SOAR: an architecture for general intelligence
Artificial Intelligence
A hippocampal model of recognition memory
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
The effect of correlated variability on the accuracy of a population code
Neural Computation
A general formulation of conceptual spaces as a meso level representation
Artificial Intelligence
Toward a unified model of attention in associative learning
Journal of Mathematical Psychology
Hi-index | 0.00 |
Interpretations of images of the brain are starting to reveal the conceptual tasks in which the person was engaged at the time of imaging. Existing mathematical models can explain the patterns of activity observed in such images in terms of the coherent activity of large populations of neurons, but not in terms of cognition. This paper is an early investigation into how such patterns might provide the internal representations for a cognitive system. Probes, working memories and memories are all represented as images. The accompanying process model describes how attention is set according to the contents of working memory, how attention determines what parts of the probe are memorised, how memories are activated according to similarity to the probe in areas in attention, and how working memory is managed. The model is demonstrated on re-creations of classic simulations of recognition memory and categorisation.