Results 31 to 40 of about 910,963 (262)

Inferring single neuron properties in conductance-based balanced networks

Frontiers in Computational Neuroscience, 2011
Balanced states in large networks are a usual hypothesis for explaining the variability of neural activity in cortical systems. These states give rise to a generic behavior in which the individual dynamics of the neurons is almost irrelevant.
Germán eMato, Roman eRossi Pool
doaj   +1 more source

Covariance-enhanced discriminant analysis

Biometrika, 2014
Linear discriminant analysis has been widely used to characterize or separate multiple classes via linear combinations of features. However, the high dimensionality of features from modern biological experiments defies traditional discriminant analysis techniques.
Peirong Xu, Ji Zhu, Lixing Zhu, Yi Li
openaire   +4 more sources

A cautionary note on the use of the Analysis of Covariance (ANCOVA) in classification designs with and without within-subject factors

Frontiers in Psychology, 2015
A number of statistical textbooks recommend using an analysis of covariance (ANCOVA) to control for the effects of extraneous factors that might influence the dependent measure of interest. However, it is not generally recognized that serious problems of
Bruce A Schneider, Meital eAvivi-Reich, Mindaugas eMozuraitis   +2 more
doaj   +1 more source

Covariance Regression Analysis

Journal of the American Statistical Association, 2015
This article introduces covariance regression analysis for a p-dimensional response vector. The proposed method explores the regression relationship between the p-dimensional covariance matrix and auxiliary information. We study three types of estimators: maximum likelihood, ordinary least squares, and feasible generalized least squares estimators ...
Zou, Tao, Lan, Wei, Hansheng Wang, Chih-Ling Tsai   +3 more
openaire   +1 more source

Covariance Matrix Preparation for Quantum Principal Component Analysis

PRX Quantum, 2022
Principal component analysis (PCA) is a dimensionality reduction method in data analysis that involves diagonalizing the covariance matrix of the dataset.
Max Hunter Gordon, M. Cerezo, Lukasz Cincio, Patrick J. Coles   +3 more
doaj   +1 more source

Structural Covariance Network Disruption and Functional Compensation in Parkinson’s Disease

Frontiers in Aging Neuroscience, 2020
Purpose: To investigate the structural covariance network disruption in Parkinson’s disease (PD), and explore the functional alterations of disrupted structural covariance network.Methods: A cohort of 100 PD patients and 70 healthy participants underwent
Cheng Zhou, Ting Gao, Tao Guo, Jingjing Wu, Xiaojun Guan, Weiwen Zhou, Peiyu Huang, Min Xuan, Quanquan Gu, Xiaojun Xu, Shunren Xia, Dexing Kong, Jian Wu, Minming Zhang   +13 more
doaj   +1 more source

Lessons Learned From a Delayed‐Start Trial of Modafinil for Freezing of Gait in Parkinson's Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Freezing of gait (FOG) in people with Parkinson's disease (PwPD) is debilitating and has limited treatments. Modafinil modulates beta/gamma band activity in the pedunculopontine nucleus (PPN), like PPN deep brain stimulation. We therefore tested the hypothesis that Modafinil would improve FOG in PwPD.
Tuhin Virmani, Lakshmi Pillai, Reid D. Landes, Aliyah Glover, Shannon Doerhoff, Jennifer Kleiner, Mitesh Lotia, Rohit Dhall, Edgar Garcia‐Rill   +8 more
wiley   +1 more source

Real‐World Performance of CSF Kappa Free Light Chains in the 2024 McDonald Criteria

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF‐restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real‐world cohort and the 2024 McDonald criteria; (2 ...
Maya M. Leibowitz, Ryan Cooper, Stefania Kaninia, Kathryn I. Challis, Will Greenway, Maria Bonello, Mahmoud Elbahnasawi, Deborah T. Shode, Dominika Gajdasik, Victor Iliev, Alison M. E. Whitelegg, Ian Galea   +11 more
wiley   +1 more source

A new covariance intersection based integrated SLAM framework for 3D outdoor agricultural applications

Electronics Letters
This letter introduces a novel integrated framework for simultaneous localization and mapping (SLAM) tailored for general agricultural applications.
Hann‐Gyoo Kim, Hea‐Min Lee, Seung‐Hwan Lee   +2 more
doaj   +1 more source

A New Approach for Nonlinear Transformation of Means and Covariances in Direct Statistical Analysis of Nonlinear Systems

IEEE Access, 2021
Covariance analysis describing function technique is a conventional method to solve the performance analysis of the nonlinear missile guidance system. Aiming at the faultiness of covariance analysis describing function technique and its improved method ...
Quancheng Li, Yonghua Fan, Hongyang Xu, Xuechao Liang, Jie Yan   +4 more
doaj   +1 more source