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INTRODUCTION Neurofeedback based on functional magnetic resonance imaging allows for learning voluntary control over one's own brain activity, aiming to enhance cognition and clinical symptoms. We previously reported improved sustained attention temporarily by training healthy participants to up-regulate the differential activity of the sustained attention network minus the default mode network (DMN). However, the long-term brain and behavioral effects of this training have not yet been studied. In general, despite their relevance, long-term learning effects of neurofeedback training remain under-explored. METHODS Here, we complement our previously reported results by evaluating the neurofeedback training effects on functional networks involved in sustained attention and by assessing behavioral and brain measures before, after, and 2 months after training. The behavioral measures include task as well as questionnaire scores, and the brain measures include activity and connectivity during self-regulation runs without feedback (i.e., transfer runs) and during resting-state runs from 15 healthy individuals. RESULTS Neurally, we found that participants maintained their ability to control the differential activity during follow-up sessions. Further, exploratory analyses showed that the training increased the functional connectivity between the DMN and the occipital gyrus, which was maintained during follow-up transfer runs but not during follow-up resting-state runs. Behaviorally, we found that enhanced sustained attention right after training returned to baseline level during follow-up. CONCLUSION The discrepancy between lasting regulation-related brain changes but transient behavioral and resting-state effects raises the question of how neural changes induced by neurofeedback training translate to potential behavioral improvements. Since neurofeedback directly targets brain measures to indirectly improve behavior in the long term, a better understanding of the brain-be

Background Teledermatology is currently finding its place in modern health care worldwide as a rapidly evolving field. Objective The aim of this study was to investigate the acceptance of teledermatology compared to in-person consultation from the perspective of patients and professionals. Methods This multicenter, cross-sectional pilot study was performed at secondary and tertiary referral centers of dermatology in Switzerland from August 2019 to January 2020. A customized questionnaire addressing demographics and educational data, experience with telemedicine, and presumed willingness to replace in-patient consultations with teledermatology was completed by dermatological patients, dermatologists, and health care workers in dermatology. Results Among a total of 664 participants, the ones with previous telemedicine experience (171/664, 25.8%) indicated a high level of overall experience with it (patients: 73/106, 68.9%, dermatologists: 6/8, 75.0%, and health care workers: 27/34, 79.4%). Patients, dermatologists, and health care workers were most likely willing to replace in-person consultations with teledermatology for minor health issues (353/512, 68.9%; 37/45, 82.2%; and 89/107, 83.2%, respectively). We observed a higher preference for telemedicine among individuals who have already used telemedicine (patients: P<.001, dermatologists: P=.03, and health care workers, P=.005), as well as among patients with higher educational levels (P=.003). Conclusions This study indicates that the preference for teledermatology has a high potential to increase over time since previous experience with telemedicine and a higher level of education were associated with a higher willingness to replace in-patient consultations with telemedicine. We assume that minor skin problems are the most promising issue in teledermatology. Our findings emphasize the need for dermatologists to be actively involved in the transition to teledermatology. Trial Registration ClinicalTrials.gov NCT04495

Fundamental human feelings such as body ownership (“this” body is “my” body) and vicariousness (first-person-like experience of events occurring to others) are based on multisensory integration. Behavioral links between body ownership and vicariousness have been shown, but the neural underpinnings remain largely unexplored. To fill this gap, we investigated the neural effects of altered body ownership on vicarious somatosensation. While recording functional brain imaging data, first, we altered participants’ body ownership by robotically delivering tactile stimulations (“tactile” stroking) in synchrony or not with videos of a virtual hand being brushed (“visual” stroking). Then, we manipulated vicarious somatosensation by showing videos of the virtual hand being touched by a syringe’s plunger (touch) or needle (pain). Only after the alteration of body ownership (synchronous visuo-tactile stroking) and specifically during late epochs of vicarious somatosensation, vicarious pain was associated with lower activation in premotor and anterior cingulate cortices with respect to vicarious touch. At the methodological level, the present study highlights the importance of the neural response’s temporal evolution. At the theoretical level, it shows that the higher-level (cognitive) impact of a lower-level (sensory) body-related processing (visuo-tactile) is not limited to body ownership but also extends to other psychological body-related domains, such as vicarious somatosensation.

Reviews and meta-analyses have proved to be fundamental to establish neuroscientific theories on intelligence. The prediction of intelligence using invivo neuroimaging data and machine learning has become a widely accepted and replicated result. We present a systematic review of this growing area of research, based on studies that employ structural, functional, and/or diffusion MRI to predict intelligence in cognitively normal subjects using machine learning. We systematically assessed methodological and reporting quality using the PROBAST and TRIPOD in 37 studies. We observed that fMRI is the most employed modality, resting-state functional connectivity is the most studied predictor. A meta-analysis revealed a significant difference between the performance obtained in the prediction of general and fluid intelligence from fMRI data, confirming that the quality of measurement moderates this association. Studies predicting general intelligence from Human Connectome Project fMRI averaged r = 0.42 (CI95% = [0.35, 0.50]) while studies predicting fluid intelligence averaged r = 0.15 (CI95% = [0.13, 0.17]). We identified virtues and pitfalls in the methods for the assessment of intelligence and machine learning. The lack of treatment of confounder variables and small sample sizes were two common occurrences in the literature which increased risk of bias. Reporting quality was fair across studies, although reporting of results and discussion could be vastly improved. We conclude that the current literature on the prediction of intelligence from neuroimaging data is reaching maturity. Performance has been reliably demonstrated, although extending findings to new populations is imperative. Current results could be used by future works to foment new theories on the biological basis of intelligence differences.

At the early stages of the COVID-19 outbreak in 2020, Switzerland was among the countries with the highest number of SARS-CoV2-infections per capita in the world. Lockdowns had a remarkable impact on primary care access and resulted in postponed cancer screenings. The aim of this study was to investigate the effects of the COVID-19 lockdown on the diagnosis of melanomas and stage of melanomas at diagnosis. In this retrospective, exploratory cohort study, 1240 patients with a new diagnosis of melanoma were analyzed at five tertiary care hospitals in German-speaking Switzerland over a period of two years and three months. We compared the pre-lockdown (01/FEB/19–15/MAR/20, n = 655) with the lockdown (16/MAR/20–22/JUN/20, n = 148) and post-lockdown period (23/JUN/20–30/APR/21, n = 437) by evaluating patients’ demographics and prognostic features using Breslow thickness, ulceration, subtype, and stages. We observed a short-term, two-week rise in melanoma diagnoses after the major lift of social lockdown restrictions. The difference of mean Breslow thicknesses was significantly greater in older females during the lockdown compared to the pre-lockdown (1.9 ± 1.3 mm, p = 0.03) and post-lockdown period (1.9 ± 1.3 mm, p = 0.048). Thickness increase was driven by nodular melanomas (2.9 ± 1.3 mm, p = 0.0021; resp. 2.6 ± 1.3 mm, p = 0.008). A proportional rise of advanced melanomas was observed during lockdown (p = 0.047). The findings provide clinically relevant insights into lockdown-related gender- and age-dependent effects on melanoma diagnosis. Our data highlight a stable course in new melanomas with a lower-than-expected increase in the post-lockdown period. The lockdown period led to a greater thickness in elderly women driven by nodular melanomas and a proportional shift towards stage IV melanoma. We intend to raise awareness for individual cancer care in future pandemic management strategies.

Neurofeedback training has been shown to influence behavior in healthy participants as well as to alleviate clinical symptoms in neurological, psychosomatic, and psychiatric patient populations. However, many real-time fMRI neurofeedback studies report large inter-individual differences in learning success. The factors that cause this vast variability between participants remain unknown and their identification could enhance treatment success. Thus, here we employed a meta-analytic approach including data from 24 different neurofeedback studies with a total of 401 participants, including 140 patients, to determine whether levels of activity in target brain regions during pretraining functional localizer or no-feedback runs (i.e., self-regulation in the absence of neurofeedback) could predict neurofeedback learning success. We observed a slightly positive correlation between pretraining activity levels during a functional localizer run and neurofeedback learning success, but we were not able to identify common brain-based success predictors across our diverse cohort of studies. Therefore, advances need to be made in finding robust models and measures of general neurofeedback learning, and in increasing the current study database to allow for investigating further factors that might influence neurofeedback learning.

The brain regions supporting sustained attention (sustained attention network; SAN) and mind-wandering (default-mode network; DMN) have been extensively studied. Nevertheless, this knowledge has not yet been translated into advanced brain-based attention training protocols. Here, we used network-based real-time functional magnetic resonance imaging (fMRI) to provide healthy individuals with information about current activity levels in SAN and DMN. Specifically, 15 participants trained to control the difference between SAN and DMN hemodynamic activity and completed behavioral attention tests before and after neurofeedback training. Through training, participants improved controlling the differential SAN-DMN feedback signal, which was accomplished mainly through deactivating DMN. After training, participants were able to apply learned self-regulation of the differential feedback signal even when feedback was no longer available (i.e., during transfer runs). The neurofeedback group improved in sustained attention after training, although this improvement was temporally limited and rarely exceeded mere practice effects that were controlled by a test-retest behavioral control group. The learned self-regulation and the behavioral outcomes suggest that neurofeedback training of differential SAN and DMN activity has the potential to become a non-invasive and non-pharmacological tool to enhance attention and mitigate specific attention deficits.