Jose Enrique “Iking” Lopez is an Erasmus Mundus Master's student in Brain and Data Science conducting his thesis in collaboration with the Digital Surgery and Neuropsychiatry Labs at the Champalimaud Foundation. With a background in computer science and computer vision for robotics, he is applying those skills to make brain stimulation therapy more precise and personalized.

Brain stimulation treatments like TMS (transcranial magnetic stimulation) show promise for conditions like depression and OCD. During a TMS session, a coil placed on the scalp induces electric fields in the brain to modulate neural activity in regions like the left dorsolateral prefrontal cortex (DLPFC), which is thought to be underactive in patients with depression. However, clinicians currently lack real-time guidance for optimal coil placement. Iking is using AI to address this challenge by building on deep learning models that predict electric field distributions to enable real-time, electric-field-guided coil placement during treatment. This real-time guidance is envisioned to help clinicians position the coil more precisely, enhancing targeting accuracy and patient outcomes.