Recent studies demonstrate that interleaving the exemplars of different categories, rather than blocking exemplars by category, can enhance inductive learning-the ability to categorize new exemplars-presumably because interleaving affords discriminative contrasts between exemplars from different categories. Consistent with this view, other studies have demonstrated that decreasing between-category similarity and increasing within-category variability can eliminate or even reverse the interleaving benefit. We tested another hypothesis, one based on the dual-learning systems framework-namely, that the optimal schedule for learning categories should depend on an interaction of the cognitive system that mediates learning and the structure of the particular category being learned. Blocking should enhance rule-based category learning, which is mediated by explicit, hypothesis-testing processes, whereas interleaving should enhance information-integration category learning, which is mediated by an implicit, procedural-based learning system. Consistent with this view, we found a crossover interaction between schedule (blocked vs. interleaved) and category structure (rule-based vs. information-integration).

Studies have found that anterior temporal lobe (ATL) is critical for detailed knowledge of object categories, suggesting that it has an important role in semantic memory. However, in addition to information about entities, such as people and objects, semantic memory also encompasses information about places. We tested predictions stemming from the PMAT model, which proposes there are distinct systems that support different kinds of semantic knowledge: an anterior temporal (AT) network, which represents information about entities; and a posterior medial (PM) network, which represents information about places. We used representational similarity analysis to test for activation of semantic features when human participants viewed pictures of famous people and places, while controlling for visual similarity. We used machine learning techniques to quantify the semantic similarity of items based on encyclopedic knowledge in the Wikipedia page for each item and found that these similarity models accurately predict human similarity judgments. We found that regions within the AT network, including ATL and inferior frontal gyrus, represented detailed semantic knowledge of people. In contrast, semantic knowledge of places was represented within PM network areas, including precuneus, posterior cingulate cortex, angular gyrus, and parahippocampal cortex. Finally, we found that hippocampus, which has been proposed to serve as an interface between the AT and PM networks, represented fine-grained semantic similarity for both individual people and places. Our results provide evidence that semantic knowledge of people and places is represented separately in AT and PM areas, whereas hippocampus represents semantic knowledge of both categories.

The induction of categories and concepts from examples—which plays an important role in how we come to organize and understand the world—can happen at multiple levels, but how does competing values of these different levels affect their learning? Using perceptually rich images of snakes that could be categorized by their specific genus or a broader category, and that varied in value (whether the snake was venomous vs. whether it was tropical), we asked participants to attend to one level but tested induction at both levels. We found an interaction between study instruction and intrinsic value: Participants in the low-value condition were better able to induce the instructed level, whereas participants in the high-value condition, were significantly better at learning the broad category (i.e., venomness), regardless of instruction. Our results suggest that intrinsically valuable features can affect learning by disrupting the intentional learning of other, task-relevant information, but enhancing the incidental learning of these same features.

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