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Emotion perception is essential to affective and cognitive development whichinvolves distributed brain circuits. The ability of emotion identificationbegins in infancy and continues to develop throughout childhood andadolescence. Understanding the development of brain's emotion circuitry mayhelp us explain the emotional changes observed during adolescence. Our previousstudy delineated the trajectory of brain functional connectivity (FC) from latechildhood to early adulthood during emotion identification tasks. In this work,we endeavour to deepen our understanding from association to causation. Weproposed a Bayesian incorporated linear non-Gaussian acyclic model (BiLiNGAM),which incorporated our previous association model into the prior estimationpipeline. In particular, it can jointly estimate multiple directed acyclicgraphs (DAGs) for multiple age groups at different developmental stages.Simulation results indicated more stable and accurate performance over varioussettings, especially when the sample size was small (high-dimensional cases).We then applied to the analysis of real data from the PhiladelphiaNeurodevelopmental Cohort (PNC). This included 855 individuals aged 8-22 yearswho were divided into five different adolescent stages. Our network analysisrevealed the development of emotion-related intra- and inter- modularconnectivity and pinpointed several emotion-related hubs. We furthercategorized the hubs into two types: in-hubs and out-hubs, as the center ofreceiving and distributing information. Several unique developmental hubstructures and group-specific patterns were also discovered. Our findings helpprovide a causal understanding of emotion development in the human brain.

A Bayesian incorporated linear non-Gaussian acyclic model for multiple  directed graph estimation to study brain emotion circuit development in  adolescence