Estimating dynamic cortical connectivity from motor imagery EEG using KALMAN smoother & EM algorithm

No abstract is available for this paper.

• Publication year

  2014

• Venue

  Symposium on Software Performance

• Publication date

  2014-08-28

• Fields of study

  Mathematics, Computer Science

• Identifiers
  DOI 10.1109/SSP.2014.6884605
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Measuring Time-Varying Information Flow in Scalp EEG Signals: Orthogonalized Partial Directed Coherence

  2014cited by this paper
• Dynamic functional connectivity: Promise, issues, and interpretations

  2013cited by this paper
• Single-trial connectivity estimation for classification of motor imagery data

  2013influential reference
• Closed-Form Solutions to Forward–Backward Smoothing

  2012cited by this paper
• An expectation-maximization algorithm based Kalman smoother approach for single-trial estimation of event-related potentials

  2012cited by this paper
• Spectral Estimation of Nonstationary EEG Using Particle Filtering With Application to Event-Related Desynchronization (ERD)

  2011cited by this paper
• Analysis of the time-varying cortical neural connectivity in the newborn EEG: A time-frequency approach

  2011cited by this paper
• Network modelling methods for FMRI

  2011cited by this paper
• Estimation of Cortical Connectivity From EEG Using State-Space Models

  2010cited by this paper
• Extended causal modeling to assess Partial Directed Coherence in multiple time series with significant instantaneous interactions

  2010cited by this paper
• Tracking the Time-Varying Cortical Connectivity Patterns by Adaptive Multivariate Estimators

  2008cited by this paper
• Identifying true brain interaction from EEG data using the imaginary part of coherency.

  2004cited by this paper
• The use of time-variant EEG Granger causality for inspecting directed interdependencies of neural assemblies.

  2003cited by this paper
• Adaptive AR modeling of nonstationary time series by means of Kalman filtering

  1998cited by this paper
• AN APPROACH TO TIME SERIES SMOOTHING AND FORECASTING USING THE EM ALGORITHM

  1982cited by this paper

• Proficiency in motor imagery is linked to the lateralization of focused ERD patterns and beta PDC

  2025cites this paper
• The Time-Varying Network Patterns in Motor Imagery Revealed by Adaptive Directed Transfer Function Analysis for fMRI

  2018cites this paper
• Functional Brain Connectivity during Multiple Motor Imagery Tasks in Spinal Cord Injury

  2018cites this paper
• Analysis of EEG channel coupling for motor imagery applications

  2017cites this paper
• A Unified Estimation Framework for State-Related Changes in Effective Brain Connectivity

  2017cites this paper
• The Time-Varying Networks in P300: A Task-Evoked EEG Study

  2016cites this paper
• Shrinkage estimation of high-dimensional vector autoregressions for effective connectivity in fMRI

  2016cites this paper
• Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review

  2016cites this paper
• Sensor space time-varying information flow analysis of multiclass motor imagery through Kalman Smoother and EM algorithm

  2015cites this paper
• Identifying Dynamic Effective Connectivity States in fMRI Based on Time-Varying Vector Autoregressive Models

  2015cites this paper
• Motor imagery brain functional connectivity analysis via coherence

  2015cites this paper