Journal ArticleDOI
The effect of linear mixing in the EEG on Hurst exponent estimation.
TLDR
The findings imply that the long-range correlative properties of the EEG should be studied in source space, in such a way that the SNR is maximized, or at least with spatial decomposition techniques approximating source activities, rather than in sensor space.About:
This article is published in NeuroImage.The article was published on 2014-10-01. It has received 32 citations till now. The article focuses on the topics: Hurst exponent & Detrended fluctuation analysis.read more
Citations
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Journal Article
Beta-band oscillations--signalling the status quo?
Andreas K. Engel,Pascal Fries +1 more
TL;DR: It is hypothesized that beta oscillations and/or coupling in the beta-band are expressed more strongly if the maintenance of the status quo is intended or predicted, than if a change is expected.
Journal ArticleDOI
A Simulation Framework for Benchmarking EEG-Based Brain Connectivity Estimation Methodologies.
TL;DR: A simulation framework that enables researchers to test their analysis pipelines on realistic pseudo-EEG data and construct a minimal example of brain interaction, which is proposed as a benchmark for assessing a methodology’s general eligibility for EEG-based connectivity estimation.
Journal ArticleDOI
Dimensionality reduction for the analysis of brain oscillations
TL;DR: Simulations and analysis of real EEG experiments show that, while not being supervised, the SSD algorithm is capable of extracting components primarily relating to the signal of interest often using as little as 20% of the data variance, instead of > 90% variance as in case of PCA.
Journal ArticleDOI
A Review on Nonlinear Methods Using Electroencephalographic Recordings for Emotion Recognition
TL;DR: This paper summarizes the most recent works that have applied nonlinear methods in EEG signal analysis to emotion recognition and identifies some nonlinear indices that have not yet been employed in this research area.
Journal ArticleDOI
Modular co-organization of functional connectivity and scale-free dynamics in the human brain.
Alexander Zhigalov,Alexander Zhigalov,Gabriele Arnulfo,Gabriele Arnulfo,Lino Nobili,Satu Palva,J. Matias Palva +6 more
TL;DR: It is suggested that FC and scale-free dynamics—hence, putatively, neuronal criticality as well—coemerge in a hierarchically modular structure in which the modules are characterized by dense connectivity, avalanche propagation, and shared dynamic states.
References
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Journal ArticleDOI
Independent component analysis: algorithms and applications
Aapo Hyvärinen,Erkki Oja +1 more
TL;DR: The basic theory and applications of ICA are presented, and the goal is to find a linear representation of non-Gaussian data so that the components are statistically independent, or as independent as possible.
Journal ArticleDOI
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging.
Michael D. Fox,Marcus E. Raichle +1 more
TL;DR: Recent studies examining spontaneous fluctuations in the blood oxygen level dependent (BOLD) signal of functional magnetic resonance imaging as a potentially important and revealing manifestation of spontaneous neuronal activity are reviewed.
Journal ArticleDOI
Mosaic organization of DNA nucleotides
Chung-Kang Peng,Chung-Kang Peng,Chung-Kang Peng,Sergey V. Buldyrev,Sergey V. Buldyrev,Sergey V. Buldyrev,Shlomo Havlin,Shlomo Havlin,Shlomo Havlin,Michael Simons,Michael Simons,Michael Simons,H. E. Stanley,H. E. Stanley,H. E. Stanley,Ary L. Goldberger,Ary L. Goldberger,Ary L. Goldberger +17 more
TL;DR: This work analyzes two classes of controls consisting of patchy nucleotide sequences generated by different algorithms--one without and one with long-range power-law correlations, finding that both types of sequences are quantitatively distinguishable by an alternative fluctuation analysis method.
Journal ArticleDOI
Neuronal Avalanches in Neocortical Circuits
John M. Beggs,Dietmar Plenz +1 more
TL;DR: This work shows that propagation of spontaneous activity in cortical networks is described by equations that govern avalanches, and suggests that “neuronal avalanches” may be a generic property of cortical networks, and represent a mode of activity that differs profoundly from oscillatory, synchronized, or wave-like network states.