In both biometrics and facial expression recognition, previous literature emphasizes the configuration of facial features instead of their dynamics. I propose that dynamics provide essential information about person identity, neural control, communicative intent, and interpersonal coordination. To investigate this hypothesis, my colleagues and I have used multiple methods, including perceptual judgment, manual annotation of facial actions, and automatic facial image analysis and synthesis. My talk will review our findings in support of this hypothesis, including our use of real-time avatars and expression cloning to separate the joint influence of appearance and dynamics. We show that the dynamics of facial action are critical to individual differences in perception and expression of emotion and pain, communicative intent, person perception, and social interaction. I also review our related findings for vocal expression. In all, this work highlights the importance of dynamics to a broad range of intra- and interpersonal functions.