Dataset Information

Thalamocortical dysconnectivity in autism spectrum disorder: An analysis of the Autism Brain Imaging Data Exchange.

ABSTRACT: Individuals with autism spectrum disorder (ASD) exhibit differences in basic sensorimotor processing as well as general cortical excitability. These observations converge to implicate thalamocortical connectivity as a potential unifying neural mechanism. The goal of this study was to clarify mixed findings on thalamocortical functional connectivity in a large sample of individuals with ASD.Using the Autism Brain Imaging Data Exchange (ABIDE), we examined thalamocortical functional connectivity in 228 individuals with ASD and a matched comparison group of 228 typically developing individuals. In order to fully characterize thalamocortical functional networks, we employed complementary seed-based approaches that examined connectivity of major cortical divisions (e.g. prefrontal cortex, temporal lobe) with the thalamus and whole-brain connectivity of specific thalamic sub-regions.Prefrontal cortex, temporal lobe, and sensorimotor cortex exhibited hyper-connectivity with the thalamus in ASD. In the whole-brain analysis, hyper-connectivity of several thalamic seeds included multiple cortical areas, but tended to converge in temporal cortical areas, including the temporoparietal junction. Follow-up analyses of age effects revealed that the connectivity abnormalities in ASD were more pronounced in adolescents compared to children and adults.These results confirm previous findings of temporal and motor thalamocortical hyper-connectivity in ASD, and extend them to include somatosensory and prefrontal cortex. While not directly addressable with the data available in ABIDE, this widespread hyper-connectivity could theoretically account for sensorimotor symptoms and general cortical excitability in ASD. Future studies should target comprehensive clinical and behavioral characterization in combination with functional connectivity in order to explore this possibility.

SUBMITTER: Woodward ND

PROVIDER: S-EPMC5455796 | biostudies-other | 2017 Jan

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Thalamocortical dysconnectivity in autism spectrum disorder: An analysis of the Autism Brain Imaging Data Exchange.

Woodward Neil D ND Giraldo-Chica Monica M Rogers Baxter B Cascio Carissa J CJ

Biological psychiatry. Cognitive neuroscience and neuroimaging 20170101 1

<h4>Background</h4>Individuals with autism spectrum disorder (ASD) exhibit differences in basic sensorimotor processing as well as general cortical excitability. These observations converge to implicate thalamocortical connectivity as a potential unifying neural mechanism. The goal of this study was to clarify mixed findings on thalamocortical functional connectivity in a large sample of individuals with ASD.<h4>Methods</h4>Using the Autism Brain Imaging Data Exchange (ABIDE), we examined thalam ...[more]

PMID: 28584881

Similar Datasets

Project description:Background: Analyses of resting-state functional magnetic resonance imaging (rs-fMRI) have been performed to investigate pathophysiological changes in the brains of patients with autism spectrum disorder (ASD) relative to typically developing controls (CTLs). However, the results of these previous studies, which have reported mixed patterns of hypo- and hyperconnectivity, are controversial, likely due to the small sample sizes and limited age range of included participants. Methods: To overcome this issue, we analyzed multisite neuroimaging data from a large sample (n = 626) of male participants aged between 5 and 29 years (mean age = 13 years). The rs-fMRI data were preprocessed using SPM12 and DPARSF software, and signal changes in 90 brain regions were extracted. Multiple linear regression was used to exclude the effect of site differences in connectivity data. Subcortical-cortical connectivity was computed using connectivities in the hippocampus, amygdala, caudate nucleus, putamen, pallidum, and thalamus. Eighty-eight connectivities in each structure were compared between patients with ASD and CTLs using multiple linear regression with group, age, and age × group interactions, head movement parameters, and overall connectivity as variables. Results: After correcting for multiple comparisons, patients in the ASD group exhibited significant increases in connectivity between the thalamus and 19 cortical regions distributed throughout the fronto-parietal lobes, including the temporo-parietal junction and posterior cingulate cortices. In addition, there were significant decreases in connectivity between the amygdala and six cortical regions. The mean effect size of hyperconnectivity (0.25) was greater than that for hypoconnectivity (0.08). No other subcortical structures showed significant group differences. A group-by-age interaction was observed for connectivity between the thalamus and motor-somatosensory areas. Conclusions: These results demonstrate that pathophysiological changes associated with ASD are more likely related to thalamocortical hyperconnectivity than to amygdala-cortical hypoconnectivity. Future studies should examine full sets of clinical and behavioral symptoms in combination with functional connectivity to explore possible biomarkers for ASD.

Project description:This study investigated whole-brain dynamic lag pattern variations between neurotypical (NT) individuals and individuals with autism spectrum disorder (ASD) by applying a novel technique called dynamic lag analysis (DLA). The use of 3D magnetic resonance encephalography data with repetition time = 100?msec enables highly accurate analysis of the spread of activity between brain networks. Sixteen resting-state networks (RSNs) with the highest spatial correlation between NT individuals (n = 20) and individuals with ASD (n = 20) were analyzed. The dynamic lag pattern variation between each RSN pair was investigated using DLA, which measures time lag variation between each RSN pair combination and statistically defines how these lag patterns are altered between ASD and NT groups. DLA analyses indicated that 10.8% of the 120 RSN pairs had statistically significant (P-value <0.003) dynamic lag pattern differences that survived correction with surrogate data thresholding. Alterations in lag patterns were concentrated in salience, executive, visual, and default-mode networks, supporting earlier findings of impaired brain connectivity in these regions in ASD. 92.3% and 84.6% of the significant RSN pairs revealed shorter mean and median temporal lags in ASD versus NT, respectively. Taken together, these results suggest that altered lag patterns indicating atypical spread of activity between large-scale functional brain networks may contribute to the ASD phenotype. Autism Res 2020, 13: 244-258. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: Autism spectrum disorder (ASD) is characterized by atypical neurodevelopment. Using an ultra-fast neuroimaging procedure, we investigated communication across brain regions in adults with ASD compared with neurotypical (NT) individuals. We found that ASD individuals had altered information flow patterns across brain regions. Atypical patterns were concentrated in salience, executive, visual, and default-mode network areas of the brain that have previously been implicated in the pathophysiology of the disorder.

Dataset Information

Thalamocortical dysconnectivity in autism spectrum disorder: An analysis of the Autism Brain Imaging Data Exchange.

Publications

Thalamocortical dysconnectivity in autism spectrum disorder: An analysis of the Autism Brain Imaging Data Exchange.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets