Figure 1. Calculating a neural measure of temporal context.

Based on the core assumptions of retrieved context models, the temporal context state of a studied item should (1) be a slowly changing representation of temporal context from earlier studied items; (2) be reinstated if the item is recalled. A. We first calculated oscillatory power from electroencephalography (EEG) activity recorded for each studied item or recalled item in control lists. In the upper right panel, the 42 electrodes included in the event vectors are circled in dark gray on the electrode map. L = left, P = posterior, R = right, A = anterior. B. By applying PCA, we selected features accounting for a significant amount of variance in the EEG recordings. C. To meet the first criterion of a slowly changing representation, we next determined which of the PCA features were autocorrelated across studied items. D. To verify the second criterion of a neural measure of temporal context, we next needed to examine this neural signature at recall. Thus, having established a slowly changing neural signature from study of selected PCA features, we then applied those same feature vectors from study events to the recall events. E. We assessed whether a studied item’s feature vectors were reinstated when the item was recalled, by calculating the encoding-retrieval similarity (ERS) between each recalled item’s temporal context and temporal context states from study. Retrieved context models predict that the similarity between a recalled item’s retrieved temporal context and temporal contexts at study should be greater for items studied nearby in time, or smaller absolute lag, to the study position of the recalled item (see also Figure 2C,D).