. Twenty-three seated, healthy participants tapped four fingers on a keyboard or tapped the right foot on four squares on the floor in a specific order given by a 12-digit sequence (e.g., 434141243212). Two different sequences were executed: a beforehand learned (i.e., automatic) version and a newly learned (i.e., non-automatic) version. A 36-channel fNIRS device including 12 short channels covered multiple motor-related cortical areas including M1. The fNIRS data were analyzed with a general linear model (GLM). Correlation between the expected functional hemodynamic responses (i.e. task regressor) and the short channels (i.e. nuisance regressors), necessitated performing a separate short channel regression instead of integrating them in the GLM. Consistent with the M1 somatotopy, we found significant HbO increases of very large effect size in the lateral M1 channels during finger tapping (Cohen's d = 1.35, p <0.001) and significant HbO increases of moderate effect size in the medial M1 channels during foot tapping (Cohen's d = 0.8, p <0.05). The cortical activity differences between automatic and non-automatic tasks were not significantly different. Importantly, leg movements produced large systemic fluctuations, which were adequately removed by the use of all available short channels. Our results indicate that fNIRS is sensitive to leg activity in M1, though the sensitivity is lower than for finger activity and requires rigorous correction for systemic fluctuations. We furthermore highlight that systemic artifacts may result in an unreliable GLM analysis when short channels show signals that are similar to the expected hemodynamic responses. [ABSTRACT FROM AUTHOR]

Published
2023
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182. Entrainment for attentional selection in Parkinson's disease

Author

te Woerd, Erik S., Oostenveld, Robert, de Lange, Floris P., and Praamstra, Peter

Abstract

Neural entrainment plays a crucial role in perception and action, especially when stimuli possess a certain temporal regularity, and is also suggested to serve as a neural process to select and attend the relevant stream in situations where there are competing stimulus streams. Beneficial effects of entrainment have led to the suggestion that rhythmic stimuli can improve motor function in patients with Parkinson's disease (PD). Behavioural studies support this suggestion, but neurophysiological studies have shown reduced entrainment of motor areas in PD. However, oscillatory entrainment in PD has only been tested in paradigms with a single isochronous stimulus stream, whereas entrainment has an enhanced benefit in situations where one rhythmic stimulus stream has to be segregated from distractor stimuli. Therefore, we here used an intermodal selective attention task with concurrent auditory and visual stimulus streams while recording oscillatory brain activity with Magnetoencephalography (MEG). We aimed to (i) replicate earlier findings of deficient motor entrainment in PD patients in conditions where there is a single stimulus stream, and (ii) to evaluate whether increasing the benefit of entrainment by introducing a distractor stream would lead to entrainment in PD patients not seen otherwise. Contrary to this hypothesis, PD patients showed reduced motor entrainment compared to controls during both conditions, as indexed by beta oscillatory activity. These results suggest that entrainment in PD patients is deficient, even under conditions that encourage entrainment.

Published
2018
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183. Independent EEG sources are dipolar.

Author

Delorme, Arnaud, Delorme, Arnaud, Palmer, Jason, Onton, Julie, Oostenveld, Robert, Makeig, Scott, Delorme, Arnaud, Delorme, Arnaud, Palmer, Jason, Onton, Julie, Oostenveld, Robert, and Makeig, Scott

Abstract

Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison).

Published
2012

184. Introduction to the shared near infrared spectroscopy format.

Author

Tucker, Stephen, Dubb, Jay, Kura, Sreekanth, von Lühmann, Alexander, Franke, Robert, Horschig, Jörn M., Powell, Samuel, Oostenveld, Robert, Lührs, Michael, Delaire, Édouard, Aghajan, Zahra M., Yun, Hanseok, Yücel, Meryem A., Fang, Qianqian, Huppert, Theodore J., Frederick, Blaise B., Pollonini, Luca, Boas, David, and Luke, Robert

Published
2023
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194. EEG and MEG Data Analysis in SPM8

Author

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

Published
2011
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197. Improving EEG source analysis using prior knowledge

Author

Oostenveld, Robert and Oostenveld, Robert

Abstract

Contains fulltext : 19301_impreesoa.pdf (publisher's version ) (Open Access), The research described in this thesis covers different aspects of EEG and ERP source modeling. Both basic research in volume conduction and source modeling, as well as application of inverse source modeling techniques to experimental data are described. This thesis demonstrates how prior information can be applied in physical models that are used for source analysis of the EEG. It shows that realistic volume conduction models can be used that incorporate holes in the skull. The accurate placement of electrodes for high-density EEG measurements is described. It discusses how information on symmetry of sources in the brain can be used, and what the influence of incorrectly assumed symmetry in the sources is. The application of prior information on source locations is demonstrated in a forward modeling approach. A high-resolution EEG experiment is described to which source analysis was applied, making use of the prior information available in this experiment. In general, this thesis demonstrates that the application of source modeling can provide valuable information in EEG analysis

Published
2003

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