Digital Theses Archive


Tesi etd-01072021-160504

Type of thesis
Updating deep brain stimulation: novel quantitative methods to determine sweet spots and patients state through electrophysiological activity
Scientific disciplinary sector
Istituto di Biorobotica - BIOROBOTICS
relatore Dott. MAZZONI, ALBERTO
  • Basal Ganglia
  • Deep Brain Stimulation
  • Electrophysiology
  • Sweet Spots
Exam session start date
Deep Brain Stimulation (DBS) is a highly effective treatment to ameliorate pharmacologically intractable cardinal symptoms in movement disorders such as Parkinson’s Disease (PD), Tourette Syndrome (TS) and Dystonia. Promising results with DBS intervention are emerging for an expanding palette of brain diseases such as Impulse Control Disorder (ICD), obsessive compulsive disorder, depression. The objective of work is tackling the current scientific DBS challenges hovering around the localization of neural targets that mediate optimal clinical outcomes for patients without emerging noxious DBS-induced side-effects – the so-called sweet spots – and the computation of patient-state related biomarkers that could be potentially used to inform the pattern of the stimulation. Herein, I focused on developing quantitative tools to elucidate how different basal ganglia nuclei are functionally organized and to characterize the relationship between the neural activity with either the stimulation in situ or the state (e.g., clinical severity, motor behaviour) of the patient. These methods have been applied to a variegate repertoire of neural signals acquired either with explorative microelectrodes (intraoperatively) or DBS electrodes (postoperatively) from different DBS target nuclei in the basal ganglia (e.g., Subthalamic Nucleus and Globus Pallidus internus) in multiple cohorts of patients (e.g., PD, TS, and ICD). The results of this PhD thesis revealed the wealth of information contained in the neural activity of the basal ganglia. For instance, I found that discharge patterns of the STN neurons identify optimal sweet spots for stimulation in TS patients and that the temporal pattern of the STN oscillations in the beta range can characterize the encoding of dysfunctional motor behaviour in PD patients. This work also involved the use of computational models to grasp new insights into the pathological neuron activity associated with PD and the realization of an open-source platform where DBS imaging users can query the label of a specific region of the brain from different atlases. These results can remarkably contribute to the DBS field providing the necessary neuroscientific knowledge i) to build new algorithms to facilitate clinicians during the assessment of the optimal DBS electrode location, ii) to describe the relationship between neural oscillations and specific symptoms and/or compensatory activity and iii) to identify symptom-specific and task-related biomarkers to use as feedback signals for adaptive DBS paradigms.