Maturational trajectories of local and long-range functional connectivity in autism during face processing

Abstract

Autism spectrum disorder (ASD) is characterized neurophysiologically by, among other things, functional connectivity abnormalities in the brain. Recent evidence suggests that the nature of these functional connectivity abnormalities might not be uniform throughout maturation. Comparing between adolescents and young adults (ages 14-21) with ASD and age- and IQ-matched typically developing (TD) individuals, we previously documented, using magnetoencephalography (MEG) data, that local functional connectivity in the fusiform face areas (FFA) and long-range functional connectivity between FFA and three higher order cortical areas were all reduced in ASD. Given the findings on abnormal maturation trajectories in ASD, we tested whether these results extend to preadolescent children (ages 7-13). We found that both local and long-range functional connectivity were in fact normal in this younger age group in ASD. Combining the two age groups, we found that local and long-range functional connectivity measures were positively correlated with age in TD, but negatively correlated with age in ASD. Last, we showed that local functional connectivity was the primary feature in predicting age in ASD group, but not in the TD group. Furthermore, local functional connectivity was only correlated with ASD severity in the older group. These results suggest that the direction of maturation of functional connectivity for processing of faces from childhood to young adulthood is itself abnormal in ASD, and that during the processing of faces, these trajectory abnormalities are more pronounced for local functional connectivity measures than they are for long-range functional connectivity measures.

Keywords: ASD; MEG; adolescence; coherence; development; face processing; phase amplitude coupling.

Figure 1

(a) Probability map of FFA location across all subjects. The contour map shows the localization overlap from 50% to 80% across subjects. (b) Averaged evoked responses of emotional faces and houses across all subjects of FFA in TD and ASD for (b) children (ages 7–13) and (c) adolescents (ages 14–21). The shaded area shows one standard error around the mean [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 2

PAC of emotional faces relative to houses, compared between TD and ASD, for (a) children and (b) adolescents. (c) Correlation of age with the mean PAC from 80 to 120 Hz in TD and ASD. A linear model was fitted to each group's data [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

Correlation between age and Z‐coherence (normalized coherence, faces relative to houses) between the FFA and (a) AAC, (b) IFG, and (c) precuneus. R and corrected p values are noted on each panel [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 4

(a) Performance of multivariate linear regression model in TD and ASD. (b) Feature importance in TD and ASD. The error bar was computed using the standard deviation across 250 trees [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 5

(a) ADOS‐PAC correlation for ASD participants ages 14–21. (b) ADOS–PAC correlation R value and (c) p value across development using sliding five year age windows. Standard error bars for panels b and c were computed using bootstrapping [Color figure can be viewed at http://wileyonlinelibrary.com]