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Enabling Unobtrusive Real-World Monitoring of Brain-Networks with Wearable Neurotechnology and Multimodal Machine Learning

Project description

Wearable tech for real-world brain imaging

Understanding how brain networks function in real-world situations could revolutionise treatments for brain disorders. However, current tools like functional MRI are limited to controlled lab environments, and mobile EEG lacks the ability to fully capture brain networks. The ERC-funded INTEGRAL project aims to solve this by developing a wearable platform that combines high-density diffuse optical tomography, EEG and physiological sensors. This hybrid system will enable continuous, unobtrusive brain imaging in everyday settings. By advancing both hardware and machine learning analysis, INTEGRAL promises to offer new insights into brain function, transforming neurotechnology research and applications in fields like digital health and neuroscience.

Objective

Measuring and linking brain network activity to human physiology and behavior in natural everyday situations promises profound new insights into healthy brain function and disorders. However, the absence of suitable mobile neurotechnology presents a significant roadblock. Functional magnetic resonance imaging (fMRI) has greatly advanced our understanding of brain function and networks, but it is limited to single-snapshot experiments in constrained lab settings. Electroencephalography (EEG), while mobile, cannot directly be linked to brain networks captured by fMRI. To overcome these roadblocks and to advance neuro-inspired treatments and discoveries to natural environments, a hybrid wearable platform is required that combines innovations in hardware and analysis methods to enable continuous and stable measurements of brain network activity maps in the everyday world. Advancing high-density diffuse optical tomography (HD-DOT) can provide such a suitable alternative to fMRI. With a unique systems engineering concept, INTEGRAL aims to miniaturize and integrate DOT, EEG, and physiological sensors with advanced multimodal machine learning to improve spatio-temporal contrast in mobile brain-imaging. To this end, Objective 1 (Instruments) will develop hardware for unobtrusive and continuous wearable brain-body imaging with HD-DOT-EEG. Objective 2 (Experiments) will collect extensive multimodal data for measuring brain networks while controlling for environmental and physiological artifacts. Objective 3 (Analysis) will enable estimation of brain network activity with multimodal sensor fusion and machine learning and Objective 4 (Integration) will provide validation of robust brain-networks imaging in ecologically valid everyday world environments. If successful, this new platform will provide unprecedented opportunities to study brain function with global impact on neurotechnology applications and research from Neuroscience of the Everyday World to digital health.

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Topic(s)

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Funding Scheme

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2024-STG

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Host institution

TECHNISCHE UNIVERSITAT BERLIN
Net EU contribution

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.

€ 1 654 850,00
Address
STRASSE DES 17 JUNI 135
10623 Berlin
Germany

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Region
Berlin Berlin Berlin
Activity type
Higher or Secondary Education Establishments
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Total cost

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.

€ 1 654 850,00

Beneficiaries (1)

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