scholarly journals Changes in EEG Power Spectral Density and Cortical Connectivity in Healthy and Tetraplegic Patients during a Motor Imagery Task

2009 ◽  
Vol 2009 ◽  
pp. 1-12 ◽  
Author(s):  
Filippo Cona ◽  
Melissa Zavaglia ◽  
Laura Astolfi ◽  
Fabio Babiloni ◽  
Mauro Ursino
Keyword(s):  
Brain Connectivity ◽  
Real Data ◽  
Element Model ◽  
Inhibitory Neurons ◽  
Imagery Task ◽  
Power Spectral ◽  
Neural Mass ◽  
The Difference ◽  
Cortical Regions ◽  
Shell Boundary

Knowledge of brain connectivity is an important aspect of modern neuroscience, to understand how the brain realizes its functions. In this work, neural mass models including four groups of excitatory and inhibitory neurons are used to estimate the connectivity among three cortical regions of interests (ROIs) during a foot-movement task. Real data were obtained via high-resolution scalp EEGs on two populations: healthy volunteers and tetraplegic patients. A 3-shell Boundary Element Model of the head was used to estimate the cortical current density and to derive cortical EEGs in the three ROIs. The model assumes that each ROI can generate an intrinsic rhythm in the beta range, and receives rhythms in the alpha and gamma ranges from other two regions. Connectivity strengths among the ROIs were estimated by means of an original genetic algorithm that tries to minimize several cost functions of the difference between real and model power spectral densities. Results show that the stronger connections are those from the cingulate cortex to the primary and supplementary motor areas, thus emphasizing the pivotal role played by theCMA_Lduring the task. Tetraplegic patients exhibit higher connectivity strength on average, with significant statistical differences in some connections. The results are commented and virtues and limitations of the proposed method discussed.

scholarly journals Estimating Differential Latent Variable Graphical Models with Applications to Brain Connectivity

Biometrika ◽  
2020 ◽  
Author(s):  
S Na ◽  
M Kolar ◽  
O Koyejo
Keyword(s):  
Graphical Models ◽  
Latent Variable ◽  
Graphical Model ◽  
Brain Connectivity ◽  
Statistical Error ◽  
Real Data ◽  
Low Rank ◽  
Conditional Dependence ◽  
Gradient Descent Algorithm ◽  
The Difference

Abstract Differential graphical models are designed to represent the difference between the conditional dependence structures of two groups, thus are of particular interest for scientific investigation. Motivated by modern applications, this manuscript considers an extended setting where each group is generated by a latent variable Gaussian graphical model. Due to the existence of latent factors, the differential network is decomposed into sparse and low-rank components, both of which are symmetric indefinite matrices. We estimate these two components simultaneously using a two-stage procedure: (i) an initialization stage, which computes a simple, consistent estimator, and (ii) a convergence stage, implemented using a projected alternating gradient descent algorithm applied to a nonconvex objective, initialized using the output of the first stage. We prove that given the initialization, the estimator converges linearly with a nontrivial, minimax optimal statistical error. Experiments on synthetic and real data illustrate that the proposed nonconvex procedure outperforms existing methods.

Inflections of Periodicities of Background Photon Spectral Power Densities Are Predicted by the Lorentz Contraction for a Potential Indicator for the Intrinsic Structure of Space

2016 ◽  
pp. 4014-4017
Author(s):  
Michael A Persinger
Keyword(s):  
Spectral Power ◽  
Neutral Hydrogen ◽  
Intrinsic Structure ◽  
Lorentz Contraction ◽  
Intrinsic Nature ◽  
Basic Interval ◽  
Power Spectral ◽  
The Difference ◽  
Background Photon ◽  
Power Densities

                The value for the Lorentz contraction to produce a discrepancy for a hypothetical number that reflects a property (21.3π4) of sub-matter space was calculated. When applied to time the contraction would be ~35 min. The difference in mass-equivalent energy for an electron at c (the velocity of light in a vacuum) and the required v was ~2 ·10-20 J which has emerged as a significant quantity that may permeate from the force at Planck’s Length when applied across the wavelength of the neutral hydrogen line. Two separate types of photomultiplier instruments (digital and analogue) measuring with different sampling rates for background photon quantities over 50 randomly selected days demonstrated averaged conspicuous inflections of standardized spectral power densities around 35 min. This is the same basic interval where microvariations in the value of the gravitational constant (G) approached a limit at which white noise dominated.  The possibility is considered that this value for temporal inflections in photon power spectral densities may reflect the intrinsic nature of space-time contractions that relate gravity and photons.

scholarly journals Implications of Extended Inhibitory Neuron Development

2021 ◽  
Vol 22 (10) ◽  
pp. 5113
Author(s):  
Jae-Yeon Kim ◽  
Mercedes F. Paredes
Keyword(s):  
Neural Circuit ◽  
Inhibitory Neuron ◽  
Postnatal Period ◽  
Specific Pattern ◽  
Inhibitory Neurons ◽  
Gabaergic Interneuron ◽  
Gabaergic Interneurons ◽  
Neuron Development ◽  
Cortical Regions ◽  
Circuit Formation

A prolonged developmental timeline for GABA (γ-aminobutyric acid)-expressing inhibitory neurons (GABAergic interneurons) is an amplified trait in larger, gyrencephalic animals. In several species, the generation, migration, and maturation of interneurons take place over several months, in some cases persisting after birth. The late integration of GABAergic interneurons occurs in a region-specific pattern, especially during the early postnatal period. These changes can contribute to the formation of functional connectivity and plasticity, especially in the cortical regions responsible for higher cognitive tasks. In this review, we discuss GABAergic interneuron development in the late gestational and postnatal forebrain. We propose the protracted development of interneurons at each stage (neurogenesis, neuronal migration, and network integration), as a mechanism for increased complexity and cognitive flexibility in larger, gyrencephalic brains. This developmental feature of interneurons also provides an avenue for environmental influences to shape neural circuit formation.

Numerical Prediction of Noise Radiated From a Panel Subjected to Boundary Layer Excitation

1999 ◽  
Author(s):  
Michael Allen ◽  
Nickolas Vlahopoulos
Keyword(s):  
Boundary Layer ◽  
Finite Element ◽  
Boundary Element ◽  
Transfer Functions ◽  
Element Model ◽  
Acoustic Response ◽  
Spectral Densities ◽  
Wind Noise ◽  
Element Analysis ◽  
Power Spectral

Abstract In this paper an algorithm is developed for combining finite element analysis and boundary element techniques in order to compute the noise radiated from a panel subjected to boundary layer excitation. The excitation is presented in terms of the auto and cross power spectral densities of the fluctuating wall pressure. The structural finite element model for the panel is divided into a number of sub-panels. A uniform fluctuating pressure is applied as excitation on each sub-panel separately. The corresponding vibration is computed, and is utilized as excitation for an acoustic boundary element analysis. The acoustic response is computed at any data recovery point of interest. The relationships between the acoustic response and the pressure excitation applied at each particular sub-panel constitute a set of transfer functions. They are combined with the spectral densities of the excitation for computing the noise generated from the vibration of the panel subjected to the boundary layer excitation. The development presented in this paper has the potential of computing wind noise in automotive applications, or boundary layer noise in aircraft applications.

scholarly journals A Robust Rerank Approach for Feature Selection and Its Application to Pooling-Based GWA Studies

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jia-Rou Liu ◽  
Po-Hsiu Kuo ◽  
Hung Hung
Keyword(s):  
Characteristic Curve ◽  
Real Data ◽  
Tuning Parameter ◽  
Practical Implementation ◽  
Tuning Parameters ◽  
Genome Wide ◽  
Feature Based ◽  
The Difference ◽  
Gwa Studies ◽  
Selection Of

Large-p-small-ndatasets are commonly encountered in modern biomedical studies. To detect the difference between two groups, conventional methods would fail to apply due to the instability in estimating variances int-test and a high proportion of tied values in AUC (area under the receiver operating characteristic curve) estimates. The significance analysis of microarrays (SAM) may also not be satisfactory, since its performance is sensitive to the tuning parameter, and its selection is not straightforward. In this work, we propose a robust rerank approach to overcome the above-mentioned diffculties. In particular, we obtain a rank-based statistic for each feature based on the concept of “rank-over-variable.” Techniques of “random subset” and “rerank” are then iteratively applied to rank features, and the leading features will be selected for further studies. The proposed re-rank approach is especially applicable for large-p-small-ndatasets. Moreover, it is insensitive to the selection of tuning parameters, which is an appealing property for practical implementation. Simulation studies and real data analysis of pooling-based genome wide association (GWA) studies demonstrate the usefulness of our method.

scholarly journals Analysing Random Vibration of KLT Box during Transporting by Finite Element Method

10.29007/b1th ◽  
2022 ◽  
Author(s):  
Cong Hoa Vu ◽  
Ngoc Thien Ban Dang
Keyword(s):  
Finite Element ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Automotive Industry ◽  
Random Vibration ◽  
Element Model ◽  
Vibration Testing ◽  
Time Data ◽  
Power Spectral ◽  
The Impact

Today, freight is an extremely important industry for the world we are living. Fast transportation, large volume...will optimize the cost, time and effort. Besides, ensuring the products safety is a matter of concern. During transporting, it is inevitable that the vibration caused by the engine, rough road surface...the cargo inside can be damaged. Automobile industries have prime importance to vibration testing. Sine vibration testing is performed when we have been given with only one frequency at given time instant. Trend to perform random vibration testing has been increased in recent times. As random vibration considers all excited frequencies in defined spectrum at known interval of time, it gives real-time data of vibration severities. The vibration severity is expressed in terms of Power Spectral Density (PSD). KLT box is an industrial stacking container conforming to the VDA 4500 standard that was defined by German Association of the Automotive Industry (VDA) for the automotive industry. The aim of this paper is study about random vibration and power spectral density analysis, how it can be used to predict the impact of hash road to the KLT box on container / truck during transportation. Finite element model is developed in ANSYS, modal analysis and random vibration analysis were done.

Ion Beam Figuring Fabricate Effect with Different Removal Sizes

2013 ◽  
Vol 552 ◽  
pp. 142-146
Author(s):  
Yong Qiang Gu
Keyword(s):  
Spatial Frequency ◽  
Ion Beam ◽  
Influence Factors ◽  
Frequency Range ◽  
Surface Errors ◽  
Power Spectral ◽  
The Difference ◽  
Lens Surface ◽  
Ion Beam Figuring

Ion Beam Figure (IBF) is believed to be one of the most effective technics that can fabricate lens with nano or even sub-nano accuracy. For different sizes of IBF removal functions, the correct effects in different spatial frequency range are different. Power Spectral Density (PSD) curve can describe surface errors in full spatial frequency range, so it is a very convenient way to evaluate the quality of lens’ surface. In this paper, firstly, the principles of IBF and PSD are introduced briefly; Secondly, IBF removal functions with sizes from 2 mm to 15 mm are generated. A lens with surface error more than PV value 400nm is simulated with different sizes of IBF removal functions by Lucy-Richardson algorithm. Finally, experiments are done by IBF plant. A lens is fabricated by different sizes of removal functions and the fabricate results are tested by interferometer precisely and calculated to PSD curves. By the comparison of these curves, the IBF fabricate effects with different removal sizes are analyzed, which show that the smaller the removal size, the better the removal effect in higher spatial frequency range, but in the meantime, it will take a much longer time. Also the reasons of the difference between theory simulation and actual fabrication result are taken into account, and several influence factors are analyzed.

scholarly journals Empirical Study of Omnichannel Purchasing Pattern with Real Customer Data from Health and Lifestyle Company

2019 ◽  
Vol 11 (24) ◽  
pp. 7185 ◽  
Author(s):  
Jongsoo Kang ◽  
Marko Majer ◽  
Hyun-Jung Kim
Keyword(s):  
High Performance ◽  
Statistical Significance ◽  
Real Data ◽  
Usage Pattern ◽  
Customer Data ◽  
Customer Group ◽  
Trading Period ◽  
Online Channel ◽  
The Difference ◽  
Offline Channels

This study examines the effect of omnichannel usage pattern on customers’ purchasing amount by determining statistical significance of different purchasing amount occurred for online and offline channel usage pattern with empirical analysis. The data is collected from a health and lifestyle company operated by Major Pharmaceutical company in Korea, which sells health supplement and skincare products through their owned online and offline channels. The channel usage pattern of customers is categorized into four groups: Customer using online channel only, customer using offline channel only, customer first joined membership through online and use both on/offline channels and customers joined membership through offline channel and use both on/offline. Then, the trading period, total number of purchasing, average purchasing amount per transaction and total purchasing amount during trading period among the above four groups were analyzed. The result demonstrated the number of purchasing, average purchasing amount and total purchasing amount for the omnichannel customer groups who cross used on and offline showed statistical significance. However, the difference in purchasing amount between the group of customers who joined online membership and use offline channel and another customer group that joined offline membership and use online channel was not statistically significant. This study overcame the limitation of conventional studies used survey based data, by the application of empirical data from the real customers in on/offline channels, and provides meaningful insights based on empirical real data that group of customers with higher purchasing experience in both on/offline channels shows high performance.

scholarly journals Characterizing the Complexity of Weighted Networks via Graph Embedding and Point Pattern Analysis

Entropy ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. 925
Author(s):  
Shuo Chen ◽  
Zhen Zhang ◽  
Chen Mo ◽  
Qiong Wu ◽  
Peter Kochunov ◽  
...  
Keyword(s):  
Complex Networks ◽  
Pattern Analysis ◽  
Brain Connectivity ◽  
Graph Embedding ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Healthy Controls ◽  
Weighted Networks ◽  
The Difference ◽  
Weighted Complex Networks

We propose a new metric to characterize the complexity of weighted complex networks. Weighted complex networks represent a highly organized interactive process, for example, co-varying returns between stocks (financial networks) and coordination between brain regions (brain connectivity networks). Although network entropy methods have been developed for binary networks, the measurement of non-randomness and complexity for large weighted networks remains challenging. We develop a new analytical framework to measure the complexity of a weighted network via graph embedding and point pattern analysis techniques in order to address this unmet need. We first perform graph embedding to project all nodes of the weighted adjacency matrix to a low dimensional vector space. Next, we analyze the point distribution pattern in the projected space, and measure its deviation from the complete spatial randomness. We evaluate our method via extensive simulation studies and find that our method can sensitively detect the difference of complexity and is robust to noise. Last, we apply the approach to a functional magnetic resonance imaging study and compare the complexity metrics of functional brain connectivity networks from 124 patients with schizophrenia and 103 healthy controls. The results show that the brain circuitry is more organized in healthy controls than schizophrenic patients for male subjects while the difference is minimal in female subjects. These findings are well aligned with the established sex difference in schizophrenia.

scholarly journals Bayesian Inference for the Difference of Two Proportion Parameters in Over-Reported Two-Sample Binomial Data Using the Doubly Sample

Stats ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 111-120 ◽  
Author(s):  
Dewi Rahardja
Keyword(s):  
Bayesian Inference ◽  
Closed Form ◽  
Bayesian Approach ◽  
Interval Estimation ◽  
Real Data ◽  
Simulation Studies ◽  
Posterior Distributions ◽  
Binomial Data ◽  
The Difference ◽  
Data Subject

We construct a point and interval estimation using a Bayesian approach for the difference of two population proportion parameters based on two independent samples of binomial data subject to one type of misclassification. Specifically, we derive an easy-to-implement closed-form algorithm for drawing from the posterior distributions. For illustration, we applied our algorithm to a real data example. Finally, we conduct simulation studies to demonstrate the efficiency of our algorithm for Bayesian inference.

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