Spreading activation is a method for searching associative networks, biological and artificial neural networks, or semantic networks.[1] The search process is initiated by labeling a set of source nodes (e.g. concepts in a semantic network) with weights or "activation" and then iteratively propagating or "spreading" that activation out to other nodes linked to the source nodes. Most often these "weights" are real values that decay as activation propagates through the network. When the weights are discrete this process is often referred to as marker passing. Activation may originate from alternate paths, identified by distinct markers, and terminate when two alternate paths reach the same node. However brain studies show that several different brain areas play an important role in semantic processing.[2]
Spreading activation in semantic networks as a model were invented in cognitive psychology[3][4] to model the fan out effect.[citation needed]
Spreading activation can also be applied in information retrieval,[5][6] by means of a network of nodes representing documents and terms contained in those documents.