Perceptual Categorization: Connectionist Modelling and Decision Rules

Although it is currently popular to model human associative learning using connectionist networks, the mechanism by which their output activations are converted to probabilities of response has received relatively little attention. Several possible models of this decision process are considered here, including a simple ratio rule, a simple difference rule, their exponential versions, and a winner-take-all network. Two categorization experiments that attempt to dissociate these models are reported. Analogues of the experiments were presented to a single-layer, feed-forward, delta-rule network. Only the exponential ratio rule and the winner-take-all architecture, acting on the networks' output activations that corresponded to responses available on test, were capable of fully predicting the mean response results. In addition, unlike the exponential ratio rule, the winner-take-all model has the potential to predict latencies. Further studies will be required to determine whether latencies produced under more stringent conditions conform to the model's predictions.     

To know where the bodies are buried: The use of the cognitive interview in an environmental scale spatial memory retrieval task

Missing body homicide cases have gained public interest globally due to some high-profile cases. In many of these cases, the task of locating the victim's remains relies on the information investigators can gain through the interviewing of willing suspects. To date, investigative interviewing research has largely focused on the retrieval of episodic memory (events) without focusing on spatial memory, a prominent cognitive task required in locating a victim's remains. The current experiment tests the enhanced cognitive interview (ECI) against a free recall strategy in a mock homicide scenario where participants are required to hide and retrieve an object in a natural bushland setting. The results showed that those in the ECI condition produced more coarse- and fine-grained details of landmarks and their actions at and journeying to the deposition site. This demonstrates the value of using the ECI in generating more valuable information to assist in successive search attempts.