Predicting the integration of overlapping memories by decoding mnemonic processing states during learning

Abstract

The hippocampal memory system is thought to alternate between two opposing processing states: encoding and retrieval. When present experience overlaps with past experience, this creates a potential tradeoff between encoding the present and retrieving the past. This tradeoff may be resolved by memory integration—that is, by forming a mnemonic representation that links present experience with overlapping past experience. Here, we used fMRI decoding analyses to predict when—and establish how—past and present experiences become integrated in memory. In an initial experiment, we alternately instructed subjects to adopt encoding, retrieval or integration states during overlapping learning. We then trained across-subject pattern classifiers to ‘read out’ the instructed processing states from fMRI activity patterns. We show that an integration state was clearly dissociable from encoding or retrieval states. Moreover, trial-by-trial fluctuations in decoded evidence for an integration state during learning reliably predicted behavioral expressions of successful memory integration. Strikingly, the decoding algorithm also successfully predicted specific instances of spontaneous memory integration in an entirely independent sample of subjects for whom processing state instructions were not administered. Finally, we show that medial prefrontal cortex and hippocampus differentially contribute to encoding, retrieval, and integration states: whereas hippocampus signals the tradeoff between encoding vs. retrieval states, medial prefrontal cortex actively represents past experience in relation to new learning.

Temporal Proximity Promotes Integration of Overlapping Events

“…Evidence for reactivation of existing memories—as measured by a visual content classifier—was equivalent during encoding of overlapping pairs from the two temporal conditions. In contrast, evidence for integration—as measured by a mnemonic strategy classifier from an independent study (Richter, Chanales & Kuhl, 2016, NeuroImage 124, 323–335)—was greater for same day overlapping events, paralleling the behavioral results. During inference itself, activation patterns further differentiated when participants were making inferences about events acquired on the same day versus across days.…”

Hippocampal–medial prefrontal circuit supports memory updating during learning and post-encoding rest

“…A number of existing studies have shown that prior memories may be reactivated during encoding of overlapping experiences (Hupbach et al, 2007; Kuhl et al, 2010; Jones et al, 2012; Zeithamova et al, 2012a; Schlichting and Preston, 2014; Richter et al, 2015). Such reactivation has been linked to better memory for the reactivated content itself (Kuhl et al, 2010), superior learning of the overlapping content (Schlichting and Preston, 2014), and an enhanced ability to make novel judgments that span the two events (Zeithamova et al, 2012a; Richter et al, 2015).…”

“…Such reactivation has been linked to better memory for the reactivated content itself (Kuhl et al, 2010), superior learning of the overlapping content (Schlichting and Preston, 2014), and an enhanced ability to make novel judgments that span the two events (Zeithamova et al, 2012a; Richter et al, 2015). Accordingly, we hypothesized that greater functional coupling of HPC and MPFC with face-sensitive visual regions should also be associated with better subsequent memory specifically for the overlapping associations due to the related A stimuli being faces.…”

Memory integration constructs maps of space, time, and concepts

“…For instance, what are the boundary conditions that determine when representations of overlapping memories are integrated rather than separated, and how might we manipulate the formation of integrated codes of experience? While initial findings suggest that the strength of existing knowledge [18], the degree of memory reactivation during encoding [17], the magnitude of memory-based prediction errors [15], and task demands [84] all impact the likelihood of integration, more work is needed to understand the full complement of conditions that influence how we represent related episodes in memory. As noted above, different memory circuits (e.g., anterior and posterior hippocampus) may integrate information at different scales.…”