Magnetic Resonance Imaging (MRI) is the principal method for studying structural age-related brain changes in vivo. However, previous research has yielded inconsistent results, precluding understanding of structural changes of the aging brain. This inconsistency is due to methodological differences and/or different aging patterns across samples. To overcome these problems, we tested age effects on 17 different neuroanatomical structures and total brain volume across five samples, of which one was split to further investigate consistency (883 participants). Widespread age-related volume differences were seen consistently across samples. In four of the five samples, all structures, except the brain stem, showed age-related volume differences. The strongest and most consistent effects were found for cerebral cortex, pallidum, putamen and accumbens volume. Total brain volume, cerebral white matter, caudate, hippocampus and the ventricles consistently showed non-linear age functions. Healthy aging appears associated with more widespread and consistent age-related neuroanatomical volume differences than previously believed.
MRI morphometry; Age; Cortex; White matter; Cerebellum; Ventricles; Hippocampus; Amygdala; Thalamus; Basal ganglia
Alzheimer's disease (AD) has a slow onset, so it is challenging to distinguish brain changes in healthy elderly persons from incipient AD. One-year brain changes with a distinct frontotemporal pattern have been shown in older adults. However, it is not clear to what extent these changes may have been affected by undetected, early AD. To address this, we estimated 1-year atrophy by magnetic resonance imaging (MRI) in 132 healthy elderly persons who had remained free of diagnosed mild cognitive impairment or AD for at least 3 years. We found significant volumetric reductions throughout the brain. The sample was further divided into low-risk groups based on clinical, biomarker, genetic, or cognitive criteria. Although sample sizes varied, significant reductions were observed in all groups, with rates and topographical distribution of atrophy comparable to that of the full sample. Volume reductions were especially pronounced in the default mode network, closely matching the previously described frontotemporal pattern of changes in healthy aging. Atrophy in the hippocampus predicted change in memory, with no additional default mode network contributions. In conclusion, reductions in regional brain volumes can be detected over the course of 1 year even in older adults who are unlikely to be in a presymptomatic stage of AD.
Reduced levels of β-amyloid1-42 (Aβ1-42) and increased levels of tau proteins in the cerebrospinal fluid (CSF) are found in Alzheimer’s disease (AD), likely reflecting Aβ deposition in plaques and neuronal and axonal damage. It is not known whether these biomarkers are associated with brain atrophy also in healthy aging. We tested the relationship between CSF levels of Aβ1-42 and tau (total tau and tau phosphorylated at threonine 181) proteins and 1-year brain atrophy in 71 cognitively normal elderly individuals. Results showed that under a certain threshold value, levels of Aβ1-42 correlated highly with 1-year change in a wide range of brain areas. The strongest relationships were not found in the regions most vulnerable early in AD. Above the threshold level, Aβ1-42 was not related to brain changes, but significant volume reductions as well as ventricular expansion were still seen. It is concluded that Aβ1-42 correlates with brain atrophy and ventricular expansion in a subgroup of cognitively normal elderly individuals but that reductions independent of CSF levels of Aβ1-42 is common. Further research and follow-up examinations over several years are needed to test whether degenerative pathology will eventually develop in the group of cognitively normal elderly individuals with low levels of Aβ1-42.
aging; amyloid; cerebral cortex; CSF biomarkers; MRI
Burgmans, van Boxtel, Vuurman, et al. (2009) published an interesting study titled “The Prevalence of Cortical Gray Matter Atrophy May Be Overestimated in the Healthy Aging Brain” on how subclinical cognitive disorders may affect correlations between age and cortical volume. Correlations between cortical gray matter volume and age were found in 30 elderly with cognitive decline after 6 years, but not in 28 elderly without cognitive decline. This study is important, and demonstrates that preclinical cognitive disorders may affect cortical brain volumes before being detectable by neuropsychological tests. However, we are not convinced by the conclusions: “… gray matter atrophy … is to a lesser extent associated with the healthy aging process, but more likely with brain processes underlying significant cognitive decline” (p. 547) and “… cortical gray matter atrophy in the aging brain may be overestimated in a large number of studies on healthy aging” (p. 547). We analyzed the cross-sectional MR data (n = 1,037) as well as longitudinal data from a sample of very well-screened elderly followed by cognitive testing for 2 years. In the cross-sectional data, the correlations between age and brain volumes were generally not much reduced when the upper age limit was lowered. This would not be expected if age-related incipient cognitive disorders caused the correlations given that the incidence of cognitive decline increased with age. Longitudinally, 1-year atrophy was identified in all tested regions. It is likely that cortical brain atrophy is manifested in cognitively normal elderly without subclinical cognitive disorders.
aging; atrophy; cerebral cortex; hippocampus; cognition
MRI-based estimates of cerebral morphometric properties, e.g. cortical thickness, are pivotal to studies of normal and pathological brain changes. These measures are based on automated or manual segmentation procedures, which utilize the tissue contrast between gray and white matter on T1-weighted MR images. Tissue contrast is unlikely to remain a constant property across groups of different age and health. An important question is therefore how the sensitivity of cortical thickness estimates is influenced by variability in WM/GM contrast. The effect of adjusting for variability in WM/GM contrast on age sensitivity of cortical thickness was tested in 1,189 healthy subjects from six different samples, enabling evaluation of consistency of effects within and between sites and scanners. Further, the influence of Alzheimer’s disease (AD) diagnosis on cortical thickness with and without correction for contrast was tested in an additional sample of 96 patients. In healthy controls, regional increases in the sensitivity of the cortical thickness measure to age were found after correcting for contrast. Across samples, the strongest effects were observed in frontal, lateral temporal and parietal areas. Controlling for contrast variability also increased the cortical thickness estimates’ sensitivity to AD, thus replicating the finding in an independent clinical sample. The results showed increased sensitivity of cortical estimates to AD in areas earlier reported to be compromised in AD, including medial temporal, inferior and superior parietal regions. In sum, the findings indicate that adjusting for contrast can increase the sensitivity of MR morphometry to variables of interest.
Cross-sectional magnetic resonance imaging (MRI) studies of cortical thickness and volume have shown age effects on large areas, but there are substantial discrepancies across studies regarding the localization and magnitude of effects. These discrepancies hinder understanding of effects of aging on brain morphometry, and limit the potential usefulness of MR in research on healthy and pathological age-related brain changes. The present study was undertaken to overcome this problem by assessing the consistency of age effects on cortical thickness across 6 different samples with a total of 883 participants. A surface-based segmentation procedure (FreeSurfer) was used to calculate cortical thickness continuously across the brain surface. The results showed consistent age effects across samples in the superior, middle, and inferior frontal gyri, superior and middle temporal gyri, precuneus, inferior and superior parietal cortices, fusiform and lingual gyri, and the temporo-parietal junction. The strongest effects were seen in the superior and inferior frontal gyri, as well as superior parts of the temporal lobe. The inferior temporal lobe and anterior cingulate cortices were relatively less affected by age. The results are discussed in relation to leading theories of cognitive aging.
aging; cortex; frontal lobes; morphometry; MRI
Brain atrophy and altered CSF-levels of amyloid beta (Aβ42) and the microtubule-associated protein tau are potent biomarkers of Alzheimer's Disease (AD) related pathology. However, the relationship between CSF biomarkers and brain morphometry is poorly understood. Thus, we addressed the following questions: (1) Can CSF biomarker levels explain the morphometric differences between normal controls (NC) and patients with mild cognitive impairment (MCI) or AD? (2) How are CSF biomarkers related to atrophy across the brain? (3) How closely are CSF biomarkers and morphometry related to clinical change (CDR sum of boxes [CDR-sb])? 370 participants (105 NC/ 175 MCI/ 90 AD) from the Alzheimer's Disease Neuroimaging Initiative were studied, of whom 309 were followed for one and 176 for two years. Analyses were performed across the entire cortical surface, as well as for 30 cortical and subcortical regions of interest (ROIs). Results showed that CSF biomarker levels could not account for group differences in brain morphometry at baseline but that CSF biomarker levels showed moderate relationships to longitudinal atrophy rates in numerous brain areas, not restricted to medial temporal structures. Baseline morphometry was at least as predictive of atrophy as were CSF biomarkers. Even MCI patients with levels of Aβ42 comparable to controls and of p-tau lower than controls showed more atrophy than the controls. Morphometry predicted change in CDR-sb better than did CSF biomarkers. These results indicate that morphometric changes in MCI and AD are not secondary to CSF biomarker changes, and that the two types of biomarkers yield complementary information.
Alzheimer's disease; Magnetoencephalography; ABeta-peptide; Phosphorylation; Hippocampus; Cerebral cortex; Entorhinal cortex; Parahippocampal cortex
An accurate description of changes in the brain in healthy aging is needed to understand the basis of age-related changes in cognitive function. Cross-sectional magnetic resonance imaging (MRI) studies suggest thinning of the cerebral cortex, volumetric reductions of most subcortical structures and ventricular expansion. However, there is a paucity of detailed longitudinal studies to support the cross-sectional findings. In the present study, 142 healthy elderly participants (60–91 years) were followed with repeated MRI, and were compared to 122 patients with mild to moderate Alzheimer's disease (AD). Volume changes were measured across the entire cortex and in 48 regions of interest (ROIs). Cortical reductions in the healthy elderly were extensive after only one year, especially evident in temporal and prefrontal cortex where annual decline was about 0.5%. All subcortical and ventricular regions except caudate nucleus and the 4th ventricle changed significantly over one year. Some of the atrophy occurred in areas vulnerable to AD, while other changes were observed in areas less characteristic of the disease in early stages. This suggests that the changes are not primarily driven by degenerative processes associated with AD, although it is likely that preclinical changes associated with AD are superposed on changes due to normal aging in some subjects, especially in the temporal lobes. Finally, atrophy was found to accelerate with increasing age, and this was especially prominent in areas vulnerable to AD. Thus, it is possible that the accelerating atrophy with increasing age is due to preclinical AD.
MRI; aging; longitudinal; ADNI; cerebral cortex; hippocampus
Age is associated with substantial macro-structural brain changes. While some recent magnetic resonance imaging (MRI) studies have reported larger age-effects in men than women, others find no sex differences. As brain morphometry is a potentially important tool in diagnosis and monitoring of age-related neurological diseases, e.g. Alzheimer’s disease (AD), it is important to know whether sex influences brain aging. We analyzed cross-sectional MR scans from 1143 healthy participants from seven subsamples provided by four independent research groups. In addition, 96 patients with mild AD were included. Estimates of cortical thickness continuously across the brain surface, as well as volume of 17 subcortical structures, were obtained by use of automated segmentation tools (FreeSurfer). In the healthy participants, no differences in aging slopes between women and men were found in any part of the cortex. Pallidum corrected for intracranial volume showed slightly higher age correlations for men. The analyses were repeated in each of the seven sub-samples, and the lack of age × sex interactions was largely replicated. Analyses of the AD sample showed no interactions between sex and age for any brain region. It is concluded that sex has negligible effects on the age-slope of brain volumes both in healthy participants and in AD.
MRI; aging; sex; cerebral cortex; hippocampus; FreeSurfer
Right–left regional cerebral differences are a feature of the human brain linked to functional abilities, aging, and neuro-developmental and mental disorders. The role of genetic factors in structural asymmetry has been incompletely studied. We analyzed data from 515 individuals (130 monozygotic twin pairs, 97 dizygotic pairs, and 61 unpaired twins) from the Vietnam Era Twin Study of Aging to answer three questions about genetic determinants of brain structural asymmetry: First, does the magnitude of heritability differ for homologous regions in each hemisphere? Despite adequate power to detect regional differences, heritability estimates were not significantly larger in one hemisphere versus the other, except left > right inferior lateral ventricle heritability. Second, do different genetic factors influence left and right hemisphere size in homologous regions? Inter-hemispheric genetic correlations were high and significant; in only two subcortical regions (pallidum and accumbens) did the estimate statistically differ from 1.0. Thus, there was little evidence for different genetic influences on left and right hemisphere regions. Third, to what extent do genetic factors influence variability in left–right size differences? There was no evidence that variation in asymmetry (i.e., the size difference) of left and right homologous regions was genetically determined, except in pallidum and accumbens. Our findings suggest that genetic factors do not play a significant role in determining individual variation in the degree of regional cortical size asymmetries measured with MRI, although they may do so for volume of some subcortical structures. Despite varying interpretations of existing left–right, we view the present results as consistent with previous findings.
Retinotopy constrained source estimation (RCSE) is a method for non-invasively measuring the time courses of activation in early visual areas using magnetoencephalography (MEG) or electroencephalography (EEG). Unlike conventional equivalent current dipole or distributed source models, the use of multiple, retinotopically-mapped stimulus locations to simultaneously constrain the solutions allows for the estimation of independent waveforms for visual areas V1, V2, and V3, despite their close proximity to each other. We describe modifications that improve the reliability and efficiency of this method. First, we find that increasing the number and size of visual stimuli results in source estimates that are less susceptible to noise. Second, to create a more accurate forward solution, we have explicitly modeled the cortical point spread of individual visual stimuli. Dipoles are represented as extended patches on the cortical surface, which take into account the estimated receptive field size at each location in V1, V2, and V3 as well as the contributions from contralateral, ipsilateral, dorsal, and ventral portions of the visual areas. Third, we implemented a map fitting procedure to deform a template to match individual subject retinotopic maps derived from functional magnetic resonance imaging (fMRI). This improves the efficiency of the overall method by allowing automated dipole selection, and it makes the results less sensitive to physiological noise in fMRI retinotopy data. Finally, the iteratively reweighted least squares (IRLS) method was used to reduce the contribution from stimulus locations with high residual error for robust estimation of visual evoked responses.
An important challenge in the design of diffusion MRI experiments is how to optimize statistical efficiency, i.e., the accuracy with which parameters can be estimated from the diffusion data in a given amount of imaging time. In model-based spherical deconvolution analysis, the quantity of interest is the fiber orientation density (FOD). Here, we demonstrate how the spherical harmonics (SH) can be used to form an explicit analytic expression for the efficiency of the minimum variance (maximally efficient) linear unbiased estimator of the FOD. Using this expression, we calculate optimal b-values for maximum FOD estimation efficiency with SH expansion orders of L = 2, 4, 6, and 8 to be approximately b = 1500, 3000, 4600, and 6200 s/mm2, respectively. However, the arrangement of diffusion directions and scanner-specific hardware limitations also play a role in determining the realizable efficiency of the FOD estimator that can be achieved in practice. We show how some commonly used methods for selecting diffusion directions are sometimes inefficient, and propose a new method for selecting diffusion directions in MRI based on maximizing the statistical efficiency. We further demonstrate how scanner-specific hardware limitations generally lead to optimal b-values that are slightly lower than the ideal b-values. In summary, the analytic expression for the statistical efficiency of the unbiased FOD estimator provides important insight into the fundamental tradeoff between angular resolution, b-value, and FOD estimation accuracy.
HARDI; spherical deconvolution; q-space; Q-ball; crossing fibers; fiber tracks; tracktography; linear model; spherical harmonics
Diffusion magnetic resonance imaging (dMRI) is a powerful tool for studying biological tissue microarchitectures in vivo. Recently, there has been increased effort to develop quantitative dMRI methods to probe both length scale and orientation information in diffusion media. Diffusion spectrum imaging (DSI) is one such approach that aims to resolve such information on the basis of the three-dimensional diffusion propagator at each voxel. However, in practice only the orientation component of the propagator function is preserved when deriving the orientation distribution function. Here, we demonstrate how a straightforward extension of the linear spherical deconvolution (SD) model can be used to probe tissue orientation structures over a range (or “spectrum”) of length scales with minimal assumptions on the underlying microarchitecture. Using high b-value Cartesian q-space data on a fixed rat brain sample, we demonstrate how this “restriction spectrum imaging” (RSI) model allows for separating the volume fraction and orientation distribution of hindered and restricted diffusion, which we argue stems primarily from diffusion in the extra- and intra-neurite water compartment, respectively. Moreover, we demonstrate how empirical RSI estimates of the neurite orientation distribution and volume fraction capture important additional structure not afforded by traditional DSI or fixed-scale SD-like reconstructions, particularly in grey matter. We conclude that incorporating length scale information in geometric models of diffusion offers promise for advancing state-of-the-art dMRI methods beyond white matter into grey matter structures while allowing more detailed quantitative characterization of water compartmentalization and histoarchitecture of healthy and diseased tissue.
Diffusion MRI; DTI; HARDI; DSI; FOD; Fiber Orientation; Tractography; Histology; Cerebellum; Cerebral Cortex; Striatum; Basal Ganglia; Rat
Background and Purpose
Age and the ε4 allele of apolipoprotein E (APOE ε4) are well-known risk factors for Alzheimer disease (AD), but whether female sex is also a risk factor remains controversial. It is also unclear how these risk factors affect rates of structural brain and clinical decline across the spectrum of preclinical to clinical AD. Our objective is to estimate the effects of APOE ε4 and sex on age-specific rates of morphometric and clinical decline in late onset sporadic AD.
Materials and Methods
Using linear mixed effects models, we examined the effect of age, APOE ε4, and sex on longitudinal brain atrophy and clinical decline among cognitively normal older individuals, and individuals with mild cognitive impairment and AD (total = 688). We also evaluated the relationship between these effects and cerebrospinal fluid (CSF) biomarkers of AD pathology.
APOE ε4 significantly accelerated rates of decline, and women in all cohorts experienced higher rates of decline than men. The magnitude of the sex effect on rates of decline were as large as those of ε4, yet their relationship to measures of CSF biomarkers were weaker.
These results indicate that in addition to APOE ε4 status, diagnostic and therapeutic strategies should take into account the effect of female sex on the Alzheimer disease process.
Individuals with a diagnosis of specific language impairment (SLI) show abnormal spoken language occurring alongside normal non-verbal abilities. Behaviorally, people with SLI exhibit diverse profiles of impairment involving phonological, grammatical, syntactic, and semantic aspects of language. In this study, we used a multimodal neuroimaging technique called anatomically constrained magnetoencephalography (aMEG) to measure the dynamic functional brain organization of an adolescent with SLI. Using single-subject statistical maps of cortical activity, we compared this patient to a sibling and to a cohort of typically developing subjects during the performance of tasks designed to evoke semantic representations of concrete objects. Localized patterns of brain activity within the language impaired patient showed marked differences from the typical functional organization, with significant engagement of right hemisphere heteromodal cortical regions generally homotopic to the left hemisphere areas that usually show the greatest activity for such tasks. Functional neuroanatomical differences were evident at early sensoriperceptual processing stages and continued through later cognitive stages, observed specifically at latencies typically associated with semantic encoding operations. Our findings show with real-time temporal specificity evidence for an atypical right hemisphere specialization for the representation of concrete entities, independent of verbal motor demands. More broadly, our results demonstrate the feasibility and potential utility of using aMEG to characterize individual patient differences in the dynamic functional organization of the brain.
magnetoencephalography; specific language impairment; object concepts; semantic representations; hemispheric specialization; cerebral dominance
Clinical research studies generate data that need to be shared and statistically analyzed by their participating institutions. The distributed nature of research and the different domains involved present major challenges to data sharing, exploration, and visualization. The Data Portal infrastructure was developed to support ongoing research in the areas of neurocognition, imaging, and genetics. Researchers benefit from the integration of data sources across domains, the explicit representation of knowledge from domain experts, and user interfaces providing convenient access to project specific data resources and algorithms. The system provides an interactive approach to statistical analysis, data mining, and hypothesis testing over the lifetime of a study and fulfills a mandate of public sharing by integrating data sharing into a system built for active data exploration. The web-based platform removes barriers for research and supports the ongoing exploration of data.
data exploration; data sharing; genetics; data dictionary; imaging; hypothesis testing
We present a database client software—Neurovascular Network Explorer 1.0 (NNE 1.0)—that uses MATLAB® based Graphical User Interface (GUI) for interaction with a database of 2-photon single-vessel diameter measurements from our previous publication (Tian et al., 2010). These data are of particular interest for modeling the hemodynamic response. NNE 1.0 is downloaded by the user and then runs either as a MATLAB script or as a standalone program on a Windows platform. The GUI allows browsing the database according to parameters specified by the user, simple manipulation and visualization of the retrieved records (such as averaging and peak-normalization), and export of the results. Further, we provide NNE 1.0 source code. With this source code, the user can database their own experimental results, given the appropriate data structure and naming conventions, and thus share their data in a user-friendly format with other investigators. NNE 1.0 provides an example of seamless and low-cost solution for sharing of experimental data by a regular size neuroscience laboratory and may serve as a general template, facilitating dissemination of biological results and accelerating data-driven modeling approaches.
database; graphical user interface; MATLAB; 2-photon microscopy; hemodynamic; cerebral cortex; arteriole; dilation
Education may reduce risk of dementia through passive reserve, by increasing neural substrate. We tested the hypotheses that education is associated with thicker cortex and reduced rates of atrophy in brain regions related to literacy and intellectual ability. Healthy older adults and those with mild cognitive impairment were categorized into High (≥18 yrs) and Low (≤13 yrs) education groups. Higher education was associated with thinner cortices in several areas, but one-year atrophy rates in these areas did not differ by education group. These results do not support a passive reserve model in which early life education protects against dementia by increasing cortical thickness. Connectivity and synaptic efficiency, or other lifestyle factors may more directly reflect cognitive reserve.
Brain reserve; cortical thickness; education; hippocampal volume; literacy; Mild Cognitive Impairment (MCI); aging
Structural changes in neuroanatomical subregions can be measured using serial magnetic resonance imaging scans, and provide powerful biomarkers for detecting and monitoring Alzheimer's disease. The Alzheimer's Disease Neuroimaging Initiative (ADNI) has made a large database of longitudinal scans available, with one of its primary goals being to explore the utility of structural change measures for assessing treatment effects in clinical trials of putative disease-modifying therapies. Several ADNI-funded research laboratories have calculated such measures from the ADNI database and made their results publicly available. Here, using sample size estimates, we present a comparative analysis of the overall results that come from the application of each laboratory's extensive processing stream to the ADNI database. Obtaining accurate measures of change requires correcting for potential bias due to the measurement methods themselves; and obtaining realistic sample size estimates for treatment response, based on longitudinal imaging measures from natural history studies such as ADNI, requires calibrating measured change in patient cohorts with respect to longitudinal anatomical changes inherent to normal aging. We present results showing that significant longitudinal change is present in healthy control subjects who test negative for amyloid-β pathology. Therefore, sample size estimates as commonly reported from power calculations based on total structural change in patients, rather than change in patients relative to change in healthy controls, are likely to be unrealistically low for treatments targeting amyloid-related pathology. Of all the measures publicly available in ADNI, thinning of the entorhinal cortex quantified with the Quarc methodology provides the most powerful change biomarker.
MCI; bias; biomarker; clinical trial; disease-specific effect; amyloid; aging; Alzheimer's disease; entorhinal cortex; hippocampus
The ability of written and spoken words to access the same semantic meaning provides a test case for the multimodal convergence of information from sensory to associative areas. Using anatomically-constrained magnetoencephalography (aMEG), the present study investigated the stages of word comprehension in real time in the auditory and visual modalities, as subjects participated in a semantic judgment task. Activity spread from the primary sensory areas along the respective ventral processing streams and converged in anterior temporal and inferior prefrontal regions, primarily on the left at around 400ms. Comparison of response patterns during repetition priming between the two modalities suggest that they are initiated by modality-specific memory systems, but that they are eventually elaborated mainly in supramodal areas.
We describe six cases from three unrelated consanguineous Egyptian families with a novel characteristic brain malformation at the level of the diencephalic–mesencephalic junction. Brain magnetic resonance imaging demonstrated a dysplasia of the diencephalic–mesencephalic junction with a characteristic ‘butterfly’-like contour of the midbrain on axial sections. Additional imaging features included variable degrees of supratentorial ventricular dilatation and hypoplasia to complete agenesis of the corpus callosum. Diffusion tensor imaging showed diffuse hypomyelination and lack of an identifiable corticospinal tract. All patients displayed severe cognitive impairment, post-natal progressive microcephaly, axial hypotonia, spastic quadriparesis and seizures. Autistic features were noted in older cases. Talipes equinovarus, non-obstructive cardiomyopathy and persistent hyperplastic primary vitreous were additional findings in two families. One of the patients required shunting for hydrocephalus; however, this yielded no change in ventricular size suggestive of dysplasia rather than obstruction. We propose the term ‘diencephalic–mesencephalic junction dysplasia’ to characterize this autosomal recessive malformation.
diencephalon; mesencephalon; mental retardation; brainstem malformation; brain wiring
Self-esteem and well-being are important for successful aging, and some evidence suggests that self-esteem and well-being are associated with hippocampal volume, cognition, and stress responsivity. Whereas most of this evidence is based on studies of older adults, we investigated self-esteem, well-being and hippocampal volume in 474 male middle-age twins. Self-esteem was significantly positively correlated with hippocampal volume (.09, p=.03 for left hippocampus, .10, p=.04 for right). Correlations for well-being were not significant (ps ≫.05). There were strong phenotypic correlations between self-esteem and well-being (.72, p<.001) and between left and right hippocampal volume (.72, p<.001). In multivariate genetic analyses, a 2-factor AE model with well-being and self-esteem on one factor and left and right hippocampal volumes on the other factor fit the data better than Cholesky, independent pathway or common pathway models. The correlation between the two genetic factors was .12 (p=.03); the correlation between the environmental factors was .09 (p>05). Our results indicate that largely different genetic and environmental factors underlie self-esteem and well-being on the one hand and hippocampal volume on the other.
self-esteem; well-being; hippocampus; twins; heritability; aging
In vivo optical imaging of cerebral blood flow (CBF) and metabolism did not exist 50 years ago. While point optical fluorescence and absorption measurements of cellular metabolism and hemoglobin concentrations had already been introduced by then, point blood flow measurements appeared only 40 years ago. The advent of digital cameras has significantly advanced two-dimensional optical imaging of neuronal, metabolic, vascular, and hemodynamic signals. More recently, advanced laser sources have enabled a variety of novel three-dimensional high-spatial-resolution imaging approaches. Combined, as we discuss here, these methods are permitting a multifaceted investigation of the local regulation of CBF and metabolism with unprecedented spatial and temporal resolution. Through multimodal combination of these optical techniques with genetic methods of encoding optical reporter and actuator proteins, the future is bright for solving the mysteries of neurometabolic and neurovascular coupling and translating them to clinical utility.
energy metabolism; hemodynamic; homeostasis; in vivo imaging; neurovascular
Surface area of the cerebral cortex is a highly heritable trait, yet little is known about genetic influences on regional cortical differentiation in humans. Using a data-driven, fuzzy clustering technique with magnetic resonance imaging data from 406 twins, we parceled cortical surface area into genetic subdivisions, creating a human brain atlas based solely on genetically informative data. Boundaries of the genetic divisions corresponded largely to meaningful structural and functional regions; however, the divisions represented previously undescribed phenotypes different from conventional (non–genetically based) parcellation systems. The genetic organization of cortical area was hierarchical, modular, and predominantly bilaterally symmetric across hemispheres. We also found that the results were consistent with human-specific regions being subdivisions of previously described, genetically based lobar regionalization patterns.
Although reading skill remains relatively stable with advancing age in humans, neurophysiological measures suggest potential reductions in efficiency of lexical information processing. It is unclear whether these age-related changes are secondary to decreases in regional cortical thickness and/or microstructure of fiber tracts essential to language. Magnetoencephalography, volumetric MRI, and diffusion tensor imaging were performed in 10 young (18–33 years) and 10 middle-aged (42–64 years) human individuals to evaluate the spatiotemporal dynamics and structural correlates of age-related changes in lexical-semantic processing. Increasing age was associated with reduced activity in left temporal lobe regions from 250–350ms and in left inferior prefrontal cortex from 350–450ms (i.e., N400). Hierarchical regression indicated that age no longer predicted left inferior prefrontal activity after cortical thickness and fractional anisotropy (FA) of the uncinate fasciculus (UF) were considered. Interestingly, FA of the UF was a stronger predictor of the N400 response than cortical thickness. Age-related reductions in left-lateralization of language responses were observed between 250–350ms, and were associated with left temporal thinning and frontotemporal FA reductions. N400 reductions were not associated with poorer task performance. Rather, increasing age was associated with reduction in the left prefrontal N400, which in turn was also associated with slower response time. These results reveal that changes in the neurophysiology of language occur by middle age and appear to be partially mediated by structural brain loss. These neurophysiological changes may reflect an adaptive process that ensues as communication between left perisylvian regions declines.
N400; magnetoencepholography; language; semantic processing; cortical thickness; diffusion tensor imaging