DOI: 10.5281/zenodo.3885042
title: fMRI during lower body negative pressure (LBNP) with concurrent physiological measurements

description: This dataset was acquired at Hannover Medical School, Hanover, Germany. The study complied with the Declaration of Helsinki, and was approved by the local ethics committee (# 3404-2016). All subjects gave written informed consent, and consent to publish their data anonimously. We simulated orthostatic stress by means of lower body negative pressure (LBNP). Negative pressure of 30 mmHg was built up inside a custom-made polycarbonate chamber using a vacuum cleaner and a pressure gauge. The stimulation paradigm consisted of four alternating five-minute blocks, two with and two without negative pressure, starting with the negative pressure. Functional MR images and physiological measures were continuously acquired during this cardiovascular challenge. Transitions between pressure states were excluded to avoid excessive movement. <strong>Data acquisition</strong><br> <em>MRI data</em><br> All MR images were acquired on a Siemens 3T MAGNETOM Skyra using a 64-channel head/neck coil. The scanning protocol consisted of the following sequences (see Sequences.ods): func_i: Functional whole brain gradient-echo echo-planar images (EPI) (TR=1230 ms; TE=32 ms; 2mm isotropic resolution; simultaneous multi-slice factor=6; partial Fourier=7/8; 4x233 volumes) func_ref: Reference scan for motion correction and template formation; equivalent to func but without multi-band acceleration (TR=7530 ms) SE_AP_PA: Reference scans for unwarping: Two spin-echo images matched to func in distortion without multi-band acceleration; one with the same, the other one with inverted phase encoding direction. t1: T1-weighted magnetisation-prepared rapid acquisition gradient-echo image (MPRAGE) (TR=2300 ms; TE=2.95 ms; TI=900 ms; resolution: 1.1x1.1x1.2 mm3, in-plane acceleration factor=2) <em>fMRI data preprocessing</em><br> Our preprocessing pipleine (JPreprocessing) is optimised for the brainstem and hypothalamus by avoiding superfluous resampling steps and unnecessary smoothing. On that account, motion correction (MCFLIRT (Jenkinson et al., 2002)) and unwarping (topup (Andersson et al.,2003)) are applied in a single transformation. Afterwards, brain extraction (BET (Smith, 2002)), grand mean scaling and high pass filtering (0.005 Hz) are applied. The data are not smoothed. Two study templates were generated using Advanced Normalization Tools (ANTs (Avants et al., 2008) using antsMultivariateTemplateConstruction2.sh). The first one using the unwarped EPI reference images (func_ref); the second one using the T1-images. <br> <em>Physiological data</em><br> The following physiological measures were acquired with an MR-compatible BIOPAC MP150 system Blood pressure (systolic and dyastolic): Non-invasive continuous blood pressure of the digital artery (pulse decomposition analysis using CareTaker) Electrodermal activity Photoplethysmography Respiration (belt) Electrocardiography <br> <em>Subject information</em><br> 01 m 21 a 182 cm 73 kg 129/62 mmHg<br> 02 f 18 a 167 cm 55 kg 104/58 mmHg<br> 03 m 27 a 200 cm 92 kg 127/62 mmHg<br> 04 f 22 a 160 cm 59 kg 120/73 mmHg<br> 05 f 21 a 170 cm 62 kg 125/67 mmHg<br> 06 f 22 a 171 cm 56 kg 130/70 mmHg<br> 07 f 22 a 174 cm 55 kg 119/61 mmHg<br> 08 f 37 a 171 cm 82 kg 130/71 mmHg<br> 09 m 25 a 170 cm 72 kg 129/62 mmHg<br> 10 f 21 a 173 cm 58 kg 116/71 mmHg<br> 11 m 30 a 185 cm 113 kg 125/65 mmHg<br> 12 f 27 a 157 cm 48 kg 127/76 mmHg<br> 13 m 21 a 184 cm 70 kg 127/80 mmHg<br> 14 f 26 a 173 cm 63 kg 120/68 mmHg<br> 15 m 24 a 200 cm 92 kg 129/72 mmHg<br> 16 m 38 a 196 cm 86 kg 133/67 mmHg<br> 17 m 24 a 186 cm 76 kg 125/65 mmHg<br> 18 f 19 a 178 cm 69 kg 102/53 mmHg<br> 19 f 18 a 168 cm 60 kg 125/66 mmHg<br> 20 f 26 a 171 cm 63 kg 122/70 mmHg<br> 21 f 20 a 175 cm 62 kg 122/76 mmHg<br> 22 f 24 a 169 cm 58 kg 114/64 mmHg <br> <em>Missing data</em> sub01: physio.acq and physio_cuts.txt sub14: func_3 has 209 time points sub15: func_2 has 167 time points <strong>Data structure</strong><br> <em>Raw data</em> acqparams.txt: Acquisition parameters needed for topup func_i: raw functional data (dummy volumes already deleted) func_ref: Reference image for motion correction and template generation physio.acq: Physiological measurements Trigger Blood pressure (systolic and dyastolic) Electrodermal activity Photoplethysmogram Respiration Electrocardiogram physio_cuts.txt: time points in the physio data that correspond to fMRI blocks (start-time end-time TR #volumes) SE_AP_PA: auxiliary image for unwarping slicetiming_i.txt: Slice timing information in seconds t1: Defaced T1-weighted image. (Undefaced images were used for template generation) <br> <em>Templates and masks</em> EPI-template: Generated from unwarped func_ref images Transformations for all subjects (can be applied using antsApplyTransforms) wb_mask EPI-2-T1: Transformation from EPI to T1-template MNI-template: T1-template warped into MNI_152 hyp_mask lower_bs_mask T1-template: Generated from t1 images hyp_mask lower_bs_mask T1-2-MNI: Transformation from T1 to MNI_152-template <br> <em>JPreprocessing</em><br> Preprocessing pipeline