Objetivo Brain functions likely emerge from the concerted, context-dependent operations of its microscopic and macroscopic networks. Therefore, the organization and operational principles of such complex systems may be best investigated by using multi-modal approaches, including concurrent measurements of neural activity on multiple spatiotemporal scales. Performing and interpreting such multi-scale measures, though, presents enormous challenges for both experimental and mathematical neuroscientists. Existing analysis methods, however, make limited use of newly acquired concurrent multi-scale information. To dramatically advance analysis methods for these data, I propose a novel multi-scale model that bridges the gap between single cell statistics and neural mass signals. The model describes mixed discrete statistics, covering single cell and small population spike trains, as well as continuous statistics, such as those describing mesoscopic and macroscopic measures of mass neural activity in neuroimaging experiments. These elements are combined by means of copulas, describing multivariate interactions within and between scales of activity. I will extend this method to the level of efficient applicability and, in the course of a secondment with Prof. Logothetis at the Max Planck Institute in Tübingen, exploit the technique to solve current problems of multi-scale analysis of interactions between cortical and subcortical brain areas. The new mathematical approach will lead to a set of new tools that I will disseminate in an Open Source format for maximal impact, and will be widely applicable to multi-modal recordings in animals and humans, in both research and clinical settings. My own application of this method to multi-modal datasets will establish a deeper general understanding of the mechanisms of large-scale communication among brain areas, with particular emphasis on the principles of communication among networks involved in the formation of declarative memory. Ámbito científico natural sciencesbiological sciencesneurobiologynatural sciencescomputer and information sciencessoftwarenatural sciencesmathematicsapplied mathematicsstatistics and probabilitynatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Programa(s) H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions Main Programme H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility Tema(s) MSCA-IF-2014-EF - Marie Skłodowska-Curie Individual Fellowships (IF-EF) Convocatoria de propuestas H2020-MSCA-IF-2014 Consulte otros proyectos de esta convocatoria Régimen de financiación MSCA-IF-EF-ST - Standard EF Coordinador FONDAZIONE ISTITUTO ITALIANO DI TECNOLOGIA Aportación neta de la UEn € 168 277,20 Dirección VIA MOREGO 30 16163 Genova Italia Ver en el mapa Región Nord-Ovest Liguria Genova Tipo de actividad Research Organisations Enlaces Contactar con la organización Opens in new window Sitio web Opens in new window Participación en los programas de I+D de la UE Opens in new window Red de colaboración de HORIZON Opens in new window Coste total € 168 277,20
