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AbstractPatient\u2010reported quality\u2010of\u2010life (QoL) and carer impacts are not reported after leucine\u2010rich glioma\u2010inactivated 1\u2010antibody encephalitis (LGI1\u2010Ab\u2010E). From 60 patients, 85% (51 out of 60) showed one abnormal score across QoL assessments and 11 multimodal validated questionnaires. Compared to the premorbid state, QoL significantly deteriorated (p\u2009<\u20090.001) and, at a median of 41\u2009months, fatigue was its most important predictor (p\u2009=\u20090.025). In total, 51% (26 out of 51) of carers reported significant burden. An abbreviated five\u2010item battery explained most variance in QoL. Wide\u2010ranging impacts post\u2010LGI1\u2010Ab\u2010E include decreased QoL and high caregiver strain. We identify a rapid method to capture QoL in routine clinic or clinical trial settings.
\n \n\n \n \nThe convergence of an interdisciplinary team of neurocritical care specialists to organize the Curing Coma Campaign is the first effort of its kind to coordinate national and international research efforts aimed at a deeper understanding of disorders of consciousness (DoC). This process of understanding includes translational research from bench to bedside, descriptions of systems of care delivery, diagnosis, treatment, rehabilitation, and ethical frameworks. The description and measurement of varying confounding factors related to hospital care was thought to be critical in furthering meaningful research in patients with DoC. Interdisciplinary hospital care is inherently varied across geographical areas as well as community and academic medical centers. Access to monitoring technologies, specialist consultation (medical, nursing, pharmacy, respiratory, and rehabilitation), staffing resources, specialty intensive and acute care units, specialty medications and specific surgical, diagnostic and interventional procedures, and imaging is variable, and the impact on patient outcome in terms of DoC is largely unknown. The heterogeneity of causes in DoC is the source of some expected variability in care and treatment of patients, which necessitated the development of a common nomenclature and set of data elements for meaningful measurement across studies. Guideline adherence in hemorrhagic stroke and severe traumatic brain injury may also be variable due to moderate or low levels of evidence for many recommendations. This article outlines the process of the development of common data elements for hospital course, confounders, and medications to streamline definitions and variables to collect for clinical studies of DoC.
\n \n\n \n \nBACKGROUND: Over the past 5 decades, advances in neuroimaging have yielded insights into the pathophysiologic mechanisms that cause disorders of consciousness (DoC) in patients with severe brain injuries. Structural, functional, metabolic, and perfusion imaging studies have revealed specific neuroanatomic regions, such as the brainstem tegmentum, thalamus, posterior cingulate cortex, medial prefrontal cortex, and occipital cortex, where lesions correlate with the current or future state of consciousness. Advanced imaging modalities, such as diffusion tensor imaging, resting-state functional magnetic resonance imaging (fMRI), and task-based fMRI, have been used to improve the accuracy of diagnosis and long-term prognosis, culminating in the endorsement of fMRI for the clinical evaluation of patients with DoC in the 2018 US (task-based fMRI) and 2020 European (task-based and resting-state fMRI) guidelines. As diverse neuroimaging techniques are increasingly used for patients with DoC in research and clinical settings, the need for a standardized approach to reporting results is clear. The success of future multicenter collaborations and international trials fundamentally depends on the implementation of a shared nomenclature and infrastructure. METHODS: To address this need, the Neurocritical Care Society's Curing Coma Campaign convened an international panel of DoC neuroimaging experts to propose common data elements (CDEs) for data collection and reporting in this field. RESULTS: We report the recommendations of this CDE development panel and disseminate CDEs to be used in neuroimaging studies of patients with DoC. CONCLUSIONS: These CDEs will support progress in the field of DoC neuroimaging and facilitate international collaboration.
\n \n\n \n \nThe association between nightmare frequency (NMF) and suicidal ideation (SI) is well known, yet the impact of the COVID-19 pandemic on this relation is inconsistent. This study aimed to investigate changes in NMF, SI, and their association during the COVID-19 pandemic. Data were collected in 16 countries using a harmonised questionnaire. The sample included 9328 individuals (4848 women; age M[SD]\u2009=\u200946.85 [17.75] years), and 17.60% reported previous COVID-19. Overall, SI was significantly 2% lower during the pandemic vs. before, and this was consistent across genders and ages. Most countries/regions demonstrated decreases in SI during this pandemic, with Austria (-9.57%), Sweden (-6.18%), and Bulgaria (-5.14%) exhibiting significant declines in SI, but Italy (1.45%) and Portugal (2.45%) demonstrated non-significant increases. Suicidal ideation was more common in participants with long-COVID (21.10%) vs. short-COVID (12.40%), though SI did not vary by COVID-19 history. Nightmare frequency increased by 4.50% during the pandemic and was significantly higher in those with previous COVID-19 (14.50% vs. 10.70%), during infection (23.00% vs. 8.10%), and in those with long-COVID (18.00% vs. 8.50%). The relation between NMF and SI was not significantly stronger during the pandemic than prior (rs\u2009=\u20090.18 vs. 0.14; z\u2009=\u20092.80). Frequent nightmares during the pandemic increased the likelihood of reporting SI (OR\u2009=\u20091.57, 95% CI 1.20-2.05), while frequent dream recall during the pandemic served a protective effect (OR\u2009=\u20090.74, 95% CI 0.59-0.94). These findings have important implications for identifying those at risk of suicide and may offer a potential pathway for suicide prevention.
\n \n\n \n \nPURPOSE: We aimed to adapt the Turkish Sleep Condition Indicator (SCI) version and examine its psychometric properties among the general population. METHODS: This study was a cross-sectional study. The item-total correlation, standard error of measurement, Cronbach's \u03b1, and McDonald's \u03c9 were used for internal consistency. We ran confirmatory factor analysis (CFA) and network analysis to confirm the factor structure. Multigroup CFA was run to assess the measurement invariance across gender, whether clinical insomnia or not, and poor sleep quality. We correlated SCI scores with Insomnia Severity Index (ISI) and Pittsburgh Sleep Quality Index (PSQI) scores to evaluate construct validity. A receiver operating characteristic (ROC) curve analysis was conducted to calculate the cut-off score of the SCI. The temporal stability was examined with the intraclass correlation coefficient. RESULTS: Eight hundred thirty-four participants attended. Over half of the participants were women (63.2% n = 527); the mean age was 36.15 \u00b1 9.64. Confirmatory factor and network analysis results show that the two-factor correlated model had a good model fit for the SCI. The SCI had scalar level invariance across gender, having clinical insomnia and poor sleep quality in the Multigroup CFA. ROC curve analysis shows that the SCI has good sensitivity (90.3%) and specificity (91.8%) for cut-off \u2264 15. The intraclass correlation coefficient computed between the first and second SCI total scores was significant (r=0.80 with a 95% confidence interval from 0.78 to 0.87; p < 0.001). CONCLUSION: The Turkish SCI is a practical self-reported insomnia scale with good psychometric properties that can be used to screen for insomnia disorder.
\n \n\n \n \nOBJECTIVE: This study aims to characterize the time course of impedance, a crucial electrophysiological property of brain tissue, in the human thalamus (THL), amygdala-hippocampus (AMG-HPC), and posterior hippocampus (post-HPC) over an extended period. APPROACH: Impedance was periodically sampled every 5-15 minutes over several months in five subjects with drug-resistant epilepsy using an experimental neuromodulation device. Initially, we employed descriptive piecewise and continuous mathematical models to characterize the impedance response for approximately three weeks post-electrode implantation. We then explored the temporal dynamics of impedance during periods when electrical stimulation was temporarily halted, observing a monotonic increase (rebound) in impedance before it stabilized at a higher value. Lastly, we assessed the stability of amplitude and phase over the 24-hour impedance cycle throughout the multi-month recording. MAIN RESULTS: Immediately post-implantation, the impedance decreased, reaching a minimum value in all brain regions within approximately two days, and then increased monotonically over about 14 days to a stable value. The models accounted for the variance in short-term impedance changes. Notably, the minimum impedance of the THL in the most epileptogenic hemisphere was significantly lower than in other regions. During the gaps in electrical stimulation, the impedance rebound decreased over time and stabilized around 200 days post-implant, likely indicative of the foreign body response and fibrous tissue encapsulation around the electrodes. The amplitude and phase of the 24-hour impedance oscillation remained stable throughout the multi-month recording, with circadian variation in impedance dominating the long-term measures. SIGNIFICANCE: Our findings illustrate the complex temporal dynamics of impedance in implanted electrodes and the impact of electrical stimulation. We discuss these dynamics in the context of the known biological foreign body response of the brain to implanted electrodes. The data suggest that the temporal dynamics of impedance are dependent on the anatomical location and tissue epileptogenicity. These insights may offer additional guidance for the delivery of therapeutic stimulation at various time points post-implantation for neuromodulation therapy.
\n \n\n \n \nINTRODUCTION: Many people living with dementia experience sleep disturbance and there are no known effective treatments. Non-pharmacological treatment options should be the first-line sleep management. For family carers, relatives' sleep disturbance leads to interruption of their sleep, low mood and breakdown of care. Our team developed and delivered DREAMS START (Dementia RElAted Manual for Sleep; STrAtegies for RelaTives), a multimodal non-pharmacological intervention, showing it to be feasible and acceptable. The aim of this randomised controlled trial is to establish whether DREAMS START is clinically cost-effective in reducing sleep disturbances in people living with dementia living at home compared with usual care. METHODS AND ANALYSIS: We will recruit 370 participant dyads (people living with dementia and family carers) from memory services, community mental health teams and the Join Dementia Research Website in England. Those meeting inclusion criteria will be randomised (1:1) either to DREAMS START or to usual treatment. DREAMS START is a six-session (1\u2009hour/session), manualised intervention delivered every 1-2 weeks by supervised, non-clinically trained graduates. Outcomes will be collected at baseline, 4 months and 8 months with the primary outcome being the Sleep Disorders Inventory score at 8 months. Secondary outcomes for the person with dementia (all proxy) include quality of life, daytime sleepiness, neuropsychiatric symptoms and cost-effectiveness. Secondary outcomes for the family carer include quality of life, sleep disturbance, mood, burden and service use and caring/work activity. Analyses will be intention-to-treat and we will conduct a process evaluation. ETHICS AND DISSEMINATION: London-Camden & Kings Cross Ethics Committee (20/LO/0894) approved the study. We will disseminate our findings in high-impact peer-reviewed journals and at national and international conferences. This research has the potential to improve sleep and quality of life for people living with dementia and their carers, in a feasible and scalable intervention. TRIAL REGISTRATION NUMBER: ISRCTN13072268.
\n \n\n \n \n\nIntroduction\nMagnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King\u2019s College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data.\n\n\nConclusion\nThese results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study.\n
\n \n\n \n \nSleep plays a key role in supporting brain function and resilience to brain decline. It is well known that sleep changes substantially with aging and that aging is associated with deterioration of brain structure. In this study, we sought to characterize the relationship between slow wave slope (SWslope)-a key marker of sleep architecture and an indirect proxy of sleep quality-and microstructure of white matter pathways in healthy adults with no sleep complaints. Participants were 12 young (24-27 years) and 12 older (50-79 years) adults. Sleep was assessed with nocturnal electroencephalography (EEG) and the Pittsburgh Sleep Quality Index (PSQI). White matter integrity was assessed using tract-based spatial statistics (TBSS) on tensor-based metrics such as Fractional Anisotropy (FA) and Mean Diffusivity (MD). Global PSQI score did not differ between younger (n = 11) and older (n = 11) adults (U = 50, p = 0.505), but EEG revealed that younger adults had a steeper SWslope at both frontal electrode sites (F3: U = 2, p < 0.001, F4: U = 4, p < 0.001, n = 12 younger, 10 older). There were widespread correlations between various diffusion tensor-based metrics of white matter integrity and sleep SWslope, over and above effects of age (n = 11 younger, 9 older). This was particularly evident for the corpus callosum, corona radiata, superior longitudinal fasciculus, internal and external capsule. This indicates that reduced sleep slow waves may be associated with widespread white matter deterioration. Future studies should investigate whether interventions targeted at improving sleep architecture also impact on decline in white matter microstructure in older adults.
\n \n\n \n \nWe present a new software package with a library of standardised tractography protocols devised for the robust automated extraction of white matter tracts both in the human and the macaque brain. Using in vivo data from the Human Connectome Project (HCP) and the UK Biobank and ex vivo data for the macaque brain datasets, we obtain white matter atlases, as well as atlases for tract endpoints on the white-grey matter boundary, for both species. We illustrate that our protocols are robust against data quality, generalisable across two species and reflect the known anatomy. We further demonstrate that they capture inter-subject variability by preserving tract lateralisation in humans and tract similarities stemming from twinship in the HCP cohort. Our results demonstrate that the presented toolbox will be useful for generating imaging-derived features in large cohorts, and in facilitating comparative neuroanatomy studies. The software, tractography protocols, and atlases are publicly released through FSL, allowing users to define their own tractography protocols in a standardised manner, further contributing to open science.
\n \n\n \n \nAbstractThe World Health Organization (WHO) promotes physical exercise and a healthy lifestyle as means to improve youth development. However, relationships between physical lifestyle and brain development are not fully understood. Here, we asked whether a brain \u2013 physical latent mode of covariation underpins the relationship between physical activity, fitness, and physical health measures with multimodal neuroimaging markers. In 50 12-year old school pupils (26 females), we acquired multimodal whole-brain MRI, characterizing brain structure, microstructure, function, myelin content, and blood perfusion. We also acquired physical variables measuring objective fitness levels, 7-days physical activity, body-mass index, heart rate, and blood pressure. Using canonical correlation analysis we unravel a latent mode of brain \u2013 physical covariation, independent of demographics, school, or socioeconomic status. We show that MRI metrics with greater involvement in this mode also showed spatially extended patterns across the brain. Specifically, global patterns of greater grey matter perfusion, volume, cortical surface area, greater white matter extra-neurite density, and resting state networks activity, covaried positively with measures reflecting a physically active phenotype (high fit, low sedentary individuals). Showing that a physically active lifestyle is linked with systems-level brain MRI metrics, these results suggest widespread associations relating to several biological processes. These results support the notion of close brain-body relationships and underline the importance of investigating modifiable lifestyle factors not only for physical health but also for brain health early in adolescence.Significance statementAn active lifestyle is key for healthy development. In this work, we answer the following question: How do brain neuroimaging markers relate with young adolescents\u2019 level of physical activity, fitness, and physical health? Combining advanced whole-brain multimodal MRI metrics with computational approaches, we show a robust relationship between physically active lifestyles and spatially extended, multimodal brain imaging derived phenotypes. Suggesting a wider effect on brain neuroimaging metrics than previously thought, this work underlies the importance of studying physical lifestyle, as well as other brain \u2013 body relationships in an effort to foster brain health at this crucial stage in development.
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