A neuronal basis for the fan effect

The fan effect says that "activation" spreading from a concept is divided a mong the concepts it spreads to. Because this activation is not a physical entity, but on abstraction of unknown lower-level processes, the spreading activation model has predictive but not explanatory power. We provide one e xplanation of the fan effect by showing that distributed neuronal memory ne tworks (specifically, Hopfield networks) reproduce four qualitative aspects of the fan effect: faster recognition of sentences containing lower-fan wo rds, faster recognition of sentences when more cues ore provided, foster ac ceptance of studied sentences than rejection of probes, and foster recognit ion of sentences studied more frequently. These are all a natural result of the dynamics of distributed associative memory.