Nonlinear Directed Interactions Between HRV and EEG Activity in Children With TLE

Research output: Contribution to journalResearch articleContributedpeer-review


  • Karin Schiecke - , Friedrich Schiller University Jena (Author)
  • Britta Pester - , Friedrich Schiller University Jena (Author)
  • Diana Piper - , Friedrich Schiller University Jena (Author)
  • Franz Benninger - , University Hospital Vienna (Author)
  • Martha Feucht - , University Hospital Vienna (Author)
  • Lutz Leistritz - , Friedrich Schiller University Jena (Author)
  • Herbert Witte - , Friedrich Schiller University Jena (Author)


Objective: Epileptic seizure activity influences the autonomic nervous system (ANS) in different ways. Heart rate variability (HRV) is used as indicator for alterations of the ANS. It was shown that linear, nondirected interactions between HRV and EEG activity before, during, and after epileptic seizure occur. Accordingly, investigations of directed nonlinear interactions are logical steps to provide, e.g., deeper insight into the development of seizure onsets. Methods: Convergent crossmapping (CCM) investigates nonlinear, directed interactions between time series by using nonlinear state space reconstruction. CCM is applied to simulated and clinically relevant data, i.e., interactions between HRV and specific EEG components of children with temporal lobe epilepsy (TLE). In addition, time-variant multivariate Autoregressive model (AR)-based estimation of partial directed coherence (PDC) was performed for the same data. Results: Influence of estimation parameters and time-varying behavior of CCM estimation could be demonstrated by means of simulated data. AR-based estimation of PDC failed for the investigation of our clinical data. Time-varying interval-based application of CCM on these data revealed directed interactions between HRV and delta-related EEG activity. Interactions between HRV and alpha-related EEG activity were visible but less pronounced. EEG components mainly drive HRV. The interaction pattern and directionality clearly changed with onset of seizure. Statistical relevant interactions were quantified by boot-strapping and surrogate data approach. Conclusion and Significance: In contrast to AR-based estimation of PDC CCM was able to reveal time-courses and frequency-selective views of nonlinear interactions for the further understanding of complex interactions between the epileptic network and the ANS in children with TLE.


Original languageEnglish
Article number7488249
Pages (from-to)2497-2504
Number of pages8
JournalIEEE transactions on biomedical engineering
Issue number12
Publication statusPublished - Dec 2016
Externally publishedYes

External IDs

PubMed 27305667
WOS 000391735300006
ORCID /0000-0001-8264-2071/work/142254073


ASJC Scopus subject areas


  • Convergent cross mapping (CCM), electroencephalogram (EEG), heart rate variability (HRV), nonlinear directed interaction, temporal lobe epilepsy (TLE)