#	Pagina
attuale pagina	/open-h2020/projects/209963/index.html

Opendata, web and dolomites

NEUROMODEL SIGNED

Statistical Modelling for relating multimodal neuroimaging to clinical outcomes in order to predict patient response to depression therapy.

Total Cost €

EC-Contrib. €

Partnership

Views

Outcomes and
results

NEUROMODEL project word cloud

Explore the words cloud of the NEUROMODEL project. It provides you a very rough idea of what is the project "NEUROMODEL" about.

linear data reuptake depression patient variables life followed 15 multimodal serotonin 50 insufficient treatments europeans lvm host involve every gaussian inhibitor environmental latent emission perfectly acquired functional cohort depressed expand adjusted suffer fmri integrate drug dimensional situated healthy magnetic types medicine relationships forms identification outcome foundation chosen tomography personalized uniquely neuropsychological genetic complexity brain images resonance longitudinal intervention outcomes ssri therapy combines statistical exist model ultimate adapt predict positron psychological posit deal heterogeneous individualized biomarkers disability database resolution pet latter later neurobiology individuals imaging single mdd combination treatment selective patients flexible

Project "NEUROMODEL" data sheet

The following table provides information about the project.

Coordinator	REGION HOVEDSTADEN Organization address address: KONGENS VAENGE 2 city: HILLEROD postcode: 3400 website: www.regionh.dk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.
Coordinator Country	Denmark [DK]
Project website	https://bozenne.github.io/Funding/
Total cost	200˙194 €
EC max contribution	200˙194 € (100%)
Programme	1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
Code Call	H2020-MSCA-IF-2016
Funding Scheme	MSCA-IF-EF-ST
Starting year	2017
Duration (year-month-day)	from 2017-06-01 to 2019-05-31

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	REGION HOVEDSTADEN REGION HOVEDSTADEN Organization address address: KONGENS VAENGE 2 city: HILLEROD postcode: 3400 website: www.regionh.dk contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	DK (HILLEROD)	coordinator	200˙194.00

Map

Project objective

Every year, 1 out of 15 Europeans suffer from major depression (MDD) and MDD is the third cause of Disability-adjusted life-years. Today, the available treatments are clearly insufficient; only about 50% of MDD patients respond to drug intervention. We here posit that identification of biomarkers that can predict treatment response is needed to adapt a personalized medicine approach, and most likely this will involve not a single outcome but a combination of multimodal brain imaging outcomes, psychological, genetic, and environmental data. The complexity of such data requires a complex statistical model that currently does not exist. Thus, my aim is to develop a new flexible statistical method that can take into account heterogeneous types of data. More specifically, I will develop a fully flexible Latent Variable Model (LVM) that can deal with high dimensional measurements (e.g. images), non-Gaussian variables, and non-linear relationships. I will apply this flexible LVM on existing data from depressed and healthy individuals and later expand the application to predict treatment outcomes. The latter data are currently acquired and includes a cohort of MDD patients treated with a selective serotonin reuptake inhibitor (SSRI), followed in a longitudinal design. The chosen host institution is perfectly situated to this project, as they have an established unique database including, e.g., functional Magnetic Resonance Imaging (fMRI), high resolution Positron Emission Tomography (PET), and neuropsychological test outcomes. This research project uniquely combines advanced statistical modelling of rich data sets with the ultimate aim to establish individualized depression therapy. Moreover, it forms a foundation for a more general approach to integrate brain neurobiology in terms of imaging outcomes with other patient-specific data.

Publications

List of publications.
year	authors and title	journal	last update
2019	Martin K. Madsen, Patrick M. Fisher, Daniel Burmester, Agnete Dyssegaard, Dea S. StenbÃ¦k, Sara Kristiansen, Sys S. Johansen, Sczabolz Lehel, Kristian Linnet, Claus Svarer, David Erritzoe, Brice Ozenne, Gitte M. Knudsen Psychedelic effects of psilocybin correlate with serotonin 2A receptor occupancy and plasma psilocin levels published pages: 1328-1334, ISSN: 0893-133X, DOI: 10.1038/s41386-019-0324-9	Neuropsychopharmacology 44/7	2019-09-02
2019	S. E. Ebert, P. Jensen, B. Ozenne, S. Armand, C. Svarer, D. S. Stenbaek, K. Moeller, A. Dyssegaard, G. Thomsen, J. Steinmetz, B. H. Forchhammer, G. M. Knudsen, L. H. Pinborg Molecular imaging of neuroinflammation in patients after mild traumatic brain injury: a longitudinal 123 Iâ€CLINDE single photon emission computed tomography study published pages: , ISSN: 1351-5101, DOI: 10.1111/ene.13971	European Journal of Neurology	2019-09-02
2019	Martin NÃ¸rgaard, Brice Ozenne, Claus Svarer, Stephen C. Strother, Vibe G. Frokjaer, Gitte M. Knudsen, and Melanie Ganz Preprocessing, prediction and significance: Framework and application to brain imaging published pages: , ISSN: , DOI:		2019-09-02

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "NEUROMODEL" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "NEUROMODEL" are provided by the European Opendata Portal: CORDIS opendata.