Welcome to Nanjing Center for Ocean-Atmosphere Dynamical Studies!

Nanjing Center for Ocean-Atmosphere Dynamical Studies


Information flow analysis reveals an altered brain causal network in autism spectrum disorder

Recently, using the Liang-Kleeman and the IF-based causality analysis, a team of scientists from Xihua University and University of Electronic Science and Technology of China identified an altered brain causal network in the autism spectrum disorder (ASD), a developmental disability that leads to significant behavioral challenges and severe difficulties in social interaction and communication. With point prevalence exceeding 1%, ASD has become one of the most serious diseases worldwide which threatens the health of children.

Dysfunction in ASD has been linked with the abnormal structure of the default mode network (DMN), a large-scale brain network consisting of posterior cingulate cortex, medial prefrontal cortex, precuneus, as well as the medial, lateral, and inferior parietal regions. Connectivity patterns within the DMN is believed to be important to understanding the underlying neuro-mechanism of ASD. However, the widely used functional connectivity is based on spatial-temporal correlation which fails to capture the causal influence of one brain region on another. To better reflect the interactions between brain regions, causal connectivity serves as an important clue.

Motivated by this, scientists recently introduced the information flow-based causality analysis into their investigation of the neuro-mechanism of ASD. The formalism of information flow has been rigorously established from first principles in physics by Prof. X. San Liang, allowing for a quantitative measurement of the causal relations between network nodes, and hence an efficient way to reveal the causal connectivity within the DMN.

Using information flow, the scientists constructed and compared the DMN causal connectivity networks in ASD and healthy controls, respectively, as shown in Fig. 1. It indicates that the interactions among the dorsal medial prefrontal cortex, ventral medial prefrontal cortex, hippocampal formation, and temporo-parietal junction show more inter-regional causal connectivity differences in ASD than in healthy controls. Among others, the causal connectivity from the dorsal to ventral medial prefrontal cortices is correlated with the clinical symptoms of ASD. In particular, they found that the dorsal medial prefrontal cortex acts in the DMN as a causal source in HC, whereas causal target in ASD (Fig. 2). These altered causal connectivity patterns indicate that the DMN inter-regions information processing is perturbed in ASD, which may cause the deficits of social cognition.

The study shows that, to quote as the authors stated, “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.” The paper has been published in Human Brain Mapping, with the citation as follows:

Cong, J.Zhuang, W.Liu, Y.Yin, S.Jia, H.Yi, C.Chen, K.Xue, K.Li, F.Yao, D.Xu, P., & Zhang, T. (2023). Altered default mode network causal connectivity patterns in autism spectrum disorder revealed by Liang information flow analysisHuman Brain Mapping44(6), 2279-2293https://doi.org/10.1002/hbm.26209


Figure 1 (Figs. 2a-d in the article). The information flow-based mean causal connectivity patterns of DMN for (a) ASD and (b) healthy controls. (c) The causal connectivity differences between the healthy-control group and the ASD group (pFDR p < .05). (d) Causal connectivity differences t-values map.


Figure 2 (Fig. 3b in the article). The mean In–Out degrees of the nodes in the ASD and healthy-control groups. The negative values represent the node as the causal source, and positive values the causal target.