Genetic contributions to altered callosal morphology in schizophrenia

Microstructurally Informed Subject-Specific Parcellation of the Corpus Callosum using Axonal Water Fraction

The corpus callosum (CC) is the most important interhemispheric white matter (WM) structure composed of several anatomically and functionally distinct WM tracts. Resolving these tracts is a challenge since the callosum appears relatively homogenous in conventional structural imaging. Commonly used callosal parcellation methods such as the Hofer/Frahm scheme rely on rigid geometric guidelines to separate the substructures that are limited to consider individual variation. Here we present a novel subject-specific and microstructurally-informed method for callosal parcellation based on axonal water fraction (ƒ) known as a diffusion metric reflective of axon caliber and density. We studied 30 healthy subjects from the Human Connectome Project (HCP) dataset with multi-shell diffusion MRI. The biophysical parameter ƒ was derived from compartment-specific WM modeling. Inflection points were identified where there were concavity changes in ƒ across the CC to delineate callosal subregions. We observed relatively higher ƒ in anterior and posterior areas consisting of a greater number of small diameter fibers and lower ƒ in posterior body areas of the CC consisting of a greater number of large diameter fibers. Based on degree of change in ƒ along the callosum, seven callosal subregions can be consistently delineated for each individual. We observe that ƒ can capture differences in underlying tissue microstructures and seven subregions can be identified across CC. Therefore, this method provides microstructurally informed callosal parcellation in a subject-specific way, allowing for more accurate analysis in the corpus callosum.

Brain features of nearly drug-naïve female monozygotic twins with first-episode schizophrenia and the classification accuracy of brain feature patterns: A pilot study

BACKGROUND

Data on differences in brain features between monozygotic (MZ) twins with and without schizophrenia are scarce.

METHODS

We compared brain features of female MZ twins with and without first-episode schizophrenia and healthy controls (n = 20 each). Voxel-based morphometry and tract-based spatial statistics were used to analyze differences in brain structure. Whole-brain effective connectivity (EC) and functional connectivity (FC) networks were constructed using resting-state functional magnetic resonance imaging (rs-fMRI) data.

RESULTS

Female twins with schizophrenia exhibited abnormal gray matter volume (GMV) in the basal ganglia and prefrontal and parietal cortices, impairments in the arcuate fasciculus, and significant disruptions (primarily decreases) in nine EC networks. They exhibited rs-EC alterations involving the limbic areas and subcortex. Combined rs-EC and rs-FC data distinguished twins with first-episode schizophrenia with high accuracy. Combined consideration of structural and functional features enabled the distinction of female MZ twins with schizophrenia from those without schizophrenia and healthy controls with 100% accuracy.

CONCLUSIONS

Female MZ twins with schizophrenia exhibited increased GMV, white matter impairment, and disruptions in EC and FC networks. The combination of rs-EC + rs-FC data could distinguish female twins with schizophrenia from twins without schizophrenia and healthy controls with 97.4% accuracy, and the addition of structural brain features yielded a 100% accuracy rate. These findings may provide pivotal insight for further study of the mechanisms underlying schizophrenia.

Schizophrenia as a progressive brain disease

There is convincing evidence that schizophrenia is characterized by abnormalities in brain volume. At the Department of Psychiatry of the University Medical Centre Utrecht, Netherlands, we have been carrying out neuroimaging studies in schizophrenia since 1995. We focused our research on three main questions. First, are brain volume abnormalities static or progressive in nature? Secondly, can brain volume abnormalities in schizophrenia be explained (in part) by genetic influences? Finally, what environmental factors are associated with the brain volume abnormalities in schizophrenia?

Based on our findings we suggest that schizophrenia is a progressive brain disease. We showed different age-related trajectories of brain tissue loss suggesting that brain maturation that occurs in the third and fourth decade of life is abnormal in schizophrenia. Moreover, brain volume has been shown to be a useful phenotype for studying schizophrenia. Brain volume is highly heritable and twin and family studies show that unaffected relatives show abnormalities that are similar, but usually present to a lesser extent, to those found in the patients. However, also environmental factors play a role. Medication intake is indeed a confounding factor when interpreting brain volume (change) abnormalities, while independent of antipsychotic medication intake brain volume abnormalities appear influenced by the outcome of the illness.

In conclusion, schizophrenia can be considered as a progressive brain disease with brain volume abnormalities that are for a large part influenced by genetic factors. Whether the progressive volume change is also mediated by genes awaits the results of longitudinal twin analyses. One of the main challenges for the coming years, however, will be the search for gene-by-environment interactions on the progressive brain changes in schizophrenia.

Running in the Family? Structural Brain Abnormalities and IQ in Offspring, Siblings, Parents, and Co-twins of Patients with Schizophrenia

Structural brain abnormalities and cognitive deficits have been reported in patients with schizophrenia and to a lesser extent in their first-degree relatives (FDRs). Here we investigated whether brain abnormalities in nonpsychotic relatives differ per type of FDR and how these abnormalities are related to intelligent quotient (IQ). Nine hundred eighty individuals from 5 schizophrenia family cohorts (330 FDRs, 432 controls, 218 patients) were included. Effect sizes were calculated to compare brain measures of FDRs and patients with controls, and between each type of FDR. Analyses were repeated with a correction for IQ, having a nonpsychotic diagnosis, and intracranial volume (ICV). FDRs had significantly smaller ICV, surface area, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, thalamus, putamen, amygdala, and accumbens volumes as compared with controls (ds < -0.19, q < 0.05 corrected). Offspring showed the largest effect sizes relative to the other FDRs; however, none of the effects in the different relative types survived correction for multiple comparisons. After IQ correction, all effects disappeared in the FDRs after correction for multiple comparisons. The findings in FDRs were not explained by having a nonpsychotic disorder and were only partly explained by ICV. FDRs show brain abnormalities that are strongly covarying with IQ. On the basis of consistent evidence of genetic overlap between schizophrenia, IQ, and brain measures, we suggest that the brain abnormalities in FDRs are at least partly explained by genes predisposing to both schizophrenia risk and IQ.

Ethnicity Influences Corpus Callosum Dimensions

Background and Objective

Corpus callosum (CC), the main white matter cable which connects two hemispheres of brain, is important in special procedures such as stereotaxic surgeries vary in size, in different populations. Determination of possible size differences in ethnical groups has special values.

Patients and Methods

The size of the CC on midsagittal view was determined in 76 normal male subjects using MRI of brain hemispheres in northern Iran. The size of rostrum, body, splenium, length, and height of CC was measured for each subject. The width of the body of the corpus callosum (B), the anterior to posterior length (L) and the maximum height (H) of the corpus callosum, and ratios B/L and B/H were also calculated.

Results

The longitudinal dimensions of the CC were 70.21 mm and 74.05 mm in native Fars and Turkmens, respectively (P < 0.05). The heights were 25 mm and 25.75 mm in native Fars and Turkmen subjects, respectively. The width of CC in Turkmen people was significantly higher than native Fars people (P < 0.05). The Evans index in Turkmen group (0.314) was significantly higher than in native Fars (0.3). The B/L and B/H ratios were nonsignificantly different between two groups.

Conclusion

The CC parameters vary in different ethnical groups in northern Iran.

Quantitative magnetic resonance imaging traits as endophenotypes for genetic mapping in epilepsy

Over the last decade, the field of imaging genomics has combined high-throughput genotype data with quantitative magnetic resonance imaging (QMRI) measures to identify genes associated with brain structure, cognition, and several brain-related disorders. Despite its successful application in different psychiatric and neurological disorders, the field has yet to be advanced in epilepsy. In this article we examine the relevance of imaging genomics for future genetic studies in epilepsy from three perspectives. First, we discuss prior genome-wide genetic mapping efforts in epilepsy, considering the possibility that some studies may have been constrained by inherent theoretical and methodological limitations of the genome-wide association study (GWAS) method. Second, we offer a brief overview of the imaging genomics paradigm, from its original inception, to its role in the discovery of important risk genes in a number of brain-related disorders, and its successful application in large-scale multinational research networks. Third, we provide a comprehensive review of past studies that have explored the eligibility of brain QMRI traits as endophenotypes for epilepsy. While the breadth of studies exploring QMRI-derived endophenotypes in epilepsy remains narrow, robust syndrome-specific neuroanatomical QMRI traits have the potential to serve as accessible and relevant intermediate phenotypes for future genetic mapping efforts in epilepsy.

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QMRI traits have the potential to serve as robust intermediate phenotypes for brain-related disorders.

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Hippocampal volume is the most promising neuroimaging endophenotype for MTLE + HS.

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Imaging genomics holds great promise in advancing epilepsy genetic research.

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Studies are encouraged to explore the validity of QMRI traits as endophenotypes for epilepsy.

Single-shot T1 mapping of the corpus callosum: a rapid characterization of fiber bundle anatomy

Using diffusion-tensor magnetic resonance imaging and fiber tractography the topographic organization of the human corpus callosum (CC) has been described to comprise five segments with fibers projecting into prefrontal (I), premotor and supplementary motor (II), primary motor (III), and primary sensory areas (IV), as well as into parietal, temporal, and occipital cortical areas (V). In order to more rapidly characterize the underlying anatomy of these segments, this study used a novel single-shot T1 mapping method to quantitatively determine T1 relaxation times in the human CC. A region-of-interest analysis revealed a tendency for the lowest T1 relaxation times in the genu and the highest T1 relaxation times in the somatomotor region of the CC. This observation separates regions dominated by myelinated fibers with large diameters (somatomotor area) from densely packed smaller axonal bundles (genu) with less myelin. The results indicate that characteristic T1 relaxation times in callosal profiles provide an additional means to monitor differences in fiber anatomy, fiber density, and gray matter in respective neocortical areas. In conclusion, rapid T1 mapping allows for a characterization of the axonal architecture in an individual CC in less than 10 s. The approach emerges as a valuable means for studying neocortical brain anatomy with possible implications for the diagnosis of neurodegenerative processes.

Corpus callosum and motor development in healthy term infants

BACKGROUND

Corpus callosum atrophy has been associated with cognitive and motor deficits in elderly people. However, the role of the corpus callosum in infant development is unclear. The aim of this study was to assess the impact of corpus callosum size on motor development in infants.

METHODS

We investigated cerebral ultrasonograms performed on healthy infants aged 4 to 6 months. The correlation between the development of rolling over and corpus callosum size was calculated for determining odds ratios. Covariates, including gestational age, sex, age in months, and head circumference were tested using logistic regression.

RESULTS

We investigated 244 cerebral ultrasonograms performed on term infants from 2009 to 2011. The percentage of rolling over development in the examined infants increased with age (47.8%, 78.4%, and 97.5% at ages 4, 5, and 6 months, respectively). There was no significant difference in the development of rolling over between male (67.9%) and female (73.6%) children or among different gestational age groups. After the other covariates in the logistic model were adjusted, only age and corpus callosum size (length and thickness) were significantly associated with the development of rolling over: 3.86 times the odds (confidence interval, 2.1 to 7.0) for age in months, 1.14 times the odds (confidence interval, 1.0 to 1.3) for corpus callosum length, and 3.92 times the odds (confidence interval, 1.6 to 9.6) for corpus callosum thickness.

CONCLUSIONS

Corpus callosum size is positively associated with the development of rolling over in healthy term infants, independent of the gestational age, sex, age, and head circumference.

Corpus callosum and epilepsies

Introduction.Corpus callosum (CC) is the largest forebrain commissure. Structural anomalies and accompanying clinical symptoms are not in the focus of neurologists, epileptologists or neurosurgeons.

Aim and method.Anatomy, embryological development, normal functions, structural abnormalities, additional malformations, clinical symptoms and seizure disorders with CC anomalies are reviewed from the literature.

Review.The detection of callosal anomalies increased rapidly with widespread use of brain imaging methods. Agenesis or dysgenesis of corpus callosum (AgCC) might be considered an accidental finding. Epileptic seizures occur in up to 89% of patients with AgCC. The causal relationship correctly is questioned. However, additional causative malformations of midline and/or telencephalic structures can be demonstrated in most seizure patients. The interruption of bilateral spread of seizure activities acts as the concept for callosotomy as epilepsy surgery. Indications are drug-resistant generalized, diffuse, or multifocal epilepsies. A resectable seizure onset zone should be excluded. Most treated patients are diagnosed as Lennox-Gastaut or Lennox-like syndrome.

Conclusions.In cases with callosal abnormalities and clinical symptoms additional malformations are frequently observed, especially with seizure disorders. Callosotomy is the most effective option against drop attacks. The method probably is underused. After callosotomy a circumscript seizure focus might be unveiled and a second step of resective epilepsy surgery can be successful.

A review of neuroimaging studies of young relatives of individuals with schizophrenia: a developmental perspective from schizotaxia to schizophrenia

In an effort to identify the developing abnormalities preceding psychosis, Dr. Ming T. Tsuang and colleagues at Harvard expanded Meehl's concept of "schizotaxia," and examined brain structure and function in families affected by schizophrenia (SZ). Here, we systematically review genetic (familial) high-risk (HR) studies of SZ using magnetic resonance imaging (MRI), examine how findings inform models of SZ etiology, and suggest directions for future research. Neuroimaging studies of youth at HR for SZ through the age of 30 were identified through a MEDLINE (PubMed) search. There is substantial evidence of gray matter volume abnormalities in youth at HR compared to controls, with an accelerated volume reduction over time in association with symptoms and cognitive deficits. In structural neuroimaging studies, prefrontal cortex (PFC) alterations were the most consistently reported finding in HR. There was also consistent evidence of smaller hippocampal volume. In functional studies, hyperactivity of the right PFC during performance of diverse tasks with common executive demands was consistently reported. The only longitudinal fMRI study to date revealed increasing left middle temporal activity in association with the emergence of psychotic symptoms. There was preliminary evidence of cerebellar and default mode network alterations in association with symptoms. Brain abnormalities in structure, function and neurochemistry are observed in the premorbid period in youth at HR for SZ. Future research should focus on the genetic and environmental contributions to these alterations, determine how early they emerge, and determine whether they can be partially or fully remediated by innovative treatments.

[Are variations of structural neuro-anatomy promising endophenotype candidates in bipolar disorder?]

Bipolar disorder is a complex pathology which has a strong heritability component. Epidemiologic studies have pinpointed the contribution of genetic factors to the heritability component. The molecular studies, that have used classical genetic approaches, have been inconclusive at indentifying genes involved in the etiology of this disorder. To overcome these difficulties, a number of strategies have been developed. One of them is the endophenotypic approach. Its main scope is to identify biological markers that are influenced by genetic factors that are less complex than those involved in the clinical expression of the disorder. Thus, it is likely these markers will be more readily linked to specific genetic loci. In this article, we describe the main phenotypes of neuro-anatomic measurements that are widely used in research, and report data on their heritability in the general population. Then, we focus on the results of the few structural neuro-imaging studies that have been carried out in families of patients suffering of bipolar disorders. The current data converge to indicate that subtle structural abnormalities, particularly at the level white matter tracts, seem to be promising endophenotype candidates for bipolar disorder.

Statistical shape analysis of the corpus callosum in Schizophrenia

We present a statistical shape-analysis framework for characterizing and comparing morphological variation of the corpus callosum. The midsagittal boundary of the corpus callosum is represented by a closed curve and analyzed using an invariant shape representation. The shape space of callosal curves is endowed with a Riemannian metric. Shape distances are given by the length of shortest paths (geodesics) that are invariant to shape-confounding transformations. The statistical framework enables computation of shape averages and covariances on the shape space in an intrinsic manner (unique to the shape space). The statistical framework makes use of the tangent principal component approach to achieve dimension reduction on the space of corpus callosum shapes. The advantages of this approach are - it is fully automatic, invariant, and avoids the use of landmarks to define shapes. We applied our method to determine the effects of sex, age, schizophrenia and schizophrenia-related genetic liability on callosal shape in a large sample of patients and controls and their first-degree relatives (N=218). Results showed significant age, sex, and schizophrenia effects on both global and local callosal shape structure.

Automated analysis of fundamental features of brain structures

Automated image analysis of the brain should include measures of fundamental structural features such as size and shape. We used principal axes (P-A) measurements to measure overall size and shape of brain structures segmented from MR brain images. The rationale was that quantitative volumetric studies of brain structures would benefit from shape standardization as had been shown for whole brain studies. P-A analysis software was extended to include controls for variability in position and orientation to support individual structure spatial normalization (ISSN). The rationale was that ISSN would provide a bias-free means to remove elementary sources of a structure's spatial variability in preparation for more detailed analyses. We studied nine brain structures (whole brain, cerebral hemispheres, cerebellum, brainstem, caudate, putamen, hippocampus, inferior frontal gyrus, and precuneus) from the 40-brain LPBA40 atlas. This paper provides the first report of anatomical positions and principal axes orientations within a standard reference frame, in addition to "shape/size related" principal axes measures, for the nine brain structures from the LPBA40 atlas. Analysis showed that overall size (mean volume) for internal brain structures was preserved using shape standardization while variance was reduced by more than 50%. Shape standardization provides increased statistical power for between-group volumetric studies of brain structures compared to volumetric studies that control only for whole brain size. To test ISSN's ability to control for spatial variability of brain structures we evaluated the overlap of 40 regions of interest (ROIs) in a standard reference frame for the nine different brain structures before and after processing. Standardizations of orientation or shape were ineffective when not combined with position standardization. The greatest reduction in spatial variability was seen for combined standardizations of position, orientation and shape. These results show that ISSNs automated processing can be a valuable asset for measuring and controlling variability of fundamental features of brain structures.

Understanding aberrant white matter development in schizophrenia: an avenue for therapy?

Although historically gray matter changes have been the focus of neuropathological and neuroradiological studies in schizophrenia, in recent years an increasing body of research has implicated white matter structures and its constituent components (axons, their myelin sheaths and supporting oligodendrocytes). This article summarizes this body of literature, examining neuropathological, neurogenetic and neuroradiological evidence for white matter pathology in schizophrenia. We then look at the possible role that antipsychotic medication may play in these studies, examining both its role as a potential confounder in studies examining neuronal density and brain volume, but also the possible role that these medications may play in promoting myelination through their effects on oligodendrocytes. Finally, the role of potential novel therapies is discussed.

Mapping corticocortical structural integrity in schizophrenia and effects of genetic liability

BACKGROUND

Structural and diffusion tensor imaging studies implicate gray and white matter (WM) abnormalities and disruptions of neural circuitry in schizophrenia. However, the structural integrity of the superficial WM, comprising short-range association (U-fibers) and intracortical axons, has not been investigated in schizophrenia.

METHODS

High-resolution structural and diffusion tensor images and sophisticated cortical pattern matching methods were used to measure and compare global and local variations in superficial WM fractional anisotropy between schizophrenia patients and their relatives and community comparison subjects and their relatives (n = 150).

RESULTS

Compared with control subjects, patients showed reduced superficial WM fractional anisotropy distributed across each hemisphere, particularly in left temporal and bilateral occipital regions (all p < .05, corrected). Furthermore, by modeling biological risk for schizophrenia in patients, patient relatives, and control subjects, fractional anisotropy was shown to vary in accordance with relatedness to a patient in both hemispheres and in the temporal and occipital lobes (p < .05, corrected). However, effects did not survive correction procedures for two-group comparisons between patient relatives and control subjects.

CONCLUSIONS

Results extend previous findings restricted to deep WM pathways to demonstrate that disturbances in corticocortical connectivity are associated with schizophrenia and might indicate a genetic predisposition for the disorder. Because the structural integrity of WM plays a crucial role in the functionality of networks linking gray matter regions, disturbances in the coherence and organization of fibers at the juncture of the neuropil might relate to features of schizophrenia at least partially attributable to disease-related genetic factors.

Putative structural neuroimaging endophenotypes in schizophrenia: a comprehensive review of the current evidence

The genetic contribution to schizophrenia etiopathogenesis is underscored by the fact that the best predictor of developing schizophrenia is having an affected first-degree relative, which increases lifetime risk by tenfold, as well as the observation that when both parents are affected, the risk of schizophrenia increases to approximately 50%, compared with 1% in the general population. The search to elucidate the complex genetic architecture of schizophrenia has employed various approaches, including twin and family studies to examine co-aggregation of brain abnormalities, studies on genetic linkage and studies using genome-wide association to identify genetic variations associated with schizophrenia. ‘Endophenotypes’, or ‘intermediate phenotypes’, are potentially narrower constructs of genetic risk. Hypothetically, they are intermediate in the pathway between genetic variation and clinical phenotypes and can supposedly be implemented to assist in the identification of genetic diathesis for schizophrenia and, possibly, in redefining clinical phenomenology.

Mean diffusivity and fractional anisotropy as indicators of disease and genetic liability to schizophrenia

The goals of this study were to first determine whether the fractional anisotropy (FA) and mean diffusivity (MD) of major white matter pathways associate with schizophrenia, and secondly to characterize the extent to which differences in these metrics might reflect a genetic predisposition to schizophrenia. Differences in FA and MD were identified using a comprehensive atlas-based tract mapping approach using diffusion tensor imaging and high-resolution structural data from 35 patients, 28 unaffected first-degree relatives of patients, 29 community controls, and 14 first-degree relatives of controls. Schizophrenia patients had significantly higher MD in the following tracts compared to controls: the right anterior thalamic radiations, the forceps minor, the bilateral inferior fronto-occipital fasciculus (IFO), the temporal component of the left superior longitudinal fasciculus (tSLF), and the bilateral uncinate. FA showed schizophrenia effects and a linear relationship to genetic liability (represented by schizophrenia patients, first-degree relatives, and controls) for the bilateral IFO, the left inferior longitudinal fasciculus (ILF), and the left tSLF. Diffusion tensor imaging studies have previously identified white matter abnormalities in all three of these tracts in schizophrenia; however, this study is the first to identify a significant genetic liability. Thus, FA of these three tracts may serve as biomarkers for studies seeking to identify how genes influence brain structure predisposing to schizophrenia. However, differences in FA and MD in frontal and temporal white matter pathways may be additionally driven by state variables that involve processes associated with the disease.

Putative diffusion tensor neuroimaging endophenotypes in schizophrenia: a review of the early evidence

Although schizophrenia has a high heritability, the genetic effects conferring diathesis to schizophrenia are thought to be complex and underlain by multifactorial polygenic inheritance. ‘Endophenotypes’, or ‘intermediate phenotypes’, are narrowed constructs of genetic risk that are assumed to be more proximal to the gene effects in the disease pathway than clinical phenotypes. A current aim in schizophrenia research is to identify promising putative endophenotypes for use in molecular genetics studies. Recently, much of the focus has been on neurocognitive, conventional T1-weighted structural MRI, functional MRI and electrophysiological endophenotypes. Diffusion tensor imaging has emerged as another important structural neuroimaging modality in the aim to identify abnormalities in brain connectivity and diffusivity in schizophrenia, and abnormalities detected via this method may be promising candidate endophenotypes. In this article, we present the first comprehensive review of the early evidence that qualifies diffusion tensor abnormalities as potentially appropriate endophenotypes of schizophrenia.

Mapping corpus callosum morphology in twin pairs discordant for bipolar disorder

Callosal volume reduction has been observed in patients with bipolar disorder, but whether these deficits reflect genetic vulnerability to the illness remains unresolved. Here, we used computational methods to map corpus callosum abnormalities in a population-based sample of twin pairs discordant for bipolar disorder. Twenty-one probands with bipolar I disorder (mean age 44.4 ± 7.5 years; 48% female), 19 of their non-bipolar co-twins, and 34 demographically matched control twin individuals underwent magnetic resonance imaging. Three-dimensional callosal surface models were created to visualize its morphologic variability and to localize group differences. Neurocognitive correlates of callosal area differences were additionally investigated in a subsample of study participants. Bipolar (BPI) probands, but not their co-twins, showed significant callosal thinning and area reduction, most pronounced in the genu and splenium, relative to healthy twins. Altered callosal curvature was additionally observed in BPI probands. In bipolar probands and co-twins, genu and splenium midsagittal areas were significantly correlated with verbal processing speed and response inhibition. These findings suggest that aberrant connections between cortical regions--possibly reflecting decreased myelination of white matter tracts--may be involved in bipolar pathophysiology. However, findings of callosal thinning appear to be disease related, rather than reflecting genetic vulnerability to bipolar illness.

Characterization of the corpus callosum in very preterm and full-term infants utilizing MRI

The corpus callosum is the largest white matter tract, important for interhemispheric communication. The aim of this study was to investigate and compare corpus callosum size, shape and diffusion characteristics in 106 very preterm infants and 22 full-term infants. Structural and diffusion magnetic resonance images were obtained at term equivalent. The corpus callosum was segmented, cross-sectional areas were calculated, and shape was analyzed. Fractional anisotropy, mean, axial and radial diffusivity measures were obtained from within the corpus callosum, with additional probabilistic tractography analysis. Very preterm infants had significantly reduced callosal cross-sectional area compared with term infants (p=0.004), particularly for the mid-body and posterior sub-regions. Very preterm callosi were more circular (p=0.01). Fractional anisotropy was lower (p=0.007) and mean (p=0.006) and radial (p=0.001) diffusivity values were higher in very preterm infants' callosi, particularly at the anterior and posterior ends. The volume of tracts originating from the corpus callosum was reduced in very preterm infants (p=0.001), particularly for anterior mid-body (p=0.01) and isthmus tracts (p=0.04). This study characterizes callosal size, shape and diffusion in typically developing infants at term equivalent age, and reports macrostructural and microstructural abnormalities as a result of prematurity.

DTI studies of corpus callosum in bipolar disorder

Although the pathogenesis of bipolar disorder is still not completely understood, there is evidence from imaging studies that abnormalities in inter-hemispheric communication may play a major role in the pathophysiology of bipolar disorder. In the present review, we discuss the most consistent findings from diffusion imaging studies exploring corpus callosum integrity in bipolar disorder.

Probabilistic topography of human corpus callosum using cytoarchitectural parcellation and high angular resolution diffusion imaging tractography

The function of the corpus callosum (CC) is to distribute perceptual, motor, cognitive, learned, and voluntary information between the two hemispheres of the brain. Accurate parcellation of the CC according to fiber composition and fiber connection is of upmost important. In this work, population-based probabilistic connection topographies of the CC, in the standard Montreal Neurological Institute (MNI) space, are estimated by incorporating anatomical cytoarchitectural parcellation with high angular resolution diffusion imaging (HARDI) tractography. First, callosal fibers are extracted using multiple fiber assignment by continuous tracking algorithm based on q-ball imaging (QBI), on 12 healthy and young subjects. Then, the fiber tracts are aligned in the standard MNI coordinate system based on a tract-based transformation scheme. Next, twenty-eight Brodmann's areas on the surface of cortical cortex are registered to the MNI space to parcellate the aligned callosal fibers. Finally, the population-based topological subdivisions of the midsagittal CC to each cortical target are then mapped. And the resulting subdivisions of the CC that connect to the frontal and somatosensory associated cortex are also showed. To our knowledge, it is the first topographic subdivisions of the CC done using HARDI tractography and cytoarchitectonic information. In conclusion, this sophisticated topography of the CC may serve as a landmark to further understand the correlations between the CC, brain intercommunication, and functional cytoarchitectures.

Neuroanatomical asymmetry patterns in individuals with schizophrenia and their non-psychotic siblings

Neuroanatomical endophenotypes may reveal insights into the processes by which genetic factors increase the risk of developing schizophrenia. To determine whether patterns of neuroanatomical asymmetries may be useful as schizophrenia-related endophenotypes, we compared patterns of structural asymmetries in patients with schizophrenia, healthy controls, and their respective siblings. The surfaces of the left and right amygdala, hippocampus, thalamus, caudate nucleus, putamen, globus pallidus, and nucleus accumbens were assessed in 40 pairs of healthy comparison controls (CON) and their siblings (CON-SIB) and 25 pairs of patients with schizophrenia (SCZ) and their siblings (SCZ-SIB) in magnetic resonance (MR) images using large deformation diffeomorphic metric mapping (LDDMM) and parallel transport techniques. The within-subject asymmetry deformation of each structure was first measured via LDDMM, and then translated to a global template via parallel transport for evaluation of the patterns of asymmetry both within and across siblings. Our results revealed that asymmetries observed in CON subjects occurred in the amygdala and the anterior segment of the hippocampus with more pronounced expansion deformation in the right-sided structures (R>L asymmetry) but not in the basal ganglia and thalamus. Disturbance in this pattern of asymmetries was observed in both SCZ and SCZ-SIB subjects. More specifically, exaggerations and reductions in the normative pattern of asymmetries were observed in the amygdala-hippocampus formation, basal ganglia, and thalamus. These altered patterns of asymmetries are present in subjects with schizophrenia and their siblings, and therefore may represent a schizophrenia-related endophenotype.

Online resource for validation of brain segmentation methods

One key issue that must be addressed during the development of image segmentation algorithms is the accuracy of the results they produce. Algorithm developers require this so they can see where methods need to be improved and see how new developments compare with existing ones. Users of algorithms also need to understand the characteristics of algorithms when they select and apply them to their neuroimaging analysis applications. Many metrics have been proposed to characterize error and success rates in segmentation, and several datasets have also been made public for evaluation. Still, the methodologies used in analyzing and reporting these results vary from study to study, so even when studies use the same metrics their numerical results may not necessarily be directly comparable. To address this problem, we developed a web-based resource for evaluating the performance of skull-stripping in T1-weighted MRI. The resource provides both the data to be segmented and an online application that performs a validation study on the data. Users may download the test dataset, segment it using whichever method they wish to assess, and upload their segmentation results to the server. The server computes a series of metrics, displays a detailed report of the validation results, and archives these for future browsing and analysis. We applied this framework to the evaluation of 3 popular skull-stripping algorithms--the Brain Extraction Tool [Smith, S.M., 2002. Fast robust automated brain extraction. Hum. Brain Mapp. 17 (3),143-155 (Nov)], the Hybrid Watershed Algorithm [Ségonne, F., Dale, A.M., Busa, E., Glessner, M., Salat, D., Hahn, H.K., Fischl, B., 2004. A hybrid approach to the skull stripping problem in MRI. NeuroImage 22 (3), 1060-1075 (Jul)], and the Brain Surface Extractor [Shattuck, D.W., Sandor-Leahy, S.R., Schaper, K.A., Rottenberg, D.A., Leahy, R.M., 2001. Magnetic resonance image tissue classification using a partial volume model. NeuroImage 13 (5), 856-876 (May) under several different program settings. Our results show that with proper parameter selection, all 3 algorithms can achieve satisfactory skull-stripping on the test data.

Measuring fractional anisotropy of the corpus callosum using diffusion tensor imaging: mid-sagittal versus axial imaging planes

OBJECTIVE

Many diffusion tensor imaging (DTI) studies of the corpus callosum (CC) have been performed with a relatively thick slice thickness in the axial plane, which may result in underestimating the fractional anisotropy (FA) of the CC due to a partial volume effect. We hypothesized that the FA of the CC can be more accurately measured by using mid-sagittal DTI. We compared the FA values of the CC between the axial and mid-sagittal DTI.

MATERIALS AND METHODS

Fourteen healthy volunteers underwent MRI at 3.0 T. DTI was performed in both the mid-sagittal and axial planes. One 5-mm mid-sagittal image and twenty-five 2-mm axial images were obtained for the CC. The five regions of interest (ROIs) that included the prefrontal (I), premotor and supplementary motor (II), motor (III), sensory (IV) and parietal, temporal and occipital regions (V) were drawn along the border of the CC on each sagittal FA map. The FA values obtained from each region were compared between the two sagittal maps.

RESULTS

The FA values of all the regions, except for region V, were significantly increased on the mid-sagittal imaging. The FA values in region IV were significantly underestimated on the mid-sagittal image from the axial imaging, compared with those in the regions I and V (p = 0.037 and p = 0.001, respectively).

CONCLUSION

The FA values of the CC were significantly higher on the mid-sagittal DTI than those on the axial DTI in regions I-IV, and particularly in the region IV. Mid-sagittal DTI may provide more accurate FA values of the CC than can the axial DTI, and mid-sagittal DTI may be more desirable for studies that compare between patients and healthy subjects.

Statistical Modelling of Brain Morphological Measures Within Family Pedigrees

Large, family-based imaging studies can provide a better understanding of the interactions of environmental and genetic influences on brain structure and function. The interpretation of imaging data from large family studies, however, has been hindered by the paucity of well-developed statistical tools for that permit the analysis of complex imaging data together with behavioral and clinical data. In this paper, we propose to use two methods for these analyses. First, a variance components model along with score statistics is used to test linear hypotheses of unknown parameters, such as the associations of brain measures (e.g., cortical and subcortical surfaces) with their potential genetic determinants. Second, we develop a test procedure based on a resampling method to assess simultaneously the statistical significance of linear hypotheses across the entire brain. The value of these methods lies in their computational simplicity and in their applicability to a wide range of imaging data. Simulation studies show that our test procedure can accurately control the family-wise error rate. We apply our methods to the detection of statistical significance of gender-by-age interactions and of the effects of genetic variation on the thickness of the cerebral cortex in a family study of major depressive disorder.

The hippocampus in families with schizophrenia in relation to obstetric complications

BACKGROUND

Hippocampal volume reduction is a well replicated finding in schizophrenia. Evidence indicates a contribution of genetic and environmental factors, especially the influence of obstetric complications to this volume reduction. The aim of this study was to compare hippocampal volume of schizophrenic patients as well as and their relatives with control subjects and to quantify the additional contribution of obstetric complications.

METHODS

T1 weighted MRI brain scans of 50 schizophrenic patients, 88 first-degree relatives and 53 healthy control subjects were used to perform volumetric measurements on the left and right hippocampus. A set of clinical measures including obstetric complications were recorded for all family members.

RESULTS

Numerically our measurements revealed a hippocampal volume reduction in schizophrenic patients (left: -14%, right: -15%) and, although less pronounced, in their unaffected relatives (left: -6%, right: -10%). Noted differences in hippocampal volume between schizophrenic patients and controls were only significant for the left side. Hippocampal volumes of patients and their relatives with obstetric complications were reduced bilaterally.

CONCLUSIONS

Hippocampal volume reduction is present in schizophrenic patients and their first-degree relatives, suggesting an influence of genetic factors. In addition, however, obstetric complications have also been shown to play a major role.

Mapping callosal morphology in early- and late-onset elderly depression: an index of distinct changes in cortical connectivity

There is some evidence of corpus callosum abnormalities in elderly depression, but it is not known whether these deficits are region-specific or differ based on age at onset of depression. Twenty-four patients with early-onset depression (mean age = 68.00, SD+/-5.83), 22 patients with late-onset depression (mean age = 74.50, SD+/-8.09) and 34 elderly control subjects (mean age = 72.38; SD+/-6.93) were studied. Using 3D MRI data, novel mesh-based geometrical modeling methods were applied to compare the midsagittal thickness of the corpus callosum at high spatial resolution between groups. Neuropsychological correlates of midsagittal callosal area differences were additionally investigated in a subsample of subjects. Depressed patients exhibited significant callosal thinning in the genu and splenium compared to controls. Significant callosal thinning was restricted to the genu in early-onset patients, but patients with late-onset depression exhibited significant callosal thinning in both the genu and splenium relative to controls. The splenium of the corpus callosum was also significantly thinner in subjects with late- vs early-onset depression. Genu and splenium midsagittal areas significantly correlated with memory and attention functioning among late-onset depressed patients, but not early-onset depressed patients or controls. Circumscribed structural alterations in callosal morphology may distinguish late- from early-onset depression in the elderly. These findings suggest distinct abnormalities of cortical connectivity in late- and early-onset elderly depression with possible influence on the course of illness. Patients with a late onset of depression may be at higher risk of illness progression and eventually dementia conversion than early-onset depression, with potentially important implications for research and therapy.

Meta-analysis of magnetic resonance imaging studies of the corpus callosum in schizophrenia

OBJECTIVES

The corpus callosum plays a pivotal role in inter-hemispheric transfer and integration of information. Magnetic resonance studies have reported callosal abnormalities in schizophrenia but findings have been inconsistent. Uncertainty has persisted despite a meta-analytic evaluation of this structure several years ago. We set out to perform a further meta-analysis with the addition of the numerous reports published on the subject to test the hypothesis that the corpus callosum is abnormal in schizophrenia.

METHOD

A systematic search was carried out to identify suitable magnetic resonance studies which reported callosal areas in schizophrenia compared to controls. Results from the retrieved studies were compared in a meta-analysis whilst the influence of biological and clinical variables on effect size was ascertained with meta-regression analysis.

RESULTS

Twenty-eight studies were identified. Corpus callosum area was reduced in schizophrenia in comparison to healthy volunteers. This effect was larger in first episode patients. Similarly, heterogeneity detected among the studies was associated with course of illness indicating that chronic subjects with schizophrenia showed larger callosal areas. There was no evidence of publication bias.

CONCLUSIONS

This study confirms the presence of reduced callosal areas in schizophrenia. The effect is of a larger magnitude at first presentation and less so in subjects with a chronic course generally medicated with antipsychotics.

Construction of a 3D probabilistic atlas of human cortical structures

We describe the construction of a digital brain atlas composed of data from manually delineated MRI data. A total of 56 structures were labeled in MRI of 40 healthy, normal volunteers. This labeling was performed according to a set of protocols developed for this project. Pairs of raters were assigned to each structure and trained on the protocol for that structure. Each rater pair was tested for concordance on 6 of the 40 brains; once they had achieved reliability standards, they divided the task of delineating the remaining 34 brains. The data were then spatially normalized to well-known templates using 3 popular algorithms: AIR5.2.5's nonlinear warp (Woods et al., 1998) paired with the ICBM452 Warp 5 atlas (Rex et al., 2003), FSL's FLIRT (Smith et al., 2004) was paired with its own template, a skull-stripped version of the ICBM152 T1 average; and SPM5's unified segmentation method (Ashburner and Friston, 2005) was paired with its canonical brain, the whole head ICBM152 T1 average. We thus produced 3 variants of our atlas, where each was constructed from 40 representative samples of a data processing stream that one might use for analysis. For each normalization algorithm, the individual structure delineations were then resampled according to the computed transformations. We next computed averages at each voxel location to estimate the probability of that voxel belonging to each of the 56 structures. Each version of the atlas contains, for every voxel, probability densities for each region, thus providing a resource for automated probabilistic labeling of external data types registered into standard spaces; we also computed average intensity images and tissue density maps based on the three methods and target spaces. These atlases will serve as a resource for diverse applications including meta-analysis of functional and structural imaging data and other bioinformatics applications where display of arbitrary labels in probabilistically defined anatomic space will facilitate both knowledge-based development and visualization of findings from multiple disciplines.

Brain neuroplasticity in healthy, hyperactive and psychotic children: insights from neuroimaging

Noninvasive brain imaging permits longitudinal studies of anatomic brain development in healthy and psychiatrically ill children. The time course for gray matter maturation varies by region and parallels earlier histological studies, indicating dynamic patterns of overproduction and regression. Developmental trajectories vary in relation to gender, intelligence, and overall functioning. Twin studies show high heritability for brain volumes, which varies with region and with age. Diagnostically specific, illness-related changes as well as outcome-associated plastic response are observed as illustrated for two pediatric populations, childhood-onset schizophrenia and attention-deficit/hyperactivity disorder, conditions which may be, in part, disorders of brain plasticity.

Cortical mapping of genotype-phenotype relationships in schizophrenia

Although schizophrenia is highly heritable, the search for susceptibility genes has been challenging. The "endophenotype" approach is an alternative method for measuring phenotypic variation that may make it easier to identify susceptibility genes in the context of complexly inherited traits. Neuroimaging methods in particular offer a powerful way to bridge the neurobiology of genes and behavior. Such investigations may be further empowered by complementary strategies involving chromosomal abnormalities associated with schizophrenia, which can help to localize causative genes and better understand the genetic complexity of the illness. Here, we illustrate our use of these convergent approaches, with a focus on neuroimaging studies using novel computational brain mapping algorithms, to investigate genetic influences on brain structure in the development of psychosis. These studies provide compelling evidence that specific genetic loci suspected to predispose to schizophrenia may affect quantitative variation in neural indicators underlying the neurobehavioral phenotype, and illustrate how genetic-neuroimaging paradigms can improve our understanding of the pathogenesis of this highly disabling mental illness.

A statistical analysis of brain morphology using wild bootstrapping

Methods for the analysis of brain morphology, including voxel-based morphology and surface-based morphometries, have been used to detect associations between brain structure and covariates of interest, such as diagnosis, severity of disease, age, IQ, and genotype. The statistical analysis of morphometric measures usually involves two statistical procedures: 1) invoking a statistical model at each voxel (or point) on the surface of the brain or brain subregion, followed by mapping test statistics (e.g., t test) or their associated p values at each of those voxels; 2) correction for the multiple statistical tests conducted across all voxels on the surface of the brain region under investigation. We propose the use of new statistical methods for each of these procedures. We first use a heteroscedastic linear model to test the associations between the morphological measures at each voxel on the surface of the specified subregion (e.g., cortical or subcortical surfaces) and the covariates of interest. Moreover, we develop a robust test procedure that is based on a resampling method, called wild bootstrapping. This procedure assesses the statistical significance of the associations between a measure of given brain structure and the covariates of interest. The value of this robust test procedure lies in its computationally simplicity and in its applicability to a wide range of imaging data, including data from both anatomical and functional magnetic resonance imaging (fMRI). Simulation studies demonstrate that this robust test procedure can accurately control the family-wise error rate. We demonstrate the application of this robust test procedure to the detection of statistically significant differences in the morphology of the hippocampus over time across gender groups in a large sample of healthy subjects.

Neuroimaging endophenotypes: strategies for finding genes influencing brain structure and function

It is vitally important to identify the genetic determinants of complex brain-related disorders such as autism, dementia, mood disorders, and schizophrenia. However, the search for genes predisposing individuals to these illnesses has been hampered by their genetic and phenotypic complexity and by reliance upon phenomenologically based qualitative diagnostic systems. Neuroimaging endophenotypes are quantitative indicators of brain structure or function that index genetic liability for an illness. These indices will significantly improve gene discovery and help us to understand the functional consequences of specific genes at the level of systems neuroscience. Here, we review the feasibility of using neuroanatomic and neuropsychological measures as endophenotypes for brain-related disorders. Specifically, we examine specific indices of brain structure or function that are genetically influenced and associated with neurological and psychiatric illness. In addition, we review genetic approaches that capitalize on the use of quantitative traits, including those derived from brain images.

Direct mapping of hippocampal surfaces with intrinsic shape context

We propose in this paper a new method for the mapping of hippocampal (HC) surfaces to establish correspondences between points on HC surfaces and enable localized HC shape analysis. A novel geometric feature, the intrinsic shape context, is defined to capture the global characteristics of the HC shapes. Based on this intrinsic feature, an automatic algorithm is developed to detect a set of landmark curves that are stable across population. The direct map between a source and target HC surface is then solved as the minimizer of a harmonic energy function defined on the source surface with landmark constraints. For numerical solutions, we compute the map with the approach of solving partial differential equations on implicit surfaces. The direct mapping method has the following properties: (1) it has the advantage of being automatic; (2) it is invariant to the pose of HC shapes. In our experiments, we apply the direct mapping method to study temporal changes of HC asymmetry in Alzheimer's disease (AD) using HC surfaces from 12 AD patients and 14 normal controls. Our results show that the AD group has a different trend in temporal changes of HC asymmetry than the group of normal controls. We also demonstrate the flexibility of the direct mapping method by applying it to construct spherical maps of HC surfaces. Spherical harmonics (SPHARM) analysis is then applied and it confirms our results on temporal changes of HC asymmetry in AD.

Shape variability of the human striatum—Effects of age and gender

Human striatum is involved in the regulation of movement, reinforcement, learning, reward, cognitive functioning, and addiction. Previous classical volumetric MRI studies have implicated age-, disease- and medication-related changes in striatal structures. Yet, no studies to date have addressed the effects of these factors on the shape variability and local structural alterations in the striatum. The local alterations may provide meaningful additional information in the context of functional neuroanatomy and brain connectivity. We developed image analysis methodology for the measurement of the volume and local shape variability of the human striatum. The method was applied in a group of 43 healthy controls to study the effects of age and gender on striatal shape variability. In the volume analysis, the volume of the striatum was normalized using the volume of the whole brain. In the local shape analysis, the deviations from a mean surface were studied for each surface point using high-dimensional mapping. Also, discriminant functions were constructed from a statistical shape model. The accuracy and reproducibility of the methods used were evaluated. The results confirmed that the volume of the striatum decreases as a function of age. However, the volume decrease was not uniform and age-related shape differences were observed in several subregions of the human striatum whereas no local gender differences were seen. Examination of the variability of striatal shape in the healthy population will pave the way for applying this method in clinical settings. This method will be particularly useful for investigating neuropsychiatric disorders that are associated with subtle morphological alterations of the brain, such as schizophrenia.

Lipoma on the corpus callosum in a patient with schizophrenia-like episode: is there a causal relationship?

Disturbed interhemispheric communication has been proposed as responsible for schizophrenia. We present a case of a schizophrenia-like episode with no neurologic or other psychiatric symptoms. However, magnetic resonance imaging revealed a lipoma on the splenium of the corpus callosum. Neuropsychologic examination revealed normal interhemispheric transfer, but a slight dysfunction associated with right-hemispheric anterior regions. Rather than supporting the hypothesis of a causal relationship between callosal abnormality and schizophrenia-like symptoms, our findings argue against a direct causal relationship between lesion site and psychotic episode. We conclude that cerebral abnormality per se may represent a risk factor for neuropsychiatric symptoms.

Mapping corpus callosum deficits in autism: an index of aberrant cortical connectivity

BACKGROUND

Volumetric studies have reported reductions in the size of the corpus callosum (CC) in autism, but the callosal regions contributing to this deficit have differed among studies. In this study, a computational method was used to detect and map the spatial pattern of CC abnormalities in male patients with autism.

METHODS

Twenty-four boys with autism (aged 10.0 +/- 3.3 years) and 26 control boys (aged 11.0 +/- 2.5 years) underwent a magnetic resonance imaging (MRI) scan at 3 Tesla. Total and regional areas of the CC were determined using traditional morphometric methods. Three-dimensional (3D) surface models of the CC were also created from the MRI scans. Statistical maps were created to visualize morphologic variability of the CC and to localize regions of callosal thinning in autism.

RESULTS

Traditional morphometric methods detected a significant reduction in the total callosal area and in the anterior third of the CC in patients with autism; however, 3D maps revealed significant reductions in both the splenium and genu of the CC in patients.

CONCLUSIONS

Statistical maps of the CC revealed callosal deficits in autism with greater precision than traditional morphometric methods. These abnormalities suggest aberrant connections between cortical regions, which is consistent with the hypothesis of abnormal cortical connectivity in autism.

Topography of the human corpus callosum revisited--comprehensive fiber tractography using diffusion tensor magnetic resonance imaging

Several tracing studies have established a topographical distribution of fiber connections to the cortex in midsagittal cross-sections of the corpus callosum (CC). The most prominent example is Witelson's scheme, which defines five vertical partitions mainly based on primate data. Conventional MRI of the human CC does not reveal morphologically discernable structures, although microscopy techniques identified myelinated axons with a relatively small diameter in the anterior and posterior third of the CC as opposed to thick fibers in the midbody and posterior splenium. Here, we applied diffusion tensor imaging (DTI) in conjunction with a tract-tracing algorithm to gain cortical connectivity information of the CC in individual subjects. With DTI-based tractography, we distinguished five vertical segments of the CC, containing fibers projecting into prefrontal, premotor (and supplementary motor), primary motor, and primary sensory areas as well as into parietal, temporal, and occipital cortical areas. Striking differences to Witelson's classification were recognized in the midbody and anterior third of the CC. In particular, callosal motor fiber bundles were found to cross the CC in a much more posterior location than previously indicated. Differences in water mobility were found to be in qualitative agreement with differences in the microstructure of transcallosal fibers yielding the highest anisotropy in posterior regions of the CC. The lowest anisotropy was observed in compartments assigned to motor and sensory cortical areas. In conclusion, DTI-based fiber tractography of healthy human subjects suggests a modification of the widely accepted Witelson scheme and a new classification of vertical CC partitions.

Gray and white matter density changes in monozygotic and same-sex dizygotic twins discordant for schizophrenia using voxel-based morphometry

Global gray matter brain tissue volume decreases in schizophrenia have been associated to disease-related (possibly nongenetic) factors. Global white matter brain tissue volume decreases were related to genetic risk factors for the disease. However, which focal gray and white matter brain regions best reflect the genetic and environmental risk factors in the brains of patients with schizophrenia remains unresolved. 1.5-T MRI brain scans of 11 monozygotic and 11 same-sex dizygotic twin-pairs discordant for schizophrenia were compared to 11 monozygotic and 11 same-sex dizygotic healthy control twin-pairs using voxel-based morphometry. Linear regression analysis was done in each voxel for the average and difference in gray and white matter density separately, in each twin-pair, with group (discordant, healthy) and zygosity (monozygotic, dizygotic) as between subject variables, and age, sex and handedness as covariates. The t-maps (critical threshold value mid R:tmid R: > 6.0, P < 0.05) revealed a focal decrease in gray matter density accompanied by a focal increase in white matter density in the left medial orbitofrontal gyrus and a focal decrease in white matter density in the left sensory motor gyrus in twin-pairs discordant for schizophrenia as compared to healthy twin-pairs. Focal changes in left medial (orbito)frontal and left sensory motor gyri may reflect the increased genetic risk to develop schizophrenia. Focal changes in the left anterior hemisphere may therefore be particularly relevant as endophenotype in genetic studies of schizophrenia.

Genetics of brain structure and intelligence

Genetic influences on brain morphology and IQ are well studied. A variety of sophisticated brain-mapping approaches relating genetic influences on brain structure and intelligence establishes a regional distribution for this relationship that is consistent with behavioral studies. We highlight those studies that illustrate the complex cortical patterns associated with measures of cognitive ability. A measure of cognitive ability, known as g, has been shown highly heritable across many studies. We argue that these genetic links are partly mediated by brain structure that is likewise under strong genetic control. Other factors, such as the environment, obviously play a role, but the predominant determinant appears to be genetic.

Cortical thinning in cingulate and occipital cortices in first episode schizophrenia

BACKGROUND

Postmortem studies examining discrete regions show reduced cortical thickness in schizophrenia. Computational image analysis methods allow spatially detailed cortical thickness measurements across the entire cortex in 3D, but have not addressed thickness changes in cingulate or other cortices bordering the medial walls of the cerebral hemispheres in first episode schizophrenia.

METHODS

Magnetic resonance images and cortical pattern matching methods were used to compare gray matter thickness, measured at sub-voxel resolution at thousands of spatially equivalent locations on the medial hemispheric surfaces, between 72 (51m/21f) first episode schizophrenia patients and 78 (37m/41f) healthy controls similar in age. Group differences were mapped in 3D, and their overall significance was confirmed by permutation testing.

RESULTS

Patients with little or no prior antipsychotic medication treatment showed significant cortical thinning within cingulate, occipital and frontopolar cortices with no significant increases in any cortical location. Regional sex differences were observed with pronounced thinning in the left paracentral lobule and right posterior cingulate in male and female patients respectively compared to same sex controls.

CONCLUSIONS

Cortical thinning may correspond to cytoarchitectural and neurochemical abnormalities observed in similar anatomic locations and may underlie systems-wise disturbances that include heteromodal association cortices, where cortical thinning has been previously observed in first episode schizophrenia.

Morphometric analysis of lateral ventricles in schizophrenia and healthy controls regarding genetic and disease-specific factors

The structural variability of lateral ventricles is poorly understood notwithstanding that enlarged size has been identified as an unspecific marker for psychiatric illness, including schizophrenia. This paper explores the effects of heritability and genetic risk for schizophrenia reflected in ventricular size and structure. We examined ventricular size and shape in the MRI studies of monozygotic (MZ) twin pairs discordant for schizophrenia (DS), healthy MZ twin pairs, healthy dizygotic twin pairs, and healthy nonrelated subject pairs. Heritability and effect due to disease were analyzed in two tests. First, heritability was examined by ventricle similarity between pairs of co-twins. Results show that co-twin ventricle shape similarity decreases with decreasing genetic identity, an effect not seen in the volume analysis. Co-twin shape similarity of healthy MZ twins did not differ from DS MZ twins. Second, the disease effect was examined through the ventricular differences of DS subjects to a template shape representing healthy subjects. Affected DS twins showed shape differences from healthy subjects on the left and right sides. Interestingly, unaffected DS twins also showed significant shape differences from healthy subjects for both sides. Volume comparisons did not show differences between these groups. Locality of shape difference suggests that the ventricular shape of the anterior and posterior regions is under genetic influence in both healthy controls and schizophrenia patients. Affected and unaffected groups demonstrate main shape differences, compared with healthy controls, only in the posterior region. Our results suggest that genetics have a stronger influence on the shape of lateral ventricles than do the disease-related changes in schizophrenia.

Brain structural mapping using a novel hybrid implicit/explicit framework based on the level-set method

This paper presents a novel approach to feature-based brain image warping, by using a hybrid implicit/explicit framework, which unifies many prior approaches in a common framework. In the first step, we develop links between image warping and the level-set method, and we formulate the fundamental mathematics required for this hybrid implicit/explicit approach. In the second step, we incorporate the large-deformation models into these formulations, leading to a complete and elegant treatment of anatomical structure matching. In this latest approach, exact matching of anatomy is achieved by comparing the target to the warped source structure under the forward mapping and the source to the warped target structure under the backward mapping. Because anatomy is represented nonparametrically, a path is constructed linking the source to the target structure without prior knowledge of their point correspondence. The final point correspondence is constructed based on the linking path with the minimal energy. Intensity-similarity measures can be naturally incorporated in the same framework as landmark constraints by combining them in the gradient descent body forces. We illustrate the approach with two applications: (1) tensor-based morphometry of the corpus callosum in autistic children; and (2) matching cortical surfaces to measure the profile of cortical anatomic variation. In summary, the new mathematical techniques introduced here contribute fundamentally to the mapping of brain structure and its variation and provide a framework that unites feature and intensity-based image registration techniques.

Smaller corpus callosum subregions containing motor fibers in schizophrenia

Neuropsychological and neurophysiological studies provide evidence for abnormal interhemispheric communication in schizophrenia. These abnormalities may have a substrate in structural irregularities of the corpus callosum. This study investigated schizophrenia patients (n=27) and healthy comparison subjects (n=31). Global and regional measurements of the corpus callosum were acquired from one midsagittal SPGR slice. Eight subregions were approximately matched to fiber pathways from cortical regions. Overall effects of diagnosis [Wilks' Lambda F(8,46)=2.45, p=0.03] and diagnosis by age interaction [Wilks' Lambda F(8,46)=2.58, p=0.02] were found in a MANCOVA of the eight functionally specific subregions. Specifically, chronic schizophrenia was associated with a smaller rostral body [lower by 6.9%, F(1,53)=9.70, p=0.003] and anterior midbody [lower by 9.7%, F(1,53)=4.89, p=0.03] subregions. The rostral body and anterior midbody subregions of the corpus callosum primarily have premotor, supplementary motor, and motor cortical fibers transversing through them. Functional abnormalities of the associated cortical regions are reported in schizophrenia. These novel findings suggest that structural abnormalities of the corpus callosum exist in schizophrenia, with perhaps the motor-specific subregions affected more than others. Structural differences in the corpus callosum may be a substrate for interhemispheric functional dysconnectivity in schizophrenia.

Ventricular size mapping in a transgenic model of schizophrenia

Genetically engineered mice have been generated to model a variety of neurological disorders. The chakragati (ckr) mouse is beginning to provide valuable insights into the structural brain changes underlying certain manifestations of schizophrenia. For instance, these mice show enlargement of the lateral ventricles, an abnormality frequently reported as a structural aberration in the schizophrenic brain. As neither the anatomical pattern nor the timing of this ventricular enlargement is known, we used magnetic resonance imaging (MRI) techniques to non-invasively visualize the development of the ventricular system in 5-, 10- and 30-day-old ckr pups. High-resolution MR images obtained from these mutants showed a progressive enlargement of the lateral ventricles, starting at day 5 of postnatal life. These emerging deficits were associated with abnormalities in mid-saggital corpus callosum area and thickness, particularly in 30-day-old adolescent animals. At this time of development, aberrant behaviors that mimic certain symptoms of schizophrenia also appeared in ckr mice suggesting that structural changes in ventricular size predates the onset of psychotic-like behaviors. These results are viewed as further indication that pre- and peri-natal disturbances of the ventricular system and adjacent neural regions may be important pathogenic factors in schizophrenia. Application of MRI to the ckr mouse is relatively new but has great potential for clarifying the relationship between brain structure changes and genetically induced vulnerabilities to psychoses.