Manuela La Rosa

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In this paper, systems formed by networks of simple nonlinear cells are studied. Using lattice models, some of the fundamental features of complex systems such as self-organization and pattern formation are illustrated. In the first part of this work, a lattice of identical Chua's circuit is used to experimentally study its global spatiotemporal dynamics,(More)
Magnetoencephalography (MEG) brain signals are studied using a method for characterizing complex nonlinear dynamics. This approach uses the value of d(infinity) (d-infinite) to characterize the system's asymptotic chaotic behavior. A novel procedure has been developed to extract this parameter from time series when the system's structure and laws are(More)
In this paper, we investigate the role of topology on synchronization, a fundamental feature of many technological and biological fields. We study it in Hindmarsh-Rose neural networks, with electrical and chemical synapses, where neurons are placed on a bi-dimensional lattice, folded on a torus, and the synapses are set according to several topologies. In(More)
Nonlinear spatio-temporal analysis was performed on neural activity recorded with 148-channel whole-head Magnetoencephalography (MEG). The analysis consists of two phases: artifact removal and nonlinear feature evaluation. Known artifacts, produced by cardiac and eye movement, and unknown artifacts have been isolated from neural activity by using two(More)