Neuroscan system

Manufactured by Compumedics

Sourced in United States, Australia

The Neuroscan system is a comprehensive suite of hardware and software designed for neurophysiological research and clinical applications. It provides high-quality data acquisition, analysis, and visualization capabilities for various neuroimaging modalities, including electroencephalography (EEG), event-related potentials (ERPs), and magnetoencephalography (MEG).

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Lab products found in correlation

Masscomp, by Compumedics (2 mentions) Brainproducts eeg system, by Brain Products (1 mentions) Curry 7, by Compumedics (1 mentions) Matlab 9, by MathWorks (1 mentions) Neuroscan quik cap, by Compumedics (1 mentions) Hd 280 pro, by Sennheiser (1 mentions) Eeglab, by MathWorks (1 mentions) Matlab, by MathWorks (1 mentions) Synamps rt amplifier, by Compumedics (1 mentions)

31 protocols using neuroscan system

Standardized Resting-State EEG Protocol for Depression Classification

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We used a Neuroscan system with an Easycap of 64 electrodes to carry and acquire EEG data with a sampling rate of 500 Hz. Two electrodes placed up and below the left eye were used to keep control of blinks and vertical eye movements (VEO).
The participants were asked to remove jewelry and piercings. Then they signed an informed consent form and received instructions to ensure their understanding of the EEG procedure and task. The participants were asked to stay calm and keep their eyes on a fixation point while we recorded EEG for 3 min for the open-eyes resting-state condition. Afterwards, they were asked to close their eyes and stay as calm as possible for 3 min while we recorded the EEG closed-eyes resting-state condition (EC). Impedances were kept less than 10 kΩ during the whole experiment. For this analysis, we used only time segments of the EC condition, as it seemed to be the most accepted while classifying depression [6 (link)]. After this, the participants completed the Edinburgh handedness inventory [21 (link)].

Jan D., de Vega M., López-Pigüi J, & Padrón I. (2022). Applying Deep Learning on a Few EEG Electrodes during Resting State Reveals Depressive States: A Data Driven Study. Brain Sciences, 12(11), 1506.

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64-Channel EEG Recording and Data Acquisition

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EEG was recorded using a 64-channel (Ag–AgCl) NeuroScan system (NeuroScan). Electrodes were positioned following the 10–20 system convention. The reference electrode was placed at the tip of the nose and the ground electrode was placed at FPz. The vertical electro-oculogram (EOG) was recorded supra- and infra-orbitally from the left eye. The horizontal EOG was recorded as the left vs. right orbital rim. The impedance of each electrode was kept below 5 kΩ. EEG and EOG signals were digitized online at 500 Hz and band-pass filtered from 0.05 to 100 Hz.

Yu K., Wang R., Li L, & Li P. (2014). Processing of acoustic and phonological information of lexical tones in Mandarin Chinese revealed by mismatch negativity. Frontiers in Human Neuroscience, 8, 729.

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Scalp EEG Recording and Eye Monitoring

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Scalp recorded EEG was obtained using a 32-channel Neuroscan system with electrodes in the international 10–20 configuration at impedances <5 kΩ. Activity was low pass filtered at 100 Hz and a high pass filtered at 0.1 Hz and sampled at 500 Hz/32-bit resolution creating MATLAB files. Subjects maintained centered visual fixation (+/−10°) on a centered spot screen during recording. Eye position was monitored using infrared oculometry (ASL, Inc.). EEGLAB created independent components for each subject and recording session to remove eye blinks in one or two components.

Jacob M.S, & Duffy C.J. (2014). Might Cortical Hyper-Responsiveness in Aging Contribute to Alzheimer’s Disease?. PLoS ONE, 9(9), e105962.

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Modified Sternberg Task EEG Protocol

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On Day 1 and Day 7, the EEG data during the modified Sternberg task were recorded by a 64-channel Neuroscan system, and electrode locations were according to the international 10–20 system. The ground was located at the area between FPz and Fz. The reference electrode was placed on the left mastoid. The impedance for all electrodes was kept below 5 kΩ. The signals were amplified through an amplifier (Neuroscan Amps2) with a sampling rate of 500 Hz. A 0.05–100 Hz bandpass filter was enabled in the amplifier to filter out low-frequency and high-frequency noise.

Zhou W., Nan W., Xiong K, & Ku Y. (2024). Alpha neurofeedback training improves visual working memory in healthy individuals. NPJ Science of Learning, 9, 32.

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Comprehensive EEG and PSG Protocol

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Both EEG and PSG applied 21 scalp electrodes in combination with the Neuroscan system (NeuroScan, El Paso, Texas, USA). Electrodes were placed following the international 10/20 system (Fp1, Fpz, Fp2, F7, F3, Fz, F4, F8, T3, C3, Cz, C4, T4, T5, P3, Pz, P4, T6, O1, Oz, O2, and included mastoids A1 and A2). PSG recordings included five additional electro‐oculogram channels, one bipolar electrocardiogram channel, one bipolar submental electromyogram channel, and one bipolar respiratory channel. Signals were filtered (high‐pass = 0.10 Hz; low‐pass = 70 Hz; 50 Hz notch filter) and acquired using a 250 Hz sampling rate.

van Schalkwijk F.J., Sauter C., Hoedlmoser K., Heib D.P., Klösch G., Moser D., Gruber G., Anderer P., Zeitlhofer J, & Schabus M. (2017). The effect of daytime napping and full‐night sleep on the consolidation of declarative and procedural information. Journal of Sleep Research, 28(1), e12649.

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Resting State and Thermal Pain EEG Experiments

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For resting state experiments conducted at the University of Minnesota, a 64 channel MR-compatible BrainProducts EEG system was used (Gilching, Germany). For resting state experiments conducted at Children's National, a 64 channel Neuroscan system was used (Charlotte, NC). For thermal pain experiments, a 128 channel BioSemi Active-II EEG system was used (Amsterdam, Netherlands). All electrode impedances were below 20 kΩ and all EEG data was recorded at 1 kHz.
The EEG data was processed using the EEGLAB toolbox (Delorme and Makeig, 2004 (link)). Visual artifact removal was performed be removing noisy sections of the EEG recordings. Additionally, independent component analysis was used to remove noisy components. The EEG data were resampled to 256 Hz, bandpass filtered between one and 50 Hz, and average referenced. Finally, an automatic artifact rejection toolbox in EEGLAB was used to further clean the data (Gomez-Herrero et al., 2006 ). The first and last minute of EEG recordings were removed from the resting state data. At least 5 min of artifact-free EEG data was required for participants to be included for further analysis.

Case M., Shirinpour S., Vijayakumar V., Zhang H., Datta Y., Nelson S., Pergami P., Darbari D.S., Gupta K, & He B. (2018). Graph theory analysis reveals how sickle cell disease impacts neural networks of patients with more severe disease. NeuroImage : Clinical, 21, 101599.

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EEG Data Processing and Component Analysis

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EEG recordings were obtained with NeuroScan system (NeuroScan, Inc., Herndon, VA, USA) from 32 electrodes positioned according to the 10/20 system and referenced to the bilateral mastoid with a bandpass filter of 0.05–30 Hz. An electrooculogram was recorded from electrodes placed below and lateral to the eyes. Curry 7 software was used for offline data processing (Compumedics, Abbotsford, Australia). The time window was chosen from –200 ms before stimulus onset (pre-stimulus 200 ms was used as the baseline) and 1800 ms after the stimulus. Blinks and other eye movement artifacts were removed using independent-component analyses. Six ERP components were separately analyzed based on previous research and our hypotheses. For the N1 and P2 components, the mean amplitudes were separately averaged at three centro-frontal electrodes (Fz, FCz, and Cz) in the 70–140 ms and 150–190 ms time windows, respectively; the same was applied for the EPN at two posterior electrodes (O1 and O2) in the 250–350 ms time window, and for the LPP at two centro-parietal electrodes (CPz and Pz) in the 320–800 ms interval, as well as for the CNV at the centro-frontal electrodes (Fz and FCz) from 250 ms to the end of the stimulus presentation.

Qu F., Shi X., Dai J., Gao T., Wang H, & Gu C. (2023). Dynamic and static angry faces influence time perception differently—Evidence from ERPs. Frontiers in Neuroscience, 17, 1124929.

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Bipolar Surface EMG Recordings of Arm Muscles

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Surface EMG signals were recorded by NeuroScan system (NeuroScan Inc., El Paso, TX, United States). Bipolar electrode pairs were placed longitudinally over the right BB and TB muscle bellies at an inter-electrode distance of 2 cm according to SENIAM recommendations¹. A common reference electrode was placed on the left mastoid. Skin was shaved and cleaned with alcohol to minimize impedance before applying the electrodes. The electrodes filled with conducting gel were secured with surgical tape. The EMG signals were amplified (×1,000), band pass filtered (3∼1,000 Hz), and digitized (2,000 samples/s). All logged data were stored on a computer for further analysis.

Wang L., Wang C., Yang H., Shao Q., Niu W., Yang Y, & Zheng F. (2022). Halo Sport Transcranial Direct Current Stimulation Improved Muscular Endurance Performance and Neuromuscular Efficiency During an Isometric Submaximal Fatiguing Elbow Flexion Task. Frontiers in Human Neuroscience, 16, 758891.

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EEG-based Brain-Computer Interface Protocol

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The skin of the participants was cleaned before the placement of electrodes according to the international registration system 10-20.²¹ A brain-computer interface (BCI) experimental platform was used to collect and process EEG data, as shown in Figure 1. EEG signals were collected by an embedded 32-channel EEG cap and Neuroscan system. The frontal lobe and occipital lobe were the regions of interest (ROI). Thirteen EEG electrodes in ROI as the interested electrodes, including FP1, FP2, F7, F3, FZ, F4, F8, FC3, FCZ, FC4, O1, OZ, and O2, were placed as shown in Figure 1.

Li Y., Shen L, & Sun M. (2022). Electroencephalography Study of Frontal Lobe Evoked by Dynamic Random-Dot Stereogram. Investigative Ophthalmology & Visual Science, 63(5), 7.

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EEG Analysis of Social Influence Effects

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Electroencephalographic (EEG) data were recoded while participants were completing the initial rating session. Participants sat comfortably in an electrically shielded room ∼80 cm from a computer screen. The EEG data were recorded with a 64-channel NeuroScan system (NeuroScan Inc, Herndon, VA). Raw EEG data were sampled at 1000 Hz/channel, with impedances < 5 kΩ. Online recordings were referenced to the nose, and re-referenced offline to the average bilateral mastoids. Vertical electrooculograms were recorded supra- and infra-orbitally at the left eye. Horizontal electrooculograms were recorded by electrodes at the left and right orbital rims. The online continuous data were digitized with a bandpass filter of 0.05–100 Hz.
EEG data were filtered with a low pass of 30 Hz (24 dB/oct) off-line. Epochs were locked to the normative feedback, beginning 200 ms before feedback onset to 600 ms after. Trials exceeding the threshold of ± 80 μV were excluded from further analysis. Trials without a response were excluded from both behavioral and EEG average analyses. To examine the effect of social influence, trials from three conditions (i.e. peers-agree, peers-higher, and peers-lower) were respectively averaged, and a −200 to 0 ms baseline was used to perform a baseline correction.

Feng C., Cao J., Li Y., Wu H, & Mobbs D. (2018). The pursuit of social acceptance: aberrant conformity in social anxiety disorder. Social Cognitive and Affective Neuroscience, 13(8), 809-817.

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