Abstract:
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a well-established
symptomatic treatment for Parkinson’s diseases (PD). However, knowledge on local
electrophysiological biomarkers within the STN and their cortical connectivity profile is still
scarce. Such information would be necessary for optimal positioning of the DBS leads based
on PD network pathophysiology.
This thesis describes the introduction and exploration of a novel technique for
electrophysiological measurements during DBS surgery. Combined electroencephalography
(EEG) with stepwise local field potentials recordings during insertion of the DBS lead was
performed intraoperatively, thereby, allowing to capture local STN and cortico-subthalamic
physiology with high speactral and spatial specificity. Our results revealed that strong beta
oscillatory activity in the STN was located more dorsally than the STN-ipsilateral motor
network phase coupling; the respective frequency bands were in the low and high beta-band,
respectively. Moreover, the spot within the STN, where this STN-cortical phase coupling
occurred, correlated highly with the STN spot where the phase of beta oscillations modulated
the amplitude of high-frequency oscillations. This STN location was furthermore,
characterized by information flowed from the ipsilateral motor cortex to the STN in the high
beta-band suggesting a pathologically synchronized network with a direct STN-motor cortex
connection via the hyperdirect pathway. Interestingly, the very same STN spot showed a
resonance like responses to electrical stimulation suggesting a decoupling of pathologically
synchronized STN-motor cortex connectivity during therapeutic DBS.
In conclusion, this PhD thesis provides first evidence that macroelectrode recordings with
the chronic electrode concurrent with EEG recordings are a reliable method for STN
localization during DBS surgery. Additionally, combining LFP and EEG recordings during
mapping of STN offered a new way of DBS targeting on the basis of pathological local
biomarkers and network activity.