Decades of research have demonstrated that a region of the right fusiform gyrus (FG) and right posterior superior temporal sulcus (pSTS) responds preferentially to static faces and biological motion, respectively. Despite this view, both regions activate in response to both stimulus categories and to a range of other stimuli, such as goal-directed actions, suggesting that these regions respond to characteristics of animate agents more generally. Here we propose a neural model for animacy detection composed of processing streams that are initially differentially sensitive to cues signaling animacy, but that ultimately act in concert to support reasoning about animate agents. We use dynamic causal modeling, a measure of effective connectivity, to demonstrate that the directional flow of information between the FG and pSTS is initially dependent on the characteristics of the animate agent presented, a key prediction of our proposed network for animacy detection.
Keywords: animate; dynamic casual modeling; effective connectivity; fusiform; pSTS.
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