Modeling Age Differences in Infant Category Learning.

We used an encoder version of cascade correlation to simulate Younger and Cohen's (1983, 1986) finding that 10-month-olds recover attention on the basis of correlations among stimulus features, but 4- and 7-month-olds recover attention on the basis of stimulus features. We captured these effects by varying the score threshold parameter in cascade correlation, which controls how deeply training patterns are learned. When networks learned deeply, they showed more error to uncorrelated than to correlated test patterns, indicating that they abstracted correlations during familiarization. When prevented from learning deeply, networks decreased error during familiarization and showed as much error to correlated as to uncorrelated tests but less than to test items with novel features, indicating that they learned features but not correlations among features. Our explanation is that older infants learn more from the same exposure than do younger infants. Unlike previous explanations that postulate unspecified qualitative shifts in processing with age, our explanation focuses on quantitatively deeper learning with increasing age. Finally, we provide some new empirical evidence to support this explanation.