Semantic Knowledge of Famous People and Places Is Represented in Hippocampus and Distinct Cortical Networks.

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.SIGNIFICANCE STATEMENT Humans acquire detailed semantic knowledge about people (e.g., their occupation and personality) and places (e.g., their cultural or historical significance). While research has demonstrated that brain regions preferentially respond to pictures of people and places, less is known about whether these regions preferentially represent semantic knowledge about specific people and places. We used machine learning techniques to develop a model of semantic similarity based on information available from Wikipedia, validating the model against similarity ratings from human participants. Using our computational model, we found that semantic knowledge about people and places is represented in distinct anterior temporal and posterior medial brain networks, respectively. We further found that hippocampus, an important memory center, represented semantic knowledge for both types of stimuli.