Idiosyncratic Patterns of Representational Similarity in Prefrontal Cortex Predict Attentional Performance

Abstract

The efficiency of finding an object in a crowded environment depends largely on the similarity of nontargets to the search target. Models of attention theorize that the similarity is determined by representations stored within an "attentional template" held in working memory. However, the degree to which the contents of the attentional template are individually unique and where those idiosyncratic representations are encoded in the brain are unknown. We investigated this problem using representational similarity analysis of human fMRI data to measure the common and idiosyncratic representations of famous face morphs during an identity categorization task; data from the categorization task were then used to predict performance on a separate identity search task. We hypothesized that the idiosyncratic categorical representations of the continuous face morphs would predict their distractability when searching for each target identity. The results identified that patterns of activation in the lateral prefrontal cortex (LPFC) as well as in face-selective areas in the ventral temporal cortex were highly correlated with the patterns of behavioral categorization of face morphs and search performance that were common across subjects. However, the individually unique components of the categorization behavior were reliably decoded only in right LPFC. Moreover, the neural pattern in right LPFC successfully predicted idiosyncratic variability in search performance, such that reaction times were longer when distractors had a higher probability of being categorized as the target identity. These results suggest that the prefrontal cortex encodes individually unique components of categorical representations that are also present in attentional templates for target search.