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Attending to Remember: Recent Advances in Methods and Theory

Shawn T. Schwartz, Haopei Yang, Alice M. Xue, Anthony D. Wagner

Current Directions in Psychological Science

June 4, 2025DOIPDF

Abstract

The ability to learn from and remember experiences (episodic memory) depends on multiple neurocognitive systems. In this article, we highlight recent advances in methods and theory that are unveiling how mechanisms of attention impact episodic memory. We first provide a high-level overview of the construct and neural substrates underlying attention and related goal-state processes, along with their interactions with memory. We then highlight budding evidence supporting the rhythmic nature of memory and attention, raising key questions about the role that the oscillatory phase of attention rhythms plays on memory encoding and retrieval. Third, we consider how understanding age-related changes in memory and attention can be further advanced by assaying the precision of memory. Last, we illustrate how real-time closed-loop experiments provide opportunities to test causal relationships between attention and memory. Along the way, we raise open questions and future research directions about how attention-memory interactions enable learning and remembering in the mind and brain.

Figure 1: Assessing the influence of attention on memory retrieval. Shown in (a) are the frontoparietal networks of attention and cognitive control derived from network parcellations computed from the full sample (N = 1,000) in Yeo et al. (2011). The schematic of the goal-directed memory-retrieval task used in Madore et al. (2020) shows (b) that pre-goal lapsing was measured using EEG posterior alpha power and pupil size in the last 1 s of the ITI, whereas goal-coding strength was measured using a retrieval goal- cue-locked ERP extracted from a midfrontal cluster of electrodes. In (c) the 1 s prior to the onset of the retrieval goal cue, pupil size (and posterior alpha power; not shown) significantly correlated with retrieval success, and midfrontal EEG goal-coding strength partially mediated this effect (n = 75; Madore et al., 2020). DAN = dorsal attention network; VAN = ventral attention network; CCN = cognitive control network; ITI = intertrial interval; ERP = event-related potential. Created in BioRender (Schwartz, 2025a). https:// BioRender.com/mejp1fu.
Figure 1: Assessing the influence of attention on memory retrieval. Shown in (a) are the frontoparietal networks of attention and cognitive control derived from network parcellations computed from the full sample (N = 1,000) in Yeo et al. (2011). The schematic of the goal-directed memory-retrieval task used in Madore et al. (2020) shows (b) that pre-goal lapsing was measured using EEG posterior alpha power and pupil size in the last 1 s of the ITI, whereas goal-coding strength was measured using a retrieval goal- cue-locked ERP extracted from a midfrontal cluster of electrodes. In (c) the 1 s prior to the onset of the retrieval goal cue, pupil size (and posterior alpha power; not shown) significantly correlated with retrieval success, and midfrontal EEG goal-coding strength partially mediated this effect (n = 75; Madore et al., 2020). DAN = dorsal attention network; VAN = ventral attention network; CCN = cognitive control network; ITI = intertrial interval; ERP = event-related potential. Created in BioRender (Schwartz, 2025a). https:// BioRender.com/mejp1fu.

Cite this paper

@article{schwartz2025,
  title = {Attending to Remember: Recent Advances in Methods and Theory},
  author = {Shawn T. Schwartz and Haopei Yang and Alice M. Xue and Anthony D. Wagner},
  year = {2025},
  journal = {Current Directions in Psychological Science},
  doi = {10.1177/09637214251339452}
}