Neural Patterns are More Similar across Individuals during Successful Memory Encoding than during Failed Memory Encoding

Abstract

After experiencing the same episode, some people can recall certain details about it, whereas others cannot. We investigate how common (intersubject) neural patterns during memory encoding influence whether an episode will be subsequently remembered, and how divergence from a common organization is associated with encoding failure. Using functional magnetic resonance imaging with intersubject multivariate analyses, we measured brain activity as people viewed episodes within wildlife videos and then assessed their memory for these episodes. During encoding, greater neural similarity was observed between the people who later remembered an episode (compared with those who did not) within the regions of the declarative memory network (hippocampus, posterior medial cortex [PMC], and dorsal Default Mode Network [dDMN]). The intersubject similarity of the PMC and dDMN was episode-specific. Hippocampal encoding patterns were also more similar between subjects for memory success that was defined after one day, compared with immediately after retrieval. The neural encoding patterns were sufficiently robust and generalizable to train machine learning classifiers to predict future recall success in held-out subjects, and a subset of decodable regions formed a network of shared classifier predictions of subsequent memory success. This work suggests that common neural patterns reflect successful, rather than unsuccessful, encoding across individuals.

Keywords: MVPA; encoding; episodic memory; hippocampus; recall.

Figure 1

Regions of interest displayed on standard TT_N27 template brain. A (primary visual network: red; FG: turquoise; hippocampus: orange; PHC: blue; ACC: pink; PCC: purple). B (dDMN: navy; vDMN: salmon; PMC: green).

Figure 2

Overview of methodological approach for measuring the similarity of neural representations for individual episodes, and when collapsed across episodes. Columns outlined in black represent episodes that were subsequently retrieved; columns outlined in gray represent episodes that were not subsequently retrieved. Rows represent individual voxels within the ROI. Colors within the patterns represent z-scored BOLD response. A: Procedure for collapsing individual episodes within a subject to create average patterns based on subsequent memory (retrieved and not-retrieved). B: Procedure for correlating patterns for average individual episodes between each subject and other subjects showing successful retrieval. C: Procedure for correlating average patterns for collapsed episodes between individual subjects and the group.

Figure 3

Representational similarity, quantified as Fisher-Z r-values, of individual retrieved and not-retrieved episodes within each ROI. *indicates statistical significance (P < 0.05). Error bars reflect the standard error of the mean.

Figure 4

Representational similarity, quantified as Fisher-Z r-values, of average retrieved and not-retrieved episodes within each ROI, collapsed across episodes. *indicates statistical significance (P < 0.05). Error bars reflect the standard error of the mean.

Figure 5

Depiction of the discrimination network of subsequently retrieved and not-retrieved outcomes based on encoding activity. The network consists of ACC, PCC, and PMC. Panel A depicts the observed frequencies of classifier concordance. Width of connecting bars between regions depicts the magnitude of Chi-Square statistic for classifier predictions. Panel B depicts the expected frequencies of classifier concordance if the regions were independent. Values within black boxes indicate the frequency of classifier agreement; values within white boxes indicate the frequency of disagreement.