Assessment and Confidence Estimates of Newborn Brain Maturity from Sleep EEG

2013 ◽  
pp. 215-226
Author(s):  
V. Schetinin ◽  
L. Jakaite
Keyword(s):  
Parameter Space ◽  
High Likelihood ◽  
Reasonable Time ◽  
Model Parameter ◽  
Newborn Brain ◽  
Eeg Recordings ◽  
Areas Of Interest ◽  
Confidence Estimates ◽  
Large Model ◽  
Eeg Features

Electroencephalograms (EEGs) recorded from sleeping newborns contain information about their brain maturity. Although these EEGs are very weak and distorted by artifacts, and widely vary during sleep hours as well as between patients, the main maturity-related patterns are recognizable by experts. However, experts are typically incapable of quantitatively providing accurate estimates of confidence in assessments. The most accurate estimates are, in theory, provided with the Bayesian methodology of probabilistic inference which has been practically implemented with Markov Chain Monte Carlo (MCMC) integration over a model parameter space. Typically this technique aims to approximate the integral by sampling areas of interests with high likelihood of the true model. In practice, the likelihood distributions are typically multimodal, and for this reason, the existing MCMC techniques have been shown incapable of providing the proportional sampling of multiple areas of interest. Besides, the lack of prior information increases this problem especially for a large model parameter space, making its detailed exploration impossible within a reasonable time. Specifically, the absence of information about EEG features has been shown affecting the results of the Bayesian assessment of EEG maturity. In this chapter, authors discuss how the posterior information can be used in order to mitigate the problem of disproportional sampling in order to improve the accuracy of assessments. Having analyzed the posterior information, they found that the MCMC integration tends to oversample the areas in which a model parameter space includes EEG features making a weak contribution to the assessment. This observation has motivated the authors to cure the results of MCMC integration, and when they tested the proposed method on the EEG recordings, they found an increase in the accuracy of assessment.

scholarly journals Ghosts- and tachyon-free regions of the Randall-Sundrum model parameter space

2018 ◽  
Vol 2018 (7) ◽  
Author(s):  
G. N. Wojcik ◽  
J. L. Hewett ◽  
T. G. Rizzo
Keyword(s):  
Parameter Space ◽  
Model Parameter

scholarly journals LEPTON-FLAVOR-VIOLATING τ DECAYS IN TWO-HIGGS-DOUBLET MODEL III

2010 ◽  
Vol 25 (25) ◽  
pp. 4827-4837 ◽  
Author(s):  
WEN-JUN LI ◽  
YING-YING FAN ◽  
LIN-XIA LÜ ◽  
SU-ZHI GAO ◽  
GONG-WEI LIU
Keyword(s):  
Perturbation Theory ◽  
Parameter Space ◽  
Chiral Perturbation Theory ◽  
Higgs Doublet ◽  
Higgs Bosons ◽  
Chiral Perturbation ◽  
Model Parameter ◽  
Lepton Flavor ◽  
Doublet Model ◽  
Two Higgs Doublet Model

We study the lepton-flavor-violating processes of τ- → μ-PP decays with PP = K+K-, [Formula: see text], π+π-, π0π0 in the framework of two-Higgs-doublet model III by virtue of the chiral perturbation theory. In this model, only three neutral Higgs bosons contribute to these decays. With the current experimental constraints, we show that (a) the contributions of the |λuu(dd)| term are very small for these four decays; (b) we get the correlation between |λss| and |λτμ|; for |λτμ| ~ 10–400, one has |λss| ~ 40–1; (c) in the existing model parameter space, Br (τ- → μ- K+K-) could reach the order of [Formula: see text], but Br (τ → μ-π+π-/π0π0) are too small to be observed.

History matching for exploring and reducing climate model parameter space using observations and a large perturbed physics ensemble

2013 ◽  
Vol 41 (7-8) ◽  
pp. 1703-1729 ◽  
Author(s):  
Daniel Williamson ◽  
Michael Goldstein ◽  
Lesley Allison ◽  
Adam Blaker ◽  
Peter Challenor ◽  
...  
Keyword(s):  
Parameter Space ◽  
History Matching ◽  
Climate Model ◽  
Model Parameter ◽  
Perturbed Physics Ensemble ◽  
Physics Ensemble ◽  
Perturbed Physics

scholarly journals T131. EVENT RELATED POTENTIALS (ERPS) DURING FREE VIEWING OF IMAGES WITH INCREASING SEMANTIC COMPLEXITY IN SUBJECTS’ AFFECTED WITH SCHIZOPHRENIA

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S280-S280
Author(s):  
Christ Devia ◽  
José Egaña ◽  
Rocío Mayol-Troncoso ◽  
Gricel Orellana Vidal ◽  
Pedro Maldonado
Keyword(s):  
Event Related Potentials ◽  
Natural Scenes ◽  
Healthy Controls ◽  
Pink Noise ◽  
Positive Diagnosis ◽  
Free Exploration ◽  
Free Viewing ◽  
Related Potentials ◽  
Eeg Recordings ◽  
Eeg Features

Abstract Background Currently, the diagnosis of schizophrenia is made solely based on interviews and behavioral observations by a trained psychiatrist. Technologies such as electroencephalography (EEG) are used for differential diagnosis and not to support the psychiatrist’s positive diagnosis. Here, we show the potential of EEG recordings as biomarkers of the schizophrenia syndrome. EEG (electroencephalography) differences between patients with schizophrenia (SCZ) and controls have been reported. Tasks used are complex and specialized, not necessarily resemble natural stimuli/ environment to which the brain is adapted. We tested if SCZ global cognitive deficits could be described by EEG features using an ecological and simple approach. Methods We recorded EEG while schizophrenia patients freely viewed natural scenes, and we analyzed the average EEG activity locked to the image onset. We compared occipital ERPs obtained from 11 subjects with SCZ and 9 aged-- matched healthy controls (HC) during free-- exploration of images. Image categories included Plain Gray, Pink Noise and Landscapes (n=10 each). ERPs locked to image onset were obtained from occipital electrodes ader ocular artifacts rejection (by ICA decomposition). Results We found significant differences between patients and healthy controls in occipital areas approximately 500 ms after image onset. These differences were used to train a classifier to discriminate the schizophrenia patients from the controls. The best classifier had 81% sensitivity for the detection of patients and specificity of 59% for the detection of controls, with an overall accuracy of 71%. We observed a positive wave after NS (natural scenes) landscape image onset, with late differences between the SZ patients and HCs. After visual inspection of the ERPs from each area (frontal, central, parietal, and occipital), we found significant differences only in the occipital ERP. It had two positive peaks in the HCs but a reduced second peak in the SZ patients. The median ERP at 0.4–0.6 s after image onset for the HCs was 4.14 μ V and 1.55 μ V for the SZ patients. The patients had a significant decrease in their ERP amplitude compared to the HCs (p = 0.01, Z = −2.5, T = 82, WRS test). Only the occipital electrodes showed differences in this period with the NS images. No other differences between the HC and SZ groups were found at other locations or time periods. We found significant differences between HC and SZ groups at the occipital electrodes only for the NS. Neither gray (p = 0.29, Z = −1.06, T = 101, WRS test) nor pink noise images (p = 0.93, Z = −0.07, T = 114, WRS test) showed significant differences between the HCs and SZ patients at any group of electrodes at this or any other time period. With an accuracy of 71% we are able to classified subjects. We performed 1350 cross--validation leaving 4 subjects out (two SCZ and two controls). 70.5% of the subjects with schizophrenia were correctly detected. Discussion This study shows that EEG features can differentiate between SCZ and HC in a simple, instruction--free visual task. Differences in late potentials (>300 ms) and in more complex images suggests deficits in top--down (cognitive) rather than bottom--up (perception) mechanisms. These results indicate that EEG signals from a free-viewing paradigm discriminate patients from healthy controls and have the potential to become a tool for the psychiatrist to support the positive diagnosis of schizophrenia.

scholarly journals Dimension of model parameter space and operating characteristics in adaptive dose-finding studies

2016 ◽  
Vol 35 (21) ◽  
pp. 3760-3775 ◽  
Author(s):  
Alexia Iasonos ◽  
Nolan A. Wages ◽  
Mark R. Conaway ◽  
Ken Cheung ◽  
Ying Yuan ◽  
...  
Keyword(s):  
Parameter Space ◽  
Dose Finding ◽  
Operating Characteristics ◽  
Model Parameter

scholarly journals Combining EEG and Eye Tracking: Using Fixation-Locked Potentials in Visual Search

2013 ◽  
Vol 6 (4) ◽  
Author(s):  
Brent Winslow ◽  
Angela Carpenter ◽  
Jesse Flint ◽  
Xuezhong Wang ◽  
David Tomasetti ◽  
...  
Keyword(s):  
Visual Search ◽  
Eye Tracking ◽  
Time Pressure ◽  
Neural Pathways ◽  
Search Tasks ◽  
Analysis Process ◽  
Eeg Recordings ◽  
And Performance ◽  
Search Training ◽  
Areas Of Interest

Visual search is a complex task that involves many neural pathways to identify relevant areas of interest within a scene. Humans remain a critical component in visual search tasks, as they can effectively perceive anomalies within complex scenes. However, this task can be challenging, particularly under time pressure. In order to improve visual search training and performance, an objective, process-based measure is needed. Eye tracking technology can be used to drive real-time parsing of EEG recordings, providing an indication of the analysis process. In the current study, eye fixations were used to generate ERPs during a visual search task. Clear differences were observed following performance, suggesting that neurophysiological signatures could be developed to prevent errors in visual search tasks.

scholarly journals No-scale gauge non-singlet inflation inducing TeV scale inverse seesaw mechanism

2021 ◽  
Vol 2021 (10) ◽  
Author(s):  
Ahmad Moursy
Keyword(s):  
Gauge Symmetry ◽  
Parameter Space ◽  
Crucial Role ◽  
Essential Role ◽  
Mass Parameter ◽  
Susy Breaking ◽  
The Other ◽  
Neutrino Masses ◽  
Seesaw Mechanism ◽  
Model Parameter

Abstract We develop a model of sneutrino inflation that is charged under U(1)B−L gauge symmetry, in no-scale supergravity framework. The model provides an interesting modification of tribrid inflation. We impose U(1)R symmetry on the renormalizable level while allow Planck suppressed non-renormalizable operators that break R-symmetry. This plays a crucial role in realizing a Starobinsly-like inflation scenario from one hand. On the other hand it plays an essential role, as well as SUSY breaking effects, in deriving the tiny neutrino masses via TeV inverse seesaw mechanism. Thus, we provide an interpretation for the extremely small value of the μS mass parameter required for inverse seesaw mechanism. We discuss a reheating scenario and possible constraints on the model parameter space in connection to neutrino masses.

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