ABSTRACT
Dynamic interactions between brain regions, either during rest or performance of cognitive tasks, have been studied extensively using a wide variance of methods. Although some of these methods allow elegant mathematical interpretations of the data, they can easily become computationally expensive or difficult to interpret and compare between subjects or groups. Here, we propose an intuitive and computationally efficient method to measure dynamic reconfiguration of brain regions, also termed flexibility. Our flexibility measure is defined in relation to an a-priori set of biologically plausible brain modules (or networks) and does not rely on a stochastic data-driven module estimation, which, in turn, minimizes computational burden. The change of affiliation of brain regions over time with respect to these a-priori template modules is used as an indicator of brain network flexibility. We demonstrate that our proposed method yields highly similar patterns of whole-brain network reconfiguration (i.e., flexibility) during a working memory task as compared to a previous study that uses a data-driven, but computationally more expensive method. This result illustrates that the use of a fixed modular framework allows for valid, yet more efficient estimation of whole-brain flexibility, while the method additionally supports more fine-grained (e.g. node and group of nodes scale) flexibility analyses restricted to biologically plausible brain networks.
ABSTRACT
BACKGROUND: Higher levels of stress and negative emotions such as anxiety and depression have been reported since the beginning of the COVID-19 pandemic, but it remains less clear how positive emotions, such as hedonic capacity, may be affected. Further, during lockdowns, the ability to learn new pleasurable activities (hedonic learning) may be particularly relevant. Here, we investigated if state hedonia and/or hedonic learning mediated the relationship between COVID-19 stress and mental health. Moreover, we explored whether positive appraisal style (PAS), a major resilience factor, influenced these relationships. METHODS: Using a cross-sectional design, 5000 German-speaking participants filled out online questionnaires targeting stressors, mental health, state hedonia, hedonic learning, and PAS between April 9 and May 15, 2020. After confirming the factor structure of our constructs, we applied latent structural equation modeling to test mediation as well as moderated mediation models. RESULTS: Stress showed a positive association with mental health symptoms, which was buffered by both state hedonia and hedonic learning. While higher stress was related to lower state hedonia, participants reported more hedonic learning with greater stressor load. The latter effect was greater for individuals with high PAS. LIMITATIONS: The present results should be replicated in longitudinal designs with representative samples to confirm the directionality and generalizability of effects. CONCLUSIONS: Both state hedonia and hedonic learning buffered the effect of stress on mental health in an early phase of the COVID-19 pandemic. Learning new rewarding activities in combination with a PAS may be especially relevant for maintaining mental health during lockdowns.
ABSTRACT
In this paper, the domain positive valence systems (PVS) of the Research Domain Criteria (RDoC) matrix and its subconstructs are presented and discussed. The PVS basically reflect different forms and aspects of reward processing. These have been investigated in psychiatry in the context of addiction, schizophrenia and depression for decades; the latter are therefore not the topic of this paper. This article presents the heuristic value of the RDoC system in understanding other disorders and constructs, namely the transdiagnostic symptom of anhedonia, autism spectrum disorder and eating disorders. In addition, it outlines how the PVS domain has also enriched the clinical perspective of traditional psychopathology and stimulated the development of new behavioral measurement instruments. Finally, the limitations and potential future developments of the framework are discussed.
Subject(s)
Autism Spectrum Disorder , Cognitive Neuroscience , Schizophrenia , Anhedonia , Autism Spectrum Disorder/diagnosis , Humans , Reward , Schizophrenia/diagnosisABSTRACT
Healthy reward processing is a complex interplay of several components. Recent self-report measures of anhedonia, the decrease or loss of hedonic capacity, take this complexity into account. The Dimensional Anhedonia Rating Scale (DARS) measures interest, motivation, effort and consummatory pleasure across four domains: hobbies, food/drink, social activities and sensory experiences. In the present cross-sectional survey study, we validated the German version of the DARS in a sample of 557 young healthy adults. Factor structure as well as convergent and divergent validity were assessed. As a secondary aim, we examined the effects of the COVID-19 pandemic on state anhedonia and depression severity. Our results suggest good convergent and divergent validity and high internal consistency of the German DARS. The original differentiation of four factors mapping onto the four domains was confirmed and measurement invariance before and during the COVID-19 pandemic was established. We conclude that the DARS is a valid instrument to comprehensively assess state anhedonia in healthy German samples. Future studies should further assess the utility of the German DARS in clinical contexts. In line with many previous studies, participants during the pandemic reported significantly higher levels of depressive symptoms compared to participants in the months before. We found no indication that the COVID-19 pandemic affected state hedonic capacity.
