Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.01.10.575038

Sleep selectively and durably enhances real-world sequence memory

Abstract

Sleep is thought to play a critical role in the retention of episodic memories. Yet it remains unclear whether and how sleep actively transforms memory for specific experiences. More generally, little is known about sleeps effects on memory for multidimensional real-world experiences, both overnight and in the days to months that follow. In an exception to the law of forgetting, we showed that sleep actively and selectively improves retrieval of a one-time real-world experience (a controlled but immersive art tour) - specifically boosting memory for the order of tour items (sequential associations), but not perceptual details from the tour (featural associations). This above-baseline increase in sequence memory was not evident after a matched period of wakefulness. Moreover, the sleep-induced advantage of sequence over featural memory grew over time up to one-year post-encoding. Finally, overnight polysomnography showed that sleep-related memory enhancement was associated with the duration and neurophysiological hallmarks of slow-wave sleep previously linked to neural replay, particularly spindle-slow wave coupling. These results suggest that sleep serves a crucial and selective role in enhancing sequential organization in episodic memory at the expense of specific details, linking sleep-related neural mechanisms to the transformation and enhancement of memory for complex real-life experiences. Significance StatementSleep affects the retention of episodic memories. Yet, it remains unclear whether sleep active transforms how we remember past experiences, overnight and beyond. We investigated memory for different dimensions underlying a dynamic real-world event - sequential associations versus atemporal featural associations - before and after sleep or wakefulness, and serially up to a year later. Sleep actively and selectively enhanced sequence memory, with this preferential sequence retention growing with time. Overnight memory enhancement is associated with the duration and neurophysiological hallmarks of slow-wave sleep previously linked to sequential neural replay, particularly spindle-slow wave coupling. Our findings support an active role for sleep in transforming different aspects of real-world memory, with sequence structure coming to dominate long-term memory for dynamic real-world experiences.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Diamond, N. B., Simpson, S., Baena Perez, D., Murray, B., Fogel, S., Levine, B.. 2024-01-12. Sleep selectively and durably enhances real-world sequence memory. https://doi.org/10.1101/2024.01.10.575038

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗