Dynamics underlying spontaneous human alpha oscillations: A data-driven approach

• Published in: NeuroImage (Orlando, Fla.) Vol. 57; no. 2; pp. 440 - 451
• Main Authors: Hindriks, R., Bijma, F., van Dijk, B.W., van der Werf, Y.D., van Someren, E.J.W., van der Vaart, A.W.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 15-07-2011; Elsevier Limited
• Subjects: Aged; Algorithms; Alpha Rhythm - physiology; Alzheimer Disease - physiopathology; Brain - physiology; Brain Mapping - methods; Cognitive ability; Economic models; Electroencephalography; Female; Humans; Magnetoencephalography; Male; Middle Aged; Models, Neurological; Noise; Nonlinear Dynamics; Signal Processing, Computer-Assisted
• ISSN: 1053-8119; 1095-9572
• DOI: 10.1016/j.neuroimage.2011.04.043

Although the cognitive and clinical correlates of spontaneous human alpha oscillations as recorded with electroencephalography (EEG) or magnetoencephalography (MEG) are well documented, the dynamics underlying these oscillations is still a matter of debate. This study proposes a data-driven method to reveal the dynamics of these oscillations. It demonstrates that spontaneous human alpha oscillations as recorded with MEG can be viewed as noise-perturbed damped harmonic oscillations. This provides evidence for the hypothesis that these oscillations reflect filtered noise and hence do not possess limit-cycle dynamics. To illustrate the use of the model, we apply it to two data-sets in which a decrease in alpha power can be observed across conditions. The associated differences in the estimated model parameters show that observed decreases in alpha power are associated with different kinds of changes in the dynamics. Thus, the model parameters are useful dynamical biomarkers for spontaneous human alpha oscillations.
► The dynamics underlying spontaneous alpha oscillations is still a matter of debate ► Data-driven modeling using stochastic differential equations can provide insight ► Spontaneous alpha oscillations can be described by noisy harmonic oscillators ► The model provides a dynamical account of observed power changes