Brainamp exg

Electromyographic activity was recorded (Brainamp ExG, BrainProducts) by electrodes placed in a belly-tendon montage at the contralateral first dorsal interosseous muscle (FDI) using silver/silver-chloride self-adhesive surface electrodes (Neuroline 700, Ambu). EMG was sampled at 5 kHz with a time constant of 10 s and a high cutoff of 1 kHz. Offline, data were downsampled to 500 Hz and high pass filtered at 20 Hz (48 dB/Oct). Segmentation and baseline correction were carried out identical to the EEG processing (see section EEG above). Next, data were averaged across subjects and conditions. MEPs were quantified as the peak-to-peak amplitude within 18–40 ms after the TMS pulse.

EEG via a cap (modified BrainCapMR, Easycap) was recorded continuously during fMRI acquisition (1505 volumes of T2*-weighted echo planar images, TR/TE = 2080 ms/30 ms, matrix 64 × 64, voxel size 3 × 3 × 2 mm³, distance factor 50%; FOV 192 mm²) at 3T (Siemens Trio). An optimized polysomnographic setting was employed [chin and tibial EMG, ECG, EOG recorded bipolarly (sampling rate 5 kHz, low pass filter 1 kHz) with 30 EEG channels recorded with FCz as the reference (sampling rate 5 kHz, low pass filter 250 Hz); pulse oxymetry and respiration were recorded via sensors from the Trio (sampling rate 50 Hz)] and MR scanner compatible devices (BrainAmp MR+, BrainAmpExG; Brain Products), facilitating sleep scoring during fMRI acquisition (AASM, 2007 ; Jahnke et al., 2012 (link)). MRI and pulse artifact correction were performed based on the average artifact subtraction (AAS) method (Allen et al., 1998 (link)) as implemented in Vision Analyzer2 (Brain Products) followed by objective (CBC parameters, Vision Analyzer) ICA-based rejection of residual artifact-laden components after AAS resulting in EEG with a sampling rate of 250 Hz (Jahnke et al., 2012 (link)). EEG artifacts due to motion were detected and eliminated using an ICA procedure implemented in Vision Analyzer2. Sleep stages were scored manually by an expert according to the AASM criteria (AASM, 2007 ).

To estimate autonomic nervous system reactivity during the study protocol, a standard three-lead ECG signal was digitally recorded with a sample rate of 1000 Hz employing a BrainAmp ExG bio signal amplifier system (Brain Products, Munich, Germany). Inter-beat-interval times (RR) were derived from the raw digital signal by means of a robust peak detection algorithm, implemented in MATLAB (MathWorks, Inc., Natick MA, USA). Ectopic heart beats and passages of disturbed ECG signal due to movement artifacts were deleted upon visual inspection. The missing RR intervals in the resulting gaps were estimated using a cubic Hermite spline interpolation technique.

Participants were seated in a chair facing a computer screen at a distance of ∼1 m. They were asked to place their hands in their lap and to position their right foot to the right of a 10 × 20 cm floor-mounted switch pedal (Marquardt Mechatronik GmbH). Throughout the experiment, EEG was recorded at 1 kHz with a 64-electrode Ag/AgCl cap (EasyCap, Brain Products GmbH) mounted according to the 10–20 system, referenced to FCz and re-referenced offline to a common average. EEG was recorded from the following 51 electrodes: AF7, AF3, Fpz, AF4, AF8, FT7, F5, F3, F1, Fz, F2, F4, F6, FT8, FC5, FC3, FC1, FC2, FC4, FC6, C5, C3, C1, Cz, C2, C4, C6, CP5, CP3, CP1, CPz, CP2, CP4, CP6, TP7, P5, P3, P1, Pz, P2, P4, P6, TP8, PO3, PO1, POz, PO2, PO2, O1, Oz, O2. In order to obtain the earliest measure of movement onset, 3D acceleration of the right leg was recorded with an accelerometer (Brain Products GmbH) that was attached with an elastic band to the right calf. The amplified signal (analog filters: 0.1, 250 Hz) was converted to digital (BrainAmp MR Plus and BrainAmp ExG, Brain Products GmbH), saved for offline analysis, and simultaneously processed online by the Berlin Brain-Computer Interface toolbox (BBCI; https://github.com/bbci/bbci_public). The Pythonic Feedback Framework (Venthur et al., 2010 (link)) was used to generate visual feedback.

Simultaneous fMRI and EEG was measured for a total of 73 subjects EEG via a cap (modified BrainCapMR, Easycap, Herrsching, Germany) was recorded continuously during fMRI acquisition (1505 volumes of T2*-weighted echo planar images, TR/TE  =  2080 ms/30 ms, matrix 64 × 64, voxel size 3 × 3 × 2 mm³, distance factor 50%; FOV 192 mm2) with a 3 T Siemens Trio (Erlangen, Germany). An optimized polysomnographic setting was employed (chin and tibial EMG, ECG, EOG recorded bipolarly [sampling rate 5 kHz, low pass filter 1 kHz] with 30 EEG channels recorded with FCz as the reference [sampling rate 5 kHz, low pass filter 250 Hz]. Scalp potentials measured with EEG allow the classification of sleep into 4 stages (wakefulness, N1, N2 and N3 sleep) according to the American Academy of Sleep Medicine (AASM) rules (54). Pulse oximetry and respiration were recorded via sensors from the Trio [sampling rate 50 Hz]) and MR scanner compatible devices (BrainAmp MR+, BrainAmpExG; Brain Products, Gilching, Germany), facilitating sleep scoring during fMRI acquisition. We selected 15 subjects who reached stage N3 sleep (deep sleep) and contiguous time series of least 200 volumes for all sleep stages. Previous publications based on this dataset can be consulted for further details (see, e.g., [68 (link)]).