Effects of exercise in people with severe mental illness and recommendations for its implementation as add-on therapy [Abstract]

There are many reasons for people with (and without) severe mental illness to exercise regularly. In people with schizophrenia, major depression and bipolar disorder, it has already been shown that regular physical activity as an add-on therapy can improve quality of life and symptom severity. This is particularly important in domains that standard therapy is currently not able to treat sufficiently, such as cognitive deficits. Postulated underlying neurobiological effects include increased volume in hippocampal areas as demonstrated by data of a current clinical trial in people with schizophrenia. Furthermore, regular exercise is essential to counteract the increased cardiovascular morbidity and mortality of people with severe mental illness. However, most people with severe mental illness do not achieve the recommended amount of physical activity and the potential of exercise as an add-on therapy is currently not even close to being fully realized. On the one hand, it is important that mental health staff also considers the physical condition of patients with mental illnesses and counsels them on their health behavior. On the other hand, there is a need for individually adapted training programs delivered by qualified exercise professionals that incorporate motivational and adherence strategies. Examples of barriers and facilitators for the implementation of exercise as an add-on therapy are discussed on the basis of current local projects

Resting-State Network Alterations Differ between Alzheimer's Disease Atrophy Subtypes

Several Alzheimer's disease (AD) atrophy subtypes were identified, but their brain network properties are unclear. We analyzed data from two independent datasets, including 166 participants (103 AD/63 controls) from the DZNE-longitudinal cognitive impairment and dementia study and 151 participants (121 AD/30 controls) from the AD neuroimaging initiative cohorts, aiming to identify differences between AD atrophy subtypes in resting-state functional magnetic resonance imaging intra-network connectivity (INC) and global and nodal network properties. Using a data-driven clustering approach, we identified four AD atrophy subtypes with differences in functional connectivity, accompanied by clinical and biomarker alterations, including a medio-temporal-predominant (S-MT), a limbic-predominant (S-L), a diffuse (S-D), and a mild-atrophy (S-MA) subtype. S-MT and S-D showed INC reduction in the default mode, dorsal attention, visual and limbic network, and a pronounced reduction of "global efficiency" and decrease of the "clustering coefficient" in parietal and temporal lobes. Despite severe atrophy in limbic areas, the S-L exhibited only marginal global network but substantial nodal network failure. S-MA, in contrast, showed limited impairment in clinical and cognitive scores but pronounced global network failure. Our results contribute toward a better understanding of heterogeneity in AD with the detection of distinct differences in functional connectivity networks accompanied by CSF biomarker and cognitive differences in AD subtypes

High-definition tDCS of the temporo-parietal cortex enhances access to newly learned words

Learning associations between words and their referents is crucial for language learning in the developing and adult brain and for language re-learning after neurological injury. Non-invasive transcranial direct current stimulation (tDCS) to the posterior temporo-parietal cortex has been suggested to enhance this process. However, previous studies employed standard tDCS set-ups that induce diffuse current flow in the brain, preventing the attribution of stimulation effects to the target region. This study employed high-definition tDCS (HD-tDCS) that allowed the current flow to be constrained to the temporo-parietal cortex, to clarify its role in novel word learning. In a sham-controlled, double-blind, between-subjects design, 50 healthy adults learned associations between legal non-words and unfamiliar object pictures. Participants were stratified by baseline learning ability on a short version of the learning paradigm and pairwise randomized to active (20 mins; N = 25) or sham (40 seconds; N = 25) HD-tDCS. Accuracy was comparable during the baseline and experimental phases in both HD-tDCS conditions. However, active HD-tDCS resulted in faster retrieval of correct word-picture pairs. Our findings corroborate the critical role of the temporo-parietal cortex in novel word learning, which has implications for current theories of language acquisition

Task-Specific Effects of tDCS-Induced Cortical Excitability Changes on Cognitive and Motor Sequence Set Shifting Performance

In this study, we tested the effects of transcranial Direct Current Stimulation (tDCS) on two set shifting tasks. Set shifting ability is defined as the capacity to switch between mental sets or actions and requires the activation of a distributed neural network. Thirty healthy subjects (fifteen per site) received anodal, cathodal and sham stimulation of the dorsolateral prefrontal cortex (DLPFC) or the primary motor cortex (M1). We measured set shifting in both cognitive and motor tasks. The results show that both anodal and cathodal single session tDCS can modulate cognitive and motor tasks. However, an interaction was found between task and type of stimulation as anodal tDCS of DLPFC and M1 was found to increase performance in the cognitive task, while cathodal tDCS of DLPFC and M1 had the opposite effect on the motor task. Additionally, tDCS effects seem to be most evident on the speed of changing sets, rather than on reducing the number of errors or increasing the efficacy of irrelevant set filtering

Genetic variants associated with longitudinal changes in brain structure across the lifespan

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging