Hydrocel geodesic sensor net

Manufactured by Electrical Geodesics

Sourced in United States

The HydroCel Geodesic Sensor Net is a high-density electroencephalography (EEG) recording system. It is designed to provide comprehensive coverage of the scalp for neural data acquisition. The net features a geodesic arrangement of electrodes and utilizes saline-based hydrogel sensors to optimize electrical connectivity with the scalp.

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110 protocols using hydrocel geodesic sensor net

Neurophysiological Signatures of Finger Tapping

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EEG was acquired during the whole experiment using a 128-channel HydroCel Geodesic Sensor Net (GSN) with Ag/AgCl electrodes provided by Electrical Geodesics (EGI, Eugene Oregon, USA). This system uses the vertex (Cz) electrode as a physical reference. EEG recordings, electrooculograms for horizontal and vertical eye movements, and an electromyogram for the muscular noise associated with swallowing were recorded in parallel with a sampling frequency of 1000 Hz. During acquisition participants sat in a dimly lit room in front of a computer screen and performed a finger tapping task at maximum voluntary speed using the paradigm described above.

Bächinger M., Lehner R., Thomas F., Hanimann S., Balsters J, & Wenderoth N. (2019). Human motor fatigability as evoked by repetitive movements results from a gradual breakdown of surround inhibition. eLife, 8, e46750.

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Comprehensive EEG and MRI Acquisition Protocol

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EEG signals were recorded by the 256-channel HydroCel Geodesic Sensor Net (GSN) using Ag/AgCl electrodes provided by Electrical Geodesics (EGI, Eugene, Oregon, USA). The EGI system uses the vertex (Cz) electrode as physical reference. EEG recordings were sampled online at 1000 Hz. All sensors and three fiducial positions were localized prior to the EEG acquisition by using a Geodesic Photogrammetry System (GPS) (Russell et al 2005 (link)). Electric reference signals were collected in parallel to EEG data: those included electrooculograms for horizontal and vertical eye movements respectively, and an electromyogram for the muscular noise associated with swallowing.
The T1-weighted MRI of each subject was acquired in a separate experimental session using a Philips 3T Ingenia scanner with a turbo field echo sequence (Barttfeld et al 2014 (link)). The scanning parameters were: TR=8.25ms, TE=3.8ms, 8° flip angle, 240×240×160 field of view, 1 mm isotropic resolution.

Liu Q., Balsters J.H., Baechinger M., van der Groen O., Wenderoth N, & Mantini D. (2015). Estimating a neutral reference for electroencephalographic recordings: the importance of using a high-density montage and a realistic head model. Journal of Neural Engineering, 12(5), 056012.

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Continuous EEG Acquisition Protocols

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EGI system. Continuous EEG was acquired using the 128-channel Geodesic EEG System (Electrical Geodesics, Inc., Eugene, OR, USA) and the HydroCel Geodesic Sensor Net, which arrays 19 electrode sensors (AgCl-coated electrodes) in a geodesic pattern over the surface of the head at the equivalent 10–20 system locations. Consistent positioning was achieved by aligning the Sensor Net with skull landmarks (nasion, vertex, and pre-auricular points). Low-noise EEG data were obtained using high-input impedance amplifiers (Net Amps300) with sensor-skin impedances maintained below 50 kΩ. The signal was digitized at a sampling rate of 500 Hz (0.01 Hz high-pass filter) and recorded with a vertex reference, the impedance of which was kept below 10 kΩ. EEG data were stored in raw format in NetStation.
Biohub system. Continuous EEG was acquired using the Biohub system and sampling the scalp at seven recording sites (Fpz, Fz, Cz, Pz, Oz, C3, C4) having the corresponding channels on the HydroCel Geodesic Sensor Net. Raw EEG signals were collected at 500 Hz with OpenBCI, the left earlobe was used as a reference, and the dry electrodes’ impedances were kept below 300 kΩ. Signals were wirelessly transmitted to the Jetson, which created LSL streams with EEG data, markers, and information about the lost packets and the temporary loss of connection. The streams were saved as XDF files using LabRecorder.

Ascari L., Marchenkova A., Bellotti A., Lai S., Moro L., Koshmak K., Mantoan A., Barsotti M., Brondi R., Avveduto G., Sechi D., Compagno A., Avanzini P., Ambeck-Madsen J, & Vecchiato G. (2021). Validation of a Novel Wearable Multistream Data Acquisition and Analysis System for Ergonomic Studies. Sensors (Basel, Switzerland), 21(24), 8167.

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Comprehensive EEG Analysis of Cognitive Tasks

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EEG was recorded with a 256-channel HydroCel Geodesic-Sensor-Net (Electrical Geodesics, Inc., Eugene, OR) using Net Station 5 software. Data were collected using the electrode Cz as reference and keeping electrode impedance below 50 kΩ. Seventy-eight electrodes located over the neck and cheeks were excluded before data pre-processing, as these were consistently contaminated with muscle artifacts.
EEG data were analyzed using Brainstorm [28 (link)]. Pre-processing followed standard procedures as recommended in [29 ] and Brainstorm. Continuous EEG recordings were filtered (0.1–30 Hz) down-sampled to 500 Hz and re-referenced to the right and left mastoid electrodes. Automatic blink detection was done using four electrodes located above and below each eye and artifact correction was performed with Signal-Space Projection.
Only correct trials without activity exceeding ± 100 μV were analyzed. The average number of trials included for the Simon task was 109 (SD 34) (congruent), and 102 (SD 38) (incongruent). For the oddball task, a mean of 51 (SD 8) large deviant and 49 (SD 9) small deviant trials were included.

Fernandez Cruz A.L., Chen C.M., Sanford R., Collins D.L., Brouillette M.J., Mayo N.E, & Fellows L.K. (2021). Multimodal neuroimaging markers of variation in cognitive ability in older HIV+ men. PLoS ONE, 16(7), e0243670.

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Neuroimaging of Healthy Young Adults

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Eyes-open resting-state data were collected in a cohort of 19 healthy young adults (age 28 ± 6 years, 5 males) and were previously used in other studies from our group [11 (link),12 (link),49 (link)]. Ethical approval was granted by the Ethics Committee of ETH Zurich; informed consent was obtained from all participants and the experiment was performed in accordance with the relevant guidelines and regulations. For each participant, we recorded hdEEG signals for 5 min at 1000 Hz sampling rate using a 256-channel HydroCel Geodesic Sensor Net by Electrical Geodesics (Eugene, OR, USA). Electromyograms and vertical and horizontal electrooculograms (EOG) were collected in addition to the hdEEG signals. Positions of the EEG sensors and of three landmarks (nasion, left and right preauricular points) were localized using a Geodesic Photogrammetry System (GPS) [42 (link)]. In a separate session, we acquired a T1-weighted whole-head anatomical image using a Philips Ingenia 3T MR scanner (Best, The Netherlands) with a turbo field echo sequence. Scanning parameters were: TR = 8.25 ms, TE = 3.8 ms, flip angle = 8°, voxel size = 1 mm³ isotropic.

Taberna G.A., Samogin J., Marino M, & Mantini D. (2021). Detection of Resting-State Functional Connectivity from High-Density Electroencephalography Data: Impact of Head Modeling Strategies. Brain Sciences, 11(6), 741.

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EEG Analysis of Reward Processing

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EEG data were recorded using a 128-channel HydroCel Geodesic Sensor Net (Electrical Geodesics, Inc., Eugene, OR) in an electrically and acoustically shielded room. BrainVision Analyzer 2.1.1 (Brain Products, Munich, Germany) was used for EEG data processing. For time-domain analyses, EEG data were segmented from 200 ms before stimulus onset (win or loss feedback) up to 1,000 ms after stimulus onset. A baseline correction was applied using the average amplitude over 200 ms prior to stimulus onset. Consistent with prior work (16 (link)), RewP values were computed as the mean amplitude from 250-350 ms post-stimulus at electrode FCz (see Figure 1, Panel A), and the LPP was assessed using the average of frontocentral midline electrode sites (Fz, FCz, and Cz) between 600-1,000 ms post-stimulus (16 (link),36 (link),42 (link),43 (link))(Figure 2). For time-frequency analyses, and consistent with prior work isolating RewP-linked theta and delta power (16 (link)), a complex Morlet wavelet transformation was applied (Morlet parameter c = 3.5) from 0.5 to 20 Hz using 30 frequency steps distributed on a logarithmic scale (44 )(Figure 1, Panel B). See Supplement for additional details.

Webb C.A., Auerbach R.P., Bondy E., Stanton C.H., Appleman L, & Pizzagalli D.A. (2020). Reward-related neural predictors and mechanisms of symptom change in cognitive behavioral therapy for depressed adolescent girls. Biological psychiatry. Cognitive neuroscience and neuroimaging, 6(1), 39-49.

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Infant EEG During Vocal Stimuli

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The EEG recording was made in an electrically shielded quiet room. The infant was seated in the mother's lap and tested in a behavioral state of quiet alert. The mother was instructed to remain as still as possible and maintain a neutral expression if the infant looked at her during EEG recording.
The EEG was recorded with a 60-electrode HydroCel Geodesic Sensor Net (Electrical Geodesics Inc., Eugene, OR). The EEG signal was amplified using a 0.1-100 Hz bandpass and digitized at 500 Hz. Impedances were maintained below 50K Ohms throughout recording. Recording in every electrode was vertex-referenced. The raw data were stored for later analysis. After placement of EEG electrodes on the infant's scalp, the electrical brain activity was measured during a baseline condition and a condition in which the human voice stimuli were presented.

Mai X., Xu L., Li M., Shao J., Zhao Z., Lamm C., Fox N.A., Nelson C.A, & Lozoff B. (2014). Sounds elicit relative left frontal alpha activity in 2-month-old infants. International journal of psychophysiology : official journal of the International Organization of Psychophysiology, 94(3), 287-291.

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Resting-state EEG Acquisition Protocol

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EEG data were recorded in a dimly lit room using a 64-channel HydroCel Geodesic Sensor Net (Electrical Geodesics, Inc, USA) containing Ag/AgCl electrodes surrounded by electrolyte-wetted sponges. Data were acquired using NetStation software (version 5.0) via a Net Amps 400 amplifier using a sampling rate of 1 KHz, with data online referenced to the Cz electrode. Prior to the commencement of recording, electrode impedances were checked to ensure they were < 50 KOhms. The resting-state data were recorded for two minutes while participants sat with their eyes open and stared at a fixation cross on a computer screen, and two minutes while participants had their eyes closed.

Hill A.T., Clark G.M., Bigelow F.J., Lum J.A.G., & Enticott P.G. (2021). Periodic and Aperiodic Neural Activity Displays Age-Dependent Changes Across Early-to-Middle Childhood.

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High-Density EEG Acquisition and Pre-Processing

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Electroencephalogram (EEG) signals were recorded using Net Amps 300 that connects a high-density 128 channel HydroCel Geodesic Sensor Net [18 (link)] (Electrical Geodesics Inc., Eugene, OR) with Net-Station 4.3 software. All electrode impedances were below 50 KΩ before recording was started [19 (link)]. Regions of interest (ROIs) around the parietal-occipital cortex were selected from the following standard international 10/20 posterior parietal electrodes for PO3 and PO4. Electrodes were referenced to the average Cz channel. All signals were anti-aliasing, low-pass filtered at 100 Hz, and digitized at a sample rate of 250 Hz.

Kuo C.C., Zhang C., Rissman R.A, & Chiu A.W. (2014). Long-Term Electrophysiological and Behavioral Analysis on the Improvement of Visual Working Memory Load, Training Gains, and Transfer Benefits. Journal of behavioral and brain science, 4(5), 234-246.

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High-Density EEG Acquisition and Pre-Processing

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