Brain-heart interactions considering complex physiological data: processing schemes for time-variant, frequency-dependent, topographic and statistical examination of directed interactions by convergent cross mapping

Background: A multitude of complex methods is available to quantify interactions in highly complex physiological systems. Brain-heart interactions play an important role to identify couplings between the central nervous system and the autonomic nervous system during defined physiological states or specific diseases. Crucial point of those interaction analyses are an adequate pre-processing taking into account nonlinearity of data, and intuitive graphical representation as well as suitable statistical evaluation of achieved results. Objective: Aim of this study is to provide generalized processing schemes for such investigations taking into account pre-processing, graphical representation as well as statistical analysis. Approach: Two defined data sets were used to develop those processing schemes. Brain-heart interaction in children with temporal lobe epilepsy during pre-ictal, ictal and post-ictal period as well as in patients with paranoid schizophrenia and healthy control subjects during resting state period were investigated by nonlinear Convergent Cross Mapping. Surrogate data, bootstrapping and linear mixed-effects model approach were utilized for statistical analyses. Main Results: CCM was able to reveal specific and statistical significant time- and frequency dependent pattern of brain-heart interactions for children with temporal lobe epilepsy and to provide statistical significant pattern of topographic and frequency dependent brain-heart interactions for schizophrenic patients as well as to show their differences to healthy control subjects. Suitable statistical models were found to quantify group differences. Significance: Generalized processing schemes and crucial points of pre-processing, adapted interaction analysis as well as performed statistical analysis are provide. General concept of analyses is transferable also to other methods of interactions analysis and data respresenting even more complex physiological systems.