Study of local field potentials in the subthalamic nucleus of patients with advanced Parkinson's disease implanted with Deep Brain Stimulation electrodes

Advanced Parkinson's disease represents the final stage of this degenerative illness, where pharmacological measures are no longer able to control the disease's symptoms. Deep Brain Stimulation emerges as a therapeutic alternative at this stage to control both motor symptoms (rigidity, bradykinesia, and tremor) and non-motor symptoms (apathy, depression). The brain electrodes currently implanted have the capacity to record brain signals, and this biomarker is used to modulate the electrical response these devices provide to the brain.

The student will join our center's movement disorders group, where they will have the opportunity to interact with patients who have been implanted with these devices. They will also collaborate with a wide range of professionals (neurologists, psychologists, neurosurgeons, bioengineers), with the possibility of assisting in implantation surgeries. The computational work will require processing real brain images with specific software and processing the brain signals extracted from these devices using the group's own algorithms.

The student will have their own dedicated space in our research area, complete with a workstation and access to clinical image and signal data.

Important Warning

The clinical data used in this work is highly sensitive and protected by intellectual property. Consequently, it cannot be exported from the designated workstations. Any manipulation of this data outside the initial study protocol must be reported to the project supervisor and will be discussed on an individual basis.

Project Objective

To advance the knowledge of brain signals in advanced Parkinson's disease. Specifically, the project aims to understand the distribution of different oscillations (beta, gamma, and high-frequency oscillations) within the subthalamic nucleus and the implications this has for the therapy's automatic response.

Necessary Computational Skills

For data analysis and the clinical reasoning behind it, the student will have close supervision and contact with our group's clinical-technical team.

  • Programming Languages: Python, MATLAB (basic-intermediate)

  • Data Analysis: Proficiency in statistical packages (Stata), image processing with Lead-DBS and SPM software, supervised machine learning (classification), signal processing with the group’s own algorithms.

  • Simulation Tools: Simulink

  • Database Management: Excel, Stata

  • Other Specific Skills: Development and/or refinement of machine learning algorithms

 

Hosting group: Brain Neuromodulation Computational Lab.

Supervisors: Juan Aibar ([email protected])