Biomedical subjects

Evan Fletcher

Publications and source records attributed to Evan Fletcher.

3 recordsLinked to original sources

PubMed2006

White matter changes compromise prefrontal cortex function in healthy elderly individuals.

Changes in memory function in elderly individuals are often attributed to dysfunction of the prefrontal cortex (PFC). One mechanism for this dysfunction may be disruption of white matter tracts that connect the PFC with its anatomical targets. Here, we tested the hypothesis that white matter degeneration is associated with reduced prefrontal activation. We used white matter hyperintensities (WMH), a magnetic resonance imaging (MRI) finding associated with cerebrovascular disease in elderly individuals, as a marker for white matter degeneration. Specifically, we used structural MRI to quantify the extent of WMH in a group of cognitively normal elderly individuals and tested whether these measures were predictive of the magnitude of prefrontal activity (fMRI) observed during performance of an episodic retrieval task and a verbal working memory task. We also examined the effects of WMH located in the dorsolateral frontal regions with the hypothesis that dorsal PFC WMH would be strongly associated with not only PFC function, but also with areas that are anatomically and functionally linked to the PFC in a task-dependent manner. Results showed that increases in both global and regional dorsal PFC WMH volume were associated with decreases in PFC activity. In addition, dorsal PFC WMH volume was associated with decreased activity in medial temporal and anterior cingulate regions during episodic retrieval and decreased activity in the posterior parietal and anterior cingulate cortex during working memory performance. These results suggest that disruption of white matter tracts, especially within the PFC, may be a mechanism for age-related changes in memory functioning.

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PubMed2005

Current concepts of analysis of cerebral white matter hyperintensities on magnetic resonance imaging.

Cerebrovascular disease is common and associated with cognitive deficits and increased risk for dementia. Until recently, only limited attention has focused on advances in imaging techniques to better define and quantify the spectrum of asymptomatic cerebrovascular disease commonly seen on magnetic resonance imaging, such as abnormal white matter signals. Abnormal signals in cerebral white matter, although nonspecific, are increased in prevalence and severity in association with aging and cerebrovascular risk factors among older individuals. The ubiquitous occurrence of these abnormal white matter signals commonly referred to as white matter hyperintensities (WMHs) and the association with cerebrovascular risk and cognitive impairment among older individuals make scientific evaluation of WMHs an important and much needed avenue of research. In this section, we review current methods of WMH analysis. Strengths and limitation of both quantitative and qualitative methods are discussed initially, followed by a brief review of current magnetic resonance imaging segmentation and mapping techniques that make it possible to assess the anatomical location of WMHs. We conclude by discussing future analytic methods designed to better understand the pathophysiology and cognitive consequences of WMHs.

Brain↗

PubMed2004

Anatomical mapping of white matter hyperintensities (WMH): exploring the relationships between periventricular WMH, deep WMH, and total WMH burden.

BACKGROUND AND PURPOSE: MRI segmentation and mapping techniques were used to assess evidence in support of categorical distinctions between periventricular white matter hyperintensities (PVWMH) and deep WMH (DWMH). Qualitative MRI studies generally identify 2 categories of WMH on the basis of anatomical localization. Separate pathophysiologies and behavioral consequences are often attributed to these 2 classes of WMH. However, evidence to support these empirical distinctions has not been rigorously sought. METHODS: MRI analysis of 55 subjects included quantification of WMH volume, mapping onto a common anatomical image, and spatial localization of each WMH voxel. WMH locations were then divided into PVWMH and DWMH on the basis of distance from the lateral ventricles and correlations, with total WMH volume determined. Periventricular distance histograms of WMH voxels were also calculated. RESULTS: PVWMH and DWMH were highly correlated with total WMH (R2>0.95) and with each other (R2>0.87). Mapping of all WMH revealed smooth expansion from around central cerebrospinal fluid spaces into more distal cerebral white matter with increasing WMH volume. CONCLUSIONS: PVWMH, DWMH, and total WMH are highly correlated with each other. Moreover, spatial analysis failed to identify distinct subpopulations for PVWMH and DWMH. These results suggest that categorical distinctions between PVWMH and DWMH may be arbitrary, and conclusions regarding individual relationships between causal factors or behavior for PVWMH and DWMH may more accurately reflect total WMH volume relationships.

Aged↗