SOURCE-LINKED INTELLIGENCE

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

CORDIS · observation · Publication date unknown

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

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recordType

award

status

SIGNED

region

EU

value

1654850

unit

EUR