| To improve the quality of life for patients with neurodegenerative diseases, this thesis describes electrophysiological techniques that can be used to characterize and modulate the neural circuits behind glaucoma and Parkinson's disease (PD). These studies contribute fundamental knowledge that facilitates the development of neural interfaces (e.g. retinal prosthetics and deep brain stimulation (DBS)) that replace the functions of damaged neural structures. In designing neural interfaces, one must first understand how neural computations are performed in the healthy and diseased nervous system. To better understand visual response in the retina, we devised an area-threshold technique for multielectrode recordings that identifies the classical center-surround receptive field (RF) organization of retinal ganglion cells (RGCs). This technique revealed, for the first time in mice, the size and gain of the RF surround, which eludes standard reverse-correlation analysis. Remarkably, surround modulation was significant enough in 42% of RGCs to alter their response sign (e.g. ON or OFF) for different stimulus sizes. We next assessed physiological changes in RGCs in a mouse model of human high-tension glaucoma. Using Gaussian white noise analysis, RGCs were found to degenerate in a subtype and location dependent manner. Namely, our results suggested that bistratified RGCs were less susceptible to elevated intraocular pressure than monolaminated RGCs and that RGCs along the vertical axis of the retina appear to be more vulnerable than those along the horizontal axis. These findings corroborate the hypothesis that certain RGC subtypes die early in glaucoma, opening new possibilities for its early detection and treatment. Finally, we explored DBS as a therapy for PD in an in vivo sheep model. DBS of the basal ganglia, whose dysfunction underlies PD, produced dose and location dependent motor responses in a manner consistent with the DBS side effects observed in humans. Notably, DBS with beta frequencies (i.e. 8-30Hz) led to tremor like movements typically associated with PD. Thus, an ovine DBS model is an invaluable system with which to develop new DBS features and investigate the mechanisms underlying PD and DBS. It is hoped that these techniques will contribute to the successful implementation of neural interfaces for treating neurodegenerative diseases. |
