The detrended fluctuation and cross-correlation analysis of EEG signals. (2018)

• Record Type: Journal Article
• Authors: Hirekhan, Sunil R.; Manthalkar, Ramchandra R.
• Is Part Of: International journal of intelligent systems design and computing. Volume 2:Number 2(2018)
• Page Start: 139
• Page End: 155
• Publication Date: 2018
• Subjects: detrended fluctuation analysis -- DFA -- detrended cross-correlation analysis -- DCCA -- power-law correlation -- mindfulness meditation -- complexity indicator; Artificial intelligence -- Periodicals; Human-computer interaction -- Periodicals; 006.3
• Languages: English
• ISSNs: 2052-8477

Abstract

The detrended fluctuation analysis (DFA) and detrended cross-correlation analysis (DCCA) are the widely used methods for analysis of non-stationary time series. The detrended fluctuation and cross-correlation analysis of the EEG signals pre- and post-meditation (mindfulness) intervention are compared. It is observed that the EEG data obtained from seven subjects out of total 11 subjects shows reduction in the DFA and DCCA exponent values. The reduction in DFA exponent value represents the lower intrinsic fluctuation in the EEG time series, which is a measure of better (higher) complexity of these vital rhythms. The reduced DFA exponent values after 8-weeks of focused attention (mindfulness) meditation practice in more number of subjects indicate that the meditation practice enhances the ability to handle complexity. The detrended cross-correlation analysis (DCCA) of EEG signals shows that the EEG signals of electrode pair of two brain lobe hemispheres obeys the power-law relationship, and the DCCA exponent is reduced in value after the meditation intervention. The reduced DFA and DCCA exponents indicate improved neuronal functioning of these subjects.