878 resultados para Corpus callosum agenesis


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The NTRK3 gene (also known as TRKC) encodes a high affinity receptor for the neurotrophin 3'-nucleotidase (NT3), which is implicated in oligodendrocyte and myelin development. We previously found that white matter integrity in young adults is related to common variants in genes encoding neurotrophins and their receptors. This underscores the importance of neurotrophins for white matter development. NTRK3 variants are putative risk factors for schizophrenia, bipolar disorder, and obsessive-compulsive disorder hoarding, suggesting that some NTRK3 variants may affect the brain.To test this, we scanned 392 healthy adult twins and their siblings (mean age, 23.6. ±. 2.2. years; range: 20-29. years) with 105-gradient 4-Tesla diffusion tensor imaging (DTI). We identified 18 single nucleotide polymorphisms (SNPs) in the NTRK3 gene that have been associated with neuropsychiatric disorders. We used a multi-SNP model, adjusting for family relatedness, age, and sex, to relate these variants to voxelwise fractional anisotropy (FA) - a DTI measure of white matter integrity.FA was optimally predicted (based on the highest false discovery rate critical p), by five SNPs (rs1017412, rs2114252, rs16941261, rs3784406, and rs7176429; overall FDR critical p=. 0.028). Gene effects were widespread and included the corpus callosum genu and inferior longitudinal fasciculus - regions implicated in several neuropsychiatric disorders and previously associated with other neurotrophin-related genetic variants in an overlapping sample of subjects. NTRK3 genetic variants, and neurotrophins more generally, may influence white matter integrity in brain regions implicated in neuropsychiatric disorders.

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We defined a new statistical fluid registration method with Lagrangian mechanics. Although several authors have suggested that empirical statistics on brain variation should be incorporated into the registration problem, few algorithms have included this information and instead use regularizers that guarantee diffeomorphic mappings. Here we combine the advantages of a large-deformation fluid matching approach with empirical statistics on population variability in anatomy. We reformulated the Riemannian fluid algorithmdeveloped in [4], and used a Lagrangian framework to incorporate 0 th and 1st order statistics in the regularization process. 92 2D midline corpus callosum traces from a twin MRI database were fluidly registered using the non-statistical version of the algorithm (algorithm 0), giving initial vector fields and deformation tensors. Covariance matrices were computed for both distributions and incorporated either separately (algorithm 1 and algorithm 2) or together (algorithm 3) in the registration. We computed heritability maps and two vector and tensorbased distances to compare the power and the robustness of the algorithms.

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In this paper, we used a nonconservative Lagrangian mechanics approach to formulate a new statistical algorithm for fluid registration of 3-D brain images. This algorithm is named SAFIRA, acronym for statistically-assisted fluid image registration algorithm. A nonstatistical version of this algorithm was implemented, where the deformation was regularized by penalizing deviations from a zero rate of strain. In, the terms regularizing the deformation included the covariance of the deformation matrices Σ and the vector fields (q). Here, we used a Lagrangian framework to reformulate this algorithm, showing that the regularizing terms essentially allow nonconservative work to occur during the flow. Given 3-D brain images from a group of subjects, vector fields and their corresponding deformation matrices are computed in a first round of registrations using the nonstatistical implementation. Covariance matrices for both the deformation matrices and the vector fields are then obtained and incorporated (separately or jointly) in the nonconservative terms, creating four versions of SAFIRA. We evaluated and compared our algorithms' performance on 92 3-D brain scans from healthy monozygotic and dizygotic twins; 2-D validations are also shown for corpus callosum shapes delineated at midline in the same subjects. After preliminary tests to demonstrate each method, we compared their detection power using tensor-based morphometry (TBM), a technique to analyze local volumetric differences in brain structure. We compared the accuracy of each algorithm variant using various statistical metrics derived from the images and deformation fields. All these tests were also run with a traditional fluid method, which has been quite widely used in TBM studies. The versions incorporating vector-based empirical statistics on brain variation were consistently more accurate than their counterparts, when used for automated volumetric quantification in new brain images. This suggests the advantages of this approach for large-scale neuroimaging studies.

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Genetic and environmental factors influence brain structure and function profoundly. The search for heritable anatomical features and their influencing genes would be accelerated with detailed 3D maps showing the degree to which brain morphometry is genetically determined. As part of an MRI study that will scan 1150 twins, we applied Tensor-Based Morphometry to compute morphometric differences in 23 pairs of identical twins and 23 pairs of same-sex fraternal twins (mean age: 23.8 ± 1.8 SD years). All 92 twins' 3D brain MRI scans were nonlinearly registered to a common space using a Riemannian fluid-based warping approach to compute volumetric differences across subjects. A multi-template method was used to improve volume quantification. Vector fields driving each subject's anatomy onto the common template were analyzed to create maps of local volumetric excesses and deficits relative to the standard template. Using a new structural equation modeling method, we computed the voxelwise proportion of variance in volumes attributable to additive (A) or dominant (D) genetic factors versus shared environmental (C) or unique environmental factors (E). The method was also applied to various anatomical regions of interest (ROIs). As hypothesized, the overall volumes of the brain, basal ganglia, thalamus, and each lobe were under strong genetic control; local white matter volumes were mostly controlled by common environment. After adjusting for individual differences in overall brain scale, genetic influences were still relatively high in the corpus callosum and in early-maturing brain regions such as the occipital lobes, while environmental influences were greater in frontal brain regions that have a more protracted maturational time-course.

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Brain-derived neurotrophic factor (BDNF) plays a key role in learning and memory, but its effects on the fiber architecture of the living brain are unknown. We genotyped 455 healthy adult twins and their non-twin siblings (188 males/267 females; age: 23.7 ± 2.1. years, mean ± SD) and scanned them with high angular resolution diffusion tensor imaging (DTI), to assess how the BDNF Val66Met polymorphism affects white matter microstructure. By applying genetic association analysis to every 3D point in the brain images, we found that the Val-BDNF genetic variant was associated with lower white matter integrity in the splenium of the corpus callosum, left optic radiation, inferior fronto-occipital fasciculus, and superior corona radiata. Normal BDNF variation influenced the association between subjects' performance intellectual ability (as measured by Object Assembly subtest) and fiber integrity (as measured by fractional anisotropy; FA) in the callosal splenium, and pons. BDNF gene may affect the intellectual performance by modulating the white matter development. This combination of genetic association analysis and large-scale diffusion imaging directly relates a specific gene to the fiber microstructure of the living brain and to human intelligence.

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Large multi-site image-analysis studies have successfully discovered genetic variants that affect brain structure in tens of thousands of subjects scanned worldwide. Candidate genes have also associated with brain integrity, measured using fractional anisotropy in diffusion tensor images (DTI). To evaluate the heritability and robustness of DTI measures as a target for genetic analysis, we compared 417 twins and siblings scanned on the same day on the same high field scanner (4-Tesla) with two protocols: (1) 94-directions; 2mm-thick slices, (2) 27-directions; 5mm-thickness. Using mean FA in white matter ROIs and FA skeletons derived using FSL, we (1) examined differences in voxelwise means, variances, and correlations among the measures; and (2) assessed heritability with structural equation models, using the classical twin design. FA measures from the genu of the corpus callosum were highly heritable, regardless of protocol. Genome-wide analysis of the genu mean FA revealed differences across protocols in the top associations.

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Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20-30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ∼ 6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.

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A key question in diffusion imaging is how many diffusion-weighted images suffice to provide adequate signal-to-noise ratio (SNR) for studies of fiber integrity. Motion, physiological effects, and scan duration all affect the achievable SNR in real brain images, making theoretical studies and simulations only partially useful. We therefore scanned 50 healthy adults with 105-gradient high-angular resolution diffusion imaging (HARDI) at 4T. From gradient image subsets of varying size (6 ≤ N ≤ 94) that optimized a spherical angular distribution energy, we created SNR plots (versus gradient numbers) for seven common diffusion anisotropy indices: fractional and relative anisotropy (FA, RA), mean diffusivity (MD), volume ratio (VR), geodesic anisotropy (GA), its hyperbolic tangent (tGA), and generalized fractional anisotropy (GFA). SNR, defined in a region of interest in the corpus callosum, was near-maximal with 58, 66, and 62 gradients for MD, FA, and RA, respectively, and with about 55 gradients for GA and tGA. For VR and GFA, SNR increased rapidly with more gradients. SNR was optimized when the ratio of diffusion-sensitized to non-sensitized images was 9.13 for GA and tGA, 10.57 for FA, 9.17 for RA, and 26 for MD and VR. In orientation density functions modeling the HARDI signal as a continuous mixture of tensors, the diffusion profile reconstruction accuracy rose rapidly with additional gradients. These plots may help in making trade-off decisions when designing diffusion imaging protocols.

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Background Although there are many structural neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) in children, there are inconsistencies across studies and no consensus regarding which brain regions show the most robust area or volumetric reductions relative to control subjects. Our goal was to statistically analyze structural imaging data via a meta-analysis to help resolve these issues. Methods We searched the MEDLINE and PsycINFO databases through January 2005. Studies must have been written in English, used magnetic resonance imaging, and presented the means and standard deviations of regions assessed. Data were extracted by one of the authors and verified independently by another author. Results Analyses were performed using STATA with metan, metabias, and metainf programs. A meta-analysis including all regions across all studies indicated global reductions for ADHD subjects compared with control subjects, standardized mean difference equal to .408, p less than .001. Regions most frequently assessed and showing the largest differences included cerebellar regions, the splenium of the corpus callosum, total and right cerebral volume, and right caudate. Several frontal regions assessed in only two studies also showed large significant differences. Conclusions This meta-analysis provides a quantitative analysis of neuroanatomical abnormalities in ADHD and information that can be used to guide future studies.

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The concept of vascular cognitive impairment (VCI) covers a wide spectrum of cognitive dysfunctions related to cerebrovascular disease. Among the pathophysiological determinants of VCI are cerebral stroke, white matter lesions and brain atrophy, which are known to be important risk factors for dementia. However, the specific mechanisms behind the brain abnormalities and cognitive decline are still poorly understood. The present study investigated the neuropsychological correlates of particular magnetic resonance imaging (MRI) findings, namely, medial temporal lobe atrophy (MTA), white matter hyperintensities (WMH), general cortical atrophy and corpus callosum (CC) atrophy in subjects with cerebrovascular disease. Furthermore, the cognitive profile of subcortical ischaemic vascular disease (SIVD) was examined. This study was conducted as part of two large multidisciplinary study projects, the Helsinki Stroke Aging Memory (SAM) Study and the multinational Leukoaraiosis and Disability (LADIS) Study. The SAM cohort consisted of 486 patients, between 55 and 85 years old, with ischaemic stroke from the Helsinki University Hospital, Helsinki, Finland. The LADIS Study included a mixed sample of subjects (n=639) with age-related WMH, between 65 and 84 years old, gathered from 11 centres around Europe. Both studies included comprehensive clinical and neuropsychological assessments and detailed brain MRI. The relationships between the MRI findings and the neuropsychological test performance were analysed by controlling for relevant confounding factors such as age, education and other coexisting brain lesions. The results revealed that in elderly patients with ischaemic stroke, moderate to severe MTA was specifically related to impairment of memory and visuospatial functions, but mild MTA had no clinical relevance. Instead, WMH were primarily associated with executive deficits and mental slowing. These deficits mediated the relationship between WMH and other, secondary cognitive deficits. Cognitive decline was best predicted by the overall degree of WMH, whereas the independent contribution of regional WMH measures was low. Executive deficits were the most prominent cognitive characteristic in SIVD. Compared to other stroke patients, the patients with SIVD also presented more severe memory deficits, which were related to MTA. The cognitive decline in SIVD occurred independently of depressive symptoms and, relative to healthy control subjects, it was substantial in severity. In stroke patients, general cortical atrophy also turned out to be a strong predictor of cognitive decline in a wide range of cognitive domains. Moreover, in elderly subjects with WMH, overall CC atrophy was related to reduction in mental speed, while anterior CC atrophy was independently associated with frontal lobe-mediated executive functions and attention. The present study provides cross-sectional evidence for the involvement of WMH, MTA, general cortical atrophy and CC atrophy in VCI. The results suggest that there are multifaceted pathophysiological mechanisms behind VCI in the elderly, including both vascular ischaemic lesions and neurodegenerative changes. The different pathological changes are highly interrelated processes and together they may produce cumulative effects on cognitive decline.

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Developmental dyslexia is a specific reading disability, which is characterised by unexpected difficulty in reading, spelling and writing despite adequate intelligence, education and social environment. It is the most common childhood learning disorder affecting 5-10 % of the population and thus constitutes the largest portion of all learning disorders. It is a persistent developmental failure although it can be improved by compensation. According to the most common theory, the deficit is in phonological processing, which is needed in reading when the words have to be divided into phonemes, or distinct sound elements. This occurs in the lowest level of the hierarchy of the language system and disturbs processes in higher levels, such as understanding the meaning of words. Dyslexia is a complex genetic disorder and previous studies have found nine locations in the genome that associate with it. Altogether four susceptibility genes have been found and this study describes the discovery of the first two of them, DYX1C1 and ROBO1. The first clues were obtained from two Finnish dyslexic families that have chromosomal translocations which disrupt these genes. Genetic analyses supported their role in dyslexia: DYX1C1 associates with dyslexia in the Finnish population and ROBO1 was linked to dyslexia in a large Finnish pedigree. In addition a genome-wide scan in Finnish dyslexic families was performed. This supported the previously detected dyslexia locus on chromosome 2 and revealed a new locus on chromosome 7. Dyslexia is a neurological disorder and the neurobiological function of the susceptibility genes DYX1C1 and ROBO1 are consistent with this. ROBO1 is an axon guidance receptor gene, which is involved in axon guidance across the midline in Drosophila and axonal pathfinding between the two hemispheres via the corpus callosum, as well as neuronal migration in the brain of mice. The translocation and decreased ROBO1 expression in dyslexic individuals indicate that two functional copies of ROBO1 gene are required in reading. DYX1C1 was a new gene without a previously known function. Inhibition of Dyx1c1 expression showed that it is needed in normal brain development in rats. Without Dyx1c1 protein, the neurons in the developing brain will not migrate to their final position in the cortex. These two dyslexia susceptibility genes DYX1C1 and ROBO1 revealed two distinct neurodevelopmental mechanisms of dyslexia, axonal pathfinding and neuronal migration. This study describes the discovery of the genes and our research to clarify their role in developmental dyslexia.

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The need for special education (SE) is increasing. The majority of those whose problems are due to neurodevelopmental disorders have no specific aetiology. The aim of this study was to evaluate the contribution of prenatal and perinatal factors and factors associated with growth and development to later need for full-time SE and to assess joint structural and volumetric brain alterations among subjects with unexplained, familial need for SE. A random sample of 900 subjects in full-time SE allocated into three levels of neurodevelopmental problems and 301 controls in mainstream education (ME) provided data on socioeconomic factors, pregnancy, delivery, growth, and development. Of those, 119 subjects belonging to a sibling-pair in full-time SE with unexplained aetiology and 43 controls in ME underwent brain magnetic resonance imaging (MRI). Analyses of structural brain alterations and midsagittal area and diameter measurements were made. Voxel-based morphometry (VBM) analysis provided detailed information on regional grey matter, white matter, and cerebrospinal fluid (CSF) volume differences. Father’s age ≥ 40 years, low birth weight, male sex, and lower socio-economic status all increased the probability of SE placement. At age 1 year, one standard deviation score decrease in height raised the probability of SE placement by 40% and in head circumference by 28%. At infancy, the gross motor milestones differentiated the children. From age 18 months, the fine motor milestones and those related to speech and social skills became more important. Brain MRI revealed no specific aetiology for subjects in SE. However, they had more often ≥ 3 abnormal findings in MRIs (thin corpus callosum and enlarged cerebral and cerebellar CSF spaces). In VBM, subjects in full-time SE had smaller global white matter, CSF, and total brain volumes than controls. Compared with controls, subjects with intellectual disabilities had regional volume alterations (greater grey matter volumes in the anterior cingulate cortex bilaterally, smaller grey matter volume in left thalamus and left cerebellar hemisphere, greater white matter volume in the left fronto-parietal region, and smaller white matter volumes bilaterally in the posterior limbs of the internal capsules). In conclusion, the epidemiological studies emphasized several factors that increased the probability of SE placement, useful as a framework for interventional studies. The global and regional brain MRI findings provide an interesting basis for future investigations of learning-related brain structures in young subjects with cognitive impairments or intellectual disabilities of unexplained, familial aetiology.

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Shwachman-Diamond syndrome (SDS) is a rare autosomal recessive disorder in which the cardinal symptoms arise from exocrine pancreatic insufficiency and bone marrow dysfunction. Previous studies have suggested increased risk of fatal complications among Finnish SDS infants. The genetic defect responsible for the disease was recently identified; the SBDS gene is located at chromosome 7q11 and encodes a protein that is involved in ribosome biosynthesis. The discovery of the SBDS gene has opened new insights into the pathogenesis of this multi-organ disease. This study aimed to assess phenotypic and genotypic features of Finnish patients with SDS. Seventeen Finnish patients with a clinical diagnosis of SDS were included in the study cohort. Extensive clinical, biochemical and imaging assessments were performed to elucidate the phenotypic features, and the findings were correlated with the SBDS genotype. Imaging studies included abdominal magnetic reso-nance imaging (MRI), brain MRI, cardiac echocardiography including tissue Doppler examination, and cardiac MRI. The skeletal phenotype was assessed by dual-energy X-ray absorptiometry and bone histomorphometry. Twelve patients had mutations in the SBDS gene. In MRI, a characteristic pattern of fat-replaced pancreas with occasional enhancement of scattered parenchymal foci and of pancreatic duct was noted in the SBDS mutation-positive patients while the mutation-negative patients did not have pancreatic fat accumulation. The patients with SBDS mutations had significantly reduced bone mineral density associated with low-energy peripheral fractures and vertebral compression fractures. Bone histomorphometry confirmed low-turnover osteoporosis. The patients with SBDS mutations had learning difficulties and smaller head size and brain volume than control subjects. Corpus callosum, cerebellar vermis, and pos-terior fossa structures were significantly smaller in SDS patients than in controls. Patients with SDS did not have evidence of clinical heart disease or myocardial fibrosis. However, subtle diastolic changes in the right ventricle and exercise-induced changes in the left ventricle contractile reserve were observed. This study expanded the phenotypic features of SDS to include primary low-turnover osteoporosis and structural alterations in the brain. Pancreatic MRI showed characteristic changes in the SBDS mutation-positive patients while these were absent in the mutation-negative patients, suggesting that MRI can be used to differentiate patients harbouring SBDS mutations from those without mutations. No evidence for clinical cardiac manifestations was found, but imaging studies revealed slightly altered myocardial function that may have clinical implications. These findings confirm the pleiotropic nature of SDS and underscore the importance of careful multidisciplinary follow-up of the affected individuals.

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After stroke, white matter integrity can be affected both locally and distally to the primary lesion location. It has been shown that tract disruption in mirror's regions of the contralateral hemisphere is associated with degree of functional impairment. Fourteen patients suffering right hemispheric focal stroke (S) and eighteen healthy controls (HC) underwent Diffusion Weighted Imaging (DWI) and neuropsychological assessment. The stroke patient group was divided into poor (SP; n = 8) and good (SG; n = 6) cognitive recovery groups according to their cognitive improvement from the acute phase (72 hours after stroke) to the subacute phase (3 months post-stroke). Whole-brain DWI data analysis was performed by computing Diffusion Tensor Imaging (DTI) followed by Tract Based Spatial Statistics (TBSS). Assessment of effects was obtained computing the correlation of the projections on TBSS skeleton of Fractional Anisotropy (FA) and Radial Diffusivity (RD) with cognitive test results. Significant decrease of FA was found only in right brain anatomical areas for the S group when compared to the HC group. Analyzed separately, stroke patients with poor cognitive recovery showed additional significant FA decrease in several left hemisphere regions; whereas SG patients showed significant decrease only in the left genu of corpus callosum when compared to the HC. For the SG group, whole brain analysis revealed significant correlation between the performance in the Semantic Fluency test and the FA in the right hemisphere as well as between the performance in the Grooved Pegboard Test (GPT) and theTrail Making Test-part A and the FA in the left hemisphere. For the SP group, correlation analysis revealed significant correlation between the performance in the GPT and the FA in the right hemisphere. Palabras clave

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Several patients of P. J. Vogel who had undergone cerebral commissurotomy for the control of intractable epilepsy were tested on a variety of tasks to measure aspects of cerebral organization concerned with lateralization in hemispheric function. From tests involving identification of shapes it was inferred that in the absence of the neocortical commissures, the left hemisphere still has access to certain types of information from the ipsilateral field. The major hemisphere can still make crude differentiations between various left-field stimuli, but is unable to specify exact stimulus properties. Most of the time the major hemisphere, having access to some ipsilateral stimuli, dominated the minor hemisphere in control of the body.

Competition for control of the body between the hemispheres is seen most clearly in tests of minor hemisphere language competency, in which it was determined that though the minor hemisphere does possess some minimal ability to express language, the major hemisphere prevented its expression much of the time. The right hemisphere was superior to the left in tests of perceptual visualization, and the two hemispheres appeared to use different strategies in attempting to solve the problems, namely, analysis for the left hemisphere and synthesis for the right hemisphere.

Analysis of the patients' verbal and performance I.Q.'s, as well as observations made throughout testing, suggest that the corpus callosum plays a critical role in activities that involve functions in which the minor hemisphere normally excels, that the motor expression of these functions may normally come through the major hemisphere by way of the corpus callosum.

Lateral specialization is thought to be an evolutionary adaptation which overcame problems of a functional antagonism between the abilities normally associated with the two hemispheres. The tests of perception suggested that this function lateralized into the mute hemisphere because of an active counteraction by language. This latter idea was confirmed by the finding that left-handers, in whom there is likely to be bilateral language centers, are greatly deficient on tests of perception.