ABSTRACT
Several recent studies suggest that quantitative description of signal complexity using algorithms of nonlinear analysis could uncover new information about the autonomic system that is not reflected using common methods applied to measures of autonomic activity. With this aim we have performed complexity analysis of electrodermal activity (EDA) assessed in 106 healthy university students during rest conditions and non-conflicting and conflicting Stroop task. Complexity analysis applied to EDA was performed using Skinner's algorithm for pointwise correlation dimension (PD2). Results have shown that EDA responses during the Stroop Colour Word test are related to significantly increased or decreased complexity. Particularly significant result is that PD2 has a unique ability to predict to an extent the change in EDA response to stress i.e. that subjects with low initial PD2 tended to respond to experimental stress by its increase and subjects with high initial PD2 values tended to respond by its decrease. This response was not found in EDA measures where increase of the EDA presented predominant response to experimental stress in majority of the subjects. These findings suggest that PD2 is more sensitive to subtle aspects of functionally and spatially distributed modulatory influences of various parts of the brain that are involved in the EDA modulation and provides novel information in comparison to traditional methods.
