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The targeted brain dysfunction that accompanies aging can have a devastating effect on cognitive and intellectual abilities. A significant proportion of older adults experience precipitous cognitive decline that negatively impacts functional activities. Such individuals meet clinical diagnostic criteria for dementia, which is commonly attributed to Alzheimer's disease (AD). Structural neuroimaging, including magnetic resonance imaging (MRI), has contributed significantly to our understanding of the morphological and pathology-related changes that may underlie normal and disease-associated cognitive change in aging. White matter hyperintensities (WMH), which are distributed patches of increased hyperintense signal on T2-weighted MRI, are among the most common structural neuroimaging findings in older adults. In recent years, WMH have emerged as robust radiological correlates of cognitive decline. Studies suggest that WMH distributed in anterior brain regions are related to decline in executive abilities that is typical of normal aging, whereas WMH distributed in more posterior brain regions are common in AD. Although epidemiological, observational, and pathological studies suggest that WMH may be ischemic in origin and caused by consistent or variable hypoperfusion, there is emerging evidence that they may also reflect vascular deposition of beta-amyloid, particularly when they are distributed in posterior areas and are present in patients with AD. Findings from the literature highlight the potential contribution of small-vessel cerebrovascular disease to the pathogenesis of AD, and suggest a mechanistic interaction, but future longitudinal studies using multiple imaging modalities are required to fully understand the complex role of WMH in AD.

Although we rarely think about our everyday cognition as skilled cognition --- because it comes naturally and all of us possess it --- we are all experts in mastering our everyday environment. This expertise may be manifested in mundane or everyday tasks like discerning familiar faces from strangers, or for some people, in more complex situations such as determining whether to swing at a 95mph fastball. The athlete's brain offers a good opportunity for studying neuroplasticity and perceptual expertise because athletes participate in long term training and practice, often starting very early in childhood, and continuing throughout their entire careers. The goal of this dissertation is to investigate the effect of expertise on brain network dynamics during perceptual decision making tasks using techniques for multimodal data fusion. Specifically, we design novel stimuli and methods of combining simultaneously collected electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to investigate brain networks involved in the split-second decisions faced by baseball batters. Using single-trial analysis with experts in baseball, we find the neural correlates of expertise in baseball pitch recognition in both the temporal domain (EEG) and spatial domain (fMRI). We find that experts in baseball pitch recognition exhibit larger activations in early visual prediction networks as well as motor planning areas which aid in the experts superior behavioral performance. In this dissertation, we also focus on leveraging the complementary strengths of the two neuroimaging modalities (EEG, fMRI) to create novel fusion techniques that can provide richer network dynamics than by either modality separately. We design a novel encoding model to fuse EEG and fMRI to provide unprecedented spatio-temporal resolution of a perceptual decision in the human brain. On top of the methodologies for EEG-fMRI fusion, we show that motion correction hardware can be implemented to significantly improve signal-to-noise for fMRI acquisition by reducing motion artifacts which highly contaminate simultaneous EEG-fMRI data. These tools taken together provide researchers with another dimension---temporal ordering of brain activations--- to probe behavioral, psychological, or even compromised states during perceptual decision making.

Hitting a baseball is often described as the most difficult thing to do in sports. A key aptitude of a good hitter is the ability to determine which pitch is coming. This rapid decision requires the batter to make a judgment in a fraction of a second based largely on the trajectory and spin of the ball. When does this decision occur relative to the ball’s trajectory and is it possible to identify neural correlates that represent how the decision evolves over a split second? Using single-trial analysis of electroencephalography (EEG) we address this question within the context of subjects discriminating three types of pitches (fastball, curveball, slider) based on pitch trajectories. We find clear neural signatures of pitch classification and, using signal detection theory, we identify the times of discrimination on a trial-to-trial basis. Based on these neural signatures we estimate neural discrimination distributions as a function of the distance the ball is from the plate. We find all three pitches yield unique distributions, namely the timing of the discriminating neural signatures relative to the position of the ball in its trajectory. For instance, fastballs are discriminated at the earliest points in their trajectory, relative to the two other pitches, which is consistent with the need for some constant time to generate and execute the motor plan for the swing (or inhibition of the swing). We also find incorrect discrimination of a pitch (errors) yields neural sources in Brodmann Area 10, which has been implicated in prospective memory, recall, and task difficulty. In summary, we show that single-trial analysis of EEG yields informative distributions of the relative point in a baseball’s trajectory when the batter makes a decision on which pitch is coming.

International audience; The present study examines the epidemiological evidence for a causal relationship between caffeine consumption and cognitive deterioration in the elderly. Using a population of 641 elderly persons, we examined cognitive functioning, caffeine consumption, magnetic resonance imaging volumetrics, and other factors known to affect cognitive performance. Our findings demonstrate the association between caffeine consumption and lower cognitive change over time to be statistically significant for women only, taking into account multiple confounders, to be dose-dependent and temporarily related (caffeine consumption precedes cognitive change). Mean log transformed white matter lesion/cranial volume ratios were found to be significantly lower in women consuming more than 3 units of caffeine per day after adjustment for age (-1.23 SD=0.06) than in women consuming 2-3 units (-1.04 SD=0.04) or one unit or less (-1.04 SD=0.07, -35% in cm3 compared to low drinkers). This observation is coherent with biological assumptions that caffeine through adenosine is linked to amyloid accumulation and subsequently white matter lesion formation. The significant relationship observed between caffeine intake in women and lower cognitive decline is highly likely to be a true causal relationship and not a spurious association.