Dynamical complexity in cognitive neural networks

Eric Goles, Adrián G. Palacios

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


In the last twenty years an important effort in brain sciences, especially in cognitive science, has been the development of mathematical tool that can deal with the complexity of extensive recordings corresponding to the neuronal activity obtained from hundreds of neurons. We discuss here along with some historical issues, advantages and limitations of Artificial Neural Networks (ANN) that can help to understand how simple brain circuits work and whether ANN can be helpful to understand brain neural complexity.

Original languageEnglish
Pages (from-to)479-485
Number of pages7
JournalBiological Research
Issue number4
StatePublished - 2007
Externally publishedYes


  • Artificial
  • Brain
  • Cellular automata
  • Computational neurosciences
  • Dynamical complexity
  • Neural net


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