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No phylogeny without ontogeny-a comparative and developmental search for the sources of sleep-like neural and behavioral rhythms

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Neuroscience Bulletin 2012年第1期28卷 25-38页

作者： Michael Corner Chris van der Togt The Netherlands Institute for Brain Research Amsterdam The Netherlands Institute for Neurosciences Amsterdam

A comprehensive review is presented of reported aspects and putative mechanisms of sleep-like motility rhythms throughout the animal kingdom. It is proposed that ＇rapid eye movement （REM） sleep＇ be regarded as a special case of a distinct but much broader category of behavior, ＇rapid body movement （RBM） sleep＇, defined by intrinsically- generated and apparently non-purposive movements. Such a classification completes a 2 2 matrix defined by the axes sleep versus waking and active versus quiet. Although ＇paradoxical＇ arousal of forebrain electrical activity is restricted to warm-blooded vertebrates, we urge that juvenile or even infantile stages of development be investigated in cold-blooded animals, in view of the many reports of REM-like spontaneous motility （RBMs） in a wide range of species during sleep. The neurophysiological bases for motorically active sleep at the brainstem level and for slow-wave sleep in the forebrain appear to be remarkably similar, and to be subserved in both cases by a primitive diffuse mode of neuronal organization. Thus, the spontaneous synchronous burst discharges which are characteristics of the sleeping brain can be readily simu- lated even by highly unstructured neural network models. Neuromotor discharges during active sleep appear to reflect a hierarchy of simple relaxation oscillation mechanisms, spanning a wide range of spike-dependent relaxation times, where- as the periodic alternation of active and quiet sleep states more likely results from the entrainment of intrinsic cellular rhythms and/or from activity-dependent homeostatic changes in network excitability.

关键词： sleep cortical arousal development evolution neural network models brain rhythms spontaneous motility neuroplasticity

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Prediction of the Shearing Property of Worsted Fabrics Using BP neural network

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Journal of Donghua University(English Edition) 2006年第6期23卷 47-49页

作者：徐广标张向华王府梅 College of Textiles Donghua University Panyu Entry-Exit Inspection and Quarantine Bureau

In this paper, three layers of BP neural network were used to model the shearing properties of worsted fabrics. We train the neural network models with 27 kinds of fabrics, and then use 6 kinds of fabrics to validate ... 详细信息

关键词： worsted fabric shearing properties neural network models predictive accuracy.

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Advancing critical care recovery:The pivotal role of machine learning in early detection of intensive care unit-acquired weakness

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World Journal of Clinical Cases 2024年第21期12卷 4455-4459页

作者： Georges Khattar Elie Bou Sanayeh Department of Medicine Staten Island University HospitalStaten IslandNY 10305United States

This editorial explores the significant challenge of intensive care unit-acquiredweakness(ICU-AW),a prevalent condition affecting critically ill patients,characterizedby profound muscle weakness and complicating patient *** paradox of modern medical advances,it emphasizes the urgent needfor early identification and intervention to mitigate ICU-AW's ***,the study by Wang et al is showcased for employing a multilayer perceptronneural network model,achieving high accuracy in predicting *** advancement underscores the potential of neural network models inenhancing patient care but also calls for continued research to address limitationsand improve model *** editorial advocates for the developmentand validation of sophisticated predictive tools,aiming for personalized carestrategies to reduce ICU-AW incidence and severity,ultimately improving patientoutcomes in critical care settings.

关键词： Critical illness myopathy Critical illness polyneuropathy Early detection Intensive care unit-acquired weakness neural network models Patient outcomes Personalized intervention strategies Predictive modeling

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