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Brain network based stratification of mental illness

Ziel

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.

Aufforderung zur Vorschlagseinreichung

ERC-2015-AdG
Andere Projekte für diesen Aufruf anzeigen

Finanzierungsplan

ERC-ADG - Advanced Grant

Gastgebende Einrichtung

CHARITE - UNIVERSITAETSMEDIZIN BERLIN
Adresse
Chariteplatz 1
10117 Berlin
Deutschland
Aktivitätstyp
Higher or Secondary Education Establishments
EU-Beitrag
€ 823 242,53

Begünstigte (5)

CHARITE - UNIVERSITAETSMEDIZIN BERLIN
Deutschland
EU-Beitrag
€ 823 242,53
Adresse
Chariteplatz 1
10117 Berlin
Aktivitätstyp
Higher or Secondary Education Establishments
THE UNIVERSITY OF NOTTINGHAM
United Kingdom
EU-Beitrag
€ 314 162,50
Adresse
University Park
NG7 2RD Nottingham
Aktivitätstyp
Higher or Secondary Education Establishments
THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD, OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN
Irland
EU-Beitrag
€ 182 601,25
Adresse
College Green
2 Dublin
Aktivitätstyp
Higher or Secondary Education Establishments
UNIVERSITY OF SOUTHAMPTON
United Kingdom
EU-Beitrag
€ 354 385
Adresse
Highfield
SO17 1BJ Southampton
Aktivitätstyp
Higher or Secondary Education Establishments
KING'S COLLEGE LONDON

Beteiligung beendet

United Kingdom
EU-Beitrag
€ 1 719 823,60
Adresse
Strand
WC2R 2LS London
Aktivitätstyp
Higher or Secondary Education Establishments