Social robotics is a highly useful field that is rapidly growing. Advances in embedded systems and fields like neuromorphic computing provide hardware solutions for the computationally complex models needed to produce realistic, pro-social socio-emotional robots. This work details a robot which executes a simplified amygdala model to determine an emotional state from visual input and a subsequent behavioral response. Each nuclei of this model is processed on a different neuromorphic platform, including the SpiNNaker, Loihi, and Braindrop chips. Although simplified, this robot and its underlying model illustrate a proof of concept for more complicated and biologically-plausible socio-emotional robots.