Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder

Abstract

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with atypical gray matter (GM) and white matter (WM) functional developmental course. However, the functional co‐developmental pattern between GM and WM in ASD is unclear. Here, we utilized a functional covariance connectivity method to explore the concordance pattern between GM and WM function in individuals with ASD. A multi‐center resting‐state fMRI dataset composed of 105 male children with ASD and 102 well‐matched healthy controls (HCs) from six sites of the ABIDE dataset was utilized. GM and WM ALFF maps were calculated for each subject. Voxel by voxel functional covariance connectivity of the ALFF values across subjects was calculated between GM and WM for children with ASD and HCs. A Z‐test combining FDR multi‐comparison correction was then employed to determine whether the functional covariance is significantly different between the two groups. A “bundling” strategy was utilized to ensure that the GM/WM clusters showing atypical functional covariance were larger than 5 voxels. Finally, canonical correlation analysis was conducted to explore whether the atypical GM/WM functional covariance is related to ASD symptoms. Results showed atypical functional covariance connections between specific GM and WM regions, whereas the ALFF values of these regions indicated no significant difference between the two groups. Canonical correlation analysis revealed a significant relationship between the atypical functional covariance and stereotyped behaviors of ASD. The results indicated an altered functional co‐developmental pattern between WM and GM in ASD. Lay Summary White matter (WM) and gray matter (GM) are two major human brain organs supporting brain function. WM and GM functions show a specific co‐developmental pattern in typical developed individuals. This study showed that this GM/WM co‐developmental pattern was altered in children with ASD, while this altered GM/WM co‐developmental pattern was related to stereotyped behaviors. These findings may help understand the GM/WM functional development of ASD.

Transcriptomic and macroscopic architectures of intersubject functional variability in human brain white-matter

“…5a ; Supplementary Result 6 and Supplementary Table 2 ). The results were consistent with previous studies that reported functional abnormalities of WM in major depressive disorders 49 , schizophrenia 50 , 51 , and autism spectrum disorder 52 . The PLS1− ranking genes were also enriched for neurological diseases, including peripheral nervous system diseases, neurodegenerative disease, polyneuropathies, demyelinating diseases, hereditary motor and sensory neuropathies, muscle weakness, and neuromuscular diseases (all FDR-corrected P < 0.05; Fig.…”

Power spectra reveal distinct BOLD resting‐state time courses in white matter

“…However, dual-peak patterns within the low-frequency range, as we reliably observed in DP voxels, have not been previously reported in GM. In addition, while recent studies have reported significant changes in the amplitude of low-frequency fluctuations (ALFF) in WM in patients with schizophrenia and autism spectrum disorder 33,34 , these findings were restricted to the intensity of Figure 9. The relationship between behavior scores and power spectral peaks in DP voxels across 199 subjects.…”

“…However, dual‐peak patterns within the low‐frequency range, as we reliably observed in DP voxels, have not been previously reported in GM. In addition, while recent studies have reported significant changes in the amplitude of low-frequency fluctuations (ALFF) in WM in patients with schizophrenia and autism spectrum disorder 33,34 , these findings were restricted to the intensity of spontaneous neural activity. The patterns of power spectra over the frequency range of interest correspond to variations in underlying HRF characteristics and may add insights to the functional mechanism underlying the association between signal features, neurovascular coupling, and anatomical substrates.…”

Functional Covariance Connectivity of Gray and White Matter in Olfactory-Related Brain Regions in Parkinson’s Disease

“…The product of the standard scores of each pair of voxels is the FCS. The FCS can be used to measure the strength of the functional covariance of each pair of voxels (Eisenberg et al, 2015;Chen et al, 2021).…”

“…Therefore, in this study we selected Parkinson's patients with hyposmia, and analyzed the differences between Parkinson's patients with hyposmia and normal subjects. The functional covariance connectivity (FCC) between the white and gray matter voxels was constructed based on ALFF maps (Chen et al, 2021) and explored its value as a potential neuroimaging marker for early diagnosis.…”