2 resultados para COMPUTATIONAL NEUROSCIENCE

em Universidade Federal do Rio Grande do Norte(UFRN)


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Following the new tendency of interdisciplinarity of modern science, a new field called neuroengineering has come to light in the last decades. After 2000, scientific journals and conferences all around the world have been created on this theme. The present work comprises three different subareas related to neuroengineering and electrical engineering: neural stimulation; theoretical and computational neuroscience; and neuronal signal processing; as well as biomedical engineering. The research can be divided in three parts: (i) A new method of neuronal photostimulation was developed based on the use of caged compounds. Using the inhibitory neurotransmitter GABA caged by a ruthenium complex it was possible to block neuronal population activity using a laser pulse. The obtained results were evaluated by Wavelet analysis and tested by non-parametric statistics. (ii) A mathematical method was created to identify neuronal assemblies. Neuronal assemblies were proposed as the basis of learning by Donald Hebb remain the most accepted theory for neuronal representation of external stimuli. Using the Marcenko-Pastur law of eigenvalue distribution it was possible to detect neuronal assemblies and to compute their activity with high temporal resolution. The application of the method in real electrophysiological data revealed that neurons from the neocortex and hippocampus can be part of the same assembly, and that neurons can participate in multiple assemblies. (iii) A new method of automatic classification of heart beats was developed, which does not rely on a data base for training and is not specialized in specific pathologies. The method is based on Wavelet decomposition and normality measures of random variables. Throughout, the results presented in the three fields of knowledge represent qualification in neural and biomedical engineering

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As neuroscience gains social traction and entices media attention, the notion that education has much to benefit from brain research becomes increasingly popular. However, it has been argued that the fundamental bridge toward education is cognitive psychology, not neuroscience. We discuss four specific cases in which neuroscience synergizes with other disciplines to serve education, ranging from very general physiological aspects of human learning such as nutrition, exercise and sleep, to brain architectures that shape the way we acquire language and reading, and neuroscience tools that increasingly allow the early detection of cognitive deficits, especially in preverbal infants. Neuroscience methods, tools and theoretical frameworks have broadened our understanding of the mind in a way that is highly relevant to educational practice. Although the bridge’s cement is still fresh, we argue why it is prime time to march over it.