Neurally Inspired Models of Psychological Processes

Computational models provide a way to quantitatively explore theories about how brains give rise to cognition and behavior. This chapter introduces some basic approaches to modeling psychological phenomena, focusing on connectionist simulations of perception and memory. First, a rationale for developing computer models of behavior and brain function is presented, along with a brief description of basic computational properties of artificial neural networks. This is followed by a series of illustrative models of object recognition, perceptual learning, episodic memory, and age-related cognitive deficits. Collectively, these modeling efforts demonstrate the utility of emulating neural mechanisms in attempts to understand both observed actions and inferred mental processes. Although much work remains before the gaps between brain and behavior are bridged, the results of computational modeling efforts so far suggest that computer simulations provide a powerful tool that ultimately may help to span this divide.