Neuronal plasticity mechanisms induced by brain-machine interfaces: connecting brain to artificial neural network

Autores/as

  • Marcelo Antônio Oliveira Santos Centro Universitário Maurício de Nassau http://orcid.org/0000-0001-6025-9821
  • José Daniel dos Santos Figueredo Universidade Federal Rural de Pernambuco
  • Lucas Soares Bezerra Centro Universitário Maurício de Nassau
  • Francisco Nêuton de Oliveira Magalhães Universidade de São Paulo

Palabras clave:

aptidão física, saúde, aptidão cardiorrespiratória, corrida

Resumen

Brain-machine interfaces, also known as Brain-Computer Interfaces (BCI), are devices that connect the brain to a computer. In the last decade it is been used to investigate the restore of sensorimotor function in patients with cortical damage. Some evidence supports that the results obtained in the research using BCIs in the treatment of these patients are directly dependent on plasticity mechanisms very similar to those observed in learning and memory tasks. Recent studies have been making use of Artificial Neural Networks (ANN) to classify signal patterns throughout neuronal circuits in order to command movements. In this review, we attempted to make a survey on the available data in the literature on this topic in order to gather the most relevant evidence of such mechanisms and the role of ANN on human brain neuronal input decoding compared to other data processing techniques.

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Publicado

2017-03-02

Cómo citar

Oliveira Santos, M. A., dos Santos Figueredo, J. D., Soares Bezerra, L., & de Oliveira Magalhães, F. N. (2017). Neuronal plasticity mechanisms induced by brain-machine interfaces: connecting brain to artificial neural network. Revista De Medicina E Saúde De Brasília, 5(3). Recuperado a partir de https://portalrevistas.ucb.br/index.php/rmsbr/article/view/7469