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[HTML][HTML] Can EEG and MEG detect signals from the human cerebellum?
The cerebellum plays a key role in the regulation of motor learning, coordination and timing,
and has been implicated in sensory and cognitive processes as well. However, our current …
and has been implicated in sensory and cognitive processes as well. However, our current …
Wiener–Granger causality in network physiology with applications to cardiovascular control and neuroscience
A Porta, L Faes - Proceedings of the IEEE, 2015 - ieeexplore.ieee.org
Since the operative definition given by CWJ Granger of an idea expressed by N. Wiener, the
Wiener-Granger causality (WGC) has been one of the most relevant concepts exploited by …
Wiener-Granger causality (WGC) has been one of the most relevant concepts exploited by …
[LLIBRE][B] Transfer entropy
Transfer Entropy Page 1 Chapter 4 Transfer Entropy In this chapter we get to the essential
mathematics of the book—a detailed discussion of transfer entropy. To begin with we look at …
mathematics of the book—a detailed discussion of transfer entropy. To begin with we look at …
Direction of information flow in large-scale resting-state networks is frequency-dependent
Normal brain function requires interactions between spatially separated, and functionally
specialized, macroscopic regions, yet the directionality of these interactions in large-scale …
specialized, macroscopic regions, yet the directionality of these interactions in large-scale …
JIDT: An information-theoretic toolkit for studying the dynamics of complex systems
JT Lizier - Frontiers in Robotics and AI, 2014 - frontiersin.org
Complex systems are increasingly being viewed as distributed information processing
systems, particularly in the domains of computational neuroscience, bioinformatics, and …
systems, particularly in the domains of computational neuroscience, bioinformatics, and …
Entropy measures, entropy estimators, and their performance in quantifying complex dynamics: Effects of artifacts, nonstationarity, and long-range correlations
Entropy measures are widely applied to quantify the complexity of dynamical systems in
diverse fields. However, the practical application of entropy methods is challenging, due to …
diverse fields. However, the practical application of entropy methods is challenging, due to …
[HTML][HTML] Frequency-dependent functional connectivity within resting-state networks: an atlas-based MEG beamformer solution
The brain consists of functional units with more-or-less specific information processing
capabilities, yet cognitive functions require the co-ordinated activity of these spatially …
capabilities, yet cognitive functions require the co-ordinated activity of these spatially …
A critical assessment of connectivity measures for EEG data: a simulation study
Information flow between brain areas is difficult to estimate from EEG measurements due to
the presence of noise as well as due to volume conduction. We here test the ability of …
the presence of noise as well as due to volume conduction. We here test the ability of …
Phase transfer entropy: a novel phase-based measure for directed connectivity in networks coupled by oscillatory interactions
We introduce here phase transfer entropy (Phase TE) as a measure of directed connectivity
among neuronal oscillations. Phase TE quantifies the transfer entropy between phase time …
among neuronal oscillations. Phase TE quantifies the transfer entropy between phase time …
A new framework for the time-and frequency-domain assessment of high-order interactions in networks of random processes
While the standard network description of complex systems is based on quantifying the link
between pairs of system units, higher-order interactions (HOIs) involving three or more units …
between pairs of system units, higher-order interactions (HOIs) involving three or more units …