Relational Integration, Inhibition, and Analogical Reasoning in Older Adults.

Abstract

The difficulty of reasoning tasks depends on their relational complexity, which increases with the number of relations that must be considered simultaneously to make an inference, and on the number of irrelevant items that must be inhibited. The authors examined the ability of younger and older adults to integrate multiple relations and inhibit irrelevant stimuli. Young adults performed well at all but the highest level of relational complexity, whereas older adults performed poorly even at a medium level of relational complexity, especially when irrelevant information was presented. Simulations based on a neurocom- putational model of analogical reasoning, Learning and Inference with Schemas and Analogies (LISA), suggest that the observed decline in reasoning performance may be explained by a decline in attention and inhibitory functions in older adults. Human reasoning depends in part on the ability to integrate multiple relations and inhibit irrelevant information. For example, if Bill is taller than Carl and Abe is taller than Bill, one must integrate the two "taller than" relations to make the inference that Abe is taller than Carl. A relational analysis of reasoning provides a framework that makes it possible to define levels of complexity for particular reasoning tasks. According to Halford (1998; Hal- ford & Wilson, 1980; Halford, Wilson, & Phillips, 1998), the processing load for any step in a task is determined by the number of dimensions, or relations, that must be processed simultaneously to make the decisions required for that step. Dimensions are viewed as analogous to degrees of freedom, or the number of independent sources of variation. At the first level of complexity (Level 1), the reasoner needs to consider only one relation to solve the task correctly.1 At Level 2, the reasoner must integrate two relations, and so on. For example, it is necessary to integrate two relations to correctly solve the transitive inference problem de- scribed previously. More generally, we define relational complexity as the number of relations that a reasoner must simultaneously "hold in mind" to