Combining Cardiac Monitoring with Actigraphy Aids Nocturnal Arousal Detection during Ambulatory Sleep Assessment in Insomnia

Study Objectives: The objective assessment of insomnia has remained difficult. Multisensory devices collecting heart rate (HR) and motion are regarded as the future of ambulatory sleep monitoring. Unfortunately, reports on altered average HR or heart rate variability (HRV) during sleep in insomnia are equivocal. Here, we evaluated whether the objective quantification of insomnia improves by assessing state-related changes in cardiac measures. Methods: We recorded electrocardiography, posture, and actigraphy in 33 people without sleep complaints and 158 patients with mild to severe insomnia over 4 d in their home environment. At the microscale, we investigated whether HR changed with proximity to gross (body) and small (wrist) movements at nighttime. At the macroscale, we calculated day-night differences in HR and HRV measures. For both timescales, we tested whether outcome measures were related to insomnia diagnosis and severity. Results: At the microscale, an increase in HR was often detectable already 60 s prior to as well as following a nocturnal chest, but not wrist, movement. This increase was slightly steeper in insomnia and was associated with insomnia severity, but future EEG recordings are necessary to elucidate whether these changes occur prior to or simultaneously with PSG-indicators of wakefulness. At the macroscale, we found an attenuated cardiac response to sleep in insomnia: patients consistently showed smaller day-night differences in HR and HRV. Conclusions: Incorporating state-related changes in cardiac features in the ambulatory monitoring of sleep might provide a more sensitive biomarker of insomnia than the use of cardiac activity averages or actigraphy alone

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

ENIGMA-Sleep:Challenges, opportunities, and the road map

Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

A neurobiological and clinical perspective on preventing depression with insomnia treatment

Insomnia is a major risk factor for the development of major depressive disorder (MDD), and has a negative impact on the course of the disease and the effectivity of treatment. Prevention of depression in insomnia patients is essential to reduce the global disease burden of MDD. Targeting insomnia seems promising, yet it remains unclear whether insomnia treatment can effectively prevent depression in insomnia patients, and how insomnia treatment can best be optimized. Therefore, in this thesis we examined whether we can prevent depression in insomnia patients with therapist-guided digital interventions aimed at improving sleep. Neurobiology of insomnia and its relation to depression In chapter 2 we investigated hippocampal volume and functional connectivity of the hippocampus in insomnia patients. Hippocampal volume and functional connectivity patterns were obtained from structural and functional MRI scans. The findings indicate that compared to good sleeper controls, insomnia patients showed increased functional connectivity between the bilateral hippocampus and the left middle frontal gyrus. Impaired hippocampal-prefrontal circuits might contribute to the vulnerability of insomnia patients to develop mood disorders. In chapter 3 we assessed structural brain correlates of insomnia severity in MDD patients. We acquired cortical surface area, thickness and subcortical volume measures from 1053 MDD patients from 15 cohorts of the ENIGMA-MDD consortium. The results revealed that MDD patients with more severe insomnia had a smaller total cortical surface area. The better specificity of reduced surface area with insomnia severity than with total depression severity provide support for the possibility that insomnia may represent a symptom cluster of MDD with a distinct underlying neurobiology. Preventing depression with insomnia treatment The randomized controlled trial of chapter 4 and 5 focused on the prevention of worsening of depressive symptoms in insomnia subtypes at high risk to develop MDD. A total of 132 insomnia patients were randomized to therapist-guided digital CBT-I, CRS, CBT-I+CRS, or no treatment (NT). Depressive symptoms were measured prior to treatment, and at four follow-up assessments during the following year. Without treatment depressive symptoms worsened during the one-year follow-up in individuals with an insomnia subtype with high-risk to develop depression, while a reference group including insomnia subtypes with a low-risk of depression did not worsen over time. Therapist-guided CBT-I and CBT-I+CRS reduced depressive symptoms across all four follow-up assessments. Only CBT-I+CRS had a reduced incidence of clinical meaningful worsening during the one-year follow-up. These results demonstrate that CBT-I, especially in combination with CRS, could be an effective and feasible approach to prevent worsening of depressive symptoms. In chapter 6 we evaluated diagnoses of first-onset MDD and dysthymia in insomnia patients on average 3.6 years after they had received either therapist-guided digital CBT-I, CBT-I+CRS, or NT. People that had received CBT-I combined with CRS were less likely to be diagnosed with MDD and/or dysthymia than participants that had received either standalone CBT-I or no treatment at all. These findings extent the findings from chapter 5, by demonstrating the effectivity of CBT-I+CRS to prevent new-onset mood disorders at a long follow-up. Effect of insomnia interventions on activity in emotional brain circuits Chapter 7 focused on the effect of these therapist-guided digital insomnia interventions on activity in the brain circuits involved in emotion regulation. Pre-to-post-intervention changes in emotional brain activity, assessed with the Hariri emotion face/shape fMRI task, were compared between insomnia patients who received CBT-I, CRS, CBT- I+CRS, or NT. Combined CBT-I+CRS intervention had the longest-lasting favorable effect on mood, which was paralleled by a significant pre-to-post-intervention increase in bilateral amygdala activation in response to emotional stimuli. These results provide a better understanding of how neurobiological changes in emotional brain functioning might underlie the therapeutic effects of CBT-I+CRS

Replication of Mehta & Zhu (2009, Science, Study 3)

Original citation: Mehta, R., & Zhu, R. (2009). Blue or Red? Exploring the Effect of Color on Cognitive Task Performances. Science, 323(5918), 1226-1229. doi:10.1126/science.116914

Reduced dynamic functional connectivity between salience and executive brain networks in insomnia disorder

International audienceResearch into insomnia disorder has pointed to large-scale brain network dysfunctions. Dynamic functional connectivity is instrumental to cognitive functions but has not been investigated in insomnia disorder. This study assessed between-network functional connectivity strength and variability in patients with insomnia disorder as compared with matched controls without sleep complaints. Twelve-minute resting-state functional magnetic resonance images and T1-weighed images were acquired in 65 people diagnosed with insomnia disorder (21-69 years, 48 female) and 65 matched controls without sleep complaints (22-70 years, 42 female). Pairwise correlations between the activity time series of 14 resting-state networks and temporal variability of the correlations were compared between cases and controls. After false discovery rate correction for multiple comparisons, people with insomnia disorder and controls did not differ significantly in terms of mean between-network functional connectivity strength; people with insomnia disorder did, however, show less functional connectivity variability between the anterior salience network and the left executive-control network. The finding suggests less flexible interactions between the networks during the resting state in people with insomnia disorder

Actigraphy in studies on insomnia: Worth the effort?

In the past decades, actigraphy has emerged as a promising, cost-effective, and easy-to-use tool for ambulatory sleep recording. Polysomnography (PSG) validation studies showed that actigraphic sleep estimates fare relatively well in healthy sleepers. Additionally, round-the-clock actigraphy recording has been used to study circadian rhythms in various populations. To this date, however, there is little evidence that the diagnosis, monitoring, or treatment of insomnia can significantly benefit from actigraphy recordings. Using a case–control design, we therefore critically examined whether mean or within-subject variability of actigraphy sleep estimates or circadian patterns add to the understanding of sleep complaints in insomnia. We acquired actigraphy recordings and sleep diaries of 37 controls and 167 patients with varying degrees of insomnia severity for up to 9 consecutive days in their home environment. Additionally, the participants spent one night in the laboratory, where actigraphy was recorded alongside PSG to check whether sleep, in principle, is well estimated. Despite moderate to strong agreement between actigraphy and PSG sleep scoring in the laboratory, ambulatory actigraphic estimates of average sleep and circadian rhythm variables failed to successfully differentiate patients with insomnia from controls in the home environment. Only total sleep time differed between the groups. Additionally, within-subject variability of sleep efficiency and wake after sleep onset was higher in patients. Insomnia research may therefore benefit from shifting attention from average sleep variables to day-to-day variability or from the development of non-motor home-assessed indicators of sleep quality