Alcohol addiction ranks among the primary global causes of preventable death and disabilities in human population, but treatment options are very limited. Rational strategies for design and development of novel, evidence based therapies for alcohol addiction are still missing. Within this project, we will utilize a translational approach based on clinical studies and animal experiments to fill this gap. We will provide a novel discovery strategy based on systems biology concepts that uses mathematical and network theoretical models to identify brain sites and functional networks that can be targeted specifically by therapeutic interventions. To build predictive models of the ‘relapse-prone’ state of brain networks we will use magnetic resonance imaging and neurochemical data from patients and laboratory animals. The mathematical models will be rigorously tested through experimental procedures aimed to guide network dynamics towards increased resilience. We expect to identify hubs that promote ‘relapse-proneness’ and to predict how aberrant network states could be normalized. Proof of concept experiments in animal will need to demonstrate this possibility by showing directed remodeling of functional brain networks by targeted interventions prescribed by the theoretical framework. Thus, our translational goal will be achieved by a theoretical and experimental framework for making predictions based on fMRI and mathematical modeling, which is verified in animals, and which can be transferred to humans. To achieve this goal we have assembled an interdisciplinary consortium (eight European countries) of world-class expertise in all complementary skills required for the project. If successful this project will positively impact on the development of new therapies for a disorder with largely unmet clinical needs, and thus help to address a serious and widespread health problem in our societies.
Field of science
- /natural sciences/mathematics/applied mathematics/mathematical model
- /medical and health sciences/clinical medicine/radiology/medical imaging/magnetic resonance imaging
Call for proposal
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Funding SchemeRIA - Research and Innovation action