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Petzka, M.

Publications and source records attributed to Petzka, M..

7 recordsLinked to original sources

The human hippocampus retroactively binds experiences across time

Creating memories requires linking events across seconds and minutes, but canonical mechanisms of associative plasticity operate over much shorter timescales. This poses a fundamental problem: how can the brain bind information that arrives at different times? Computational model and animal studies implicate the hippocampus in associating events across time, but when the hippocampus becomes engaged and how it interacts with representations of preceding events are unknown. Here we show, using intracranial recordings in humans forming image-word associations across a ~2-s temporal gap, that hippocampal high-frequency activity predicts later memory when the second event arrives, but not during the initial image or intervening delay. At this moment, neurons tuned to the preceding image reinstate stimulus-specific firing despite its sensory absence. Across trials, hippocampal high-frequency activity was selectively coupled to this reinstatement during successful encoding and increased before spiking of image-tuned neurons. These findings reveal a retroactive mode of hippocampal binding, whereby representations of preceding events are recruited when new information arrives. This mechanism provides a neural solution for binding experiences across the temporal discontinuities that characterize everyday life.

neuroscience↗

Respiration shapes the neural dynamics of successful remembering in humans.

Respiration has been shown to impact memory retrieval, yet the neural dynamics underlying this effect remain unclear. Here, we investigated how respiration shapes both behavioral and neural expressions of memory retrieval by re-analyzing an existing dataset where scalp electroencephalography and respiration recordings were acquired while participants (N = 18) performed an episodic memory task. Our results unveil that respiration influences retrieval-related power fluctuations in the /{beta} band and concomitant memory reactivation. Specifically, we found that both key neural signatures of successful remembering were co-modulated during exhalation, with the strength of the interaction between respiration and reactivation processes being associated with memory performance. Together, these findings suggest that respiration may act as a scaffold for episodic memory retrieval in humans by coordinating the neural conditions that support effective remembering. Significance statementRecent evidence suggests that respiration may shape neural dynamics underlying various cognitive processes. In this study, we identify respiration as a potential pacemaker for memory retrieval by showing that key neural signatures of effective remembering--namely, decreases in /{beta} power and the reactivation of previously encoded neural representations--are tightly synchronized with the respiratory cycle. Notably, the strength of this respiration-brain coupling is associated with individual memory performance, underscoring the critical role and functional significance of brain-body interactions in supporting cognitive functions.

neuroscience↗

N2 Sleep Inspires Insight

Humans sometimes have an insight that leads to a sudden and drastic performance im-provement on the task they are working on. The precise origins of such insights are unknown. Some evidence has shown that sleep facilitates insights, while other work has not found such a relationship. One recent suggestion that could explain this mixed evidence is that different sleep stages have differential effects on insight. In addition, computational work has suggested that neural variability and regularisation play a role in increasing the likelihood of insight. To investigate the link between insight and different sleep stages as well as regularisation, we conducted a preregistered study in which N=90 participants performed a perceptual insight task before and after a 20 minute daytime. Sleep EEG data showed that N2 sleep, but not N1 sleep, increases the likelihood of insight after a nap, suggesting a specific role of deeper sleep. Exploratory analyses of EEG power spectra showed that spectral slopes could predict insight beyond sleep stages, which is broadly in line with theoretical suggestions of a link between insight and regularisation. In combination, our findings point towards a role of N2 sleep and aperiodic, but not oscillatory, neural activity for insight.

neuroscience↗

Motor adaptation is facilitated by sleep-associated modulation of beta oscillations

Motor adaptation reflects the ability of the brains sensorimotor system to flexibly deal with environmental changes to generate effective motor behaviour. Whether sleep contributes to the consolidation of motor adaptation remains controversial. In this study, we investigated the impact of sleep on motor adaptation and its neurophysiological correlates in a novel motor adaptation task that leverages a highly automatized motor skill, i.e., typing. We hypothesized that sleep-associated memory consolidation would benefit motor adaptation and induce modulations in task-related beta band (13-30Hz) activity during adaptation. Healthy young male experts in typing on the regular computer keyboard were trained to type on a vertically mirrored keyboard while brain activity was recorded using electroencephalography (EEG). Typing performance was assessed either after a full night of sleep with polysomnography or a similar period of daytime wakefulness. Results showed improved motor adaptation performance after nocturnal sleep but not after daytime wakefulness, and decreased beta power (a) during mirrored typing as compared to regular typing, and (b) in the post-sleep vs. the pre-sleep mirrored typing sessions. Furthermore, the slope of the EEG signal, a measure of aperiodic brain activity, decreased during mirrored as compared to regular typing. Changes in the EEG spectral slope from pre- to post-sleep mirrored typing sessions were correlated with changes in task performance. Finally, increased fast sleep spindle density (13-15Hz) during the night following motor adaptation training was predictive of successful motor adaptation. These findings suggest that post-training sleep modulates neural activity mechanisms supporting adaptive motor functions.

neuroscience↗

Respiration shapes sleep-oscillations and memory reactivation in humans.

The beneficial effect of sleep on memory consolidation relies on the precise interplay of slow oscillations (SOs) and spindles. However, whether these rhythms are orchestrated by an underlying pacemaker has remained elusive. Here, we tested whether respiration, which has been shown to impact brain rhythms and cognition during wake, shapes memory reactivation by modulating sleep-related oscillations and their interplay in humans. We recorded scalp EEG and respiration throughout an experiment in which participants acquired associative memories before taking a nap. Our results reveal that respiration strongly modulates the emergence of sleep oscillations. Specifically, SOs, spindles as well as their interplay (i.e., coupled SO_spindle complexes) systematically increase towards inhalation peaks. Moreover, the strength of respiration-SO_spindle coupling is linked to the extent of memory reactivation during SO_spindles. Our results identify respiration as a potential pacemaker for memory consolidation in humans and highlight the critical role of brain-body interactions during sleep.

neuroscience↗

Sleep spindles track cortical learning patterns for memory consolidation

Memory consolidation, the transformation of labile memory traces into stable long-term representations, is facilitated by post-learning sleep. Computational and biophysical models suggest that sleep spindles may play a key mechanistic role for consolidation, igniting structural changes at cortical sites involved in prior learning. Here we tested the resulting prediction that spindles are most pronounced over learning-related cortical areas and that the extent of this learning-spindle overlap predicts behavioural measures of memory consolidation. Using high-density scalp Electroencephalography (EEG) and Polysomnography (PSG) in healthy volunteers, we first identified cortical areas engaged during a temporospatial associative memory task (power decreases in the alpha/beta frequency range, 6-20 Hz). Critically, we found that participant-specific topographies (i.e., spatial distributions) of post-learning sleep spindle amplitude correlated with participant-specific learning topographies. Importantly, the extent to which spindles tracked learning patterns further predicted memory consolidation across participants. Our results provide empirical evidence for a role of post-learning sleep spindles in tracking learning networks, thereby facilitating memory consolidation.

neuroscience↗

Endogenous memory reactivation during sleep in humans is clocked by slow oscillation-spindle complexes.

Sleep is thought to support memory consolidation via reactivation of prior experiences, with particular electrophysiological sleep signatures (slow oscillations (SOs) and sleep spindles) gating the information flow between relevant brain areas. However, empirical evidence for a role of endogenous memory reactivation (i.e., without experimentally delivered memory cues) for consolidation in humans is lacking. Here, we devised a paradigm in which participants acquired associative memories before taking a nap. Multivariate decoding was then used to capture endogenous memory reactivation during non-rapid eye movement (NREM) sleep in surface EEG recordings. Our results reveal reactivation of learning material during SO-spindle complexes, with the precision of SO-spindle coupling predicting reactivation strength. Critically, reactivation strength (i.e. classifier evidence in favor of the previously studied stimulus category) in turn predicts the level of consolidation across participants. These results elucidate the memory function of sleep in humans and emphasize the importance of SOs and spindles in clocking endogenous consolidation processes.

neuroscience↗