PubMed Health⌕ Search

PubMed · 11783720

The function of dreaming.

Abstract

Theories on the function of REM sleep and dreaming, with which it has a contingent relationship, remain diverse. They include facilitation of memory storage, reverse learning, anatomical and functional brain maturation, catecholamine restoration, psychoanalytical (wish fulfilment or otherwise). It is possible that one function is grafted onto another as the personality develops. Given a close relationship between REM sleep and dreaming, and given that the neonate spends 18 hours asleep per day, of which 12 hours are spent in REM sleep, it is logical to look in the neonate for a primary function of dreaming. The two constants in the dreaming process are: 1) the dreamer is always present as first person observer; 2) there is always a topographical setting. Based on the foregoing, it is proposed that a major function of REM sleep is the development and maintenance of a sense of personal identity, through creating a 'being there' environment at regular intervals during prolonged periods of absence from a waking state in topographical surrounds. The infant cannot forget who he/she is. Thus, he/she develops a clear sense of his/her own identity, or the 'I'ness of me', and a sense of his/her separateness from the topographical world. At the same time, by largely forgetting the dreams, he/she is not burdened by the need for an elaborate method of storage of the vicarious and bizarre experiences.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

H Staunton. 2001. The function of dreaming.. https://doi.org/10.1515/revneuro.2001.12.4.365

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

KEEP EXPLORING

Related citations

An open benchmark and language models for AI in aging biology.

Over the past two decades, human aging has been characterized across DNA methylation, transcriptomic, proteomic, and clinical modalities, yet no benchmark evaluates whether AI systems can interpret these heterogeneous data types in the context of aging biology. We introduce LongevityBench, an open suite of 17 tasks spanning five biodata domains, and use it to assess 18 frontier AI systems from six developer teams. Despite recent advances in AI, no single model dominates all tasks, with omics-based age prediction being the hardest task regardless of scale. To test whether these gaps can be closed without frontier-scale resources, we fine-tuned a family of five multitask Longevity-LLMs on domain-specific aging data. The compact (0.6B-9B parameters) Longevity-LLMs matched or exceeded far larger frontier systems on LongevityBench, showing that general-purpose language models can be adapted to structured-omics tasks. We publicly release the benchmark, models, and Longevity Claw, an agentic research interface for aging researchers.

Aging↗

Association between sirtuin 1 and markers of oxidative stress in master athletes.

BACKGROUND: Lifelong training in master athletes confers protective effects, promoting higher sirtuin levels and enhanced antioxidant capacity. Although Sirtuin 1 (SIRT1) is well studied, no previous study has examined the relationship between circulating SIRT1 levels and antioxidant defense variables in master athletes. PURPOSE: To compare and analyze the relationships between circulating levels of SIRT1 and variables related to antioxidant defense in master athletes (MA) and untrained middle-aged individuals (UMA). METHODS: Male MA (n&#x2009;=&#x2009;42; 51.62&#x2009;&#xb1;&#x2009;7.33 years; &#x2265;10 years of training and competition in running) and UMA (n&#x2009;=&#x2009;15; 47.73&#x2009;&#xb1;&#x2009;8.52 years) were evaluated. Venous blood samples were collected for biochemical analyses of SIRT1, antioxidant enzymes, TBARS and F2-isoprostanes, 8-OHdG, and redox balance indexes. RESULTS: MA showed higher levels of SIRT1 (18.22&#x2009;&#xb1;&#x2009;4.53 vs. 6.08&#x2009;&#xb1;&#x2009;2.11 ng/mL; p&#x2009;<&#x2009;0.0001), as well as of SOD, CAT, and GSH (p&#x2009;<&#x2009;0.001), indicating a more favorable antioxidant profile. After adjustment for body fat percentage, differences in SOD, CAT, GSH and TBARS, remained significant. SIRT1 was positively correlated with SOD (r&#x2009;=&#x2009;0.279; p&#x2009;=&#x2009;0.031), CAT (r&#x2009;=&#x2009;0.485; p&#x2009;<&#x2009;0.001), GSH (r&#x2009;=&#x2009;0.476; p&#x2009;<&#x2009;0.001) and CAT/8-OHdG (r&#x2009;=&#x2009;0.430; p&#x2009;=&#x2009;0.032), and negatively correlated with TBARS (r&#x2009;=&#x2009;-&#x2009;0.518; p&#x2009;<&#x2009;0.001). CONCLUSION: Master athletes exhibited higher circulating SIRT1 concentrations and a more favorable systemic redox profile than untrained individuals, with SIRT1 being associated with markers of antioxidant defense, lipid peroxidation, and redox balance.

Aging↗

Decoding SUMOylation as a metabolic stress sensor in aging and age-related disorders: Mechanisms, tissue specificity and therapeutic potential.

SUMOylation is a reversible post-translational modification increasingly recognized for its role in coordinating cellular responses to metabolic stress during aging. Emerging evidence indicates that it functions beyond a conventional modification, representing an adaptive stress&#x2011;responsive regulatory network that integrates metabolic, oxidative, inflammatory, and proteotoxic signals. Rather than acting on isolated pathways, this network finely tunes mitochondrial function, proteostasis, genome maintenance, immune balance, and epigenetic regulation. Accumulating evidence indicates that SUMO-dependent regulation exhibits remarkable tissue specificity, supporting mitochondrial adaptation and contractile integrity in skeletal muscle, shaping lipid and glucose metabolism in the liver, modulating proteotoxic stress and neuronal resilience in the brain, and contributing to immune cell differentiation and chronic low-grade inflammation during aging. In this review, we summarize current mechanistic insights into SUMO signaling across aging-relevant tissues, with particular emphasis on its functional interplay with other post-translational modifications, including ubiquitination and acetylation. We discuss how SUMOylation operates as a shared regulatory layer while enabling context-dependent outcomes that underlie diverse aging phenotypes and age-related disorders. Finally, we evaluate emerging translational approaches-ranging from pharmacological modulation of SUMO enzymes to lifestyle interventions such as caloric restriction and exercise-that highlight both the opportunities and challenges of targeting SUMO-regulated stress responses in aging. Together, this synthesis provides a framework for understanding how SUMOylation links metabolic stress to tissue-specific aging trajectories and therapeutic potential.

Aging↗