Abstract We analyze electroencephalographic signals (EEG signals) collected during an experiment, where each man was exposed to light of two different colors (blue and red) as well as to darkness as a control condition. For each man and each lighting condition, after signal filtering, we apply independent component analysis to EEG signals to obtain sources of the EEG signals (ICA sources). In the next step, we use a nonlinear method, recurrence plot, to characterize the ICA sources. Taking into account Taken’s theorem, we construct a set of vectors composed of successive values of a single ICA source. For each man, light condition and ICA source we analyze the distance matrix between these vectors. Based on this matrix, we perform recurrence quantification analysis. Considering all participants, light conditions, and ICA sources we get a set of distance matrices. For each matrix, we calculate: percent of determinism, Shannon entropy, and average line length. These measures provide information about changes in the dynamics of the ICA sources producing the EEG signal under light–dark conditions. We demonstrate that light exposure, and its color in particular, selectively affects EEG signal ICA sources by changing its dynamic properties.
Weber et al. (Sat,) studied this question.