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Nonlinear multivariate analysis of neurophysiological signals
Multivariate time series analysis is extensively used in neurophysiology with the aim of
studying the relationship between simultaneously recorded signals. Recently, advances on …
studying the relationship between simultaneously recorded signals. Recently, advances on …
[ספר][B] Methods for neural ensemble recordings
MAL Nicolelis - 1998 - taylorfrancis.com
Neuroscientists have long recognized the importance of understanding the underlying
principles of information processing by large populations of neurons. Methods for Neural …
principles of information processing by large populations of neurons. Methods for Neural …
Speaker gaze increases information coupling between infant and adult brains
When infants and adults communicate, they exchange social signals of availability and
communicative intention such as eye gaze. Previous research indicates that when …
communicative intention such as eye gaze. Previous research indicates that when …
Partial directed coherence: a new concept in neural structure determination
This paper introduces a new frequency-domain approach to describe the relationships
(direction of information flow) between multivariate time series based on the decomposition …
(direction of information flow) between multivariate time series based on the decomposition …
A new method of the description of the information flow in the brain structures
The paper describes the method of determining direction and frequency content of the brain
activity flow. The method was formulated in the framework of the AR model. The transfer …
activity flow. The method was formulated in the framework of the AR model. The transfer …
Estimating structured high-dimensional covariance and precision matrices: Optimal rates and adaptive estimation
This is an expository paper that reviews recent developments on optimal estimation of
structured high-dimensional covariance and precision matrices. Minimax rates of …
structured high-dimensional covariance and precision matrices. Minimax rates of …
Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and …
In this article we consider the application of parametric spectral analysis to multichannel
event-related potentials (ERPs) during cognitive experiments. We show that with proper data …
event-related potentials (ERPs) during cognitive experiments. We show that with proper data …
Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks
This article explores the use of scalar and multivariate autoregressive (AR) models to extract
features from the human electroencephalogram (EEG) with which mental tasks can be …
features from the human electroencephalogram (EEG) with which mental tasks can be …
Determination of information flow direction among brain structures by a modified directed transfer function (dDTF) method
A modification of directed transfer function—direct DTF—is proposed for the analysis of
direct information transfer among brain structures on the basis of local field potentials (LFP) …
direct information transfer among brain structures on the basis of local field potentials (LFP) …
Comparison of different cortical connectivity estimators for high‐resolution EEG recordings
The aim of this work is to characterize quantitatively the performance of a body of techniques
in the frequency domain for the estimation of cortical connectivity from high‐resolution EEG …
in the frequency domain for the estimation of cortical connectivity from high‐resolution EEG …