Objetivo Neural network simulations have been a driving force behind our advances in the artificial intelligence filed, but also a key tool in our understanding of the human brain. However, exploring such networks usually engages substantial computational resources requiring specific programing skills and dedicated facilities. In our main project NETSIGNAL, we have developed computational environment ARACHNE aiming to facilitate high-end neural network exploration among scientific and industrial users. ARACHNE enables an investigator to construct and explore cellular networks of arbitrary biophysical and architectural complexity using a simple interface on a local computer or a mobile device. Through small-file exchange via the internet, the interface controls a pre-configured computational kernel installed on a remote computer cluster or cloud. Uniquely, ARACHNE can integrate traditional wired network connections with diffuse, volume-transmitted type of inter-cellular signalling, to reflect the emerging role of glia in brain processing. ARACHNE thus affords a flexible neural network design and incorporates latest advances in neuroscience while providing a portable console suitable for IT-untrained explorers. ARACHNE has passed a feasibility and novelty test by independent experts (Aleksin et al, PLoS Comp Biology 2017, in press), its test version is available on-line (https://github.com/LeonidSavtchenko/Arachne/). Our goal here is to determine market potential and the commercial viability of ARACHNE and its conceptual design, but also to establish industry-standard provisions for its commercial exploitation. We plan: (a) to upgrade ARACHNE technical specs, interface, support, etc. to the industry standard; (b) to assess the market and the competitors; (c) to determine IPR position and strategy, (d) to explore budgeting and further funding strategy, (e) to establish initial provisions for its distribution and/or licensing of ARACHNE. Ámbito científico natural sciencesbiological sciencesneurobiologynatural sciencescomputer and information sciencesinternetengineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networksmobile networknatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Palabras clave brain synaptic circuit neural network astroglia Programa(s) H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC) Main Programme Tema(s) ERC-2017-PoC - ERC-Proof of Concept Convocatoria de propuestas ERC-2017-PoC Consulte otros proyectos de esta convocatoria Régimen de financiación ERC-POC - Proof of Concept Grant Institución de acogida UNIVERSITY COLLEGE LONDON Aportación neta de la UEn € 148 550,00 Dirección GOWER STREET WC1E 6BT London Reino Unido Ver en el mapa Región London Inner London — West Camden and City of London Tipo de actividad Higher or Secondary Education Establishments 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 € 148 550,00 Beneficiarios (1) Ordenar alfabéticamente Ordenar por aportación neta de la UE Ampliar todo Contraer todo UNIVERSITY COLLEGE LONDON Reino Unido Aportación neta de la UEn € 148 550,00 Dirección GOWER STREET WC1E 6BT London Ver en el mapa Región London Inner London — West Camden and City of London Tipo de actividad Higher or Secondary Education Establishments 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 € 148 550,00
