Gyral and sulcal connectivity in the human cerebral cortex.

The rapid evolution of image acquisition and data analytic methods has established in vivo whole-brain tractography as a routine technology over the last 20 years. Imaging-based methods provide an additional approach to classic neuroanatomical studies focusing on biomechanical principles of anatomical organization and can in turn overcome the complexity of inter-individual variability associated with histological and tractography studies. In this work we propose a novel, reliable framework for determining brain tracts resolving the anatomical variance of brain regions. We distinguished 4 region types based on anatomical considerations: (i) gyral regions at borders between cortical communities; (ii) gyral regions within communities; (iii) sulcal regions at invariant locations across subjects; and (iv) other sulcal regions. Region types showed strikingly different anatomical and connection properties. Results allowed complementing the current understanding of the brain's communication structure with a model of its anatomical underpinnings.

Heritability of Structural Patterning in the Human Cerebral Cortex.

Genetic influences that govern the spatial patterning of the human cortex and its structural variability are still incompletely known. We analyzed structural MR images in twins, siblings, and pairs of unrelated subjects. A comprehensive set of methods was employed to quantify properties of cortical features at different spatial scales. Measures were used to assess the influence of genetic similarity on structural patterning. Results indicated that: (1) Genetic effects significantly influence all structural features assessed here at all spatial resolutions, albeit at different strengths. (2) While strong genetic effects were found at the whole-brain and hemisphere level, effects were weaker at the regional and vertex level, depending on the measure under study. (3) Besides cortical thickness, sulcal (geodesic) depth was found to be under strong genetic control. The local pattern indicated that two axes along (a) the anterior-posterior direction (insula to parieto-occipital sulcus), and (b) superior-inferior direction (central sulcus to callosal sulcus) presumably determine the segregation of four quadrants in each hemisphere early in development. (4) While strong structural asymmetries were found at the regional level, genetic influences on laterality were relatively minor.

Determinants of structural segregation and patterning in the human cortex.

This study aimed at uncovering mechanisms that govern the spatio-temporal patterning of the human cortex and its structural variability, and drawing links between fetal brain development and variability in adult brains. A data-driven analytic approach based on structural MR images revealed the following findings: (1) The cortical surface can be subdivided into 13 independent regions ("communities") based on macroscopic features. (2) Thirty centers of low inter-subject variability were found in major sulci on the cortical surface. Their variability showed a strong positive correlation with the known time points at which they appear in fetal development. Centers forming early induce a higher inter-subject regularity in a larger local vicinity, while those forming later result in smaller regions of higher variability. (3) The layout of sulcal and gyral patterns within a community is governed typically by two centers. Depending on the relative variability of each center, communities can be classified into structural sub-types. (4) Sub-types across ipsi-lateral communities are independent, but associated with the sub-type of the same community on the contra-lateral side. Results shown here integrate well with current knowledge about macroscopic, microscopic, and genetic determinants of brain development.

The macro-structural variability of the human neocortex.

The human neocortex shows a considerable individual structural variability. While primary gyri and sulci are found in all normally developed brains and bear clear-cut gross structural descriptions, secondary structures are highly variable and not present in all brains. The blend of common and individual structures poses challenges when comparing structural and functional results from quantitative neuroimaging studies across individuals, and sets limits on the precision of location information much above the spatial resolution of current neuroimaging methods. This work aimed at quantifying structural variability on the neocortex, and at assessing the spatial relationship between regions common to all brains and their individual structural variants. Based on structural MRI data provided as the "900 Subjects Release" of the Human Connectome Project, a data-driven analytic approach was employed here from which the definition of seven cortical "communities" emerged. Apparently, these communities comprise common regions of structural features, while the individual variability is confined within a community. Similarities between the community structure and the state of the brain development at gestation week 32 lead suggest that communities are segregated early. Subdividing the neocortex into communities is suggested as anatomically more meaningful than the traditional lobar structure.

Quantitative mapping of the per-axon diffusion coefficients in brain white matter.

PURPOSE: This article presents a simple method for estimating the effective diffusion coefficients parallel and perpendicular to the axons unconfounded by the intravoxel fiber orientation distribution. We also call these parameters the per-axon or microscopic diffusion coefficients. THEORY AND METHODS: Diffusion MR imaging is used to probe the underlying tissue material. The key observation is that for a fixed b-value the spherical mean of the diffusion signal over the gradient directions does not depend on the axon orientation distribution. By exploiting this invariance property, we propose a simple, fast, and robust estimator of the per-axon diffusion coefficients, which we refer to as the spherical mean technique. RESULTS: We demonstrate quantitative maps of the axon-scale diffusion process, which has factored out the effects due to fiber dispersion and crossing, in human brain white matter. These microscopic diffusion coefficients are estimated in vivo using a widely available off-the-shelf pulse sequence featuring multiple b-shells and high-angular gradient resolution. CONCLUSION: The estimation of the per-axon diffusion coefficients is essential for the accurate recovery of the fiber orientation distribution. In addition, the spherical mean technique enables us to discriminate microscopic tissue features from fiber dispersion, which potentially improves the sensitivity and/or specificity to various neurological conditions. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc.

Empirical derivation of the reference region for computing diagnostic sensitive ¹8fluorodeoxyglucose ratios in Alzheimer's disease based on the ADNI sample.

Careful selection of the reference region for non-quantitative positron emission tomography (PET) analyses is critically important for Region of Interest (ROI) data analyses. We introduce an empirical method of deriving the most suitable reference region for computing neurodegeneration sensitive (18)fluorodeoxyglucose (FDG) PET ratios based on the dataset collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. Candidate reference regions are selected based on a heat map of the difference in coefficients of variation (COVs) of FDG ratios over time for each of the Automatic Anatomical Labeling (AAL) atlas regions normalized by all other AAL regions. Visual inspection of the heat map suggests that the portion of the cerebellum and vermis superior to the horizontal fissure is the most sensitive reference region. Analyses of FDG ratio data show increases in significance on the order of ten-fold when using the superior portion of the cerebellum as compared with the traditionally used full cerebellum. The approach to reference region selection in this paper can be generalized to other radiopharmaceuticals and radioligands as well as to other disorders where brain changes over time are hypothesized and longitudinal data is available. Based on the empirical evidence presented in this study, we demonstrate the usefulness of the COV heat map method and conclude that intensity normalization based on the superior portion of the cerebellum may be most sensitive to measuring change when performing longitudinal analyses of FDG-PET ratios as well as group comparisons in Alzheimer's disease. This article is part of a Special Issue entitled: Imaging Brain Aging and Neurodegenerative disease.

Analyzing the cortical fine structure as revealed by ex-vivo anatomical MRI.

The human cortex has a rich fiber structure as revealed by myelin-staining of histological slices. Myelin also contributes to the image contrast in Magnetic Resonance Imaging (MRI). Recent advances in Magnetic Resonance (MR) scanner and imaging technology allowed the acquisition of an ex-vivo data set at an isotropic resolution of 100 µm. This study focused on a computational analysis of this data set with the aim of bridging between histological knowledge and MRI-based results. This work highlights: (1) the design and implementation of a processing chain that extracts intracortical features from a high-resolution MR image; (2) a demonstration of the correspondence between MRI-based cortical intensity profiles and the myelo-architectonic layering of the cortex; (3) the characterization and classification of four basic myelo-architectonic profile types; (4) the distinction of cortical regions based on myelo-architectonic features; and (5) the segmentation of cortical modules in the entorhinal cortex.

Behavioral and neuroanatomical investigation of Highly Superior Autobiographical Memory (HSAM).

A single case study recently documented one woman's ability to recall accurately vast amounts of autobiographical information, spanning most of her lifetime, without the use of practiced mnemonics (Parker, Cahill, & McGaugh, 2006). The current study reports findings based on eleven participants expressing this same memory ability, now referred to as Highly Superior Autobiographical Memory (HSAM). Participants were identified and subsequently characterized based on screening for memory of public events. They were then tested for personal autobiographical memories as well as for memory assessed by laboratory memory tests. Additionally, whole-brain structural MRI scans were obtained. Results indicated that HSAM participants performed significantly better at recalling public as well as personal autobiographical events as well as the days and dates on which these events occurred. However, their performance was comparable to age- and sex-matched controls on most standard laboratory memory tests. Neuroanatomical results identified nine structures as being morphologically different from those of control participants. The study of HSAM may provide new insights into the neurobiology of autobiographical memory.

Impact of scanner hardware and imaging protocol on image quality and compartment volume precision in the ADNI cohort.

Morphometry of brain structures based on magnetic resonance imaging (MRI) data has become an important tool in neurobiology. Recent multicenter studies in neurodegenerative diseases raised the issue of the precision of volumetric measures, and their dependence on the scanner properties and imaging protocol. A large dataset consisting of 1073 MRI examinations in 843 subjects, acquired on 90 scanners at 58 sites, is analyzed here. A comprehensive set of image quality and content measures is used to describe the influence of the scanner hardware and imaging protocol on the variability of morphometric measures. Scanners equipped with array coils show a remarkable advantage over conventional coils in terms of image quality measures. The signal- and contrast-to-noise ratio in similar systems is equal or slightly better at 1.5 T than 3.0 T, while the white/grey matter tissue contrast is generally better on high-field systems. Repeated MRI investigations on the same scanner were available in 41 subjects, on different scanners in 172 subjects. The retest reliability of repeated volumetric measures under the same conditions was found as sufficient to track changes in longitudinal examinations in individual subjects. Using different acquisition conditions in the same subject, however, the variance of volumetric measures was up to 10 times greater. Two likely factors explaining this finding are scanner-dependent geometrical inaccuracies and differences in the white/grey matter tissue contrast.

Effects of advanced aging on the neural correlates of successful recognition memory.

Functional neuroimaging studies have reported that the neural correlates of retrieval success (old>new effects) are larger and more widespread in older than in young adults. In the present study we investigated whether this pattern of age-related 'over-recruitment' continues into advanced age. Using functional magnetic resonance imaging (fMRI), retrieval-related activity from two groups (N=18 per group) of older adults aged 84-96 years ('old-old') and 64-77 years ('young-old') was contrasted. Subjects studied a series of pictures, half of which were presented once, and half twice. At test, subjects indicated whether each presented picture was old or new. Recognition performance of the old-old subjects for twice-studied items was equivalent to that of the young-old subjects for once-studied items. Old>new effects common to the two groups were identified in several cortical regions, including medial and lateral parietal and prefrontal cortex. There were no regions where these effects were of greater magnitude in the old-old group, and thus no evidence of over-recruitment in this group relative to the young-old individuals. In one region of medial parietal cortex, effects were greater (and only significant) in the young-old group. The failure to find evidence of over-recruitment in the old-old subjects relative to the young-old group, despite their markedly poorer cognitive performance, suggests that age-related over-recruitment effects plateau in advanced age. The findings for the medial parietal cortex underscore the sensitivity of this cortical region to increasing age.

A Simple Measure for Acuity in Medical Images.

An automatic and objective assessment of image quality is important in an era, where large-scale processing of imaging data from multi-center studies becomes commonplace. Based on a comprehensive statistical image model that includes noise and blur, a measure for image acuity is derived here as the ratio of the maximal gradient magnitude and the intensity difference at a boundary. Acuity may be affected by the object under study, the image acquisition, reconstruction processes, and any post-processing steps. The acuity measure presented here is post-hoc, intuitive to understand, simple to compute, and easily integrates with other standard measures of image quality. Three applications in medical imaging are included where our acuity measure is useful in the objective and automatic assessment of image quality.

Texture anisotropy of the brain's white matter as revealed by anatomical MRI.

The purpose of this work was to study specific texture properties of the brain's white matter (WM) based on conventional high-resolution T1-weighted magnetic resonance imaging (MRI) datasets. Quantitative parameters anisotropy and laminarity were derived from 3-D texture analysis. Differences in WM texture associated with gender were evaluated on an age-matched sample of 210 young healthy subjects (mean age 24.8, SD 3.97 years, 103 males and 107 females). Changes of WM texture with age were studied using 112 MRI-T1 datasets of healthy subjects aged 16 to 70 years (57 males and 55 females). Both texture measures indicated a "more regular" WM structure in females (p < 10(-6)). An age-related deterioration of WM structure manifests itself as a remarkable decline of both parameters (p < 10(-6)) that is more prominent in females (p < 10(-6)) than in males (p = 0.02). Texture analysis of anatomical MRI-T1 brain datasets provides quantitative information about macroscopic WM characteristics and helps discriminating between normal and pathological aging.

Analysis of longitudinal diffusion-weighted images in healthy and pathological aging: An ADNI study.

BACKGROUND & NEW METHOD: The widely used framework of voxel-based morphometry for analyzing neuroimages is extended here to model longitudinal imaging data by exchanging the linear model with a linear mixed-effects model. The new approach is employed for analyzing a large longitudinal sample of 756 diffusion-weighted images acquired in 177 subjects of the Alzheimer's Disease Neuroimaging initiative (ADNI). RESULTS AND COMPARISON WITH EXISTING METHODS: While sample- and group-level results from both approaches are equivalent, the mixed-effect model yields information at the single subject level. Interestingly, the neurobiological relevance of the relevant parameter at the individual level describes specific differences associated with aging. In addition, our approach highlights white matter areas that reliably discriminate between patients with Alzheimer's disease and healthy controls with a predictive power of 0.99 and include the hippocampal alveus, the para-hippocampal white matter, the white matter of the posterior cingulate, and optic tracts. In this context, notably the classifier includes a sub-population of patients with minimal cognitive impairment into the pathological domain. CONCLUSION: Our classifier offers promising features for an accessible biomarker that predicts the risk of conversion to Alzheimer's disease. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how to apply/ADNI Acknowledgement List.pdf. Significance statement This study assesses neuro-degenerative processes in the brain's white matter as revealed by diffusion-weighted imaging, in order to discriminate healthy from pathological aging in a large sample of elderly subjects. The analysis of time-series examinations in a linear mixed effects model allowed the discrimination of population-based aging processes from individual determinants. We demonstrate that a simple classifier based on white matter imaging data is able to predict the conversion to Alzheimer's disease with a high predictive power.

The brain anatomy of attention-deficit/hyperactivity disorder in young adults - a magnetic resonance imaging study.

BACKGROUND: This is one of the first studies to examine the structural brain anatomy and connectivity associated with an ADHD diagnosis and child as well as adult ADHD symptoms in young adults. It was hypothesized that an adult ADHD diagnosis and in particular childhood symptoms, are associated with widespread changes in the brain macro- and microstructure, which can be used to develop a morphometric biomarker for ADHD. METHODS: Voxel-wise linear regression models were used to examine structural and diffusion-weighted MRI data in 72 participants (31 young adults with ADHD and 41 controls without ADHD) in relation to diagnosis and the number of self-reported child and adult symptoms. RESULTS: Findings revealed significant associations between ADHD diagnosis and widespread changes to the maturation of white matter fiber bundles and gray matter density in the brain, such as structural shape changes (incomplete maturation) of the middle and superior temporal gyrus, and fronto-basal portions of both frontal lobes. ADHD symptoms in childhood showed the strongest association with brain macro- and microstructural abnormalities. At the brain circuitry level, the superior longitudinal fasciculus (SLF) and cortico-limbic areas are dysfunctional in individuals with ADHD. The morphometric findings predicted an ADHD diagnosis correctly up to 83% of all cases. CONCLUSION: An adult ADHD diagnosis and in particular childhood symptoms are associated with widespread micro- and macrostructural changes. The SLF and cortico-limbic findings suggest complex audio-visual, motivational, and emotional dysfunctions associated with ADHD in young adults. The sensitivity of the morphometric findings in predicting an ADHD diagnosis was sufficient, which indicates that MRI-based assessments are a promising strategy for the development of a biomarker.

A novel maturation index based on neonatal diffusion tensor imaging reflects typical perinatal white matter development in humans.

Human birth presents an abrupt transition from intrauterine to extrauterine life. Here we introduce a novel Maturation Index (MI) that considers the relative importance of gestational age at birth and postnatal age at scan in a General Linear Model. The MI is then applied to Diffusion Tensor Imaging (DTI) in newborns for characterizing typical white matter development in neonates. DTI was performed cross-sectionally in 47 neonates (gestational age at birth=39.1±1.6 weeks [GA], postnatal age at scan=25.5±12.2days [SA]). Radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA) along 27 white matter fiber tracts were considered. The MI was used to characterize inflection in maturation at the time of birth using GLM estimated rates of change before and after birth. It is proposed that the sign (positive versus negative) of MI reflects the period of greatest maturation rate. Two general patterns emerged from the MI analysis. First, RD and AD (but not FA) had positive MI on average across the whole brain (average MIAD=0.31±0.42, average MIRD=0.22±0.34). Second, significant regions of negative MI in RD and FA (but not AD) were observed in the inferior corticospinal regions, areas known to myelinate early. Observations using the proposed method are consistent with proposed models of the white matter maturation process in which pre-myelination is described by changes in AD and RD due to oligodendrocyte proliferation while true myelination is characterized by changes in RD and FA due to myelin formation.

Quasi-real-time neurosurgery support by MRI processing via grid computing.

One problem of providing time-critical medical services over the grid is always its dependency on the Internet. It cannot be assumed that transfer ofa certain amount of data over the Internet is always achieved during a specified period. Such a requirement cannot be fulfilled by the infrastructure of the Web. There is always the risk of a network delay or even an overload. Because of this, another goal of this project is the evaluation of grid services versus the use of local services. A further point for future research related to the chain has to deal with the optimization approach for the linear registration step. Because the optimization uses the downhill simplex algorithm in a nine-dimensional search space, the number of iterations needed to find the optimum can vary dramatically. This makes linear registration the most unpredictable step of the chain in terms of execution time. It cannot be assured that the global optimum is found. Additional work has to be done in validating the registration accuracy, including the examination of the influence of intensity variations between intraoperative images as well as the influence of tumor resection and the presence of the opened skull versus the closed skull in the fluid-based registration.

Structural correlates of mild cognitive impairment.

The structural correlates of mild cognitive impairment (MCI) were examined in 105 elderly subjects whose cognitive function ranged from intact to demented, including 38 subjects with MCI. Hippocampal volumes (left and right HcV), brain volume (BV), and grey matter volume (GMV) and white matter volume (WMV) were segmented from high resolution magnetic resonance data sets and normalised to intracranial volume (ICV). Hippocampal volume reductions, but not global brain, white or grey matter atrophy, were associated with MCI. White matter lesion severity did not differ over cognitive states. In multiple logistic regression models, normalised HcV and ICV (indicating premorbid brain volume) were significant predictors of MCI versus normality. Normalised BV and ICV significantly predicted dementia versus MCI. Absolute volumetric measures of HcV and BV yielded comparable classification accuracies. Hippocampal atrophy may be the crucial step for the transition from normality to MCI. Widespread brain atrophy may be the step to determine the transition from MCI to dementia. Brain volume reserve effects appear to be involved in both of these steps.

Do quiescent arachnoid cysts alter CNS functional organization?: A fMRI and morphometric study.

OBJECTIVE: To investigate whether congenital and clinically quiescent arachnoid cysts (AC) in the left temporal fossa alter the functional organization of adjacent cortices. METHODS: fMRI mapping was applied in five right-handed asymptomatic patients to determine the functional organization of language. Moreover, morphometry was performed in each patient to gain the size of cortical surface areas and cortical thickness values in the neighboring brain adjacent to the AC and explicitly in the left opercular region. RESULTS: Four patients showed a clear left hemisphere language dominance regardless of the cyst size; a mixed laterality of language organization was found in the remaining patient. An interesting dissociation of morphometric data was assessed when comparing strongly language-related cortices in the inferior frontal gyrus with the entire neighboring cortices. Morphometry in the neighboring brain regions of the AC showed 1) overall reduced cortical surface areas and 2) a decrease in cortical thickness compared to the homologous right side. However, the surface area of the fronto-opercular region in the left inferior frontal gyrus-i.e., the pars triangularis and the pars opercularis-was larger on the left as compared to the right side. Both structures have earlier been identified to represent the morphologic substrate of language dominance in the left hemisphere. CONCLUSION: Arachnoid cysts do not disturb the normal asymmetry of hemisphere language organization despite delicate locations adjacent to the left inferior frontal gyrus.

The relationship between head size and intracranial volume in elderly subjects.

OBJECTIVE: To study the relationship between parenchymal head volume (PHV) and intracranial volume (ICV), and to compare the ability of these two measurements to reflect the association between maximum mature brain volume and late-life cognition. METHODS: An elderly sample of humans with a range of cognitive functions from normality, via mild cognitive impairment (MCI) to dementia (mean age 78.6, S.D. 2.8; mean MMSE 25.4, S.D. 4.2) was examined. Head-to-head measurements of ICV and parenchymal head volume (PHV) were obtained from three-dimensional T1 weighted magnetic resonance images using automated procedures. Analyses of cognitive functions were based on continuous and categorial variables. RESULTS: PHV explained 55% of the variance in ICV. The ratio between PHV and ICV remained constant with increasing age and cognitive impairment. Measurements of PHV and ICV yielded comparable correlations with global cognitive performance. Group differences over gender and cognitive states were equally present in ICV and PHV. The relative risks of cognitive impairment that were associated with either small ICV or PHV were comparable. CONCLUSIONS: Measures of PHV can be considered as useful estimates of ICV and cerebral volume reserve.

Computional cost of nonrigid registration algorithms based on fluid dynamics.

Though fluid dynamics offer a good approach to nonrigid registration and give accurate results, even with large-scale deformations, its application is still very time consuming. We introduce and discuss different approaches to solve the core problem of nonrigid registration, the partial differential equation of fluid dynamics. We focus on the solvers, their computional costs and the accuracy of registration. Numerical experiments show that relaxation is currently the best approach, especially when reducing the cost/iteration by focusing the updates on deformation spots.