Selective attention improves self-organization of cortical maps with multiple inputs

Models of self-organizing cortical maps have focused on demonstrations with single objects in the environment. Recently, the validity of a traditional biological model has been questioned for the case of multiple simultaneous input sources. Here we show that the standard model is able to self-organize with multiple inputs. However, we also show that the ability to self-organization can be enhanced considerably by including top-down attention as well as some noise. The model is also used to simulate the development of tuning curves.