A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume

Buckner, Randy L.; Head, Denise; Parker, Jamie; Fotenos, Anthony F.; Marcus, Daniel S.; Morris, John C.; Snyder, Abraham Z.

doi:10.1016/j.neuroimage.2004.06.018

Cited by 1,171 publications

(1,008 citation statements)

References 63 publications

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“…Typical registration targets for MRI (e.g., MNI152) are based on a young adult sample, which systematically introduces greater registration error among older adults (61). To avoid this issue, following the procedure outlined in Buckner et al (61), an adult-lifespan sample-representative template was created (see SI Appendix, Supplemental Experimental Procedures for details) to incorporate typical structural variation present across our healthy adult lifespan sample (n = 268; age range, 20-89 y). Standard fMRI preprocessing.…”

Section: Data Preprocessingmentioning

confidence: 99%

Decreased segregation of brain systems across the healthy adult lifespan

Chan

Park

Savalia

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

753

128

956

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Healthy aging has been associated with decreased specialization in brain function. This characterization has focused largely on describing age-accompanied differences in specialization at the level of neurons and brain areas. We expand this work to describe systems-level differences in specialization in a healthy adult lifespan sample (n = 210; 20-89 y). A graph-theoretic framework is used to guide analysis of functional MRI resting-state data and describe systems-level differences in connectivity of individual brain networks. Young adults' brain systems exhibit a balance of within-and between-system correlations that is characteristic of segregated and specialized organization. Increasing age is accompanied by decreasing segregation of brain systems. Compared with systems involved in the processing of sensory input and motor output, systems mediating "associative" operations exhibit a distinct pattern of reductions in segregation across the adult lifespan. Of particular importance, the magnitude of association system segregation is predictive of long-term memory function, independent of an individual's age.aging | brain networks | resting-state correlations | memory | connectome

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Section: Data Preprocessingmentioning

confidence: 99%

Decreased segregation of brain systems across the healthy adult lifespan

Chan

Park

Savalia

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

753

128

956

View full text Add to dashboard Cite

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“…This entails registering the data for each subject to an atlas space, so that common imaging masks and fcMRI seeds can be used to define these nuisance signals in each subject. This transformation of the functional data to atlas space, in this case, 711-2B (Buckner et al, 2004;Talairach and Tournoux, 1988;Ojemann, 1997) was computed for each individual via the MP-RAGE scan. Each run then was resampled in atlas space (Talairach and Tournoux, 1988) on an isotropic grid (3 mm voxels) combining movement correction and atlas transformation in one interpolation (Lancaster et al, 1995;Snyder, 1996).…”

Section: Data Preprocessingmentioning

confidence: 99%

Defining functional areas in individual human brains using resting functional connectivity MRI

et al. 2008

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The cerebral cortex is anatomically organized at many physical scales starting at the level of single neurons and extending up to functional systems. Current functional magnetic resonance imaging (fMRI) studies often focus at the level of areas, networks, and systems. Except in restricted domains, (e.g. topographically-organized sensory regions), it is difficult to determine area boundaries in the human brain using fMRI. The ability to delineate functional areas non-invasively would enhance the quality of many experimental analyses allowing more accurate across-subject comparisons of independently identified functional areas. Correlations in spontaneous BOLD activity, often referred to as resting state functional connectivity (rs-fcMRI), are especially promising as a way to accurately localize differences in patterns of correlated activity across large expanses of cortex. In the current report, we applied a novel set of image analysis tools to explore the utility of rs-fcMRI for defining wide-ranging functional area boundaries. We find that rs-fcMRI patterns show sharp transitions in correlation patterns and that these putative areal boundaries can be reliably detected in individual subjects as well as in group data. Additionally, combining surface-based analysis techniques with image processing algorithms allows automated mapping of putative areal boundaries across large expanses of cortex without the need for prior information about a region's function or topography. Our approach reliably produces maps of bounded regions appropriate in size and number for putative functional areas. These findings will hopefully stimulate further methodological refinements and validations.CORRESPONDING AUTHORS: Alexander

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“…The methodology of FreeSurfer has been described in detail (Dale and Sereno, 1993;Dale et al, 1999;Fischl et al, 1999;Fischl and Dale, 2000;Fischl et al, 2001Fischl et al, , 2002Fischl et al, , 2004aSegonne et al, 2004;Desikan et al, 2006;Han et al, 2006;Jovicich et al, 2006;Segonne et al, 2007). Hippocampal measures were based on subcortical segmentation (Fischl et al, 2002(Fischl et al, , 2004aBuckner et al, 2004), and a neuroanatomically trained operator reviewed images for accuracy.…”

Section: Mri Acquisition and Postprocessingmentioning

confidence: 99%

Hippocampal Subregions are Differentially Affected in the Progression to Alzheimer's Disease

Greene

Killiany

2011

The Anatomical Record

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Atrophy within the hippocampus (HP) as measured by magnetic resonance imaging (MRI) is a promising biomarker for the progression to Alzheimer's disease (AD). Subregions of the HP along the longitudinal axis have been found to demonstrate unique function, as well as undergo differential changes in the progression to AD. Little is known of relationships between such HP subregions and other potential biomarkers, such as neuropsychological (NP), genetic, and cerebral spinal fluid (CSF) beta amyloid and tau measures. The purpose of this study was to subdivide the hippocampus to determine how the head, body, and tail were affected in normal control, mild cognitively impaired, and AD subjects, and investigate relationships with HP subregions and other potential biomarkers. MRI scans of 120 participants of the Alzheimer's Disease Neuroimaging Initiative were processed using FreeSurfer, and the HP was subdivided using 3D Slicer. Each subregion was compared among groups, and correlations were used to determine relationships with NP, genetic, and CSF measures. Results suggest that HP subregions are undergoing differential atrophy in AD, and demonstrate unique relationships with NP and CSF data. Discriminant function analyses revealed that these regions, when combined with NP and CSF measures, were able to classify by diagnostic group, and classify MCI subjects who would and would not progress to AD within 12 months. Anat Rec,

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A unified approach for morphometric and functional data analysis in young, old, and demented adults using automated atlas-based head size normalization: reliability and validation against manual measurement of total intracranial volume

Cited by 1,171 publications

References 63 publications

Decreased segregation of brain systems across the healthy adult lifespan

Decreased segregation of brain systems across the healthy adult lifespan

Defining functional areas in individual human brains using resting functional connectivity MRI

Hippocampal Subregions are Differentially Affected in the Progression to Alzheimer's Disease

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