Mobile data collection of cognitive-behavioral tasks in substance use disorders

$\bf Introduction:$ Over the last decades, our understanding of the cognitive, motivational, and neural processes involved in addictive behavior has increased enormously. A plethora of laboratory-based and cross-sectional studies has linked cognitive-behavioral measures to between-subject differences in drinking behavior. However, such laboratory-based studies inevitably suffer from small sample sizes and the inability to link temporal fluctuations in task measures to fluctuations in real-life substance use. To overcome these problems, several existing behavioral tasks have been transferred to smartphones to allow studying cognition in the field. $\bf Method:$ In this narrative review, we first summarize studies that used existing behavioral tasks in the laboratory and self-reports of substance use with ecological momentary assessment (EMA) in the field. Next, we review studies on psychometric properties of smartphone-based behavioral tasks. Finally, we review studies that used both smartphone-based tasks and self-reports with EMA in the field. $\bf Results:$ Overall, studies were scarce and heterogenous both in tasks and in study outcomes. Nevertheless, existing findings are promising and point toward several methodological recommendations: concerning psychometrics, studies show that – although more systematic studies are necessary – task validity and reliability can be improved, for example, by analyzing several measurement sessions at once rather than analyzing sessions separately. Studies that use tasks in the field, moreover, show that power can be improved by choosing sampling schemes that combine time-based with event-based sampling, rather than relying on time-based sampling alone. Increasing sampling frequency can further increase power. However, as this also increases the burden to participants, more research is necessary to determine the ideal sampling frequency for each task. $\bf Conclusion:$ Although more research is necessary to systematically study both the psychometrics of smartphone-based tasks and the frequency at which task measures fluctuate, existing studies are promising and reveal important methodological recommendations useful for researchers interested in implementing behavioral tasks in EMA studies

Role of Circadian Neuroendocrine Rhythms in the Control of Behavior and Physiology

Hormones play a major role in regulating behavior and physiology, and their efficacy is often dependent on the temporal pattern in which they are secreted. Significant insights into the mechanisms underlying rhythmic hormone secretion have been gained from transgenic rodent models, suggesting that many of the body's rhythmic functions are regulated by a coordinated network of central and peripheral circadian pacemakers. Some neuroendocrine rhythms are driven by transcriptional-posttranslational feedback circuits comprising ‘core clock genes’, while others represent a cyclic cascade of neuroendocrine events. This review focuses on recent data from the rhesus macaque, a non-human primate model with high clinical translation potential. With primary emphasis on adrenal and gonadal steroids, it illustrates the rhythmic nature of hormone secretion, and discusses the impact that fluctuating hormone levels have on the accuracy of clinical diagnoses and on the design of effective hormone replacement therapies in the elderly. In addition, this minireview raises awareness of the rhythmic expression patterns shown by many genes, and discusses how this could impact interpretation of data obtained from gene profiling studies, especially from nocturnal rodents