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Sieluzycki C, Matysiak A, Konig R, Iskander DR. Reducing the Number of MEG/EEG Trials Needed for the Estimation of Brain Evoked Responses: A Bootstrap Approach. IEEE Trans Biomed Eng 2021; 68:2301-2312. [PMID: 33606623 DOI: 10.1109/tbme.2021.3060495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
OBJECTIVE A common problem in magnetoencephalographic (MEG) and electroencephalographic (EEG) experimental paradigms relying on the estimation of brain evoked responses is the lengthy time of the experiment, which stems from the need to acquire a large number of repeated recordings. Using a bootstrap approach, we aim at reliably reducing the number of these repeated trials. METHODS To this end, we assessed five variants of non-parametric bootstrapping based on the classical signal-plus-noise model constituting the foundation of signal averaging in MEG/EEG. We explain which of these approaches should and which should not be used for the aforementioned purpose, and why. RESULTS We present results for two advocated bootstrap variants applied to auditory MEG data. The ensuing trial-averaged magnetic fields served as input to the estimation of cortical source generators, with spatio-temporal matching pursuit as an example of an inverse solution technique. We propose, for a wide range of trial numbers, a general framework to evaluate the statistical properties of the parameter estimates for source locations and related time courses. CONCLUSION The proposed bootstrap framework offers a systematic approach to reduce the number of trials required to estimate the evoked response. The general validity of our findings is neither bound to any particular type of MEG/EEG data nor to any specific source localization method. SIGNIFICANCE Practical implications of this work relate to the optimization of acquisition time of MEG/EEG experiments, thus reducing stress for the subjects (especially for patients) and minimizing related artifacts.
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Mamashli F, Hämäläinen M, Ahveninen J, Kenet T, Khan S. Permutation Statistics for Connectivity Analysis between Regions of Interest in EEG and MEG Data. Sci Rep 2019; 9:7942. [PMID: 31138854 PMCID: PMC6538606 DOI: 10.1038/s41598-019-44403-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2018] [Accepted: 05/15/2019] [Indexed: 01/01/2023] Open
Abstract
Connectivity estimates based on electroencephalography (EEG) and magnetoencephalography (MEG) are unique in their ability to provide neurophysiologically meaningful spectral and temporal information non-invasively. This multi-dimensional aspect of the MEG/EEG based connectivity increases the challenges of the analysis and interpretation of the data. Many MEG/EEG studies address this complexity by using a hypothesis-driven approach, which focuses on particular regions of interest (ROI). However, if an effect is distributed unevenly over a large ROI and variable across subjects, it may not be detectable using conventional methods. Here, we propose a novel approach, which enhances the statistical power for weak and spatially discontinuous effects. This results in the ability to identify statistically significant connectivity patterns with spectral, temporal, and spatial specificity while correcting for multiple comparisons using nonparametric permutation methods. We call this new approach the Permutation Statistics for Connectivity Analysis between ROI (PeSCAR). We demonstrate the processing steps with simulated and real human data. The open-source Matlab code implementing PeSCAR are provided online.
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Affiliation(s)
- Fahimeh Mamashli
- Department of Neurology, MGH, Harvard Medical School, Boston, MA, USA.
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Boston, MA, USA.
- Department of Radiology, MGH, Harvard Medical School, Boston, MA, USA.
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Boston, MA, USA
- Department of Radiology, MGH, Harvard Medical School, Boston, MA, USA
| | - Jyrki Ahveninen
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Boston, MA, USA
- Department of Radiology, MGH, Harvard Medical School, Boston, MA, USA
| | - Tal Kenet
- Department of Neurology, MGH, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Boston, MA, USA
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, MGH/HST, Boston, MA, USA.
- Department of Radiology, MGH, Harvard Medical School, Boston, MA, USA.
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
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Phase shift invariant imaging of coherent sources (PSIICOS) from MEG data. Neuroimage 2018; 183:950-971. [DOI: 10.1016/j.neuroimage.2018.08.031] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2018] [Revised: 07/25/2018] [Accepted: 08/15/2018] [Indexed: 12/17/2022] Open
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Sun L, Hämäläinen MS, Okada Y. Noise cancellation for a whole-head magnetometer-based MEG system in hospital environment. Biomed Phys Eng Express 2018; 4. [PMID: 30174830 DOI: 10.1088/2057-1976/aad627] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
We describe a strategy of removing magnetic field interference for a whole-head pediatric magnetoencephalography (MEG) system ("babyMEG") installed in a hospital. The 375-channel sensor array of babyMEG consists entirely of magnetometers in two layers to maximize the sensitivity for detecting MEG signals from infants, toddlers, and young children. It is equipped with a continuously operating closed-cycle helium recycler to reduce the operating costs. These two features pose special challenges for noise cancellation. Our strategy uses a combination of several methods. The system is installed in a light-weight, magnetically shielded room (MSR) equipped with an active external shielding. In addition we employ two software-based techniques - a signal space projection (SSP) technique and a synthetic gradiometer (SG) method - for removing the environmental magnetic noise in real time and displaying the output online. The shielding effects are: passive shielding - 36 dB, active shielding - 12 dB, SSP - 40 dB and SG - 40 dB, for a combined maximum shielding of about 90 dB at 0.1 Hz. We evaluated the performance of the babyMEG after applying the noise cancellation techniques. The dipole localization errors were <3 mm after averaging 50 epochs with empty room noise in a simulation study for dipoles >10 nAm, which is in the low range of empirically observed dipole moments. In a phantom study with realistic environmental noise, we could clearly recover an evoked cortical magnetic field produced by a 20 nAm dipole after averaging 50 epochs. The localization error was ~6 mm after averaging 20 epochs. In infants, we could clearly detect a somatic evoked field after averaging ~20 responses. The unique two-layer sensor design combined with the SSP or SG provides effective noise suppression for a magnetometer-based pediatric MEG system in hospital environment with the closed-cycle helium recycler operating continuously during MEG measurements.
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Affiliation(s)
- Limin Sun
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts 02115, USA.,Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Matti S Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Massachusetts 02129, USA.,Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Yoshio Okada
- Division of Newborn Medicine, Department of Medicine, Boston Children's Hospital, Boston, Massachusetts 02115, USA.,Harvard Medical School, Boston, Massachusetts 02115, USA
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Kalogianni K, de Munck JC, Nolte G, Vardy AN, van der Helm FC, Daffertshofer A. Spatial resolution for EEG source reconstruction—A simulation study on SEPs. J Neurosci Methods 2018; 301:9-17. [DOI: 10.1016/j.jneumeth.2018.02.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2017] [Revised: 01/22/2018] [Accepted: 02/24/2018] [Indexed: 11/28/2022]
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Disentangling Somatosensory Evoked Potentials of the Fingers: Limitations and Clinical Potential. Brain Topogr 2018; 31:498-512. [PMID: 29353446 PMCID: PMC5889784 DOI: 10.1007/s10548-017-0617-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2017] [Accepted: 12/30/2017] [Indexed: 12/21/2022]
Abstract
In searching for clinical biomarkers of the somatosensory function, we studied reproducibility of somatosensory potentials (SEP) evoked by finger stimulation in healthy subjects. SEPs induced by electrical stimulation and especially after median nerve stimulation is a method widely used in the literature. It is unclear, however, if the EEG recordings after finger stimulation are reproducible within the same subject. We tested in five healthy subjects the consistency and reproducibility of responses through bootstrapping as well as test–retest recordings. We further evaluated the possibility to discriminate activity of different fingers both at electrode and at source level. The lack of consistency and reproducibility suggest responses to finger stimulation to be unreliable, even with reasonably high signal-to-noise ratio and adequate number of trials. At sources level, somatotopic arrangement of the fingers representation was only found in one of the subjects. Although finding distinct locations of the different fingers activation was possible, our protocol did not allow for non-overlapping dipole representations of the fingers. We conclude that despite its theoretical advantages, we cannot recommend the use of somatosensory potentials evoked by finger stimulation to extract clinical biomarkers.
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Kuttikat A, Noreika V, Shenker N, Chennu S, Bekinschtein T, Brown CA. Neurocognitive and Neuroplastic Mechanisms of Novel Clinical Signs in CRPS. Front Hum Neurosci 2016; 10:16. [PMID: 26858626 PMCID: PMC4728301 DOI: 10.3389/fnhum.2016.00016] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2015] [Accepted: 01/12/2016] [Indexed: 12/16/2022] Open
Abstract
Complex regional pain syndrome (CRPS) is a chronic, debilitating pain condition that usually arises after trauma to a limb, but its precise etiology remains elusive. Novel clinical signs based on body perceptual disturbances have been reported, but their pathophysiological mechanisms remain poorly understood. Investigators have used functional neuroimaging techniques (including MEG, EEG, fMRI, and PET) to study changes mainly within the somatosensory and motor cortices. Here, we provide a focused review of the neuroimaging research findings that have generated insights into the potential neurocognitive and neuroplastic mechanisms underlying perceptual disturbances in CRPS. Neuroimaging findings, particularly with regard to somatosensory processing, have been promising but limited by a number of technique-specific factors (such as the complexity of neuroimaging investigations, poor spatial resolution of EEG/MEG, and use of modeling procedures that do not draw causal inferences) and more general factors including small samples sizes and poorly characterized patients. These factors have led to an underappreciation of the potential heterogeneity of pathophysiology that may underlie variable clinical presentation in CRPS. Also, until now, neurological deficits have been predominantly investigated separately from perceptual and cognitive disturbances. Here, we highlight the need to identify neurocognitive phenotypes of patients with CRPS that are underpinned by causal explanations for perceptual disturbances. We suggest that a combination of larger cohorts, patient phenotyping, the use of both high temporal, and spatial resolution neuroimaging methods, and the identification of simplified biomarkers is likely to be the most fruitful approach to identifying neurocognitive phenotypes in CRPS. Based on our review, we explain how such phenotypes could be characterized in terms of hierarchical models of perception and corresponding disturbances in recurrent processing involving the somatosensory, salience and executive brain networks. We also draw attention to complementary neurological factors that may explain some CRPS symptoms, including the possibility of central neuroinflammation and neuronal atrophy, and how these phenomena may overlap but be partially separable from neurocognitive deficits.
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Affiliation(s)
- Anoop Kuttikat
- Department of Rheumatology, Addenbrooke's Hospital , Cambridge , UK
| | - Valdas Noreika
- Cognition and Brain Sciences Unit, Medical Research Council , Cambridge , UK
| | - Nicholas Shenker
- Department of Rheumatology, Addenbrooke's Hospital , Cambridge , UK
| | - Srivas Chennu
- Cognition and Brain Sciences Unit, Medical Research Council, Cambridge, UK; Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Tristan Bekinschtein
- Cognition and Brain Sciences Unit, Medical Research Council, Cambridge, UK; Department of Psychology, University of Cambridge, Cambridge, UK
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Kozunov VV, Ossadtchi A. GALA: group analysis leads to accuracy, a novel approach for solving the inverse problem in exploratory analysis of group MEG recordings. Front Neurosci 2015; 9:107. [PMID: 25954141 PMCID: PMC4404950 DOI: 10.3389/fnins.2015.00107] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2015] [Accepted: 03/12/2015] [Indexed: 11/13/2022] Open
Abstract
Although MEG/EEG signals are highly variable between subjects, they allow characterizing systematic changes of cortical activity in both space and time. Traditionally a two-step procedure is used. The first step is a transition from sensor to source space by the means of solving an ill-posed inverse problem for each subject individually. The second is mapping of cortical regions consistently active across subjects. In practice the first step often leads to a set of active cortical regions whose location and timecourses display a great amount of interindividual variability hindering the subsequent group analysis. We propose Group Analysis Leads to Accuracy (GALA)-a solution that combines the two steps into one. GALA takes advantage of individual variations of cortical geometry and sensor locations. It exploits the ensuing variability in electromagnetic forward model as a source of additional information. We assume that for different subjects functionally identical cortical regions are located in close proximity and partially overlap and their timecourses are correlated. This relaxed similarity constraint on the inverse solution can be expressed within a probabilistic framework, allowing for an iterative algorithm solving the inverse problem jointly for all subjects. A systematic simulation study showed that GALA, as compared with the standard min-norm approach, improves accuracy of true activity recovery, when accuracy is assessed both in terms of spatial proximity of the estimated and true activations and correct specification of spatial extent of the activated regions. This improvement obtained without using any noise normalization techniques for both solutions, preserved for a wide range of between-subject variations in both spatial and temporal features of regional activation. The corresponding activation timecourses exhibit significantly higher similarity across subjects. Similar results were obtained for a real MEG dataset of face-specific evoked responses.
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Affiliation(s)
- Vladimir V Kozunov
- MEG Centre, Moscow State University of Psychology and Education Moscow, Russia
| | - Alexei Ossadtchi
- Centre for Cognition and Decision Making, National Research University Higher School of Economics Moscow, Russia ; Laboratory of Control of Complex Systems, Institute of Problems of Mechanical Engineering Russian Academy of Sciences St. Petersburg, Russia
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Chang A, Chen CC, Li HH, Li CSR. Perigenual anterior cingulate event-related potential precedes stop signal errors. Neuroimage 2015; 111:179-85. [PMID: 25700955 DOI: 10.1016/j.neuroimage.2015.02.017] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2014] [Revised: 02/02/2015] [Accepted: 02/09/2015] [Indexed: 10/24/2022] Open
Abstract
Momentary lapses in attention disrupt goal-directed behavior. Attentional lapse has been associated with increased "default-mode" network (DMN) activity. In our previous fMRI study of a stop signal task (SST), greater activation of the perigenual anterior cingulate cortex (pgACC) - an important node of the DMN - predicts stop signal errors. In event-related potential (ERP) studies, the amplitude of an error-preceding positivity (EPP) also predicts response error. However, it is not clear whether the EPP originates from DMN regions. Here, we combined high-density array EEG and an SST to examine response-locked ERPs of error preceding trials in twenty young adult participants. The results showed an EPP in go trials that preceded stop error than stop success trials. Importantly, source modeling identified the origin of the EPP in the pgACC. By employing a bootstrapping procedure, we further confirmed that pgACC rather than the dorsal ACC as the source provides a better fit to the EPP. Together, these results suggest that attentional lapse in association with EPP in the pgACC anticipates failure in response inhibition.
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Affiliation(s)
- Andrew Chang
- Department of Psychology, National Taiwan University, Taipei 106, Taiwan
| | - Chien-Chung Chen
- Department of Psychology, National Taiwan University, Taipei 106, Taiwan; Center for Neurobiology and Cognitive Science, National Taiwan University, Taipei 106, Taiwan.
| | - Hsin-Hung Li
- Department of Psychology, National Taiwan University, Taipei 106, Taiwan
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University, New Haven, CT 06511, USA; Department of Neurobiology, Yale University, New Haven, CT 06511, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06511, USA.
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Ross B, Jamali S, Tremblay KL. Plasticity in neuromagnetic cortical responses suggests enhanced auditory object representation. BMC Neurosci 2013; 14:151. [PMID: 24314010 PMCID: PMC3924184 DOI: 10.1186/1471-2202-14-151] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2013] [Accepted: 11/27/2013] [Indexed: 11/20/2022] Open
Abstract
Background Auditory perceptual learning persistently modifies neural networks in the central nervous system. Central auditory processing comprises a hierarchy of sound analysis and integration, which transforms an acoustical signal into a meaningful object for perception. Based on latencies and source locations of auditory evoked responses, we investigated which stage of central processing undergoes neuroplastic changes when gaining auditory experience during passive listening and active perceptual training. Young healthy volunteers participated in a five-day training program to identify two pre-voiced versions of the stop-consonant syllable ‘ba’, which is an unusual speech sound to English listeners. Magnetoencephalographic (MEG) brain responses were recorded during two pre-training and one post-training sessions. Underlying cortical sources were localized, and the temporal dynamics of auditory evoked responses were analyzed. Results After both passive listening and active training, the amplitude of the P2m wave with latency of 200 ms increased considerably. By this latency, the integration of stimulus features into an auditory object for further conscious perception is considered to be complete. Therefore the P2m changes were discussed in the light of auditory object representation. Moreover, P2m sources were localized in anterior auditory association cortex, which is part of the antero-ventral pathway for object identification. The amplitude of the earlier N1m wave, which is related to processing of sensory information, did not change over the time course of the study. Conclusion The P2m amplitude increase and its persistence over time constitute a neuroplastic change. The P2m gain likely reflects enhanced object representation after stimulus experience and training, which enables listeners to improve their ability for scrutinizing fine differences in pre-voicing time. Different trajectories of brain and behaviour changes suggest that the preceding effect of a P2m increase relates to brain processes, which are necessary precursors of perceptual learning. Cautious discussion is required when interpreting the finding of a P2 amplitude increase between recordings before and after training and learning.
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Affiliation(s)
- Bernhard Ross
- Rotman Research Institute, Baycrest Centre, 3560 Bathurst Street, Toronto M6A 2E1, ON, Canada.
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Kuchenbuch A, Paraskevopoulos E, Herholz SC, Pantev C. Effects of musical training and event probabilities on encoding of complex tone patterns. BMC Neurosci 2013; 14:51. [PMID: 23617597 PMCID: PMC3639196 DOI: 10.1186/1471-2202-14-51] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2012] [Accepted: 04/20/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The human auditory cortex automatically encodes acoustic input from the environment and differentiates regular sound patterns from deviant ones in order to identify important, irregular events. The Mismatch Negativity (MMN) response is a neuronal marker for the detection of sounds that are unexpected, based on the encoded regularities. It is also elicited by violations of more complex regularities and musical expertise has been shown to have an effect on the processing of complex regularities. Using magnetoencephalography (MEG), we investigated the MMN response to salient or less salient deviants by varying the standard probability (70%, 50% and 35%) of a pattern oddball paradigm. To study the effects of musical expertise in the encoding of the patterns, we compared the responses of a group of non-musicians to those of musicians. RESULTS We observed significant MMN in all conditions, including the least salient condition (35% standards), in response to violations of the predominant tone pattern for both groups. The amplitude of MMN from the right hemisphere was influenced by the standard probability. This effect was modulated by long-term musical training: standard probability changes influenced MMN amplitude in the group of non-musicians only. CONCLUSION This study indicates that pattern violations are detected automatically, even if they are of very low salience, both in non-musicians and musicians, with salience having a stronger impact on processing in the right hemisphere of non-musicians. Long-term musical training influences this encoding, in that non-musicians benefit to a greater extent from a good signal-to-noise ratio (i.e. high probability of the standard pattern), while musicians are less dependent on the salience of an acoustic environment.
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Affiliation(s)
- Anja Kuchenbuch
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
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Somatotopic finger mapping using MEG: toward an optimal stimulation paradigm. Clin Neurophysiol 2013; 124:1659-70. [PMID: 23518470 DOI: 10.1016/j.clinph.2013.01.027] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2012] [Revised: 12/19/2012] [Accepted: 01/15/2013] [Indexed: 11/21/2022]
Abstract
OBJECTIVE In non-invasive somatotopic mapping based on neuromagnetic source analysis, the recording time can be shortened and accuracy improved by applying simultaneously vibrotactile stimuli at different frequencies to multiple body sites and recording multiple steady-state responses. This study compared the reliability of sensory evoked responses, source localization performance, and reproducibility of digit maps for three different stimulation paradigms. METHODS Vibrotactile stimuli were applied to the fingertip and neuromagnetic steady-state responses were recorded. Index and middle fingers were stimulated either sequentially in separate blocks, simultaneously at different frequencies, or in alternating temporal order within a block. RESULTS Response amplitudes were largest and source localization was most accurate between 21 and 23 Hz. Separation of adjacent digits was significant for all paradigms in all participants. Suppressive interactions occurred between simultaneously applied stimuli. However, when frequently alternating between stimulus sites, the higher stimulus novelty resulted in increased amplitudes and superior localization performance. CONCLUSIONS When receptive fields are strongly overlapping, the alternating stimulation is preferable over recording multiple steady state responses. SIGNIFICANCE The new paradigm improved the measurement of the distance of somatotopic finger representation in human primary somatosensory cortex, which is an important metric for neuroplastic reorganization after learning and rehabilitation training.
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Gross J, Baillet S, Barnes GR, Henson RN, Hillebrand A, Jensen O, Jerbi K, Litvak V, Maess B, Oostenveld R, Parkkonen L, Taylor JR, van Wassenhove V, Wibral M, Schoffelen JM. Good practice for conducting and reporting MEG research. Neuroimage 2013; 65:349-63. [PMID: 23046981 PMCID: PMC3925794 DOI: 10.1016/j.neuroimage.2012.10.001] [Citation(s) in RCA: 432] [Impact Index Per Article: 39.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2012] [Revised: 08/23/2012] [Accepted: 10/01/2012] [Indexed: 11/20/2022] Open
Abstract
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.
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Affiliation(s)
- Joachim Gross
- Centre for Cognitive Neuroimaging, University of Glasgow, Glasgow, UK.
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Jamali S, Ross B. Precise mapping of the somatotopic hand area using neuromagnetic steady-state responses. Brain Res 2012; 1455:28-39. [PMID: 22507747 DOI: 10.1016/j.brainres.2012.02.038] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2011] [Revised: 02/14/2012] [Accepted: 02/14/2012] [Indexed: 12/01/2022]
Abstract
The body surface is represented in somatotopically organized maps in the primary somatosensory cortex. Estimating the size of the hand area with neuromagnetic source analysis has been used as a metric for monitoring neuroplastic changes related to training, learning, and brain injury. Commonly, results were significant as group statistics only because source localization accuracy was limited by factors such as residual noise and head motion. In this study we aimed to develop a robust method for obtaining the somatotopic map of the hand area in individuals using the bootstrap framework. Furthermore, a comprehensive analysis of the different factors affecting the accuracy of the obtained maps was provided. We applied vibrotactile touch stimuli to the tip of the index finger or the ring finger of the right hand and recorded the 22-Hz steady-state response using MEG. Single equivalent dipole sources were localized in contralateral left somatosensory cortex. Bootstrap resampling revealed the confidence intervals for the source coordinates using a single block of 5 min MEG recording. Residual noise in the averaged evoked response predominantly affected source localization, and the related confidence interval was reciprocally related to the signal-to-noise ratio. Apparently, head movements within a block of MEG recording contributed less to the variability of source localization in cooperative volunteers. The results of the current study indicate that significant separations of index finger and ring finger representations along the somatotopic map can be revealed in an individual using bootstrap framework.
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Affiliation(s)
- Shahab Jamali
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada.
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Kuchenbuch A, Paraskevopoulos E, Herholz SC, Pantev C. Electromagnetic correlates of musical expertise in processing of tone patterns. PLoS One 2012; 7:e30171. [PMID: 22279568 PMCID: PMC3261169 DOI: 10.1371/journal.pone.0030171] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2011] [Accepted: 12/13/2011] [Indexed: 11/18/2022] Open
Abstract
Using magnetoencephalography (MEG), we investigated the influence of long term musical training on the processing of partly imagined tone patterns (imagery condition) compared to the same perceived patterns (perceptual condition). The magnetic counterpart of the mismatch negativity (MMNm) was recorded and compared between musicians and non-musicians in order to assess the effect of musical training on the detection of deviants to tone patterns. The results indicated a clear MMNm in the perceptual condition as well as in a simple pitch oddball (control) condition in both groups. However, there was no significant mismatch response in either group in the imagery condition despite above chance behavioral performance in the task of detecting deviant tones. The latency and the laterality of the MMNm in the perceptual condition differed significantly between groups, with an earlier MMNm in musicians, especially in the left hemisphere. In contrast the MMNm amplitudes did not differ significantly between groups. The behavioral results revealed a clear effect of long-term musical training in both experimental conditions. The obtained results represent new evidence that the processing of tone patterns is faster and more strongly lateralized in musically trained subjects, which is consistent with other findings in different paradigms of enhanced auditory neural system functioning due to long-term musical training.
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Affiliation(s)
- Anja Kuchenbuch
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | | | - Sibylle C. Herholz
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Christo Pantev
- Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
- * E-mail:
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Realignment of magnetoencephalographic data for group analysis in the sensor domain. J Clin Neurophysiol 2011; 28:190-201. [PMID: 21399522 DOI: 10.1097/wnp.0b013e3182121843] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Magnetoencephalography (MEG) is a neuroimaging modality with high temporal resolution for studying functional brain processes in relatively small neural assemblies on the time scale of <100 milliseconds and with synchrony and coherence in the recorded signals at high frequencies. Advanced MEG signal analysis gained importance for clinical applications, e.g., as a sensitive classifier for the diagnosis of neuropsychiatric disorders. Despite tremendous improvements in magnetic source imaging, MEG analysis often does not require explicit source estimation and can be performed in the sensor domain. However, group analysis of MEG sensor data is complicated by variable positioning of the sensor array relative to the head and needs realignment of the sensor configuration. Here, the authors provide an algorithm for transforming the magnetic field data as recorded at various sensor positions onto a common sensor array. Based on the measured magnetic field at the original sensor position, they estimate a source distribution and project it onto a virtual sensor array using the leadfield description of the magnetic forward solution. First, they analyzed the variation of sensor positioning in a typical MEG study and reported the impact on the leadfield matrix. Then they evaluated the realignment algorithm and reported its properties. Including efficient regularization to the inverse solution, they demonstrated that the introduced error is in the order of the sensor noise, and smoothing of data is limited to the set of smallest eigenvalues of the data. They demonstrated the performance of the algorithm with dipole source modeling on group averaged MEG data and comparison of grand averaged auditory evoked responses with and without sensor realignment.
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17
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Wang W, Sudre GP, Xu Y, Kass RE, Collinger JL, Degenhart AD, Bagic AI, Weber DJ. Decoding and cortical source localization for intended movement direction with MEG. J Neurophysiol 2010; 104:2451-61. [PMID: 20739599 DOI: 10.1152/jn.00239.2010] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Magnetoencephalography (MEG) enables a noninvasive interface with the brain that is potentially capable of providing movement-related information similar to that obtained using more invasive neural recording techniques. Previous studies have shown that movement direction can be decoded from multichannel MEG signals recorded in humans performing wrist movements. We studied whether this information can be extracted without overt movement of the subject, because the targeted users of brain-controlled interface (BCI) technology are those with severe motor disabilities. The objectives of this study were twofold: 1) to decode intended movement direction from MEG signals recorded during the planning period before movement onset and during imagined movement and 2) to localize cortical sources modulated by intended movement direction. Ten able-bodied subjects performed both overt and imagined wrist movement while their cortical activities were recorded using a whole head MEG system. The intended movement direction was decoded using linear discriminant analysis and a Bayesian classifier. Minimum current estimation (MCE) in combination with a bootstrapping procedure enabled source-space statistical analysis, which showed that the contralateral motor cortical area was significantly modulated by intended movement direction, and this modulation was the strongest ∼100 ms before the onset of overt movement. These results suggest that it is possible to study cortical representation of specific movement information using MEG, and such studies may aid in presurgical localization of optimal sites for implanting electrodes for BCI systems.
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Affiliation(s)
- Wei Wang
- Department of Physical Medicine and Rehabilitation, University of Pittsburgh, Pittsburgh, PA, USA
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18
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Arlot S, Blanchard G, Roquain E. Some nonasymptotic results on resampling in high dimension, II: Multiple tests. Ann Stat 2010. [DOI: 10.1214/08-aos668] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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19
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Arlot S, Blanchard G, Roquain E. Some nonasymptotic results on resampling in high dimension, I: Confidence regions. Ann Stat 2010. [DOI: 10.1214/08-aos667] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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20
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Gavaret M, Badier JM, Chauvel P. EEG haute résolution (EEG-HR) et magnétoencéphalographie (MEG). Neurochirurgie 2008; 54:185-90. [DOI: 10.1016/j.neuchi.2008.02.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2008] [Accepted: 02/13/2008] [Indexed: 11/29/2022]
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21
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Head movements of children in MEG: quantification, effects on source estimation, and compensation. Neuroimage 2008; 40:541-550. [PMID: 18252273 DOI: 10.1016/j.neuroimage.2007.12.026] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2007] [Revised: 11/29/2007] [Accepted: 12/14/2007] [Indexed: 11/22/2022] Open
Abstract
Head movements during magnetoencephalography (MEG) recordings may lead to inaccurate localization of brain activity. This can be particularly problematic for studies with children. We quantified head movements in 8- to 12-year-old children performing a cognitive task and examined how the movements affected source estimation. Each child was presented auditory word stimuli in five 4-min runs. The mean change in the MEG sensor locations during the experiment ranged from 3 to 26mm across subjects. The variation in the head position was largest in the up-down direction. The mean localization error in equivalent current dipole (ECD) simulations was 12mm for runs with the most head movement, with the frontal cortex appearing to be most prone to errors due to head movements. In addition, we examined the effect of head movements on two types of source estimates, ECDs and minimum-norm estimates (MNE), for an auditory evoked response. Application of a recently introduced signal space separation (SSS) method to compensate for the head movements was found to increase the goodness-of-fit of the ECDs, reduce the spatial confidence intervals of the ECDs, and enhance the peak amplitude in the MNE. These results are indicative of the SSS method being able to compensate for the spatial smoothing of the signals caused by head movements. Overall, the results suggest that MEG source estimates are relatively robust against head movements in children, and that confounds due to head movements can be successfully dealt with in MEG studies of developmental cognition.
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22
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Zvyagintsev M, Thönnessen H, Dammers J, Boers F, Mathiak K. An automatic procedure for the analysis of electric and magnetic mismatch negativity based on anatomical brain mapping. J Neurosci Methods 2007; 168:325-33. [PMID: 18093661 DOI: 10.1016/j.jneumeth.2007.10.025] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2007] [Revised: 10/22/2007] [Accepted: 10/24/2007] [Indexed: 10/22/2022]
Abstract
Data processing techniques in electroencephalography (EEG) and magnetoencephalography (MEG) need user interactions. However, particularly in clinical applications, fast and objective data processing is important. Here we present an observer-independent method for EEG and MEG analysis of mismatch negativity (MMN) that allows reliable estimation of source activity based on objective anatomical references. The procedure integrates several steps including artifact rejection, source estimation and statistical analysis. It enables the evaluation of source activity in a fully automatic and unsupervised manner. To test its feasibility we obtained EEG and MEG responses in an auditory oddball paradigm in 12 healthy volunteers. The automatized method of EEG and MEG data analysis estimated source activity. The automatically detected MMN was closely comparable with the results obtained by a user-controlled method based on the dipole fitting. The presented workflow can be performed easily, rapidly, and reliably. This development may open new fields in research and clinical applications of source-based EEG and MEG.
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Affiliation(s)
- Mikhail Zvyagintsev
- Department of Psychiatry and Psychotherapy, University Hospital Aachen, RWTH Aachen, 52074 Aachen, Germany.
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23
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Lajiness-O'Neill R, Akamine Y, Bowyer SM. Treatment effects of Fast ForWord demonstrated by magnetoencephalography (MEG) in a child with developmental dyslexia. Neurocase 2007; 13:390-401. [PMID: 18781438 DOI: 10.1080/13554790701851544] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Treatment effects of Fast ForWord, hypothesized to ameliorate temporal processing deficits, were demonstrated by magnetoencephalography in a child with dyslexia using four paradigms: Word/Non-word Reading (NW), Grapheme-to-Phoneme Matching (GP), Verbal, and Spatial Working Memory (VWM, SWM). Shifts in brain activation from right inferior frontal and temporal to left frontal, bilateral supramarginal, and transverse temporal regions occurred during GP. During NW, shifts progressed from (1) right or bilateral anterior and superior to (2) left, inferior frontal, to (3) left, superior posterior temporoparietal, to (4) left, inferior, posterior temporooccipital regions. Reading and written language improvements were noted in passage comprehension and spelling.
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Affiliation(s)
- R Lajiness-O'Neill
- Department of Psychology, Eastern Michigan University, Ypsilanti, MI 48197, USA.
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24
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Plis SM, George JS, Jun SC, Ranken DM, Volegov PL, Schmidt DM. Probabilistic forward model for electroencephalography source analysis. Phys Med Biol 2007; 52:5309-27. [PMID: 17762088 DOI: 10.1088/0031-9155/52/17/014] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Source localization by electroencephalography (EEG) requires an accurate model of head geometry and tissue conductivity. The estimation of source time courses from EEG or from EEG in conjunction with magnetoencephalography (MEG) requires a forward model consistent with true activity for the best outcome. Although MRI provides an excellent description of soft tissue anatomy, a high resolution model of the skull (the dominant resistive component of the head) requires CT, which is not justified for routine physiological studies. Although a number of techniques have been employed to estimate tissue conductivity, no present techniques provide the noninvasive 3D tomographic mapping of conductivity that would be desirable. We introduce a formalism for probabilistic forward modeling that allows the propagation of uncertainties in model parameters into possible errors in source localization. We consider uncertainties in the conductivity profile of the skull, but the approach is general and can be extended to other kinds of uncertainties in the forward model. We and others have previously suggested the possibility of extracting conductivity of the skull from measured electroencephalography data by simultaneously optimizing over dipole parameters and the conductivity values required by the forward model. Using Cramer-Rao bounds, we demonstrate that this approach does not improve localization results nor does it produce reliable conductivity estimates. We conclude that the conductivity of the skull has to be either accurately measured by an independent technique, or that the uncertainties in the conductivity values should be reflected in uncertainty in the source location estimates.
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Affiliation(s)
- Sergey M Plis
- MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
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25
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Cottereau B, Jerbi K, Baillet S. Multiresolution imaging of MEG cortical sources using an explicit piecewise model. Neuroimage 2007; 38:439-51. [PMID: 17889564 DOI: 10.1016/j.neuroimage.2007.07.046] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2007] [Revised: 07/06/2007] [Accepted: 07/16/2007] [Indexed: 10/23/2022] Open
Abstract
Imaging neural generators from MEG magnetic fields is often considered as a compromise between computationally-reasonable methodology that usually yields poor spatial resolution on the one hand, and more sophisticated approaches on the other hand, potentially leading to intractable computational costs. We approach the problem of obtaining well-resolved source images with unexcessive computation load with a multiresolution image model selection (MiMS) technique. The building blocks of the MiMS source model are parcels of the cortical surface which can be designed at multiple spatial resolutions with the combination of anatomical and functional priors. Computation charge is reduced owing to 1) compact parametric models of the activation of extended brain parcels using current multipole expansions and 2) the optimization of the generalized cross-validation error on image models, which is closed-form for the broad class of linear estimators of neural currents. Model selection can be complemented by any conventional imaging approach of neural currents restricted to the optimal image support obtained from MiMS. The estimation of the location and spatial extent of brain activations is discussed and evaluated using extensive Monte-Carlo simulations. An experimental evaluation was conducted with MEG data from a somatotopic paradigm. Results show that MiMS is an efficient image model selection technique with robust performances at realistic noise levels.
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Affiliation(s)
- Benoit Cottereau
- Cognitive Neuroscience and Brain Imaging Laboratory, CNRS UPR 640 LENA, University Pierre and Marie Curie-Paris 6, Hôpital de la Salpêtrière, Paris, France.
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26
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Tecchio F, Zappasodi F, Tombini M, Caulo M, Vernieri F, Rossini PM. Interhemispheric asymmetry of primary hand representation and recovery after stroke: A MEG study. Neuroimage 2007; 36:1057-64. [PMID: 17543542 DOI: 10.1016/j.neuroimage.2007.02.058] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2006] [Revised: 02/26/2007] [Accepted: 02/28/2007] [Indexed: 11/28/2022] Open
Abstract
In patients affected by monohemispheric stroke in the middle cerebral artery territory, who do not regain a normal neurological function, a positive contribution to the clinical recovery seems to be made by the involvement of primary hand representation areas in the affected hemisphere (AH), excessively asymmetric to its homologous in the unaffected hemisphere (UH). We investigated primary sensory hand areas in 41 chronic patients who had improved their clinical status without reaching complete recovery. The location and strength of the first cerebral sources activated by a contralateral galvanic median nerve stimulation (M20 and M30) were evaluated in both hemispheres, together with their interhemispheric differences. The source displacement in the AH with respect to the UH was positively correlated with clinical recovery (Spearman's rho=0.584, p=0.003). The excessive interhemispheric asymmetry - as defined on the basis of reference ranges in the healthy population - could be interpreted as the involvement of neuronal pools in the AH outside the hand 'omega zone' of the Rolandic sulcus, revealing the presence of plasticity phenomena. The present data provide support to a positive role of cerebral plasticity phenomena, partially contributing to post-stroke recovery in patients unable to achieve normal neurological function.
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Affiliation(s)
- F Tecchio
- ISTC-CNR, Unità MEG, Dip. Neuroscienze, Fatebenefratelli Hospital, 39, Isola Tiberina, 00186 Rome, Italy.
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27
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Iida T, Fenwick PBC, Ioannides AA. Analysis of brain activity immediately before conscious teeth clenching using magnetoencephalographic method. J Oral Rehabil 2007; 34:487-96. [PMID: 17559616 DOI: 10.1111/j.1365-2842.2007.01736.x] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The reasons for unconscious teeth clenching have not been clarified. The long-term goal of our project was the elucidation of processing in the brain immediately before unconscious teeth clenching, in order to clarify its significance in humans. The objective of the present study was to establish a magnetoencephalographic (MEG) method of measuring brain activity immediately before clenching, and to clarify the time-course of brain activity immediately before conscious clenching. We measured the MEG signal in six subjects before, during and after clenching in a protocol that restricted head movement <5 mm. We derived tomographic estimates of brain activity for each time slice of data, as well as time courses for regional brain activations. Analysis of the tomographic images and time courses yielded statistical maps of activity in the motor, pre-motor and somatosensory cortices immediately before clenching in all subjects. Activations were found bilaterally, but with a strong unilateral bias in most subjects. Our results demonstrate that the MEG procedures, we have introduced are capable of measuring brain activity immediately before clenching, and indicate that analysis should begin from at least 200 ms before electromyogram onset.
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Affiliation(s)
- T Iida
- Clinical Pathology, Nihon University Graduate School of Dentistry at Matsudo, Matsudo, Chiba, Japan.
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28
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Papadelis C, Ioannides AA. Localization accuracy and temporal resolution of MEG: A phantom experiment. ACTA ACUST UNITED AC 2007. [DOI: 10.1016/j.ics.2007.01.055] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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29
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Bast T, Boppel T, Rupp A, Harting I, Hoechstetter K, Fauser S, Schulze-Bonhage A, Rating D, Scherg M. Noninvasive source localization of interictal EEG spikes: effects of signal-to-noise ratio and averaging. J Clin Neurophysiol 2007; 23:487-97. [PMID: 17143137 DOI: 10.1097/01.wnp.0000232208.14060.c7] [Citation(s) in RCA: 46] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022] Open
Abstract
Source localization using single current dipoles estimates equivalent centers of the spiking gray matter. The extent of the active cortex, however, is difficult to assess from scalp EEG because of the unknown individual volume conduction. The spatial scatter of dipole localizations of single spikes has been proposed as a measure of extent. Single spike localization, however, is strongly dependent on the signal-to-noise ratio (SNR), that is, the ratio of spike and background EEG amplitudes. On the other hand, averaging of all spikes yields only the localization of equivalent centers of activity. We investigated the influence of SNR and multiple subaverages on the estimation of spatial extent by comparing the localization scatter of 100 single spikes in 27 spike types of 25 epilepsy patients with 1000 different subaverages computed by random sampling and bootstrapping. Averaging increased SNR and therefore allowed for localization not only at the spike peak but also during spike onset when less cortex is active. In several subjects with known cortical lesions, the single spike scatter considerably exceeded the lesion. Single dipole scatter was highly correlated with SNR (r = -0.83, P < 0.0001) and was greatly reduced when analyzing multiple subaverages of 10, 25, 50, and 100 spikes. Thus, we found a dominant role of the SNR on the estimated extent and improvement by scatterplots based on the dipole localization of randomly sampled subaverages.
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Affiliation(s)
- Thomas Bast
- Department of Pediatric Neurology, University Hospital Heidelberg, Germany.
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30
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Functional Imaging of Brain Activity and Connectivity with MEG. UNDERSTANDING COMPLEX SYSTEMS 2007. [DOI: 10.1007/978-3-540-71512-2_7] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
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31
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Im CH, Gururajan A, Zhang N, Chen W, He B. Spatial resolution of EEG cortical source imaging revealed by localization of retinotopic organization in human primary visual cortex. J Neurosci Methods 2006; 161:142-54. [PMID: 17098289 PMCID: PMC1851670 DOI: 10.1016/j.jneumeth.2006.10.008] [Citation(s) in RCA: 30] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2006] [Revised: 09/26/2006] [Accepted: 10/02/2006] [Indexed: 10/23/2022]
Abstract
The aim of the present study is to investigate the spatial resolution of electroencephalography (EEG) cortical source imaging by localizing the retinotopic organization in the human primary visual cortex (V1). Retinotopic characteristics in V1 obtained from functional magnetic resonance imaging (fMRI) study were used as reference to assess the spatial resolution of EEG since fMRI can discriminate small changes in activation in visual field. It is well known that the activation of the early C1 component in the visual evoked potential (VEP) elicited by pattern onset stimuli coincides well with the activation in the striate cortex localized by fMRI. In the present experiments, we moved small circular checkerboard stimuli along horizontal meridian and compared the activations localized by EEG cortical source imaging with those from fMRI. Both fMRI and EEG cortical source imaging identified spatially correlated activity within V1 in each subject studied. The mean location error, between the fMRI-determined activation centers in V1 and the EEG source imaging activation peak estimated at equivalent C1 components (peak latency: 74.8+/-10.6 ms), was 7 mm (25% and 75% percentiles are 6.45 mm and 8.4 mm, respectively), which is less than the change in fMRI activation map by a 3 degrees visual field change (7.8 mm). Moreover, the source estimates at the earliest major VEP component showed statistically good correlation with those obtained by fMRI. The present results suggest that the spatial resolution of the EEG cortical source imaging can correctly discriminate cortical activation changes in V1 corresponding to less than 3 degrees visual field changes.
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Affiliation(s)
- Chang-Hwan Im
- Department of Biomedical Engineering, University of Minnesota
| | | | - Nanyin Zhang
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota
| | - Wei Chen
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota
| | - Bin He
- Department of Biomedical Engineering, University of Minnesota
- *Corresponding author: Bin He, Ph.D., Department of Biomedical Engineering, University of Minnesota, 7-105 Hasselmo Hall, 312 Church St. S.E., Minneapolis, MN 55455, USA. Tel.: +1-612-626-1115 Fax.: +1-612-626-6583 E-mail:
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32
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Jun SC, Plis SM, Ranken DM, Schmidt DM. Spatiotemporal noise covariance estimation from limited empirical magnetoencephalographic data. Phys Med Biol 2006; 51:5549-64. [PMID: 17047269 DOI: 10.1088/0031-9155/51/21/011] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The performance of parametric magnetoencephalography (MEG) and electroencephalography (EEG) source localization approaches can be degraded by the use of poor background noise covariance estimates. In general, estimation of the noise covariance for spatiotemporal analysis is difficult mainly due to the limited noise information available. Furthermore, its estimation requires a large amount of storage and a one-time but very large (and sometimes intractable) calculation or its inverse. To overcome these difficulties, noise covariance models consisting of one pair or a sum of multi-pairs of Kronecker products of spatial covariance and temporal covariance have been proposed. However, these approaches cannot be applied when the noise information is very limited, i.e., the amount of noise information is less than the degrees of freedom of the noise covariance models. A common example of this is when only averaged noise data are available for a limited prestimulus region (typically at most a few hundred milliseconds duration). For such cases, a diagonal spatiotemporal noise covariance model consisting of sensor variances with no spatial or temporal correlation has been the common choice for spatiotemporal analysis. In this work, we propose a different noise covariance model which consists of diagonal spatial noise covariance and Toeplitz temporal noise covariance. It can easily be estimated from limited noise information, and no time-consuming optimization and data-processing are required. Thus, it can be used as an alternative choice when one-pair or multi-pair noise covariance models cannot be estimated due to lack of noise information. To verify its capability we used Bayesian inference dipole analysis and a number of simulated and empirical datasets. We compared this covariance model with other existing covariance models such as conventional diagonal covariance, one-pair and multi-pair noise covariance models, when noise information is sufficient to estimate them. We found that our proposed noise covariance model yields better localization performance than a diagonal noise covariance, while it performs slightly worse than one-pair or multi-pair noise covariance models - although these require much more noise information. Finally, we present some localization results on median nerve stimulus empirical MEG data for our proposed noise covariance model.
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Affiliation(s)
- Sung C Jun
- MS-D454, Applied Modern Physics Group, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.
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33
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Lv J, Simpson DM, Bell SL. Objective detection of evoked potentials using a bootstrap technique. Med Eng Phys 2006; 29:191-8. [PMID: 16621656 DOI: 10.1016/j.medengphy.2006.03.001] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2005] [Revised: 02/17/2006] [Accepted: 03/03/2006] [Indexed: 11/28/2022]
Abstract
Evoked potentials are usually evaluated subjectively, by visual inspection, and considerable differences between interpretations can occur. Objective, automated methods are normally based on calculating one (or more) parameters from the data, but only some of these techniques can provide statistical significance (p-values) for the presence of a response. In this work, we propose a bootstrap technique to provide such p-values, which can be applied to a wide variety of parameters. The bootstrap method is based on randomly resampling (with replacement) the original data and gives an estimate of the probability that the response obtained is due to random variation in the data rather than a physiological response. The method is illustrated using auditory brainstem responses (ABRs) to detecting hearing thresholds. The flexibility of the approach is illustrated, showing how it can be used with different parameters, numbers of stimuli and with user-defined false-positive rates. The bootstrap method provides a new, simple and yet powerful means of detecting evoked potentials, which is very flexible and readily adapted to a wide variety of signal parameters.
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Affiliation(s)
- Jing Lv
- Institute of Sound and Vibration Research, University of Southampton, Highfield, Southampton, SO17 1BJ, UK.
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34
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Parra LC, Spence CD, Gerson AD, Sajda P. Recipes for the linear analysis of EEG. Neuroimage 2005; 28:326-41. [PMID: 16084117 DOI: 10.1016/j.neuroimage.2005.05.032] [Citation(s) in RCA: 324] [Impact Index Per Article: 17.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2004] [Revised: 03/02/2005] [Accepted: 05/05/2005] [Indexed: 11/30/2022] Open
Abstract
In this paper, we describe a simple set of "recipes" for the analysis of high spatial density EEG. We focus on a linear integration of multiple channels for extracting individual components without making any spatial or anatomical modeling assumptions, instead requiring particular statistical properties such as maximum difference, maximum power, or statistical independence. We demonstrate how corresponding algorithms, for example, linear discriminant analysis, principal component analysis and independent component analysis, can be used to remove eye-motion artifacts, extract strong evoked responses, and decompose temporally overlapping components. The general approach is shown to be consistent with the underlying physics of EEG, which specifies a linear mixing model of the underlying neural and non-neural current sources.
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Affiliation(s)
- Lucas C Parra
- Department of Biomedical Engineering, City College of New York, New York, NY 10031, USA.
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