2017 — 2019 |
Wiesman, Alex |
F31Activity Code Description: To provide predoctoral individuals with supervised research training in specified health and health-related areas leading toward the research degree (e.g., Ph.D.). |
Oscillatory Markers of Cognitive Deficits in Patients With Alzheimer's Disease @ University of Nebraska Medical Center
ABSTRACT/PROJECT SUMMARY Aging is typically associated with some limited cognitive decline, although a subgroup of the aging population will experience the rapid and progressive declines that are associated with Alzheimer?s disease (AD) and its common precursor, mild cognitive impairment (MCI). With around 5.1 million Americans living with AD today, there is an immediate need to understand the neurophysiological basis of these mental declines. Attention and working memory (WM) processes are among the earliest and most severely affected cognitive functions in MCI and AD. Attention is defined as the preferential allocation of processing resources towards a specific stimulus or stimuli, whereas WM denotes the on-line temporary storage of information to be used in ongoing cognitive processing. Although neuropsychological testing has shown a clear deficit in these domains in patients with MCI and AD, far less is known about the neural oscillatory activity and computational dynamics that underlie these deficits. The current study aims to partially remedy this knowledge gap by utilizing the spatial precision and exquisite temporal resolution (i.e., millisecond) of magnetoencephalographic (MEG) imaging. Using MEG, we will determine the neurophysiological bases of attentional and WM dysfunction in adults with MCI and AD, as compared to a demographically-matched sample of neurologically-healthy older adults. Briefly, participants will complete two cognitive tasks during MEG recording, one tapping attentional processing and another aimed at WM. Both of these cognitive tasks have been shown to produce robust neural oscillatory activity in healthy controls. The resulting MEG data will be transformed into the time-frequency domain and imaged using an advanced beamforming approach. The output dynamic functional maps of electrical neural activity will be used to examine low frequency (i.e., alpha and theta) oscillatory activity and dynamic functional connectivity among regions serving attention and WM processes. Essentially, we will identify the statistically anomalous neural oscillations and functional connectivity in patients with MCI and AD, and then link these neural data to cognitive performance metrics. Our specific aims are: (1) To identify aberrant theta and alpha oscillatory dynamics in neural regions serving WM and attention processing in patients with MCI and mild AD, and (2) to quantify dynamic functional connectivity during these same cognitive processes in patients with MCI and mild AD. To this end, we will utilize the latest MEG and advanced source reconstruction techniques, neural oscillatory analysis methods, and neuropsychological assessment to delineate the neurophysiological bases of cognitive impairments in patients with MCI and AD. With the world population aging in a highly disproportionate manner, AD prevalence is set to rise in future decades, and the hefty economical and societal burdens associated with the disease will certainly follow. Research aimed at better understanding the disease and providing potential markers for diagnosing and tracking disease progression may ultimately reduce the societal impact, by guiding and informing novel treatment development and reducing the overall financial burden.
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0.915 |
2020 |
Wiesman, Alex |
F32Activity Code Description: To provide postdoctoral research training to individuals to broaden their scientific background and extend their potential for research in specified health-related areas. |
Characterizing the Interaction Between Neural Attention and Somato-Motor Systems in Non-Demented Patients With Parkinson's Disease
Parkinson?s disease (PD) is a progressive neurodegenerative disorder that presents a looming economic and societal challenge in the United States and worldwide. Despite being primarily a disorder of the motor system (i.e., the brain systems controlling movement), patients with PD are also known to exhibit profound deficits in attention, which is our ability to direct brain resources towards important aspects of the environment. Importantly, these issues are not isolated from one another, as attentional issues are robustly linked to risk of falls in patients with PD, which are the most common reason for hospitalization and major injury in this population. Indeed, attention-based therapies have been developed for patients with PD and have been moderately successful, but a great deal of variability exists in patient outcomes. This variability is largely due to the lack of specific neurophysiological and cognitive targets of these therapies, so a better understanding of the brain systems being affected is essential to improving patient outcomes. The current project aims to identify and quantify the brain- basis of attentional impairments in patients with PD, as well as the neurophysiology underlying the interactions between these deficient attentional sub-systems and somato-motor systems. The primary goal of this research will be to provide novel targets for enhanced clinical interventions, such as brain stimulation and attention-training therapies. A secondary goal of this project is to provide a data-driven framework for the assessment of attention- training in the brains of patients with PD, and the impact of this training on the brain circuits that control movement (i.e., somato-motor networks). To reach these goals, a series of innovative cognitive neuroscience experiments will be utilized, combined with advanced brain imaging techniques. These data will be collected using expansive data repositories available in Montreal (the Quebec Parkinson Network and the Montreal Neurological Institute Clinical Biological Imaging and Genetic Repository) and analyzed using a number of highly innovative signal processing techniques developed by Professor Sylvain Baillet in his state-of-the-art software housed in his laboratory at McGill University (Brainstorm; > 23,000 users worldwide). These studies which will allow for novel investigations of the role of dynamic brain activity patterns between and within attention and somato-motor networks in patients with PD. This will provide new targets for attention- training and brain stimulation therapies, while also enhancing our understanding of the neurobiological aberrations that contribute to PD. The aim of my research project is to understand (1) which attentional neural sub-systems are being preferentially affected by PD, and (2) how these attentional sub-systems interact with established PD-related somato-motor system aberrations. These findings will then provide key metrics for the assessment of treatment efficacy, as well as targets for therapeutic intervention. With the prevalence of PD rising both nationally and worldwide, concrete targets for intervention are desperately needed to minimize the impact of this debilitating disorder, both on the personal level for those affected, and broadly on a socio-economic scale.
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0.915 |