Dynamic Modulation of the Action Observation Network by Movement Familiarity

Abstract

When watching another person’s actions, a network of sensorimotor brain regions, collectively termed the action observation network (AON), is engaged. Previous research suggests that the AON is more responsive when watching familiar compared with unfamiliar actions. However, most research into AON function is premised on comparisons of AON engagement during different types of task using univariate, magnitude-based approaches. To better understand the relationship between action familiarity and AON engagement, here we examine how observed movement familiarity modulates AON activity in humans using dynamic causal modeling, a type of effective connectivity analysis. Twenty-one subjects underwent fMRI scanning while viewing whole-body dance movements that varied in terms of their familiarity. Participants’ task was to either predict the next posture the dancer’s body would assume or to respond to a non– action-related attentional control question. To assess individuals’ familiarity with each movement, participants rated each video on a measure of visual familiarity after being scanned. Parametric analyses showed more activity in left middle temporal gyrus, inferior parietal lobule, and inferior frontal gyrus as videos were rated as increasingly familiar. These clusters of activity formed the regions of interest for dynamic causal modeling analyses, which revealed attenuation of effective connectivity bidirectionally between parietal and temporalAONnodes when participants observed videos they rated as increasingly familiar. As such, the findings provide partial support for a predictive coding model of the AON, as well as illuminate how action familiarity manipulations can be used to explore simulationbased accounts of action understanding.