Dystonia is a movement disorder characterized by abnormal postures and repetitive movements, often treated with Deep Brain Stimulation (DBS) in cases resistant to other therapies. Intraoperative MicroElectrode Recordings (MER) are typically used to guide electrode placement during DBS surgery, but this process remains largely subjective. This study explores an automated method to analyze MER data and identify optimal implantation sites, aiming to improve surgical outcomes. MER recordings were collected from five pediatric patients undergoing DBS targeting the Globus Pallidus internus (GPi), with data obtained on three trajectories -anterior, central, and posterior- at multiple depths. Preprocessing involved filtering high-energy interferences and applying an automated spike-sorting pipeline to extract features such as firing rate, firing regularity, and oscillatory activity.