Project description
Machine learning discovers the rules governing the neural substrates of real learning
Models are used in virtually all fields from aerospace design to drug development. They are developed with observational or experimental data and refined through additional data and high-tech methods including machine learning. The better they get at predicting real-life and new outcomes, the more valuable they are in so many ways. Modelling the rules governing the changing 'weights' of synaptic connection between neurons (synaptic plasticity) that underlies learning and memory is an extremely challenging task. The EU-funded SynapSeek project will bring together a wealth of published data with advanced machine learning methods to 'discover' synaptic plasticity rules in silico.
Fields of science
Programme(s)
Funding Scheme
ERC-COG - Consolidator Grant
Host institution
INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
Net EU contribution
€ 1 768 919,41
Address
Am Campus 1
3400 Klosterneuburg
Austria
3400 Klosterneuburg
Austria
See on map
Region
Niederösterreich Wiener Umland/Nordteil
Activity type
Higher or Secondary Education Establishments
Other funding
€ 0,00
Beneficiaries (2)
INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
Austria
Net EU contribution
€ 1 768 919,41
Address
Am Campus 1
3400 Klosterneuburg
3400 Klosterneuburg
See on map
Region
Niederösterreich Wiener Umland/Nordteil
Activity type
Higher or Secondary Education Establishments
Other funding
€ 0,00
THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD
Participation ended
United Kingdom
Net EU contribution
€ 29 685,59
Address
Wellington Square University Offices
OX1 2JD Oxford
OX1 2JD Oxford
Region
South East (England) Berkshire, Buckinghamshire and Oxfordshire Oxfordshire
Activity type
Higher or Secondary Education Establishments
Other funding
€ 0,00