User profiles for Raul Vicente
Raul VicenteProfessor of Data Science, Institute of Computer Science, University of Tartu Verified email at ut.ee Cited by 7190 |
Analysis and characterization of the hyperchaos generated by a semiconductor laser subject to a delayed feedback loop
We characterize the chaotic dynamics of semiconductor lasers subject to either optical or
electrooptical feedback modeled by Lang-Kobayashi and Ikeda equations, respectively. This …
electrooptical feedback modeled by Lang-Kobayashi and Ikeda equations, respectively. This …
[HTML][HTML] Multiagent cooperation and competition with deep reinforcement learning
Evolution of cooperation and competition can appear when multiple adaptive agents share
a biological, social, or technological niche. In the present work we study how cooperation …
a biological, social, or technological niche. In the present work we study how cooperation …
[HTML][HTML] Transfer entropy—a model-free measure of effective connectivity for the neurosciences
Understanding causal relationships, or effective connectivity, between parts of the brain is of
utmost importance because a large part of the brain’s activity is thought to be internally …
utmost importance because a large part of the brain’s activity is thought to be internally …
Untangling cross-frequency coupling in neuroscience
Highlights • Fundamental caveats and confounds in the methodology of assessing CFC are
discussed. • Significant CFC can be observed without any underlying physiological coupling. …
discussed. • Significant CFC can be observed without any underlying physiological coupling. …
Zero-lag long-range synchronization via dynamical relaying
We show that isochronous synchronization between two delay-coupled oscillators can be
achieved by relaying the dynamics via a third mediating element, which surprisingly lags …
achieved by relaying the dynamics via a third mediating element, which surprisingly lags …
Dynamical relaying can yield zero time lag neuronal synchrony despite long conduction delays
Multielectrode recordings have revealed zero time lag synchronization among remote cerebral
cortical areas. However, the axonal conduction delays among such distant regions can …
cortical areas. However, the axonal conduction delays among such distant regions can …
[HTML][HTML] Measuring information-transfer delays
In complex networks such as gene networks, traffic systems or brain circuits it is important to
understand how long it takes for the different parts of the network to effectively influence one …
understand how long it takes for the different parts of the network to effectively influence one …
[HTML][HTML] TRENTOOL: A Matlab open source toolbox to analyse information flow in time series data with transfer entropy
Background Transfer entropy (TE) is a measure for the detection of directed interactions.
Transfer entropy is an information theoretic implementation of Wiener's principle of …
Transfer entropy is an information theoretic implementation of Wiener's principle of …
[BOOK][B] Directed information measures in neuroscience
In scientific discourse and the media it is commonplace to state that brains exist to ‘process
information’. Curiously enough, however, we only have a certain understanding of what is …
information’. Curiously enough, however, we only have a certain understanding of what is …
Transfer entropy in magnetoencephalographic data: quantifying information flow in cortical and cerebellar networks
…, B Rahm, M Rieder, M Lindner, R Vicente… - Progress in biophysics …, 2011 - Elsevier
The analysis of cortical and subcortical networks requires the identification of their nodes, and
of the topology and dynamics of their interactions. Exploratory tools for the identification of …
of the topology and dynamics of their interactions. Exploratory tools for the identification of …