Two PhD positions to study “Computational models for the treatment of epilepsy with deep brain stimulation”

Deep brain stimulation (DBS) is a neurosurgical procedure that involves the implantation of electrodes into specific targets within the brain and the delivery of electric current from an implanted battery. Over 160,000 patients worldwide have undergone DBS for various conditions, from Parkinson’s disease to epilepsy. Whereas the majority of Parkinson’s disease patients benefit from DBS, in epilepsy its efficacy is very variable, resulting in disappointment and distress to non-responders and clinicians.

The aim is to improve the fundamental understanding and the efficacy of DBS, focusing on its application in treating epilepsy. The overall strategy is to develop a novel approach that integrates personalized computational models with a unique combination of clinical data. Patients with refractory epilepsy who are not eligible for resective surgery are implanted with DBS and we will record scalp electroencephalogram (EEG) and local field potentials (LFPs) in the thalamus to bridge these different levels.

We are looking for two highly motivated PhD candidates to strengthen our research. In Project 1, leveraging EEG data during DBS stimulation, you will develop personalized biophysical models based on patient-specific anatomical characteristics, bioelectrical signatures such as tissue conductivity, and clinical outcomes. The application of state-of-the-art finite element methods (FEMs) and source reconstruction methods will lead to new strategies for DBS treatment optimization. With simultaneous EEG and LFP recordings, in Project 2, you will build and validate a multiscale approach that combines a mesoscopic model of the thalamocortical projections involved during DBS stimulation and a macroscopic volume conduction model based on EEG recordings.

Keywords Project 1: FEM modeling, source reconstruction, signal analysis

Keywords Project 2: computational models (micro/meso/macro), validation, tractography

MISSION STATEMENT AND RESEARCH LINES CLINICAL NEUROPHYSIOLOGY GROUP (CNPH)

Research in the Clinical Neurophysiology group is at the interface of neuroscience, neurophysiology and clinical neurology, focusing on cerebral ischemia and epilepsy. In addition to improve understanding of pathophysiology, we aim to develop novel diagnostic tools and treatments. Our research is truly translational: from the UT to the clinic and back.

The EEG is a key clinical and research tool. EEG signal analysis includes various machine learning techniques to improve diagnostic values and (bedside) application. Applied EEG studies are complemented by biophysical modeling and simulation for improved understanding of underlying neuronal dynamics and prediction of treatment effects. In addition, we use in vitro models consisting of cultured neurons (from rodent or human induced pluripotent stem cells) on multi-electrode arrays to study basic neuronal and synaptic functioning, identify treatment targets, and screen treatments.

RESEARCH LINES

1. Cerebral ischemia after ischemic stroke or cardiac arrest

• Pathophysiological understanding: biophysical modeling, in vitro modeling (electrophysiology and immunocytochemistry), bio-banking of post mortem patient brains. Focus: dynamics of cell swelling and synaptic failure.
• Diagnosis: advanced EEG analysis (including machine learning) and prediction models
• Treatment: multicenter, randomized, controlled clinical trials

1. Epilepsy

• Pathophysiological understanding: biophysical and in vitro modeling, EEG and fMRI in ECT induced epileptic seizures as a human epilepsy model.
• Diagnosis: cortical excitability testing with TMS/EEG/EMG for improved diagnosis and monitoring of therapeutic efficacy.
• Treatment: proof of principle clinical trials