Transfer entropy is a way to estimate interdependencies between two time series that is sensitive to both linear and nonlinear interactions so a useful measure for brain signals. However, it […]
Applying Transfer Entropy to the EEG
Lab Talk
A New Metric of Waveform Complexity in EEG Analysis
It is yet unclear which features of the EEG signal are the most informative about brain states and outcomes. A new complexity measure with different assumptions does a better job […]
Understanding Multiscale Entropy
Multiscale entropy extends sample entropy to multiple time scales or signal resolutions to provide an additional perspective when the time scale of relevance is unknown. Multiscale entropy (MSE) provides insights […]
The Impact of Parameter Choices on EEG Entropy Measures
Entropy measures are affected by data length, choice of window length and threshold suggesting caution in how they are used and interpreted. In previous posts we have discussed different entropy […]
Measuring Entropy in the EEG
Entropy measures quantify the uncertainty in the EEG, which roughly equates to the possible configurations or their predictability. However there are many method and parameter choices that can fundamentally change […]