Development and organization of the human brain tissue compartments across the lifespan using diffusion tensor imaging

Hasan, Khader M.; Sankar, Ambika; Halphen, Christopher; Kramer, Larry A.; Brandt, Michael E.; Juranek, Jenifer; Cirino, Paul T.; Fletcher, Jack Μ.; Papanicolaou, Andrew C.; Ewing‐Cobbs, Linda

doi:10.1097/wnr.0b013e3282f0d40c

Cited by 100 publications

(106 citation statements)

References 17 publications

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“…WM FA tends to decrease with aging in men and women (reviewed in Moseley 2002). Similar to the volumetric data, FA peaks in early middle age when myelination peaks (Kemper 1994) and then declines in the elderly at a rate that parallels or precedes WM volumetric loss (Hasan et al 2007;Hasan et al 2008;Hasan et al 2010;Lebel et al 2010;Westlye et al 2010). Regionally, age-related deficits of FA have been described in the genu of the CC centrum semiovale, frontal, and parietal pericallosal WM of men (Pfefferbaum et al 2000), with a similar pattern found in both sexes (Sullivan et al 2001).…”

Section: Diffusion Tensor Imaging In Humansmentioning

confidence: 77%

Age-related changes in human and non-human primate white matter: from myelination disturbances to cognitive decline

Kohama

Rosene

Sherman

2011

AGE

117

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The cognitive decline associated with normal aging was long believed to be due primarily to decreased synaptic density and neuron loss. Recent studies in both humans and non-human primates have challenged this idea, pointing instead to disturbances in white matter (WM) including myelin damage. Here, we review both cross-sectional and longitudinal studies in humans and non-human primates that collectively support the hypothesis that WM disturbances increase with age starting at middle age in humans, that these disturbances contribute to age-related cognitive decline, and that age-related WM changes may occur as a result of free radical damage, degenerative changes in cells in the oligodendrocyte lineage, and changes in microenvironments within WM.

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Section: Diffusion Tensor Imaging In Humansmentioning

confidence: 77%

Age-related changes in human and non-human primate white matter: from myelination disturbances to cognitive decline

Kohama

Rosene

Sherman

2011

AGE

117

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“…For example, Anokhin et al (1996) and MeyerLindenberg (1996) demonstrated that while EEG power shows a progressive decrease as a function of age, correlation dimension values increase linearly within the age interval of 7 to 60 years. Similarly, while neuroanatomical studies on GM development show a progressive reduction of its volume which starts in childhood (Giedd et al 1999;Sowell et al 1999;Steen et al 1997), WM investigations tend to exhibit an opposite tendency (Ben Bashat et al 2005;Gao et al 2009;Hasan et al 2009;Hasan et al 2007). These parallel trajectories of WM and complexity values might appear as apparently broken during late adulthood, since some studies (see for example McLaughlin et al 2007) demonstrated a FA peak in young adulthood followed by a decline.…”

Section: Discussionmentioning

confidence: 97%

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

Fernández¹,

Ríos-Lago²,

Abásolo³

et al. 2011

NeuroImage

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The advent of new signal processing methods, such as non-linear analysis techniques, represents a new perspective which adds further value to brain signals' analysis. Particularly, Lempel-Ziv's Complexity (LZC) has proven to be useful in exploring the complexity of the brain electromagnetic activity. However, an important problem is the lack of knowledge about the physiological determinants of these measures. Although a correlation between complexity and connectivity has been proposed, this hypothesis was never tested in vivo.Thus, the correlation between the microstructure of the anatomic connectivity and the functional complexity of the brain needs to be inspected. In this study we analysed the correlation between LZC and fractional anisotropy (FA), a scalar quantity derived from diffusion tensors that is particularly useful as an estimate of the functional integrity of myelinated axonal fibers, in a group of sixteen healthy adults (all female, mean age 65.56 ± 6.06 years, interval 58-82). Our results showed a positive correlation between FA and LZC scores in regions including clusters in the splenium of the corpus callosum, cingulum, parahipocampal regions and the sagittal stratum. This study supports the notion of a positive correlation between the functional complexity of the brain and the microstructure of its anatomical connectivity. Our investigation proved that a combination of neuroanatomical and neurophysiological techniques may shed some light on the underlying physiological determinants of brain's oscillations.

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“…Given previous reports (Allen et Rauch and Jinkins, 1994), both linear and quadratic age terms were included. The DTI metrics (e.g., FA,λ ⊥ ) were modeled (fitted) for both males and females as y f =β 0 +β 1 *age+β 2 *age 2 , then the general least-squares methods were used to compute the coefficients, standard errors and their significance using analysis-of-variance (ANOVA) methods (Hasan et al, 2007b;Hasan et al, 2008). For comparison of two fit parameters between males and females, we used a two-tailed t-test of the difference (β iM -β iF ) divided by the root of the pooled variance σ(β iM ) 2 +σ(β iF ) 2 at the corresponding degrees of freedom (Glantz, 2002).…”

Section: Discussionmentioning

confidence: 99%

Diffusion tensor quantification of the human midsagittal corpus callosum subdivisions across the lifespan

et al. 2008

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The midsagittal corpus callosum (CC) cross-sectional area subdivisions have been used as early and sensitive markers of human brain white matter connectivity, development, natural aging and disease. Despite the simplicity and conspicuity of the appearance of the CC on anatomical magnetic resonance imaging (MRI), the published quantitative MRI literature on its regional sex and age trajectories are contradictory. The availability of noninvasive quantitative methods to assess the CC regions across the human lifespan would help clarify its contribution to behavior and cognition. In this report, we extended the utility of a recently described semi-automated diffusion tensor imaging (DTI) tissue segmentation method to utilize the high orientation contrast of the CC on DTI. Using optimized DTI methods on a cohort of 121 right-handed children and adults aged 6-68 years, we examined the CC areas and corresponding DTI metrics of the different functionally specialized sectors of the CC. Both the area and fractional anisotropy metrics followed inverted U-shaped curves, while the mean and radial diffusivities followed U-curve reflecting white matter progressive and regressive myelination dynamics that continue into young adulthood.

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Development and organization of the human brain tissue compartments across the lifespan using diffusion tensor imaging

Cited by 100 publications

References 17 publications

Age-related changes in human and non-human primate white matter: from myelination disturbances to cognitive decline

Age-related changes in human and non-human primate white matter: from myelination disturbances to cognitive decline

The correlation between white-matter microstructure and the complexity of spontaneous brain activity: A difussion tensor imaging-MEG study

Diffusion tensor quantification of the human midsagittal corpus callosum subdivisions across the lifespan

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