Periodic Reporting for period 1 - ConnectToBrain (Connecting to the Networks of the Human Brain)
Reporting period: 2019-09-01 to 2021-02-28
1) Multilocus TMS (mTMS) coil array, power and control electronics, and user interface, the array covering most of the cortical mantle and allowing real-time high-precision control over the locus, direction, intensity, and timing of the stimulation pulses.
2) Real-time analysis of brain activity and connectivity by using functional information from high-density electroencephalography (EEG) and anatomical information from magnetic resonance imaging for brain-state-dependent and closed-loop stimulation.
3) Demonstration of feasibility, safety, and efficacy of the developed techniques and methods, and their therapeutic utility in dysfunctional brain networks in brain disorders such as Alzheimer’s disease and motor stroke.
An illustration of the future system is presented in Fig. 1. By the end of the project, we expect to have developed new technology capable of correcting dysfunctional brain networks in several brain disorders with better therapeutic efficacy than current state-of-the-art techniques and the potential to induce a major paradigm shift in therapeutic neuromodulation. If successful and widely transferred for clinical use, ConnectToBrain will eventually lead to a substantial reduction in the suffering and economic burden caused by several brain disorders.
At AALTO, we have experimented with the existing 2-coil TMS device to help develop closed-loop algorithms for ConnectToBrain multi-coil systems. The planned 5-coil prototype at Aalto has been built but not yet fully tested. The prototype for Tübingen, with novel features, including compatibility for hospital use, will be ready in June 2021, delayed by about 9 months due to corona and the somewhat unexpected complications related to regulatory requirements. We have worked also on the 12-channel design and on solutions for TMS-compatible EEG and algorithms and cap design for reducing TMS-related artifacts in EEG.
We organized the BrainSTIM 2020 conference, with a strong emphasis on TMS. The meeting was very successful. We have participated in several other international meetings.
At EKUT, we have completed the first two steps of Task 7 in our proposal (brain-state-dependent stimulation in simple 2-node networks in healthy subjects). We confirmed our hypothesis that effective connectivity between the primary motor cortices of the two hemispheres as tested by dual-coil interhemispheric short-interval inhibition is most strongly expressed if the two TMS pulses are applied when the sensorimotor µ-rhythm in the two hemispheres is synchronized. In addition, we have completed several studies that elaborate on principles of signal-to-noise ratio for real-time estimation of the phase in EEG-recorded oscillations, and on causal decoding of EEG data for estimation of cortical excitability at the individual level. The results of these studies are pivotal for further usage and software development in our brain-state-dependent stimulation approaches.
At UdA, we have worked towards establishing algorithms to assess whole brain connectivity in real time from EEG data. To this aim, the real-time performance of algorithms widely used for off-line analysis of functional connectivity have been assessed, using simulated data as a first approach. We have demonstrated that to achieve a reliable connectivity estimate in real-time, a data analysis window of about 5 cycles (i.e. 500 ms at 10 Hz) is sufficient for the majority of the tested connectivity metrics for sustained brain connectivity. For dynamic connectivity, we found that the length of the data analysis window must be shorter than the coupling duration. The results of these studies will allow to include connectivity algorithms with optimized parameter settings in brain-state-dependent stimulation at multiple sites by mTMS.
1) We have constructed a multi-locus TMS device, with 5 overlapping coils: one round, two figure-of-eight, two cloverleaf-shaped. When these coils are activated simultaneously, a focal electric field in the brain can be produced. By adjusting the relative intensities of the 5 coil currents, the focal point of stimulation in the cortex can be electronically defined; these stimulation points can be changed in less than a millisecond, allowing spatially distributed sequences of TMS pulses that were not possible before. This work has involved the design of the coils, power electronics, control electronics, navigation, patient support systems, software architecture and user interface design, all of which include novel features that will allow safe and efficient use of the technology.
2) We have developed algorithms for analyzing electromyography (EMG) and electroencephalography (EEG) data for brain-state-dependent closed-loop brain stimulation. We have developed algorithms to predict the phase of EEG-recorded oscillations at sensor and source levels in real time, in order to deliver TMS pulses at desired phases of the oscillatory activity. We have also developed algorithms that clean noise and artifacts from the EEG signal, in particular eye-movement and TMS-evoked muscle artifacts. Furthermore, we have developed algorithms for determining time-dependent changes of functional connectivity in the brain based on EEG; this will allow one to perform closed-loop stimulation based on connectivity information.
3) We have demonstrated with existing one-coil technology that TMS efficacy for induction of long-term plasticity in motor cortex can be enhanced by triggering the pulses at the right phase of alpha-frequency EEG signals. We have demonstrated with the existing two-coil device that one can find motor representation areas without moving the transducer and with a much smaller number of pulses than with traditional methods.
By the end of the project, we expect to have developed new technology capable of correcting dysfunctional brain networks in several brain disorders with better therapeutic efficacy than current state-of-the-art techniques and the potential to induce a major paradigm shift in therapeutic neuromodulation. If successful and widely transferred for clinical use, ConnectToBrain will eventually lead to a substantial reduction in the suffering and economic burden caused by brain disorders.