Object-based morphometry of the cerebral cortex

Atypical sulcal anatomy in young children with autism spectrum disorder

Autism spectrum disorder is associated with an altered early brain development. However, the specific cortical structure abnormalities underlying this disorder remain largely unknown. Nonetheless, atypical cortical folding provides lingering evidence of early disruptions in neurodevelopmental processes and identifying changes in the geometry of cortical sulci is of primary interest for characterizing these structural abnormalities in autism and their evolution over the first stages of brain development. Here, we applied state-of-the-art sulcus-based morphometry methods to a large highly-selective cohort of 73 young male children of age spanning from 18 to 108 months. Moreover, such large cohort was selected through extensive behavioral assessments and stringent inclusion criteria for the group of 59 children with autism. After manual labeling of 59 different sulci in each hemisphere, we computed multiple shape descriptors for each single sulcus element, hereby separating the folding measurement into distinct factors such as the length and depth of the sulcus. We demonstrated that the central, intraparietal and frontal medial sulci showed a significant and consistent pattern of abnormalities across our different geometrical indices. We also found that autistic and control children exhibited strikingly different relationships between age and structural changes in brain morphology. Lastly, the different measures of sulcus shapes were correlated with the CARS and ADOS scores that are specific to the autistic pathology and indices of symptom severity. Inherently, these structural abnormalities are confined to regions that are functionally relevant with respect to cognitive disorders in ASD. In contrast to those previously reported in adults, it is very unlikely that these abnormalities originate from general compensatory mechanisms unrelated to the primary pathology. Rather, they most probably reflect an early disruption on developmental trajectory that could be part of the primary pathology.

•

A new single-site cohort of 73 young children (1.5–11 years) with autism and controls

•

State-of-the-art methodology used to compare geometrical attributes of sulci

•

Combination of automatic extraction of descriptors with manual identification of sulci

•

Clearly evidence localized sulcal shape abnormalities in the autism group

•

Different relationships between age and structural changes in brain morphology

Different early rearing experiences have long-term effects on cortical organization in captive chimpanzees (Pan troglodytes)

Consequences of rearing history in chimpanzees (Pan troglodytes) have been explored in relation to behavioral abnormalities and cognition; however, little is known about the effects of rearing conditions on anatomical brain development. Human studies have revealed that experiences of maltreatment and neglect during infancy and childhood can have detrimental effects on brain development and cognition. In this study, we evaluated the effects of early rearing experience on brain morphology in 92 captive chimpanzees (ages 11-43) who were either reared by their mothers (n = 46) or in a nursery (n = 46) with age-group peers. Magnetic resonance brain images were analyzed with a processing program (BrainVISA) that extracts cortical sulci. We obtained various measurements from 11 sulci located throughout the brain, as well as whole brain gyrification and white and grey matter volumes. We found that mother-reared chimpanzees have greater global white-to-grey matter volume, more cortical folding and thinner grey matter within the cortical folds than nursery-reared animals. The findings reported here are the first to demonstrate that differences in early rearing conditions have significant consequences on brain morphology in chimpanzees and suggests potential differences in the development of white matter expansion and myelination.

Advanced Image Coregistration within the Leksell Workstation for the Planning of Glioma Surgery: Initial Experience

Background Leksell GammaPlan (LGP) and SurgiPlan (ELEKTA Instruments AB, Stockholm, Sweden) may be used effectively for the detailed evaluation of regional neuroanatomy before open neurosurgical procedures. We report our initial experience in the cases of cerebral gliomas. Methods LGP v.8.3 was used before the surgical resection of cerebral gliomas for (1) the delineation of subdural grid electrodes and a detailed evaluation of their position relatively to cortical structures, and (2) for the fusion of structural magnetic resonance imaging and diffusion tensor imaging (DTI) for a detailed visualization of the corticospinal tract (CST) and optic radiation. Results Delineation of the subdural grid within LGP in a patient with seizures caused by left parietal glioma permitted a detailed assessment of the location of electrodes relative to the cortical gyri and sulci and significantly facilitated interpretation of brain mapping before tumor resection. In another patient with parieto-occipital glioma, simultaneous three-dimensional visualization of the tumor, CST, and optic radiation with the use of LGP permitted us to perform tumor resection without postoperative neurologic complications. Finally, incorporation of DTI into SurgiPlan resulted in precise planning of stereotactic biopsy for bilateral thalamic glioma. Conclusion The possibility for detailed evaluation of regional neuroanatomy based on various images within LGP and SurgiPlan may facilitate effective and safe surgical management of intracranial gliomas.

Subclinical abnormal gyration pattern, a potential anatomic marker of epileptogenic zone in patients with magnetic resonance imaging-negative frontal lobe epilepsy

BACKGROUND

Epilepsy surgery for magnetic resonance imaging (MRI)-negative patients has a less favorable outcome.

OBJECTIVE

Detection of subclinical abnormal gyration (SAG) patterns and their potential contribution to assessment of the topography of the epileptogenic zone (EZ) is addressed in MRI-negative patients with frontal lobe epilepsy.

METHODS

Between September 1998 and July 2005, 12 MRI-negative frontal lobe epilepsy patients underwent stereoelectroencephalography with postcorticectomy follow-up of longer than 1 year (average, 3.3 years). Original software (BrainVISA/Anatomist, http://brainvisa.info) trained on a database of normal volunteers was used to determine which sulci had morphology out of the normal range (SAG). Topography of the EZ, SAG pattern, corticectomy, postoperative seizure control, and histopathology were analyzed.

RESULTS

At last follow-up, 8 of 12 patients (66.7%) were Engel class I (7 IA and 1 IB), 2 class II, and 2 class IV. Small focal cortical dysplasia was histologically diagnosed in 9 of the 12 patients (75%), including 7 of 8 seizure-free patients (87.5%). A SAG pattern was found to be in the EZ area in 9 patients (75%), in the ipsilateral frontal lobe out of the EZ in 2, and limited to the contralateral hemisphere in 1.

CONCLUSION

SAG patterns appear to be associated with the topography of the EZ in MRI-negative frontal lobe epilepsy and may have a useful role in preoperative assessment. Small focal cortical dysplasia not detected with MRI is often found on histopathological examination, particularly in the depth of the posterior part of the superior frontal sulcus and intermediate frontal sulcus, suggesting a specific developmental critical zone in these locations.

Quantitative analysis of structural neuroimaging of mesial temporal lobe epilepsy

Mesial temporal lobe epilepsy (MTLE) is the most common of the surgically remediable drug-resistant epilepsies. MRI is the primary diagnostic tool to detect anatomical abnormalities and, when combined with EEG, can more accurately identify an epileptogenic lesion, which is often hippocampal sclerosis in cases of MTLE. As structural imaging technology has advanced the surgical treatment of MTLE and other lesional epilepsies, so too have the analysis techniques that are used to measure different structural attributes of the brain. These techniques, which are reviewed here and have been used chiefly in basic research of epilepsy and in studies of MTLE, have identified different types and the extent of anatomical abnormalities that can extend beyond the affected hippocampus. These results suggest that structural imaging and sophisticated imaging analysis could provide important information to identify networks capable of generating spontaneous seizures and ultimately help guide surgical therapy that improves postsurgical seizure-freedom outcomes.

Usefulness of Leksell GammaPlan for preoperative planning of brain tumor resection: delineation of the cranial nerves and fusion of the neuroimaging data, including diffusion tensor imaging

Leksell GammaPlan (LGP) software was initially designed for Gamma Knife radiosurgery, but it can be successfully applied to planning of the open neurosurgical procedures as well. We present our initial experience of delineating the cranial nerves in the vicinity of skull base tumors, combined visualization of the implanted subdural electrodes and cortical anatomy to facilitate brain mapping, and fusion of structural magnetic resonance imaging and diffusion tensor imaging performed with the use of LGP before removal of intracranial neoplasms. Such preoperative information facilitated choosing the optimal approach and general surgical strategy, and corresponded well to the intraoperative findings. Therefore, LGP may be helpful for planning open neurosurgical procedures in cases of both extraaxial and intraaxial intracranial tumors.

Larger is twistier: spectral analysis of gyrification (SPANGY) applied to adult brain size polymorphism

The description of cortical folding pattern (CFP) is challenging because of geometric complexity and inter-subject variability. On a cortical surface mesh, curvature estimation provides a good scalar proxy of CFP. The oscillations of this function can be studied using a Fourier-like analysis to produce a power spectrum representative of the spatial frequency composition of CFP. First, we introduce an original method for the SPectral ANalysis of GYrication (Spangy), which performs a spectral decomposition of the mean curvature of the grey/white interface mesh based on the Laplace-Beltrami operator eigenfunctions. Spangy produces an ordered 7 bands power spectrum of curvature (B0-B6) and provides an anatomically relevant segmentation of CFP based on local spectral composition. A spatial frequency being associated with each eigenfunction, the bandwidth design assumes frequency doubling between consecutive spectral bands. Next, we observed that the last 3 spectral bands (B4, 5 and 6) accounted for 93% of the analyzed spectral power and were associated with fold-related variations of curvature, whereas the lower frequency bands were related to global brain shape. The spectral segmentation of CFP revealed 1st, 2nd and 3rd order elements associated with B4, B5 and B6 respectively. These elements could be related to developmentally-defined primary, secondary and tertiary folds. Finally, we used allometric scaling of frequency bands power and segmentation to analyze the relationship between the spectral composition of CFP and brain size in a large adult dataset. Total folding power followed a positive allometric scaling which did not divide up proportionally between the bands: B4 contribution was constant, B5 increased like total folding power and B6 much faster. Besides, apparition of new elements of pattern with increasing size only concerned the 3rd order. Hence, we demonstrate that large brains are twistier than smaller ones because of an increased number of high spatial frequency folds, ramifications and kinks that accommodate the allometric increase of cortical surface.

Cortical sulci asymmetries in chimpanzees and macaques: a new look at an old idea

Functional and neuroanatomical asymmetries are an important characteristic of the human brain. The evolution of such specializations in the human cortex has provoked great interest in primate brain evolution. Most research on cortical sulci has revolved around linear measurements, which represent only one dimension of sulci organization. Here, we used a software program (BrainVISA) to quantify asymmetries in cortical depth and surface area from magnetic resonance images in a sample of 127 chimpanzees and 49 macaques. Population brain asymmetries were determined from 11 sulci in chimpanzees and seven sulci in macaques. Sulci were taken from the frontal, temporal, parietal, and occipital lobes. Population-level asymmetries were evident in chimpanzees for several sulci, including the fronto-orbital, superior precentral, and sylvian fissure sulci. The macaque population did not reveal significant population-level asymmetries, except for surface area of the superior temporal sulcus. The overall results are discussed within the context of the evolution of higher order cognition and motor functions.

Changes in the sulcal size associated with autism spectrum disorder revealed by sulcal morphometry

Autism spectrum disorder (ASD) is a complex, neurodevelopmental disorder with various structural abnormalities for different patient groups. Because of the heterogeneity of the disorder, several biomarkers have been suggested so far. Here, we explore the potential of sulcal surface and length as biomarkers. Three-dimensional T1-weighted images of 15 adolescents of normal intelligence with ASD and 15 age-, sex-, and intelligence quotient-matched control adolescents were analysed using Brainvisa 4.0 (http://www.brainvisa.info), which automatically extracts the cortical folds and labels them as 59 sulcal pieces. For each sulcus, the surface, length, and mean geodesic depth were computed using morphometry analysis within this software package. General linear model was conducted to compare the estimated values for the two groups, ASD and control. In the ASD group, the left insula and the right intraparietal sulcus (IPS) had significantly higher values for surface and length, respectively. Nonetheless for all sulcal pieces, the mean geodesic depth was not significantly different between the two groups. Our results suggest that sulcal surface and length can have correlation with morphological changes of cortex in ASD. Greater surface area and length in insula and IPS, respectively, may reflect greater folding. This could result in greater separation of functions with an impact upon the integrative functions of these regions.

A library of cortical morphology analysis tools to study development, aging and genetics of cerebral cortex

Sharing of analysis techniques and tools is among the main driving forces of modern neuroscience. We describe a library of tools developed to quantify global and regional differences in cortical anatomy in high resolution structural MR images. This library is distributed as a plug-in application for popular structural analysis software, BrainVisa (BV). It contains tools to measure global and regional gyrification, gray matter thickness and sulcal and gyral white matter spans. We provide a description of each tool and examples for several case studies to demonstrate their use. These examples show how the BV library was used to study cortical folding process during antenatal development and recapitulation of this process during cerebral aging. Further, the BV library was used to perform translation research in humans and non-human primates on the genetics of cerebral gyrification. This library, including source code and self-contained binaries for popular computer platforms, is available from the NIH-Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC) resource ( http://www.nitrc.org/projects/brainvisa_ext ).

Genetic analysis of cortical thickness and fractional anisotropy of water diffusion in the brain

OBJECTIVES

The thickness of the brain's cortical gray matter (GM) and the fractional anisotropy (FA) of the cerebral white matter (WM) each follow an inverted U-shape trajectory with age. The two measures are positively correlated and may be modulated by common biological mechanisms. We employed four types of genetic analyses to localize individual genes acting pleiotropically upon these phenotypes.

METHODS

Whole-brain and regional GM thickness and FA values were measured from high-resolution anatomical and diffusion tensor MR images collected from 712, Mexican American participants (438 females, age = 47.9 ± 13.2 years) recruited from 73 (9.7 ± 9.3 individuals/family) large families. The significance of the correlation between two traits was estimated using a bivariate genetic correlation analysis. Localization of chromosomal regions that jointly influenced both traits was performed using whole-genome quantitative trait loci (QTL) analysis. Gene localization was performed using SNP genotyping on Illumina 1M chip and correlation with leukocyte-based gene-expression analyses. The gene-expressions were measured using the Illumina BeadChip. These data were available for 371 subjects.

RESULTS

Significant genetic correlation was observed among GM thickness and FA values. Significant logarithm of odds (LOD ≥ 3.0) QTLs were localized within chromosome 15q22-23. More detailed localization reported no significant association (p < 5·10(-5)) for 1565 SNPs located within the QTLs. Post hoc analysis indicated that 40% of the potentially significant (p ≤ 10(-3)) SNPs were localized to the related orphan receptor alpha (RORA) and NARG2 genes. A potentially significant association was observed for the rs2456930 polymorphism reported as a significant GWAS finding in Alzheimer's disease neuroimaging initiative subjects. The expression levels for RORA and ADAM10 genes were significantly (p < 0.05) correlated with both FA and GM thickness. NARG2 expressions were significantly correlated with GM thickness (p < 0.05) but failed to show a significant correlation (p = 0.09) with FA.

DISCUSSION

This study identified a novel, significant QTL at 15q22-23. SNP correlation with gene-expression analyses indicated that RORA, NARG2, and ADAM10 jointly influence GM thickness and WM-FA values.

A robust cerebral asymmetry in the infant brain: the rightward superior temporal sulcus

In order to understand how genetic mutations might have favored language development in our species, we need a better description of the human brain at the beginning of life. As the linguistic network mainly involves the left perisylvian regions in adults, we used anatomical MRI to study the structural asymmetries of these regions in 14 preverbal infants. Our results show four significant asymmetries. First and foremost, they stress an important but little-known asymmetry: the larger depth of the right superior temporal sulcus (STS) at the base of Heschl's gyrus. Then, we characterized the early forward and upward shift of the posterior end of the right Sylvian fissure, the elongation of the left planum temporale as well as the thickening of the left Heschl's gyrus. The rightward bias of the STS is robust and large, and is not correlated with the leftward asymmetries of the planum and Heschl's gyrus, suggesting that different morphogenetic factors drive these asymmetries. As this sulcus is engaged in multiple high-level functions (e.g. language and theory of mind), and has been spotted as abnormal in several developmental disorders (e.g. schizophrenia, autism), this early rightward asymmetry should be further explored as a target for a genetic evolutionary pressure.

Diffeomorphic brain registration under exhaustive sulcal constraints

The alignment and normalization of individual brain structures is a prerequisite for group-level analyses of structural and functional neuroimaging data. The techniques currently available are either based on volume and/or surface attributes, with limited insight regarding the consistent alignment of anatomical landmarks across individuals. This article details a global, geometric approach that performs the alignment of the exhaustive sulcal imprints (cortical folding patterns) across individuals. This DIffeomorphic Sulcal-based COrtical (DISCO) technique proceeds to the automatic extraction, identification and simplification of sulcal features from T1-weighted Magnetic Resonance Image (MRI) series. These features are then used as control measures for fully-3-D diffeomorphic deformations. Quantitative and qualitative evaluations show that DISCO correctly aligns the sulcal folds and gray and white matter volumes across individuals. The comparison with a recent, iconic diffeomorphic approach (DARTEL) highlights how the absence of explicit cortical landmarks may lead to the misalignment of cortical sulci. We also feature DISCO in the automatic design of an empirical sulcal template from group data. We also demonstrate how DISCO can efficiently be combined with an image-based deformation (DARTEL) to further improve the consistency and accuracy of alignment performances. Finally, we illustrate how the optimized alignment of cortical folds across subjects improves sensitivity in the detection of functional activations in a group-level analysis of neuroimaging data.

Fractional anisotropy of cerebral white matter and thickness of cortical gray matter across the lifespan

We examined age trajectories of fractional anisotropy (FA) of cerebral white matter (WM) and thickness of cortical gray matter (GM) in 1031 healthy human subjects (aged 11-90 years). Whole-brain FA and GM thickness values followed quadratic trajectories with age but the relationship between them was linear, indicating that a putative biological mechanism may explain the non-linearity of their age trajectories. Inclusion of the FA values into the quadratic model of the whole-brain and regional GM thickness changes with age made the effect of the age(2) term no longer significant for the whole-brain GM thickness and greatly reduced its significance for regional GM thickness measurements. The phylogenetic order of cerebral myelination helped to further explain the intersubject variability in GM thickness. FA values for the early maturing WM were significantly better (p=10(-6)) at explaining variability in GM thickness in maturing (aged 11-20) subjects than FA values for the late maturing WM. The opposite trend was observed for aging subjects (aged 40-90) where FA values for the late maturing WM were better (p=10(-16)) at explaining the variability in GM thickness. We concluded that the non-linearity of the age trajectory for GM thickness, measured from T1-weighted MRI, was partially explained by the heterogeneity and the heterochronicity of the age-related changes in the microintegrity of cerebral WM. We consider these findings as the evidence that the measurements of age-related changes in GM thickness and FA are driven, in part, by a common biological mechanism, presumed to be related to changes in cerebral myelination.

Consistent sulcal parcellation of longitudinal cortical surfaces

Automated accurate and consistent sulcal parcellation of longitudinal cortical surfaces is of great importance in studying longitudinal morphological and functional changes of human brains, since longitudinal cortical changes are normally very subtle, especially in aging brains. However, applying the existing methods (which were typically developed for cortical sulcal parcellation of a single cortical surface) independently to longitudinal cortical surfaces might generate longitudinally-inconsistent results. To overcome this limitation, this paper presents a novel energy function based method for accurate and consistent sulcal parcellation of longitudinal cortical surfaces. Specifically, both spatial and temporal smoothness are imposed in the energy function to obtain consistent longitudinal sulcal parcellation results. The energy function is efficiently minimized by a graph cut method. The proposed method has been successfully applied to sulcal parcellation of both real and simulated longitudinal inner cortical surfaces of human brain MR images. Both qualitative and quantitative evaluation results demonstrate the validity of the proposed method.

In-vivo measurement of cortical morphology: means and meanings

PURPOSE OF REVIEW

Study of the variability of the cortical mantle thickness is now a key issue in neuroimaging. Here we describe a more recent trend aiming at the study of the variability of the cortical folding morphology.

RECENT FINDINGS

Computerized three-dimensional versions of gyrification index and other morphometric features dedicated to the folding patterns are modified in psychiatric syndromes and neurologic disorders. These observations provide new insights into the mechanisms involved in abnormal development or abnormal aging.

SUMMARY

Quantification of the folding morphology will contribute to the global endeavor aiming at building biomarkers from neuroimaging data, with a specific focus on developmental diseases.

Registration, atlas estimation and variability analysis of white matter fiber bundles modeled as currents

This paper proposes a generic framework for the registration, the template estimation and the variability analysis of white matter fiber bundles extracted from diffusion images. This framework is based on the metric on currents for the comparison of fiber bundles. This metric measures anatomical differences between fiber bundles, seen as global homologous structures across subjects. It avoids the need to establish correspondences between points or between individual fibers of different bundles. It can measure differences both in terms of the geometry of the bundles (like its boundaries) and in terms of the density of fibers within the bundle. It is robust to fiber interruptions and reconnections. In addition, a recently introduced sparse approximation algorithm allows us to give an interpretable representation of the fiber bundles and their variations in the framework of currents. First, we used this metric to drive the registration between two sets of homologous fiber bundles of two different subjects. A dense deformation of the underlying white matter is estimated, which is constrained by the bundles seen as global anatomical landmarks. By contrast, the alignment obtained from image registration is driven only by the local gradient of the image. Second, we propose a generative statistical model for the analysis of a collection of homologous bundles. This model consistently estimates prototype fiber bundles (called template), which capture the anatomical invariants in the population, a set of deformations, which align the geometry of the template to that of each subject and a set of residual perturbations. The statistical analysis of both the deformations and the residuals describe the anatomical variability in terms of geometry (stretching, torque, etc.) and "texture" (fiber density, etc.). Third, this statistical modeling allows us to simulate new synthetic bundles according to the estimated variability. This gives a way to interpret the anatomical features that the model detects consistently across the subjects. This may be used to better understand the bias introduced by the fiber extraction methods and eventually to give anatomical characterization of the normal or pathological variability of fiber bundles.

Observer-independent characterization of sulcal landmarks and depth asymmetry in the central sulcus of the chimpanzee brain

The central sulcus (CS) divides primary motor and sensory cortex in many mammalian brains. Recent studies have shown that experiential factors can influence the volume and lateralization of the CS in both human and nonhuman primates. In this study, we sought to define specific landmarks and the depth of the CS region corresponding to the motor-hand area of chimpanzees for comparison with humans using a novel, observer independent method applied to sample of 32 magnetic resonance images (MRI) scans. Our results showed that the dorsal-ventral location of the motor-hand region is comparable between humans and chimpanzees, though the depth of the CS was significantly greater in humans compared to chimpanzees. We further found that CS area corresponding to the motor-hand area was significantly larger in the hemisphere contralateral to the chimpanzees preferred hand. The methods employed here offer some potential advantages over traditional region-of-interest in the comparative study of cortical organization and gyrification in primates and are discussed.

Anterior cingulate and paracingulate sulci morphology in patients with schizophrenia

The anterior cingulate cortex is a cerebral region engaged in several emotional and cognitive functions. The aim of this study was to investigate possible anterior cingulate and paracingulate sulcal abnormalities in schizophrenia. Twenty-three patients with DSM-IV diagnoses of schizophrenia were compared with 23 healthy subjects matched for age, gender, and parental socioeconomic status. Magnetic resonance images were used to explore the morphology of these regions, with volume and maximum depth being measured by an automated method of sulcal recognition. Additionally, voxel-based morphometry (VBM) was performed to analyze possible reduction in gray and white matter of the anterior cingulate region. A smaller volume of the left anterior cingulate sulcus (ACS) was observed in patients with schizophrenia when compared with healthy controls. Furthermore, female patients showed a reduction in volume of the left ACS and an increase of the right paracingulate sulcus (PCS) compared to female controls. There was also a significant relationship between the depth of right PCS and neuroleptic exposure. VBM analysis showed a reduction in left anterior cingulate gray matter. These findings provide further evidence of left anterior middle frontal cortex abnormalities in schizophrenia. In addition, the results suggest gender differences in the structural abnormalities of the illness.

Connectivity-based parcellation of the cortical mantle using q-ball diffusion imaging

This paper exploits the idea that each individual brain region has a specific connection profile to create parcellations of the cortical mantle using MR diffusion imaging. The parcellation is performed in two steps. First, the cortical mantle is split at a macroscopic level into 36 large gyri using a sulcus recognition system. Then, for each voxel of the cortex, a connection profile is computed using a probabilistic tractography framework. The tractography is performed from q fields using regularized particle trajectories. Fiber ODF are inferred from the q-balls using a sharpening process focusing the weight around the q-ball local maxima. A sophisticated mask of propagation computed from a T1-weighted image perfectly aligned with the diffusion data prevents the particles from crossing the cortical folds. During propagation, the particles father child particles in order to improve the sampling of the long fascicles. For each voxel, intersection of the particle trajectories with the gyri lead to a connectivity profile made up of only 36 connection strengths. These profiles are clustered on a gyrus by gyrus basis using a K-means approach including spatial regularization. The reproducibility of the results is studied for three subjects using spatial normalization.

A computational model of cerebral cortex folding

The geometric complexity and variability of the human cerebral cortex have long intrigued the scientific community. As a result, quantitative description of cortical folding patterns and the understanding of underlying folding mechanisms have emerged as important research goals. This paper presents a computational 3D geometric model of cerebral cortex folding initialized by MRI data of a human fetal brain and deformed under the governance of a partial differential equation modeling cortical growth. By applying different simulation parameters, our model is able to generate folding convolutions and shape dynamics of the cerebral cortex. The simulations of this 3D geometric model provide computational experimental support to the following hypotheses: (1) Mechanical constraints of the skull regulate the cortical folding process. (2) The cortical folding pattern is dependent on the global cell growth rate of the whole cortex. (3) The cortical folding pattern is dependent on relative rates of cell growth in different cortical areas. (4) The cortical folding pattern is dependent on the initial geometry of the cortex.

Nurture versus nature: long-term impact of forced right-handedness on structure of pericentral cortex and basal ganglia

Does a conflict between inborn motor preferences and educational standards during childhood impact the structure of the adult human brain? To examine this issue, we acquired high-resolution T1-weighted magnetic resonance scans of the whole brain in adult "converted" left-handers who had been forced as children to become dextral writers. Analysis of sulcal surfaces revealed that consistent right- and left-handers showed an interhemispheric asymmetry in the surface area of the central sulcus with a greater surface contralateral to the dominant hand. This pattern was reversed in the converted group who showed a larger surface of the central sulcus in their left, nondominant hemisphere, indicating plasticity of the primary sensorimotor cortex caused by forced use of the nondominant hand. Voxel-based morphometry showed a reduction of gray matter volume in the middle part of the left putamen in converted left-handers relative to both consistently handed groups. A similar trend was found in the right putamen. Converted subjects with at least one left-handed first-degree relative showed a correlation between the acquired right-hand advantage for writing and the structural changes in putamen and pericentral cortex. Our results show that a specific environmental challenge during childhood can shape the macroscopic structure of the human basal ganglia. The smaller than normal putaminal volume differs markedly from previously reported enlargement of cortical gray matter associated with skill acquisition. This indicates a differential response of the basal ganglia to early environmental challenges, possibly related to processes of pruning during motor development.

An automated pipeline for cortical sulcal fundi extraction

In this paper, we propose a novel automated pipeline for extraction of sulcal fundi from triangulated cortical surfaces. This method consists of four consecutive steps. Firstly, we adopt a finite difference method to estimate principal curvatures, principal directions and curvature derivatives, along the principal directions, for each vertex. Then, we detect the sulcal fundi segment in each triangle of the cortical surface based on curvatures and curvature derivatives. Afterwards, we link the sulcal fundi segments into continuous curves. Finally, we connect breaking sulcal fundi and smooth bumping sulcal fundi by using the fast marching method on the cortical surface. The proposed method can find the accurate sulcal fundi using curvatures and curvature derivatives without any manual interaction. The method was applied to 10 normal brain MR images on inner cortical surfaces. We quantitatively evaluated the accuracy of the sulcal fundi extraction method using manually labeled sulcal fundi by experts. The average difference between automatically extracted major sulcal fundi and the expert labeled results is consistently around 1.0mm on 10 subject images, indicating the good performance of the proposed method.

Feature-based morphometry: discovering group-related anatomical patterns

This paper presents feature-based morphometry (FBM), a new fully data-driven technique for discovering patterns of group-related anatomical structure in volumetric imagery. In contrast to most morphometry methods which assume one-to-one correspondence between subjects, FBM explicitly aims to identify distinctive anatomical patterns that may only be present in subsets of subjects, due to disease or anatomical variability. The image is modeled as a collage of generic, localized image features that need not be present in all subjects. Scale-space theory is applied to analyze image features at the characteristic scale of underlying anatomical structures, instead of at arbitrary scales such as global or voxel-level. A probabilistic model describes features in terms of their appearance, geometry, and relationship to subject groups, and is automatically learned from a set of subject images and group labels. Features resulting from learning correspond to group-related anatomical structures that can potentially be used as image biomarkers of disease or as a basis for computer-aided diagnosis. The relationship between features and groups is quantified by the likelihood of feature occurrence within a specific group vs. the rest of the population, and feature significance is quantified in terms of the false discovery rate. Experiments validate FBM clinically in the analysis of normal (NC) and Alzheimer's (AD) brain images using the freely available OASIS database. FBM automatically identifies known structural differences between NC and AD subjects in a fully data-driven fashion, and an equal error classification rate of 0.80 is achieved for subjects aged 60-80 years exhibiting mild AD (CDR=1).

A hybrid system using symbolic and numeric knowledge for the semantic annotation of sulco-gyral anatomy in brain MRI images

This paper describes an interactive system for the semantic annotation of brain magnetic resonance images. The system uses both a numerical atlas and symbolic knowledge of brain anatomical structures depicted using the Semantic Web standards. This knowledge is combined with graphical data, automatically extracted from the images by imaging tools. The annotations of parts of gyri and sulci, in a region of interest, rely on constraint satisfaction problem solving and description logics inferences. The system is run on a client-server architecture, using Web services and including a sophisticated visualization tool. An evaluation of the system was done using normal (healthy) and pathological cases. The results obtained so far demonstrate that the system produces annotations with high precision and quality.

Automatic cortical sulcal parcellation based on surface principal direction flow field tracking

The human cerebral cortex is a highly convoluted structure composed of sulci and gyri, corresponding to the valleys and ridges of the cortical surface respectively. Automatic parcellation of the cortical surface into sulcal regions is of great importance in structural and functional mapping of the human brain. In this paper, a novel method is proposed for automatic cortical sulcal parcellation based on the geometric characteristics of cortical surface including its principal curvatures and principal directions. This method is composed of two major steps: 1) employing the hidden Markov random field model (HMRF) and the expectation maximization (EM) algorithm on the maximum principal curvatures of the cortical surface for sulcal region segmentation, and 2) using a principal direction flow field tracking method on the cortical surface for sulcal basin segmentation. The flow field is obtained by diffusing the principal direction field on the cortical surface mesh. A unique feature of this method is that the automatic sulcal parcellation process is quite robust and efficient, and is independent of any external guidance such as atlas-based warping. The method has been successfully applied to the inner cortical surfaces of twelve healthy human brain MR images. Both quantitative and qualitative evaluation results demonstrate the validity and efficiency of the proposed method.

Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds

Neuroimaging studies, using various modalities, have evidenced a link between the general intelligence factor (g) and regional brain function and structure in several multimodal association areas. While in the last few years, developments in computational neuroanatomy have made possible the in vivo quantification of cortical thickness, the relationship between cortical thickness and psychometric intelligence has been little studied. Recently, cortical thickness estimations have been improved by the use of an iterative hemisphere-specific template registration algorithm which provides a better between-subject alignment of brain surfaces. Using this improvement, we aimed to further characterize brain regions where cortical thickness was associated with cognitive ability differences and to test the hypothesis that these regions are mostly located in multimodal association areas. We report associations between a general cognitive ability factor (as an estimate of g) derived from the four subtests of the Wechsler Abbreviated Scale of Intelligence and cortical thickness adjusted for age, gender, and scanner in a large sample of healthy children and adolescents (ages 6-18, N=216) representative of the US population. Significant positive associations were evidenced between the cognitive ability factor and cortical thickness in most multimodal association areas. Results are consistent with a distributed model of intelligence.

Mean q-ball strings obtained by constrained procrustes analysis with point sliding

The idea underpinning the work we present herein is to design robust and objective tools for brain white matter (WM) morphometry. We focus on WM tracts, and propose to represent them by their mean lines, to which we associate the attributes derived from high-angular resolution diffusion imaging (HARDI). The definition of the tract mean line derives directly from the geometry of the tract fibres. We determine the fibre point correspondences and impact factors of individual fibres, upon which we estimate average HARDI models along the tract mean lines. This way we obtain a compact tract representation that exploits all the available information, and is at the same time free of the outlier influence and undesired tract edge effects.

Loss of cerebral white matter structural integrity tracks the gray matter metabolic decline in normal aging

Relationships between structural MRI-based markers of declining cerebral integrity, and regional PET measurements of (18)FDG uptake have not been studied well in normal aging. In this manuscript we relate changes in cerebral morphology to regional cerebral glucose uptake for 14 major cortical areas in 19 healthy older individuals (age 59-92 years). Measurements of cerebral integrity included gray matter (GM) thickness, sulcal and intergyral spans, fractional anisotropy (FA) of water diffusion and volume of hyperintense WM (HWM) lesions. (18)FDG-PET measurements were converted to standard uptake values and corrected for partial volume artifact. Following this, cortical FDG uptake was significantly correlated with several indices of WM integrity that we previously observed to be sensitive to cognitive decline in executive function, including intergyral span and HWM volumes. Our findings suggest that the age-related decline in white matter integrity, observed as increases in HWM lesions, intergyral spans and reduction in FA, correlated with a decline in the global and regional cerebral glucose uptake. Our findings support the emerging consensus that WM integrity indices are sensitive predictors of declining cerebral health in normal aging. Specifically, age-related WM degradation in the thinly myelinated association tracts appears to track the decreases in global and regional rates of glucose uptake.

Global and temporal cortical folding in patients with early-onset schizophrenia

OBJECTIVE

Adult-onset schizophrenia has repeatedly been associated with disturbances in the temporal lobes and alterations in cortical folding, which are thought to reflect neurodevelopmental impairment. Early-onset schizophrenia (EOS; onset before 18 years) is considered to involve even more pronounced neurodevelopmental deviance across a wide range of brain structural measures. We hypothesized that overall alteration of cortical folding also applies to EOS, and EOS involves prominent structural aberrations in superior temporal and collateral sulci.

METHOD

Magnetic resonance T1 images of 51 patients with EOS and 59 healthy participants were investigated. A fully automated method was applied to the images to extract, label, and measure the sulcus area in the whole cortex. Cortical folding was assessed by computing global sulcal indices (the ratio between total sulcal area and total outer cortex area) for each hemisphere and local sulcal indices (the ratio between the area of labeled sulcus and total outer cortex area in the corresponding hemisphere) for superior temporal and collateral sulci.

RESULTS

Relative to healthy individuals, patients with EOS had significantly lower global sulcal indices in both hemispheres and a lower local sulcal index in the left collateral sulcus.

CONCLUSIONS

Reduced hemispheric sulcation appears to be a feature of schizophrenia, irrespective of age at onset. Structural aberration involving the left collateral sulcus may contribute to neurobiological substrate of EOS.

Computer-assisted identification of the central sulcus in patients with brain tumors using MRI

PURPOSE

To develop computer-assisted image processing to identify the central sulcus from the MRI data sets in patients with brain tumors.

MATERIALS AND METHODS

All MR images were acquired with a 3.0 Tesla scanner by three-dimensional (3D) spoiled gradient recalled acquisition using the steady state (SPGR) gradient-echo sequence and short inversion time inversion-recovery fast spin-echo sequence. The sulci were extracted automatically from reconstructed two-dimensional images of the cortical surface of 30 patients with brain tumors, and the extracted sulci were scored according to matching of the accepted anatomical features of the central sulcus. The candidates with the three highest scores were then superimposed on the 3D images. The correct position of the central sulcus was agreed by two senior neurosurgeons and one neuroradiologist.

RESULTS

One of the three candidates corresponded to the central sulcus identified by the manual segmentation method for all 60 affected and unaffected hemispheres in the 30 patients. The candidate with the highest score coincided with the central sulcus in 26 of the 28 unaffected hemispheres and in 28 of the 32 affected hemispheres.

CONCLUSION

The proposed method of computer-assisted image processing can provide accurate guidance to identifying the central sulcus in patients with brain tumors.

Inferring brain variability from diffeomorphic deformations of currents: an integrative approach

In the context of computational anatomy, one aims at understanding and modelling the anatomy of the brain and its variations across a population. This geometrical variability is often measured from precisely defined anatomical landmarks such as sulcal lines or meshes of brain structures. This requires (1) to compare geometrical objects without introducing too many non realistic priors and (2) to retrieve the variability of the whole brain from the variability of the landmarks. We propose, in this paper, to infer a statistical brain model from the consistent integration of variability of sulcal lines. The similarity between two sets of lines is measured by a distance on currents that does not assume any type of point correspondences and it is not sensitive to the sampling of lines. This shape similarity measure is used in a diffeomorphic registrations which retrieves a single deformation of the whole 3D space. This diffeomorphism integrates the variability of all lines in a as spatially consistent manner as possible. Based on repeated pairwise registrations on a large database, we learn how the mean anatomy varies in a population by computing statistics on diffeomorphisms. Whereas usual methods lead to descriptive measures of variability, such as variability maps or statistical tests, our model is generative: we can simulate new observations according to the learned probability law on deformations. In practice, this variability captured by the model is synthesized in the principal modes of deformations. As a deformation is dense, we can also apply it to other anatomical structures defined in the template space. This is illustrated the action of the principal modes of deformations to a mean cortical surface. Eventually, our current-based diffeomorphic registration (CDR) approach is carefully compared to a pointwise line correspondences (PLC) method. Variability measures are computed with both methods on the same dataset of sulcal lines. The results suggest that we retrieve more variability with CDR than with PLC, especially in the direction of the lines. Other differences also appear which highlight the different methodological assumptions each method is based on.

Hamilton-Jacobi skeleton on cortical surfaces

In this paper, we propose a new method to construct graphical representations of cortical folding patterns by computing skeletons on triangulated cortical surfaces. In our approach, a cortical surface is first partitioned into sulcal and gyral regions via the solution of a variational problem using graph cuts, which can guarantee global optimality. After that, we extend the method of Hamilton-Jacobi skeleton [1] to subsets of triangulated surfaces, together with a geometrically intuitive pruning process that can trade off between skeleton complexity and the completeness of representing folding patterns. Compared with previous work that uses skeletons of 3-D volumes to represent sulcal patterns, the skeletons on cortical surfaces can be easily decomposed into branches and provide a simpler way to construct graphical representations of cortical morphometry. In our experiments, we demonstrate our method on two different cortical surface models, its ability of capturing major sulcal patterns and its application to compute skeletons of gyral regions.

Probabilistic maps, morphometry, and variability of cytoarchitectonic areas in the human superior parietal cortex

Recently, 8 areas (5Ci, 5M, 5L, 7PC, 7A, 7P, 7M, hIP3) in the human superior parietal cortex (SPC) were delineated in 10 postmortem brains using observer-independent cytoarchitectonic analysis. Here we present 3D probabilistic maps of these areas, quantifying the interindividual overlap for each voxel in stereotaxic reference space, and a maximum probability map, providing a contiguous parcellation. For all areas, we determined probabilities of mutual borders, calculated stereotaxic centers of gravity, and estimated volumes. A basic pattern of areas and borders was observed, which showed, however, intersubject variations and a significant interhemispheric asymmetry (7P, 7M) that may be functionally relevant. There was a trend toward higher intersubject anatomical variability in lateral compared with medial areas. For several areas (5M, 7PC, 7A, 7P), variability was significantly higher in the left hemisphere and/or in men, whereas for areas 5Ci and 5M there was a hemisphere-by-gender interaction. Differences in anatomical variability could bias group analyses in functional imaging studies by reducing sensitivity for activations of entities with high variability. The probabilistic maps provide an objective anatomical reference and account for the structural variability of the human brain. Integrated into functional imaging experiments, they can improve structure-function investigations of the human SPC.

Measuring brain variability via sulcal lines registration: a diffeomorphic approach

In this paper we present a new way of measuring brain variability based on the registration of sulcal lines sets in the large deformation framework. Lines are modelled geometrically as currents, avoiding then matchings based on point correspondences. At the end we retrieve a globally consistent deformation of the underlying brain space that best matches the lines. Thanks to this framework the measured variability is defined everywhere whereas a previous method introduced by P. Fillard requires tensors extrapolation. Evaluating both methods on the same database, we show that our new approach enables to describe different details of the variability and to highlight the major trends of deformation in the database thanks to a Tangent-PCA analysis.

Structural analysis of fMRI data revisited: improving the sensitivity and reliability of fMRI group studies

Group studies of functional magnetic resonance imaging datasets are usually based on the computation of the mean signal across subjects at each voxel (random effects analyses), assuming that all subjects have been set in the same anatomical space (normalization). Although this approach allows for a correct specificity (rate of false detections), it is not very efficient for three reasons: i) its underlying hypotheses, perfect coregistration of the individual datasets and normality of the measured signal at the group level are frequently violated; ii) the group size is small in general, so that asymptotic approximations on the parameters distributions do not hold; iii) the large size of the images requires some conservative strategies to control the false detection rate, at the risk of increasing the number of false negatives. Given that it is still very challenging to build generative or parametric models of intersubject variability, we rely on a rule based, bottom-up approach: we present a set of procedures that detect structures of interest from each subject's data, then search for correspondences across subjects and outline the most reproducible activation regions in the group studied. This framework enables a strict control on the number of false detections. It is shown here that this analysis demonstrates increased validity and improves both the sensitivity and reliability of group analyses compared with standard methods. Moreover, it directly provides information on the spatial position correspondence or variability of the activated regions across subjects, which is difficult to obtain in standard voxel-based analyses.

High level group analysis of FMRI data based on Dirichlet process mixture models

Inferring the position of functionally active regions from a multi-subject fMRI dataset involves the comparison of the individual data and the inference of a common activity model. While voxel-based analyzes, e.g. Random Effect statistics, are widely used, they do not model each individual activation pattern. Here, we develop a new procedure that extracts structures individually and compares them at the group level. For inference about spatial locations of interest, a Dirichlet Process Mixture Model is used. Finally, inter-subject correspondences are computed with Bayesian Network models. We show the power of the technique on both simulated and real datasets and compare it with standard inference techniques.

Brain functional localization: a survey of image registration techniques

Functional localization is a concept which involves the application of a sequence of geometrical and statistical image processing operations in order to define the location of brain activity or to produce functional/parametric maps with respect to the brain structure or anatomy. Considering that functional brain images do not normally convey detailed structural information and, thus, do not present an anatomically specific localization of functional activity, various image registration techniques are introduced in the literature for the purpose of mapping functional activity into an anatomical image or a brain atlas. The problems addressed by these techniques differ depending on the application and the type of analysis, i.e., single-subject versus group analysis. Functional to anatomical brain image registration is the core part of functional localization in most applications and is accompanied by intersubject and subject-to-atlas registration for group analysis studies. Cortical surface registration and automatic brain labeling are some of the other tools towards establishing a fully automatic functional localization procedure. While several previous survey papers have reviewed and classified general-purpose medical image registration techniques, this paper provides an overview of brain functional localization along with a survey and classification of the image registration techniques related to this problem.

Classification based on cortical folding patterns

We describe here a classification system based on automatically identified cortical sulci. Multivariate recognition methods are required for the detection of complex brain patterns with a spatial distribution. However, such methods may face the well-known issue of the curse of dimensionality-the risk of overfitting the training dataset in high-dimensional space. We overcame this problem, using a classifier pipeline with one- or two-stage of descriptor selection based on machine-learning methods, followed by a support vector machine classifier or linear discriminant analysis. We compared alternative designs of the pipeline on two different datasets built from the same database corresponding to 151 brains. The first dataset dealt with cortex asymmetry and the second dealt with the effect of the subject's sex. Our system successfully (98%) distinguished between the left and right hemispheres on the basis of sulcal shape (size, depth, etc.). The sex of the subject could be determined with a success rate of 85%. These results highlight the attractiveness of multivariate recognition models combined with appropriate descriptor selection. The sulci selected by the pipeline are consistent with previous whole-brain studies on sex effects and hemispheric asymmetries.

Measuring brain variability by extrapolating sparse tensor fields measured on sulcal lines

Modeling and understanding the variability of brain structures is a fundamental problem in neurosciences. Improved mathematical representations of structural brain variation are needed to help detect and understand genetic or disease related sources of abnormality, as well as to improve statistical power when integrating functional brain mapping data across subjects. In this paper, we develop a new mathematical model of normal brain variation based on a large set of cortical sulcal landmarks (72 per brain) delineated in each of 98 healthy human subjects scanned with 3D MRI (age: 51.8+/-6.2 years). We propose an original method to compute an average representation of the sulcal curves, which constitutes the mean anatomy. After affine alignment of the individual data across subjects, the second order moment distribution of the sulcal position is modeled as a sparse field of covariance tensors (symmetric, positive definite matrices). To extrapolate this information to the full brain, one has to overcome the limitations of the standard Euclidean matrix calculus. We propose an affine-invariant Riemannian framework to perform computations with tensors. In particular, we generalize radial basis function (RBF) interpolation and harmonic diffusion partial differential equations (PDEs) to tensor fields. As a result, we obtain a dense 3D variability map that agrees well with prior results on smaller subject samples. Moreover, "leave one (sulcus) out" tests show that our model is globally able to recover the missing information on brain variation when there is a consistent neighboring pattern of variability. Finally, we propose an innovative method to analyze the asymmetry of brain variability. As expected, the greatest asymmetries are found in regions that includes the primary language areas. Interestingly, any such asymmetries in anatomical variance, if it remains after anatomical normalization, could explain why there may be greater power to detect group activation in one hemisphere versus the other in fMRI studies.

Cortical sulci and bipolar disorder

The width of cortical sulci in bipolar patients (n=19) and healthy controls (n=35) was examined using a novel automated technique involving magnetic resonance imaging. All sulci were wider for bipolar patients than for healthy controls. Bipolar-control differences were largest for the superior and intermediate frontal sulci, smallest for the occipital and cingulate sulci, and intermediate in magnitude for the other sulci (intraparietal, inferior frontal, and central sulci). The results were interpreted in terms of neurodegenerative-illness-related processes, which could produce cortical atrophy and result in wider sulci.

Exploiting human anatomical variability as a link between genome and cognome

Although talents and disabilities appear to run in families, direct links between genes and cognitive ability are difficult to establish. Investigators are currently searching for intermediate phenotypes with plausible links to both genome and cognome (the cognitive phenotype). Cortical anatomy could provide one such intermediate phenotype. Variation in cortical size, asymmetry and sulcal pattern is influenced by genetic variation in neurotrophic factors and can predict variation in verbal and mathematical talent. Anecdotal evidence suggests that individuals with a rare morphological variant of Sylvian fissure sometimes have superior visualization ability combined with verbal deficits. Documentation of such 'cognitive cortical syndromes' might prove as genetically informative as the identification of dysmorphic syndromes associated with mental retardation. A necessary prerequisite for the establishment of such syndromes is a reliable technique for the identification of cortical patterns. Recent technical advances in software for automatically labeling and measuring cortical sulci now provide the possibility of establishing standard measures for their shape, size and location. Such measures are a prerequisite for genetic studies of cortical patterns that could illuminate the neurodevelopmental pathways by which genes affect cognitive ability.

Anatomical variability of the lateral frontal lobe surface: implication for intersubject variability in language neuroimaging

The lateral surface of the frontal lobe shows functional activation in a large number of language related tasks. Group analyses, however, demonstrate remarkable intersubject variability of activation. There are different sources for functional variability, anatomical variability being considered as one of them. The aim of the present study therefore was to qualitatively and quantitatively investigate the anatomical variability of the lateral frontal lobe surface and to search for reliable and stable landmarks connected to language functions. MRIs of 23 healthy right-handed subjects were investigated using the publicly available software "Anatomist/BrainVISA". After standardization of the brains (SPM) and sulci identification, the most frequent pattern was determined and the variance of selected landmarks calculated. The variability of the lateral frontal lobe surface is remarkable, particularly in the prefrontal region. Relatively stable landmarks were selected as follows: (1) connection between the superior frontal sulcus (SFS) and the superior precentral sulcus (SPCS); (2) connection between the inferior frontal sulcus (IFS) and the inferior precentral sulcus (IPCS); (3) inferior end of the precentral sulcus (PCS); and (4) origin of the ascending ramus (AscR) of the Sylvian fissure (SYF). The variability (standard deviation) of the spatial coordinates along the 3 axis of these landmarks after normalization ranged from 2.5 to 5.7 mm. The present study demonstrates that intersubject variability of selected landmarks of the frontal lobe surface remains notable even after spatial normalization of the brains. These results support the concept that anatomical variability is a relevant source of functional variability. We therefore suggest to express functional activation in relation to landmarks obtained from individual anatomy. This approach may contribute to a better analysis of the differences between individuals.