Neural subspaces encode sequential working memory without detectable neural sequences

The neural mechanisms of multiple-item working memory are not well understood. In the current study, we address two competing hypotheses about the neural basis of sequential working memory: neural subspaces versus neural sequences. Using broadband MEG data from human participants, we applied dimensionality reduction and multivariate decoding techniques to test whether a sequence of items is maintained through the reactivation of individual items in sequence (neural sequences) or by organizing them into distinct low-dimensional subspaces (neural subspaces). Our results revealed behaviorally relevant, low-dimensional neural subspaces that organized memory representations according to ordinal position in the sequence, supporting the neural subspaces hypothesis. In contrast, we found no evidence of sequential neural replay during the retention period, contrary to the neural sequences hypothesis. In this work, we show that sequential working memory is maintained through structured geometric organization in low-dimensional representational space, rather than through the sequential reactivation of individual items, thus clarifying the mechanisms of multi-item working memory.