LAUSR

Certain transformations must occur within the brain to allow rapid processing of familiar experiences. Complex objects are thought to become unitized, whereby multifeature conjunctions are retrieved as rapidly as a single feature. Behavioral studies strongly support unitization theory, but a compelling neural mechanism is lacking. Here, we examined how unitization transforms conjunctive representations to become more "feature-like" by recruiting posterior regions of the ventral visual stream (VVS) whose architecture is specialized for processing single features. We used functional magnetic resonance imaging to scan humans before and after visual training with novel objects. We implemented a novel multivoxel pattern analysis to measure a conjunctive code, which represented a conjunction of object features above and beyond the sum of the parts. Importantly, a multivoxel searchlight showed that the strength of conjunctive coding in posterior VVS increased posttraining. Furthermore, multidimensional scaling revealed representational separation at the level of individual features in parallel to the changes at the level of feature conjunctions. Finally, functional connectivity between anterior and posterior VVS was higher for novel objects than for trained objects, consistent with early involvement of anterior VVS in unitizing feature conjunctions in response to novelty. These data demonstrate that the brain implements unitization as a mechanism to refine complex object representations over the course of multiple learning experiences.