Towards the interpretability of deep learning models for multi-modal neuroimaging: Finding structural changes of the ageing brain.

Brain-age (BA) estimates based on deep learning are increasingly used as neuroimaging biomarker for brain health; however, the underlying neural features have remained unclear. We combined ensembles of convolutional neural networks with Layer-wise Relevance Propagation (LRP) to detect which brain features contribute to BA. Trained on magnetic resonance imaging (MRI) data of a population-based study (n = 2637, 18-82 years), our models estimated age accurately based on single and multiple modalities, regionally restricted and whole-brain images (mean absolute errors 3.37-3.86 years). We find that BA estimates capture ageing at both small and large-scale changes, revealing gross enlargements of ventricles and subarachnoid spaces, as well as white matter lesions, and atrophies that appear throughout the brain. Divergence from expected ageing reflected cardiovascular risk factors and accelerated ageing was more pronounced in the frontal lobe. Applying LRP, our study demonstrates how superior deep learning models detect brain-ageing in healthy and at-risk individuals throughout adulthood.

Relationship between regional white matter hyperintensities and alpha oscillations in older adults.

Aging is associated with increased white matter hyperintensities (WMHs) and with alterations of alpha oscillations (7-13 Hz). However, a crucial question remains, whether changes in alpha oscillations relate to aging per se or whether this relationship is mediated by age-related neuropathology like WMHs. Using a large cohort of cognitively healthy older adults (N = 907, 60-80 years), we assessed relative alpha power, alpha peak frequency, and long-range temporal correlations from resting-state EEG. We further associated these parameters with voxel-wise WMHs from 3T MRI. We found that a higher prevalence of WMHs in the superior and posterior corona radiata as well as in the thalamic radiation was related to elevated alpha power, with the strongest association in the bilateral occipital cortex. In contrast, we observed no significant relation of the WMHs probability with alpha peak frequency and long-range temporal correlations. Finally, higher age was associated with elevated alpha power via total WMH volume. We suggest that an elevated alpha power is a consequence of WMHs affecting a spatial organization of alpha sources.

Decoding subjective emotional arousal from EEG during an immersive virtual reality experience.

Immersive virtual reality (VR) enables naturalistic neuroscientific studies while maintaining experimental control, but dynamic and interactive stimuli pose methodological challenges. We here probed the link between emotional arousal, a fundamental property of affective experience, and parieto-occipital alpha power under naturalistic stimulation: 37 young healthy adults completed an immersive VR experience, which included rollercoaster rides, while their EEG was recorded. They then continuously rated their subjective emotional arousal while viewing a replay of their experience. The association between emotional arousal and parieto-occipital alpha power was tested and confirmed by (1) decomposing the continuous EEG signal while maximizing the comodulation between alpha power and arousal ratings and by (2) decoding periods of high and low arousal with discriminative common spatial patterns and a long short-term memory recurrent neural network. We successfully combine EEG and a naturalistic immersive VR experience to extend previous findings on the neurophysiology of emotional arousal towards real-world neuroscience.

Human emotions are complex and difficult to study. It is particularly difficult to study emotional arousal, this is, how engaging, motivating, or intense an emotional experience is. To learn how the human brain processes emotions, researchers usually show emotional images to participants in the laboratory while recording their brain activity. But viewing sequences of photos is not quite like experiencing the dynamic and interactive emotions people face in everyday life. New technologies, such as immersive virtual reality, allow individuals to experience dynamic and interactive situations, giving scientists the opportunity to study human emotions in more realistic settings. These tools could lead to new insights regarding emotions and emotional arousal. Hofmann, Klotzsche, Mariola et al. show that virtual reality can be a useful tool for studying emotions and emotional arousal. In the experiment, 37 healthy young adults put on virtual reality glasses and 'experienced' two virtual rollercoaster rides. During the virtual rides, Hofmann, Klotzsche, Mariola et al. measured the participants' brain activity using a technique called electroencephalography (EEG). Then, the participants rewatched their rides and rated how emotionally arousing each moment was. Three different computer modeling techniques were then used to predict the participant's emotional arousal based on their brain activity. The experiments confirmed the results of traditional laboratory experiments and showed that the brain's alpha waves can be used to predict emotional arousal. This suggests that immersive virtual reality is a useful tool for studying human emotions in circumstances that are more like everyday life. This may make future discoveries about human emotions more useful for real-life applications such as mental health care.

Impact of implantation depth on outcomes of new-generation balloon-expandable transcatheter heart valves.

BACKGROUND: Little is known about the impact of the ID on outcomes and device success using balloon-expandable devices. This study sought to analyze the impact of implantation depth (ID) on procedural outcomes. METHODS: In consecutive patients (n = 969) undergoing transfemoral TAVR with new-generation balloon-expandable prostheses, the mean ID (IDMean) was determined by aortography and categorized into low, correct, and high device position. Outcomes of interest were device success (VARC-2), paravalvular regurgitation (PVR) ≥ moderate, severe prosthesis-patient mismatch (PPM), permanent pacemaker implantation (PPI), and the composite of the three latter outcome measures (COMPPPP). RESULTS: IDMean was greater among patients with PPI (median 4.0 [interquartile range 2.0; 4.0] vs. 3.5 [1.5; 5.5] mm; p = 0.002), severe PPM (3.5 [1.5; 5.0] vs. 4.0 [2.0; 6.0] mm; p = 0.028), and COMPPPP (4.0 [2.0; 6.0] vs. 3.0 [1.5; 5.5] mm; p < 0.001) when compared with the respective groups without these complications. There was no significant association between IDMean and device success or PVR ≥ moderate. Categorization into low (7.3%), correct (90.7%), and high (2.0%) device position showed significant discrimination with an increase of severe PPM, PPI, and COMPPPP with lower position, whereas device success was not significantly affected by position. Only PVR ≥ moderate showed an asymmetric distribution with highest rates in the high and low position group, which was non-significant. However, among patients without correct position the rate of device success was 45.6%. CONCLUSIONS: A higher device position was associated with improved outcomes. Malpositioning without functional impairment should not be classified as device failure. The odds ratio of IDMean was calculated by univariate logistic regression for each outcome variable, showing that with higher values of IDMean (i.e., low implantation depth), the risk of severe PPM, PPI, and COMPPPP increases. The bar charts under the heading "Position category" denote the frequency of each outcome measure across patients with high, correct, and low device position. The p values are derived from chi-squared test.

Latest Developments in Robotic Percutaneous Coronary Intervention.

Interventional cardiovascular medicine has seen constant progress over the last few decades. Since the first angiograms and percutaneous transluminal coronary angioplasty were carried out, this progress has been tremendous and has led to a substantial decline in cardiovascular morbidity and mortality. The purpose of this article is to report and review the latest developments and evidence in robotics-assisted percutaneous coronary intervention (rPCI) and its potential future applications, opportunities, and limitations. Contemporary evidence shows that rPCI can lead to a significant reduction in radiation exposure as well as medical hazards for cardiologists. Rates of device and procedural success remain high and there is no evidence of a disadvantage for the patient. The accuracy of implantation with a reduced geographic mismatch is a further advantage that can result in a higher quality of treatment. Even in complex coronary lesions and procedures, rPCI seems to be safe and efficient. The latest developments include telestenting over hundreds of kilometers from a remote platform. Currently, the main limitations are the absence of large-scale randomized trials for the valid assessment of the benefits and disadvantages of rPCI as well as the technical limitations of the currently available rPCI systems. rPCI is a forward-looking innovation in cardiology that is applicable to a wide range of coronary interventions. Despite the present lack of knowledge and the limited data concerning the outcome for the patient, the available literature reveals promising results that should lead to improvements for physicians and patients.

Larch Bark as a Formaldehyde Scavenger in Thermal Insulation Panels.

The aim of this study is to investigate the formaldehyde content and emissions of bark-based insulation panels bonded with three types of adhesives: urea formaldehyde, melamine urea-formaldehyde, and tannin-based adhesives. These panels were produced at two levels of density-300 and 500 kg/m3-and a thickness of 20 mm, and the influence of the adhesive amount and type on the formaldehyde emissions and content was measured. Other mechanical and physical properties such as modulus of rupture, modulus of elasticity, internal bond, and dimensional stability were also scrutinized. With one exception, all the panels belonged to the super E0 classification for free formaldehyde content (perforator value ≤1.5 mg/100 g oven dry mass of panels). The measurements using the desiccator method for formaldehyde emissions assigned all the testing specimens in the F **** category for low-emission panels according to the Japanese International Standards.