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1

Multimodal MEG and Eye Tracking Protocol

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Prior to the measurement, the head position of the participant was digitized using the Polhemus Fastrack electromagnetic digitiser system (Polhemus Inc., USA). The MEG data were acquired using a 306-sensor TRIUX Elekta Neuromag system (Elekta, Finland), while the participant was sitting in an upright position (60°) in a dim light magnetically shielded room. The magnetic signals were bandpass filtered within 0.1 – 330 Hz with embedded anti-aliasing filters and sampled at 1000 Hz. Simultaneously with the MEG, we also acquired the coordinates of the pupil and the pupil diameter using an EyeLink eye-tracker (SR Research, Canada).
The broadband flickering (or tagging) signals were recorded using a custom-made photodetector (Aalto NeuroImaging Centre, Aalto University, Finland) that was connected to a miscellaneous channel of the MEG system. This allowed us to acquire the tagging signal with the same temporal precision as the MEG data.
Additionally, a high-resolution T1-weighted anatomical image (TR/TE of 7.4/3.5 ms, a flip angle of 7°, FOV of 256×256×176 mm, 176 sagittal slices, and a voxel size of 1×1×1 mm3) was acquired using 3-Tesla Phillips Achieva scanner.

Zhigalov A, & Jensen O. (2023). Travelling waves observed in MEG data can be explained by two discrete sources. NeuroImage, 272, 120047.

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Multimodal MEG and Eye Tracking Protocol

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Prior to the measurement, the head position of the participant was digitized using the Polhemus Fastrack electromagnetic digitiser system (Polhemus Inc., USA). The MEG data were acquired using a 306-sensor TRIUX Elekta Neuromag system (Elekta, Finland), while the participant was sitting in an upright position (60°) in a dim light magnetically shielded room. The magnetic signals were bandpass filtered within 0.1 – 330 Hz with embedded anti-aliasing filters and sampled at 1000 Hz. Simultaneously with the MEG, we also acquired the coordinates of the pupil and the pupil diameter using an EyeLink eye-tracker (SR Research, Canada).
The broadband flickering (or tagging) signals were recorded using a custom-made photodetector (Aalto NeuroImaging Centre, Aalto University, Finland) that was connected to a miscellaneous channel of the MEG system. This allowed us to acquire the tagging signal with the same temporal precision as the MEG data.
Additionally, a high-resolution T1-weighted anatomical image (TR/TE of 7.4/3.5 ms, a flip angle of 7°, FOV of 256×256×176 mm, 176 sagittal slices, and a voxel size of 1×1×1 mm3) was acquired using 3-Tesla Phillips Achieva scanner.

Zhigalov A, & Jensen O. (2023). Travelling waves observed in MEG data can be explained by two discrete sources. NeuroImage, 272, 120047.

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3

MEG Acquisition and Digitalization Protocol

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We used a MEGIN system to collect the neuromagnetic signals from 306 sensors, of which 204 were orthogonal planar gradiometers and 102 were magnetometers (Elekta, Finland). For the preparations, we first placed 4 head-position indicator (HPI) coils on the participant’s head: 2 were on the forehead with more than 3 cm distance in between, and the other 2 were on the left and right mastoid bone behind the ears. Then, we used the Polhemus Fastrack electromagnetic digitizer system (Polhemus, United States of America) to digitise the head position by 3 fiducial anatomical markers (the nasion, left and right preauricular points). Next, we digitised the 4 HPI coils. For the final step, we digitised at least 200 points on the scalp to obtain the whole shape of the head. With the help of head digitalization, the MEG head position can be spatially co-registered with the individual structural MRI images for the source modelling analysis.
Afterwards, participants walked to a dimly lit room and sat in the MEG gantry (60 degrees upright position). The distance between the participant and the projector screen was 145 cm, which yielded 1 visual degree from 35 pixels. The MEG data were sampled at 1,000 Hz after the application of an anti-aliasing 0.1 to 330 Hz band-pass filter.

Pan Y., Popov T., Frisson S, & Jensen O. (2023). Saccades are locked to the phase of alpha oscillations during natural reading. PLOS Biology, 21(1), e3001968.

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4

Magnetoencephalography Experiment on Tactile Perception

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After digitization of the head‐shape and head‐position coils, digitized with Polhemus Fastrack (Polhemus Inc.), subjects were seated in the MEG with the tactor attached to the left hand. Subjects then completed a training session of 10 trials in which half of the trial contained targets, to familiarize them with the procedure. Subjects then completed the experiment in four blocks of 50 trials, with a short break after the first and third block, and a longer break after the second block, in which they were lowered out of the MEG helmet. Care was taken to reposition subjects in the same position as the initial measurement, using in‐house developed real‐time head localization of the MEG system. The number of subjects and trials were decided a priori, based on previous studies and experience with similar paradigms which were shown to provide sufficient power in similar analyses (e.g., Whitmarsh et al., 2014 (link), 2017 (link)). The analysis and hypothesis testing were performed only after all data were collected.

Whitmarsh S., Gitton C., Jousmäki V., Sackur J, & Tallon‐Baudry C. (2021). Neuronal correlates of the subjective experience of attention. The European Journal of Neuroscience, 55(11-12), 3465-3482.

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5

Multimodal MEG and MRI Data Acquisition

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MEG was acquired using a 306‐sensor TRIUX Elekta Neuromag system (Elekta, Finland). The MEG data were low‐pass filtered at 300 Hz using embedded anti‐aliasing filters and sampled at 1,000 Hz. Head position of the participants was digitized using the Polhemus Fastrack electromagnetic digitizer system (Polhemus Inc.). We also used an EyeLink eye tracker, and vertical and horizontal EOG sensors to remove trials containing blinks and saccades.
The tagging signals were recorded using a custom‐made photodetector (Aalto NeuroImaging Centre, Aalto University, Finland) that was connected to a miscellaneous channel of MEG system. This allowed us to acquire the tagging signal with the same temporal precision as the MEG data.
A high‐resolution T1‐weighted anatomical image (TR/TE of 7.4/3.5 ms, a flip angle of 7°, FOV of 256 × 256 × 176 mm, 176 sagittal slices, and a voxel size of 1 × 1 × 1 mm³) was acquired using 3‐T Phillips Achieva scanner.

Zhigalov A, & Jensen O. (2020). Alpha oscillations do not implement gain control in early visual cortex but rather gating in parieto‐occipital regions. Human Brain Mapping, 41(18), 5176-5186.

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6

MEG Acquisition and Preprocessing Protocol

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MEG was acquired using a 306-sensor TRIUX Elekta Neuromag system (Elekta, Finland). The MEG data were lowpass filtered at 300 Hz using embedded anti-aliasing filters and sampled at 1000 Hz. Head position of the participants was digitized using the Polhemus Fastrack electromagnetic digitiser system (Polhemus Inc., USA). We also used an EyeLink eye tracker, and vertical and horizontal EOG sensors to remove trials containing blinks and saccades.
The tagging signals were recorded using a custom-made photodetector (Aalto NeuroImaging Centre, Aalto University, Finland) that was connected to a miscellaneous channel of MEG system. This allowed us to acquire the tagging signal with the same temporal precision as the MEG data.
A high-resolution T1-weighted anatomical image (TR/TE of 7.4/3.5 ms, a flip angle of 7°, FOV of 256×256×176 mm, 176 sagittal slices, and a voxel size of 1×1×1 mm 3 ) was acquired using 3-Tesla Phillips Achieva scanner.

Zhigalov A., & Jensen O. (2020). Alpha oscillations do not implement gain control in early visual cortex but rather gating in parieto-occipital regions.

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7

Postural Sway Measurement Using Magnetic Tracking

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Postural sway was measured using Polhemus FASTRACK (Polhemus, Inc, Colchester, Vermont), a magnetic motion tracking system. A tracking system receiver was attached at the seventh cervical vertebrae to record torso movements. 20, 24 Cloth medical tape and Velcro bands were used to avoid slippage during the trial. Data reflecting the 3-dimensional position of the receiver were sampled at 120 Hz for each 60-second trial, yielding a total of 7200 data points per trial. The raw data regarding postural sway were subsequently stored on a laptop computer for further analysis.

Chen F.C., Tsai C.L., Chang W.D., Li Y.C., Chou C.L, & Wu S.K. (2015). Postural Control of Anteroposterior and Mediolateral Sway in Children With Probable Developmental Coordination Disorder. Pediatric physical therapy : the official publication of the Section on Pediatrics of the American Physical Therapy Association, 27(4).

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8

Prefrontal Cortex Hemodynamics via fNIRS

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Data of localized blood oxygenation levels in the prefrontal cortex indicating neural activity were acquired by a functional near-infrared spectroscopy (fNIRS) system that included an array of sensors (FOIRE-3000, Shimadzu Co. Japan) worn on the head, which recorded change in cerebral blood flow during task performance. The array of sensors (fNIRS sources and detectors) was equipped with 22 channels and was attached to the head in a location positioned from the prefrontal area in accordance with the International 10–20 system (Figure 2). The sensors were positioned across from each other at 3 cm intervals. Basing on the modified Beer–Lambert law, the oxy-hemoglobin change (Δoxy-Hb, mM·mm) was acquired from the cortical concentration levels. The sites to measure oxy-hemoglobin change associated with cerebral blood flow change were determined using a 3D digitizer (FASTRACK, Polhemus) as previously described [20 (link),21 (link)]. Their placements coincided with Brodmann Areas BA9, BA10, and BA46. The physiological noise from cardiac signal and respiration, and so forth was filtered by a temporal low-pass cut-off at 0.1 Hz.

Cong L., Miyaguchi H, & Ishizuki C. (2021). Comparison of Activation in the Prefrontal Cortex of Native Speakers of Mandarin by Ability of Japanese as a Second Language Using a Novel Speaking Task. Healthcare, 9(4), 412.

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9

Functional Near-Infrared Spectroscopy for Language Study

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We acquired all fNIRS data with a commercial continuous-wave NIRS system (NIRScout, NIRx Medical Systems, New York). The optical probe contained 16 sources at two different wavelengths (LEDs centered at 760 and 850 nm,

\sim 15 mW

light power emission for each) and 16 detectors. This configuration enabled the use of 32 source–detector combinations (i.e., channels) at 3 cm, and two source–detector pairs at 0.8 cm (short channels). Data were acquired at 7.8 Hz.
The probe design was arranged to be sensitive to the primary regions related to language and speech in the frontal, temporal, and parietal lobes. We positioned one short channel in each brain hemisphere. The short-channel data enabled us to regress out extracortical contributions hemispherically. To secure the optodes on the heads of the subjects, we used a 10–20 standard cap from NIRx Medical Systems.⁵⁸ (link) We digitized the position of all optodes using a commercial digitizer (Fastrack, Polhemus, Colchester, Vermont) for better accuracy concerning the location of each source and detector. Figure 1(a) shows a sensitive profile for the probe, which was obtained from Monte Carlo simulations through the AtlasViewer package.⁵⁹ (link)

Novi S.L., Roberts E., Spagnuolo D., Spilsbury B.M., Price D.C., Imbalzano C.A., Forero E., Yodh A.G., Tellis G.M., Tellis C.M, & Mesquita R.C. (2020). Functional near-infrared spectroscopy for speech protocols: characterization of motion artifacts and guidelines for improving data analysis. Neurophotonics, 7(1), 015001.

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10

Upper Limb Kinematic Analysis Protocol

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The upper limb movements were recorded using a three-dimensional electromagnetic motion capture system (Fastrack, Polhemus Inc, U.S.A.) and a custom-made data acquisition software written in C. The sensor was placed on the index finger. The three-dimensional position of the sensor was recorded with a sampling frequency of 40 Hz and was time stamped. The upper limb kinematics were recorded and synchronized using the same computer that captured the ECoG, EEG and EMG data. An example of recorded signals is shown in Fig 2.

Talakoub O., Marquez-Chin C., Popovic M.R., Navarro J., Fonoff E.T., Hamani C, & Wong W. (2017). Reconstruction of reaching movement trajectories using electrocorticographic signals in humans. PLoS ONE, 12(9), e0182542.

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Fastrack

Lab products found in correlation

32 protocols using fastrack

Multimodal MEG and Eye Tracking Protocol

Multimodal MEG and Eye Tracking Protocol

MEG Acquisition and Digitalization Protocol

Magnetoencephalography Experiment on Tactile Perception

Multimodal MEG and MRI Data Acquisition

MEG Acquisition and Preprocessing Protocol

Postural Sway Measurement Using Magnetic Tracking

Prefrontal Cortex Hemodynamics via fNIRS

Functional Near-Infrared Spectroscopy for Language Study

Upper Limb Kinematic Analysis Protocol

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