Cortical Network Modulation by Subthalamic Nucleus DBS

Deep brain stimulation of the subthalamic nucleus (STN DBS) in Parkinson's disease (PD) can provide substantial motor benefit yet can also produce unwanted mood and cognitive side effects. Although the neural mechanisms underlying benefits and side effects are not well understood, current hypotheses center on the potentially measurable yet currently undefined effects within downstream cortical networks. Limitations of current tools have impeded attempts to assess network connectivity directly and dynamically in humans with implanted DBS; PET lacks the necessary temporal resolution while fMRI is neither optimal nor safe for patients with implanted DBS. In this proposal, to overcome these significant limitations, the investigators apply high-density diffuse optical tomography (HD-DOT) methods to investigate how STN DBS modulates cortical functional networks and behavior in PD patients. HD-DOT uses a collection of functional near-infrared spectroscopy (fNIRS) measurements, free of radiation exposure concerns, and without electrical/metal artifacts or contraindications or safety concerns for DBS. However, common fNIRS systems are critically hampered by typically sparse measurement distributions that lead to poor anatomical specificity, unreliable image quality due to crosstalk with scalp signals, poor spatial resolution, limited field of view, unstable point spread functions, and uneven spatial coverage. HD-DOT solves these problems by using high-density interlaced source and detector imaging arrays that support densely overlapping measurements and anatomical head models that together result in higher spatial resolution, stable point spread functions, and greatly improved isolation of brain signals from scalp signals. The investigators have demonstrated that HD-DOT accurately maps functional connectivity (FC) within and between cortical resting state networks (RSNs) in the outer \~1cm of cortex with comparable temporal and spatial resolution to fMRI. Preliminary data in