Search Results - "Blythe, Duncan A.J."

The effect of linear mixing in the EEG on Hurst exponent estimation by Blythe, Duncan A.J., Haufe, Stefan, Müller, Klaus-Robert, Nikulin, Vadim V.

“…Although the long-range temporal correlation (LRTC) of the amplitude fluctuations of neuronal EEG/MEG oscillations is widely acknowledged, the majority of…”
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Multiscale temporal neural dynamics predict performance in a complex sensorimotor task by Samek, Wojciech, Blythe, Duncan A.J., Curio, Gabriel, Müller, Klaus-Robert, Blankertz, Benjamin, Nikulin, Vadim V.

“…Ongoing neuronal oscillations are pivotal in brain functioning and are known to influence subjects' performance. This modulation is usually studied on short…”
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Power-law dynamics in neuronal and behavioral data introduce spurious correlations by Schaworonkow, Natalie, Blythe, Duncan A.J., Kegeles, Jewgeni, Curio, Gabriel, Nikulin, Vadim V.

“…Relating behavioral and neuroimaging measures is essential to understanding human brain function. Often, this is achieved by computing a correlation between…”
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Power-law dynamics in neuronal and behavioral data introduce spurious correlations: Power-Law Dynamics in Neuronal and Behavioral Data by Schaworonkow, Natalie, Blythe, Duncan A.J., Kegeles, Jewgeni, Curio, Gabriel, Nikulin, Vadim V.

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Long-range temporal correlations in neural narrowband time-series arise due to critical dynamics by Blythe, Duncan A J, Nikulin, Vadim V

“…We show theoretically that the hypothesis of criticality as a theory of long-range fluctuation in the human brain may be distinguished from the theory of…”
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Robust Statistical Detection of Power-Law Cross-Correlation by Blythe, Duncan A. J., Nikulin, Vadim V., Müller, Klaus-Robert

“…We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market…”
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Prediction and Quantification of Individual Athletic Performance of Runners by Blythe, Duncan A J, Király, Franz J

“…We present a novel, quantitative view on the human athletic performance of individual runners. We obtain a predictor for running performance, a parsimonious…”
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Feature Extraction for Change-Point Detection Using Stationary Subspace Analysis by Blythe, D. A. J., von Bunau, P., Meinecke, F. C., Muller, K-R

“…Detecting changes in high-dimensional time series is difficult because it involves the comparison of probability densities that need to be estimated from…”
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Explorative data analysis for changes in neural activity by Blythe, Duncan A J, Meinecke, Frank C, von Bünau, Paul, Müller, Klaus-Robert

“…Neural recordings are non-stationary time series, i.e. their properties typically change over time. Identifying specific changes, e.g., those induced by a…”
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