scholarly journals The Superficial White Matter in Autism and Its Role in Connectivity Anomalies and Symptom Severity

2018 ◽  
Vol 29 (10) ◽  
pp. 4415-4425 ◽  
Author(s):  
Seok-Jun Hong ◽  
Brian Hyung ◽  
Casey Paquola ◽  
Boris C Bernhardt
Keyword(s):  
White Matter ◽  
Functional Connectivity ◽  
Symptom Severity ◽  
Short Range ◽  
Autism Spectrum ◽  
Structure And Function ◽  
Symptom Load ◽  
Spectrum Disorders ◽  
And Function ◽  
Cortical Morphology

Abstract In autism spectrum disorders (ASDs), the majority of neuroimaging studies have focused on the analysis of cortical morphology. White matter changes remain less understood, particularly their association to cortical structure and function. Here, we focused on region that has gained only little attention in ASD neuroimaging: the superficial white matter (SWM) immediately beneath the cortical interface, a compartment playing a prominent role in corticogenesis that incorporates long- and short-range fibers implicated in corticocortical connectivity. Studying a multicentric dataset of ASD and neurotypical controls, we harnessed surface-based techniques to aggregate microstructural SWM diffusion features. Multivariate analysis revealed SWM anomalies in ASD compared with controls in medial parietal and temporoparietal regions. Effects were similar in children and adolescents/adults and consistent across sites. Although SWM anomalies were more confined when correcting for cortical thickness and surface area, findings were overall robust. Diffusion anomalies modulated functional connectivity reductions in ASD and related to symptom severity. Furthermore, mediation models indicated a link between SWM changes, functional connectivity, and symptom load. Analyses targeting the SWM offer a novel perspective on the interplay between structural and functional network perturbations in ASD, highlighting a potentially important neurobiological substrate contributing to its diverse behavioral phenotype.

scholarly journals Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity

2015 ◽  
Author(s):  
Manjari Narayan ◽  
Genevera I. Allen
Keyword(s):  
Autism Spectrum Disorders ◽  
Functional Connectivity ◽  
Network Structure ◽  
Symptom Severity ◽  
Statistical Power ◽  
Autism Spectrum ◽  
Covariate Effects ◽  
Activity Measurements ◽  
Wide Range ◽  
Spectrum Disorders

AbstractMany complex brain disorders, such as autism spectrum disorders, exhibit a wide range of symptoms and disability. To understand how brain communication is impaired in such conditions, functional connectivity studies seek to understand individual differences in brain network structure in terms of covariates that measure symptom severity. In practice, however, functional connectivity is not observed but estimated from complex and noisy neural activity measurements. Imperfect subject network estimates can compromise subsequent efforts to detect covariate effects on network structure. We address this problem in the case of Gaussian graphical models of functional connectivity, by proposing novel two-level models that treat both subject level networks and population level covariate effects as unknown parameters. To account for imperfectly estimated subject level networks when fitting these models, we propose two related approaches — R2 based on resampling and random effects test statistics, and R3 that additionally employs random adaptive penalization. Simulation studies using realistic graph structures reveal that R2 and R3 have superior statistical power to detect covariate effects compared to existing approaches, particularly when the number of within subject observations is comparable to the size of subject networks. Using our novel models and methods to study parts of the ABIDE dataset, we find evidence of hypoconnectivity associated with symptom severity in autism spectrum disorders, in frontoparietal and limbic systems as well as in anterior and posterior cingulate cortices.

scholarly journals Atypical Local and Distal Patterns of Occipito-frontal Functional Connectivity are Related to Symptom Severity in Autism

2018 ◽  
Vol 29 (8) ◽  
pp. 3319-3330 ◽  
Author(s):  
R Joanne Jao Keehn ◽  
Sangeeta Nair ◽  
Ellyn B Pueschel ◽  
Annika C Linke ◽  
Inna Fishman ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Symptom Severity ◽  
Autism Spectrum ◽  
Typically Developing ◽  
Local Connectivity ◽  
Long Distance ◽  
Opposite Pattern ◽  
Spectrum Disorders ◽  
Integrative Processing ◽  
Brain Behavior

Abstract Autism spectrum disorders (ASDs) are increasingly prevalent neurodevelopmental disorders characterized by sociocommunicative impairments. Growing consensus indicates that neurobehavioral abnormalities require explanation in terms of interconnected networks. Despite theoretical speculations about increased local and reduced distal connectivity, links between local and distal functional connectivity have not been systematically investigated in ASDs. Specifically, it remains open whether hypothesized local overconnectivity may reflect isolated versus overly integrative processing. Resting state functional MRI data from 57 children and adolescents with ASDs and 51 typically developing (TD) participants were included. In regional homogeneity (ReHo) analyses, pericalcarine visual cortex was found be locally overconnected (ASD > TD). Using this region as seed in whole-brain analyses, we observed overconnectivity in distal regions, specifically middle frontal gyri, for an ASD subgroup identified through k-means clustering. While in this subgroup local occipital to distal frontal overconnectivity was associated with greater symptom severity, a second subgroup showed the opposite pattern of connectivity and symptom severity correlations. Our findings suggest that increased local connectivity in ASDs is region-specific and may be partially associated with more integrative long-distance connectivity. Results also highlight the need to test for subtypes, as differential patterns of brain–behavior links were observed in two distinct subgroups of our ASD cohort.

FC05-05 - Fronto-temporal disconnectivity and symptom severity in autism spectrum disorders

2011 ◽  
Vol 26 (S2) ◽  
pp. 1838-1838
Author(s):  
L. Poustka ◽  
C. Jennen-Steinmetz ◽  
R. Henze ◽  
B. Stieltjes ◽  
Keyword(s):  
Autism Spectrum Disorders ◽  
White Matter ◽  
Symptom Severity ◽  
Diffusion Tensor ◽  
Autism Spectrum ◽  
Diagnostic Interview ◽  
Embedded Figures Test ◽  
Fiber Tracts ◽  
Spectrum Disorders ◽  
The Right

BackgroundThere is increasing evidence that many of the core behavioral impairments in autism spectrum disorders (ASD) emerge from disconnectivity of networks that are important for social communication. It is less clear, which specific fiber tracts are involved and how possible alterations of white matter are associated with clinical symptomatology and neuropsychololgical characteristics in ASD.Methods18 children with ASD and 18 carefully matched typically developing controls aged 6–12 years were examined using diffusion tensor imaging (DTI) and voxel-based morphometry (VBM). Fractional anisotropy (FA) values were correlated with symptom severity as indexed by the children's scores on the Autisms Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview-Revised (ADI-R) and results from the Childrens Embedded Figures Test (CEFT).ResultsDecreased FA values were identified for the fornix (FO), the superior longitudinal fasciculus (SLF) the corpus callosum and the uncinate fasciculus (UF) in the ASD group compared to controls, with most prominent differences in the UF bilaterally and the right SLF. FA values of affected fiber tracts were negatively associated with clinical measures of autistic smypotmatology and response time of the CEFT. Additionally, we observed decreased grey matter concentration in the left supramarginal gyrus.ConclusionOur findings support the hypothesis of abnormal white matter microstructure of fronto-temporal cortical networks in ASD, which are associated with core symptoms of the disorder.

scholarly journals Dynamic Functional Connectivity Alterations and Their Associated Gene Expression Pattern in Autism Spectrum Disorders

2022 ◽  
Vol 15 ◽  
Author(s):  
Lin Ma ◽  
Tengfei Yuan ◽  
Wei Li ◽  
Lining Guo ◽  
Dan Zhu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Autism Spectrum Disorders ◽  
Functional Connectivity ◽  
Symptom Severity ◽  
Molecular Mechanisms ◽  
Autism Spectrum ◽  
Angular Gyrus ◽  
Dynamic Functional Connectivity ◽  
Spectrum Disorders ◽  
The Right

Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders that are highly heritable and are associated with impaired dynamic functional connectivity (DFC). However, the molecular mechanisms behind DFC alterations remain largely unknown. Eighty-eight patients with ASDs and 87 demographically matched typical controls (TCs) from the Autism Brain Imaging Data Exchange II database were included in this study. A seed-based sliding window approach was then performed to investigate the DFC changes in each of the 29 seeds in 10 classic resting-state functional networks and the whole brain. Subsequently, the relationships between DFC alterations in patients with ASDs and their symptom severity were assessed. Finally, transcription-neuroimaging association analyses were conducted to explore the molecular mechanisms of DFC disruptions in patients with ASDs. Compared with TCs, patients with ASDs showed significantly increased DFC between the right dorsolateral prefrontal cortex (DLPFC) and left fusiform/lingual gyrus, between the DLPFC and the superior temporal gyrus, between the right frontal eye field (FEF) and left middle frontal gyrus, between the FEF and the right angular gyrus, and between the left intraparietal sulcus and the right middle temporal gyrus. Moreover, significant relationships between DFC alterations and symptom severity were observed. Furthermore, the genes associated with DFC changes in ASDs were identified by performing gene-wise across-sample spatial correlation analysis between gene expression extracted from six donors’ brain of the Allen Human Brain Atlas and case-control DFC difference. In enrichment analysis, these genes were enriched for processes associated with synaptic signaling and voltage-gated ion channels and calcium pathways; also, these genes were highly expressed in autistic disorder, chronic alcoholic intoxication and several disorders related to depression. These results not only demonstrated higher DFC in patients with ASDs but also provided novel insight into the molecular mechanisms underlying these alterations.

scholarly journals Synchronous nonmonotonic changes in functional connectivity and white matter integrity in a rat model of sporadic Alzheimer’s disease

2020 ◽  
Author(s):  
Catarina Tristão Pereira ◽  
Yujian Diao ◽  
Ting Yin ◽  
Analina R da Silva ◽  
Bernard Lanz ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
White Matter ◽  
Functional Connectivity ◽  
Structure And Function ◽  
Acute Injury ◽  
Therapeutic Window ◽  
Brain Glucose ◽  
And Function ◽  
Glucose Hypometabolism

AbstractBrain glucose hypometabolism has been singled out as an important contributor and possibly main trigger to Alzheimer’s disease (AD). Intracerebroventricular injections of streptozotocin (icv-STZ) cause brain glucose hypometabolism without systemic diabetes. Here, a first-time longitudinal study of brain glucose metabolism, functional connectivity and white matter microstructure was performed in icv-STZ rats using PET and MRI. Histological markers of pathology were tested at an advanced stage of disease. STZ rats exhibited altered functional connectivity and intra-axonal damage and demyelination in brain regions typical of AD, in a temporal pattern of acute injury, transient recovery/compensation and chronic degeneration. In the context of sustained glucose hypometabolism, these nonmonotonic trends – also reported in behavioral studies of this animal model as well as in human AD – suggest a compensatory mechanism, possibly recruiting ketone bodies, that allows a partial and temporary repair of brain structure and function. The early acute phase could thus become a valuable therapeutic window to strengthen the recovery phase and prevent or delay chronic degeneration, to be considered both in preclinical and clinical studies of AD. In conclusion, this work reveals the consequences of brain insulin resistance on structure and function, highlights signature nonmonotonic trajectories in their evolution and proposes potent MRI-derived biomarkers translatable to human AD and diabetic populations.

scholarly journals High resolution structural and functional MRI of the hippocampus in young adults with Down syndrome

2021 ◽  
Author(s):  
Katherine A Koenig ◽  
Se-Hong Oh ◽  
Melissa R Stasko ◽  
Elizabeth C Roth ◽  
H Gerry Taylor ◽  
...  
Keyword(s):  
Down Syndrome ◽  
Functional Connectivity ◽  
Cortical Thickness ◽  
Right Hemisphere ◽  
Gray Matter Volume ◽  
Drug Efficacy ◽  
Structure And Function ◽  
7 Tesla ◽  
Whole Brain ◽  
And Function

Abstract Down syndrome is the phenotypic consequence of trisomy 21, with clinical presentation including both neurodevelopmental and neurodegenerative components. Although the intellectual disability typically displayed by individuals with Down syndrome is generally global, it also involves disproportionate deficits in hippocampally-mediated cognitive processes. Hippocampal dysfunction may also relate to Alzheimer’s disease-type pathology, which can appear in as early as the first decade of life and becomes universal by age 40. Using 7-tesla MRI of the brain, we present an assessment of the structure and function of the hippocampus in 34 individuals with Down syndrome (mean age 24.5 years ± 6.5) and 27 age- and sex-matched typically developing healthy controls. In addition to increased whole-brain mean cortical thickness and lateral ventricle volumes (p < 1.0 × 10−4), individuals with Down syndrome showed selective volume reductions in bilateral hippocampal subfields CA1, dentate gyrus, and tail (p < 0.005). In the group with Down syndrome, bilateral hippocampi showed widespread reductions in the strength of functional connectivity, predominately to frontal regions (p < 0.02). Age was not related to hippocampal volumes or functional connectivity measures in either group, but both groups showed similar relationships of age to whole-brain volume measures (p < 0.05). Finally, we performed an exploratory analysis of a subgroup of individuals with Down syndrome with both imaging and neuropsychological assessments. This analysis indicated that measures of spatial memory were related to mean cortical thickness, total gray matter volume, and right hemisphere hippocampal subfield volumes (p < 0.02). This work provides a first demonstration of the usefulness of high-field MRI to detect subtle differences in structure and function of the hippocampus in individuals with Down syndrome, and suggests the potential for development of MRI-derived measures as surrogate markers of drug efficacy in pharmacological studies designed to investigate enhancement of cognitive function.

Individual Differences in Intrinsic Brain Networks Predict Symptom Severity in Autism Spectrum Disorders

2020 ◽  
Vol 31 (1) ◽  
pp. 681-693 ◽  
Author(s):  
Emmanuel Peng Kiat Pua ◽  
Phoebe Thomson ◽  
Joseph Yuan-Mou Yang ◽  
Jeffrey M Craig ◽  
Gareth Ball ◽  
...  
Keyword(s):  
Autism Spectrum Disorders ◽  
Individual Differences ◽  
Face Perception ◽  
Symptom Severity ◽  
Brain Networks ◽  
Monozygotic Twins ◽  
Autism Spectrum ◽  
Social Impairment ◽  
Individual Level ◽  
Spectrum Disorders

Abstract The neurobiology of heterogeneous neurodevelopmental disorders such as Autism Spectrum Disorders (ASD) is still unknown. We hypothesized that differences in subject-level properties of intrinsic brain networks were important features that could predict individual variation in ASD symptom severity. We matched cases and controls from a large multicohort ASD dataset (ABIDE-II) on age, sex, IQ, and image acquisition site. Subjects were matched at the individual level (rather than at group level) to improve homogeneity within matched case–control pairs (ASD: n = 100, mean age = 11.43 years, IQ = 110.58; controls: n = 100, mean age = 11.43 years, IQ = 110.70). Using task-free functional magnetic resonance imaging, we extracted intrinsic functional brain networks using projective non-negative matrix factorization. Intrapair differences in strength in subnetworks related to the salience network (SN) and the occipital-temporal face perception network were robustly associated with individual differences in social impairment severity (T = 2.206, P = 0.0301). Findings were further replicated and validated in an independent validation cohort of monozygotic twins (n = 12; 3 pairs concordant and 3 pairs discordant for ASD). Individual differences in the SN and face-perception network are centrally implicated in the neural mechanisms of social deficits related to ASD.

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