Dataset Information

Predicting language lateralization from gray matter.

ABSTRACT: 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.

SUBMITTER: Josse G

PROVIDER: S-EPMC2795346 | biostudies-other | 2009 Oct

REPOSITORIES: biostudies-other

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Predicting language lateralization from gray matter.

Josse Goulven G Kherif Ferath F Flandin Guillaume G Seghier Mohamed L ML Price Cathy J CJ

The Journal of neuroscience : the official journal of the Society for Neuroscience 20091001 43

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 n ...[more]

PMID: 19864564

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Project description:BackgroundDespite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.MethodsDifferences in MRI-based GM density and volume were examined in 6-25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47-154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67-155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.ResultsNo density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.LimitationsThe method for determining "density" is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.ConclusionsThese results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Project description:BackgroundAutism spectrum disorder (ASD) is a complex neurodevelopmental condition. Understanding the brain's microstructure and its relationship to clinical characteristics is important to advance our understanding of the neural supports underlying ASD. In the current work, we implemented Gray-Matter Based Spatial Statistics (GBSS) to examine and characterize cortical microstructure and assess differences between typically developing (TD) and autistic males.MethodsA multi-shell diffusion MRI (dMRI) protocol was acquired from 83 TD and 70 autistic males (5-to-21-years) and fit to the DTI and NODDI models. GBSS was performed for voxelwise analysis of cortical gray matter (GM). General linear models were used to investigate group differences, while age-by-group interactions assessed age-related differences between groups. Within the ASD group, relationships between cortical microstructure and measures of autistic symptoms were investigated.ResultsAll dMRI measures were significantly associated with age across the GM skeleton. Group differences and age-by-group interactions are reported. Group-wise increases in neurite density in autistic individuals were observed across frontal, temporal, and occipital regions of the right hemisphere. Significant age-by-group interactions of neurite density were observed within the middle frontal gyrus, precentral gyrus, and frontal pole. Negative relationships between neurite dispersion and the ADOS-2 Calibrated Severity Scores (CSS) were observed within the ASD group.DiscussionFindings demonstrate group and age-related differences between groups in neurite density in ASD across right-hemisphere brain regions supporting cognitive processes. Results provide evidence of altered neurodevelopmental processes affecting GM microstructure in autistic males with implications for the role of cortical microstructure in the level of autistic symptoms.ConclusionUsing dMRI and GBSS, our findings provide new insights into group and age-related differences of the GM microstructure in autistic males. Defining where and when these cortical GM differences arise will contribute to our understanding of brain-behavior relationships of ASD and may aid in the development and monitoring of targeted and individualized interventions.

Dataset Information

Predicting language lateralization from gray matter.

Publications

Predicting language lateralization from gray matter.

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