Study design

This randomized, sham-controlled, and double-blind study was conducted at the Medical University of Vienna. Twelve healthy male participants with 18–35 years of age (mean age 26.50 years, SD = 5.00) that were right-handed and did not suffer from any neurological, psychiatric, or major somatic disease were recruited. For each participant, the study duration was seven weeks including one week pause between the two experimental blocks (3 weeks each, Fig. 1).

Fig. 1
figure1

Longitudinal study design. An experimental block lasted three weeks with magnetic resonance (MR) imaging and behavioral tasks (2-point orientation discrimination [23] and coin rotation [24]) one week before and after transcranial pulse stimulation (TPS). Each subject received one block with sham and one block with verum TPS (three sessions on consecutive days) using a within-subject crossover design and one week pause between the blocks

The baseline assessments in the 1 week of each block (week 1 and 5) comprised MR measurements and behavioral assessments of tactile and sensorimotor functions. In the second week of each block (week 2 and 6) three TPS interventions on three consecutive days were applied, either as real (verum) brain stimulation or as placebo (sham) stimulation. The MR and behavioral measurements were repeated in the third week of each block (week 3 and 7) to assess post-stimulation changes. Each subject received one block with sham and one block with verum TPS using a within-subject crossover design. The order of the experimental conditions was counterbalanced and randomly assigned. The experimenter applying TPS was informed about the actual condition (sham or verum), experimenters conducting MRI, safety evaluations, behavioral assessments, as well as data analysis were blinded.

Transcranial pulse stimulation (TPS)

TPS generates single ultrashort (3 µs) ultrasound pulses with typical energy flux densities of 0.2–0.3 mJ/mm2 and pulse repetition rates of 1–5 Hz (maximum spatial peak temporal average intensity ISPTA = 100 mW/cm2, maximum spatial peak pulse average intensity ISPPA = 111 W/cm2, maximum peak pressure = 25 MPa, mechanical index (MI) = 10.95). The ISPTA fulfils the DIN EN 61689 norm, and the maximum peak pressure lies well below tissue damaging pressure levels (40 MPa, [25]). The US Food and Drug Administration (FDA) guidelines only exist for diagnostic, but not for therapeutic ultrasound [26]. tFUS studies typically exceed diagnostic limits in one or more parameters [27]. While the ISPPA for TPS lies within the FDA limits for cephalic use (ISPPA = 190 W/cm2), the ISPTA is marginally higher (ISPTA = 94 mW/cm2) and the MI exceeds respective FDA limits (MI = 1.90) [26]. However, comprehensive animal studies exist for therapeutic ultrasound applications and have been used for the successful clinical certification process of TPS [13]. Indeed, TPS is clinically certified as therapy for Alzheimer’s disease (CE mark). Comprehensive simulations and measurements of the temporal-peak intensities for free water, human skull and brain sample are provided by our preceding work [11]. Figure 2a shows measurements of the temporal-peak intensities field of a pressure pulse trough a human skull bone demonstrating a high transversal resolution of the acoustic focus. The human skull produces a temporal-peak intensity drop of 80–90% [11] across the frequency spectrum (Fig. 2b).

Fig. 2
figure2

TPS pulse characterization. a Temporal-peak intensities (ITP) of a TPS pressure pulse through a human skull bone showing a highly focal transversal resolution of a few millimeters. b Fourier spectrum of a pressure pulse at TPS focus and under the skull demonstrating pressure attenuation through the skull across the frequency spectrum

For the current investigation, the TPS handpiece was fixed with the ultrasound beam focused on the cortical primary somatosensory representation of the right hand, in the left postcentral gyrus posterior to the individual sigmoidal hook sign (Fig. 3). The participants were seated in a comfortable armchair with the head laid on a restricting headrest. A tripod with a clamp was used to fix the handpiece to the participant’s head. Exact positioning was achieved by MR-based real-time neuronavigation including an infrared camera system that tracked the positions of the handpiece and the head of the participant via goggles affixed with infrared markers (Fig. 3). Plenty of bubble-free ultrasound gel (Aquasonic Clear, Parker Laboratories) had to be applied to cover the skin and hair at the stimulation area to avoid acoustic impedance borders. Using TPS parameters as defined by a pilot experiment [11], 1000 TPS pulses (energy flux density = 0.25 mJ/mm2, pulse repetition rate = 4 Hz) were applied in each TPS session that lasted approximately 4 min. Sham stimulation was achieved by blocking the ultrasound beam with a sham cap on the TPS handpiece that looked identical and produced a similar knocking sound as the verum stimulation. After each TPS session, participants were asked about sensations, potential side effects and a subjective estimation if sham or verum TPS was applied.

Fig. 3
figure3

Focal transcranial pulse stimulation (TPS). TPS setup included a pulse generator device, a touch screen for real-time neuronavigation and an infrared camera system tracking the positions of the handpiece and the head of the participant via goggles affixed with infrared markers (left). The TPS handpiece was fixed using a tripod with a clamp focusing the ultrasound beam on the cortical primary somatosensory representation of the right hand, in the left postcentral gyrus posterior to the individual sigmoidal hook sign (marked by a turquoise circle). The TPS pulses of one session in a representative subject are displayed on the reconstructed head surface and in top, front and left orientation of the individual brain anatomy, showing the lowest (green) to highest pulse density (magenta)

Structural MRI

MR measurements were conducted at a 3 Tesla Siemens Prisma MR scanner using a 64-channel head coil and comprised anatomical, functional resting state, diffusion-tensor imaging (DTI), as well as clinical standard scans. Brain structural anatomy was assessed using a T1-weighted MPRAGE sequence with a spatial resolution of 1 mm isotropic (TE/TR = 2.7/1800 ms, inversion time = 900 ms, flip angle = 9°). These anatomical scans were used for TPS neuronavigation and for volumetric analyses (voxel-based morphometry, VBM). A T2-weighted fluid-attenuated inversion recovery (FLAIR) sequence (TE/TR = 100/10000 ms, inversion time = 2500 ms, flip angle = 160°) and a T2-weighted 2D-fast-low-angle shot (FLASH) sequence (TE/TR = 19.9/690 ms, flip angle = 20°) were applied to detect potential lesions, edemas or bleedings.

VBM analyses were performed using the SPM toolbox Computational Anatomy Toolbox CAT12 (http://www.neuro.uni-jena.de/cat/). VBM preprocessing included segmentation for longitudinal data, an estimation of the total intracranial volume, and smoothing (8 mm FWHM kernel) using CAT12 default values. On second level, segmented data were compared between the post stimulation sessions (referenced to the respective pre stimulation scan) with the intracranial volume as a covariate to account for different brain sizes. VBM analysis was applied to whole-brain data as well as for the grey matter volume within regions of interest (ROIs) of the Neuromophometrics atlas implemented in CAT12.

Resting state functional connectivity

For the resting state scan, a whole-brain T2*-weighted gradient-echo-planar imaging (EPI) sequence was applied (TE/TR = 35/1400 ms, flip angle = 90°, in-plane acceleration = GRAPPA 2, multiband acceleration factor = 2, resolution = 2 mm isotropic). During the resting state measurement, the participants were required to think of nothing in particular while fixating a visually presented cross. The resting state scan lasted approximately 10 min (430 volumes). Resting state data analyses were performed with the CONN toolbox v19c [28] and included default preprocessing comprising realignment, unwarping, slice-time correction, structural segmentation, normalization, outlier detection (ART-based scrubbing) and smoothing (8 mm FWHM kernel). Denoising was achieved using a band-pass filter [0.008–0.09 Hz], removal of motion confounds (6 motion parameters and their first derivatives), removal of white matter and cerebrospinal fluid signals (five principal components extracted from the cerebrospinal fluid and the white matter masks) and scrubbing. For first level analysis, a bivariate correlation of the corrected time series of all voxels was calculated. On second level, the graph theoretical measure global efficiency (GE) was analyzed for the left- and right-lateralized sensorimotor network. GE is defined as the inverse of the shortest path length between each pair of nodes of the network and represents the capacity for parallel information processing within a network [29]. The sensorimotor network comprised the primary motor and somatosensory cortex (precentral and postcentral gyri), the secondary somatosensory cortex (left parietal operculum [30]), and higher-order somatosensory integration areas (superior parietal lobe, supramarginal and angular gyri, superior lateral occipital cortex). These anatomical ROIs were defined according to the Harvard–Oxford-atlas as implemented in the CONN toolbox. On group level, global efficiency was compared between the post stimulation sessions referenced to the respective pre stimulation scans (correlation coefficient 0.35, false discovery rate (FDR) 0.05 corr.).

Diffusion tensor imaging (DTI)

DTI data were acquired using a whole-brain 64-direction EPI sequence (TE/TR = 95/10500 ms, multiband acceleration factor = 2, resolution = 2 mm isotropic, b-value = 1000 s/mm2). DTI indices fractional anisotropy (FA), mean diffusivity (MD), as well as axial (AD) and radial diffusivity (RD) were investigated to comprehensively assess alterations of the white matter microstructure on a whole-brain level and within sensorimotor ROIs. FA is a measure for the coherence of water diffusion direction with higher values indicating better white matter integrity [31, 32]⁠. MD is the mean rate of free water diffusion independent of the directionality [32]. AD measures the rate of water diffusion along the principal axis of diffusion, i.e., the underlying fiber orientation, and reflects axon number and caliper [33]⁠, while RD is the magnitude of water diffusion perpendicular to the white matter tract indicating myelin changes [34]. Intact neuronal microstructures, such as axonal cell membranes and myelin sheaths, displace intra- and extracellular water leading to lower MD, AD and RD values [31, 32]⁠.

DTI data preprocessing and statistical analyses were performed using FSL 5.0.9 and related toolboxes. Data preprocessing included extraction of brain tissue from the b0 volume using the FSL Brain Extraction Tool (BET, threshold 0.1), eddy current correction using the FMRIB’s Diffusion Toolbox 3.0 and smoothing of DTI images using fslmaths with a 1-voxel box kernel an the f-median flag as recommended for longitudinal data [35]. Subsequently, DTI indices were reconstructed using DTI-FIT. The resulting images were further processed with Tract-based Spatial Statistics (TBSS) [36]. After the removal of outliers, the FA images of all four sessions of a participant were coregistered to a subject-specific template using the TBSS registration with the -n flag option. Subsequently, the coregistered images were normalized to MNI standard space using FMRIB58_FA template. The resulting mean FA map was thinned to create an average white matter tract skeleton using the default threshold 0.2 and individual FA values were projected onto the mean skeleton (Fig. 4a). By using the registration and skeletonization warps as well as the skeleton projection vectors derived from the TBSS processing of the FA images, the MD, AD and RD images were similarly processed.

Fig. 4
figure4

Diffusion tensor imaging (DTI) analysis. a For whole-brain white matter data analysis the Tract-based Spatial Statistics (TBSS) white matter skeleton (green) was used. b For the regions of interest analysis, left primary somatosensory (S1, blue) and the left primary motor (M1, orange) white matter regions, derived from the Human Sensorimotor Tracts Labels atlas, were used

Statistical evaluation of all DTI indices projected onto the white matter skeleton was done using FSL randomise with the threshold-free cluster enhancement option (5000 permutations, family-wise error (FWE) 0.05 corr.). As for within-subject comparisons using FSL randomise a one-sample t-test against 0 is recommended, the contrast of interest [(verum post vs. verum pre) vs. (sham post vs. sham pre)] was computed with fslmaths first. For the ROI-analyses of DTI indices, the Human Sensorimotor Tracts Labels [37] implemented in FSLeyes was used to create the left primary somatosensory (S1) and left primary motor (M1) white matter ROIs (Fig. 4b). The accurate location of these ROIs was visually inspected by overlaying the ROIs on the individual white matter segments derived from the SPM segmentation procedure. The mean values for FA, MD, AD, and RD were extracted within these ROIs and statistically analyzed using SPSS v26. As ROI data were not normally distributed, a non-parametric Wilcoxon test was applied to compare pre- and post-stimulation values for both conditions (FDR 0.05 corr.).

Behavioral assessments

After the MR measurements, behavioral assessments of tactile and sensorimotor functions were performed. The tactile spatial discrimination threshold was measured using a 2-point orientation discrimination task [23]. Here, a caliper with a given tip separation distance was applied at the participant’s thenar eminence of the right hand in either horizontal or vertical orientation. The participant was not able to see the caliper and should indicate if the horizontally oriented stimulus preceded or followed the vertical stimulus. Nine distances between 0 and 10 mm (each repeated eight times) were tested in randomized order. The proportion of correct responses was assessed and the spatial threshold for 75% correct responses served as the main outcome variable. After the 2-point orientation discrimination task, the participants underwent a coin rotation task as a measure for manual dexterity and sensorimotor processing [24]. The coin rotation task was shown to be related to functional activation in the primary somatosensory cortex [38] and predicts fine hand movements relevant for activities of daily living [39]. The subjects were asked to flip a 2€ coin along the horizontal axis with their right hand as fast as possible and time needed for 20 coin turns (180 degree flips) was recorded. Behavioral tasks were tested and validated in ten pilot subjects beforehand. Behavioral data were analyzed with SPSS v26 using a factorial design with the within-subject factors condition (sham/verum) and session (pre/post stimulation).

Correlation analyses

The relations between neurophysiological measures demonstrating a TPS effect and behavioral scores (2-point-orientation discrimination, coin rotation) were examined by correlation analyses. As data were not normally distributed, a non-parametric Spearman’s rank correlation analysis was applied. Previous literature demonstrated an non-linear relation between age and DTI indices [40]. To account for this potentially confounding between-subject difference, age was controlled for by applying a partial Spearman’s correlation analysis.

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