Altered default mode network causal connectivity patterns in autism spectrum disorder revealed by Liang information flow analysis

Abstract

Autism spectrum disorder (ASD) is a pervasive developmental disorder with severe cognitive impairment in social communication and interaction. Previous studies have reported that abnormal functional connectivity patterns within the default mode network (DMN) were associated with social dysfunction in ASD. However, how the altered causal connectivity pattern within the DMN affects the social functioning in ASD remains largely unclear. Here, we introduced the Liang information flow method, widely applied to climate science and quantum mechanics, to uncover the brain causal network patterns in ASD. Compared with the healthy controls (HC), we observed that the interactions among the dorsal medial prefrontal cortex (dMPFC), ventral medial prefrontal cortex (vMPFC), hippocampal formation, and temporo‐parietal junction showed more inter‐regional causal connectivity differences in ASD. For the topological property analysis, we also found the clustering coefficient of DMN and the In‐Out degree of anterior medial prefrontal cortex were significantly decreased in ASD. Furthermore, we found that the causal connectivity from dMPFC to vMPFC was correlated with the clinical symptoms of ASD. These altered causal connectivity patterns indicated that the DMN inter‐regions information processing was perturbed in ASD. In particular, we found that the dMPFC acts as a causal source in the DMN in HC, whereas it plays a causal target in ASD. Overall, our findings indicated that the Liang information flow method could serve as an important way to explore the DMN causal connectivity patterns, and it also can provide novel insights into the nueromechanisms underlying DMN dysfunction in ASD.

Prefrontal Cortex Responses to Social Video Stimuli in Young Children with and without Autism Spectrum Disorder

“…Also, abnormal functional specialization within the mPFC was found among individuals with ASD when using multi-voxel analysis to compare brain activation of verbal versus spatial tasks [60]. Altered functional connectivity of the mPFC and other regions of the default mode network among individuals with ASD was also found in an fMRI study [61,62]. In ASD, general hyperconnectivity, specifically between the primary sensory cortex with paralimbic systems and the association cortex, has been reported [63].…”

Normalized Multivariate Time Series Causality Analysis and Causal Graph Reconstruction

“…A comprehensive study with generic systems has been fulfilled recently, with explicit formulas attained in closed form; see [2] and [1]. These formulas have been validated with benchmark systems such as baker transformation, Hénon map, etc., and have been applied successfully to real world problems in the diverse disciplines such as global climate change (e.g., [3], [4], [5]), dynamic meteorology (e.g., [6]), land-atmosphere interaction (e.g., [7]), data-driven prediction (e.g., [8], [9]), near-wall turbulence (e.g., [10]), neuroscience (e.g., [11], [12]), financial analysis (e.g., [13], [14]), quantum information (e.g, [15]), to name several.…”