IEEE transactions on bio-medical engineering · 2016
Directed Transfer Function: Unified Asymptotic Theory and Some of Its Implications.
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Baccala Luiz A, Takahashi Daniel Y, Sameshima Koichi
Аннотация
OBJECTIVE: To present a unified mathematical derivation of the frequency-dependent asymptotic behavior of the three main forms of directed transfer function (DTF).
METHODS: A synthesis of the results (proved in an extended Appendix) is followed by a series of Monte Carlo simulations of representative examples.
RESULTS: DTF estimators are asymptotically normal when the true values are different from zero. Under the null hypothesis H0: DTF=0, the estimator is distributed as a linear combination of independent χ21 variables.
CONCLUSIONS: Null DTF rejection is shown to be achievable with identical performance irrespective of which DTF form is adopted.
SIGNIFICANCE: Together with recent allied partial directed coherence results, this paper rounds up connectivity inference tools for a class of frequency-domain connectivity estimators.
METHODS: A synthesis of the results (proved in an extended Appendix) is followed by a series of Monte Carlo simulations of representative examples.
RESULTS: DTF estimators are asymptotically normal when the true values are different from zero. Under the null hypothesis H0: DTF=0, the estimator is distributed as a linear combination of independent χ21 variables.
CONCLUSIONS: Null DTF rejection is shown to be achievable with identical performance irrespective of which DTF form is adopted.
SIGNIFICANCE: Together with recent allied partial directed coherence results, this paper rounds up connectivity inference tools for a class of frequency-domain connectivity estimators.