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.
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.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesneurobiology
- engineering and technologyelectrical engineering, electronic engineering, information engineeringinformation engineeringtelecommunicationstelecommunications networksoptical networks
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- medical and health sciencesbasic medicinephysiology
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Keywords
Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
10623 Berlin
Germany