PubMed Health⌕ Search

PubMed · 12531134

Mental activity during sleep.

Abstract

Since remote antiquity humankind has believed in the supernatural origin of dreaming. The scientific approach to mental activity during sleep dates back to the eighteenth century. One hundred years ago, psychoanalysis introduced dream analysis for diagnostic and therapeutic purposes. Only 50 years ago psychophysiology made it possible to collect mental sleep activity by means of experimental awakenings while monitoring physiological variables; this approach encouraged investigation into the relationship between the features of sleep activity and sleep state (REM versus NREM). Advances in neurophysiology, in neurochemistry, and recently in brain imaging techniques, have shed light on the roles played by the different cerebral structures in determining specific characteristics of mental activity during sleep. The development of cognitive psychology has enabled investigation of dream generation in terms of output from a complex multilevel system of information processing. In addition to sleep state, other factors, such as the time of the night and the sequence of the NREM-REM cycles, have been shown to influence the characteristics of mental activity. The usefulness of investigation of mental sleep activity as a clinical tool is controversial. The psychophysiological approach to mental sleep activity in clinical contexts has enabled the exploration of adaptation processes and contributed to neuropsychological studies on focal and systemic brain pathology.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Igino Fagioli. 2002. Mental activity during sleep.. https://doi.org/10.1053/smrv.2001.0214

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

KEEP EXPLORING

Related citations

A MAGIBU-based model for pediatric and juvenile CNS tumors: an in-house epigenetic decision-support framework compared with online DNA methylation classifiers.

Background: DNA methylation profiling is a tool that provides key support for central nervous system (CNS) tumor classification. However, diagnostically ambiguous pediatric cases may result in discordant outputs across classifiers. We developed MAGIBU, a cross-platform, projection-based framework that embeds individual methylomes into a fixed CNS reference landscape, ranking diagnostic entities by local epigenetic proximity to support clinician-led integrative diagnosis. Methods: As a proof-of-concept, we evaluated MAGIBU in eight morphologically challenging pediatric/juvenile CNS tumors with unresolved diagnoses after institutional and central pathology review. To establish a benchmark in the absence of a definitive histopathological ground truth, a consensus epigenetic reference was defined a priori for cases showing concordant results between the Heidelberg CNS Tumor Methylation Classifier and Methylscape Analysis. Comparisons were also performed with Epigenomic Digital Pathology (EpiDiP). To validate MAGIBU beyond this discovery cohort, performance was assessed at the family level across the CNS methylation spectrum (n = 678, 28 methylation families), on non-array platforms (whole-genome bisulfite sequencing and Oxford Nanopore), and in a focused analysis of the low-grade glioma and diffuse midline glioma compartment across four independent cohorts (n = 670). Results: In the discovery cohort, MAGIBU achieved high concordance with the consensus reference (Cohen's κ = 0.855), outperforming EpiDiP (κ = 0.278), which frequently placed low-grade tumors in proximity to higher-grade reference regions. Conclusions: MAGIBU provides a stable, quantitative differential diagnosis framework that mitigates the limitations of rigid categorical assignments. By leveraging a distance-based proximity metric, it offers a transparent decision-support tool that integrates effectively with clinical, radiological, and molecular data. While performance is inherently dependent on reference atlas composition, MAGIBU represents a robust complementary approach for the diagnostic workup of ambiguous CNS tumors.

Brain↗

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Brain↗