Sleep duration moderates the association between insula activation and risky decisions under stress in adolescents and adults

Influences of sleep, cortisol reactivity, and risk/reward-based decision-making on suicide

BACKGROUND AND OBJECTIVES

Poor sleep quality is a known contributor to suicidal thoughts and behaviors. This study examines whether sleep quality modulates the effect of an individual's stress response and risk/reward-based decision making on suicide risk.

METHODS

Participants were 160 adults at a residential substance use treatment facility with lifetime exposure to trauma who completed a clinician-administered measure of suicide risk, the Iowa Gambling Task (IGT), and a self-report measure of sleep. Cortisol reactivity (i.e., changes in cortisol before and after a personalized trauma script) was used to measure stress response. We used quantile regression to examine the effects of sleep, cortisol, and risk/reward decision-making on suicide risk.

RESULTS

We found poor sleep quality to be increasingly salient in individuals at greater risk for suicide than those at lower risk for suicide. Furthermore, individuals with moderate to moderate-high levels of suicide risk seem to have greater cortisol reactivity. In the low-moderate quantile, we found suicide risk to be associated with both high stress reactivity and low-risk, high-reward decision-making, as well as low stress reactivity and high-risk/low-reward decision-making.

LIMITATIONS

These findings should be interpreted considering several methodological constraints, such as the use of a pre-determined sample and instruments not tailored for our hypotheses, the MINI 'Suicide' Module's limited differentiation between suicidal ideation and behavior, and variably timed cortisol sampling.

CONCLUSIONS

Despite these limitations, the findings from this study support the use of evidence-based interventions focused on improving sleep quality and managing emotional reactivity to decrease suicide risk.

Better together: A systematic review of studies combining magnetic resonance imaging with ecological momentary assessment

Social neuroscientists often use magnetic resonance imaging (MRI) to understand the relationship between social experiences and their neural substrates. Although MRI is a powerful method, it has several limitations in the study of social experiences, first and foremost its low ecological validity. To address this limitation, researchers have conducted multimethod studies combining MRI with Ecological Momentary Assessment (EMA). However, there are no existing recommendations for best practices for conducting and reporting such studies. To address the absence of standards in the field, we conducted a systematic review of papers that combined the methods. A systematic search of peer-reviewed papers resulted in a pool of 11,558 articles. Inclusion criteria were studies in which participants completed (a) Structural or functional MRI and (b) an EMA protocol that included self-report. Seventy-one papers met inclusion criteria. The following review compares these studies based on several key parameters (e.g., sample size) with the aim of determining feasibility and current standards for design and reporting in the field. The review concludes with recommendations for future research. A special focus is given to the ways in which the two methods were combined analytically and suggestions for novel computational methods that could further advance the field of social neuroscience.

Examining the relationship between poor sleep health and risky driving behaviors among college students

Objective: Risky driving behaviors, such as texting while driving, are common among young adults and increase risk of traffic accidents and injuries. We examine the relationship between poor sleep and risky driving behaviors among college students as potential targets for traffic injury prevention.Methods: Data for this study were obtained from a cross-sectional survey administered to a college student sample in the United States Midwest (n = 1,305). Sleep was measured using the Pittsburgh Sleep Quality Index (PSQI). Risky driving behaviors were measured, including sending texts/emails; reading texts/emails while driving; talking on the phone while driving; falling asleep while driving; and driving under the influence. Risky driving behavior was defined as a response of "just once," "rarely," "sometimes," "fairly often" or "regularly" (reference = "never"). Logistic regression was used to examine the relationship between sleep and risky driving, after adjusting for confounders.Results: Among participants, 75% reported sending texts/emails while driving, 82% reported reading texts/emails while driving, and 84% reported phone talking while driving; 20% reported falling asleep while driving; 8% reported driving under the influence; and 62% reported 3 or more risky behaviors. Compared to those reporting no sleep disturbance, those with sleep disturbance "once or twice a week" were more likely to report sending a text/email while driving (aOR: 2.9, 95%CI:1.7-4.9), reading a text/email while driving (aOR:3.1,95%CI:1.5-5.5), talking on the phone while driving (aOR:1.9, 95%CI:1.0-3.4), and falling asleep while driving (aOR:3.4,95%CI:1.5-7.4). Compared to those reporting no daytime dysfunction, those reporting issues "once or twice a week" were more likely to report talking on the phone while driving (aOR:1.7, 95%CI:1.1-2.7) and falling asleep while driving (aOR:3.6,95%CI:2.3-5.6).Conclusions: Future research may consider designing behavioral interventions that aim to improve sleep, reduce drowsy driving among young adults.

Brain and Behavior Correlates of Risk Taking in Pediatric Anxiety Disorders

Avoidant behavior is a defining feature of pediatric anxiety disorders. Although prior research has examined it from the perspective of early information processing events, there has been relatively less consideration of the processes by which anxious youth make avoidant decisions and how these choices are reinforced over time. Studies of risk taking are valuable in this regard because they consider how individuals identify the pros and cons of their choices, how they weigh potential gains and losses and estimate their respective probabilities, and how they tolerate the uncertainty intrinsic to any decision. In this review, we place risk taking within existing models of information processing in pediatric anxiety disorders and highlight the particular value of this construct for informing models of developmental psychopathology and individual differences in outcome over time. We review existing behavioral and neurobiological studies of risk taking in anxious youth and conclude by identifying directions for future research.

Learning to make smart choices in the context of risk: The roles of internal affective feedback and life events

Autonomic arousal may facilitate beneficial decision-making when the link between choices and outcomes is uncertain. However, it is unknown whether greater risk-specific autonomic arousal is linearly associated with faster learning to avoid risky decisions. Furthermore, although the influence of stress on decision-making is well documented, it is unknown whether recent life stress might moderate the relationship between this internal affective feedback and decision-making. We report two studies using the Iowa Gambling Task with diverse community samples. Each study demonstrated a linear relationship between the level of autonomic arousal prior to risky decision-making and the rate of learning to avoid risk. Additionally, participants' recent life events conditionally moderated this association. Specifically, the relationship between risk-specific arousal and advantageous learning was strongest for participants who experienced relatively more positive and fewer negative life events in the previous four months. These findings suggest that autonomic arousal may generally inform decision-making, but less so when life circumstances are relatively poor.

Individual differences in accumbofrontal tract integrity relate to risky decisions under stress in adolescents and adults

Psychosocial stress increases risky decision-making (DM). It is widely accepted that individual variation in neural phenotypes underlie variability in this behavioral tendency in adults, but is less examined in adolescents. Our goal was to test the hypothesis that the relation between neural phenotypes and stress-related risky DM is better characterized by individual variation than by age. Using diffusion tensor imaging (DTI) tractography to characterize the accumbofrontal tract, we determined if it uniquely moderated how stress affects risky DM, over and above age. A daily diary design monitored participants’ daily stress for two weeks. Participants completed a DTI scan and performed a task in which decisions varied by expected value, once each on a day when they endorsed feeling higher (and lower) than usual levels of stress. Multilevel logistic regression analyses revealed that all participants were more likely to take risks as expected reward value increased; this behavior was greater under high versus low stress for individuals with low accumbofrontal tract integrity, whereas DM was less influenced by stress for individuals with high accumbofrontal tract integrity, regardless of age. Results suggest that individual differences in brain structure may be more germane to characterizing risky decisions in adolescents, rather than ontogeny.

Parsing inter- and intra-individual variability in key nervous system mechanisms of stress responsivity and across functional domains

Exposure to stressful events is omnipresent in modern human life, yet people show considerable heterogeneity in the impact of stress exposure(s) on their functionality and overall health. Encounter with stressor(s) is counteracted by an intricate repertoire of nervous-system responses. This narrative review starts with a brief summary of the vast evidence that supports heart rate variability, cortisol secretion, and large-scale cortical network interactions as kay physiological, endocrinological, and neural mechanisms of stress responsivity, respectively. The second section highlights potential sources for inter-individual variability in these mechanisms, by focusing on biological, environmental, social, habitual, and psychological factors that may influence stress responsivity patterns and thus contribute to heterogeneity in the impact of stress exposure on functionality and health. The third section introduces intra-individually variability in stress responsivity across functional domains as a novel putative source for heterogeneity in the impact of stress exposure. Challenges and future directions are further discussed. Parsing inter- and intra-individual variability in nervous-system mechanisms of stress responsivity and across functional domains is critical towards potential clinical translation.

Decision Making, Stress Assessed by Physiological Response and Virtual Reality Stimuli

Many decisions must be made under stress; therefore, stress and decision-making are intrinsically related not only at the behavioral level but also at the neural level. Additionally, virtual reality tools have been proposed as a method to induce stress in the laboratory. This review focuses on answering the following research question: Does stress assessed by physiological variables of a subject under virtual reality stimuli increase the chances of error in decision-making? The reviewed studies were consulted in the following databases: PubMed, IEEE Xplore, and Science Direct. The analysis of the consulted literature indicates that the stress induced in the laboratory using virtual reality tools and the physiological response of the central and autonomous nervous system are complementary subjects and allow the design of training and support systems for the decision-making process

Structural Alterations in Large-scale Brain Networks and Their Relationship with Sleep Disturbances in the Adolescent Population

Although sleep disturbances are highly prevalent in adolescents, neuroimaging evidence on the effects of sleep disturbances on their developing brains remains limited. Therefore, we explored gray matter volumes (GMVs) at the whole-brain level and investigated their relationship to sleep disturbances in a sample of Korean adolescents in the general population. We recruited participants from one middle school and high school. All participants and their legal guardians gave informed consent before participating in our study. We used component 5 of the Pittsburgh Sleep Quality Index to measure sleep disturbances and conducted a voxel-based morphometry-DARTEL procedure to measure GMVs. We performed partial correlation analyses to examine whether the GMVs were associated with sleep disturbances. A total of 56 adolescents participated in this study. Our results revealed that GMVs in multiple global regions were negatively correlated with sleep disturbances. Moreover, most of these identified regions belong to large-scale brain networks categorized by functional neuroimaging studies. We found an association between regional GMVs in multiple global regions involved in large-scale networks and the severity of sleep disturbances in the adolescent population. Based on this evidence and previous neuroimaging evidence, we suggest that structural alterations in the networks may be linked to sleep disturbances.

Integrating sleep, neuroimaging, and computational approaches for precision psychiatry

In advancing precision psychiatry, we focus on what imaging technology and computational approaches offer for the future of diagnostic subtyping and personalized tailoring of interventions for sleep impairment in mood and anxiety disorders. Current diagnostic criteria for mood and anxiety tend to lump different forms of sleep disturbance together. Parsing the biological features of sleep impairment and brain circuit dysfunction is one approach to identifying subtypes within these disorders that are mechanistically coherent and offer targets for intervention. We focus on two large-scale neural circuits implicated in sleep impairment and in mood and anxiety disorders: the default mode network and negative affective network. Through a synthesis of existing knowledge about these networks, we pose a testable framework for understanding how hyper- versus hypo-engagement of these networks may underlie distinct features of mood and sleep impairment. Within this framework we consider whether poor sleep quality may have an explanatory role in previously observed associations between network dysfunction and mood symptoms. We expand this framework to future directions including the potential for connecting circuit-defined subtypes to more distal features derived from digital phenotyping and wearable technologies, and how new discovery may be advanced through machine learning approaches.

Magnetic Resonance Imaging Exploration of the Human Brain During 10 kHz Spinal Cord Stimulation for Failed Back Surgery Syndrome: A Resting State Functional Magnetic Resonance Imaging Study

INTRODUCTION

Apart from the clinical efficacy of high frequency spinal cord stimulation at 10 kHz, the underlying mechanism of action remains unclear. In parallel with spinal or segmental theories, supraspinal hypotheses have been recently proposed. In order to unveil hidden altered brain connectome patterns, a resting state functional magnetic resonance imaging (rsfMRI) protocol was performed in subjects routinely treated for back and/or leg pain with high-frequency spinal cord stimulation (HF-SCS) HF-SCS at 10 kHz.

METHODS

RsfMRI imaging was obtained from ten patients with failed back surgery syndrome who were eligible for HF-SCS at 10 kHz. Specifically-chosen regions of interest with different connectivity networks have been investigated over time. Baseline measurements were compared with measurements after 1 month and 3 months of HF-SCS at 10 kHz. Additionally, clinical parameters on pain intensity, central sensitization, pain catastrophizing, and sleep quality were correlated with the functional connectivity strengths.

RESULTS

The study results demonstrate an increased connectivity over time between the anterior insula (affective salience network) and regions of the frontoparietal network and the central executive network. After 3 months of HF-SCS, the increased strength in functional connectivity between the left dorsolateral prefrontal cortex and the right anterior insula was significantly correlated with the minimum clinically important difference (MCID) value of the Pittsburgh sleep quality index.

CONCLUSION

These findings support the hypothesis that HF-SCS at 10 kHz might influence the salience network and therefore also the emotional awareness of pain.

Methodological considerations for developmental longitudinal fMRI research

There has been a large spike in longitudinal fMRI studies in recent years, and so it is essential that researchers carefully assess the limitations and challenges afforded by longitudinal designs. In this article, we provide an overview of important considerations for longitudinal fMRI research in developmental samples, including task design, sampling strategies, and group-level analyses. We first discuss considerations for task designs, weighing the pros and cons of many commonly used tasks, as well as outlining how the tasks may be impacted by repeated exposure. Secondly, we review the types of group-level analyses that can be conducted on longitudinal fMRI data, analyses which must account for repeated measures. Finally, we review and critique recent longitudinal studies that have emerged in the past few years.

Influence of sleep on developing brain functions and structures in children and adolescents: A systematic review

This systematic review examined the associations between sleep and brain functions and structures in children and adolescents aged 1-17 ys. Included studies (n = 24) were peer-reviewed and met the a priori determined population (apparently healthy children and adolescents aged 1 y to 17 ys), intervention/exposure/comparator (various sleep characteristics including duration, architecture, quality, timing), and outcome criteria (brain functions and/or brain structures, excluding cognitive function outcomes). Collectively, the reviewed studies report some relationships between inadequate sleep and resultant differences in brain functions or structures. Although the research presented supports and offers more insight into the importance of sleep for the developing brain of children and adolescents, no firm conclusions that apply broadly may be drawn from these results, particularly because of the diversity of the sleep variables and outcomes. However, it is clear that sleeping habits in the pediatric population should be prioritized. Health care providers should continue to recommend healthy sleep practices and adequate time for sleep, as they are essential for overall health, including brain health.

Future Directions for Examination of Brain Networks in Neurodevelopmental Disorders

Neurodevelopmental disorders are associated with atypical development and maturation of brain networks. A recent focus on human connectomics research and the growing popularity of open science initiatives has created the ideal climate in which to make real progress toward understanding the neurobiology of disorders affecting youth. Here we outline future directions for neuroscience researchers examining brain networks in neurodevelopmental disorders, highlighting gaps in the current literature. We emphasize the importance of leveraging large neuroimaging and phenotypic data sets recently made available to the research community, and we suggest specific novel methodological approaches, including analysis of brain dynamics and structural connectivity, that have the potential to produce the greatest clinical insight. Transdiagnostic approaches will also become increasingly necessary as the Research Domain Criteria framework put forth by the National Institute of Mental Health permeates scientific discourse. During this exciting era of big data and increased computational sophistication of analytic tools, the possibilities for significant advancement in understanding neurodevelopmental disorders are limitless.

Sleep quality and adolescent default mode network connectivity

Sleep suffers during adolescence and is related to academic, emotional and social behaviors. How this normative change relates to ongoing brain development remains unresolved. The default mode network (DMN), a large-scale brain network important for complex cognition and socioemotional processing, undergoes intra-network integration and inter-network segregation during adolescence. Using resting state functional connectivity and actigraphy over 14 days, we examined correlates of naturalistic individual differences in sleep duration and quality in the DMN at rest in 45 human adolescents (ages 14-18). Variation in sleep quality, but not duration, was related to weaker intrinsic DMN connectivity, such that those with worse quality sleep evinced weaker intra-network connectivity at rest. These novel findings suggest sleep quality, a relatively unexplored sleep index, is related to adolescent brain function in a network that contributes to behavioral maturation and undergoes development during adolescence.