Metaphor comprehension involves an interaction between the meaning of the topic and vehicle terms of the metaphor. Meaning is represented by vectors in a high-dimensional semantic space. Predication modifies the topic vector by merging it with selected features of the vehicle vector. The resulting metaphor vector can be evaluated by comparing it with known landmarks in the semantic space. Thus, metaphorical predication is treated in the present model in exactly the same way as literal predication. Some experimental results concerning metaphor comprehension are simulated within this framework, such as the non-reversibility of metaphors, priming of metaphors with literal statements, and priming of literal statements with metaphors. (Walter Kintsch)