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Fear extinction is the well-known process of fear reduction through repeated re-exposure to a feared stimulus without the aversive outcome. The last two decades have witnessed a surge of interest in extinction learning. First, extinction learning is observed across species, and especially research on rodents has made great strides in characterising the physical substrate underlying extinction learning. Second, extinction learning is considered of great clinical significance since it constitutes a crucial component of exposure treatment. While effective in reducing fear responding in the short term, extinction learning can lose its grip, resulting in a return of fear (i.e., laboratory model for relapse of anxiety symptoms in patients). Optimization of extinction learning is, therefore, the subject of intense investigation. It is thought that the success of extinction learning is, at least partly, determined by the mismatch between what is expected and what actually happens (prediction error). However, while much of our knowledge about the neural circuitry of extinction learning and factors that contribute to successful extinction learning comes from animal models, translating these findings to humans has been challenging for a number of reasons. Here, we present an overview of what is known about the animal circuitry underlying extinction of fear, and the role of prediction error. In addition, we conducted a systematic literature search to evaluate the degree to which state-of-the-art neuroimaging methods have contributed to translating these findings to humans. Results show substantial overlap between networks in animals and humans at a macroscale, but current imaging techniques preclude comparisons at a smaller scale, especially in sub-cortical areas that are functionally heterogeneous. Moreover, human neuroimaging shows the involvement of numerous areas that are not typically studied in animals. Results obtained in research aimed to map the extinction circuit are largely dependent on the methods employed, not only across species, but also across human neuroimaging studies. Directions for future research are discussed.