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Wakefulness

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Physiological signal-based drowsiness detection using machine learning: Singular and hybrid signal approaches.

Journal of safety research
INTRODUCTION: Drowsiness is one of the main contributors to road-related crashes and fatalities worldwide. To address this pressing global issue, researchers are continuing to develop driver drowsiness detection systems that use a variety of measures...

Directed Evolution of a Selective and Sensitive Serotonin Sensor via Machine Learning.

Cell
Serotonin plays a central role in cognition and is the target of most pharmaceuticals for psychiatric disorders. Existing drugs have limited efficacy; creation of improved versions will require better understanding of serotonergic circuitry, which ha...

Neurophysiological brain mapping of human sleep-wake states.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: We recently proposed a spectrum-based model of the awake intracranial electroencephalogram (iEEG) (Kalamangalam et al., 2020), based on a publicly-available normative database (Frauscher et al., 2018). The latter has been expanded to inclu...

A heuristic perspective on non-variational free energy modulation at the sleep-like edge.

Bio Systems
BACKGROUND: The variational Free Energy Principle (FEP) establishes that a neural system minimizes a free energy function of their internal state through environmental sensing entailing beliefs about hidden states in their environment.

Generalized Deep Learning EEG Models for Cross-Participant and Cross-Task Detection of the Vigilance Decrement in Sustained Attention Tasks.

Sensors (Basel, Switzerland)
Tasks which require sustained attention over a lengthy period of time have been a focal point of cognitive fatigue research for decades, with these tasks including air traffic control, watchkeeping, baggage inspection, and many others. Recent researc...

Automated sleep state classification of wide-field calcium imaging data via multiplex visibility graphs and deep learning.

Journal of neuroscience methods
BACKGROUND: Wide-field calcium imaging (WFCI) allows for monitoring of cortex-wide neural dynamics in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wakefulness, non-REM (NREM) and REM by use of adjun...

Quantifying arousal and awareness in altered states of consciousness using interpretable deep learning.

Nature communications
Consciousness can be defined by two components: arousal (wakefulness) and awareness (subjective experience). However, neurophysiological consciousness metrics able to disentangle between these components have not been reported. Here, we propose an ex...

Frameless Robot-Assisted vs Frame-Based Awake Deep Brain Stimulation Surgery: An Evaluation of Technique and New Challenges.

Operative neurosurgery (Hagerstown, Md.)
BACKGROUND: Methodological approaches to deep brain stimulation (DBS) continue to evolve from awake frame-based to asleep frameless procedures with robotic assistance, primarily directed to optimize operative efficiency, lead accuracy, and patient co...

Multimodal Vigilance Estimation Using Deep Learning.

IEEE transactions on cybernetics
The phenomenon of increasing accidents caused by reduced vigilance does exist. In the future, the high accuracy of vigilance estimation will play a significant role in public transportation safety. We propose a multimodal regression network that cons...

Multi-Level Classification of Driver Drowsiness by Simultaneous Analysis of ECG and Respiration Signals Using Deep Neural Networks.

International journal of environmental research and public health
The high number of fatal crashes caused by driver drowsiness highlights the need for developing reliable drowsiness detection methods. An ideal driver drowsiness detection system should estimate multiple levels of drowsiness accurately without interv...