The Hypno-PC: Uncovering Sleep Dynamics Through Principal Component Analysis and Hidden Markov Modelling of Electrophysiological Signals

Опубликована: Янв. 16, 2025

The conventional approach to sleep analysis relies on pre-defined, visually scored stages derived from electrophysiological signals. This manual method demands substantial effort and is influenced by subjective assessments, implicitly assuming that these categories accurately reflect underlying biological processes. Recent advancements indicate low-dimensional representations of complex brain activity can provide objective means identifying states. These approaches potentially uncover inherent patterns within sleep, offering valuable insights into its organization. In this study, we applied Principal Component Analysis (PCA) spectral features extracted high-density EEG, EOG, EMG, ECG recorded overnight at both 30– 4-second resolutions. Notably, the first principal component—the “Hypno-PC”—strongly aligns with hypnogram time scales. Subsequently, employed a Gaussian Hidden Markov Model (GHMM) delineate discrete states in PCA-transformed data quantify their temporal dynamics. Using minimal supervision (less than 0.5% labeled) cross-subject approach, model achieved alignment standard labels comparable typical inter-rater agreement. Finally, independent component (ICA) was PCA space, decomposing it an set components represent distinct physiological integrated use PCA, GHMM, ICA provides reproducible scalable methodology traditional staging, while more flexible comprehensive perspective Our findings data-driven, unsupervised methods effectively intrinsic dynamics advancing automated enhancing our understanding

Язык: Английский

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Monoaminergic signaling during mammalian NREM sleep - Recent insights and next-level questions

Current Opinion in Neurobiology, Год журнала: 2025, Номер 92, С. 103025 - 103025

Опубликована: Апрель 22, 2025

Язык: Английский

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Where is my mind? A neurocognitive investigation of mind blanking

Trends in Cognitive Sciences, Год журнала: 2025, Номер unknown

Опубликована: Апрель 1, 2025

During wakefulness, our thoughts transition between different contents. However, there are moments that seemingly devoid of reportable content, referred to as mind blanking (MB). It remains unclear what these blanks represent, highlighting the definitional and phenomenological ambiguities surrounding MB. We map out MB in terms its expressions, neurophysiology, relationship adjacent phenomenology, including meditative practices sleep. propose a mechanistic account linking changes at physiological, neural, cognitive levels. suggest ongoing experiences characterized by degrees richness, contentless events represent distinct mental states with their own diversity. encourage future research acknowledge category, leading comprehensive understanding experience.

Язык: Английский

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Sedative and hypnotic effects with cortical EEG Sleep-wake profiles of Millingtonia hortensis dried flower aqueous in mice

Heliyon, Год журнала: 2024, Номер unknown, С. e37531 - e37531

Опубликована: Сен. 1, 2024

Язык: Английский

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How to quantify sleepiness during an attempt to sleep?

Physiological Measurement, Год журнала: 2024, Номер 45(9), С. 095008 - 095008

Опубликована: Сен. 1, 2024

Abstract Background . Sleepiness assessment tools were mostly developed for detection of an elevated sleepiness level in the condition sleep deprivation and several medical conditions. However, occurs various other conditions including transition from wakefulness to during everyday attempt get sleep. Objective We examined whether objective indexes can be implicated fluctuations polysomnographically-monitored sleep, i.e. absence self-reports on perceived throughout such attempt. Approach The polysomnographic signals recorded afternoon 106 90 min napping attempts 53 university students (28 females). To calculate two indexes, electroencephalographic (EEG) spectra averaged 30 s epochs each record, assigned one 5 sleep–wake stages, scored using either frequency weighting curve substate wake state or loadings 2nd principal component variation EEG spectrum (either score PC2 score, respectively). Main results showed that statistically significant these stage described terms changes verbally anchored levels subjective assessed by scoring 9-step Karolinska Scale. Significance afford new opportunities elaborate importance intermediate substates between states dynamics healthy individuals patients with disturbed

Язык: Английский

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Toward an electroclinical approach for neurophysiological hypersomnolence in sleep medicine

Neurophysiologie Clinique, Год журнала: 2024, Номер 54(2), С. 102958 - 102958

Опубликована: Март 14, 2024

Язык: Английский

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Breaking the borders of wakefulness and sleep – the search for novel biomarkers to quantify sleepiness

SLEEP, Год журнала: 2024, Номер unknown

Опубликована: Июль 24, 2024

Язык: Английский

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Discovery of Dynamic Functional MRI Markers of Sleep Onset Period

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Авг. 9, 2024

Understanding the Sleep Onset Period (SOP) remains challenging despite its critical role in sleep architecture. Recent research suggests that resting-state functional MRI (rs-fMRI) and Blood-Oxygen-Level-Dependent (BOLD) signal may offer new insights. This study investigates brain activity during SOP using BOLD oscillation focuses on detecting drowsiness through an innovative scoring system. Forty-one healthy young volunteers underwent a 45-minute rs-fMRI scan. Drowsiness was assessed by analyzing standard surveillance video, specifically measuring ocular activity. method, originally designed for road accident prevention, is applied here first time neuroimaging study. We observed increase low-frequency oscillations across different states (awake, likely drowsy, sleep), peaking at 0.05 Hz. The Power Spectral Density of Hz (PSD_0.05) increases from earliest sign progresses until sleep. evident up to 58 regions, particularly within primary sensory cortices visual somatomotor networks. findings suggest PSD_0.05 networks be valuable marker improving delineation. Additionally, eye closure dynamics provide objective measure scans, which crucial addressing confounds data.

Язык: Английский

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Investigation of Elderly Patient Actimetries for Night Sleep/Wake Phases Prediction

2022 8th International Conference on Control, Decision and Information Technologies (CoDIT), Год журнала: 2024, Номер 15, С. 2633 - 2638

Опубликована: Июль 1, 2024

Язык: Английский

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