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Benavidez, S. M.

Publications and source records attributed to Benavidez, S. M..

4 recordsLinked to original sources

Structural brain alterations in autism: A large-scale voxel-based morphometry mega-analysis

BackgroundPrevious large-scale structural MRI analyses of the brain in autism have identified gray matter (GM) differences when using region-of-interest analyses based on gross anatomical regions. However, such analyses have limited spatial specificity and may obscure subtle focal differences. Whole brain voxel-based morphometry (VBM) analyses enable greater spatial precision to identify and localize previously undetected neuroanatomical alterations. PurposeTo rigorously identify voxel-wise GM and white matter (WM) volume differences in autism in the largest VBM mega-analysis to date. Materials and MethodsThis retrospective mega-analysis included structural 3D volumetric T1-weighted MRI brain scans from 3,051 participants (15.0 {+/-} 8.2 yrs; 76.8% male; 1,519 autism; 1,532 neurotypicals) collected across 51 sites/scanners. Voxel-wise GM and WM volumes were quantified using the ENIGMA CAT12 VBM pipeline. Linear mixed-effects regression was performed at each voxel to evaluate the association between diagnostic group and voxel-wise volume while adjusting for standard nuisance covariates ResultsAutism was associated with widespread lower GM volume involving cortical, subcortical, and cerebellar regions (peak t=7.39, peak {beta}=0.13); such GM differences were most notably detected in the bilateral orbitofrontal cortex, amygdala, thalamus, and posterior lobes of the cerebellum. WM volume was lower in autism across major projection, commissural, association, and cerebellar/brainstem tracts (peak t=6.74, peak {beta}=0.08), including the corona radiata, internal capsule, corpus callosum, and cerebellar peduncles. These findings remained consistent in sensitivity analyses, including covarying for full-scale IQ and the application of increasingly strict motion exclusion criteria. ConclusionAutism is associated with smaller voxel-wise GM and WM volume involving widespread cortical, subcortical, and cerebellar regions. This high-resolution identification and localization of structural brain differences support the involvement of distributed neural systems in autism that underlie reward processing, sensory integration, and motor functioning in autism. Summary statementIn the largest voxel-based morphometry study of autism to date, widespread smaller gray and white matter volumes were identified across distributed brain regions implicated in reward and sensorimotor function. Key ResultsO_LIOur largest voxel-based morphometry mega-analysis to date in autism (N=3,051), identified widespread gray and white matter alterations (peak t=7.39, peak {beta}=0.13). C_LIO_LIWe reveal novel associations within thalamic mediodorsal nuclei by leveraging finer voxel-wise volumetric analyses. C_LIO_LIAdditional associations in orbitofrontal cortex, amygdala, and cerebellum, along with extensive white matter alterations across projection, commissural, association fibers, reinforce reward-processing, sensory and motor development theories in autism. C_LI

neuroscience↗

Mapping Along-Tract White Matter Microstructural Differences in Autism

Previous diffusion magnetic resonance imaging (dMRI) research has indicated altered white matter microstructure in autism, but the implicated regions are highly inconsistent across studies. Such prior work has largely used conventional dMRI analysis methods, including the traditional microstructure model, based on diffusion tensor imaging (DTI). However, these methods are limited in their ability to precisely map microstructural differences and accurately resolve complex fiber configurations. In our study, we investigated white matter microstructure alterations in autism using the refined along-tract analytic approach, BUndle ANalytics (BUAN), and an advanced microstructure model, the tensor distribution function (TDF). We analyzed dMRI data from 365 autistic and neurotypical participants (5-24 years; 34% female) from 10 cohorts to examine commissural and association tracts. Autism was associated with lower fractional anisotropy and higher diffusivity in localized portions of nearly every commissural and association tract examined; these tracts inter-connected a wide range of brain regions, including frontal, temporal, parietal, and occipital. Taken together, BUAN and TDF allow robust and spatially precise mapping of microstructural properties in autism. Our findings rigorously demonstrate that white matter microstructure alterations in autism may be greater within specific regions of individual tracts, and that the implicated tracts are distributed across the brain.

neuroscience↗

White Matter Microstructural Alterations in Autism Localized with Bundle Analytics

Previous diffusion magnetic resonance imaging research in autism has reported altered microstructure in the corpus callosum (CC), the major commissure connecting the two brain hemispheres. However, the CC consists of many fibers connecting various brain regions, and the precise localization of these differences in autism remains unclear. Additionally, the conventional diffusion tensor imaging (DTI) model cannot resolve complex fiber configurations and may miss subtle alterations. In this study, we investigated CC microstructure in 365 participants (5-25 years; 34.0% female; 195 with autism) from 10 sites/scanners by using a novel along-tract mapping method, BUndle ANalytics (BUAN), and advanced microstructure model, the tensor distribution function (TDF). Autism was associated with regionally specific reductions in white matter integrity and elevations in diffusivity. The TDF model detected CC microstructure differences more sensitively than DTI. Taken together, BUAN and TDF allow for precise and rigorous white matter analyses, enhancing the detection of subtle neural differences.

neuroscience↗

Sex Differences in the Brain's White Matter Microstructure during Development assessed using Advanced Diffusion MRI Models

Typical sex differences in white matter (WM) microstructure during development are incompletely understood. Here we evaluated sex differences in WM microstructure during typical brain development using a sample of neurotypical individuals across a wide developmental age (N=239, aged 5-22 years). We used the conventional diffusion-weighted MRI (dMRI) model, diffusion tensor imaging (DTI), and two advanced dMRI models, the tensor distribution function (TDF) and neurite orientation dispersion density imaging (NODDI) to assess WM microstructure. WM microstructure exhibited significant, regionally consistent sex differences across the brain during typical development. Additionally, the TDF model was most sensitive in detecting sex differences. These findings highlight the importance of considering sex in neurodevelopmental research and underscore the value of the advanced TDF model.

neuroscience↗