Attentional biases in geometric form perception

This paper reports the operation of robust attentional bias to the top and right during perception of small, single geometric forms. Same/different judgements of successively presented standard and comparison forms are faster when local differences are located at top and right rather than in other regions of the forms. The bias persists when form size is reduced to approximately one degree of visual angle, and it is unaffected by saccadic eye movements and by instructions to attend to other reliably differentiating regions of the forms. Results lend support in various degrees to two of the possible explanations of the bias: (1) a static, skewed distribution of attentional resources around eye fixation; and (2) biased, covert scanning that commences invariably at the top and right of stim ulus forms. Origins of the bias in terms of possible left-hemispheric capacity for constructing representations of visual stimuli from parts, as well as in terms of reading experience and prevailing optic flow during locomotion through space are considered. Recent investigations of conditions under which the bias can be maintained or reduced are mentioned.     

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.     

Multiattribute Decision Making in Context: A Dynamic Neural Network Methodology

A theoretical structure for multiattribute decision making is presented, based on a dynamical system for interactions in a neural network incorporating affective and rational variables. This enables modeling of problems that elude two prevailing economic decision theories: subjective expected utility theory and prospect theory. The network is unlike some that fit economic data by choosing optimal weights or coefficients within a predetermined mathematical framework. Rather, the framework itself is based on principles used elsewhere to model many other cognitive and behavioral data, in a manner approximating how humans perform behavioral functions. Different, interconnected modules within the network encode (a) attributes of objects among which choices are made, (b) object categories, (c) and goals of the decision maker. An example is utilized to simulate the actual consumer choice between old and new versions of Coca-Cola. Potential applications are also discussed to market decisions involving negotiations between participants, such as international petroleum traders.