Dementia is common in Parkinson’s disease but there is wide variation in severity and timing, and identifying at-risk individuals has proved challenging. Lanskey et al. provide an overview of conventional and emerging neuroimaging techniques with the potential to predict dementia in patients with Parkinson’s disease.

We present a hierarchical (i.e., empirical) Bayesian framework for testing hypotheses about synaptic neurotransmission, based on the integration of ultra-high field magnetic resonance spectroscopy (7T-MRS) and magnetoencephalography. A first level dynamic causal modelling of cortical microcircuits is used to infer the connectivity parameters of a generative model of neurophysiological observations. At the second level, 7T- magnetic resonance spectroscopy (MRS) estimates of regional neurotransmitter concentration supply empirical priors on synaptic connectivity. We compare the evidence for alternative empirical priors, defined by monotonic functions of spectroscopic estimates, on subsets of synaptic connections. For efficiency and reproducibility, we used Bayesian model reduction, parametric empirical Bayes and variational Bayesian inversion. In particular, we used Bayesian model reduction to compare models of how spectroscopic neurotransmitter measures inform estimates of synaptic connectivity. This identifies the synaptic connections that are influenced by neurotransmitter levels, as measured by 7T-MRS . We demonstrate the method using resting-state magnetoencephalography (i.e., task-free recording) and 7T-MRS data from healthy adults. We validate the analysis by split-sampling of the magnetoencephalography dataset. Our results confirm the hypotheses that GABA concentration influences local recurrent inhibitory intrinsic connectivity in deep and superficial cortical layers, while glutamate influences the excitatory connections between superficial and deep layers and connections from superficial to inhibitory interneurons. The method is suitable for applications with magnetoencephalography or electroencephalography, and is well-suited to evince the mechanisms of neurological and psychiatric disorders, including responses to psychopharmacological interventions.

IntroductionWith 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 analysisThe 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 statementThe 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.