Phys.org  August 15, 2024 Artificial intelligence systems and neural network models can reduce the intricacy of understanding creative cognition. The Hopfield neural network (HNN) is a simple model known for its biological plausibility in storing and retrieving neuron patterns. Researchers Germany implemented certain modifications to HNN as a step toward the larger framework of creative thinking-based association. The modifications included introducing pattern weights control, which provides a robust representation for content addressable memory and conceptual links in stored data. They identified two mechanisms controlling the transition from analytical to associative-based thinking, namely, the activation threshold of neurons, which acts as […]