Publications by authors named "Monroe Turner"

The goal of precision brain health is to accurately predict individuals' longitudinal patterns of brain change. We trained a machine learning model to predict changes in a cognitive index of brain health from neurophysiologic metrics. A total of 48 participants (ages 21-65) completed a sensorimotor task during 2 functional magnetic resonance imaging sessions 6 mo apart.

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Neural-vascular coupling (NVC) is the process by which oxygen and nutrients are delivered to metabolically active neurons by blood vessels. Murine models of NVC disruption have revealed its critical role in healthy neural function. We hypothesized that, in humans, aging exerts detrimental effects upon the integrity of the neural-glial-vascular system that underlies NVC.

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Most studies examining neurocognitive aging are based on the blood-oxygen level-dependent signal obtained during functional magnetic resonance imaging (fMRI). The physiological basis of this signal is neural-vascular coupling, the process by which neurons signal cerebrovasculature to dilate in response to an increase in active neural metabolism due to stimulation. These fMRI studies of aging rely on the hemodynamic equivalence assumption that this process is not disrupted by physiologic deterioration associated with aging.

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Standard magnetic resonance imaging approaches offer high-resolution but indirect measures of neural activity, limiting understanding of the physiological processes associated with imaging findings. Here, we used calibrated functional magnetic resonance imaging during the resting state to recover low-frequency fluctuations of the cerebral metabolic rate of oxygen (CMRO ). We tested whether functional connections derived from these fluctuations exhibited organization properties similar to those established by previous standard functional and anatomical connectivity studies.

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The present and future research efforts in cognitive neuroscience and psychophysiology rely on the measurement, understanding, and interpretation of blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) to effectively investigate brain function. Aging and age-associated pathophysiological processes change the structural and functional integrity of the cerebrovasculature which can significantly alter how the BOLD signal is recorded and interpreted. In order to gain an improved understanding of the benefits, drawbacks, and methodological implications for BOLD fMRI in the context of cognitive neuroscience, it is crucial to understand the cellular and molecular mechanism of age-related vascular pathologies.

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Cerebrovascular reactivity (CVR) is an index of the dilatory function of cerebral blood vessels and has shown great promise in the diagnosis of risk factors in cerebrovascular disease. Aging is one such risk factor; thus, it is important to characterize age-related differences in CVR. CVR can be measured by BOLD MRI but few studies have measured quantitative cerebral blood flow (CBF)-based CVR in the context of aging.

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Behavioral studies investigating fundamental cognitive abilities provide evidence that processing speed accounts for large proportions of performance variability between individuals. Processing speed decline is a hallmark feature of the cognitive disruption observed in healthy aging and in demyelinating diseases such as multiple sclerosis (MS), neuromyelitis optica, and Wilson's disease. Despite the wealth of evidence suggesting a central role for processing speed in cognitive decline, the neural mechanisms of this fundamental ability remain unknown.

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The neural mechanisms underlying motor impairment in multiple sclerosis (MS) remain unknown. Motor cortex dysfunction is implicated in blood-oxygen-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) studies, but the role of neural-vascular coupling underlying BOLD changes remains unknown. We sought to independently measure the physiologic factors (i.

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Facial recognition ability declines in adult aging, but the neural basis for this decline remains unknown. Cortical areas involved in face recognition exhibit lower dopamine (DA) receptor availability and lower blood-oxygen-level-dependent (BOLD) signal during task performance with advancing adult age. We hypothesized that changes in the relationship between these two neural systems are related to age differences in face-recognition ability.

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Theories of neurocognitive aging rely heavily on functional magnetic resonance imaging (fMRI) to test hypotheses regarding the brain basis of age-differences in cognition. This technique is based on the blood-oxygen level dependent signal (BOLD) that arises from the coordinated neural-vascular coupling that leads to increased blood flow following an increase in neural activity. Here we review the literature and current controversies regarding the mechanisms by which blood flow and neural activity are coupled, and how they change in the aging process.

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Background: Cognitive slowing occurs in ~70% of multiple sclerosis (MS) patients. The pathophysiology of this slowing is unknown. Neurovascular coupling, acute localized blood flow increases following neural activity, is essential for efficient cognition.

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Background And Purpose: Multiple sclerosis (MS) clinical management is based upon lesion characterization from 2-dimensional (2D) magnetic resonance imaging (MRI) views. Such views fail to convey the lesion-phenotype (ie, shape and surface texture) complexity, underlying metabolic alterations, and remyelination potential. We utilized a 3-dimensional (3D) lesion phenotyping approach coupled with imaging to study physiologic profiles within and around MS lesions and their impacts on lesion phenotypes.

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Functional magnetic resonance imaging (fMRI) has been used to infer age-differences in neural activity from the hemodynamic response function (HRF) that characterizes the blood-oxygen-level-dependent (BOLD) signal over time. BOLD literature in healthy aging lacks consensus in age-related HRF changes, the nature of those changes, and their implications for measurement of age differences in brain function. Between-study discrepancies could be due to small sample sizes, analysis techniques, and/or physiologic mechanisms.

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The hemodynamic response function (HRF), a model of brain blood-flow changes in response to neural activity, reflects communication between neurons and the vasculature that supplies these neurons in part by means of glial cell intermediaries (e.g., astrocytes).

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Recall accuracy decreases over successive memory trials using similar memoranda. This effect reflects proactive interference (PI) - the tendency for previously studied information to reduce recall of new information. However, recall improves if memoranda for a subsequent trial are semantically dissimilar from the previous trials.

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Multiple sclerosis (MS) involves damage to white matter microstructures. This damage has been related to grey matter function as measured by standard, physiologically-nonspecific neuroimaging indices (i.e.

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A multiple sclerosis (MS) diagnosis often relies upon clinical presentation and qualitative analysis of standard, magnetic resonance brain images. However, the accuracy of MS diagnoses can be improved by utilizing advanced brain imaging methods. We assessed the accuracy of a new neuroimaging marker, visual-evoked cerebral metabolic rate of oxygen (veCMRO₂), in classifying MS patients and closely age- and sex-matched healthy control (HC) participants.

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Multiple sclerosis (MS) results in inflammatory damage to white matter microstructure. Prior research using blood-oxygen-level dependent (BOLD) imaging indicates MS-related alterations to brain function. What is currently unknown is the extent to which white matter microstructural damage influences BOLD signal in MS.

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Cognitive slowing is a prevalent symptom observed in Gulf War Illness (GWI). The present study assessed the extent to which functional connectivity between dorsolateral prefrontal cortex (DLPFC) and other task-relevant brain regions was predictive of GWI-related cognitive slowing. GWI patients (n = 54) and healthy veteran controls (n = 29) were assessed on performance of a processing speed task (the Digit Symbol Substitution Task; DSST) while undergoing functional magnetic resonance imaging (fMRI).

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Objective: Cognitive slowing is a core neuropsychological symptom of Multiple Sclerosis (MS). We aimed to assess the extent to which cognitive slowing in MS was predicted by changes in dorsolateral prefrontal networks.

Method: We assessed patients with relapsing-remitting MS and healthy controls (HCs) on measures of processing speed.

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Dysphoria is associated with persistence of attention on mood-congruent information. Longer time attending to mood-congruent information for dysphoric individuals (DIs) detracts from goal-relevant information processing and should reduce working memory (WM) capacity. Study 1 showed that DIs and non-DIs have similar WM capacities.

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Background: Using a standard space brain template is an efficient way of determining region-of-interest (ROI) boundaries for functional magnetic resonance imaging (fMRI) data analyses. However, ROIs based on landmarks on subject-specific (i.e.

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