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The trajectory of gray matter development in Broca’s area is abnormal in people who stutter
© 2015 Beal, Lerch, Cameron, Henderson, Gracco and De Nil. The acquisition and mastery of speech-motor control requires years of practice spanning the course of development. People who stutter often perform poorly on speech-motor tasks thereby calling into question their ability to establish the stable neural motor programs required for masterful speech-motor control. There is evidence to support the assertion that these neural motor programs are represented in the posterior part of Broca’s area, specifically the left pars opercularis. Consequently, various theories of stuttering causation posit that the disorder is related to a breakdown in the formation of the neural motor programs for speech early in development and that this breakdown is maintained throughout life. To date, no study has examined the potential neurodevelopmental signatures of the disorder across pediatric and adult populations. The current study aimed to fill this gap in our knowledge. We hypothesized that the developmental trajectory of cortical thickness in people who stutter would differ across the lifespan in the left pars opercularis relative to a group of control participants. We collected structural magnetic resonance images from 116 males (55 people who stutter) ranging in age from 6 to 48 years old. Differences in cortical thickness across ages and between patients and controls were investigated in 30 brain regions previously implicated in speech-motor control. An interaction between age and group was found for the left pars opercularis only. In people who stutter, the pars opercularis did not demonstrate the typical maturational pattern of gradual gray matter thinning with age across the lifespan that we observed in control participants. In contrast, the developmental trajectory of gray matter thickness in other regions of interest within the neural network for speech-motor control was similar for both groups. Our findings indicate that the developmental trajectory of gray matter in left pars opercularis is abnormal in people who stutter.
Preparation of fixed mouse brains for MRI.
In fixed mouse brain magnetic resonance images, a high prevalence of fixation artifacts have been observed. Of more than 1700 images of fixed brains acquired at our laboratory, fixation artifacts were present in approximately 30%. In this study, two of these artifacts are described and their causes are identified. A hyperintense rim around the brain is observed when using perfusates reconstituted from powder and delivered at a high flow rate. It is proposed that these perfusion conditions cause blockage of the capillary beds and an increase in pressure that ruptures the vessels, resulting in a blister of liquid below the dura mater. Secondly, gray-white matter contrast inversion is observed when too short a fixation time or too low a concentration of fixative is used, resulting in inadequate fixation. The deleterious consequences of these artifacts for quantitative data analysis are discussed, and precautions for their prevention are provided.
Neurodevelopmental trajectories of the human cerebral cortex.
Understanding the organization of the cerebral cortex remains a central focus of neuroscience. Cortical maps have relied almost exclusively on the examination of postmortem tissue to construct structural, architectonic maps. These maps have invariably distinguished between areas with fewer discernable layers, which have a less complex overall pattern of lamination and lack an internal granular layer, and those with more complex laminar architecture. The former includes several agranular limbic areas, and the latter includes the homotypical and granular areas of association and sensory cortex. Here, we relate these traditional maps to developmental data from noninvasive neuroimaging. Changes in cortical thickness were determined in vivo from 764 neuroanatomic magnetic resonance images acquired longitudinally from 375 typically developing children and young adults. We find differing levels of complexity of cortical growth across the cerebrum, which align closely with established architectonic maps. Cortical regions with simple laminar architecture, including most limbic areas, predominantly show simpler growth trajectories. These areas have clearly identified homologues in all mammalian brains and thus likely evolved in early mammals. In contrast, polysensory and high-order association areas of cortex, the most complex areas in terms of their laminar architecture, also have the most complex developmental trajectories. Some of these areas are unique to, or dramatically expanded in primates, lending an evolutionary significance to the findings. Furthermore, by mapping a key characteristic of these development trajectories (the age of attaining peak cortical thickness) we document the dynamic, heterochronous maturation of the cerebral cortex through time lapse sequences ("movies").
Imaging sex/gender and autism in the brain: Etiological implications.
The male preponderance in autism prevalence has brought together the disparate topics of sex/gender and autism research. Two directions of neuroimaging studies on the relationships between sex/gender and autism may inform male-specific risk mechanisms and female-specific protective mechanisms of autism. First, we review how sex/gender moderates autism-related brain changes and how this informs general models of autism etiology. Better-powered human neuroimaging studies suggest that the brain characteristics of autism are qualitatively, rather than simply quantitatively, different between males and females. However, age and comorbidities might substantially moderate the pattern of differences. Second, we review how the relationship between autism-related brain changes (separately in males and females) and normative brain sex/gender differences informs specific etiological-developmental mechanisms. Both human and animal studies converge to indicate that the brain characteristics of autism are partly associated with normative brain sex/gender differences, suggesting convergence or overlap between the mechanisms leading to and modifying the development of autism and the mechanisms underlying sex differentiation and/or gender socialization. Future animal work needs to investigate sex differences in rodent mutants modeling autism-relevant genes and environmental exposures. Future human work needs to address the substantial phenotypic and etiological heterogeneity of autism and to focus on longitudinal neuroimaging studies (from early development) on the developmental trajectories of sex/gender-differential neural characteristics of autism. Combining animal and human work links up the causal chain from etiological factors, brain and physical development, to phenotypes. These together help delineate the different roles of sex and gender in relation to risk vs. protective mechanisms. © 2016 Wiley Periodicals, Inc.
A Diffusion Tensor Imaging Study in Children With ADHD, Autism Spectrum Disorder, OCD, and Matched Controls: Distinct and Non-Distinct White Matter Disruption and Dimensional Brain-Behavior Relationships.
OBJECTIVE: Neurodevelopmental disorders (NDDs) (attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], and obsessive-compulsive disorder [OCD]) share genetic vulnerability and symptom domains. The authors present direct comparison of structural brain circuitry in children and adolescents with NDDs and control subjects and examine brain circuit-behavior relationships across NDDs using dimensional measures related to each disorder. METHOD: Diffusion imaging and behavioral measures were acquired in 200 children and adolescents (ADHD: N=31; OCD: N=36; ASD: N=71; controls: N=62; mean age range: 10.3-12.6 years). Following Tract-Based Spatial Statistics, multigroup comparison of white matter indices was conducted, followed by pairwise comparisons. Relationships of fractional anisotropy with dimensional measures of inattention, social deficits, obsessive-compulsive symptoms, and general adaptive functioning were conducted across the NDD sample. RESULTS: Lower fractional anisotropy within the splenium of the corpus callosum was found in each NDD group, compared with the control group. Lower fractional anisotropy in additional white matter tracts was found in the ASD and ADHD groups, compared with the control group, but not in the OCD group. Fractional anisotropy was lower in the ASD and ADHD groups compared with the OCD group but was not different in ADHD participants compared with ASD participants. A positive relation between fractional anisotropy (across much of the brain) and general adaptive functioning across NDDs was shown. CONCLUSIONS: This study identified disruption in interhemispheric circuitry (i.e., fractional anisotropy alterations in the corpus callosum) as a shared feature of ASD, ADHD, and OCD. However, fractional anisotropy alterations may be more widespread and severe in ASD and ADHD than in OCD. Higher fractional anisotropy throughout the brain appears to be related to better adaptive function across NDDs.
Radiation-induced alterations in mouse brain development characterized by magnetic resonance imaging.
PURPOSE: The purpose of this study was to identify regions of altered development in the mouse brain after cranial irradiation using longitudinal magnetic resonance imaging (MRI). METHODS AND MATERIALS: Female C57Bl/6 mice received a whole-brain radiation dose of 7 Gy at an infant-equivalent age of 2.5 weeks. MRI was performed before irradiation and at 3 time points following irradiation. Deformation-based morphometry was used to quantify volume and growth rate changes following irradiation. RESULTS: Widespread developmental deficits were observed in both white and gray matter regions following irradiation. Most of the affected brain regions suffered an initial volume deficit followed by growth at a normal rate, remaining smaller in irradiated brains compared with controls at all time points examined. The one exception was the olfactory bulb, which in addition to an early volume deficit, grew at a slower rate thereafter, resulting in a progressive volume deficit relative to controls. Immunohistochemical assessment revealed demyelination in white matter and loss of neural progenitor cells in the subgranular zone of the dentate gyrus and subventricular zone. CONCLUSIONS: MRI can detect regional differences in neuroanatomy and brain growth after whole-brain irradiation in the developing mouse. Developmental deficits in neuroanatomy persist, or even progress, and may serve as useful markers of late effects in mouse models. The high-throughput evaluation of brain development enabled by these methods may allow testing of strategies to mitigate late effects after pediatric cranial irradiation.
Human cortical anatomical networks assessed by structural MRI
Mapping the structure and function of the brain with non-invasive brain imaging techniques has become a world-wide enterpise in the last 20 years. The core concept that drives this rapid growth has been the use of a standardized 3D coordinate space for combining data from many subjects and/or time-points. This has allowed geographically-separated laboratories to reproduce experiments in precise detail, to share data or to perform meta-analysis in ways that go far beyond the traditional reviewing of summary results in journal publications. A further corollary of the brain mapping approach is the natural fostering of multi-center collaboration among distant sites. This article describes recent progress in trans-Pacific collaboration between Canadian and Asian laboratories in the study of neuroanatomical networks obtained from MRI data, both in the normal brain and in neurodegenerative disorders. © 2008 Springer Science+Business Media, LLC.
Connectivity of anatomical and functional MRI data
We are all familiar with the correlation coefficient between two sets of numbers. Now suppose we replace the numbers by vector-valued images in any number of dimensions. The correlation random field is the 'image' of correlations at all possible pairs of points in the two images. We use random field theory to set a threshold on the correlations so that those above the threshold are statistically significant, corrected for searching over all pairs of points. We apply this idea to resting state networks of fMRI images of brain activity, and networks of connectivity in cortical thickness. © 2005 IEEE.
Multi-atlas segmentation of the whole hippocampus and subfields using multiple automatically generated templates.
INTRODUCTION: Advances in image segmentation of magnetic resonance images (MRI) have demonstrated that multi-atlas approaches improve segmentation over regular atlas-based approaches. These approaches often rely on a large number of manually segmented atlases (e.g. 30-80) that take significant time and expertise to produce. We present an algorithm, MAGeT-Brain (Multiple Automatically Generated Templates), for the automatic segmentation of the hippocampus that minimises the number of atlases needed whilst still achieving similar agreement to multi-atlas approaches. Thus, our method acts as a reliable multi-atlas approach when using special or hard-to-define atlases that are laborious to construct. METHOD: MAGeT-Brain works by propagating atlas segmentations to a template library, formed from a subset of target images, via transformations estimated by nonlinear image registration. The resulting segmentations are then propagated to each target image and fused using a label fusion method. We conduct two separate Monte Carlo cross-validation experiments comparing MAGeT-Brain and basic multi-atlas whole hippocampal segmentation using differing atlas and template library sizes, and registration and label fusion methods. The first experiment is a 10-fold validation (per parameter setting) over 60 subjects taken from the Alzheimer's Disease Neuroimaging Database (ADNI), and the second is a five-fold validation over 81 subjects having had a first episode of psychosis. In both cases, automated segmentations are compared with manual segmentations following the Pruessner-protocol. Using the best settings found from these experiments, we segment 246 images of the ADNI1:Complete 1Yr 1.5 T dataset and compare these with segmentations from existing automated and semi-automated methods: FSL FIRST, FreeSurfer, MAPER, and SNT. Finally, we conduct a leave-one-out cross-validation of hippocampal subfield segmentation in standard 3T T1-weighted images, using five high-resolution manually segmented atlases (Winterburn et al., 2013). RESULTS: In the ADNI cross-validation, using 9 atlases MAGeT-Brain achieves a mean Dice's Similarity Coefficient (DSC) score of 0.869 with respect to manual whole hippocampus segmentations, and also exhibits significantly lower variability in DSC scores than multi-atlas segmentation. In the younger, psychosis dataset, MAGeT-Brain achieves a mean DSC score of 0.892 and produces volumes which agree with manual segmentation volumes better than those produced by the FreeSurfer and FSL FIRST methods (mean difference in volume: 80 mm(3), 1600 mm(3), and 800 mm(3), respectively). Similarly, in the ADNI1:Complete 1Yr 1.5 T dataset, MAGeT-Brain produces hippocampal segmentations well correlated (r>0.85) with SNT semi-automated reference volumes within disease categories, and shows a conservative bias and a mean difference in volume of 250 mm(3) across the entire dataset, compared with FreeSurfer and FSL FIRST which both overestimate volume differences by 2600 mm(3) and 2800 mm(3) on average, respectively. Finally, MAGeT-Brain segments the CA1, CA4/DG and subiculum subfields on standard 3T T1-weighted resolution images with DSC overlap scores of 0.56, 0.65, and 0.58, respectively, relative to manual segmentations. CONCLUSION: We demonstrate that MAGeT-Brain produces consistent whole hippocampal segmentations using only 9 atlases, or fewer, with various hippocampal definitions, disease populations, and image acquisition types. Additionally, we show that MAGeT-Brain identifies hippocampal subfields in standard 3T T1-weighted images with overlap scores comparable to competing methods.
Structural covariance of brain region volumes is associated with both structural connectivity and transcriptomic similarity.
An organizational pattern seen in the brain, termed structural covariance, is the statistical association of pairs of brain regions in their anatomical properties. These associations, measured across a population as covariances or correlations usually in cortical thickness or volume, are thought to reflect genetic and environmental underpinnings. Here, we examine the biological basis of structural volume covariance in the mouse brain. We first examined large scale associations between brain region volumes using an atlas-based approach that parcellated the entire mouse brain into 318 regions over which correlations in volume were assessed, for volumes obtained from 153 mouse brain images via high-resolution MRI. We then used a seed-based approach and determined, for 108 different seed regions across the brain and using mouse gene expression and connectivity data from the Allen Institute for Brain Science, the variation in structural covariance data that could be explained by distance to seed, transcriptomic similarity to seed, and connectivity to seed. We found that overall, correlations in structure volumes hierarchically clustered into distinct anatomical systems, similar to findings from other studies and similar to other types of networks in the brain, including structural connectivity and transcriptomic similarity networks. Across seeds, this structural covariance was significantly explained by distance (17% of the variation, up to a maximum of 49% for structural covariance to the visceral area of the cortex), transcriptomic similarity (13% of the variation, up to maximum of 28% for structural covariance to the primary visual area) and connectivity (15% of the variation, up to a maximum of 36% for structural covariance to the intermediate reticular nucleus in the medulla) of covarying structures. Together, distance, connectivity, and transcriptomic similarity explained 37% of structural covariance, up to a maximum of 63% for structural covariance to the visceral area. Additionally, this pattern of explained variation differed spatially across the brain, with transcriptomic similarity playing a larger role in the cortex than subcortex, while connectivity explains structural covariance best in parts of the cortex, midbrain, and hindbrain. These results suggest that both gene expression and connectivity underlie structural volume covariance, albeit to different extents depending on brain region, and this relationship is modulated by distance.
Measurement of cerebral blood volume in mouse brain regions using micro-computed tomography.
Micro-computed tomography (micro-CT) is an X-ray imaging technique that can produce detailed 3D images of cerebral vasculature. This paper describes the development of a novel method for using micro-CT to measure cerebral blood volume (CBV) in the mouse brain. As an application of the methodology, we test the hypotheses that differences in CBV exist over anatomical brain regions and that high energy demanding primary sensory regions of the cortex have locally elevated CBV, which may reflect a vascular specialization. CBV was measured as the percentage of tissue space occupied by a radio-opaque silicon rubber that fills the vasculature. To ensure accuracy of the CBV measurements, several innovative refinements were made to standard micro-CT specimen preparation and analysis procedures. Key features of the described method are vascular perfusion under controlled pressure, registration of the micro-CT images to an MRI anatomical brain atlas and re-scaling of micro-CT intensities to CBV units with selectable exclusion of major vessels. Histological validation of the vascular perfusion showed that the average percentage of vessels filled was 93+/-3%. Comparison of thirteen brain regions in nine mice revealed significant differences in CBV between regions (p<0.0001) while cortical maps showed that primary visual and auditory areas have higher CBV than primary somatosensory areas.
Effects of prolonged treatment with memantine in the MRL model of central nervous system lupus
Neuropsychiatric manifestations and brain atrophy of unknown etiology are common and severe complications of systemic lupus erythematosus (SLE). An autoantibody that binds to N-methyl-D-aspartate (NMDA) receptor NR2 has been proposed as a key factor in the etiology of central nervous system (CNS) SLE. This hypothesis was supported by evidence suggesting memantine (MEM), an uncompetitive NMDA receptor antagonist, prevents behavioral dysfunction and brain pathology in healthy mice immunized with a peptide similar to an epitope on the NR2 receptor. Given that SLE is a chronic condition, we examined the effects of MEM in MRL/lpr mice, which develop behavioral deficits alongside SLE-like disease. A broad behavioral battery and 7-Tesla magnetic resonance imaging (MRI) were used to examine whether prolonged treatment with MEM (~25 mg/kg bodyweight in drinking water) prevents CNS involvement in this spontaneous model of SLE. Although MEM increased novel object exploration in MRL/lpr mice, it did not show other beneficial, substrain-specific effects. Conversely, MEM was detrimental to spontaneous activity in control MRL +/+ mice and had a negative effect on body mass gain. Similarly, MRI showed comparable increases in the volume of periventricular structures in MEM-treated groups. We conclude that sustained exposure to MEM affects body growth, brain morphology and behavior primarily by pharmacological, and not autoimmunity- dependent, mechanisms. Substrain-specific improvement in exploratory behavior of MEM-treated MRL/lpr mice might indicate that the NMDA system is merely a constituent of a complex pathogenic cascade. However, it was evident that chronic administration of MEM is unable to completely prevent the development of a CNS SLE-like syndrome. © 2012 Japanese Society for Neuroimmunology.
Regional brain volume changes following chronic antipsychotic administration are mediated by the dopamine D2 receptor.
BACKGROUND: Neuroanatomical alterations are well established in patients suffering from schizophrenia, however the extent to which these changes are attributable to illness, antipsychotic drugs (APDs), or their interaction is unclear. APDs have been extremely effective for treatment of positive symptoms in major psychotic disorders. Their therapeutic effects are mediated, in part, through blockade of D2-like dopamine (DA) receptors, i.e. the D2, D3 and D4 dopamine receptors. Furthermore, the dependency of neuroanatomical change on DA system function and D2-like receptors has yet to be explored. METHODS: We undertook a preclinical longitudinal study to examine the effects of typical (haloperidol (HAL)) and atypical (clozapine (CLZ)) APDs in wild type (WT) and dopamine D2 knockout (D2KO) mice over 9-weeks using structural magnetic resonance imaging (MRI). RESULTS: Chronic typical APD administration in WT mice was associated with reductions in total brain (p = 0.009) and prelimbic area (PL) (p = 0.02) volumes following 9-weeks, and an increase in striatal volume (p = 0.04) after six weeks. These APD-induced changes were not present in D2KOs, where, at baseline, we observed significantly smaller overall brain volume (p < 0.01), thinner cortices (q < 0.05), and enlarged striata (q < 0.05). Stereological assessment revealed increased glial density in PL area of HAL treated wild types. Interestingly, in WT and D2KO mice, chronic CLZ administration caused more limited changes in brain structure. CONCLUSIONS: Our results present evidence for the role of D2 DA receptors in structural alterations induced by the administration of the typical APD HAL and that chronic administration of CLZ has a limited influence on brain structure.
Neuroanatomical phenotyping of the mouse brain with three-dimensional autofluorescence imaging.
The structural organization of the brain is important for normal brain function and is critical to understand in order to evaluate changes that occur during disease processes. Three-dimensional (3D) imaging of the mouse brain is necessary to appreciate the spatial context of structures within the brain. In addition, the small scale of many brain structures necessitates resolution at the ∼10 μm scale. 3D optical imaging techniques, such as optical projection tomography (OPT), have the ability to image intact large specimens (1 cm(3)) with ∼5 μm resolution. In this work we assessed the potential of autofluorescence optical imaging methods, and specifically OPT, for phenotyping the mouse brain. We found that both specimen size and fixation methods affected the quality of the OPT image. Based on these findings we developed a specimen preparation method to improve the images. Using this method we assessed the potential of optical imaging for phenotyping. Phenotypic differences between wild-type male and female mice were quantified using computer-automated methods. We found that optical imaging of the endogenous autofluorescence in the mouse brain allows for 3D characterization of neuroanatomy and detailed analysis of brain phenotypes. This will be a powerful tool for understanding mouse models of disease and development and is a technology that fits easily within the workflow of biology and neuroscience labs.
Variance decomposition of MRI-based covariance maps using genetically informative samples and structural equation modeling.
The role of genetics in driving intracortical relationships is an important question that has rarely been studied in humans. In particular, there are no extant high-resolution imaging studies on genetic covariance. In this article, we describe a novel method that combines classical quantitative genetic methodologies for variance decomposition with recently developed semi-multivariate algorithms for high-resolution measurement of phenotypic covariance. Using these tools, we produced correlational maps of genetic and environmental (i.e. nongenetic) relationships between several regions of interest and the cortical surface in a large pediatric sample of 600 twins, siblings, and singletons. These analyses demonstrated high, fairly uniform, statistically significant genetic correlations between the entire cortex and global mean cortical thickness. In agreement with prior reports on phenotypic covariance using similar methods, we found that mean cortical thickness was most strongly correlated with association cortices. However, the present study suggests that genetics plays a large role in global brain patterning of cortical thickness in this manner. Further, using specific gyri with known high heritabilities as seed regions, we found a consistent pattern of high bilateral genetic correlations between structural homologues, with environmental correlations more restricted to the same hemisphere as the seed region, suggesting that interhemispheric covariance is largely genetically mediated. These findings are consistent with the limited existing knowledge on the genetics of cortical variability as well as our prior multivariate studies on cortical gyri.
Longitudinal neuroanatomical changes determined by deformation-based morphometry in a mouse model of Alzheimer's disease.
Magnetic resonance imaging (MRI) of transgenic mice has the potential to provide valuable insight into the complex mechanisms underlying Alzheimer's disease (AD). Quantification of pathological changes is typically performed using manual segmentation methods, and requires a priori hypotheses about anatomical structures for volumetric measurement. Alternatively, deformation-based morphometry (DBM) has been shown to be a powerful, automated technique for detecting anatomical differences between populations by examining the deformation fields used to nonlinearly warp MR images. In this multiple timepoint, in vivo study, we have applied an automated, unbiased technique for the creation of a nonlinear, population-specific reference space from which robust DBM analysis can be performed. A general, linear mixed-effects model framework was developed to follow the evolution of structural changes in mouse brain from 2.5 to 9 months of age, and to examine neuroanatomical differences between a transgenic (TG) APP/PS1 murine model of AD and wild-type (WT) littermates. Morphometric abnormalities in the TG group were localized to regions of the hippocampus, cortex, olfactory bulbs, stria terminalis, brain stem, cerebellum, and ventricles. Although volumetric reductions were detected in TG mice, no general brain atrophy was found, suggesting a developmental, rather than a degenerative, pathological process. Finally, we established a strong correlation between a DBM summary measure and manually segmented volumes for each image in the dataset. These results support the utility of DBM to study longitudinal morphological changes in mouse models of central nervous system diseases in an automated and exploratory fashion.
High resolution three-dimensional brain atlas using an average magnetic resonance image of 40 adult C57Bl/6J mice.
Detailed anatomical atlases can provide considerable interpretive power in studies of both human and rodent neuroanatomy. Here we describe a three-dimensional atlas of the mouse brain, manually segmented into 62 structures, based on an average of 32 mum isotropic resolution T(2)-weighted, within skull images of forty 12 week old C57Bl/6J mice, scanned on a 7 T scanner. Individual scans were normalized, registered, and averaged into one volume. Structures within the cerebrum, cerebellum, and brainstem were painted on each slice of the average MR image while using simultaneous viewing of the coronal, sagittal and horizontal orientations. The final product, which will be freely available to the research community, provides the most detailed MR-based, three-dimensional neuroanatomical atlas of the whole brain yet created. The atlas is furthermore accompanied by ancillary detailed descriptions of boundaries for each structure and provides high quality neuroanatomical details pertinent to MR studies using mouse models in research.
Automated 3-D extraction and evaluation of the inner and outer cortical surfaces using a Laplacian map and partial volume effect classification.
Accurate reconstruction of the inner and outer cortical surfaces of the human cerebrum is a critical objective for a wide variety of neuroimaging analysis purposes, including visualization, morphometry, and brain mapping. The Anatomic Segmentation using Proximity (ASP) algorithm, previously developed by our group, provides a topology-preserving cortical surface deformation method that has been extensively used for the aforementioned purposes. However, constraints in the algorithm to ensure topology preservation occasionally produce incorrect thickness measurements due to a restriction in the range of allowable distances between the gray and white matter surfaces. This problem is particularly prominent in pediatric brain images with tightly folded gyri. This paper presents a novel method for improving the conventional ASP algorithm by making use of partial volume information through probabilistic classification in order to allow for topology preservation across a less restricted range of cortical thickness values. The new algorithm also corrects the classification of the insular cortex by masking out subcortical tissues. For 70 pediatric brains, validation experiments for the modified algorithm, Constrained Laplacian ASP (CLASP), were performed by three methods: (i) volume matching between surface-masked gray matter (GM) and conventional tissue-classified GM, (ii) surface matching between simulated and CLASP-extracted surfaces, and (iii) repeatability of the surface reconstruction among 16 MRI scans of the same subject. In the volume-based evaluation, the volume enclosed by the CLASP WM and GM surfaces matched the classified GM volume 13% more accurately than using conventional ASP. In the surface-based evaluation, using synthesized thick cortex, the average difference between simulated and extracted surfaces was 4.6 +/- 1.4 mm for conventional ASP and 0.5 +/- 0.4 mm for CLASP. In a repeatability study, CLASP produced a 30% lower RMS error for the GM surface and a 8% lower RMS error for the WM surface compared with ASP.