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Neuro-Metrology

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Brain connectivity metrology for personalised neuroimaging in health and disease

A key step 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. Magnet... ver más

30/09/2026

THE UNIVERSITY OF...

2M€

Presupuesto del proyecto: 2M€

Líder del proyecto

THE UNIVERSITY OF NOTTINGHAM No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2021-06-25

ERC-2020-COG: ERC CONSOLIDATOR GRANTS

I+D

Cerrada hace 4 años

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Información adicional privada

No hay información privada compartida para este proyecto. Habla con el coordinador.

2 Participantes

THE UNIVERSITY OF NOTTINGHAM

2.00M€ | Lider

ASTORGANA FISH

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Duración del proyecto: 63 meses Fecha Inicio: 2021-06-25
Fecha Fin: 2026-09-30

Líder del proyecto

THE UNIVERSITY OF NOTTINGHAM No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 2M€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto A key step 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 uniquely allows to explore this systems-level view of neural connections and to probe brain organisation. Despite great promise, conventional approaches have experienced difficulties in delivering robust and tangible applications, particularly for the individual, either for neuroscience or clinical practice. The connectome, the comprehensive map of brain connections, is unique in every person; yet there are fundamental limitations in its personalised mapping. Lack of standardised, accurate measures of brain connections and absence of objective references introduce errors and reduce interpretability and reproducibility. I will develop a novel algorithmic platform for brain connectivity mapping, which will establish measurement principles to allow, for the first time, quantitative and objective characterisation of the brain connectome and its individual variability. Through a mixture of highly-interdisciplinary computational and experimental research, I propose to tackle unmet challenges and shift the paradigm from ad-hoc image processing pipelines to a comprehensive framework governed by principles of metrology. I will develop platforms that a) integrate cross-modal information for accurate standardised measurements of brain connections and b) link these measurements to reference standards, reflecting the population, as well as the individual. I will subsequently tackle important representative questions that rely on the ability to capture personalised signatures of the brain architecture: in basic neuroscience, the ability to predict the neural connectivity that underpins behavioural traits; in clinical neuroscience, the ability to use normative models of connections to improve subject-specific diagnosis in depression.

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