Participants underwent 5-min eyes-closed resting-state MEG, using a 306-channel Elekta Neuromag Oy MEG system, with a sampling frequency of 1250Hz and 0.1Hz high pass and 410Hz antialiasing filters (Supplementary materials ). We used cross-validation signal space separation, after which raw data were visually inspected and malfunctioning channels excluded [LD]. The signal was filtered between 0.5-45Hz. We used a 3D digitizer (Fastrak; Polhelmus) to digitize 4–5 head position indicator coils and the scalp-nose surface for co-registration of the MEG data to patients’ anatomical MRIs. A scalar beamformer implementation (Elekta Neuromag Oy, version 2.1.28) source-reconstructed broadband (0.5-45Hz) time series to the 210 BNA centroids [27 (link), 29 (link), 30 (link)]. We selected 15 and 8 epochs for patients and HCs, respectively (3.27s).
Meg system
Manufactured by Elekta
Sourced in Finland
The MEG system is a non-invasive medical imaging device used to measure the magnetic fields generated by the electrical activity in the brain. It provides information about the location and timing of neural activity within the brain.
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Lab products found in correlation
306 magnetic sensors, by Elekta (11 mentions)
Maxfilter, by Elekta (6 mentions)
204 planar gradiometers, by Elekta (3 mentions)
Planar gradiometers, by Elekta (2 mentions)
Achieva 3t x series scanner, by Philips (1 mentions)
Eight channel head coil, by Philips (1 mentions)
Fastrak 3d digitiser, by Polhemus (1 mentions)
Fastrak 3sf0002, by Polhemus (1 mentions)
Prisma 3t scanner, by Siemens (1 mentions)
Fastrak, by Polhemus (1 mentions)
Magnetometers, by Elekta (1 mentions)
Presentation software, by Neurobehavioral Systems (1 mentions)
Vectorview, by Elekta (1 mentions)
3space fastrak, by Polhemus (1 mentions)
40 protocols using meg system
1
MEG Resting-State Protocol for Neuroimaging
2
Magnetoencephalography and Structural MRI Acquisition
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Recordings were conducted in a magnetically-shielded room with active shielding engaged. With an acquisition bandwidth of 0.1–330 Hz, neuromagnetic responses were sampled continuously at 1 kHz using an Elekta MEG system with 306 magnetic sensors (Elekta, Helsinki, Finland). MEG data from each participant were individually-corrected for head motion and subjected to noise reduction using the signal space separation method with a temporal extension39 (link). Each participant’s MEG data were then coregistered with their structural T1-weighted MRI data using BESA MRI (Version 2.0; BESA GmbH, Gräfelfing, Germany). These neuroanatomic images were acquired with a Philips Achieva 3T X-series scanner using an eight-channel head coil and a 3D fast field echo sequence with the following parameters: TR: 8.09 ms; TE: 3.7 ms; field of view: 24 cm; matrix: 256 × 256; slice thickness: 1 mm with no gap; in-plane resolution: 0.9375 × 0.9375 mm; sense factor: 1.5. The structural MRI volumes were aligned parallel to the anterior and posterior commissures and were transformed into standardized space after source imaging (i.e., beamforming)40 (link)41 (link).
3
Detailed MEG Acquisition and Preprocessing Protocol
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All recordings were performed in a one-layer magnetically shielded room with active shielding engaged for environmental noise compensation. With an acquisition bandwidth of 0.1–330 Hz, neuromagnetic responses were sampled continuously at 1 kHz using an Elekta MEG system (Elekta, Helsinki, Finland) with 306 magnetic sensors, including 204 planar gradiometers and 102 magnetometers. Throughout data acquisition, participants were monitored using a real-time audio-video feed from inside the magnetically shielded room. MEG data from each participant were individually corrected for head motion and subjected to noise reduction using the signal space separation method with a temporal extension (Taulu and Simola, 2006 (link)). Each participant’s MEG data were coregistered with their structural T1-weighted MRI data prior to imaging analyses using BESA MRI (Version 2.0). Structural MRI data were aligned parallel to the anterior and posterior commissures and transformed into standardized space. After beamformer analysis (see below), each subject’s functional images were transformed into standardized space using the transform that was previously applied to the structural MRI volume and spatially resampled.
4
Magnetoencephalography Pipeline for Neuroimaging
5
Magnetically-Shielded MEG Recording
6
Magnetoencephalography for Neuroscience Research
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Neuromagnetic responses were acquired within a magnetically-shielded room using an Elekta MEG system with 306 sensors (102 magnetometers and 204 planar gradiometers; Elekta, Helsinki, Finland). Signals were sampled at 1 kHz with an acquisition bandwidth of 0.1–330 Hz. Each MEG data set was corrected for head motion, and the signal space separation method with a temporal extension (tSSS; Taulu and Simola, 2006 (link); Taulu et al., 2005 ) was applied for noise reduction. Further details are provided in several recent papers (Embury et al., 2019 (link); Lew et al., 2019 (link); Spooner et al., 2018 (link); Wiesman and Wilson, 2020 ).
7
MEG Data Acquisition and Preprocessing
8
Magnetoencephalography Data Acquisition
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MEG signals were sampled at 1 kHz with an acquisition bandwidth of 0.1–330 Hz using a 306-sensor Elekta MEG system equipped with 204 planar gradiometers and 102 magnetometers. All data were corrected for head movement, subjected to a noise reduction method (Taulu and Simola, 2006 ), and co-registered to high-resolution structural MRI. For a detailed account of the data acquisition, co-registration, and preprocessing steps used in this study, please refer to the Supplementary material .
9
MEG Recording and Preprocessing Protocol
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Electromagnetic brain activity was recorded using a 102 triple-sensor (two planar gradio-, one magnetometer) MEG system (Elekta Neuromag, Helsinki, Finland). Data was sampled continuously at 1 kHz. Prior to the experiment, the headshape of each participant was measured using a Polhemus FASTRAK 3D digitiser, relative to five coils (two on the left and right mastoid, three coils on the front). Head movement was monitored by passing small currents through these coils before each run. From most participants, an anatomical 3D structural image was obtained using a 4T magnetic resonance imaging (MRI) scanner (Bruker Biospin, Ettlingen Germany). All MEG data was analysed using the Matlab-based Fieldtrip toolbox38 (link). Epochs of +/−2000 ms length were extracted around stimulus onset and 1 Hz highpass filtered. Then, the data was visually inspected to identify and remove noisy trials, channel jumps and ocular artefacts. After the artefact rejection, all trials were downsampled to 300 Hz. In all further analyses, an equal number of detected and undetected trials was randomly selected to prevent any bias across conditions39 (link).
10
Magnetoencephalography Data Preprocessing
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All recordings were conducted in a one-layer magnetically-shielded room with active shielding engaged. Neuromagnetic responses were sampled continuously at 1 kHz with an acquisition bandwidth of 0.1–330 Hz using an Elekta MEG system with 306 magnetic sensors (Elekta, Helsinki, Finland). Using MaxFilter (v2.2; Elekta), MEG data from each patient were individually corrected for head motion and subjected to noise reduction using the signal space separation method with a temporal extension (Taulu and Simola, 2006 (link), Taulu et al., 2005 ). Each participant's MEG data were coregistered with structural T1-weighted MRI data prior to source space analyses using BESA MRI (Version 2.0). Structural MRI data were aligned parallel to the anterior and posterior commissures and transformed into standardized space. After beamformer analysis, each subject's functional images were also transformed into standardized space using the transform applied to the structural MRI volume and spatially resampled.
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