Abstract: We examined how the brain organizes interrelated facts during learning and how the facts are subsequently manipulated in a transitive inference (TI) paradigm (e.g., if A<B and B<C, then A<C). This task determined features such as learned facts and behavioral goals, but the learned facts could be organized in any of several ways. For example, if one learns a list by operating on paired items, the pairs may be stored individually as separate facts and reaction time (RT) should decrease with learning. Alternatively, the pairs may be stored as a single, unified list, which may yield a different RT pattern. We characterized RT patterns that occurred as participants learned, by trial and error, the predetermined order of 11 shapes. The task goal was to choose the shape occurring closer to the end of the list, and feedback about correctness was provided during this phase. RT increased even as its variance decreased during learning, suggesting that the learnt knowledge became progressively unified into a single representation, requiring more time to manipulate as participants acquired relational knowledge. After learning, non-adjacent (NA) list items were presented to examine how participants reasoned in a TI task. The task goal also required choosing from each presented pair the item occurring closer to the list end, but without feedback. Participants could solve the TI problems by applying formal logic to the previously learnt pairs of adjacent items; alternatively, they could manipulate a single, unified representation of the list. Shorter RT occurred for NA pairs having more intervening items, supporting the hypothesis that humans employ unified mental representations during TI. The response pattern does not support mental logic solutions of applying inference rules sequentially, which would predict longer RT with more intervening items. We conclude that the brain organizes information in such a way that reflects the relations among the items, even if the facts were learned in an arbitrary order, and that this representation is subsequently used to make inferences.

Abstract: Food-storing birds, black-capped chickadees (Poecile atricapilla), and nonstoring birds, dark-eyed juncos (Junco hyemalis), matched color or location on a touch screen. Both species showed a divided attention effect for color but not for location (Experiment 1). Chickadees performed better on location than on color with retention intervals up to 40 s, but juncos did not (Experiment 2). Increasing sample-distractor distance improved performance similarly in both species. Multidimensional scaling revealed that both use a Euclidean metric of spatial similarity (Experiment 3). When choosing between the location and color of a remembered item, food storers choose location more than do nonstorers. These results explain this effect by differences in memory for location relative to color, not division of attention or spatial discrimination ability.

Abstract: The traditional approach to the study of selective attention in animal discrimination learning has been to ask if animals are capable of the central selective processing of stimuli, such that certain aspects of the discriminative stimuli are partially or wholly ignored while their relationships to each other, or other relevant stimuli, are processed. A notable characteristic of this research has been that procedures involve the acquisition of discriminations, and the issue of concern is whether learning is selectively determined by the stimulus dimension defined by the discriminative stimuli. Although there is support for this kind of selective attention, in many cases, simpler nonattentional accounts are sufficient to explain the results. An alternative approach involves procedures more similar to those used in human information-processing research. When selective attention is studied in humans, it generally involves the steady state performance of tasks for which there is limited time allowed for stimulus input and a relatively large amount of relevant information to be processed; thus, attention must be selective or divided. When this approach is applied to animals and alternative accounts have been ruled out, stronger evidence for selective or divided attention in animals has been found. Similar processes are thought to be involved when animals search more natural environments for targets. Finally, an attempt is made to distinguish these top-down attentional processes from more automatic preattentional processes that have been studied in humans and other animals.