Induced α rhythms track the content and quality of visual working memory representations with high temporal precision

Abstract

Past work has suggested that neuronal oscillations coordinate the cellular assemblies that represent items in working memory (WM). In line with this hypothesis, we show that the spatial distribution of power in the alpha frequency band (8-12 Hz) can be used to decode the content and quality of the representations stored in visual WM. We acquired EEG data during an orientation WM task, and used a forward encoding model of orientation selectivity to reconstruct orientation-specific response profiles (termed channel tuning functions, or CTFs) that tracked the orientation of the memorandum during both encoding and delay periods of the trial. Critically, these EEG-based CTFs were robust predictors of both between- and within-subject differences in mnemonic precision, showing that EEG-based CTFs provide a sensitive measure of the quality of sensory population codes. Experiments 2 and 3 established that these EEG-based CTFs are contingent on the voluntary storage goals of the observer. When observers were given a postsample cue to store or drop the memorandum, the resulting CTF was sustained in the "store" condition and rapidly eliminated following the "drop" cue. When observers were instructed to store one of two simultaneously presented stimuli, only the stored item was represented in a sustained fashion throughout the delay period. These findings suggest that the oscillatory activity in the alpha frequency band plays a central role in the active storage of information in visual WM, and demonstrate a powerful approach for tracking the precision of on-line memories with high temporal resolution.

Keywords: EEG; attention; decoding; oscillatory activity; tuning function; working memory.

Figure 1.

A, Subjects maintained fixation and were instructed to remember the orientation of a sample stimulus; after a short delay, subjects were instructed to indicate the orientation of the sample stimulus by clicking on the perimeter of the rim. In Experiment 2, a change in fixation color (blue or green) immediately after sample offset indicated that the sample stimulus should be stored or dropped. In Experiment 3, subjects were instructed to remember the blue sample stimulus and ignore the green sample stimulus. B–E, Oscillatory activity was normalized relative to a prestimulus baseline by calculating proportional changes in task-related oscillatory power. TFRs were collapsed across posterior electrodes (see Results). B, TFRs revealed significant increases in evoked oscillatory power during stimulus encoding in low-frequency ranges. D, TFRs revealed significant decreases in induced oscillatory power during stimulus maintenance. C, E, Average oscillatory power observed in evoked and induced activity, respectively, across frequency bands and task epochs. F, Linear classifier performance based on orientation-selective patterns in the spatial distribution of evoked or induced oscillatory power across a broad range of individual frequencies (4–30 Hz in increments of 1 Hz) and time points. During encoding (0–250 ms), the spatial pattern of evoked and induced activity reliably decoded the content of WM in the theta (4–7 Hz) and alpha (8–12 Hz). During maintenance (250–1500 ms), only induced activity in the alpha band reliably decoded WM representations. G, An FEM was used to generate orientation-selective CTFs based on the same information used for linear classification. CTF selectivity revealed a similar decoding profile as that observed in the classification routine.

Figure 2.

Orientation selectivity in oscillatory alpha activity. A, Evoked alpha CTFs revealed a clear CTF during encoding (0–250 ms; boundaries of gray shaded window) that quickly dissipated after stimulus offset. B, Average evoked CTFs during stimulus encoding for alpha activity (black), as well as theta (red), low beta (green), and high beta (blue) activity for comparison. C, Induced alpha CTFs revealed a clear CTF during stimulus encoding and maintenance (250–1500 ms; boundaries gray shaded window). D, Average induced CTFs during stimulus maintenance for alpha activity (black), as well as theta (red), low beta (green), and high beta (blue) activity for comparison. E, Scalp topography of MI between presented stimulus orientations and induced alpha power across 100 ms bins. F, For comparison between putative cortical regions, electrodes were sorted into occipital (red), parietal (blue), and anterior (yellow) topographic regions, and average MI was calculated for each region during encoding and delay epochs. Error bars represent 95% confidence interval.

Figure 3.

Between- and within-subject links with mnemonic precision. A, D, A median-split analysis based on between-subject differences in mnemonic precision (s.d.) was performed on evoked and induced CTFs. No group difference was observed in evoked CTFs (A), and no apparent link was observed between mnemonic precision and CTF dispersion (B; R² = 0.01, p = 0.64) or amplitude (C; R² = 0.07, p = 0.22). D, A clear loss of selectivity was observed for low precision (dark blue) relative to high precision (light blue) subjects in induced CTFs (p < 0.05). A strong link was observed between mnemonic precision and induced CTF dispersion (E; R² = 0.51, p < 0.001), but not amplitude (F; R² = 0.04, p = 0.35). G, A median-split analysis based on within-subject differences in response error. CTFs were generated from trials grouped into high error (low precision; pink line) or low error (high precision; red line) bins. A clear loss of selectivity was observed in high error trials. The observed loss of selectivity was attributable to a significant difference in CTF dispersion (H; p < 0.05), but not amplitude (I; p = 0.18).

Figure 4.

Ruling out alternative explanations. A, To demonstrate that significant CTFs would not be observed under random conditions, we compared the observed empirical delay-specific CTF (solid black line) against a chance distribution (thin gray lines) derived from the analysis of 1000 surrogate time series that share statistical properties with the original data, which generated the expected flat average CTF (dotted black line). A similar flat CTF was observed during the baseline period (dark gray dotted line), during which time no stimulus was present. B, Empirically observed F statistics were compared against null distributions of surrogate F statistics derived from the randomization routine described in Materials and Methods, Randomization analyses. For baseline (black), encoding (blue), and maintenance (orange) epochs, 1000 surrogate CTFs were generated for each subject, and F statistics were calculated for each surrogate series. Each distribution of surrogate F statistics (dotted histograms) served to determine the deviation of the empirically observed pattern (thick vertical lines) from the null distribution. These data were used to estimate the probability of observing similar F statistics between null and empirical data. C, To demonstrate that stimulus-specific eye movement patterns did not contribute to the observed CTFs, we examined horizontal EOG amplitudes across each orientation channel (colored filled circles with error bars; thin gray circles represent each subject), and observed no significant modulation of EOG amplitude as a function of orientation channel. D, A linear classifier was trained on vertical EOG (black line), horizontal EOG (green line), and both horizontal and vertical (blue line) EOG amplitudes to determine if the pattern of EOGs could allow for above-chance (black dotted line) classification accuracy. None of the EOG measures could reliably predict the angle of the remembered stimulus during the delay period. Inset figure shows the average classification accuracy for each EOG measure.

Figure 5.

CTF time course across different storage demands. In Experiment 2, subjects were cued to store or drop the sample stimulus during the maintenance period. Evoked CTFs during store (A) and drop (B) trials revealed similar profiles during the initial encoding period (boundaries of gray windows). C, Average encoding-specific evoked CTFs revealed no difference in CTF selectivity during store (solid black line) and drop (dotted black line) trials. In contrast, induced CTFs revealed a sustained delay-specific CTF during store (D), but not drop (E), trials (boundaries of gray windows). F, Average delay-specific-induced CTFs revealed clear channel tuning in store trials, whereas a flat CTF was observed in drop trials.

Figure 6.

CTF time course during deployment of feature-based attention. In Experiment 3, subjects were presented with two differently colored sample stimuli during encoding, and cued to remember one (target) and ignore the other (distractor). Evoked CTFs revealed similar encoding-specific CTF profiles for target (A) and distractor (B) sample stimuli. In contrast, induced CTFs revealed a sustained delay-specific CTF profile for target stimuli (C), whereas we observed no delay-specific CTF for distractor stimuli (D). E, Average evoked CTFs during encoding (0–250 ms) revealed a significant loss of selectivity in distractor CTFs relative to target CTFs. The loss of selectivity observed in distractor-evoked CTFs was driven by a decline in CTF amplitude (F), but not CTF dispersion (G). H, Average induced CTFs during maintenance (250–1500 ms) revealed a significant target-induced CTF, whereas distractor-induced CTFs were flat.

Figure 7.

Replicating between- and within- subject links with mnemonic precision. A, D, A median-split analysis based on between-subject differences in mnemonic precision (s.d.) was performed on evoked and induced CTFs. No group difference was observed in evoked CTFs (A), and no apparent link was observed between mnemonic precision and CTF dispersion (B; R² = 0.10, p = 0.13) or amplitude (C; R² = 0.02; p = 0.54). D, A clear loss of selectivity was observed for low precision (dark blue) relative to high precision (light blue) subjects in induced CTFs (p < 0.05). A strong link was observed between mnemonic precision and induced CTF dispersion (E; R² = 0.30, p < 0.01), but not amplitude (F; R² = 0.09, p = 0.16). G, A median-split analysis based on within-subject differences in response error. CTFs were generated from trials grouped into high error (low precision; pink line) or low error (high precision; red line) bins. A clear loss of selectivity was observed in high error trials. The observed loss of selectivity was attributable to a significant difference in CTF dispersion (H; p < 0.05), but not amplitude (I; p = 0.25).