Parkinson's disease (PD), the paradigmatic Lewy body disease, is the second most frequent age-related degenerative disorder and has no cure. In PD, cognitive impairments are pervasive, heterogeneous, poorly treated, and often lead to dementia, hallucinations, and risk of falls which substantially worsen the quality of life, increase the risk of nursing home placement, and have significant economic consequences. Two distinct types of cognitive deficits have been recognized in PD. The first type is fronto-striatal/executive deficits and the second type is posterior cortical-hippocampal/visuospatial and memory deficits. Longitudinal studies have shown that although executive deficits are more common, memory and visuospatial deficits are more likely to progress to dementia and patients with these deficits have a higher risk of hallucinations and falls. Therefore, there is a need to diagnose cognitive deficits rooted in memory and visual integration in PD at the very earliest stages in the PD pathogenesis when patients have age-appropriate cognitive performance (i.e., PD with normal cognition) to prevent future cognitive impairment leading to dementia.

This proposal aims to understand the underlying neurocircuitry that contributes to the integration deficit of visual information with memory in PD. The proposal objectives are achieved with a creative behavioral paradigm (memory-based perceptual decision-making task), functional and structural brain imaging, and a computational framework to link the memory-based perceptual decision-making behavioral deficits to brain circuitry dysfunction and structural changes.

The medial temporal lobe (MTL) is involved in memory formation and high-level visual processing and basal ganglia (BG) is involved in decision-making. Our hypothesis is that memory-based perceptual decision-making deficits in PD result from the dysfunction of the MTL-BG neurocircuitry. The premise of this hypothesis is based on rigorous studies performed on animal models, healthy individuals, and our preliminary data on PD patients. First (Aim 1), we will combine behavior with computational modeling to study memory-based perceptual decisions in PD patients off dopaminergic medication and healthy controls to establish the effect of the disease on visual and memory integration. We hypothesize that PD patients fail to integrate information gained from memory with visual information to guide decisions. Second (Aim 2), we will measure the coupling between the MTL and BG using functional and structural MRI connectivity analyses. We hypothesize that the lower strength of MTL-BG connections structural integrity and functional connectivity in PD patients compared to healthy controls correlates with poorer decision-making behavior.

In the short term, these mechanistic studies will unravel the impairment in neurocircuitry involved in visual and memory integration in PD. In the long term, our longitudinal studies recruiting PD patients with normal cognition will determine whether those with more dysfunction in MTL-BG neurocircuitry early on are more prone to dementia, hallucinations, and falls in 3- and 5-year follow-ups. Therefore, MTL-BG neurocircuitry abnormality can be a predictive biomarker for early diagnosis of those at risk of dementia, hallucinations, and falls. Furthermore, it offers a platform for early treatments, using cholinergic modulations with small novel molecules or deep brain stimulations, targeting MTL-BG neurocircuitry and visual and memory integration in PD. Thus, it may halt the burdensome development of dementia, hallucinations, and falls.