Memory reactivation during rest supports upcoming learning of related content.
Ontology highlight
ABSTRACT:
SUBMITTER: Schlichting ML
PROVIDER: S-EPMC4226095 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Learning occurs in the context of existing memories. Encountering new information that relates to prior knowledge may trigger integration, whereby established memories are updated to incorporate new content. Here, we provide a critical test of recent theories suggesting hippocampal (HPC) and medial prefrontal (MPFC) involvement in integration, both during and immediately following encoding. Human participants with established memories for a set of initial (AB) associations underwent fMRI scanning during passive rest and encoding of new related (BC) and unrelated (XY) pairs. We show that HPC-MPFC functional coupling during learning was more predictive of trial-by-trial memory for associations related to prior knowledge relative to unrelated associations. Moreover, the degree to which HPC-MPFC functional coupling was enhanced following overlapping encoding was related to memory integration behavior across participants. We observed a dissociation between anterior and posterior MPFC, with integration signatures during post-encoding rest specifically in the posterior subregion. These results highlight the persistence of integration signatures into post-encoding periods, indicating continued processing of interrelated memories during rest. We also interrogated the coherence of white matter tracts to assess the hypothesis that integration behavior would be related to the integrity of the underlying anatomical pathways. Consistent with our predictions, more coherent HPC-MPFC white matter structure was associated with better performance across participants. This HPC-MPFC circuit also interacted with content-sensitive visual cortex during learning and rest, consistent with reinstatement of prior knowledge to enable updating. These results show that the HPC-MPFC circuit supports on- and offline integration of new content into memory.
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Project description:Information acquired during waking can be reactivated during sleep, promoting memory stabilization. After people learned to produce two melodies in time with moving visual symbols, we enhanced relative performance by presenting one melody during an afternoon nap. Electrophysiological signs of memory processing during sleep corroborated the notion that appropriate auditory stimulation that does not disrupt sleep can nevertheless bias memory consolidation in relevant brain circuitry.
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Project description:Humans can vividly recall and re-experience events from their past, and these are commonly referred to as episodic or autobiographical memories. fMRI experiments reliably associate autobiographical event recall with activity in a network of "default" or "core" brain regions. However, as prior studies have relied on covert (silent) recall procedures, current understanding may be hampered by methodological limitations that obscure dynamic effects supporting moment-to-moment content retrieval. Here, fMRI participants (N = 40) overtly (verbally) recalled memories for ∼2 min periods. The content of spoken descriptions was categorized using a variant of the Autobiographical Interview (AI) procedure (Levine et al., 2002) and temporally re-aligned with BOLD data so activity accompanying the recall of different details could be measured. Replicating prior work, sustained effects associated with autobiographical recall periods (which are insensitive to the moment-to-moment content of retrieval) fell primarily within canonical default network regions. Spoken descriptions were rich in episodic details, frequently focusing on physical entities, their ongoing activities, and their appearances. Critically, neural activity associated with recalling specific details (e.g., those related to people or places) was transient, broadly distributed, and grounded in category-selective cortex (e.g., regions related to social cognition or scene processing). Thus, although a single network may generally support the process of vivid event reconstruction, the structures required to provide detail-related information shift in a predictable manner that respects domain-level representations across the cortex.SIGNIFICANCE STATEMENT Humans can vividly recall memories of autobiographical episodes, a process thought to involve the reconstruction of numerous distinct event details. Yet how the brain represents a complex episode as it unfolds over time remains unclear and appears inconsistent across experimental traditions. One hurdle is the use of covert (silent) in-scanner recall to study autobiographical memory, which prevents experimenter knowledge of what information is being retrieved, and when, throughout the remembering process. In this experiment, participants overtly described autobiographical memories while undergoing fMRI. Activity associated with the recall and description of specific details was transient, broadly distributed, and grounded in category-selective cortex. Thus, it appears that as events unfold mentally, structures are dynamically reactivated to support vivid recollection.
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Project description:Animals consolidate some, but not all, learning experiences into long-term memory. Across the animal kingdom, sleep has been found to have a beneficial effect on the consolidation of recently formed memories into long-term storage. However, the underlying mechanisms of sleep dependent memory consolidation are poorly understood. Here, we show that consolidation of courtship long-term memory in Drosophila is mediated by reactivation during sleep of dopaminergic neurons that were earlier involved in memory acquisition. We identify specific fan-shaped body neurons that induce sleep after the learning experience and activate dopaminergic neurons for memory consolidation. Thus, we provide a direct link between sleep, neuronal reactivation of dopaminergic neurons, and memory consolidation.
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Project description:Long-term storage of episodic memories is hypothesized to result from the off-line transfer of information from the hippocampus to neocortex, allowing a hippocampal-independent cortical representation to emerge. However, off-line hippocampal-cortical interactions have not been demonstrated to be linked with long-term memory. Here, using functional magnetic resonance imaging, we examined if hippocampal-cortical BOLD correlations during rest following an associative encoding task are related to later associative memory performance. Our data show enhanced functional connectivity between the hippocampus and a portion of the lateral occipital complex (LO) during rest following a task with high subsequent memory compared to pretask baseline resting connectivity. This effect is not seen during rest following a task with poor subsequent memory. Furthermore, the magnitude of hippocampal-LO correlations during posttask rest predicts individual differences in later associative memory. These results demonstrate the importance of postexperience resting brain correlations for memory for recent experiences.
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Project description:In everyday life and in education, we continuously build and structure our knowledge. Successful knowledge construction is suggested to happen through reactivation of previously learned information during new learning. This reactivation is presumed to lead to integration of old and new memories and strengthen long-term retention. Additionally, congruency with prior knowledge is shown to enhance subsequent memory. However, it is unknown how subjective reactivation and congruency jointly influence learning in an educational context. In two experiments, we investigated this question using an AB-AC inference paradigm where students were asked to first study an AB (word-picture) and then an AC-association (word-description). BC-associations were either congruent or incongruent and were linked by a common, unknown word (A). During AC-learning, participants were instructed to actively reactivate B (the picture) and report their subjective reactivation strength. Participants were first-year university students studying either psychology or family studies and the stimuli consisted of new information from their curricula. We expected that both reactivation and congruency would enhance subsequent associative memory for the inferred BC-association. This was assessed by cueing participants with C (the description) and asking to freely describe the associated picture. Results show a significant enhancement of both B-reactivation and congruency on associative memory scores in both experiments. Additionally, subjective meta-memory measures exhibited the same effect. These outcomes, showing beneficial effects of both reactivation and congruency on memory formation, can be of interest to educational practice, where effectively building knowledge through reactivation is imperative for success.
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Project description:A widely accepted view in memory research is that previously acquired information can be reactivated during sleep, leading to persistent memory storage. Targeted memory reactivation (TMR) was developed as a technique whereby specific memories can be reactivated during sleep using a sensory stimulus linked to prior learning. As a research tool, TMR can improve memory, raising the possibility that it may be useful for cognitive enhancement and clinical therapy. A major challenge for the expanded use of TMR is that a skilled operator must manually control stimulation, which is impractical in many settings. To address this limitation, we developed the SleepStim system for automated TMR in the home. SleepStim includes a smartwatch to collect movement and heart-rate data, plus a smartphone to emit auditory cues. A machine-learning model identifies periods of deep sleep and triggers TMR sounds within these periods. We tested whether this system could replicate the spatial-memory benefit of in-laboratory TMR. Participants learned locations of objects on a grid, and then half of the object locations were reactivated during sleep over 3 nights. Recall was tested each morning. In an experiment with 61 participants, the TMR effect was not significant but varied systematically with stimulus intensity; low-intensity but not high-intensity stimuli produced memory benefits. In a second experiment with 24 participants, we limited stimulus intensity and found that TMR reliably improved spatial memory, consistent with effects observed in laboratory studies. We conclude that SleepStim can effectively accomplish automated TMR, and that avoiding sleep disruption is critical for TMR benefits.
| S-EPMC9649863 | biostudies-literature
Project description:We present a multi-voxel analytical approach, feature-specific informational connectivity (FSIC), that leverages hierarchical representations from a neural network to decode neural reactivation in fMRI data collected while participants performed an episodic visual recall task. We show that neural reactivation associated with low-level (e.g. edges), high-level (e.g. facial features), and semantic (e.g. "terrier") features occur throughout the dorsal and ventral visual streams and extend into the frontal cortex. Moreover, we show that reactivation of both low- and high-level features correlate with the vividness of the memory, whereas only reactivation of low-level features correlates with recognition accuracy when the lure and target images are semantically similar. In addition to demonstrating the utility of FSIC for mapping feature-specific reactivation, these findings resolve the contributions of low- and high-level features to the vividness of visual memories and challenge a strict interpretation the posterior-to-anterior visual hierarchy.
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Project description:Memory reprocessing following acquisition enhances memory consolidation. Specifically, neural activity during encoding is thought to be 'replayed' during subsequent slow-wave sleep. Such memory replay is thought to contribute to the functional reorganization of neural memory traces. In particular, memory replay may facilitate the exchange of information across brain regions by inducing a reconfiguration of connectivity across the brain. Memory reactivation can be induced by external cues through a procedure known as "targeted memory reactivation". Here, we analysed data from a published study with auditory cues used to reactivate visual object-location memories during slow-wave sleep. We characterized effects of memory reactivation on brain network connectivity using graph-theory. We found that cue presentation during slow-wave sleep increased global network integration of occipital cortex, a visual region that was also active during retrieval of object locations. Although cueing did not have an overall beneficial effect on the retention of cued versus uncued associations, individual differences in overnight memory stabilization were related to enhanced network integration of occipital cortex. Furthermore, occipital cortex displayed enhanced connectivity with mnemonic regions, namely the hippocampus, parahippocampal gyrus, thalamus and medial prefrontal cortex during cue sound presentation. Together, these results suggest a neural mechanism where cue-induced replay during sleep increases integration of task-relevant perceptual regions with mnemonic regions. This cross-regional integration may be instrumental for the consolidation and long-term storage of enduring memories.
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Project description:Brain-machine interfaces can allow neural control over assistive devices. They also provide an important platform for studying neural plasticity. Recent studies have suggested that optimal engagement of learning is essential for robust neuroprosthetic control. However, little is known about the neural processes that may consolidate a neuroprosthetic skill. On the basis of the growing body of evidence linking slow-wave activity (SWA) during sleep to consolidation, we examined whether there is 'offline' processing after neuroprosthetic learning. Using a rodent model, we found that, after successful learning, task-related units specifically experienced increased locking and coherency to SWA during sleep. Moreover, spike-spike coherence among these units was substantially enhanced. These changes were not present with poor skill acquisition or after control awake periods, demonstrating the specificity of our observations to learning. Notably, the time spent in SWA predicted the performance gains. Thus, SWA appears to be involved in offline processing after neuroprosthetic learning.
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