📋 Tender Overview
LOOP-TMS
Grant agreement ID: 101248128
DOI
10.3030/101248128
EC signature date
31 October 2025
Start date
1 November 2025
End date
30 April 2027
Objective
We aim to develop and validate adaptive closed-loop brain stimulation using advanced real-time electroencephalography-transcranial magnetic stimulation (EEG–TMS) technology guided by probabilistic deep artificial neural networks.
TMS is performed routinely worldwide in tens of thousands of healthcare institutions for treating a wide variety of brain disorders. However, current TMS protocols are limited by small therapeutic effect sizes and large portions of non-responders. A significant problem is that one size does not fit all: existing TMS protocols are non-personalized, operate without information of instantaneous brain states, function in an open-loop manner, and lack adaptability.
To address this, we have developed brain state-dependent stimulation in the ongoing ERC Synergy project ConnectToBrain. Real-time EEG–TMS has enabled reliable prediction of high- vs. low-excitability brain states and coupling of TMS to a prespecified state. While this is major progress, brain state-dependent stimulation is still open-loop and non-adaptive.
The key innovation in our current proposal is implementing truly adaptive closed-loop algorithms that continuously monitor TMS effects and optimize stimulation parameters in real-time to maximize beneficial long-term changes in targeted brain networks. Recent advances in machine learning now make this sophisticated approach possible.
This project represents a significant leap beyond ConnectToBrain by creating a user-independent, fully automated, adaptive closed-loop real-time EEG-TMS system ready for further testing in clinical trials. Our technology has breakthrough potential as a paradigm-shifting innovation in non-invasive therapeutic brain stimulation, addressing an urgent societal and medical need for more effective, individualized treatment of brain disorders
