Journal articles

Background - Transcranial direct current stimulation (tDCS), a neuromodulatory non-invasive brain stimulation technique, has shown promising results in basic and clinical studies. The known interindividual variability of the effects, however, limits the efficacy of the technique. Recently we reported neurophysiological effects of tDCS applied over the primary motor cortex at the group level, based on data from twenty-nine participants who received 15min of either sham, 0.5, 1.0, 1.5 or 2.0 mA anodal, or cathodal tDCS. The neurophysiological effects were evaluated via changes in: 1) transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEP), and 2) cerebral blood flow (CBF) measured by functional magnetic resonance imaging (MRI) via arterial spin labeling (ASL). At the group level, dose-dependent effects of the intervention were obtained, which however displayed interindividual variability. - Method - In the present study, we investigated the cause of the observed inter-individual variability. To this end, for each participant, a MRI-based realistic head model was designed to 1) calculate anatomical factors and 2) simulate the tDCS- and TMS-induced electrical fields (EFs). We first investigated at the regional level which individual anatomical factors explained the simulated EFs (magnitude and normal component). Then, we explored which specific anatomical and/or EF factors predicted the neurophysiological outcomes of tDCS. - Results - The results highlight a significant negative correlation between regional electrode-to-cortex distance (rECD) as well as regional CSF (rCSF) thickness, and the individual EF characteristics. In addition, while both rCSF thickness and rECD anticorrelated with tDCS-induced physiological changes, EFs positively correlated with the effects. - Conclusion - These results provide novel insights into the dependency of the neuromodulatory effects of tDCS on individual physical factors.

Magnetic particle imaging (MPI) is a tomographic imaging method to determine the spatial distribution of magnetic nanoparticles (MNP) within a defined volume. To evaluate the spatio-temporal resolution of existing MPI scanners, enabling the consistent comparison of the performance of different scanner setups, we developed dynamic MPI measurement phantoms based on segmented flow. These segmented flow phantoms comprise a defined bolus of ferrofluid tracer material, which can be pumped through a tube system with defined velocities. Using a hydrophobic organic carrier oil, cylindrically shaped boluses of different diameter, length, and flow velocity can be emulated. Moving boluses were imaged by different MPI scanner types and the correlation of spatial resolution und velocity of the bolus was investigated. For all bolus dimension and flow velocity combinations investigated, we observed a decreasing spatial resolution and increasing blurring for increasing bolus velocity and decreasing bolus volume.

Digital plant images are becoming increasingly important. First, given a large number of images deep learning algorithms can be trained to automatically identify plants. Second, structured image-based observations provide information about plant morphological characteristics. Finally in the course of digitalization, digital plant collections receive more and more interest in schools and universities.