12 citations · 18 across the 11 of their papers we have counts for
11 papers
Phase-based spatial ordinal patterns for characterizing oscillatory dynamics
Robison J. Santos-Silva, Bruno R. R. Boaretto, Thiago L. Prado +1
The emergence of organized spatiotemporal patterns is ubiquitous in oscillatory systems, from neural populations to engineered networks. Identifying these patterns and tracking how…
Delay coordinates synchronization and induces abrupt transition in excitable networks
Bruno R. R. Boaretto, Kalel L. Rossi, Lyle E. Muller +2
Neuronal communication is inherently time-delayed, due to the finite speed of signal propagation. Although often considered challenging or disruptive, such time delays can also end…
Approach to predicting extreme events in time series of chaotic dynamical systems using machine learning techniques
Alexandre C. Andreani, Bruno R. R. Boaretto, Elbert E. N. Macau
This work proposes an innovative approach using machine learning to predict extreme events in time series of chaotic dynamical systems. The research focuses on the time series of t…
Noise-induced Extreme Events in Hodgkin-Huxley Neural Networks
Bruno R. R. Boaretto, Elbert E. N. Macau, Cristina Masoller
Extreme events are rare, large-scale deviations from typical system behavior that can occur in nonlinear dynamical systems. In this study, we explore the emergence of extreme event…
Effects of the local dynamics in the synchronization of neural models
Bruno R. R. Boaretto
The cooperative behavior of neurons and neuronal areas associated with the synchronization behavior proves to be a fundamental neural mechanism. In addition, abnormal levels of syn…
Phase synchronization in a sparse network of randomly connected neurons under the effect of Poissonian spike inputs
Bruno R. R. Boaretto, Paulo R. Protachevicz, Matheus Hansen +3
This article investigates the emergence of phase synchronization in a network of randomly connected neurons by chemical synapses. The study uses the classic Hodgkin-Huxley model to…
Dynamical properties and mechanisms of metastability: a perspective in neuroscience
Kalel L. Rossi, Roberto C. Budzinski, Everton S. Medeiros +3
Metastability, characterized by a variability of regimes in time, is a ubiquitous type of neural dynamics. It has been formulated in many different ways in the neuroscience literat…
Small changes at single nodes can shift global network dynamics
Kalel L. Rossi, Roberto C. Budzinski, Bruno R. R. Boaretto +2
Understanding the sensitivity of a system's behavior with respect to parameter changes is essential for many applications. This sensitivity may be desired - for instance in the bra…
Discriminating chaotic and stochastic time series using permutation entropy and artificial neural networks
B. R. R. Boaretto, R. C. Budzinski, K. L. Rossi +3
Extracting relevant properties of empirical signals generated by nonlinear, stochastic, and high-dimensional systems is a challenge of complex systems research. Open questions are…
Synchronization malleability in neural networks under a distance-dependent coupling
R. C. Budzinski, K. L. Rossi, B. R. R. Boaretto +2
We investigate the synchronization features of a network of spiking neurons under a distance-dependent coupling following a power-law model. The interplay between topology and coup…
Effects of neuronal variability on phase synchronization of neural networks
Kalel Luiz Rossi, Roberto Cesar Budzisnki, Joao Antonio Paludo Silveira +4
An important idea in neural information processing is the communication-through-coherence hypothesis, according to which communication between two brain regions is effective only i…