Esophageal epithelium modeling based on globally coupled map: an approach toward precancerous lesion diagnosis.

Esophageal squamous cell carcinoma is the most predominant malignancy of the esophagus. Its histological precursors (dysplasia) emerge in the esophageal epithelium that their progression into the underlying layers leads to cancer. The epithelium is the origin of many solid cancers and, accordingly, the focus of numerous computational models.

Nonlinear Analysis of Electroencephalogram Signals while Listening to the Holy Quran.

Background: Electrical activity of the brain, resulting from electrochemical signaling between neurons, is recorded by electroencephalogram (EEG). The neural network has complex behavior at different levels that strongly confirms the nonlinear nature of interactions in the human brain. This study has been designed and implemented with the aim of determining the effects of religious beliefs and the effect of listening to Holy Quran on electrical activity of the brain of the Iranian Persian-speaking Muslim volunteers.

Predicting tipping points of dynamical systems during a period-doubling route to chaos.

Classical indicators of tipping points have limitations when they are applied to an ecological and a biological model. For example, they cannot correctly predict tipping points during a period-doubling route to chaos. To counter this limitation, we here try to modify four well-known indicators of tipping points, namely the autocorrelation function, the variance, the kurtosis, and the skewness.

Spirituality and brain waves.

The aim of this study is to investigate the effect of Quran on a Persian-speaking Muslim. Volunteers listened to three different audio files (Verses from Sura 'Forqan' unconsciously; Arabic text unconsciously; Verses from Sura 'Fath' consciously). EEG signals were recorded and the changes in the relative power of theta and alpha band are considered an indicators of relaxation.

On the discrimination of patho-physiological states in epilepsy by means of dynamical measures.

In the present paper a number of techniques were applied to determine the effects of epileptic seizure on spontaneous ongoing EEG. The idea is that seizure represents transitions of an epileptic brain from its normal (chaotic) state to an abnormal (more ordered) state. Some nonlinear measures including correlation dimension, maximum Lyapunov exponent and wavelet entropy and a graphical tool, named recurrence plot, as well as a novel technique that collects some statistics of the state space organization were used to characterize interictal, preictal and ictal states and derivate a phase transition.