2009
DOI: 10.1016/j.jneumeth.2009.01.006
|View full text |Cite
|
Sign up to set email alerts
|

Assessing the strength of directed influences among neural signals using renormalized partial directed coherence

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

2
216
0

Year Published

2012
2012
2018
2018

Publication Types

Select...
8

Relationship

1
7

Authors

Journals

citations
Cited by 199 publications
(218 citation statements)
references
References 24 publications
2
216
0
Order By: Relevance
“…In particular, the PDC can take values arbitrarily close to either one or zero if the scale of the target variable is changed accordingly [80]. -The application of time-variant multivariate analysis approaches (i.e.…”
Section: Discussionmentioning
confidence: 99%
“…In particular, the PDC can take values arbitrarily close to either one or zero if the scale of the target variable is changed accordingly [80]. -The application of time-variant multivariate analysis approaches (i.e.…”
Section: Discussionmentioning
confidence: 99%
“…In the context of partial coherence [31], falsely detected influence between two components, caused by a third component, occurs if both exhibit a connection to a common third component. This effect is referred to as marrying parents of a joint child [1,45].…”
Section: Discussionmentioning
confidence: 99%
“…The concept of detecting Granger non-causalities by zero autoregressive coefficients is also realized as a statistical tool in the frequency domain called PDC [32,33] and its further development as renormalized PDC (rPDC) [31]. Here, the rPDC is used to infer Granger causality for time-series data, and the main notions for statistical inference are listed below.…”
Section: (A) Granger Causalitymentioning
confidence: 99%
See 1 more Smart Citation
“…In • Partial directed coherence (PDC) was first proposed by [76] as a normalization of A(z) with the assumption that Σ is diagonal. The form has been renormalized in many ways: to include noise covariance in the normalization [79], or to provide meaningful connection strength [80]. The following description is proposed in [79] and described in [8].…”
Section: Therefore the Z Transform Of The Ar Equation Is A(z)y (Z) =mentioning
confidence: 99%