scholarly journals Clinical Recovery and Sleep Architecture Degradation

1990 ◽  
Vol 17 (3) ◽  
pp. 332-335 ◽  
Author(s):  
Vladimir C. Hachinski ◽  
Mortimer Mamelak ◽  
John W. Norris
Keyword(s):  
Cerebral Infarction ◽  
Rem Sleep ◽  
Sleep Eeg ◽  
Post Stroke ◽  
Clinical Recovery ◽  
Delta Activity ◽  
Wave Forms ◽  
Sleep Recording ◽  
One Year ◽  
Electroencephalogram Eeg

ABSTRACT:We achieved a unique and timely recording of cerebral activity in a 70 year old woman immediately pre- and post-stroke, while studying the effect of acute cerebral infarction on sleep-electroencephalogram (EEG) patterns. Normal patterns, except for increased wakefulness, were recorded during two pre-infarct polysomnograms. Immediately following cerebral infarction increased delta activity was recorded from the infarcted hemisphere only. Initially, REM sleep could not be recorded from either side; however, on the third post infarct day REM sleep returned. Background EEG levels from both hemispheres became progressively slower, flatter and simpler. In addition, sleep spindles and the distinctive saw-tooth wave forms of sleep almost disappeared. At one year post-stroke sleep-EEG rhythm recordings from both hemispheres became more similar except for persisting delta activity from the left hemisphere. Unexpected deterioration of sleep-EEG pattern recordings from the undamaged hemisphere taken during the patient's clinical recovery remains unexplained. Serial sleep recording may facilitate the study of brain recovery, activity and reorganization following stroke.

scholarly journals Prediction of post-stroke epilepsy using machine learning method

2020 ◽  
Author(s):  
Anjiao Peng ◽  
Xiaorong Yang ◽  
Zhining Wen ◽  
Wanling Li ◽  
Yusha Tang ◽  
...  
Keyword(s):  
Machine Learning ◽  
High Risk ◽  
Cerebral Infarction ◽  
Cerebral Hemorrhage ◽  
Characteristic Curve ◽  
Support Vector ◽  
Learning Methods ◽  
Post Stroke ◽  
Machine Learning Methods ◽  
One Year

Abstract Background : Stroke is one of the most important causes of epilepsy and we aimed to find if it is possible to predict patients with high risk of developing post-stroke epilepsy (PSE) at the time of discharge using machine learning methods. Methods : Patients with stroke were enrolled and followed at least one year. Machine learning methods including support vector machine (SVM), random forest (RF) and logistic regression (LR) were used to learn the data. Results : A total of 2730 patients with cerebral infarction and 844 patients with cerebral hemorrhage were enrolled and the risk of PSE was 2.8% after cerebral infarction and 7.8% after cerebral hemorrhage in one year. Machine learning methods showed good performance in predicting PSE. The area under the receiver operating characteristic curve (AUC) for SVM and RF in predicting PSE after cerebral infarction was close to 1 and it was 0.92 for LR. When predicting PSE after cerebral hemorrhage, the performance of SVM was best with AUC being close to 1, followed by RF ( AUC = 0.99) and LR (AUC = 0.85) . Conclusion : Machine learning methods could be used to predict patients with high risk of developing PSE, which will help to stratify patients with high risk and start treatment earlier. Nevertheless, more work is needed before the application of thus intelligent predictive model in clinical practice.

scholarly journals Depression and Sleep

2019 ◽  
Vol 20 (3) ◽  
pp. 607 ◽  
Author(s):  
Axel Steiger ◽  
Marcel Pawlowski
Keyword(s):  
Rem Sleep ◽  
Antidepressant Treatment ◽  
Therapy Response ◽  
Brain Perfusion ◽  
Sleep Eeg ◽  
Rem Density ◽  
Prognosis And Prediction ◽  
Eeg Changes ◽  
Impaired Sleep ◽  
Electroencephalogram Eeg

Impaired sleep is both a risk factor and a symptom of depression. Objective sleep is assessed using the sleep electroencephalogram (EEG). Characteristic sleep-EEG changes in patients with depression include disinhibition of rapid eye movement (REM) sleep, changes of sleep continuity, and impaired non-REM sleep. Most antidepressants suppress REM sleep both in healthy volunteers and depressed patients. Various sleep-EEG variables may be suitable as biomarkers for diagnosis, prognosis, and prediction of therapy response in depression. In family studies of depression, enhanced REM density, a measure for frequency of rapid eye movements, is characteristic for an endophenotype. Cordance is an EEG measure distinctly correlated with regional brain perfusion. Prefrontal theta cordance, derived from REM sleep, appears to be a biomarker of antidepressant treatment response. Some predictive sleep-EEG markers of depression appear to be related to hypothalamo-pituitary-adrenocortical system activity.

The Distinctive Sleep Pattern of the Human Calcarine Cortex: A Stereo-EEG Study

SLEEP ◽  
2021 ◽  
Author(s):  
Maurizio Gorgoni ◽  
Simone Sarasso ◽  
Fabio Moroni ◽  
Ivana Sartori ◽  
Michele Ferrara ◽  
...  
Keyword(s):  
Rem Sleep ◽  
Time Course ◽  
Sleep Eeg ◽  
Sleep Cycle ◽  
Sleep Spindles ◽  
Rise Rate ◽  
Delta Activity ◽  
Eeg Pattern ◽  
Eeg Features ◽  
Calcarine Cortex

Abstract Study Objectives The aim of the study was to describe the spontaneous electroencephalographic (EEG) features of sleep in the human calcarine cortex, comparing them with the well-established pattern of the parietal cortex. Methods We analysed pre-surgical intracerebral EEG activity in calcarine and parietal cortices during NREM and REM sleep in 7 patients with drug-resistant focal epilepsy. The time course of the EEG spectral power and NREM vs. REM differences were assessed. Sleep spindles were automatically detected. To assess homeostatic dynamics, we considered the 1 st vs. 2 nd half of the night ratio in the delta frequency range (0.5-4 Hz) and the rise rate of delta activity during the 1 st sleep cycle. Results While the parietal area showed the classically described NREM and REM sleep hallmarks, the calcarine cortex exhibited a distinctive pattern characterized by: a) the absence of sleep spindles; b) a large similarity between EEG power spectra of NREM and REM; c) reduced signs of homeostatic dynamics, with a decreased delta ratio between the 1 st and the 2 nd half of the night, a reduced rise rate of delta activity during the 1 st NREM sleep cycle, and lack of correlation between these measures. Conclusions Besides describing for the first time the peculiar sleep EEG pattern in the human calcarine cortex, our findings provide evidence that different cortical areas may exhibit specific sleep EEG pattern, supporting the view of sleep as a local process and promoting the idea that the functional role of sleep EEG features should be considered at a regional level.

scholarly journals The relationship between fasting-induced torpor, sleep and waking in laboratory mice

SLEEP ◽  
2021 ◽  
Author(s):  
Yi-Ge Huang ◽  
Sarah J Flaherty ◽  
Carina A Pothecary ◽  
Russell G Foster ◽  
Stuart N Peirson ◽  
...  
Keyword(s):  
Body Temperature ◽  
Rem Sleep ◽  
Brain Activity ◽  
Mammalian Species ◽  
Nrem Sleep ◽  
Laboratory Mice ◽  
State Classification ◽  
Metabolic Suppression ◽  
The Relationship ◽  
Electroencephalogram Eeg

Abstract Study objectives Torpor is a regulated and reversible state of metabolic suppression used by many mammalian species to conserve energy. Whereas the relationship between torpor and sleep has been well-studied in seasonal hibernators, less is known about the effects of fasting-induced torpor on states of vigilance and brain activity in laboratory mice. Methods Continuous monitoring of electroencephalogram (EEG), electromyogram (EMG) and surface body temperature was undertaken in adult, male C57BL/6 mice over consecutive days of scheduled restricted feeding. Results All animals showed bouts of hypothermia that became progressively deeper and longer as fasting progressed. EEG and EMG were markedly affected by hypothermia, although the typical electrophysiological signatures of NREM sleep, REM sleep and wakefulness enabled us to perform vigilance-state classification in all cases. Consistent with previous studies, hypothermic bouts were initiated from a state indistinguishable from NREM sleep, with EEG power decreasing gradually in parallel with decreasing surface body temperature. During deep hypothermia, REM sleep was largely abolished, and we observed shivering-associated intense bursts of muscle activity. Conclusions Our study highlights important similarities between EEG signatures of fasting-induced torpor in mice, daily torpor in Djungarian hamsters and hibernation in seasonally-hibernating species. Future studies are necessary to clarify the effects on fasting-induced torpor on subsequent sleep.

scholarly journals Atypical Creutzfeldt-Jakob Disease Evolution after Electroconvulsive Therapy for Catatonic Depression

2011 ◽  
Vol 2011 ◽  
pp. 1-3 ◽  
Author(s):  
Iria Grande ◽  
Juan Fortea ◽  
Ellen Gelpi ◽  
Itziar Flamarique ◽  
Marc Udina ◽  
...  
Keyword(s):  
Electroconvulsive Therapy ◽  
Disease Duration ◽  
Psychiatric Symptoms ◽  
Psychiatric Admission ◽  
Disease Evolution ◽  
Clinical Recovery ◽  
Jakob Disease ◽  
Magnetic Resonance Imaging Mri ◽  
Electroencephalogram Eeg ◽  
Codon 129

We describe a case report of an 80-year-old woman who presented with symptomatology compatible with an episode of major depression with catatonia. After psychiatric admission, electroconvulsive therapy (ECT) was applied, but symptoms progressed with cognitive impairment, bradykinesia, widespread stiffness, postural tremor, and gait disturbance. After compatible magnetic resonance imaging (MRI), diffusion changes, and electroencephalogram (EEG) findings the case was reoriented to Creutzfeldt-Jakob disease (CJD). The genetic study found a methionine/valine heterozygosity at codon 129 of the prion protein gene PrPSc. On followup, a significant clinical recovery turned out. For this reason, EEG and MRI were repeated and confirmed the findings. The patient subsequently demonstrated progressive clinical deterioration and died 21 months later. The diagnosis was verified postmortem by neuropathology. The vCJD subtype MV2 is indeed characterized by early and prominent psychiatric symptoms and a prolonged disease duration however no frank clinical recovery has before been reported.

Opioids cause dissociated states of consciousness in C57BL/6J mice

2021 ◽  
Author(s):  
Christopher B O'Brien ◽  
Clarence E Locklear ◽  
Zachary T Glovak ◽  
Diana Zebadúa Unzaga ◽  
Helen A Baghdoyan ◽  
...  
Keyword(s):  
Rem Sleep ◽  
Neuronal Excitability ◽  
Nrem Sleep ◽  
Temporal Organization ◽  
Saline Control ◽  
Organization Of Sleep ◽  
States Of Consciousness ◽  
Surgical Recovery ◽  
Eeg Power ◽  
Electroencephalogram Eeg

The electroencephalogram (EEG) provides an objective, neural correlate of consciousness. Opioid receptors modulate mammalian neuronal excitability, and this fact was used to characterize how opioids administered to mice alter EEG power and states of consciousness. The present study tested the hypothesis that antinociceptive doses of fentanyl, morphine, or buprenorphine differentially alter the EEG and states of sleep and wakefulness in adult, male C57BL/6J mice. Mice were anesthetized and implanted with telemeters that enabled wireless recordings of cortical EEG and electromyogram (EMG). After surgical recovery, EEG and EMG were used to objectively score states of consciousness as wakefulness, rapid eye movement (REM) sleep, or non-REM (NREM) sleep. Measures of EEG power (dB) were quantified as delta (0.5 to 4 Hz), theta (4 to 8 Hz), alpha (8 to 13 Hz), sigma (12 to 15 Hz), beta (13 to 30 Hz), and gamma (30 to 60 Hz). Compared to saline (control), fentanyl and morphine decreased NREM sleep, morphine eliminated REM sleep, and buprenorphine eliminated NREM sleep and REM sleep. Opioids significantly and differentially disrupted the temporal organization of sleep/wake states, altered specific EEG frequency bands, and caused dissociated states of consciousness. The results are discussed relative to the fact that opioids, pain, and sleep modulate interacting states of consciousness.

Predictors of Participation in Supervised Therapy by Post-Stroke Patients in The Singapore Community: A One-Year Cohort Study

2016 ◽  
Vol 97 (10) ◽  
pp. e8
Author(s):  
Gerald Choon-Huat Koh ◽  
Denise Yan-Yin Lim ◽  
Steven Liben Zhang ◽  
Cynthia Chen Huijun ◽  
Sanjiv Kishore Saxena ◽  
...  
Keyword(s):  
Cohort Study ◽  
Stroke Patients ◽  
Post Stroke ◽  
One Year

Abstract TP318: The Circumstances and Consequences of Post-stroke Falls

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Arlene A Schmid ◽  
H. Klar Yaggi ◽  
Nicolas Burrus ◽  
Vincent McClain ◽  
Charles Austin ◽  
...  
Keyword(s):  
Medical Care ◽  
Mental State ◽  
Fall Prevention ◽  
Secondary Analysis ◽  
Stroke Recovery ◽  
Large Trial ◽  
Post Stroke ◽  
Falling Asleep ◽  
One Year ◽  
The One

Introduction: Three-quarters of people with stroke sustain a fall. Fall risk and risk for injury persists into the chronics phases of stroke recovery. Currently, the circumstances surrounding post-stroke falls are not well understood; identifying these circumstances is a key step in the development of fall prevention programs. Likewise, the consequences of falls during the chronic phases of stroke are largely unexplored. Objectives: The objectives of the study were to identify the circumstances and consequences of post-stroke fall events. Methods: This is a secondary analysis of data derived from a large trial. To be included in the trial and these analyses, participants had to have survived a stroke and had a diagnosis of hypertension or blood pressure >140/90 mmHg. Demographics and stroke characteristics were recorded. Patients were asked about falls prospectively over the one-year study period. Once a fall event was identified, chart review and interviews were used to obtain information regarding circumstances and consequences of the fall. Fall circumstances were separated into intrinsic/personal and environmental categories including: falls with activity; falls with movement; falls due to trips or slips; falls related to a physical or mental state; location of the fall; and the season when the fall occurred. Consequences of falls were classified according to type of injury (laceration, fracture) and medical care received. Results: A total of 53 of the 225 (33%) participants reported a fall; 70% of falls occurred at home and 40% of falls were associated with impaired physical or mental state (e.g., falling asleep and falling out of a chair or inattention to tying shoes, or forgetting to use a device). Additionally, 21% of falls were associated with activities, 21% with mobility, and 34% with slips or trips. The majority of people who fell sustained an injury (72%); injuries ranged from bruising to fractures and 55% of those with an injury sought medical care (32% to emergency). Conclusion: Post-stroke falls are associated with an alarming rate of injury and healthcare utilization. Targeting mental and physical states may be key to fall prevention programming for people with chronic stroke.

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