Project description
Towards enhancing the quality of life of neurological patients
Intracortical brain-computer interfaces (BCIs) are helping to change the lives of many people suffering from movement disorders. BCIs analyse brain signals and translate them into commands that are relayed to devices that carry out an intended action such as controlling a computer cursor. Current state-of-the-art BCIs, however, are much slower and less precise than natural movements. The EU-funded IntuitiveBCI project aims to improve current BCIs by leveraging the brain’s own distributed resources to control automatic movements in a skilled and intuitive manner – one that requires little mental effort. The work of the project will enable future translational work that can lead to more skilled and intuitive control than what current approaches offer.
Objective
More than 25% of people over the age of 50 suffer a movement disorder; many of them have a functional disability as a result.
Intracortical Brain-Computer Interfaces (BCIs) that extract or “decode” the user’s intent based on recordings from tens or hundreds of cortical neurons have enabled paralyzed patients to control computer cursors, robots, or even their own limbs just by modulating their neural activity. Despite these successes, BCI control still falls short compared to natural limb control: it is far less skilled, and it requires significantly more mental effort.
My goal is to overcome these two limitations through a novel “Intuitive BCI” that leads to enhanced control compared to current approaches. Rather than follow the dominant trends of developing new decoder algorithms and interface technologies, I will adopt a unique, previously unexplored approach: to leverage the brain’s own distributed resources to control automatic movements in a skilled and intuitive manner requiring little mental effort.
Automatic movements depend critically on subcortical brain structures whose activity is not probed by current cortical BCIs. To develop my novel approach to BCI based on the neural control of automatic movements, I will combine: 1) recent breakthroughs to record from thousands of neurons across the mouse brain; 2) a novel theory to model neural population activity that I have helped establish; and 3) new experimental tasks to isolate the cortico-subcortical information underlying automatic movements. This information will provide inputs to the proposed Intuitive BCI. I seek to prove that it leads to more skilled and intuitive control than current approaches, even allowing users to multi-task –an unprecedented feat in the field.
This timely, multidisciplinary research will push BCI control forward, beyond current state-of-the-art approaches limited to cortical control. It will also help realize BCI’s promise to improve the quality of life of neurological patients
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.
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H2020-EU.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
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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
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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.
ERC-STG - Starting Grant
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2020-STG
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SW7 2AZ London
United Kingdom
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