Age-associated alterations in cortical gray and white matter signal intensity and gray to white matter contrast

Neurite imaging reveals microstructural variations in human cerebral cortical gray matter

We present distinct patterns of neurite distribution in the human cerebral cortex using diffusion magnetic resonance imaging (MRI). We analyzed both high-resolution structural (T1w and T2w images) and diffusion MRI data in 505 subjects from the Human Connectome Project. Neurite distributions were evaluated using the neurite orientation dispersion and density imaging (NODDI) model, optimized for gray matter, and mapped onto the cortical surface using a method weighted towards the cortical mid-thickness to reduce partial volume effects. The estimated neurite density was high in both somatosensory and motor areas, early visual and auditory areas, and middle temporal area (MT), showing a strikingly similar distribution to myelin maps estimated from the T1w/T2w ratio. The estimated neurite orientation dispersion was particularly high in early sensory areas, which are known for dense tangential fibers and are classified as granular cortex by classical anatomists. Spatial gradients of these cortical neurite properties revealed transitions that colocalize with some areal boundaries in a recent multi-modal parcellation of the human cerebral cortex, providing mutually supportive evidence. Our findings indicate that analyzing the cortical gray matter neurite morphology using diffusion MRI and NODDI provides valuable information regarding cortical microstructure that is related to but complementary to myeloarchitecture.

Multimodal Discrimination between Normal Aging, Mild Cognitive Impairment and Alzheimer's Disease and Prediction of Cognitive Decline

Alzheimer’s Disease (AD) and mild cognitive impairment (MCI) are associated with widespread changes in brain structure and function, as indicated by magnetic resonance imaging (MRI) morphometry and 18-fluorodeoxyglucose position emission tomography (FDG PET) metabolism. Nevertheless, the ability to differentiate between AD, MCI and normal aging groups can be difficult. Thus, the goal of this study was to identify the combination of cerebrospinal fluid (CSF) biomarkers, MRI morphometry, FDG PET metabolism and neuropsychological test scores to that best differentiate between a sample of normal aging subjects and those with MCI and AD from the Alzheimer’s Disease Neuroimaging Initiative. The secondary goal was to determine the neuroimaging variables from MRI, FDG PET and CSF biomarkers that can predict future cognitive decline within each group. To achieve these aims, a series of multivariate stepwise logistic and linear regression models were generated. Combining all neuroimaging modalities and cognitive test scores significantly improved the index of discrimination, especially at the earliest stages of the disease, whereas MRI gray matter morphometry variables best predicted future cognitive decline compared to other neuroimaging variables. Overall these findings demonstrate that a multimodal approach using MRI morphometry, FDG PET metabolism, neuropsychological test scores and CSF biomarkers may provide significantly better discrimination than any modality alone.

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database

BACKGROUND

In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the main scope being its use in daily practice. However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from a single modality, namely MRI.

NEW METHOD

Based on preprocessed MRI images from the organizers of a neuroimaging challenge,³ we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate among HC, MCI, cMCI and AD. We explored the efficacy of a novel scheme that includes multiple feature selections via Random Forest from subsets of the whole set of features (e.g. whole set, left/right hemisphere etc.), Random Forest classification using a fusion approach and ensemble classification via majority voting. From the ADNI database, 60 HC, 60 MCI, 60 cMCI and 60 CE were used as a training set with known labels. An extra dataset of 160 subjects (HC: 40, MCI: 40, cMCI: 40 and AD: 40) was used as an external blind validation dataset to evaluate the proposed machine learning scheme.

RESULTS

In the second blind dataset, we succeeded in a four-class classification of 61.9% by combining MRI-based features with a Random Forest-based Ensemble Strategy. We achieved the best classification accuracy of all teams that participated in this neuroimaging competition.

COMPARISON WITH EXISTING METHOD(S)

The results demonstrate the effectiveness of the proposed scheme to simultaneously discriminate among four groups using morphological MRI features for the very first time in the literature.

CONCLUSIONS

Hence, the proposed machine learning scheme can be used to define single and multi-modal biomarkers for AD.

Age-Related Gray and White Matter Changes in Normal Adult Brains

Normal aging is associated with both structural changes in many brain regions and functional declines in several cognitive domains with advancing age. Advanced neuroimaging techniques enable explorative analyses of structural alterations that can be used as assessments of such age-related changes. Here we used voxel-based morphometry (VBM) to investigate regional and global brain volume differences among four groups of healthy adults from the IXI Dataset: older females (OF, mean age 68.35 yrs; n=69), older males (OM, 68.43 yrs; n=66), young females (YF, 27.09 yrs; n=71), and young males (YM, 27.91 yrs; n=71), using 3D T1-weighted MRI data. At the global level, we investigated the influence of age and gender on brain volumes using a two-way analysis of variance. With respect to gender, we used the Pearson correlation to investigate global brain volume alterations due to age in the older and young groups. At the regional level, we used a flexible factorial statistical test to compare the means of gray matter (GM) and white matter (WM) volume alterations among the four groups. We observed different patterns in both the global and regional GM and WM alterations in the young and older groups with respect to gender. At the global level, we observed significant influences of age and gender on global brain volumes. At the regional level, the older subjects showed a widespread reduction in GM volume in regions of the frontal, insular, and cingulate cortices compared to the young subjects in both genders. Compared to the young subjects, the older subjects showed a widespread WM decline prominently in the thalamic radiations, in addition to increased WM in pericentral and occipital areas. Knowledge of these observed brain volume differences and changes may contribute to the elucidation of mechanisms underlying aging as well as age-related brain atrophy and disease.

Accelerated Changes in Cortical Thickness Measurements with Age in Military Service Members with Traumatic Brain Injury

Finding objective and quantifiable imaging markers of mild traumatic brain injury (TBI) has proven challenging, especially in the military population. Changes in cortical thickness after injury have been reported in animals and in humans, but it is unclear how these alterations manifest in the chronic phase, and it is difficult to characterize accurately with imaging. We used cortical thickness measures derived from Advanced Normalization Tools (ANTs) to predict a continuous demographic variable: age. We trained four different regression models (linear regression, support vector regression, Gaussian process regression, and random forests) to predict age from healthy control brains from publicly available datasets (n = 762). We then used these models to predict brain age in military Service Members with TBI (n = 92) and military Service Members without TBI (n = 34). Our results show that all four models overpredicted age in Service Members with TBI, and the predicted age difference was significantly greater compared with military controls. These data extend previous civilian findings and show that cortical thickness measures may reveal an association of accelerated changes over time with military TBI.

Partial volume model for brain MRI scan using MP2RAGE

MP2RAGE is a T1 weighted MRI sequence that estimates a composite image providing much reduction of the receiver bias, has a high intensity dynamic range, and provides an estimate of T1 mapping. It is, therefore, an appealing option for brain morphometry studies. However, previous studies have reported a difference in cortical thickness computed from MP2RAGE compared with widely used Multi-Echo MPRAGE. In this article, we demonstrated that using standard segmentation and partial volume estimation techniques on MP2RAGE introduces systematic errors, and we proposed a new model to estimate partial volume of the cortical gray matter. We also included in their model a local estimate of tissue intensity to take into account the natural variation of tissue intensity across the brain. A theoretical framework is provided and validated using synthetic and physical phantoms. A repeatability experiment comparing MPRAGE and MP2RAGE confirmed that MP2RAGE using our model could be considered for structural imaging in brain morphology study, with similar cortical thickness estimate than that computed with MPRAGE. Hum Brain Mapp 38:5115-5127, 2017. © 2017 Wiley Periodicals, Inc.

Distinguishing early and late brain aging from the Alzheimer's disease spectrum: consistent morphological patterns across independent samples

Alzheimer's disease (AD) is a debilitating age-related neurodegenerative disorder. Accurate identification of individuals at risk is complicated as AD shares cognitive and brain features with aging. We applied linked independent component analysis (LICA) on three complementary measures of gray matter structure: cortical thickness, area and gray matter density of 137 AD, 78 mild (MCI) and 38 subjective cognitive impairment patients, and 355 healthy adults aged 18-78 years to identify dissociable multivariate morphological patterns sensitive to age and diagnosis. Using the lasso classifier, we performed group classification and prediction of cognition and age at different age ranges to assess the sensitivity and diagnostic accuracy of the LICA patterns in relation to AD, as well as early and late healthy aging. Three components showed high sensitivity to the diagnosis and cognitive status of AD, with different relationships with age: one reflected an anterior-posterior gradient in thickness and gray matter density and was uniquely related to diagnosis, whereas the other two, reflecting widespread cortical thickness and medial temporal lobe volume, respectively, also correlated significantly with age. Repeating the LICA decomposition and between-subject analysis on ADNI data, including 186 AD, 395 MCI and 220 age-matched healthy controls, revealed largely consistent brain patterns and clinical associations across samples. Classification results showed that multivariate LICA-derived brain characteristics could be used to predict AD and age with high accuracy (area under ROC curve up to 0.93 for classification of AD from controls). Comparison between classifiers based on feature ranking and feature selection suggests both common and unique feature sets implicated in AD and aging, and provides evidence of distinct age-related differences in early compared to late aging.

Multimodal FLAIR/MPRAGE segmentation of cerebral cortex and cortical myelin

The MR signal from gray matter has been long known to present small differences in intensity that have been attributed to variations in cortical myelin content. Previous studies have shown that the T1-, T2-weighted signal and their ratio are sensitive to these variations. Here, we investigated different combinations of signal from MPRAGE and FLAIR images in multimodal segmentation with parametric models of signal intensity to identify a procedure for the identification of contrast in cortical gray matter and the segmentation of different cortical components at 3T. We show that a three-modal combination of these signals delivers a stable segmentation of the cortical mantle in which two distinct components are reliably identified. The resulting intensity maps correspond well to known regional myeloarchitectural differences between cortical regions. These results confirm that widely available MR sequences contain signal that may be used to reliably detect subtle differences in the composition of gray matter with a segmentation approach.

Genetic and environmental influences on cortical mean diffusivity

Magnetic resonance imaging (MRI) has become an important tool in the early detection of age-related and neuropathological brain changes. Recent studies suggest that changes in mean diffusivity (MD) of cortical gray matter derived from diffusion MRI scans may be useful in detecting early effects of Alzheimer's disease (AD), and that these changes may be detected earlier than alterations associated with standard structural MRI measures such as cortical thickness. Thus, due to its potential clinical relevance, we examined the genetic and environmental influences on cortical MD in middle-aged men to provide support for the biological relevance of this measure and to guide future gene association studies. It is not clear whether individual differences in cortical MD reflect neuroanatomical variability similarly detected by other MRI measures, or whether unique features are captured. For instance, variability in cortical MD may reflect morphological variability more commonly measured by cortical thickness. Differences among individuals in cortical MD may also arise from breakdowns in myelinated fibers running through the cortical mantle. Thus, we investigated whether genetic influences on variation in cortical MD are the same or different from those influencing cortical thickness and MD of white matter (WM) subjacent to the cortical ribbon. Univariate twin analyses indicated that cortical MD is heritable in the majority of brain regions; the average of regional heritability estimates ranged from 0.38 in the cingulate cortex to 0.66 in the occipital cortex, consistent with the heritability of other MRI measures of the brain. Trivariate analyses found that, while there was some shared genetic variance between cortical MD and each of the other two measures, this overlap was not complete (i.e., the correlation was statistically different from 1). A significant amount of distinct genetic variance influences inter-individual variability in cortical MD; therefore, this measure could be useful for further investigation in studies of neurodegenerative diseases and gene association studies.

Novel surface features for automated detection of focal cortical dysplasias in paediatric epilepsy

Focal cortical dysplasia is a congenital abnormality of cortical development and the leading cause of surgically remediable drug-resistant epilepsy in children. Post-surgical outcome is improved by presurgical lesion detection on structural MRI. Automated computational techniques have improved detection of focal cortical dysplasias in adults but have not yet been effective when applied to developing brains. There is therefore a need to develop reliable and sensitive methods to address the particular challenges of a paediatric cohort. We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort. In addition to established measures, such as cortical thickness, grey-white matter blurring, FLAIR signal intensity, sulcal depth and curvature, our novel features included complementary metrics of surface morphology such as local cortical deformation as well as post-processing methods such as the "doughnut" method - which quantifies local variability in cortical morphometry/MRI signal intensity, and per-vertex interhemispheric asymmetry. A neural network classifier was trained using data from 22 patients with focal epilepsy (mean age = 12.1 ± 3.9, 9 females), after intra- and inter-subject normalisation using a population of 28 healthy controls (mean age = 14.6 ± 3.1, 11 females). Leave-one-out cross-validation was used to quantify classifier sensitivity using established features and the combination of established and novel features. Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included, when compared to the sensitivity using only established features (59%). These methods may be applicable to aiding identification of subtle lesions in medication-resistant paediatric epilepsy as well as to the structural analysis of both healthy and abnormal cortical development.

Surface-Based Parameters of Brain Imaging in Male Patients with Alcohol Use Disorder

OBJECTIVE

The structural alteration of brain shown in patients with alcohol use disorder (AUD) can originate from both alcohol effects and genetic or developmental processes. We compared surface-based parameters of patients with AUD with healthy controls to prove the applicability of surface-based morphometry with head size correction and to determine the areas that were sensitive to brain alteration related to AUD.

METHODS

Twenty-six abstinent male patients with AUD (alcohol group, mean abstinence=13.2 months) and twenty-eight age-matched healthy participants (control group) were recruited from an inpatient mental hospital and community. All participants underwent a 3T MRI scan. Surface-based parameters were determined by using FreeSurfer.

RESULTS

Every surface-based parameter of the alcohol group was lower than the corresponding control group parameter. There were large group differences in the whole brain, grey and white matter volume, and the differences were more prominent after head size correction. Significant group differences were shown in cortical thicknesses in entire brain regions, especially in parietal, temporal and frontal areas. There were no significant group differences in surface areas, but group difference trends in surface areas of the frontal and parietal cortices were shown after head size correction.

CONCLUSION

Most of the surface-based parameters in alcohol group were altered because of incomplete recovery from chronic alcohol exposure and possibly genetic or developmental factors underlying the risk of AUD. Surface-based morphometry with controlling for head size is useful in comparing the volumetric parameters and the surface area to a lesser extent in alcohol-related brain alteration.

Increased MRI-based cortical grey/white-matter contrast in sensory and motor regions in schizophrenia and bipolar disorder

BACKGROUND

Schizophrenia and bipolar disorder share genetic risk factors and one possible illness mechanism is abnormal myelination. T1-weighted magnetic resonance imaging (MRI) tissue intensities are sensitive to myelin content. Therefore, the contrast between grey- and white-matter intensities may reflect myelination along the cortical surface.

METHOD

MRI images were obtained from patients with schizophrenia (n = 214), bipolar disorder (n = 185), and healthy controls (n = 278) and processed in FreeSurfer. The grey/white-matter contrast was computed at each vertex as the difference between average grey-matter intensity (sampled 0-60% into the cortical ribbon) and average white-matter intensity (sampled 0-1.5 mm into subcortical white matter), normalized by their average. Group differences were tested using linear models covarying for age and sex.

RESULTS

Patients with schizophrenia had increased contrast compared to controls bilaterally in the post- and precentral gyri, the transverse temporal gyri and posterior insulae, and in parieto-occipital regions. In bipolar disorder, increased contrast was primarily localized in the left precentral gyrus. There were no significant differences between schizophrenia and bipolar disorder. Findings of increased contrast remained after adjusting for cortical area, thickness, and gyrification. We found no association with antipsychotic medication dose.

CONCLUSIONS

Increased contrast was found in highly myelinated low-level sensory and motor regions in schizophrenia, and to a lesser extent in bipolar disorder. We propose that these findings indicate reduced intracortical myelin. In accordance with the corollary discharge hypothesis, this could cause disinhibition of sensory input, resulting in distorted perceptual processing leading to the characteristic positive symptoms of schizophrenia.

Quantitative T1 and T2 MRI signal characteristics in the human brain: different patterns of MR contrasts in normal ageing

Objective

The objective of this study was to examine age-dependent changes in both T₁-weighted and T₂-weighted image contrasts and spin-echo T₂ relaxation time in the human brain during healthy ageing.

Methods

A total of 37 participants between the ages of 49 and 87 years old were scanned with a 3 Tesla system, using T₁-weighted, T₂ weighted and quantitative spin-echo T₂ imaging. Contrast between image intensities and T₂ values was calculated for various regions, including between individual hippocampal subfields.

Results

The T₁ contrast-to-noise (CNR) and gray:white signal intensity ratio (GWR) did not change in the hippocampus, but it declined in the cingulate cortex with age. In contrast, T₂ CNR and GWR declined in both brain regions. T₂ relaxation time was almost constant in gray matter and most (but not all) hippocampal subfields, but increased substantially in white matter, pointing to an age effect on water relaxation in white matter.

Conclusions

Changes in T₁ and T₂ MR characteristics influence the appearance of brain images in later life and should be considered in image analyses of aged subjects. It is speculated that alterations at the cell biology level, with concomitant alterations to the local magnetic environment, reduce dephasing and subsequently prolong spin-echo T₂ through reduced diffusion effects in later life.

Electronic supplementary material

The online version of this article (doi:10.1007/s10334-016-0573-0) contains supplementary material, which is available to authorized users.

Electrophysiology of Memory-Updating Differs with Age

In oddball tasks, the P3 component of the event-related potential systematically varies with the time between target stimuli—the target-to-target interval (TTI). Longer TTIs result in larger P3 amplitudes and shorter latencies, and this pattern of results has been linked with working memory-updating processes. Given that working memory and the P3 have both been shown to diminish with age, the current study aimed to determine whether the linear relationship between P3 and TTI is compromised in healthy aging by comparing TTI effects on P3 amplitudes and latencies, and reaction time (RT), in young and older adults. Older adults were found to have an overall reduction in P3 amplitudes, longer latencies, an anterior shift in topography, a trend toward slower RTs, and a flatter linear relationship between P3 and TTI than young adults. Results suggest that the ability to maintain templates in working memory required for stimulus categorization decreases with age, and that as a result, neural compensatory mechanisms are employed.

Association of cortical thickness and neurological soft signs in patients with chronic schizophrenia and healthy controls

BACKGROUND

Neurological soft signs (NSS), i.e. subtle neurological abnormalities, have been frequently found in schizophrenia. Neuroimaging studies in schizophrenia have shown abnormal cortical thickness changes across the cortical mantle. However, few studies have examined relationships between NSS and cortical thickness abnormalities in schizophrenia.

METHOD

A sample of 18 patients with chronic schizophrenia and 20 age-matched healthy controls were included. Cortical thickness was assessed on high-resolution 3-tesla magnetic resonance imaging by using FreeSurfer software and NSS were rated on the Heidelberg Scale.

RESULTS

Significant negative correlations between NSS and cortical thickness were found in the prefrontal, inferior temporal, superior parietal, postcentral, and supramarginal cortices in the schizophrenia patients. In the controls, however, this negative correlation was found in the anterior cingulate, pericalcarine and superior/middle temporal regions.

CONCLUSION

Our results not only confirmed the association between NSS and cortical thickness in chronic schizophrenia but also indicated that patients and controls have different anatomical substrates of NSS.

Accelerated longitudinal gray/white matter contrast decline in aging in lightly myelinated cortical regions

Highly myelinated cortical regions seem to develop early and are more robust to age-related decline. By use of different magnetic resonance imaging (MRI) measures such as contrast between T1- and T2-weighted MRI scans (T1w/T2w) it is now possible to assess correlates of myelin content in vivo. Further, previous studies indicate that gray/white matter contrast (GWC) become blurred as individuals' age, apparently reflecting age-related changes in myelin structure. Here we address whether longitudinal changes in GWC are dependent on initial myelin content within tissue as defined by baseline T1w/T2w contrast, and hypothesize that lightly myelinated regions undergo more decline longitudinally. A sample of 207 healthy adult participants (range: 20-84 years) was scanned twice (interscan interval: 3.6 years). Results showed widespread longitudinal reductions of GWC throughout the cortical surface, especially in the frontal cortices, mainly driven by intensity decay in the white matter. Annual rate of GWC blurring showed acceleration with age in temporal and medial prefrontal regions. Moreover, the anatomical distribution of increased rate of GWC decline with advancing age was strongly related to baseline levels of intracortical myelin. This study provides a first evidence of accelerated regional GWC blurring with advancing age, relates GWC patterns to cortical myeloarchitectonics and supports the hypothesis of increased age-related vulnerability of lightly myelinated areas. Hum Brain Mapp 37:3669-3684, 2016. © 2016 Wiley Periodicals, Inc.

Cortical complexity as a measure of age-related brain atrophy

The structure of the human brain changes in a variety of ways as we age. While a sizeable literature has examined age-related differences in cortical thickness, and to a lesser degree, gyrification, here we examined differences in cortical complexity, as indexed by fractal dimensionality in a sample of over 400 individuals across the adult lifespan. While prior studies have shown differences in fractal dimensionality between patient populations and age-matched, healthy controls, it is unclear how well this measure would relate to age-related cortical atrophy. Initially computing a single measure for the entire cortical ribbon, i.e., unparcellated gray matter, we found fractal dimensionality to be more sensitive to age-related differences than either cortical thickness or gyrification index. We additionally observed regional differences in age-related atrophy between the three measures, suggesting that they may index distinct differences in cortical structure. We also provide a freely available MATLAB toolbox for calculating fractal dimensionality.

Neurobiological origin of spurious brain morphological changes: A quantitative MRI study

The high gray‐white matter contrast and spatial resolution provided by T1‐weighted magnetic resonance imaging (MRI) has made it a widely used imaging protocol for computational anatomy studies of the brain. While the image intensity in T1‐weighted images is predominantly driven by T1, other MRI parameters affect the image contrast, and hence brain morphological measures derived from the data. Because MRI parameters are correlates of different histological properties of brain tissue, this mixed contribution hampers the neurobiological interpretation of morphometry findings, an issue which remains largely ignored in the community. We acquired quantitative maps of the MRI parameters that determine signal intensities in T1‐weighted images (R₁ (=1/T1), R₂*, and PD) in a large cohort of healthy subjects (n = 120, aged 18–87 years). Synthetic T1‐weighted images were calculated from these quantitative maps and used to extract morphometry features—gray matter volume and cortical thickness. We observed significant variations in morphometry measures obtained from synthetic images derived from different subsets of MRI parameters. We also detected a modulation of these variations by age. Our findings highlight the impact of microstructural properties of brain tissue—myelination, iron, and water content—on automated measures of brain morphology and show that microstructural tissue changes might lead to the detection of spurious morphological changes in computational anatomy studies. They motivate a review of previous morphological results obtained from standard anatomical MRI images and highlight the value of quantitative MRI data for the inference of microscopic tissue changes in the healthy and diseased brain. Hum Brain Mapp 37:1801–1815, 2016. © 2016 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Age-associated differences on structural brain MRI in nondemented individuals from 71 to 103 years

Successful brain aging in the oldest old (≥90 years) is underexplored. This study examined cross-sectional brain morphological differences from 8th to 11th decades of life in nondemented individuals by high-resolution magnetic resonance imaging. Two hundred seventy-seven nondemented community-dwelling participants (71-103 years) from Sydney Memory and Ageing Study and Sydney Centenarian Study comprised the sample, including a subsample of 160 cognitively high-functioning elders. Relationships between age and magnetic resonance imaging-derived measurements were studied using general linear models; and structural profiles of the ≥90 years were delineated. In full sample and the subsample, significant linear negative relationship of gray matter with age was found, with the greatest age effects in the medial temporal lobe and parietal and occipital cortices. This pattern was further confirmed by comparing directly the ≥90 years to the 71-89 years groups. Significant quadratic age effects on total white matter and white matter hyperintensities were observed. Our study demonstrated heterogeneous differences across brain regions between the oldest old and young old, with an emphasis on hippocampus, temporoposterior cortex, and white matter hyperintensities.

The effect of Sailuotong (SLT) on neurocognitive and cardiovascular function in healthy adults: a randomised, double-blind, placebo controlled crossover pilot trial

Background

Sailuotong (SLT) is a standardised herbal medicine formula consisting of Panax ginseng, Ginkgo biloba, and Crocus sativus, and has been designed to enhance cognitive and cardiovascular function.

Methods

Using a randomised, double-blind, placebo controlled crossover design, this pilot study assessed the effect of treatment for 1 week with SLT and placebo (1 week washout period) on neurocognitive and cardiovascular function in healthy adults. Sixteen adults completed a computerised neuropsychological test battery (Compass), and had their electroencephalographic (EEG) activity and cardiovascular system function assessed. Primary outcome measures were cognitive test scores and oddball task event-related potential (ERP) component amplitudes. Secondary outcome measures were resting EEG spectral band amplitudes, and cardiovascular parameters.

Results

Treatment with SLT, compared to placebo, resulted in small improvements in working memory, a slight increase in auditory target (cf. nontarget) P3a amplitude, and a decrease in auditory N1 target (cf. nontarget) amplitude. There was no effect of SLT on EEG amplitude in delta, theta, alpha, or beta bands in both eyes open and eyes closed resting conditions, or on aortic and peripheral pulse pressure, and resting heartrate.

Conclusions

Findings suggest that SLT has the potential to improve working memory performance in healthy adults; a larger sample size is needed to confirm this.

Trial registration

Australia New Zealand Clinical Trials Registry Trial Registration Id: ACTRN12610000947000.

Preliminary findings demonstrating latent effects of early adolescent marijuana use onset on cortical architecture

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Early onset MJ use was associated with different patterns of cortical architecture.

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Early vs. late onset divergence was in brain regions underlying higher-order cognition.

•

Findings were above and beyond effects of alcohol and current age.

Background

As the most commonly used illicit substance during early adolescence, long-term or latent effects of early adolescent marijuana use across adolescent developmental processes remain to be determined.

Methods

We examined cortical thickness, gray/white matter border contrast (GWR) and local gyrification index (LGI) in 42 marijuana (MJ) users. Voxelwise regressions assessed early-onset (age <16) vs. late-onset (≥16 years-old) differences and relationships to continued use while controlling for current age and alcohol use.

Results

Although groups did not differ by onset status, groups diverged in their correlations between cannabis use and cortical architecture. Among early-onset users, continued years of MJ use and current MJ consumption were associated with thicker cortex, increased GWR and decreased LGI. Late-onset users exhibited the opposite pattern. This divergence was observed in all three morphological measures in the anterior dorsolateral frontal cortex (p < .05, FWE-corrected).

Conclusions

Divergent patterns between current MJ use and elements of cortical architecture were associated with early MJ use onset. Considering brain development in early adolescence, findings are consistent with disruptions in pruning. However, divergence with continued use for many years thereafter suggests altered trajectories of brain maturation during late adolescence and beyond.

Structural brain aging and speech production: a surface-based brain morphometry study

While there has been a growing number of studies examining the neurofunctional correlates of speech production over the past decade, the neurostructural correlates of this immensely important human behaviour remain less well understood, despite the fact that previous studies have established links between brain structure and behaviour, including speech and language. In the present study, we thus examined, for the first time, the relationship between surface-based cortical thickness (CT) and three different behavioural indexes of sublexical speech production: response duration, reaction times and articulatory accuracy, in healthy young and older adults during the production of simple and complex meaningless sequences of syllables (e.g., /pa-pa-pa/ vs. /pa-ta-ka/). The results show that each behavioural speech measure was sensitive to the complexity of the sequences, as indicated by slower reaction times, longer response durations and decreased articulatory accuracy in both groups for the complex sequences. Older adults produced longer speech responses, particularly during the production of complex sequence. Unique age-independent and age-dependent relationships between brain structure and each of these behavioural measures were found in several cortical and subcortical regions known for their involvement in speech production, including the bilateral anterior insula, the left primary motor area, the rostral supramarginal gyrus, the right inferior frontal sulcus, the bilateral putamen and caudate, and in some region less typically associated with speech production, such as the posterior cingulate cortex.

Breadth and age-dependency of relations between cortical thickness and cognition

Recent advances in neuroimaging have identified a large number of neural measures that could be involved in age-related declines in cognitive functioning. A popular method of investigating neural-cognition relations has been to determine the brain regions in which a particular neural measure is associated with the level of specific cognitive measures. Although this procedure has been informative, it ignores the strong interrelations that typically exist among the measures in each modality. An alternative approach involves investigating the number and identity of distinct dimensions within the set of neural measures and within the set of cognitive measures before examining relations between the 2 types of measures. The procedure is illustrated with data from 297 adults between 20 and 79 years of age with cortical thickness in different brain regions as the neural measures and performance on 12 cognitive tests as the cognitive measures. The results revealed that most of the relations between cortical thickness and cognition occurred at a general level corresponding to variance shared among different brain regions and among different cognitive measures. In addition, the strength of the thickness-cognition relation was substantially reduced after controlling the variation in age, which suggests that at least some of the thickness-cognition relations in age-heterogeneous samples may be attributable to the influence of age on each type of measure.

Age-related changes in brain hemodynamics; A calibrated MRI study

INTRODUCTION

Blood oxygenation-level dependent (BOLD) magnetic resonance imaging signal changes in response to stimuli have been used to evaluate age-related changes in neuronal activity. Contradictory results from these types of experiments have been attributed to differences in cerebral blood flow (CBF) and cerebral metabolic rate of oxygen (CMRO2 ). To clarify the effects of these physiological parameters, we investigated the effect of age on baseline CBF and CMRO2 .

MATERIALS AND METHODS

Twenty young (mean ± sd age, 28 ± 3 years), and 45 older subjects (66 ± 4 years) were investigated. A dual-echo pseudocontinuous arterial spin labeling (ASL) sequence was performed during normocapnic, hypercapnic, and hyperoxic breathing challenges. Whole brain and regional gray matter values of CBF, ASL cerebrovascular reactivity (CVR), BOLD CVR, oxygen extraction fraction (OEF), and CMRO2 were calculated.

RESULTS

Whole brain CBF was 49 ± 14 and 40 ± 9 ml/100 g/min in young and older subjects respectively (P < 0.05). Age-related differences in CBF decreased to the point of nonsignificance (B=-4.1, SE=3.8) when EtCO2 was added as a confounder. BOLD CVR was lower in the whole brain, in the frontal, in the temporal, and in the occipital of the older subjects (P<0.05). Whole brain OEF was 43 ± 8% in the young and 39 ± 6% in the older subjects (P = 0.066). Whole brain CMRO2 was 181 ± 60 and 133 ± 43 µmol/100 g/min in young and older subjects, respectively (P<0.01).

DISCUSSION

Age-related differences in CBF could potentially be explained by differences in EtCO2 . Regional CMRO2 was lower in older subjects. BOLD studies should take this into account when investigating age-related changes in neuronal activity.

Accurate cortical tissue classification on MRI by modeling cortical folding patterns

Accurate tissue classification is a crucial prerequisite to MRI morphometry. Automated methods based on intensity histograms constructed from the entire volume are challenged by regional intensity variations due to local radiofrequency artifacts as well as disparities in tissue composition, laminar architecture and folding patterns. Current work proposes a novel anatomy-driven method in which parcels conforming cortical folding were regionally extracted from the brain. Each parcel is subsequently classified using nonparametric mean shift clustering. Evaluation was carried out on manually labeled images from two datasets acquired at 3.0 Tesla (n = 15) and 1.5 Tesla (n = 20). In both datasets, we observed high tissue classification accuracy of the proposed method (Dice index >97.6% at 3.0 Tesla, and >89.2% at 1.5 Tesla). Moreover, our method consistently outperformed state-of-the-art classification routines available in SPM8 and FSL-FAST, as well as a recently proposed local classifier that partitions the brain into cubes. Contour-based analyses localized more accurate white matter-gray matter (GM) interface classification of the proposed framework compared to the other algorithms, particularly in central and occipital cortices that generally display bright GM due to their highly degree of myelination. Excellent accuracy was maintained, even in the absence of correction for intensity inhomogeneity. The presented anatomy-driven local classification algorithm may significantly improve cortical boundary definition, with possible benefits for morphometric inference and biomarker discovery.

Gray & white matter tissue contrast differentiates Mild Cognitive Impairment converters from non-converters

The clinical relevance of gray/white matter contrast ratio (GWR) in mild cognitive impairment (MCI) remains unknown. This study examined baseline GWR and 3-year follow-up diagnostic status in MCI. Alzheimer's Disease Neuroimaging Initiative MCI participants with baseline 1.5 T MRI and 3-year follow-up clinical data were included. Participants were categorized into two groups based on 3-year follow-up diagnoses: 1) non-converters (n = 69, 75 ± 7, 26 % female), and 2) converters (i.e., dementia at follow-up; n = 69, 75 ± 7, 30 % female) who were matched on baseline age and Mini-Mental State Examination scores. Groups were compared on FreeSurfer generated baseline GWR from structural images in which higher values represent greater tissue contrast. A general linear model, adjusting for APOE-status, scanner type, hippocampal volume, and cortical thickness, revealed that converters evidenced lower GWR values than non-converters (i.e., more degradation in tissue contrast; p = 0.03). Individuals with MCI who convert to dementia have lower baseline GWR values than individuals who remain diagnostically stable over a 3-year period, statistically independent of cortical thickness or hippocampal volume.

Ex vivo magnetic resonance imaging in South African manganese mine workers

BACKGROUND

Manganese (Mn) exposure is associated with increased T1-weighted magnetic resonance imaging (MRI) signal in the basal ganglia. T1 signal intensity has been correlated with occupational Mn exposure but not with clinical symptomatology or neuropathology.

OBJECTIVES

This study investigated predictors of ex vivo T1 MRI basal ganglia signal intensity in neuropathologic tissue obtained from deceased South African mine workers.

METHODS

A 3.0 T MRI was performed on ex vivo brain tissue obtained from 19 Mn mine workers and 10 race- and sex-matched mine workers of other commodities. Basal ganglia regions of interest were identified for each subject with T1-weighted intensity indices generated for each region. In a pathology subset, regional T1 indices were compared to neuronal and glial cell density and tissue metal concentrations.

RESULTS

Intensity indices were higher in Mn mine workers than non-Mn mine workers for the globus pallidus, caudate, anterior putamen, and posterior putamen with the highest values in subjects with the longest cumulative Mn exposure. Intensity indices were inversely correlated with the neuronal cell density in the caudate (p=0.040) and putamen (p=0.050). Tissue Mn concentrations were similar in Mn and non-Mn mine workers. Tissue iron (Fe) concentration trended lower across all regions in Mn mine workers.

CONCLUSIONS

Mn mine workers demonstrated elevated basal ganglia T1 indices when compared to non-Mn mine workers. Predictors of ex vivo T1 MRI signal intensity in Mn mine workers include duration of Mn exposure and neuronal density.

MPnRAGE: A technique to simultaneously acquire hundreds of differently contrasted MPRAGE images with applications to quantitative T1 mapping

PURPOSE

To introduce a new technique called MPnRAGE, which produces hundreds of images with different T1 contrasts and a B1 corrected T1 map.

THEORY AND METHODS

An interleaved three-dimensional radial k-space trajectory with a sliding window reconstruction is used in conjunction with magnetization preparation pulses. This work modifies the SNAPSHOT-FLASH T1 fitting equations for radial imaging with view-sharing and develops a new rapid B1 correction procedure. MPnRAGE is demonstrated in phantoms and volunteers, including two volunteers with eight scans each and eight volunteers with two scans each. T1 values from MPnRAGE were compared with those from fast spin echo inversion recovery (FSE-IR) in phantoms and a healthy human brain at 3 Tesla (T).

RESULTS

The T1 fit for human white and gray matter was T1MPnRAGE = 1.00 · T1FSE-IR + 24 ms, r(2) = 0.990. Voxel-wise coefficient of variation in T1 measurements across eight time points was between 0.02 and 0.08. Region of interest-based T1 values were reproducible to within 2% and agree well with literature values.

CONCLUSION

In the same amount of time as a traditional MPRAGE exam (7.5 min), MPnRAGE was shown to produce hundreds of images with alternate T1 contrasts as well as an accurate and reproducible T1 map that is robust to B1 errors.

Comparison of grey matter volume and thickness for analysing cortical changes in chronic schizophrenia: a matter of surface area, grey/white matter intensity contrast, and curvature

Grey matter volume and cortical thickness are the two most widely used measures for detecting grey matter morphometric changes in various diseases such as schizophrenia. However, these two measures only share partial overlapping regions in identifying morphometric changes. Few studies have investigated the contributions of the potential factors to the differences of grey matter volume and cortical thickness. To investigate this question, 3T magnetic resonance images from 22 patients with schizophrenia and 20 well-matched healthy controls were chosen for analyses. Grey matter volume and cortical thickness were measured by VBM and Freesurfer. Grey matter volume results were then rendered onto the surface template of Freesurfer to compare the differences from cortical thickness in anatomical locations. Discrepancy regions of the grey matter volume and thickness where grey matter volume significantly decreased but without corresponding evidence of cortical thinning involved the rostral middle frontal, precentral, lateral occipital and superior frontal gyri. Subsequent region-of-interest analysis demonstrated that changes in surface area, grey/white matter intensity contrast and curvature accounted for the discrepancies. Our results suggest that the differences between grey matter volume and thickness could be jointly driven by surface area, grey/white matter intensity contrast and curvature.

Brain structure across the lifespan: the influence of stress and mood

Normal brain aging is an inevitable and heterogeneous process characterized by a selective pattern of structural changes. Such heterogeneity arises as a consequence of cumulative effects over the lifespan, including stress and mood effects, which drive different micro- and macro-structural alterations in the brain. Investigating these differences in healthy age-related changes is a major challenge for the comprehension of the cognitive status. Herein we addressed the impact of normal aging, stress, mood, and their interplay in the brain gray and white matter (WM) structure. We showed the critical impact of age in the WM volume and how stress and mood influence brain volumetry across the lifespan. Moreover, we found a more profound effect of the interaction of aging/stress/mood on structures located in the left hemisphere. These findings help to clarify some divergent results associated with the aging decline and to enlighten the association between abnormal volumetric alterations and several states that may lead to psychiatric disorders.

Adiposity is associated with structural properties of the adolescent brain

Obesity, a major risk factor for cardiometabolic disease, is associated with variations in a number of structural properties in the adult brain, as assessed with magnetic resonance imaging (MRI). In this study, we investigated the cross-sectional relationship between visceral fat (VF), total body fat (TBF) and three MRI parameters in the brains of typically developing adolescents: (i) T1-weighted (T1W) signal intensity; (ii) T1W signal contrast between white matter (WM) and gray matter (GM); and (iii) magnetization transfer ratio (MTR). In a community-based sample of 970 adolescents (12-18 years old, 466 males), VF was quantified using MRI, and total body fat was measured using a multifrequency bioimpedance. T1W images of the brain were used to determine signal intensity in lobar GM and WM, as well as WM:GM signal contrast. A magnetization transfer (MT) sequence of MT(ON) and MT(OFF) was used to obtain MTR in GM and WM. We found that both larger volumes of VF and more TBF were independently associated with higher signal intensity in WM and higher WM:GM signal contrast, as well as higher MTR in both GM and WM. These relationships were independent of a number of potential confounders, including age, sex, puberty stage, household income and height. Our results suggest that both visceral fat and fat deposited elsewhere in the body are associated independently with structural properties of the adolescent brain. We speculate that these relationships suggest the presence of adiposity-related variations in phospholipid composition of brain lipids.

Decreased Default Mode Network connectivity correlates with age-associated structural and cognitive changes

Ageing entails cognitive and motor decline as well as brain changes such as loss of gray (GM) and white matter (WM) integrity, neurovascular and functional connectivity alterations. Regarding connectivity, reduced resting-state fMRI connectivity between anterior and posterior nodes of the Default Mode Network (DMN) relates to cognitive function and has been postulated to be a hallmark of ageing. However, the relationship between age-related connectivity changes and other neuroimaging-based measures in ageing is fragmentarily investigated. In a sample of 116 healthy elders we aimed to study the relationship between antero-posterior DMN connectivity and measures of WM integrity, GM integrity and cerebral blood flow (CBF), assessed with an arterial spin labeling sequence. First, we replicated previous findings demonstrating DMN connectivity decreases in ageing and an association between antero-posterior DMN connectivity and memory scores. The results showed that the functional connectivity between posterior midline structures and the medial prefrontal cortex was related to measures of WM and GM integrity but not to CBF. Gray and WM correlates of anterio-posterior DMN connectivity included, but were not limited to, DMN areas and cingulum bundle. These results resembled patterns of age-related vulnerability which was studied by comparing the correlates of antero-posterior DMN with age-effect maps. These age-effect maps were obtained after performing an independent analysis with a second sample including both young and old subjects. We argue that antero-posterior connectivity might be a sensitive measure of brain ageing over the brain. By using a comprehensive approach, the results provide valuable knowledge that may shed further light on DMN connectivity dysfunctions in ageing.

Magnetization-prepared rapid acquisition with gradient echo magnetic resonance imaging signal and texture features for the prediction of mild cognitive impairment to Alzheimer's disease progression

Early diagnoses of Alzheimer's disease (AD) would confer many benefits. Several biomarkers have been proposed to achieve such a task, where features extracted from magnetic resonance imaging (MRI) have played an important role. However, studies have focused exclusively on morphological characteristics. This study aims to determine whether features relating to the signal and texture of the image could predict mild cognitive impairment (MCI) to AD progression. Clinical, biological, and positron emission tomography information and MRI images of 62 subjects from the AD neuroimaging initiative were used in this study, extracting 4150 features from each MRI. Within this multimodal database, a feature selection algorithm was used to obtain an accurate and small logistic regression model, generated by a methodology that yielded a mean blind test accuracy of 0.79. This model included six features, five of them obtained from the MRI images, and one obtained from genotyping. A risk analysis divided the subjects into low-risk and high-risk groups according to a prognostic index. The groups were statistically different ([Formula: see text]). These results demonstrated that MRI features related to both signal and texture add MCI to AD predictive power, and supported the ongoing notion that multimodal biomarkers outperform single-modality ones.

An automated tool for cortical feature analysis: Application to differences on 7 Tesla T2* -weighted images between young and older healthy subjects

PURPOSE

High field T₂^* -weighted MR images of the cerebral cortex are increasingly used to study tissue susceptibility changes related to aging or pathologies. This paper presents a novel automated method for the computation of quantitative cortical measures and group-wise comparison using 7 Tesla T₂^* -weighted magnitude and phase images.

METHODS

The cerebral cortex was segmented using a combination of T₂^* -weighted magnitude and phase information and subsequently was parcellated based on an anatomical atlas. Local gray matter (GM)/white matter (WM) contrast and cortical profiles, which depict the magnitude or phase variation across the cortex, were computed from the magnitude and phase images in each parcellated region and further used for group-wise comparison. Differences in local GM/WM contrast were assessed using linear regression analysis. Regional cortical profiles were compared both globally and locally using permutation testing. The method was applied to compare a group of 10 young volunteers with a group of 15 older subjects.

RESULTS

Using local GM/WM contrast, significant differences were revealed in at least 13 of 17 studied regions. Highly significant differences between cortical profiles were shown in all regions.

CONCLUSION

The proposed method can be a useful tool for studying cortical changes in normal aging and potentially in neurodegenerative diseases. Magn Reson Med 74:240-248, 2015. © 2014 Wiley Periodicals, Inc.

Impact of brain aging and neurodegeneration on cognition: evidence from MRI

PURPOSE OF REVIEW

We present an overview of recent concepts in mechanisms underlying cognitive decline associated with brain aging and neurodegeneration from the perspective of MRI.

RECENT FINDINGS

Recent findings challenge the established link between neuroimaging biomarkers of neurodegeneration and age-related or disease-related cognitive decline. Amyloid burden, white matter hyperintensities and local patterns of brain atrophy seem to have differential impact on cognition, particularly on episodic and working memory - the most vulnerable domains in 'normal aging' and Alzheimer's disease. Studies suggesting that imaging biomarkers of neurodegeneration are independent of amyloid-β give rise to new hypothesis regarding the pathological cascade in Alzheimer's disease. Findings in patients with autosomal-dominant Alzheimer's disease confirm the notion of differential temporal trajectory of amyloid deposition and brain atrophy to add another layer of complexity on the basic mechanisms of cognitive aging and neurodegeneration. Finally, the concept of cognitive reserve in 'supernormal aging' is questioned by evidence for the preservation of neurochemical, structural and functional brain integrity in old age rather than recruitment of 'reserves' for maintaining cognitive abilities.

SUMMARY

Recent advances in clinical neuroscience, brain imaging and genetics challenge pathophysiological hypothesis of neurodegeneration and cognitive aging dominating the field in the last decade and call for reconsidering the choice of therapeutic window for early intervention.

Computational anatomy for studying use-dependant brain plasticity

In this article we provide a comprehensive literature review on the in vivo assessment of use-dependant brain structure changes in humans using magnetic resonance imaging (MRI) and computational anatomy. We highlight the recent findings in this field that allow the uncovering of the basic principles behind brain plasticity in light of the existing theoretical models at various scales of observation. Given the current lack of in-depth understanding of the neurobiological basis of brain structure changes we emphasize the necessity of a paradigm shift in the investigation and interpretation of use-dependent brain plasticity. Novel quantitative MRI acquisition techniques provide access to brain tissue microstructural properties (e.g., myelin, iron, and water content) in-vivo, thereby allowing unprecedented specific insights into the mechanisms underlying brain plasticity. These quantitative MRI techniques require novel methods for image processing and analysis of longitudinal data allowing for straightforward interpretation and causality inferences.

Effect of intrinsic and extrinsic factors on global and regional cortical thickness

Global and regional cortical thicknesses based on T1-weighted magnetic resonance images acquired at 1.5 T and 3 T were measured on a relatively large cohort of 295 subjects using FreeSurfer software. Multivariate regression analysis was performed using Pillai's trace test to determine significant differences in cortical thicknesses measured at these two field strengths. Our results indicate that global cortical thickness is not affected by the field strength or gender. In contrast, the regional cortical thickness was observed to be field dependent. Specifically, the cortical thickness in regions such as parahippocampal, superior temporal, precentral and posterior cingulate is thicker at 3 T than at 1.5 T. In contrast regions such as cuneus and pericalcarine showed higher cortical thickness at 1.5 T than at 3 T. These differences appear to be age-dependent. The differences in regional cortical thickness between field strengths were similar in both genders. Further, male vs. female differences in regional cortical thickness were observed only at 1.5 T and not at 3 T. Our results indicate that magnetic field strength has a significant effect on the estimation of regional, but not global, cortical thickness. In addition, the pulse sequence, scanner type, and spatial resolution do not appear to have significant effect on the measured cortical thickness.

Effects of insulin resistance on white matter microstructure in middle-aged and older adults

OBJECTIVE

To investigate the potential relationship between insulin resistance (IR) and white matter (WM) microstructure using diffusion tensor imaging in cognitively healthy middle-aged and older adults.

METHODS

Diffusion tensor imaging was acquired from 127 individuals (age range 41-86 years). IR was evaluated by the homeostasis model assessment of IR (HOMA-IR). Participants were divided into 2 groups based on HOMA-IR values: "high HOMA-IR" (≥2.5, n = 27) and "low HOMA-IR" (<2.5, n = 100). Cross-sectional voxel-based comparisons were performed using Tract-Based Spatial Statistics and anatomically defined regions of interest analysis.

RESULTS

The high HOMA-IR group demonstrated decreased axial diffusivity broadly throughout the cerebral WM in areas such as the corpus callosum, corona radiata, cerebral peduncle, posterior thalamic radiation, and right superior longitudinal fasciculus, and WM underlying the frontal, parietal, and temporal lobes, as well as decreased fractional anisotropy in the body and genu of corpus callosum and parts of the superior and anterior corona radiata, compared with the low HOMA-IR group, independent of age, WM signal abnormality volume, and antihypertensive medication status. These regions additionally demonstrated linear associations between diffusion measures and HOMA-IR across all subjects, with higher HOMA-IR values being correlated with lower axial diffusivity.

CONCLUSIONS

In generally healthy adults, greater IR is associated with alterations in WM tissue integrity. These cross-sectional findings suggest that IR contributes to WM microstructural alterations in middle-aged and older adults.

Quantitative comparison of cortical surface reconstructions from MP2RAGE and multi-echo MPRAGE data at 3 and 7 T

The Magnetization-Prepared 2 Rapid Acquisition Gradient Echo (MP2RAGE) method achieves spatially uniform contrast across the entire brain between gray matter and surrounding white matter tissue and cerebrospinal fluid by rapidly acquiring data at two points during an inversion recovery, and then combining the two volumes so as to cancel out sources of intensity and contrast bias, making it useful for neuroimaging studies at ultrahigh field strengths (≥7T). To quantify the effectiveness of the MP2RAGE method for quantitative morphometric neuroimaging, we performed tissue segmentation and cerebral cortical surface reconstruction of the MP2RAGE data and compared the results with those generated from conventional multi-echo MPRAGE (MEMPRAGE) data across a group of healthy subjects. To do so, we developed a preprocessing scheme for the MP2RAGE image data to allow for automatic cortical segmentation and surface reconstruction using FreeSurfer and analysis methods to compare the positioning of the surface meshes. Using image volumes with 1mm isotropic voxels we found a scan-rescan reproducibility of cortical thickness estimates to be 0.15 mm (or 6%) for the MEMPRAGE data and a slightly lower reproducibility of 0.19 mm (or 8%) for the MP2RAGE data. We also found that the thickness estimates were systematically smaller in the MP2RAGE data, and that both the interior and exterior cortical boundaries estimated from the MP2RAGE data were consistently positioned within the corresponding boundaries estimated from the MEMPRAGE data. Therefore several measureable differences exist in the appearance of cortical gray matter and its effect on automatic segmentation methods that must be considered when choosing an acquisition or segmentation method for studies requiring cortical surface reconstructions. We propose potential extensions to the MP2RAGE method that may help to reduce or eliminate these discrepancies.

It is unclear if adjusting cortical thickness for changes in gray/white matter intensity ratio improves discrimination between normal aging, MCI, and AD

The contrast between gray and white matter in MRI is critical for accurately measuring cortical thickness. The gray/white matter intensity ratio (GWIR) has been proposed to be an important adjustment factor for cortical thickness measures in Alzheimer's disease (AD) and mild cognitive impairment (MCI). This study examined the GWIR and its influence on cortical thickness in normal aging, mild cognitive impairment (MCI), and AD. The ability for GWIR to discriminate between these groups was assessed on its own and as an adjustment factor for cortical thickness. Minimal age- and AD-related changes in GWIR were observed. GWIR was not able to differentiate between normal aging, MCI, and AD. However, adjusting cortical thickness for GWIR slightly improved the ability to discriminate between groups and the effect size of cortical thickness increased after adjusting for GWIR. This work demonstrates the ambiguity in adjusting cortical thickness measures for GWIR, particularly when attempting to discriminate between normal aging, MCI, and AD groups.

Cortical Thickness Changes Associated with Photoparoxysmal Response

Photoparoxysmal response (PPR) is an EEG trait of spike and spike-wave discharges in response to photic stimulation that is closely linked to idiopathic generalized epilepsy (IGE). In our previous studies we showed that PPR is associated with functional alterations in the occipital and frontal cortices. The aim of the present study was to determine structural changes associated with PPR. For this purpose we analysed the cortical thickness as derived from T1 MRI images in PPR-positive-subjects (n = 12; 15.5 ± 8.6 years; 4 males), PPR-positive-IGE-patients (n = 12; 14.9 ± 2.7 years; 4 males) and compared these groups with a group of PPR-negative-healthy-controls (HC, n = 17; 15.3 ± 3.6 years; 6 males). Our results revealed an increase of cortical thickness in the occipital, frontal and parietal cortices bilaterally in PPR-positive-subjects in comparison to HC. Moreover PPR-positive-subjects presented a significant decrease of cortical thickness in the temporal cortex in the same group contrast. IGE patients exhibited lower cortical thickness in the temporal lobe bilaterally and in the right paracentral region in comparison to PPR-positive-subjects. Our study demonstrates structural changes in the occipital lobe, frontoparietal regions and temporal lobe, which also show functional changes associated with PPR. Patients with epilepsy present changes in the temporal lobe and supplementary motor area.

Intracortical myelin links with performance variability across the human lifespan: results from T1- and T2-weighted MRI myelin mapping and diffusion tensor imaging

Cerebral myelin maturation and aging-related degradation constitute fundamental features of human brain integrity and functioning. Although mostly studied in the white matter, the cerebral cortex contains significant amounts of myelinated axons. However, how intracortical myelin content evolves during development, decays in aging, and links with cognition remain poorly understood. Several studies have shown the potential of mapping myelin in the cortex by use of T1-weighted (T1w) and T2-weighted (T2w) magnetic resonance imaging signal intensity, which show inverse sensitivity to myelin. Here, we characterized cortical myelin in 339 participants 8-83 years of age using a recently introduced T1w/T2w ratio myelin mapping technique and mean diffusivity (MD) from diffusion tensor imaging. To test for cognitive correlates, we used intraindividual variability (IIV) in performance during a speeded task, a measure recently associated with white matter integrity. The results showed that intracortical myelin maturation was ongoing until the late 30s, followed by 20 relative stable years before declining from the late 50s. For MD, U-shaped paths showing similar patterns were observed, but with fewer maturational effects in some regions. IIV was correlated with both T1w/T2w ratio and MD, mainly indicating that the higher degree of intracortical myelin is associated with greater performance stability. The relations were more prominent with advancing age, suggesting that aging-related cortical demyelination contributes to increased IIV. The T1w/T2w ratio myelin-mapping technique thus seems sensitive to intracortical myelin content in normal development and aging, relates to cognitive functioning, and might constitute an important future tool in mapping normal and clinical brain changes.

Decreased T1 contrast between gray matter and normal-appearing white matter in CADASIL

BACKGROUND AND PURPOSE

CADASIL is the most frequent hereditary small-vessel disease of the brain. The clinical impact of various MR imaging markers has been repeatedly studied in this disorder, but alterations of contrast between gray matter and normal-appearing white matter remain unknown. The aim of this study was to evaluate the contrast alterations between gray matter and normal-appearing white matter on T1-weighted images in patients with CADASIL compared with healthy subjects.

MATERIALS AND METHODS

Contrast between gray matter and normal-appearing white matter was assessed by using histogram analyses of 3D T1 high-resolution MR imaging in 23 patients with CADASIL at the initial stage of the disease (Mini-Mental State Examination score > 24 and modified Rankin scale score ≤ 1; mean age, 53.5 ± 11.1 years) and 30 age- and sex-matched controls.

RESULTS

T1 contrast between gray matter and normal-appearing white matter was significantly reduced in patients compared with age- and sex-matched controls (patients: 1.35 ± 0.08 versus controls: 1.43 ± 0.04, P < 10(-5)). This reduction was mainly driven by a signal decrease in normal-appearing white matter. Contrast loss was strongly related to the volume of white matter hyperintensities.

CONCLUSIONS

Conventional 3D T1 imaging shows significant loss of contrast between gray matter and normal-appearing white matter in CADASIL. This probably reflects tissue changes in normal-appearing white matter outside signal abnormalities on T2 or FLAIR sequences. These contrast alterations should be taken into account for image interpretation and postprocessing.

Genetic associations between intelligence and cortical thickness emerge at the start of puberty

Cognitive abilities are related to (changes in) brain structure during adolescence and adulthood. Previous studies suggest that associations between cortical thickness and intelligence may be different at different ages. As both intelligence and cortical thickness are heritable traits, the question arises whether the association between cortical thickness development and intelligence is due to genes influencing both traits. We study this association in a longitudinal sample of young twins. Intelligence was assessed by standard IQ tests at age 9 in 224 twins, 190 of whom also underwent structural magnetic resonance imaging (MRI). Three years later at age 12, 177/125 twins returned for a follow-up measurement of intelligence/MRI scanning, respectively. We investigated whether cortical thickness was associated with intelligence and if so, whether this association was driven by genes. At age 9, there were no associations between cortical thickness and intelligence. At age 12, a negative relationship emerged. This association was mainly driven by verbal intelligence, and manifested itself most prominently in the left hemisphere. Cortical thickness and intelligence were explained by the same genes. As a post hoc analysis, we tested whether a specific allele (rs6265; Val66Met in the BDNF gene) contributed to this association. Met carriers showed lower intelligence and a thicker cortex, but only the association between the BDNF genotype and cortical thickness in the left superior parietal gyrus reached significance. In conclusion, it seems that brain areas contributing to (verbal) intellectual performance are specializing under the influence of genes around the onset of puberty.

Impact of aging brain circuits on cognition

Brain networks that engage the hippocampus and prefrontal cortex are central for enabling effective interactions with our environment. Some of the cognitive processes that these structures mediate, such as encoding and retrieving episodic experience, wayfinding, working memory and attention are known to be altered across the lifespan. As illustrated by examples given below, there is remarkable consistency across species in the pattern of age-related neural and cognitive change observed in healthy humans and other animals. These include changes in cognitive operations that are known to be dependent on the hippocampus, as well as those requiring intact prefrontal cortical circuits. Certain cognitive constructs that reflect the function of these areas lend themselves to investigation across species, allowing brain mechanisms at different levels of analysis to be studied in greater depth.