A Bahraminasab et al 2009 New J. Phys. 11 103051 doi:10.1088/1367-2630/11/10/103051
A Bahraminasab1, F Ghasemi2, A Stefanovska1,3, P V E McClintock1 and R Friedrich2
Show affiliationsWe use drift and diffusion coefficients to reveal interactions between different oscillatory processes underlying a complex signal and apply the method to EEG δ and θ frequencies in the brain. By analysis of data recorded from rats during anæsthesia, we consider the stability and basins of attraction of fixed points in the phase portrait of the deterministic part of the retrieved stochastic process. We show that different classes of dynamics are associated with deep and light anæsthesia, and we demonstrate that the predominant directionality of the interaction is such that θ drives δ.
GENERAL SCIENTIFIC SUMMARY
Introduction and background. Signals from complex systems can be hard to interpret, and require methods developed in physics and nonlinear science. This is especially so in the case of physiological signals. These may carry quite detailed information about events that normally occur unseen in the interior of the body, even though the measurements are non-invasive and occasion no discomfort. Physics is need for extraction of the relevant information.
Main results. The paper reports analyses of brain signals (EEG data) from rats under anaesthesia. A Fokker–Planck analysis is used to reveal dramatic changes between deep and light anaesthesia, which fall into different universality classes with an associated change in the P(δ, θ) joint probability (see figure). In addition, it is shown that the predominant direction of their interaction is such that the EEG θ-wave drives the δ-wave.
Wider implications. The results provide a beautiful demonstration that living systems, and brain dynamics in particular, are characterized by dynamical properties well known from the inanimate world. The clear demonstration of a deterministic pattern of interaction between brain waves is important for the understanding and further modelling of brain dynamics. The method can also be used to investigate other brain wave interactions, and under diverse conditions, e.g. Parkinsonism, cognitive tasks, sleep, autism, or following brain injury. The discovery that the EEG θ-wave usually drives the δ-wave, even in anaesthesia, carries implications for the understanding of anaesthesia and for the design of future depth-of-anaesthesia monitors.

Figure. Comparison of the δ – θ probability functions for (left) deep and (right) light anaesthesia.
87.85.Ng Biological signal processing
87.19.R- Mechanical and electrical properties of tissues and organs
Issue 10 (October 2009)
Received 3 June 2009
Published 27 October 2009
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