fMRI during lower body negative pressure (LBNP) with concurrent physiological measurements

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.

Data acquisition
MRI data
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)

fMRI data preprocessing
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.

Physiological data
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

Subject information
01    m    21 a    182 cm    73 kg    129/62 mmHg
02    f    18 a    167 cm    55 kg    104/58 mmHg
03    m    27 a    200 cm    92 kg    127/62 mmHg
04    f    22 a    160 cm    59 kg    120/73 mmHg
05    f    21 a    170 cm    62 kg    125/67 mmHg
06    f    22 a    171 cm    56 kg    130/70 mmHg
07    f    22 a    174 cm    55 kg    119/61 mmHg
08    f    37 a    171 cm    82 kg    130/71 mmHg
09    m    25 a    170 cm    72 kg    129/62 mmHg
10    f    21 a    173 cm    58 kg    116/71 mmHg
11    m    30 a    185 cm    113 kg    125/65 mmHg
12    f    27 a    157 cm    48 kg    127/76 mmHg
13    m    21 a    184 cm    70 kg    127/80 mmHg
14    f    26 a    173 cm    63 kg    120/68 mmHg
15    m    24 a    200 cm    92 kg    129/72 mmHg
16    m    38 a    196 cm    86 kg    133/67 mmHg
17    m    24 a    186 cm    76 kg    125/65 mmHg
18    f    19 a    178 cm    69 kg    102/53 mmHg
19    f    18 a    168 cm    60 kg    125/66 mmHg
20    f    26 a    171 cm    63 kg    122/70 mmHg
21    f    20 a    175 cm    62 kg    122/76 mmHg
22    f    24 a    169 cm    58 kg    114/64 mmHg

Missing data

 sub01: physio.acq and physio_cuts.txt

sub14: func_3 has 209 time points

sub15: func_2 has 167 time points

Data structure
Raw data

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)

Templates and masks

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

JPreprocessing
Preprocessing pipeline