A key challenge towards untangling the complexity of the human brain is to understand how functionally specialised subunits are interconnected in the brain’s network to influence each other and produce experiences and behaviour. Magnetic resonance imaging (MRI) uniquely allows to explore this systems-level view of neural connections and to probe brain organisation. The connectome, the comprehensive map of brain connections, is unique in every person and reflects the organisation that constraints what the brain can and cannot compute. Yet, there are fundamental limitations in its mapping. Lack of standardised, accurate measures of brain connections through MRI and absence of objective references introduce errors and reduce interpretability and reproducibility.
Mapping and understanding brain connectivity is also fundamental for gaining insight into psychiatric disorders, which affect half a billion people worldwide (~165 million people in the EU alone) and according to the World Health Organization, they are amongst the leading causes of ill-health and years lived with disability. However, their diagnosis and treatment remain particularly challenging, due to a lack of understanding of how symptoms map onto brain circuits and potential abnormalities in the underlying neural connectivity. Therefore, having the ability to robustly measure disruptions of brain connectivity of individual patients can open up unique opportunities for aiding diagnosis and subsequently informing personalised treatment.
Building on my expertise, I will develop novel algorithmic platforms and image analytics for brain connectivity mapping. Contrary to conventional approaches that typically rely on ad-hoc processing, the NeuroMetrology team will establish measurement principles to allow, quantitative and objective characterisation of the brain connectome and its individual variability. Through a mixture of highly-interdisciplinary computational and experimental research, I propose a comprehensive framework governed by principles of metrology, the science of measurement. The project will develop methodologies that a) improve accuracy and precision of measurements of brain connections, by unifying diverse types of imaging information (WP1), b) harmonise and standardise such approaches for the individual across different measurement tools and MRI scanners (WP2) and link these measurements to reference standards, reflecting the population (WP3).
I will subsequently apply these new methodologies to investigate representative scientific questions that rely on the ability to capture personalised signatures of the brain architecture (WP4). Specifically, I will explore the links of neural connectivity patterns to behavioural traits and the potential associations of disruptions in brain circuits with symptoms in mental health disorders. In doing so, this programme will establish a paradigm shift in how neuroimaging data are analysed and neural wiring diagrams are obtained in a standardised manner, opening new translational possibilities for personalised medicine applications of neuroimaging-based phenotypes.
