Project description:It has long been predicted that the degree to which language is lateralized to the left or right hemisphere might be reflected in the underlying brain anatomy. We investigated this relationship on a voxel-by-voxel basis across the whole brain using structural and functional magnetic resonance images from 86 healthy participants. Structural images were converted to gray matter probability images, and language activation was assessed during naming and semantic decision. All images were spatially normalized to the same symmetrical template, and lateralization images were generated by subtracting right from left hemisphere signal at each voxel. We show that the degree to which language was left or right lateralized was positively correlated with the degree to which gray matter density was lateralized. Post hoc analyses revealed a general relationship between gray matter probability and blood oxygenation level-dependent signal. This is the first demonstration that structural brain scans can be used to predict language lateralization on a voxel-by-voxel basis in the normal healthy brain.
Project description:Lateralization patterns are a major structural feature of brain white matter and have been investigated as a neural architecture that indicates and supports the specialization of cognitive processing and observed behaviors, e.g. language skills. Many neurodevelopmental disorders have been associated with atypical lateralization, reinforcing the need for careful measurement and study of this structural characteristic. Unfortunately, there is little consensus on the direction and magnitude of lateralization in major white matter tracts during the first months and years of life-the period of most rapid postnatal brain growth and cognitive maturation. In addition, no studies have examined white matter lateralization in a longitudinal pediatric sample-preventing confirmation of if and how white matter lateralization changes over time. Using a densely sampled longitudinal data set from neurotypical infants aged 0-6 months, we aim to (i) chart trajectories of white matter lateralization in 9 major tracts and (ii) link variable findings from cross-sectional studies of white matter lateralization in early infancy. We show that patterns of lateralization are time-varying and tract-specific and that differences in lateralization results during this period may reflect the dynamic nature of lateralization through development, which can be missed in cross-sectional studies.
Project description:The present study investigated whether children with a typical dyslexia profile and children with isolated spelling deficits show a distinct pattern of white matter alteration compared with typically developing peers. Relevant studies on the topic are scarce, rely on small samples, and often suffer from the limitations of conventional tensor-based methods. The present Constrained Spherical Deconvolution study includes 27 children with typical reading and spelling skills, 21 children with dyslexia and 21 children with isolated spelling deficits. Group differences along major white matter tracts were quantified utilizing the Automated Fiber Quantification software and a lateralization index was calculated in order to investigate the structural asymmetry of the tracts. The two deficit groups mostly displayed different patterns of white matter alterations, located in the bilateral inferior longitudinal fasciculi, right superior longitudinal fasciculus, and cingulum for the group with dyslexia and in the left arcuate fasciculus for the group with isolated spelling deficits. The two deficit groups differed also with respect to structural asymmetry. Children with dyslexia did not show the typical leftward asymmetry of the arcuate fasciculus, whereas the group with isolated spelling deficits showed absent rightward asymmetry of the inferior fronto-occipital fasciculus. This study adds evidence to the notion that different profiles of combined or isolated reading and spelling deficits are associated with different neural signatures.
Project description:AimTo determine whether variability in diffusion MRI (dMRI) white matter tract metrics, obtained in a cohort of preterm infants prior to neonatal hospital discharge, would be associated with language outcomes at age 2 years, after consideration of age at scan and number of major neonatal complications.Method30 children, gestational age 28.9 (2.4) weeks, underwent dMRI at mean post menstrual age 36.4 (1.4) weeks and language assessment with the Bayley Scales of Infant Development-III at mean age 22.2 (1.7) months chronological age. Mean fractional anisotropy (FA) and mean diffusivity (MD) were calculated for 5 white matter tracts. Hierarchical linear regression assessed associations between tract FA, moderating variables, and language outcomes.ResultsFA of the left inferior longitudinal fasciculus accounted for 17% (p = 0.03) of the variance in composite language and FA of the posterior corpus callosum accounted for 19% (p = 0.02) of the variance in composite language, beyond that accounted for by post-menstrual age at scan and neonatal medical complications. The number of neonatal medical complications moderated the relationship between language and posterior corpus callosum FA but did not moderate the association in the other tract.ConclusionLanguage at age 2 is associated with white matter metrics in early infancy in preterm children. The different pattern of associations by fiber group may relate to the stage of brain maturation and/or the nature and timing of medical complications related to preterm birth. Future studies should replicate these findings with a larger sample size to assure reliability of the findings.
Project description:A brain tumor in the left hemisphere can decrease language laterality as assessed through fMRI. However, it remains unclear whether or not this decreased language laterality is associated with a structural reshaping of the grey matter, particularly within the language network. Here, we examine if the disruption of the language hubs exclusively affects the macrostructural properties of the contralateral homologues or whether it affects both hemispheres. This study uses voxel-based morphometry applied to high-resolution MR T1-weighted MPRAGE images from 31 adult patients' left hemisphere, which is dominant for language. Eighteen patients had brain tumors in the left hemisphere, and thirteen had tumors in the right hemisphere. A cohort of 71 healthy individuals matched with respect to age and sex was used as a baseline. We defined 10 ROIs per hemisphere involved in language function. Two separate repeated-measure ANOVAs were conducted with the volume per region as the dependent variable. For the patients, tumor lateralization (right versus left) served as a between-subject factor. The current study demonstrated that the presence of a brain tumor generates global volumetric changes affecting the left language regions and their contralateral homologues. These changes are mediated by the lateralization of the lesion. Our findings suggest that functional mechanisms are supported by the rearrangement of the grey matter.
Project description:Neural structures change with age but there is no consensus on the exact processes involved. This study tested the hypothesis that white and grey matter in the language network changes during aging according to a "last in, first out" process. The fractional anisotropy (FA) of white matter and cortical thickness of grey matter were measured in 36 participants whose ages ranged from 55 to 79 years. Within the language network, the dorsal pathway connecting the mid-to-posterior superior temporal cortex (STC) and the inferior frontal cortex (IFC) was affected more by aging in both FA and thickness than the other dorsal pathway connecting the STC with the premotor cortex and the ventral pathway connecting the mid-to-anterior STC with the ventral IFC. These results were independently validated in a second group of 20 participants whose ages ranged from 50 to 73 years. The pathway that is most affected during aging matures later than the other two pathways (which are present at birth). The results are interpreted as showing that the neural structures which mature later are affected more than those that mature earlier, supporting the "last in, first out" theory.
Project description:IntroductionWhite matter hyperintensities (WMHs) increase the risk of Alzheimer's disease (AD). Whether WMHs are associated with the decline of functional neural networks in AD is debated.MethodResting-state functional magnetic resonance imaging and WMH were assessed in 78 subjects with increased amyloid levels on AV-45 positron emission tomography (PET) in different clinical stages of AD. We tested the association between WMH volume in major atlas-based fiber tract regions of interest (ROIs) and changes in functional connectivity (FC) between the tracts' projection areas within the default mode network (DMN).ResultsWMH volume within the inferior fronto-occipital fasciculus (IFOF) was the highest among all tract ROIs and associated with reduced FC in IFOF-connected DMN areas, independently of global AV-45 PET. Higher AV-45 PET contributed to reduced FC in IFOF-connected, temporal, and parietal DMN areas.ConclusionsHigh fiber tract WMH burden is associated with reduced FC in connected areas, thus adding to the effects of amyloid pathology on neuronal network function.
Project description:ObjectiveThe aim of this study was to explore the relation of language functional MRI (fMRI)-guided tractography with postsurgical naming decline in people with temporal lobe epilepsy (TLE).MethodsTwenty patients with unilateral TLE (9 left) were studied with auditory and picture naming functional MRI tasks. Activation maxima in the left posterobasal temporal lobe were used as seed regions for whole-brain fibre tractography. Clinical naming performance was assessed preoperatively, 4 months, and 12 months following temporal lobe resection. Volumes of white matter language tracts in both hemispheres as well as tract volume laterality indices were explored as moderators of postoperative naming decline using Pearson correlations and multiple linear regression with other clinical variables.ResultsLarger volumes of white matter language tracts derived from auditory and picture naming maxima in the hemisphere of subsequent surgery as well as stronger lateralization of picture naming tract volumes to the side of surgery correlated with greater language decline, which was independent of fMRI lateralization status. Multiple regression for picture naming tract volumes was associated with a significant decline of naming function with 100% sensitivity and 93% specificity at both short-term and long-term follow-up.InterpretationNaming fMRI-guided white matter language tract volumes relate to postoperative naming decline after temporal lobe resection in people with TLE. This can assist stratification of surgical outcome and minimize risk of postoperative language deficits in TLE.
Project description:Diffusion MRI and tractography hold great potential for surgery planning, especially to preserve eloquent white matter during resections. However, fiber tract reconstruction requires an expert with detailed understanding of neuroanatomy. Several automated approaches have been proposed, using different strategies to reconstruct the white matter tracts in a supervised fashion. However, validation is often limited to comparison with manual delineation by overlap-based measures, which is limited in characterizing morphological and topological differences. In this work, we set up a fully automated pipeline based on anatomical criteria that does not require manual intervention, taking advantage of atlas-based criteria and advanced acquisition protocols available on clinical-grade MRI scanners. Then, we extensively validated it on epilepsy patients with specific focus on language-related bundles. The validation procedure encompasses different approaches, including simple overlap with manual segmentations from two experts, feasibility ratings from external multiple clinical raters and relation with task-based functional MRI. Overall, our results demonstrate good quantitative agreement between automated and manual segmentation, in most cases better performances of the proposed method in qualitative terms, and meaningful relationships with task-based fMRI. In addition, we observed significant differences between experts in terms of both manual segmentation and external ratings. These results offer important insights on how different levels of validation complement each other, supporting the idea that overlap-based measures, although quantitative, do not offer a full perspective on the similarities and differences between automated and manual methods.
Project description:The neural processing loop of language is complex but highly associated with Broca's and Wernicke's areas. The left dominance of these two areas was the earliest observation of brain asymmetry. It was demonstrated that the language network and its functional asymmetry during resting state were reproducible across institutions. However, the temporal reliability of resting-state language network and its functional asymmetry are still short of knowledge. In this study, we established a seed-based resting-state functional connectivity analysis of language network with seed regions located at Broca's and Wernicke's areas, and investigated temporal reliability of language network and its functional asymmetry. The language network was found to be temporally reliable in both short- and long-term. In the aspect of functional asymmetry, the Broca's area was found to be left lateralized, while the Wernicke's area is mainly right lateralized. Functional asymmetry of these two areas revealed high short- and long-term reliability as well. In addition, the impact of global signal regression (GSR) on reliability of the resting-state language network was investigated, and our results demonstrated that GSR had negligible effect on the temporal reliability of the resting-state language network. Our study provided methodology basis for future cross-culture and clinical researches of resting-state language network and suggested priority of adopting seed-based functional connectivity for its high reliability.