Biology subjects

Siefert, E. M.

Publications and source records attributed to Siefert, E. M..

3 recordsLinked to original sources

bioRxiv2026

Arousal state modulates human hippocampal ripples

Hippocampal ripples are transient, high-frequency oscillations linked to memory replay and consolidation. Ripples are well-characterized in rodents to occur during periods of behavioral inactivity (i.e., sleep, rest), viewed as "offline" states where replay can emerge with limited sensory interference. However, human studies have increasingly observed ripples during active tasks, raising the questions of whether ripple genesis and function have been misunderstood or whether there are fundamental species differences. We propose that low arousal states--predominant during offline sleep and transient during wake--may constitute a common mechanism of ripple genesis that reconciles these observations. We recorded directly from human hippocampus during sleep and wake, measuring arousal via sleep staging, pupillometry, and heart rate. Ripple occurrence consistently tracked low arousal: rates were maximal in NREM sleep, small-pupil wake states, and slow heart rate periods across sleep and wake. This modulation was stronger in anterior than posterior hippocampus and was hippocampus specific: ripple-like activity outside the hippocampus showed an opposite modulation, increasing with high arousal. These results resolve apparent species differences and provide a unifying view of offline periods as arousal dips that can emerge across behavioral states, including transiently during active wake, suggesting hippocampal ripples, and memory consolidation, occur continuously intermixed with cognition.

neuroscience↗

bioRxiv2026

Memory reactivation during sleep promotes structure abstraction

We readily detect structure in our environments, which in turn guides future learning. Disentangling this structure from the superficial features of a specific learning environment provides an especially strong basis for future generalization, but it remains unclear when and how this kind of abstraction occurs. Memory reactivation during sleep has been hypothesized to support such abstraction, but this has yet to be directly tested. Here we examined this hypothesis by teaching participants novel categories in which patterns of feature covariation were governed by different graph structures. Participants then learned a new category, defined by entirely different features, whose structure was either congruent or incongruent with a previously learned category. If structural knowledge is abstracted away from superficial features, it should facilitate transfer when structures are congruent. In Experiment 1, when two categories were learned in immediate succession, participants showed no transfer benefit, suggesting that structure understanding remained tied to the original features. In Experiment 2, we tested whether offline processing promotes abstraction. Participants either remained awake between learning phases spaced 3 hours apart, or took a nap during which a previously learned category was reactivated using targeted memory reactivation (TMR). Transfer benefits emerged only when the reactivated and target categories shared the same structure, and these benefits increased with the number of cues presented during slow-wave sleep. These findings provide the first direct evidence that memory reactivation during sleep promotes the abstraction of structure, enabling knowledge to transfer across learning episodes with no overlap in features.

neuroscience↗

bioRxiv2023

Memory reactivation during sleep does not act holistically on object memory

Memory reactivation during sleep is thought to facilitate memory consolidation. Most sleep reactivation research has examined how reactivation of specific facts, objects, and associations benefits their overall retention. However, our memories are not unitary, and not all features of a memory persist in tandem over time. Instead, our memories are transformed, with some features strengthened and others weakened. Does sleep reactivation drive memory transformation? We leveraged the Targeted Memory Reactivation technique in an object category learning paradigm to examine this question. Participants (20 female, 14 male) learned three categories of novel objects, where each object had unique, distinguishing features as well as features shared with other members of its category. We used a real-time EEG protocol to cue the reactivation of these objects during sleep at moments optimized to generate reactivation events. We found that reactivation improved memory for distinguishing features while worsening memory for shared features, suggesting a differentiation process. The results indicate that sleep reactivation does not act holistically on object memories, instead supporting a transformation process where some features are enhanced over others.

neuroscience↗