A study of structural and functional connectivity in patients with treatment-resistant schizophrenia undergoing Deep Brain Stimulation surgery

Schizophrenia is a psychiatric illness that can present with positive symptoms (auditory hallucinations, disorganized thinking), negative symptoms (depression, apathy), and general symptoms (anxiety). Its prevalence in the population is low (1-2%); however, affected individuals experience a severe impact on their quality of life. Up to 30% of these patients do not improve with conventional medication, and currently, there are no effective therapies for these cases.

Our center has established a refractory unit for this illness and has already conducted two clinical trials on the safety and effectiveness of Deep Brain Stimulation (DBS) in patients with treatment-resistant schizophrenia (TRS). There is a global lack of data on the cerebral effects of this therapy for this illness, and especially its impact on functional magnetic resonance imaging data.

The student will join our center's refractory psychiatric 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, psychiatrists, psychologists, neurosurgeons, bioengineers), with the possibility of assisting in the implantation surgeries. The computational work will require processing real brain images using specialized software.

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 treatment-resistant schizophrenia, specifically to understand the functional changes produced after the application of Deep Brain Stimulation. Structural connectivity data will also be analyzed.

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]), Sandra Roldán

 

 

 

 

Hosting group: Brain Neuromodulation Computational Lab.

Supervisors: Juan Aibar ([email protected]), Sandra Roldán