TY - JOUR
T1 - Detrended fluctuation analysis: A scale-free view on neuronal oscillations
AU - Hardstone, R.E.
AU - Poil, S.S.
AU - Schiavone, G.
AU - Nikulin, V.V.
AU - Mansvelder, H.D.
AU - Linkenkaer Hansen, K.
PY - 2012
Y1 - 2012
N2 - Recent years of research have shown that the complex temporal structure of ongoing oscillations is scale-free and characterized by long-range temporal correlations. Detrended fluctuation analysis (DFA) has proven particularly useful, revealing that genetic variation, normal development, or disease can lead to differences in the scale-free amplitude modulation of oscillations. Furthermore, amplitude dynamics is remarkably independent of the time-averaged oscillation power, indicating that the DFA provides unique insights into the functional organization of neuronal systems. To facilitate understanding and encourage wider use of scaling analysis of neuronal oscillations, we provide a pedagogical explanation of the DFA algorithm and its underlying theory. Practical advice on applying DFA to oscillations is supported by MATLAB scripts from the Neurophysiological Biomarker Toolbox (NBT) and links to the NBT tutorial website http://www.nbtwiki.net/. Finally, we provide a brief overview of insights derived from the application of DFA to ongoing oscillations in health and disease, and discuss the putative relevance of criticality for understanding the mechanism underlying scale-free modulation of oscillations. © 2012 Hardstone, Poil, Schi-avone, Jansen, Nikulin, Mansvelder and Linkenkaer-Hansen.
AB - Recent years of research have shown that the complex temporal structure of ongoing oscillations is scale-free and characterized by long-range temporal correlations. Detrended fluctuation analysis (DFA) has proven particularly useful, revealing that genetic variation, normal development, or disease can lead to differences in the scale-free amplitude modulation of oscillations. Furthermore, amplitude dynamics is remarkably independent of the time-averaged oscillation power, indicating that the DFA provides unique insights into the functional organization of neuronal systems. To facilitate understanding and encourage wider use of scaling analysis of neuronal oscillations, we provide a pedagogical explanation of the DFA algorithm and its underlying theory. Practical advice on applying DFA to oscillations is supported by MATLAB scripts from the Neurophysiological Biomarker Toolbox (NBT) and links to the NBT tutorial website http://www.nbtwiki.net/. Finally, we provide a brief overview of insights derived from the application of DFA to ongoing oscillations in health and disease, and discuss the putative relevance of criticality for understanding the mechanism underlying scale-free modulation of oscillations. © 2012 Hardstone, Poil, Schi-avone, Jansen, Nikulin, Mansvelder and Linkenkaer-Hansen.
U2 - 10.3389/fphys.2012.00450
DO - 10.3389/fphys.2012.00450
M3 - Article
SN - 1664-042X
VL - 3
JO - Frontiers in Physiology
JF - Frontiers in Physiology
M1 - UNSP 450
ER -