Through the eHealth Eurocampus project IT and health professionals were trained for the challenge of fostering a spirit of innovation in eHealth in Europe as the way forward to ensure better health and better and safer care, and relevant material was developed and is now available for other schools to benefit from it. The main objectives of the eHealth Eurocampus were to improve the relevance and quality of higher education in the field of ICT applications for health, to foster employability through curricula adaptation to labour market needs and to develop entrepreneurship skills. The project partners included 8 higher education institutions, which represented 7 IT schools (Barcelona School of Informatics, Polytechnic School of the Balearic Islands, Polytech Engineer School of Montpellier, ISIS Engineering School of Castres, Glyndwr University of Wales, Hochschule Ulm, and the Department of Computer Science of the University of Cyprus) and 3 medical schools (Faculty of Nursing and Physiotherapy of the Balearic Islands, Medical School of Cyprus, Sant Joan de Déu School of Nursing - Barcelona), a regional centre of technological development and entrepreneurship promotion (Bit Foundation of Mallorca), and a European Grouping of Territorial Cooperation (EGTC Euroregion Pyrenees-Mediterranean). The consortium represented different European health management systems, which was an asset to form professionals aware of the European diversity in this area and prepared to adapt themselves to different environments and to find jobs outside their own country.The eHealth Eurocampus implemented new and innovative teaching methods that were previously tested through three Summer Schools and are now available to be used on different master courses. They cover all the main areas of eHealth: Innovation and Entrepreneurship in eHealth, IT for a Longer Independent Life, eHealth Applications and Tools, Robotics for Healthcare, and Graphics and Medical Imaging.The project direct beneficiaries were IT and health students and teachers, who have received special training, as well as patients in general, in particular elderly people and people with physical and cognitive disabilities, who will benefit from the outcomes of the research conducted within the consortium. The results and dissemination activities were designed to ensure that the eHealth Eurocampus has an impact on both participating and outside organisations. All the results are openly accessible through a specific website, which will make it easy for other universities to exploit the methods and materials developed within the project: http://ehealtheurocampus.eu/ Version en français en annexe: eHEC_SUMMARY.docx

Slow wave sleep and its underlying corticothalamocortical activity -slow oscillations- appears to be critical not only for memory but also for the maintenance of the brain?s structural and functional connectivity. At the same time, slow oscillations are an emergent pattern from the network, highly revealing of the underlying structure and dynamics of the system. In this project we plan to develop a data-constrained realistic model of the generation of slow oscillations. It will consist of a biophysically realistic model of adaptive exponential integrate-and-fire cells fully compatible with existing neuromorphic implementations in HBP. The model will go beyond state-of-art models by first describing mathematically and then fitting to real cortical data not only the first-order structure (mean), but also the second-order structure (variance and correlations) of the spatio-temporal organization of slow-wave oscillations. This model will be first developed and used to understand and document the cellular and network mechanisms slow wave oscillatory activity, and then to investigate the transformation of slow wave sleep with age and in two murine models of neurodegenerative disease associated to ageing. The model will be built and constrained using experimental data of cortical activity during slow oscillations obtained covering multiple scales. These data, together with a set of purpose-developed analytical methods, will reveal the causal contribution of genetically identified neurons to the slow wave dynamics, the 2D and 3D patterns of propagation of activity across different areas, an will go all the way to the very extensive data set of EEG obtained from large populations of humans during sleep through the SME in the project. A large emphasis will be on the analytical methods used at all levels, and the resulting tools will be useful for the scientific community. With this approach, we want to understand the underlying cortical system at multiple scales and reproduce it in silico. This will open up the possibilities for designing sensory stimulation patterns during sleep that restore young sleep in ageing individuals, an intervention expected to have a positive impact on cognition. This specific application will be directly accessible to society through the exploitation of the project led by the partner company.