TIHM: An open dataset for remote healthcare monitoring in dementia.

Dementia is a progressive condition that affects cognitive and functional abilities. There is a need for reliable and continuous health monitoring of People Living with Dementia (PLWD) to improve their quality of life and support their independent living. Healthcare services often focus on addressing and treating already established health conditions that affect PLWD.

Using home monitoring technology to study the effects of traumatic brain injury in older multimorbid adults.

Internet of things (IOT) based in-home monitoring systems can passively collect high temporal resolution data in the community, offering valuable insight into the impact of health conditions on patients' day-to-day lives. We used this technology to monitor activity and sleep patterns in older adults recently discharged after traumatic brain injury (TBI). The demographics of TBI are changing, and it is now a leading cause of hospitalisation in older adults.

Multicohort cross-sectional study of cognitive and behavioural digital biomarkers in neurodegeneration: the Living Lab Study protocol.

Introduction And Aims: Digital biomarkers can provide a cost-effective, objective and robust measure for neurological disease progression, changes in care needs and the effect of interventions. Motor function, physiology and behaviour can provide informative measures of neurological conditions and neurodegenerative decline. New digital technologies present an opportunity to provide remote, high-frequency monitoring of patients from within their homes.

Using home monitoring technology to study the effects of traumatic brain injury on older multimorbid adults: protocol for a feasibility study.

Introduction: The prevalence of traumatic brain injury (TBI) among older adults is increasing exponentially. The sequelae can be severe in older adults and interact with age-related conditions such as multimorbidity. Despite this, TBI research in older adults is sparse.

The effect of COVID-19 on the home behaviours of people affected by dementia.

The COVID-19 pandemic has dramatically altered the behaviour of most of the world's population, particularly affecting the elderly, including people living with dementia (PLwD). Here we use remote home monitoring technology deployed into 31 homes of PLwD living in the UK to investigate the effects of COVID-19 on behaviour within the home, including social isolation. The home activity was monitored continuously using unobtrusive sensors for 498 days from 1 December 2019 to 12 April 2021.

Home monitoring of daily living activities and prediction of agitation risk in a cohort of people living with dementia.

Background: People living with dementia (PLWD) have an increased susceptibility to developing adverse physical and psychological events. Internet of Things (IoT) technologies provides new ways to remotely monitor patients within the comfort of their homes, particularly important for the timely delivery of appropriate healthcare. Presented here is data collated as part of the on-going UK Dementia Research Institute's Care Research and Technology Centre cohort and Technology Integrated Health Management (TIHM) study.

Axonal marker neurofilament light predicts long-term outcomes and progressive neurodegeneration after traumatic brain injury.

Axonal injury is a key determinant of long-term outcomes after traumatic brain injury (TBI) but has been difficult to measure clinically. Fluid biomarker assays can now sensitively quantify neuronal proteins in blood. Axonal components such as neurofilament light (NfL) potentially provide a diagnostic measure of injury.

Dissociable effects of age and Parkinson's disease on instruction-based learning.

The cognitive deficits associated with Parkinson's disease vary across individuals and change across time, with implications for prognosis and treatment. Key outstanding challenges are to define the distinct behavioural characteristics of this disorder and develop diagnostic paradigms that can assess these sensitively in individuals. In a previous study, we measured different aspects of attentional control in Parkinson's disease using an established fMRI switching paradigm.

Associations between dimensions of behaviour, personality traits, and mental-health during the COVID-19 pandemic in the United Kingdom.

The COVID-19 pandemic (including lockdown) is likely to have had profound but diverse implications for mental health and well-being, yet little is known about individual experiences of the pandemic (positive and negative) and how this relates to mental health and well-being, as well as other important contextual variables. Here, we analyse data sampled in a large-scale manner from 379,875 people in the United Kingdom (UK) during 2020 to identify population variables associated with mood and mental health during the COVID-19 pandemic, and to investigate self-perceived pandemic impact in relation to those variables. We report that while there are relatively small population-level differences in mood assessment scores pre- to peak-UK lockdown, the size of the differences is larger for people from specific groups, e.

Neuroimaging evidence for a network sampling theory of individual differences in human intelligence test performance.

Despite a century of research, it remains unclear whether human intelligence should be studied as one dominant, several major, or many distinct abilities, and how such abilities relate to the functional organisation of the brain. Here, we combine psychometric and machine learning methods to examine in a data-driven manner how factor structure and individual variability in cognitive-task performance relate to dynamic-network connectomics. We report that 12 sub-tasks from an established intelligence test can be accurately multi-way classified (74%, chance 8.

The Effects of Working Memory Training on Brain Activity.

This study aimed to investigate if two weeks of working memory (WM) training on a progressive N-back task can generate changes in the activity of the underlying WM neural network. Forty-six healthy volunteers (23 training and 23 controls) were asked to perform the N-back task during three fMRI scanning sessions: (1) before training, (2) after the half of training sessions, and (3) at the end. Between the scanning sessions, the experimental group underwent a 10-session training of working memory with the use of an adaptive version of the N-back task, while the control group did not train anything.

Longitudinal functional connectivity changes related to dopaminergic decline in Parkinson's disease.

Background: Resting-state functional magnetic resonance imaging (fMRI) studies have demonstrated that basal ganglia functional connectivity is altered in Parkinson's disease (PD) as compared to healthy controls. However, such functional connectivity alterations have not been related to the dopaminergic deficits that occurs in PD over time.

Objectives: To examine whether functional connectivity impairments are correlated with dopaminergic deficits across basal ganglia subdivisions in patients with PD both cross-sectionally and longitudinally.

Inhibition-Related Cortical Hypoconnectivity as a Candidate Vulnerability Marker for Obsessive-Compulsive Disorder.

Background: Obsessive-compulsive disorder (OCD) is a prevalent neuropsychiatric condition, with biological models implicating disruption of cortically mediated inhibitory control pathways, ordinarily serving to regulate our environmental responses and habits. The aim of this study was to evaluate inhibition-related cortical dysconnectivity as a novel candidate vulnerability marker of OCD.

Methods: In total, 20 patients with OCD, 18 clinically asymptomatic first-degree relatives of patients with OCD, and 20 control participants took part in a neuroimaging study comprising a functional magnetic resonance imaging stop signal task.

Probing cortical and sub-cortical contributions to instruction-based learning: Regional specialisation and global network dynamics.

Diverse cortical networks and striatal brain regions are implicated in instruction-based learning (IBL); however, their distinct contributions remain unclear. We use a modified fMRI paradigm to test two hypotheses regarding the brain mechanisms that underlie IBL. One hypothesis proposes that anterior caudate and frontoparietal regions transiently co-activate when new rules are being bound in working memory.

Dynamic network coding of working-memory domains and working-memory processes.

The classic mapping of distinct aspects of working memory (WM) to mutually exclusive brain areas is at odds with the distributed processing mechanisms proposed by contemporary network science theory. Here, we use machine-learning to determine how aspects of WM are dynamically coded in the human brain. Using cross-validation across independent fMRI studies, we demonstrate that stimulus domains (spatial, number and fractal) and WM processes (encode, maintain, probe) are classifiable with high accuracy from the patterns of network activity and connectivity that they evoke.

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker.

Objective: Huntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real-life clinical diagnosis in HD.

Major Shifts in Glial Regional Identity Are a Transcriptional Hallmark of Human Brain Aging.

Gene expression studies suggest that aging of the human brain is determined by a complex interplay of molecular events, although both its region- and cell-type-specific consequences remain poorly understood. Here, we extensively characterized aging-altered gene expression changes across ten human brain regions from 480 individuals ranging in age from 16 to 106 years. We show that astrocyte- and oligodendrocyte-specific genes, but not neuron-specific genes, shift their regional expression patterns upon aging, particularly in the hippocampus and substantia nigra, while the expression of microglia- and endothelial-specific genes increase in all brain regions.

Human mesostriatal response tracks motivational tendencies under naturalistic goal conflict.

Goal conflict situations, involving the simultaneous presence of reward and punishment, occur commonly in real life, and reflect well-known individual differences in the behavioral tendency to approach or avoid. However, despite accumulating neural depiction of motivational processing, the investigation of naturalistic approach behavior and its interplay with individual tendencies is remarkably lacking. We developed a novel ecological interactive scenario which triggers motivational behavior under high or low goal conflict conditions.

Cry for her or cry with her: context-dependent dissociation of two modes of cinematic empathy reflected in network cohesion dynamics.

Two empathy-related processes were recently distinguished neuroscientifically: automatic embodied-simulation (ES) based on visceromotor representation of another's affective state via cingulo-insulary circuit, and emotional sharing relying on cognitive 'theory of mind' (ToM) via prefrontal-temporo-parietal circuit. Evidence that these regions are not only activated but also function as networks during empathic experience has yet to been shown. Employing a novel approach by analyzing fMRI fluctuations of network cohesion while viewing films portraying personal loss, this study demonstrates increased connectivity during empathic engagement (probed by behavioral and parasympathetic indices) both within these circuits, and between them and a set of limbic regions.

Portraying emotions at their unfolding: a multilayered approach for probing dynamics of neural networks.

Dynamic functional integration of distinct neural systems plays a pivotal role in emotional experience. We introduce a novel approach for studying emotion-related changes in the interactions within and between networks using fMRI. It is based on continuous computation of a network cohesion index (NCI), which is sensitive to both strength and variability of signal correlations between pre-defined regions.

The supramolecular organization of the C. elegans nuclear lamin filament.

Nuclear lamins are involved in most nuclear activities and are essential for retaining the mechano-elastic properties of the nucleus. They are nuclear intermediate filament (IF) proteins forming a distinct meshwork-like layer adhering to the inner nuclear membrane, called the nuclear lamina. Here, we present for the first time, the three-dimensional supramolecular organization of lamin 10 nm filaments and paracrystalline fibres.