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      Lesion location matters: The relationships between white matter hyperintensities on cognition in the healthy elderly

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          Abstract

          White matter hyperintensities (WMH) are associated with cognitive decline. We aimed to identify the spatial specificity of WMH impact on cognition in non-demented, healthy elderly. We quantified WMH volume among healthy participants of a community dwelling cohort ( n = 702, age range 60 - 82 years, mean age = 69.5 years, 46% female) and investigated the effects of WMH on cognition and behavior, specifically for executive function, memory, and motor speed performance. Lesion location influenced their effect on cognition and behavior: Frontal WMH in the proximity of the frontal ventricles mainly affected executive function and parieto-temporal WMH in the proximity of the posterior horns deteriorated memory, while WMH in the upper deep white matter-including the corticospinal tract-compromised motor speed performance. This study exposes the subtle and subclinical yet detrimental effects of WMH on cognition in healthy elderly, and strongly suggests a causal influence of WMH on cognition by demonstrating the spatial specificity of these effects.

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          Most cited references17

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          Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration.

          All fields of neuroscience that employ brain imaging need to communicate their results with reference to anatomical regions. In particular, comparative morphometry and group analysis of functional and physiological data require coregistration of brains to establish correspondences across brain structures. It is well established that linear registration of one brain to another is inadequate for aligning brain structures, so numerous algorithms have emerged to nonlinearly register brains to one another. This study is the largest evaluation of nonlinear deformation algorithms applied to brain image registration ever conducted. Fourteen algorithms from laboratories around the world are evaluated using 8 different error measures. More than 45,000 registrations between 80 manually labeled brains were performed by algorithms including: AIR, ANIMAL, ART, Diffeomorphic Demons, FNIRT, IRTK, JRD-fluid, ROMEO, SICLE, SyN, and four different SPM5 algorithms ("SPM2-type" and regular Normalization, Unified Segmentation, and the DARTEL Toolbox). All of these registrations were preceded by linear registration between the same image pairs using FLIRT. One of the most significant findings of this study is that the relative performances of the registration methods under comparison appear to be little affected by the choice of subject population, labeling protocol, and type of overlap measure. This is important because it suggests that the findings are generalizable to new subject populations that are labeled or evaluated using different labeling protocols. Furthermore, we ranked the 14 methods according to three completely independent analyses (permutation tests, one-way ANOVA tests, and indifference-zone ranking) and derived three almost identical top rankings of the methods. ART, SyN, IRTK, and SPM's DARTEL Toolbox gave the best results according to overlap and distance measures, with ART and SyN delivering the most consistently high accuracy across subjects and label sets. Updates will be published on the http://www.mindboggle.info/papers/ website.
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            Executive function and the frontal lobes: a meta-analytic review.

            Currently, there is debate among scholars regarding how to operationalize and measure executive functions. These functions generally are referred to as "supervisory" cognitive processes because they involve higher level organization and execution of complex thoughts and behavior. Although conceptualizations vary regarding what mental processes actually constitute the "executive function" construct, there has been a historical linkage of these "higher-level" processes with the frontal lobes. In fact, many investigators have used the term "frontal functions" synonymously with "executive functions" despite evidence that contradicts this synonymous usage. The current review provides a critical analysis of lesion and neuroimaging studies using three popular executive function measures (Wisconsin Card Sorting Test, Phonemic Verbal Fluency, and Stroop Color Word Interference Test) in order to examine the validity of the executive function construct in terms of its relation to activation and damage to the frontal lobes. Empirical lesion data are examined via meta-analysis procedures along with formula derivatives. Results reveal mixed evidence that does not support a one-to-one relationship between executive functions and frontal lobe activity. The paper concludes with a discussion of the implications of construing the validity of these neuropsychological tests in anatomical, rather than cognitive and behavioral, terms.
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              Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study. The Rotterdam Scan Study

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                Author and article information

                Journal
                Journal of Cerebral Blood Flow & Metabolism
                J Cereb Blood Flow Metab
                SAGE Publications
                0271-678X
                1559-7016
                November 06 2017
                January 2019
                November 06 2017
                January 2019
                : 39
                : 1
                : 36-43
                Affiliations
                [1 ]Department of Neurology, Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
                [2 ]Clinic of Cognitive Neurology, University Hospital Leipzig, Leipzig, Germany
                [3 ]Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, QC, Canada
                [4 ]Institute for Medical Informatics, Statistics, and Epidemiology (IMISE), University of Leipzig, Leipzig, Germany
                Article
                10.1177/0271678X17740501
                6311671
                29106319
                651d0f59-1e22-43f2-a829-a39b3feef987
                © 2019

                http://journals.sagepub.com/page/policies/text-and-data-mining-license

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