AIMC Topic: Wakefulness

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Strategies to Decipher Neuron Identity from Extracellular Recordings in Behaving Nonhuman Primates.

The Journal of neuroscience : the official journal of the Society for Neuroscience Aug 6, 2025
Identification of the neuron type is critical when using extracellular recordings in awake, behaving animal subjects to understand computation in neural circuits. Yet, modern recording probes have limited power to resolve neuron identity. Here, we pr...
Cerebellum Wakefulness Macaca mulatta Pursuit, Smooth Animals Male Deep Learning Action Potentials Neurons
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Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.

PloS one Jun 25, 2025
Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, current methods such as finger pricking and continuous glucose monitoring systems (CGMS) are invasive, ...
Machine Learning Algorithms Female Young Adult Humans Wakefulness Blood Glucose Self-Monitoring Sleep Wearable Electronic Devices Blood Glucose Adult Diabetes Mellitus, Type 1 Male Hypoglycemia Middle Aged
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Sleep Identification Enabled by Supervised Training Algorithms (SIESTA): An Open-Source Platform for Automatic Sleep Staging of Rodent Electrocorticographic and Electromyographic Data.

Journal of biological rhythms Jun 6, 2025
Accurately capturing the temporal distribution of polysomnographic sleep stages is critical for the study of sleep function, regulation, and disorders in higher vertebrates. In laboratory rodents, scoring of electrocorticography (ECoG) and electromyo...
Algorithms Animals Male Mice Wakefulness Sleep Sleep Stages Electrocorticography Rats Mice, Inbred C57BL Electromyography Circadian Rhythm
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Leveraging advanced graph neural networks for the enhanced classification of post anesthesia states to aid surgical procedures.

PloS one Apr 25, 2025
Anesthesia plays a pivotal role in modern surgery by facilitating controlled states of unconsciousness. Precise control is crucial for safe and pain-free surgeries. Monitoring anesthesia depth accurately is essential to guide anesthesiologists, optim...
Graph Neural Networks Humans Neural Networks, Computer Machine Learning Algorithms Brain Wakefulness Anesthesia
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Neural models for detection and classification of brain states and transitions.

Communications biology Apr 11, 2025
Exploring natural or pharmacologically induced brain dynamics, such as sleep, wakefulness, or anesthesia, provides rich functional models for studying brain states. These models allow detailed examination of unique spatiotemporal neural activity patt...
Animals Male Rats Models, Neurological Neural Networks, Computer Algorithms Brain Wakefulness Sleep Cerebral Cortex
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Classification of speech arrests and speech impairments during awake craniotomy: a multi-databases analysis.

International journal of computer assisted radiology and surgery Dec 9, 2024
PURPOSE: Awake craniotomy presents a unique opportunity to map and preserve critical brain functions, particularly speech, during tumor resection. The ability to accurately assess linguistic functions in real-time not only enhances surgical precision...
Speech Disorders Middle Aged Deep Learning Wakefulness Craniotomy Adult Brain Neoplasms Male Humans Female Aged
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Predictive Factors Driving Positive Awake Test in Carotid Endarterectomy Using Machine Learning.

Annals of vascular surgery Nov 22, 2024
BACKGROUND: Positive neurologic awake testing during the carotid cross-clamping may be present in around 8% of patients undergoing carotid endarterectomy (CEA). The present work aimed to assess the accuracy of an artificial intelligence (AI)-powered ...
Humans Predictive Value of Tests Machine Learning Risk Assessment Retrospective Studies Decision Support Techniques Wakefulness Aged Carotid Stenosis Case-Control Studies Female Aged, 80 and over Neurologic Examination Endarterectomy, Carotid Intraoperative Neurophysiological Monitoring Reproducibility of Results Male Risk Factors Treatment Outcome Middle Aged
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Attention-based CNN-BiLSTM for sleep state classification of spatiotemporal wide-field calcium imaging data.

Journal of neuroscience methods Aug 14, 2024
BACKGROUND: Wide-field calcium imaging (WFCI) with genetically encoded calcium indicators allows for spatiotemporal recordings of neuronal activity in mice. When applied to the study of sleep, WFCI data are manually scored into the sleep states of wa...
Sleep Stages Calcium Attention Wakefulness Sleep Mice Mice, Inbred C57BL Electroencephalography Neural Networks, Computer Brain Animals Male Image Processing, Computer-Assisted
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Automatic Sleep Stage Classification Using Nasal Pressure Decoding Based on a Multi-Kernel Convolutional BiLSTM Network.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Jul 17, 2024
Sleep quality is an essential parameter of a healthy human life, while sleep disorders such as sleep apnea are abundant. In the investigation of sleep and its malfunction, the gold-standard is polysomnography, which utilizes an extensive range of var...
Deep Learning Healthy Volunteers Wakefulness Female Humans Pressure Polysomnography Young Adult Neural Networks, Computer Sleep Stages Adult Algorithms Nose Male Sleep, REM
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Derivative Method to Detect Sleep and Awake States through Heart Rate Variability Analysis Using Machine Learning Algorithms.

Sensors (Basel, Switzerland) Jul 3, 2024
Sleep disorders can have harmful consequences in both the short and long term. They can lead to attention deficits, as well as cardiac, neurological and behavioral repercussions. One of the most widely used methods for assessing sleep disorders is po...
Young Adult Adult Male Wakefulness Heart Rate Humans Sleep Machine Learning Polysomnography Algorithms Female
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