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Ni6122

Manufactured by National Instruments
5 citations
Sourced in United States
About the product

The NI6122 is a data acquisition (DAQ) device from National Instruments. It features 16-bit analog-to-digital conversion and can sample up to 1 million samples per second. The device provides multiple analog input channels for data collection and measurement applications.

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5 protocols using «ni6122»

1

Surface EMG Recording and Preprocessing

2024
Electromyographic (EMG) activity was recorded from the muscle belly of the right First Dorsal Interosseus (FDI) using silver/silver chloride surface electrodes (Neuroline 720-01-K, Ambu® A/S). The EMG signals were sampled at 4 kHz, pre-amplified (1000 × gain), and bandpass filtered between 5 Hz and 2 kHz. The data were digitized by a 16-bit data acquisition card (National Instruments, NI6122) and saved using custom-made Labview software (Mr. Kick, Knud Larsen, SMI, Aalborg University).
EMG activity was preprocessed offline using Matlab (The Math-Works, Natick, USA). First, the TMS stimulation artefact was removed and the voltage difference at the extremities of the segments was corrected before being merged. The resulting signal was bandpass filtered between 5 and 1000 Hz and notch filtered using a 2nd-order Butterworth filter.
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2

EMG Acquisition and Preprocessing Protocol

2024
Electromyographic (EMG) activity was recorded from the muscle belly of the right First Dorsal Interosseus (FDI) using silver/silver chloride surface electrodes (Neuroline 720-01-K, Ambu® A/S). The EMG signals were sampled at 4 kHz, pre-amplified (1000 × gain), and bandpass filtered between 5 Hz and 2 kHz. The data were digitized by a 16-bit data acquisition card (National Instruments, NI6122) and saved using custom-made Labview software (Mr. Kick, Knud Larsen, SMI, Aalborg University).
EMG activity was preprocessed offline using Matlab (The Math-Works, Natick, USA). First, the TMS stimulation artefact was removed and the voltage difference at the extremities of the segments was corrected before being merged. The resulting signal was bandpass filtered between 5 and 1000 Hz and notch filtered using a 2nd-order Butterworth filter.
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Corresponding organizations : Aalborg University, Tecnalia, Aarhus University, Royal Academy of Music, University Hospital Heidelberg, Central Institute of Mental Health

3

Transcranial Magnetic Stimulation of the FDI Muscle

2019
All TMS methods will be described in accordance with guidelines on reporting TMS methodology (Chipchase et al. 2012) . A focal figure-of-eight coil (D70 2 , Magstim Company, UK) was used to deliver monophasic TMS pulses supplied by a magnetic stimulator (Magstim BiStim 2 , Magstim Company, UK). The coil handle was pointing backwards, laterally and at a 45° angle to the sagittal plane, inducing a posterior-anterior directed current, to elicit TMS MEPs from the FDI muscle. An inter-stimulus interval of 6 s was used for all stimulations. The participants were fitted with a swimming cap and the optimal scalp position was marked on a predefined grid (1 × 1 cm squares orientated to vertex) to standardize orientation and location. The optimal scalp position (hotspot) for the FDI muscle was determined using 50% maximum stimulator output and defined as the site yielding consistent and highest peak-to-peak amplitude MEPs in three trials. The intensity needed to evoke MEPs of ~1 mV was tested by increasing and decreasing stimulus intensity until ~1 mV was consistently evoked in the FDI muscle (in 10 trials). This stimulation intensity was employed for the remaining of the experiment. For each assessment, fifteen MEPs were recorded from the right FDI muscle.
Surface electromyography (EMG) was recorded from the muscle belly of the FDI muscle using bipolar Ag/AgCl electrodes (Neuroline 720, Ambu® A/S, DK). Electrodes were placed with an approximate 20 mm interelectrode distance with the reference electrode located at the styloid process. The EMG data were pre-amplified (1000x gain), analogue band-pass filtered ( 5Hz-1 kHz) and sampled at 4 kHz by a 16-bit data-acquisition card (National Instruments, NI6122). Peak-to-peak MEPs were shown on-line by custom-made LabView software (Mr. Kick III, Aalborg University). Peak-to-peak amplitude was extracted for each MEP and averaged across the 15 recorded MEPs at each time point for further analysis.
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Corresponding organizations : Aalborg University, University of Maryland, Baltimore, Neuroscience Research Australia

4

Mapping Cortical Motor Representations with TMS

2018
Single-pulse transcranial magnetic stimulation (TMS) was delivered (Magstim 200 2 , Magstim Co.
Ltd) using a figure-of-eight shaped coil (D70 2 Coil, Magstim Co. Ltd). Participants were seated and maintained their hand and forearm relaxed with the wrist pronated throughout the experiment.
With a swimming cap marked with a 1 × 1 cm stimulation grid and orientated to the vertex of the head, the coil was located over the left hemisphere at a 45-degree angle to the sagittal plane to induce current in a posterior-to-anterior direction (Schabrun et al., 2016) (link). Using surface disposable silver/silver chloride adhesive recording electrodes (Ambu Neuroline 720) bipolar mounted in parallel with the muscle fibre, MEPs were recorded over the right ECRB muscle. The reference electrode was located on the right olecranon. MEP signals were band-pass filtered at 5 Hz -1 kHz, sampled at 2 kHz, and digitized by a 16-bit data-acquisition card (National Instruments, NI6122).
The optimal cortical site (hotspot) of the right ECRB muscle was determined as the coil position that evoked a maximal peak-to-peak MEP for a given stimulation intensity. At the beginning of each session on Day-0 and Day-5, two measures were collected at the hotspot: 1) Resting motor threshold (rMT), defined as the minimum stimulation intensity at which 5 out of 10 stimuli applied at the hotspot evoked a response with a peak-to-peak amplitude of a minimum 50 μV (Schabrun et al., 2016) (link). 2) Based on the MEPs of 10 stimuli at 120% of rMT at the hotspot site, the peak-to-peak amplitudes were extracted and averaged for analysis (Schabrun et al., 2016) (link).
Using a TMS intensity of 120% rMT, the motor cortical map was established based on MEPs evoked every 6 s with a total of 5 stimuli at each site on the stimulation grid (Schabrun et al., 2016; (link)De Martino et al., 2018) (link). All grid sites were pseudo randomly stimulated from the hotspot until no MEP was recorded (defined as <50 µV peak-to-peak amplitude) in all five stimuli at all border sites (Schabrun et al., 2016) (link). The number of active map sites (map area) and map volume were calculated off-line. If the average peak-to-peak amplitude of the 5 MEPs evoked at that site was greater than 50 μV, the site was considered 'active' (Schabrun & Ridding, 2007) (link). The averaged peak-to-peak MEP amplitudes at all active sites were summed to calculate the map volume. The center of gravity (CoG) was defined as the amplitude-weighted center of the map (Wassermann et al., 1992) and was calculated by ; where Vi represents mean MEP amplitude at each site with the coordinates Xi, Yi (Uy et al., 2002) . For each session, the average peak-to-peak MEP amplitude at all sites across subjects were linearly interpolated to generate the MEP maps used for illustration of group effects.
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Corresponding organizations : Aalborg University, University of Maryland, Baltimore, Western Sydney University

5

Surface EMG Recording for TMS-MEPs

2018
Surface electromyography (EMG) was recorded from the muscle belly of the ECR and FDI muscles with bipolar Ag/AgCl electrodes (Neuroline 720, Ambu® A/S, DK) placed with an approximate 20 mm interelectrode distance. The reference electrodes were placed at the styloideus processus (FDI) or the olecranon (ECR), both of the ulna. The EMG data were sampled at 4 kHz, preamplified (1000x gain), and analogue bandpass filtered at 5 Hz–1 kHz. EMG data were digitized by a 16-bit data acquisition card (National Instruments, NI6122; voltage: 10 V), and peak-to-peak TMS-MEPs were shown online by custom-made LabVIEW software (Mr. Kick III, SMI, Aalborg University).
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Corresponding organizations : Aalborg University

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