Objective
To reduce the burden of mental disorders it is a formidable aim to identify widely applicable disease markers based on
neural processes, which predict psychopathology and allow for targeted interventions. We will generate a neurobehavioural
framework for stratification of psychopathology by characterising links between network properties of brain function and
structure and reinforcement–related behaviours, which are fundamental components of some of the most prevalent mental
disorders, major depression, alcohol use disorder and ADHD. We will assess if network configurations define subtypes
within and if they correspond to comorbidity across these diagnoses. We will identify discriminative data modalities and
characterize predictors of future psychopathology.
To identify specific neurobehavioural clusters we will carry out precision phenotyping of 900 patients with major
depression, ADHD and alcohol use disorders and 300 controls, which we will investigate with innovative deep machine
learning methods derived from artifical intelligence research. Development of these methods will optimize exploitation of a
wide range of assessment modalities, including functional and structural neuroimaging, cognitive, emotional as well as
environmental measures. The neurobehavioural clusters resulting from this analysis will be validated in a longitudinal
population-based imaging genomics cohort, the IMAGEN sample of over 2000 participants spanning the period from
adolescence to adulthood and integrated with information generated from genomic and imaging-genomic meta-analyses of
>300.000 individuals.
By targeting specific neural processes the resulting stratification markers will serve as paradigmatic examples for a
diagnostic classification, which is based upon quantifiable neurobiological measures, thus enabling targetted early
intervention, identification of novel pharmaceutical targets and the establishment of neurobehaviourally informed endpoints
for clinical trials.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences genetics
- medical and health sciences clinical medicine psychiatry
- natural sciences chemical sciences organic chemistry alcohols
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
ERC-ADG - Advanced Grant
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2015-AdG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
10117 Berlin
Germany
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.