The modern environment is associated with an increasing burden of non-communicable diseases (NCDs). Mounting evidence implicates environmental exposures, experienced early in life (including in utero), in the aetiology of many NCDs, though the cellular/molecular mechanism(s) underlying this elevated risk across the life course remain unclear. Epigenetic variation has emerged as a candidate mediator of such effects. The Barwon Infant Study (BIS) is a population-derived birth cohort study (n = 1074 infants) with antenatal recruitment, conducted in the south-east of Australia (Victoria). BIS has been designed to facilitate a detailed mechanistic investigation of development within an epidemiological framework. The broad objectives are to investigate the role of specific environmental factors, gut microbiota and epigenetic variation in early-life development, and subsequent immune, allergic, cardiovascular, respiratory and neurodevelopmental outcomes. Participants have been reviewed at birth and at 1, 6, 9 and 12 months, with 2- and 4-year reviews under way. Biological samples and measures include: maternal blood, faeces and urine during pregnancy; infant urine, faeces and blood at regular intervals during the first 4 years; lung function at 1 month and 4 years; cardiovascular assessment at 1 month and 4 years; skin-prick allergy testing and food challenge at 1 year; and neurodevelopmental assessment at 9 months, 2 and 4 years. Data access enquiries can be made at [www.barwoninfantstudy.org.au] or via [peter.vuillermin@deakin.edu.au].

The Wilson–Cowan population model of neural activity has greatly influenced our understanding of the mechanisms for the generation of brain rhythms and the emergence of structured brain activity. As well as the many insights that have been obtained from its mathematical analysis, it is now widely used in the computational neuroscience community for building large-scale in silico brain networks that can incorporate the increasing amount of knowledge from the Human Connectome Project. Here, we consider a neural population model in the spirit of that originally developed by Wilson and Cowan, albeit with the added advantage that it can account for the phenomena of event-related synchronization and desynchronization. This derived mean-field model provides a dynamic description for the evolution of synchrony, as measured by the Kuramoto order parameter, in a large population of quadratic integrate-and-fire model neurons. As in the original Wilson–Cowan framework, the population firing rate is at the heart of our new model; however, in a significant departure from the sigmoidal firing rate function approach, the population firing rate is now obtained as a real-valued function of the complex-valued population synchrony measure. To highlight the usefulness of this next-generation Wilson–Cowan style model, we deploy it in a number of neurobiological contexts, providing understanding of the changes in power spectra observed in electro- and magnetoencephalography neuroimaging studies of motor cortex during movement, insights into patterns of functional connectivity observed during rest and their disruption by transcranial magnetic stimulation, and to describe wave propagation across cortex.

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The contribution of structural connectivity to functional brain states remains poorly understood. We present a mathematical and computational study suited to assess the structure–function issue, treating a system of Jansen–Rit neural mass nodes with heterogeneous structural connections estimated from diffusion MRI data provided by the Human Connectome Project. Via direct simulations we determine the similarity of functional (inferred from correlated activity between nodes) and structural connectivity matrices under variation of the parameters controlling single-node dynamics, highlighting a nontrivial structure–function relationship in regimes that support limit cycle oscillations. To determine their relationship, we firstly calculate network instabilities giving rise to oscillations, and the so-called ‘false bifurcations’ (for which a significant qualitative change in the orbit is observed, without a change of stability) occurring beyond this onset. We highlight that functional connectivity (FC) is inherited robustly from structure when node dynamics are poised near a Hopf bifurcation, whilst near false bifurcations, and structure only weakly influences FC. Secondly, we develop a weakly coupled oscillator description to analyse oscillatory phase-locked states and, furthermore, show how the modular structure of FC matrices can be predicted via linear stability analysis. This study thereby emphasises the substantial role that local dynamics can have in shaping large-scale functional brain states.