Neurociencias
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Examinando Neurociencias por Autor "Belluscio, Mariano"
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Artículo de Publicación Periódica Classification based on dynamic mode decomposition applied to brain recognition of context(2021-09) Martínez, Sebastián; Silva, Azul; García Violini, Demián; Piriz, Joaquin; Belluscio, Mariano; Sánchez-Peña, Ricardo"Local Field Potentials (LFPs) are easy to access electrical signals of the brain that represent the summation in the extracellular space, of currents originated within the neurons. As such, LFPs could contain infor mation about ongoing computations in neuronal circuits and could potentially be used to design brain machine interface algorithms. However how brain computations could be decoded from LFPs is not clear. Within this context, a methodology for signal classification is proposed in this study, particularly based on the Dynamic Mode Decomposition method, in conjunction with binary clustering routines based on supervised learning. Note that, although the classification methodology is presented here in the context of a biological problem, it can be applied to a broad range of applications. Then, as a case-study, the proposed method is validated with the classification of LFP-based brain cognitive states. All the analysis, signals, and results shown in this study consider real data measured in the hippocampus, in rats perform ing exploration tasks. Consequently, it is shown that, using the measured LFP, the method infers which context was the animal exploring. Thus, evidence on the spatial codification in LFP signals is consequently provided, which still is an open question in neuroscience."Artículo de Publicación Periódica Dynamical models in neuroscience from a closed-loop control perspective(2022-01-28) Martínez, Sebastián; García Violini, Demián; Belluscio, Mariano; Piriz, Joaquin; Sánchez-Peña, Ricardo"Modifying neural activity is a substantial goal in neuroscience that facilitates the understanding of brain functions and the development of medical therapies. Neurobiological models play an essential role, contributing to the understanding of the underlying brain dynamics. In this context, control systems represent a fundamental tool to provide a correct articulation between model stimulus (system inputs) and outcomes (system outputs). However, throughout the literature there is a lack of discussions on neurobiological models, from the formal control perspective. In general, existing control proposals applied to this family of systems, are developed empirically, without theoretical and rigorous framework. Thus, the existing control solutions, present clear and significant limitations. The focus of this work is to survey dynamical neurobiological models that could serve for closed-loop control schemes or for simulation analysis. Consequently, this paper provides a comprehensive guide to discuss and analyze control oriented neurobiological models. It also provides a potential framework to adequately tackle control problems that could modify the behavior of single neurons or networks. Thus, this study constitutes a key element in the upcoming discussions and studies regarding control methodologies applied to neurobiological systems, to extend the present research and understanding horizon for this field."Artículo de Publicación Periódica Towards an experimental control of neural activity: The Wilson-Cowan model(IFAC-PapersOnLine, 2022) Martinez, Sebastián; Sánchez-Peña, Ricardo; Belluscio, Mariano; Piriz, Joaquín; Garcia-Violini, DemiánThe prospect of modifying neural activity in a principled way, could facilitate the understanding of brain functions and the development of medical treatments. To predict the dynamics that underlie the different brain activities, several neurobiological models have been proposed, either focusing on individual cells or whole populations. In this context, control systems are a powerful tool to provide a correct articulation between inputs, i.e. neural stimuli, and observables, i.e. system outcomes. Based on well-established neurobiological hypotheses, this study presents a control framework to regulate a neural-mass activity, with potential uses for pattern tracking, such as, rhythm evoking and phase synchronisation. Being these mechanisms closely connected with real brain computations, this study is carried out using a meaningful perspective in terms of biological interpretation. To this end, the Wilson-Cowan model is used, where the input stimuli is elicited through light signals applied to genetically modified neurons that express light-gated actuators. Thus, this study states a crucial proof of concept towards a future experimental application of the control framework for neurobiological systems.