Project description
Dynamics and processes behind learning in complex environments
Recent advancements in technology and neuroscience have enabled us to monitor a larger number of neurons across different brain regions during complex behaviours. However, existing theoretical and quantitative tools still fall short in explaining the neural mechanisms underlying flexible, goal-directed behaviours, such as adapting to changing environments. The ERC-funded DULCE project aims to address this gap by developing a unified framework for understanding learning in complex environments. The project will focus on identifying population-level behavioural and synaptic learning rules that govern learning in dynamic contexts. It will also leverage statistical modelling, machine learning, and dynamical systems theory to create the models and theories needed to gain a deeper, more comprehensive understanding of these processes.
Objective
Learning and adaptation play a central role in interacting with a changing environment, yet the neural substrate
underlying such flexible, goal-directed behaviors has remained elusive. Neuroscience experiments have traditionally focused on how individual brain regions perform abstract, highly simplified tasks. However, recent technological advances, coupled with powerful AI-accelerated software, have rapidly enabled the monitoring of large populations of neurons over many days, across multiple brain regions, and during increasingly complex, naturalistic behaviors. Yet even with such data within our reach, we still lack the theoretical and quantitative tools that are necessary to understand the fundamental principles guiding learning in neural populations. DULCE aims to fill this gap by establishing a unified framework to understand learning in complex environments. The core hypothesis of DULCE is that in naturalistic conditions, learning engages multiple co-occurring learning processes that are distributed across the brain, and which work together to reshape neural dynamics to perform new tasks. As such, DULCE aims to uncover the behavioral, population- level, and synaptic learning rules responsible for guiding learning in complex environments. By interweaving statistical modelling, dynamical systems theory and machine learning, DULCE will: i) Develop hierarchical models of behavior that can disentangle the rules governing simultaneously occurring learning processes. ii) Provide a unified theory of how region-specific learning rules in the cortex, cerebellum, and striatum coordinate to form a distributed learning system. iii) Develop interpretable dimensionality reduction methods to identify the rules governing how task-relevant dynamics evolve in large-scale neural data over learning. Through this three-pronged attack, DULCE aims to lay the foundation necessary to uncover the neural mechanisms controlling the Dynamics Underlying Learning in Complex Environments.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences neurobiology
- natural sciences computer and information sciences software
You need to log in or register to use this function
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2024-COG
See all projects funded under this callHost institution
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
75230 Paris
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.