Imaging Individual Differences in the Response of the Human Suprachiasmatic Area to Light

Circadian disruption is associated with poor health outcomes, including sleep and mood disorders. The suprachiasmatic nucleus (SCN) of the anterior hypothalamus acts as the master biological clock in mammals, regulating circadian rhythms throughout the body. The clock is synchronized to the day/night cycle via retinal light exposure. The BOLD-fMRI response of the human suprachiasmatic area to light has been shown to be greater in the night than in the day, consistent with the known sensitivity of the clock to light at night. Whether the BOLD-fMRI response of the human suprachiasmatic area to light is related to a functional outcome has not been demonstrated. In a pilot study (n = 10), we investigated suprachiasmatic area activation in response to light in a 30 s block-paradigm of lights on (100 lux) and lights off (< 1 lux) using the BOLD-fMRI response, compared to each participant's melatonin suppression response to moderate indoor light (100 lux). We found a significant correlation between activation in the suprachiasmatic area in response to light in the scanner and melatonin suppression, with increased melatonin suppression being associated with increased suprachiasmatic area activation in response to the same light level. These preliminary findings are a first step toward using imaging techniques to measure individual differences in circadian light sensitivity, a measure that may have clinical relevance in understanding vulnerability in disorders that are influenced by circadian disruption

Sensors and Systems for Monitoring Mental Fatigue: A systematic review

Mental fatigue is a leading cause of motor vehicle accidents, medical errors, loss of workplace productivity, and student disengagements in e-learning environment. Development of sensors and systems that can reliably track mental fatigue can prevent accidents, reduce errors, and help increase workplace productivity. This review provides a critical summary of theoretical models of mental fatigue, a description of key enabling sensor technologies, and a systematic review of recent studies using biosensor-based systems for tracking mental fatigue in humans. We conducted a systematic search and review of recent literature which focused on detection and tracking of mental fatigue in humans. The search yielded 57 studies (N=1082), majority of which used electroencephalography (EEG) based sensors for tracking mental fatigue. We found that EEG-based sensors can provide a moderate to good sensitivity for fatigue detection. Notably, we found no incremental benefit of using high-density EEG sensors for application in mental fatigue detection. Given the findings, we provide a critical discussion on the integration of wearable EEG and ambient sensors in the context of achieving real-world monitoring. Future work required to advance and adapt the technologies toward widespread deployment of wearable sensors and systems for fatigue monitoring in semi-autonomous and autonomous industries is examined.Comment: 19 Pages, 3 Figure

Network diffusion modeling predicts neurodegeneration in traumatic brain injury

Objective Traumatic brain injury (TBI) is a heterogeneous disease with multiple neurological deficits that evolve over time. It is also associated with an increased incidence of neurodegenerative diseases. Accordingly, clinicians need better tools to predict a patient’s long‐term prognosis. Methods Diffusion‐weighted and anatomical MRI data were collected from 17 adolescents (mean age = 15y8mo) with moderate‐to‐severe TBI and 19 healthy controls. Using a network diffusion model (NDM), we examined the effect of progressive deafferentation and gray matter thinning in young TBI patients. Moreover, using a novel automated inference method, we identified several injury epicenters in order to determine the neural degenerative patterns in each TBI patient. Results We were able to identify the subject‐specific patterns of degeneration in each patient. In particular, the hippocampus, temporal cortices, and striatum were frequently found to be the epicenters of degeneration across the TBI patients. Orthogonal transformation of the predicted degeneration, using principal component analysis, identified distinct spatial components in the temporal–hippocampal network and the cortico‐striatal network, confirming the vulnerability of these networks to injury. The NDM model, best predictive of the degeneration, was significantly correlated with time since injury, indicating that NDM can potentially capture the pathological progression in the chronic phase of TBI. Interpretation These findings suggest that network spread may help explain patterns of distant gray matter thinning, which would be consistent with Wallerian degeneration of the white matter connections (i.e., “diaschisis”) from diffuse axonal injuries and multifocal contusive injuries, and the neurodegenerative patterns of abnormal protein aggregation and transmission, which are hallmarks of brain changes in TBI. NDM approaches could provide highly subject‐specific biomarkers relevant for disease monitoring and personalized therapies in TBI

Dual tasking impairments are associated with striatal pathology in Huntington’s disease

Background: Recent findings suggest that individuals with Huntington’s disease (HD) have an impaired capacity to execute cognitive and motor tasks simultaneously, or dual task, which gradually worsens as the disease advances. The onset and neuropathological changes mediating impairments in dual tasking in individuals with HD are unclear. The reliability of dual tasking assessments for individuals with HD is also unclear. Objectives: To evaluate differences in dual tasking performance between individuals with HD (presymptomatic and prodromal) and matched controls, to investigate associations between striatal volume and dual tasking performance, and to determine the reliability of dual tasking assessments. Methods: Twenty individuals with HD (10 presymptomatic and 10 prodromal) and 20 healthy controls were recruited for the study. Individuals undertook four single and dual task assessments, comprising motor (postural stability or force steadiness) and cognitive (simple or complex mental arithmetic) components, with single and dual tasks performed three times each. Participants also undertook a magnetic resonance imaging assessment. Results: Compared to healthy controls, individuals with presymptomatic and prodromal HD displayed significant deficits in dual tasking, particularly cognitive task performance when concurrently undertaking motor tasks (P \u3c 0.05). The observed deficits in dual tasking were associated with reduced volume in caudate and putamen structures (P \u3c 0.05),however, not with clinical measures of disease burden. An analysis of the reliability of dual tasking assessments revealed moderate to high test–retest reliability [ICC: 0.61-0.99] for individuals with presymptomatic and prodromal HD and healthy controls. Conclusions: Individuals with presymptomatic and prodromal HD have significant deficits in dual tasking that are associated with striatal degeneration. Findings also indicate that dual tasking assessments are reliable in individuals presymptomatic and prodromal HD and healthy controls

Effect of multidisciplinary rehabilitation on sleep outcomes in individuals with preclinical Huntington disease: An exploratory study

Dear Editor Sleep disturbances are an early feature of Huntington disease (HD), which worsen as the disease progresses. Studies have documented increased sleep fragmentation, decreased rapid eye-movement (REM) sleep, reduced sleep efficiency, insomnia and an increase in periodic leg movements (PLMs) in individuals with HD [1], [2]. Disturbances in sleep are thought to exacerbate cognitive impairments and may hasten subcortical neurodegeneration [3], [4]. Hence, management of sleep disturbances in individuals with HD is imperative

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

Cortical thickness and resting-state cardiac function across the lifespan: a cross-sectional pooled mega analysis

Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS – or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between cortical thickness and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research

Multimodal neuroimaging with simultaneous fMRI and EEG

Functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are noninvasive techniques used to measure neural activity in the human brain. fMRI measures the magnetic resonance signal associated with hemodynamic changes driven by neural activity and has a good spatial resolution (2–3 mm isotropic) and low temporal resolution (1–3 s). Whereas EEG is used to record electrical activity in the brain with a millisecond-level temporal resolution but has a limited spatial resolution. By combining fMRI and EEG, it is possible to generate a high spatiotemporal resolution map of human brain function, which is critical for understanding complex dynamics of the human brain. Furthermore, EEG recordings during fMRI can be used to identify the sources of abnormal electrical activity in the brain (e.g., during epileptic seizures). This chapter discusses recent advances in the simultaneous recording of fMRI and EEG in humans. It focuses on the challenges of recording fMRI and EEG simultaneously, techniques for removing artifacts, experimental designs for fMRI and EEG studies, and methods for integrating fMRI and EEG data

Temporal evolution of neutral activity and connectivity during microsleeps when rested and following sleep restriction

Even when it is critical to stay awake, such as when driving, sleep deprivation weakens one's ability to do so by substantially increasing the propensity for microsleeps. Microsleeps are complete lapses of consciousness but, paradoxically, are associated with transient increases in cortical activity. But do microsleeps provide a benefit in terms of attenuating the need for sleep? And is the neural response to microsleeps altered by the degree of homeostatic drive to sleep? In this study, we continuously monitored eye-video, visuomotor responsiveness, and brain activity via fMRI in 20 healthy subjects during a 20-min visuomotor tracking task following a normally-rested night and a sleep-restricted (4-h) night. As expected, sleep restriction led to an increased number of microsleeps and an increased variability in tracking error. Microsleeps exhibited transient increases in regional activity in the fronto-parietal and parahippocampal area. Network analyses revealed divergent transient changes in the right fronto-parietal, dorsal-attention, default-mode, and thalamo-cortical functional networks. In all subjects, tracking error immediately following microsleeps was improved compared to before the microsleeps. Importantly, post-microsleep recovery in tracking response speed was associated with hyperactivation in the thalamo-cortical network. The temporal evolution of functional connectivity within the frontal and posterior nodes of the default-mode network and between the right fronto-parietal and default-mode networks was associated with temporal changes in visuomotor responsiveness. These findings demonstrate distinct brain-network-level changes in brain activity during microsleeps and suggest that neural activity in the thalamo-cortical network may facilitate the transient recovery from microsleeps. The temporal pattern of evolution in brain activity and performance is indicative of dynamic changes in vigilance during the struggle to stay awake following sleep loss

A Gut Instinct on Leukaemia: A New Mechanistic Hypothesis for Microbiota-Immune Crosstalk in Disease Progression and Relapse

Despite significant advances in the treatment of Chronic Myeloid and Acute Lymphoblastic Leukaemia (CML and ALL, respectively), disease progression and relapse remain a major problem. Growing evidence indicates the loss of immune surveillance of residual leukaemic cells as one of the main contributors to disease recurrence and relapse. More recently, there was an appreciation for how the host’s gut microbiota predisposes to relapse given its potent immunomodulatory capacity. This is especially compelling in haematological malignancies where changes in the gut microbiota have been identified after treatment, persisting in some patients for years after the completion of treatment. In this hypothesis-generating review, we discuss the interaction between the gut microbiota and treatment responses, and its capacity to influence the risk of relapse in both CML and ALL We hypothesize that the gut microbiota contributes to the creation of an immunosuppressive microenvironment, which promotes tumour progression and relapse