scholarly journals Effects of Acute Transcutaneous Vagal Stimulation on the EEG Power Maps, EEG Sources Distribution and Steadiness of Quiet and Sensory-conflicted Stance

2015 ◽  
pp. 45-54 ◽  
Author(s):  
Bozhidar Dimitrov ◽  
◽  
Plamen Gatev
Keyword(s):  
Vagal Stimulation ◽  
Power Maps ◽  
Eeg Power

scholarly journals 0669 The Effects Of Continuous Positive Airway Pressure Therapy In Moderate To Severe Obstructive Sleep Apnea: A High-density EEG Study

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A255-A255
Author(s):  
A L D’Rozario ◽  
C Kao ◽  
A E Mullins ◽  
N Memarian ◽  
B Yee ◽  
...  
Keyword(s):  
Memory Consolidation ◽  
Declarative Memory ◽  
Nrem Sleep ◽  
High Density ◽  
Sleep Eeg ◽  
Therapeutic Effects ◽  
Topographic Analysis ◽  
Pressure Therapy ◽  
Power Maps ◽  
Eeg Power

Abstract Introduction A previous high-density electroencephalography (EEG) investigation in asymptomatic OSA showed regional deficits in sleep EEG power particularly slow wave activity (SWA) during NREM sleep in the parietal region. It is unclear whether treatment with CPAP can reverse local sleep EEG abnormalities in OSA, and whether any recovery is related to improvement in sleep-dependent memory consolidation. Methods Fifteen male participants (age 50.4±6.5yrs, AHI 51.7±23.5/h) with moderate-severe OSA (AHI>15/h) underwent overnight polysomnography with 256-channel high-density EEG at baseline and following 3 months of CPAP therapy. A word paired associates declarative memory task was administered before and after sleep. After artefact removal, spectral analysis was performed for all channels. Topographical power maps were calculated for standard frequency ranges for NREM sleep (164 channels within a 0.57 radius from the vertex). Maps were compared using both absolute and normalized power (z-scores computed for each subject) and differences between baseline and treatment were determined by statistical nonparametric mapping. Results In 11 CPAP compliant patients (intolerant of CPAP [n=3]/high-density EEG [n=1]), analysis of polysomnographic variables showed that total sleep time did not differ but N1 (baseline vs. treatment: 66.9 vs. 39.5 mins,p=0.008) and N2 (195.0 vs. 150.6 mins,p=0.002) sleep was lower and N3 (89.8 vs. 128.7 mins,p=0.003) was higher after CPAP. Topographic analysis of high-density EEG data revealed a regional increase in SWA (1-4.5Hz) EEG power during N3 sleep in a cluster of electrodes overlying the centro-parietal cortex (cluster mean t-value=2.87,p=0.02). The change in overnight declarative memory consolidation (% recognition) after CPAP was significantly correlated with the change in slow spindle frequency activity in frontal regions (cluster mean r=0.875,p=0.003). Conclusion CPAP treatment may enhance localised deficits in sleep EEG activity in OSA, and specific regional recovery may translate to memory improvements in the short-term. These data also highlight the potential for long-term therapeutic effects on cognitive outcomes in OSA. Support  

An Adaptive and Learning System for Feedback-Controlled Evoked Response Studies

1981 ◽  
Vol 20 (03) ◽  
pp. 169-173
Author(s):  
J. Wagner ◽  
G. Pfurtscheixer
Keyword(s):  
Brain Activity ◽  
Evoked Response ◽  
Learning System ◽  
Time Interval ◽  
Electrical Brain Activity ◽  
Long Time ◽  
The Subject ◽  
Eeg Power ◽  
Stimulation System ◽  
Background Eeg

The shape, latency and amplitude of changes in electrical brain activity related to a stimulus (Evoked Potential) depend both on the stimulus parameters and on the background EEG at the time of stimulation. An adaptive, learnable stimulation system is introduced, whereby the subject is stimulated (e.g. with light), whenever the EEG power is subthreshold and minimal. Additionally, the system is conceived in such a way that a certain number of stimuli could be given within a particular time interval. Related to this time criterion, the threshold specific for each subject is calculated at the beginning of the experiment (preprocessing) and adapted to the EEG power during the processing mode because of long-time fluctuations and trends in the EEG. The process of adaptation is directed by a table which contains the necessary correction numbers for the threshold. Experiences of the stimulation system are reflected in an automatic correction of this table. Because the corrected and improved table is stored after each experiment and is used as the starting table for the next experiment, the system >learns<. The system introduced here can be used both for evoked response studies and for alpha-feedback experiments.

Behavioural and EEG atypicalities during rest, visual perception, and cognitive control in autistic adults

2020 ◽  
Author(s):  
Amandine Lassalle ◽  
Michael X Cohen ◽  
Laura Dekkers ◽  
Elizabeth Milne ◽  
Rasa Gulbinaite ◽  
...  
Keyword(s):  
Visual Perception ◽  
Cognitive Control ◽  
Visual Processing ◽  
Autism Spectrum ◽  
Neural Dynamics ◽  
Simple Explanation ◽  
Control Task ◽  
Neural Structure ◽  
Eeg Power ◽  
Autistic Adults

Background: People with an Autism Spectrum Condition diagnosis (ASD) are hypothesized to show atypical neural dynamics, reflecting differences in neural structure and function. However, previous results regarding neural dynamics in autistic individuals have not converged on a single pattern of differences. It is possible that the differences are cognitive-set-specific, and we therefore measured EEG in autistic individuals and matched controls during three different cognitive states: resting, visual perception, and cognitive control.Methods: Young adults with and without an ASD (N=17 in each group) matched on age (range 20 to 30 years), sex, and estimated Intelligence Quotient (IQ) were recruited. We measured their behavior and their EEG during rest, a task requiring low-level visual perception of gratings of varying spatial frequency, and the “Simon task” to elicit activity in the executive control network. We computed EEG power and Inter-Site Phase Clustering (ISPC; a measure of connectivity) in various frequency bands.Results: During rest, there were no ASD vs. controls differences in EEG power, suggesting typical oscillation power at baseline. During visual processing, without pre-baseline normalization, we found decreased broadband EEG power in ASD vs. controls, but this was not the case during the cognitive control task. Furthermore, the behavioral results of the cognitive control task suggest that autistic adults were better able to ignore irrelevant stimuli.Conclusions: Together, our results defy a simple explanation of overall differences between ASD and controls, and instead suggest a more nuanced pattern of altered neural dynamics that depend on which neural networks are engaged.

scholarly journals Spontaneous long-term and urethane induced hippocampal EEG power, activity and temperature data from mice lacking the Cav3.2 voltage-gated Ca2+ channel

Data in Brief ◽  
2021 ◽  
Vol 36 ◽  
pp. 107027
Author(s):  
Anna Papazoglou ◽  
Muhammad Imran Arshaad ◽  
Magdalena Elisabeth Siwek ◽  
Christina Henseler ◽  
Johanna Daubner ◽  
...  
Keyword(s):  
Temperature Data ◽  
Voltage Gated ◽  
Eeg Power ◽  
Hippocampal Eeg

scholarly journals An Analysis of the External Validity of EEG Spectral Power in an Uncontrolled Outdoor Environment during Default and Complex Neurocognitive States

2021 ◽  
Vol 11 (3) ◽  
pp. 330
Author(s):  
Dalton J. Edwards ◽  
Logan T. Trujillo
Keyword(s):  
External Validity ◽  
Spectral Power ◽  
Brain Activity ◽  
Outdoor Environment ◽  
Oscillatory Activity ◽  
Brain State ◽  
Beta Band ◽  
Eeg Spectral Power ◽  
Eeg Power ◽  
Human Participants

Traditionally, quantitative electroencephalography (QEEG) studies collect data within controlled laboratory environments that limit the external validity of scientific conclusions. To probe these validity limits, we used a mobile EEG system to record electrophysiological signals from human participants while they were located within a controlled laboratory environment and an uncontrolled outdoor environment exhibiting several moderate background influences. Participants performed two tasks during these recordings, one engaging brain activity related to several complex cognitive functions (number sense, attention, memory, executive function) and the other engaging two default brain states. We computed EEG spectral power over three frequency bands (theta: 4–7 Hz, alpha: 8–13 Hz, low beta: 14–20 Hz) where EEG oscillatory activity is known to correlate with the neurocognitive states engaged by these tasks. Null hypothesis significance testing yielded significant EEG power effects typical of the neurocognitive states engaged by each task, but only a beta-band power difference between the two background recording environments during the default brain state. Bayesian analysis showed that the remaining environment null effects were unlikely to reflect measurement insensitivities. This overall pattern of results supports the external validity of laboratory EEG power findings for complex and default neurocognitive states engaged within moderately uncontrolled environments.

Efferent vagal innervation of canine ventricle

1985 ◽  
Vol 248 (1) ◽  
pp. H89-H97 ◽  
Author(s):  
N. Takahashi ◽  
M. J. Barber ◽  
D. P. Zipes
Keyword(s):  
Coronary Artery ◽  
Vagal Stimulation ◽  
Left Ventricular ◽  
Constant Infusion ◽  
Epicardial Surface ◽  
Before And After ◽  
Vagal Innervation ◽  
The Subject ◽  
Infusion Of Norepinephrine ◽  
The Right

The route efferent vagal fibers travel to reach the left ventricle is not clear and was the subject of this investigation. We measured left ventricular and septal effective refractory period (ERP) changes during vagal stimulation and a constant infusion of norepinephrine, before and after phenol was applied at selected sites of the heart to interrupt efferent vagal fibers that may be traveling in that area. Phenol applied to the atrioventricular (AV) groove between the origin of the right coronary artery anteriorly to the posterior descending branch of the circumflex coronary artery completely eliminated vagal-induced prolongation of ERP in the anterior and posterior left ventricular free wall and reduced, but did not eliminate, ERP prolongation in the septum. A large (3-cm radius) epicardial circle of phenol prevented vagal-induced ERP prolongation within the circle in all dogs, while a small (1-cm radius) epicardial circle of phenol failed to prevent vagal-induced ERP changes within the circle in any dog. An intermediate (2-cm radius) circle eliminated vagal effects on ERP in 13 of 18 dogs. Arcs of phenol, to duplicate the upper portion of the circle, applied sequentially from apex to base eliminated efferent vagal effects only when painted near or at the AV groove. We conclude that the majority of efferent vagal fibers enroute to innervate the anterior and posterior left ventricular epicardium cross the AV groove within 0.25-0.5 mm (depth of phenol destruction) of the epicardial surface.(ABSTRACT TRUNCATED AT 250 WORDS)

Effect of interleukin-1 beta on EEG power density during sleep depends on circadian phase

1996 ◽  
Vol 270 (4) ◽  
pp. R830-R837 ◽  
Author(s):  
M. Lancel ◽  
S. Mathias ◽  
J. Faulhaber ◽  
T. Schiffelholz
Keyword(s):  
Power Density ◽  
Interleukin 1 ◽  
Time Of Day ◽  
Controlled Study ◽  
Randomized Experiments ◽  
Eeg Activity ◽  
Circadian Phase ◽  
Activity Phase ◽  
Eeg Power ◽  
A Minor

The cytokine interleukin (IL)-1 is a key mediator of the somnogenic response to immune challenge. In this vehicle-controlled study we evaluated circadian interference with the sleep-promoting effects of IL-1 beta. In two randomized experiments, rats were injected intracerebroventricularly with 5 ng IL-1 beta either at the beginning of the rest phase or at the beginning of the activity phase. Recordings were made during the 24 h preceding the injections (baseline) and during the first 12 postinjection hours. To avoid masking effects of light, the rats were maintained under a skeleton photoperiod during recording. During both the rest and activity phase, IL-1 beta induced fever and initially promoted non-rapid eye movement sleep (REMS). The effect of IL-1 beta on the duration of non-REMS and electroencephalogram (EEG) power densities within non-REMS was related to circadian phase. During the rest phase, IL-1 beta resulted in a minor increase in non-REMS duration but a prominent enhancement in EEG activity in the delta (0.5-4 Hz) and most other frequency bands. During the activity phase, IL-1 beta evoked a larger increase in the duration of non-REMS but hardly affected EEG activity within this state. Thus the effects of IL-1 beta on non-REMS are strongly influenced by diurnal phase. The alterations in EEG power density are in contrast to those elicited by sleep deprivation, which are largely independent of time of day. It is concluded that IL-1 beta activates EEG regulatory mechanisms mediated by processes that depend on circadian phase.

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