Partial directed coherence: a new concept in neural structure determination

By L. Baccalá, K. Sameshima. Biological cybernetics, 2001

1,748 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Signal Processing

View Paper: https://www.semanticscholar.org/paper/a555ee5d480993e2e9ee65ea21b8042f3177df14

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Citations in the corpus

EEG Based Emotion Recognition by Combining Functional Connectivity Network and Local Activations (2019, background): “partial direct coherence (PDC) [24], and phase slope index [25], and extracted features from these networks for four emotions (happy, angry, sad and relax) in pre- and post-meditation states.”
Testing for directed influences among neural signals using partial directed coherence. (2006, positive): “The partial been used inference of linear Granger-causality in the frequency domain based on vector autoregressive models of appropriate order p (VAR[ p ]) (Baccala and Sameshima, 2001; Sameshima and Bac-cala, 1999).”
Estimating brain functional connectivity with sparse multivariate autoregression (2005, methodology): “MAR modelling has been widely applied in neuroscience research (Baccala & Sameshima 2001; Kaminski et al .”
Electrophysiological Imaging of Brain Activity and Connectivity – Challenges and Opportunities (2011, background): “are able to differentiate causal interactions within specific frequency bands of interest [98], [99].”
Determination of EEG activity propagation: pair-wise versus multichannel estimate (2004, methodology): “A multivariate approach was also applied by Baccalá and Sameshima [18], who developed the partial directed coherence (PDC) method to describe direct causal relations between signals.”
Source connectivity analysis with MEG and EEG (2009, methodology): “After fitting the MVAR-model to the time courses of the estimated sources, directed interactions can be quantified by means of the directed transfer function (DTF) [Kaminski and Liang, 2005], or the partial directed coherence [Baccala and Sameshima, 2001; Kaminski and Blinowska, 1991].”
Nonlinear multivariate analysis of neurophysiological signals. (2005, methodology): “This method was introduced recently (Baccala and Sameshima, 2001b; Sameshima and Baccala, 1999) and provides a frequency domain measure for Granger causality.”
How reliable are MEG resting-state connectivity metrics? (2016, background): “…these goals, for example by partialling out data (Marrelec et al., 2006) or using temporal precedence as an indicator of causality (Granger, 1969; Baccala and Sameshima, 2001), are noisier to estimate, and the extent to which they show repeatable or reliable behaviour in MEG is poorly understood.”
Mapping directed influence over the brain using Granger causality and fMRI (2005, methodology): “…has been previously applied to electrophysiological animal data, specifically Local Field Potentials (LFPs) to detect influences at the neuronal population level (Baccala and Sameshima, 2001; Bernasconi and Konig, 1999; Bernasconi et al., 2000; Brovelli et al., 2004; Freiwald et al., 1999).”
Identifying true brain interaction from EEG data using the imaginary part of coherency. (2004, methodology): “…function (DTF) approach, a linear autoregressive model is fitted to the data and interaction is deduced and characterized from mixing coefficients (Baccala and Sameshima, 2001; Cassidy and Brown, 2003; Hesse et al., 2003; Kaminski et al., 2001; Korzeniewska et al., 2003; Mima et al., 2001).”
A critical assessment of connectivity measures for EEG data: A simulation study (2013, methodology): “This is assessed per frequency by partial directed coherence (PDC, Baccalá and Sameshima, 2001).”
Brain–computer interface boosts motor imagery practice during stroke recovery (2015, methodology): “The PDC matrices were computed per methods that have been detailed elsewhere.(61,62,64) In brief, spurious connectivity values due to random correlation between the data were discarded by asymptotic statistical procedure, returning a significance threshold for each PDC value and thus allowing only s”
FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data (2010, background): “…details related to the functionality of the di ﬀ erent modules, without the aim of being exhaustive. imaginary part of coherency [11], phase slope index [12], partial directed coherence [13], directed transfer function [14], and Geweke’s extension of Granger causality to the frequency domain [15].”
Graph analysis of functional brain networks: practical issues in translational neuroscience (2014, background): “Finally, brain nodes are typically assigned to sensors or sources, but they can also be assigned to ICA components [51].”
A MATLAB toolbox for Granger causal connectivity analysis. (2010, neutral): “Two alternativemeasures closely related to spectral G-causality re partial directed coherence (Baccalá and Sameshima, 2001) and he directed transfer function (Kaminski et al.”