Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 3 de 3
Filter
Add more filters










Database
Language
Publication year range
1.
Hum Brain Mapp ; 45(10): e26782, 2024 Jul 15.
Article in English | MEDLINE | ID: mdl-38989630

ABSTRACT

This study assesses the reliability of resting-state dynamic causal modelling (DCM) of magnetoencephalography (MEG) under conductance-based canonical microcircuit models, in terms of both posterior parameter estimates and model evidence. We use resting-state MEG data from two sessions, acquired 2 weeks apart, from a cohort with high between-subject variance arising from Alzheimer's disease. Our focus is not on the effect of disease, but on the reliability of the methods (as within-subject between-session agreement), which is crucial for future studies of disease progression and drug intervention. To assess the reliability of first-level DCMs, we compare model evidence associated with the covariance among subject-specific free energies (i.e., the 'quality' of the models) with versus without interclass correlations. We then used parametric empirical Bayes (PEB) to investigate the differences between the inferred DCM parameter probability distributions at the between subject level. Specifically, we examined the evidence for or against parameter differences (i) within-subject, within-session, and between-epochs; (ii) within-subject between-session; and (iii) within-site between-subjects, accommodating the conditional dependency among parameter estimates. We show that for data acquired close in time, and under similar circumstances, more than 95% of inferred DCM parameters are unlikely to differ, speaking to mutual predictability over sessions. Using PEB, we show a reciprocal relationship between a conventional definition of 'reliability' and the conditional dependency among inferred model parameters. Our analyses confirm the reliability and reproducibility of the conductance-based DCMs for resting-state neurophysiological data. In this respect, the implicit generative modelling is suitable for interventional and longitudinal studies of neurological and psychiatric disorders.


Subject(s)
Alzheimer Disease , Magnetoencephalography , Humans , Magnetoencephalography/methods , Magnetoencephalography/standards , Reproducibility of Results , Alzheimer Disease/physiopathology , Male , Female , Aged , Models, Neurological , Bayes Theorem
2.
BMJ Open ; 12(12): e055135, 2022 12 15.
Article in English | MEDLINE | ID: mdl-36521898

ABSTRACT

INTRODUCTION: With the pressing need to develop treatments that slow or stop the progression of Alzheimer's disease, new tools are needed to reduce clinical trial duration and validate new targets for human therapeutics. Such tools could be derived from neurophysiological measurements of disease. METHODS AND ANALYSIS: The New Therapeutics in Alzheimer's Disease study (NTAD) aims to identify a biomarker set from magneto/electroencephalography that is sensitive to disease and progression over 1 year. The study will recruit 100 people with amyloid-positive mild cognitive impairment or early-stage Alzheimer's disease and 30 healthy controls aged between 50 and 85 years. Measurements of the clinical, cognitive and imaging data (magnetoencephalography, electroencephalography and MRI) of all participants will be taken at baseline. These measurements will be repeated after approximately 1 year on participants with Alzheimer's disease or mild cognitive impairment, and clinical and cognitive assessment of these participants will be repeated again after approximately 2 years. To assess reliability of magneto/electroencephalographic changes, a subset of 30 participants with mild cognitive impairment or early-stage Alzheimer's disease will also undergo repeat magneto/electroencephalography 2 weeks after baseline. Baseline and longitudinal changes in neurophysiology are the primary analyses of interest. Additional outputs will include atrophy and cognitive change and estimated numbers needed to treat each arm of simulated clinical trials of a future disease-modifying therapy. ETHICS AND DATA STATEMENT: The study has received a favourable opinion from the East of England Cambridge Central Research Ethics Committee (REC reference 18/EE/0042). Results will be disseminated through internal reports, peer-reviewed scientific journals, conference presentations, website publication, submission to regulatory authorities and other publications. Data will be made available via the Dementias Platform UK Data Portal on completion of initial analyses by the NTAD study group.


Subject(s)
Alzheimer Disease , Cognitive Dysfunction , Humans , Middle Aged , Aged , Aged, 80 and over , Longitudinal Studies , Reproducibility of Results , Disease Progression , Cohort Studies
3.
Front Physiol ; 12: 643725, 2021.
Article in English | MEDLINE | ID: mdl-33868011

ABSTRACT

BACKGROUND: It is well-established that what is good for the heart is good for the brain. Vascular factors such as hypertension, diabetes, and high cholesterol, and genetic factors such as the apolipoprotein E4 allele increase the risk of developing both cardiovascular disease and dementia. However, the mechanisms underlying the heart-brain association remain unclear. Recent evidence suggests that impairments in vascular phenotypes and cerebrovascular reactivity (CVR) may play an important role in cognitive decline. The Heart and Brain Study combines state-of-the-art vascular ultrasound, cerebrovascular magnetic resonance imaging (MRI) and cognitive testing in participants of the long-running Whitehall II Imaging cohort to examine these processes together. This paper describes the study protocol, data pre-processing and overarching objectives. METHODS AND DESIGN: The 775 participants of the Whitehall II Imaging cohort, aged 65 years or older in 2019, have received clinical and vascular risk assessments at 5-year-intervals since 1985, as well as a 3T brain MRI scan and neuropsychological tests between 2012 and 2016 (Whitehall II Wave MRI-1). Approximately 25% of this cohort are selected for the Heart and Brain Study, which involves a single testing session at the University of Oxford (Wave MRI-2). Between 2019 and 2023, participants will undergo ultrasound scans of the ascending aorta and common carotid arteries, measures of central and peripheral blood pressure, and 3T MRI scans to measure CVR in response to 5% carbon dioxide in air, vessel-selective cerebral blood flow (CBF), and cerebrovascular lesions. The structural and diffusion MRI scans and neuropsychological battery conducted at Wave MRI-1 will also be repeated. Using this extensive life-course data, the Heart and Brain Study will examine how 30-year trajectories of vascular risk throughout midlife (40-70 years) affect vascular phenotypes, cerebrovascular health, longitudinal brain atrophy and cognitive decline at older ages. DISCUSSION: The study will generate one of the most comprehensive datasets to examine the longitudinal determinants of the heart-brain association. It will evaluate novel physiological processes in order to describe the optimal window for managing vascular risk in order to delay cognitive decline. Ultimately, the Heart and Brain Study will inform strategies to identify at-risk individuals for targeted interventions to prevent or delay dementia.

SELECTION OF CITATIONS
SEARCH DETAIL
...