Isolating memory reactivation and binding processes that support memory integration will enable a more detailed characterization of the neural mechanisms that underlie retrieval-mediated learning. Moreover, by quantitatively indexing reactivation during encoding, the present study provides a means of linking retrieval-mediated learning processes to future inference success. Specifically, we utilized a modified version of the associative inference task (Preston et al., 2004; Zeithamova and Preston, 2010) in combination with

multivoxel pattern analysis (MVPA) (Norman et al., 2006; Polyn et al., 2005) 17-AAG supplier to investigate the neural mechanisms of retrieval-mediated learning and its relationship to flexible inference about related events. The task consisted of two phases: associative encoding during block-design functional magnetic resonance imaging (fMRI) and an inferential recognition memory test after scanning. Images of objects and outdoor scenes were organized into groups of three (triads) and presented to participants as overlapping associations of image pairs (AB, BC, e.g., zucchini-pail, pail-truck,

Figure 1A). The first presented image pair from each triad consisted of stimuli of the same content class: two objects or two scenes. Images in the second pair were either of the same content class (e.g., two objects) or of mixed content (i.e., one object and one scene). Both image pairs from Talazoparib supplier a given triad were presented three times each in an interleaved manner (Figure 1B). After scanning, participants were tested using a two-alternative forced choice paradigm that Adenosine included directly learned association trials (AB, BC) as well as inference trials that tested knowledge of the relationship between two discrete episodes (AC, e.g., zucchini-truck, Figure 1C). The organization of triad types enabled us to measure reactivation of related, but unseen, stimulus content in the absence of an explicit behavioral response

by comparing encoding trials for which the presented information was of the same content class (e.g., two objects), but previously associated information was of a different content class (i.e., object or scene, Figure 2). We hypothesized that reactivation of related content during overlapping events would be reflected in content-sensitive regions within the ventral temporal cortex, with the degree of reactivation predicting performance on the inferential judgments. We also examined how activation in VMPFC, hippocampus, and surrounding MTL cortices relates to the magnitude of reactivation and successful binding of overlapping experiences. By isolating signatures of memory reactivation and integration during encoding, the current study provides important insights into the specific neural mechanisms that underlie the online formation of relational memory networks via retrieval-mediated learning.