Updating memories of unwanted emotions during human sleep

Abstract

Post-learning sleep contributes to memory consolidation. Yet it remains contentious whether sleep affords opportunities to modify or update emotional memories, particularly when people would prefer to forget those memories. Here, we attempted to update memories during sleep, using spoken positive words paired with cues to recent memories of aversive events. Affective updating using positive words during human non-rapid eye movement (NREM) sleep, compared with using neutral words instead, reduced negative affective judgments in post-sleep tests, suggesting that the recalled events were perceived as less aversive. Electroencephalogram (EEG) analyses showed that positive words modulated theta and spindle/sigma activity; specifically, to the extent that theta power was larger for the positive words than for the memory cues that followed, participants judged the memory cues less negatively. Moreover, to the extent that sigma power was larger for the positive words than for the memory cues that followed, participants forgot more episodic details about aversive events. Notably, when the onset of individual positive words coincided with the up-phase of slow oscillations (a state characterized by increased cortical excitability during NREM sleep), affective updating was more successful. In sum, we altered the affective content of memories via the strategic pairing of positive words and memory cues during sleep, linked with EEG theta power increases and the slow oscillation up-phase. These findings suggest novel possibilities for modifying unwanted memories during sleep, which would not require people to consciously confront memories that they prefer to avoid.

Keywords: memory editing; sleep learning; sleep spindle; slow oscillation; targeted memory reactivation; theta power.

Figure 1:. Experiment procedure and affective updating effect.

(A)The general procedure of experiment. (B) Affective updating procedure during sleep (for details, see STAR Methods). (C) Behavioral outcomes of affective updating (left) and memory change of detail (right). Note that the affective updating effect remained significant when using mean ± 2.5 median absolute deviation (MAD) to exclude statistical outliers (p = 0.011). *: p < 0.05.

Figure 2:. Word-elicited ERPs during NREM sleep (first: updating word; second: memory cue).

Upper panel: butterfly plot of ERPs to spoken words collapsing across positive and neutral updating conditions. Graded area denotes the global field power (GFP). Middle panel: significant time windows (colored areas) across frontal-central electrodes when comparing ERPs against zero. Bottom panel: grand averaged ERPs across frontal-central electrodes (F1/2, Fz, FC1/2, FCz, C1/2, Cz). See also Figure S1.

Figure 3:. Word-elicited, time-frequency-resolved EEG activity during NREM sleep.

(A) Time-frequency results averaging across all trials and participants over frontal-central electrodes (F1/2, Fz, FC1/2, FCz, C1/2, Cz). (B) A t-values map from a cluster-based permutation test across frequency bands and time points, representing how updating words and memory cues modulated EEG activity during NREM sleep. Time-frequency plots for (C) positive and for (D) neutral updating conditions, with solid and dash lines highlighting significant clusters derived from (B) within the 4–8 Hz theta and the 12–16 Hz sigma bands, together with their scalp distributions. (E) Theta and (F) sigma power extracted from the significant clusters (highlighted in solid lines) were significantly different between positive and neutral words. *: p_corrected < 0.05. Theta and sigma differences remained significant after excluding statistical outliers (mean ± 2.5 MAD, theta: p = 0.013, sigma: p < 0.001).

Figure 4:. Updating words (circles) and memory cues (triangles) modulated theta (A) and sigma (B) power.

Theta and sigma power were derived from their corresponding significant clusters highlighted in Figures 3C and 3D. (C) Theta power differences between positive words and cues positively predicted affective updating. (D) Sigma power differences between positive words and cues negatively predicted memory changes in details. *: p < 0.05, **: p < 0.01. See also Figure S2 and S3.

Figure 5:. The coupling between SO up-phases and positive word onset drove affective updating.

(AB) The distribution of updating words and cues onsets relative to SO phases. Upper panel: shaded areas in the radar plot indicated the trial numbers of word onset phase distribution from negative-change and negative-stay in positive (A) and neutral (B) updating conditions, using all trials from all participants. The colored circles represent the averaged preferred phase from negative-change and negative-stay sub-conditions, for each participant. Arrows indicated the mean vector length across all participants. Bottom panel: grand-averaged ERPs from negative-change and negative-stay trials in positive (A) and neutral (B) updating, with a 2 Hz low-pass filter applied. (C) Results from the linear mixed model, using the number of individual updating words (left panel) and memory cues (right panel) during SO up-phases to predict affective updating. The coupling results remained significant after excluding outliers (Figure S4). Shaded area indicates 95% CI. **: p < 0.01 ***: p < 0.001.