On the Statistical Performance of Connectivity Estimators in the Frequency Domain

  • Koichi Sameshima
  • Daniel Y. Takahashi
  • Luiz A. Baccalá
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8609)


This paper studies the performance of recently introduced asymptotic statistics for connectivity inference in the frequency domain, namely via information partial directed coherence (iPDC) and information directed transfer function (iDTF) and compares them to the behaviour of a classic time domain multivariate Granger causality test (GCT) by using Monte Carlo simulations of three widely used toy-models under varying the simulated data record lengths. In general, the false-positive rates for non-existing connections and the false-negative rates for existing connections are found to decrease with longer record lengths.


Partial Directed Coherence Directed Transfer Function Granger Causality Null hypothesis test performance 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Koichi Sameshima
    • 1
  • Daniel Y. Takahashi
    • 2
  • Luiz A. Baccalá
    • 3
  1. 1.Department of Radiology and Oncology, Faculdade de MedicinaUniversity of São PauloSão PauloBrazil
  2. 2.Psychology Department, Neuroscience InstitutePrinceton UniversityPrincetonUSA
  3. 3.Department of Telecommunications and Control EngineeringEscola Politécnica, University of São PauloSão PauloBrazil

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