One of the earliest symptoms of Parkinson's Disease (PD) is the loss of olfaction. This may be due to the damage PD causes in the olfactory bulb (OB), as evidenced by findings that in many PD patients, the OB contains large amounts of the alpha-synuclein protein, even in early stages of the disease. The olfactory bulb receives and processes olfactory input before relaying activity to higher areas of the brain. This olfactory information appears to be encoded in part by patterns of high frequency oscillations in neural firing rates in the OB. An early computational model by Z. Li and J. Hopfield simulated these high frequency oscillations. The model consisted of two groups of neurons, mitral cells (excitatory) and granule cells (inhibitory). These formed a collection of coupled nonlinear oscillators arranged on a one dimensional ring. In the present work, this model was extended to larger sizes and a two dimensional network structure. The model network was subjected to synaptic damage representative of PD pathology, and the ensuing responses to simulated odor input were characterized and compared to the baseline response. Results show increased localization of model network activity in response to odors, as well as disruption to network oscillations. The severity of the effects depends on the size and structure of the network. Future work aims to implement recent models that incorporate other OB features likely affected by PD, such as dopaminergic input. By computationally investigating the OB under conditions caused by PD, this work attempts to better understand OB function and the mechanisms by which PD impairs the OB and other regions of the brain.