Project 3

Classification of increasing parkinsonian severity in GP

Neuroanatomical studies have shown globus pallidus internus (GPi) projection neurons strongly innervate the mesencephalic locomotor region (MLR), centromedian / parafascicular complex (CM/Pf), and lateral habenula (LHb). Abnormal activity patterns within these pallidofugal output nuclei have been hypothesized to contribute to several cognitive-motor signs of Parkinson’s disease (PD), including levodopa-resistant gait dysfunction, behavioral set shifting difficulties, and deficits in goal-oriented motivation, respectively. However, little is known about the actual pathophysiological changes that occur in these nuclei with the emergence of Parkinson’s disease. 

Deep brain stimulation (DBS) targeting regions in and around the GPi and subthalamic nucleus (STN) can be highly effective for treating motor signs of PD, but how such targeting affects MLR, CM/Pf, and LHb nuclei and how those effects relate to improvement or worsening of cognitive-motor signs of PD is not well understood. Project 3 will investigate the contribution of (1) the GPi ↔ MLR network to parkinsonian gait dysfunction, (2) the GPi → CM/Pf network to difficulties with behavioral set shifting, and (3) the GPi → LHb network to deficits in goal-oriented motivation. This project will leverage our capacity to perform wireless spike and LFP recordings from chronic microdrives during untethered movement and during cognitive-motor tasks relevant to PD. The project will also develop a novel response surface optimization algorithm that uses real-time feature assessments of spike and LFP responses in the MLR, CM/Pf, and LHb to drive DBS targeting of the STN/lenticular fasciculus or GPe/GPi. The settings within the multi-dimensional DBS parameter space that generate the most robust changes in spike rate, spike pattern, spectral power, and/or information encoding within the MLR, CM/Pf, and LHb will be tested in cognitive-motor behavioral tasks that introduce obstacles and vary levels of effort and reward. This study will be critically important for not only better understanding the neural circuitry underlying cognitive-motor symptoms of PD but also to refine DBS methodologies to provide more consistent clinical outcomes with DBS therapies for PD.

Project PI

Matthew Johnson small photo

Matthew Johnson, PhD
Associate Professor, Biomedical Engineering

Project Co-PI

Tay Netoff small photo

Tay Netoff, PhD
Associate Professor, Biomedical Engineering