A unique neural signature of long-term memory encoding from EEG inter-electrode correlation

Abstract

Classic memory models proposed that the encoding process involved in visual working memory (VWM) controls the bandwidth of encoding in long-term memory (LTM). Behaviorally, VWM and LTM accuracies are reliably correlated at the behavioral level, raising the question of whether LTM encoding uniquely engages processes that are distinct from VWM encoding. To investigate this, we recorded EEG activity as participants completed recognition memory tasks with set sizes of 32 and 128, far beyond typical VWM capacity. Using interelectrode correlation (IC) analysis, we found that IC patterns reliably predicted individual differences in LTM encoding across both set sizes, indicating a robust, domain-general neural signature. Importantly, this predictive power remained even after controlling for VWM and attentional control performance, suggesting that the model captures variance specific to LTM encoding. Temporally, predictive signals emerged only after stimulus onset and persisted for 500-600 ms. Early and late encoding phases involved distinct network structures, reflecting dynamic neural processes underlying individual differences in LTM encoding. Together, our findings reveal a unique and temporally dynamic neural signature that supports individual differences in LTM encoding, independent of general cognitive abilities. Significance StatementHumans maintain visual information using two distinct memory systems: visual working memory, which is capacity-limited, and long-term memory, which has virtually unlimited capacity. Despite their differences, individuals with better VWM performance often show superior LTM performance, raising the question of whether unique LTM encoding abilities exist beyond those accounted for by VWM. Here, we leveraged EEG data to examine interelectrode correlation patterns during memory encoding. Our results show that these neural patterns uniquely predict individual differences in LTM encoding ability, even after controlling for VWM performance. Furthermore, we showed that the interelectrode correlation patterns continuously track the temporal dynamics of LTM encoding over time.