Project description DEENESFRITPL Mechanistic insight into how our brain learns Survival and adaptation to a changing environment is driven by the ability of animals and humans to utilise prior knowledge to quickly learn new behaviours. However, the mechanism by which the brain combines old information with new input remains elusive. The EU-funded Learning2Learn project aims to elucidate the role of the medial prefrontal cortex of the brain in continual learning and adaptation to new situations. The proposed mechanism is inspired by a theoretical machine-learning framework for artificial neural networks and will be investigated by combining cutting-edge experimental techniques to unveil the brain's learning mechanism. Show the project objective Hide the project objective Objective In a changing environment the ability to continually and rapidly learn new behaviors is crucial for humans and animals to survive. How the brain stores and integrates new information without forgetting (continual learning, CL) and utilizes prior knowledge to quickly adapt to new situations (fast forward generalization, FFG) remains a mystery. To shed light on this crucial question I propose a novel interdisciplinary approach that derives inspiration from a theoretical machine-learning approach for artificial neural networks (ANN) and simultaneously addresses FFG and CL. In this dual-network model, a so-called meta-network learns to identify the context for all previous tasks and modulates a second, stimulus-processing network, in a task/context specific manner to efficiently solve the task. As a result, similar task contexts elicit the selection of similar stimulus processing networks thereby enabling FFG. In the brain, the medial prefrontal cortex (mPFC) is known to receive contextual information (environment, setting), to store task information and to project to sensory areas. This makes it a promising candidate to function as a meta-network in the brain. In the proposed study, I will investigate if and how the mPFC affects sensory processing in a task-specific manner during CL and FFG, functioning as a meta-network. I will utilize cutting-edge experimental techniques including miniaturized microscopes in freely behaving mice to record neuronal populations in mPFC during FFG and CL combined with chemo- and optogenetic tools. To investigate how mPFC affects stimulus processing on the single neuron level, I will combine calcium and voltage imaging in brain slices. This interdisciplinary project will provide novel insights into the possible implementation of meta-learning in the brain to address CL and FFG. Completion of this innovative project in the multidisciplinary environment of my host lab will provide me with the ideal setting to reach scientific independence. Fields of science natural sciencesbiological sciencesneurobiologycognitive neurosciencenatural sciencescomputer and information sciencesartificial intelligencecomputational intelligence Keywords cortical circuits medial prefrontal cortex visual cortex meta-learning gain modulation plasticity continual learning visual discrimination Programme(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 Topic(s) MSCA-IF-2020 - Individual Fellowships Call for proposal H2020-MSCA-IF-2020 See other projects for this call Funding Scheme MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF) Coordinator EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH Net EU contribution € 191 149,44 Address Raemistrasse 101 8092 Zuerich Switzerland See on map Region Schweiz/Suisse/Svizzera Zürich Zürich Activity type Higher or Secondary Education Establishments Links Contact the organisation Opens in new window Website Opens in new window Participation in EU R&I programmes Opens in new window HORIZON collaboration network Opens in new window Total cost € 191 149,44
