Parkinson's disease (PD) leads to cognitive deficits that can be more disturbing to patients than the motor symptoms, yet these symptoms are overlooked and untreated despite their high frequency in early disease stages and the high risk for future mild cognitive impairment or dementia. Most PD patients eventually develop dementia, which is up to five times more prevalent than in normal aging. With emerging applications of functional magnetic resonance imaging (fMRI), there is mounting evidence of abnormal brain functioning in PD even when performance is normal on clinical testing. Early structural changes in gray- and white-matter tissue also are associated with subtle changes in cognition in PD patients without dementia. Prediction of cognitive changes before clinical symptoms manifest is vital since optimal interventions will ultimately depend on early detection. The primary goal of this proposal is to identify early multimodal signatures of brain dysfunction in different networks implicated in the development of cognitive impairment in PD. The neural bases of subtle cognitive changes in early stages of PD are not well understood. This has been hampered by a paucity of studies that probe for dysfunction in different brain networks implicated in the development of different types of cognitive impairment. Changes in some networks may be more prognostic of the risk for dementia than changes in others. Moreover, most studies focus on disease-related changes in the amount of brain activation, which is insensitive to communications among brain regions. Since brain regions interact to fulfill a cognitive function, it is essential to study their functional connectivity, which may be a more significant intermediat phenotype of early pathology. It is also critical to consider that the functionality of brain netwoks may depend partly on the structural integrity of grey- and white-matter tissue, yet this also has not been studied in PD. To this end, the proposed project will identify abnormal functional connectivity in different brain networks as measured from the blood oxygen level dependent (BOLD) signal during task-activated fMRI. We will then determine if abnormal functional connectivity in each brain network is related to a loss in white- matter tract integrity or gray-matter volume using diffusion tensor imaging (DTI) and structural MRI (sMRI). PD patients and healthy control subjects will undergo fMRI as they perform three cognitive tasks that probe for functioning in brain networks implicated in the development of cognitive impairment, namely tests of temporal integration, visuospatial working memory, and inhibitory control.
Aim 1 will identify disease-related functional changes in the connectivity of brain circuits that govern each cognitive function. The main hypotheses are that functional connectivity in PD will be altered in brain circuits that govern temporal integration (cortico-basal ganglia thalamocortical system), visuospatial working memory (dorsolateral prefrontal cortex circuit, dorsal and ventral attention networks), and inhibitory control (ventral lateral orbitofrontal circuit).
Aim 2 will then determin if abnormal functional connectivity of the different brain networks identified by fMRI is associated with a loss in white-matter fiber-tract integrity using DTI tractography. The main hypothesis is that abnormal functional connectivity in brain networks that govern processing in each cognitive domain will best correlate with abnormal tissue diffusivity in the same pathways.
For Aim 3, sMRI analyses will be conducted to determine if abnormal functional connectivity of the different brain networks correlates with volume loss. The main hypothesis is that abnormal functional connectivity in brain networks that govern processing in each cognitive domain will correlate with frontostriatal and/or temporal atrophy. Our multimodal inquiry into identifying neuroimaging markers of cognitive changes in distinct brain networks, before clinically significant symptoms manifest, be the first of its kind in PD and will promote a new understanding of pathological mechanisms of cognitive dysfunction. Ultimately, outcomes from this research may inform the selection of surrogate measures for evaluating therapeutic interventions.
Parkinson's disease (PD) is second only to Alzheimer's disease as a neurodegenerative disorder. PD leads to cognitive deficits that can be more disturbing to patients than the motor symptoms. Most PD patients eventually develop dementia, which is up to five times more prevalent than in normal aging. There are nearly 80,000 Veterans with PD and the incidence is projected to increase substantially by the year 2020, placing even greater demands on the VA Healthcare System. The primary goal of the proposed project is to identify early functional and structural changes in brain networks that support key cognitive functions. This multipronged approach to identifying neuroimaging phenotypes associated with cognitive changes in PD, before clinically significant symptoms manifest, is vital since optimal interventions will ultimately depend on early detection. This knowledge can be expected to inform future intervention therapeutics and ultimately lead to better healthcare for Veterans.
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