Patricia Wollstadt

TL;DR: This work combines the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series and tests the performance and robustness of the implementation on data from numerical simulations of stochastic processes.

TL;DR: The algorithm presented—as implemented in the IDTxl open-source software—addresses challenges by employing hierarchical statistical tests to control the family-wise error rate and to allow for efficient parallelization, and was validated on synthetic datasets involving random networks of increasing size.

TL;DR: The Information Dynamics Toolkit xl (IDTxl) as discussed by the authors is a comprehensive software package for efficient inference of networks and their node dynamics from multivariate time series data using information theory.

TL;DR: The study suggests the usefulness of AIS to detect an abnormal type of dynamics in ASD, and the observed changes in AIS are compatible with Bayesian theories of reduced use or precision of priors in ASD.

TL;DR: It is found that modification rose with maturation, but ultimately collapsed when redundant information among neurons took over, indicating that this particular developing neural system initially developed intricate processing capabilities but ultimately displayed information processing that was highly similar across neurons, possibly due to a lack of external inputs.