Clinical Research Directory

TMS for iEEG Monitoring Recordings

The current study presents a unique opportunity to measure the direct effects of transcranial magnetic stimulation (TMS) by using intracranial electrodes to record neural activity in deep brain regions when TMS single pulses are delivered. If TMS can evoke downstream responses in neural networks of the human brain, it can be a feasible way to study circuit engagement and connectivity.

Dynamic Causal Modeling of Neuromodulation of Action Speed Via Targeted TMS-EEG

Stroke is a major cause of long-term disability, with cognitive and motor deficits-especially action slowing and executive dysfunction-being strong predictors of poor recovery outcomes. Recent advances in network neuroscience suggest that action speed is governed by interactions between specific prefrontal and premotor regions. However, the precise neural mechanisms underlying action slowing in stroke remain unclear, limiting the efficacy of current rehabilitation approaches. This study integrates high-density EEG, fNIRS and dynamic causal modeling (DCM), and rTMS to map and modulate the neural circuits involved in action speed. In the first phase, we will assess the role of seven key brain regions in action speed modulation by applying virtual lesions using single-pulse TMS in 60 healthy individuals. In the second phase, we will apply offline intermittent theta burst stimulation (iTBS) to the most relevant regions and evaluate its impact on action speed. Finally, in the clinical phase, we will administer individualized iTBS to 20 stroke patients to enhance action speed. Patients will be assessed at baseline, immediately post-treatment, and after one and three months to track improvements in action speed using DCM and behavioral tests. Changes in connectivity and action speed performance will be compared to healthy controls to refine treatment parameters. Secondary outcomes include executive function and daily life motor performance. Longitudinal follow-up will determine the persistence of improvements, informing future personalized rehabilitation strategies. By characterizing effective connectivity changes post-stroke, we aim to refine neuromodulation strategies and develop a personalized rTMS approach. Our hypothesis is that targeting specific regions identified through integration of EEG, fNIRS and DCM can enhance action speed, ultimately improving functional recovery. This personalized approach could lead to more effective rehabilitation protocols, tailored to individual brain damage patterns.