A Neurally Plausible Model of Metaphor Learning

Conceptual metaphor is a widespread phenomenon in language and thought. While there has been progress in the computational modeling of metaphoric inference (Narayanan1997,99), there is no existing model model of metaphor acquisition that matches psycholinguistic data (Johnson 1997). This paper suggests that the combination of Spike Timing Dependent Plasticity (STDP) (a widely prevalent learning mechanism found in many areas of the brain) and the specific dynamics of the input activation patterns culled from the psycholinguistic data, can provide a neurally plausible account of metaphor acquisition. The dynamics of the interaction between the learning mechanism and the developmental input sequence seems also to provide insights on puzzling paradoxes in the dynamics of metaphor learning, including the partial nature of the mappings. The theory presented is based on a computational simulation of STDP with parameters culled from the experimental literature. As far as we are aware, the work reported here is the first model of metaphor acquisition that is consistent with the psychological and linguistic evidence.