Modeling the effect of hint timing on the idea generation process

In this paper we study the effect of external ideas on brainstorming by means of two computational models: a transient emergent attractors model (TEAM) and a probabilistic associative model (PAM). New behavioral experimental results show that hints or others´ ideas can either hinder or enhance ideas generated during exposure period, while they consistently enhance the quantity of ideas produced after exposure. The TEAM model consists of a neural network of concept nodes connected by means of category membership and relatedness. Ideas emerge dynamically from the activity of the network by temporarily strengthening the connections between co-active nodes. Local inhibition inactivates current idea nodes and allows another idea to form. Active nodes prime connected inactive nodes depending on the recent activity of the node. The model shows that hindering of the number of ideas during hint presentation depends on the strength of hints and that the speed and duration of priming is essential for the long-term priming effect of hints observed in experiments. For comparison purposes, a PAM model originally proposed by Brown and Paulus (1998) is used to explain the same experimental data.