Dynamical Complexity in Cognitive Neural Networks
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 wit...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
BMC
2007-01-01
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| Series: | Biological Research |
| Subjects: | |
| Online Access: | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602007000500009 |
| _version_ | 1818409655274045440 |
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| author | ERIC GOLES ADRIÁN G PALACIOS |
| author_facet | ERIC GOLES ADRIÁN G PALACIOS |
| author_sort | ERIC GOLES |
| collection | DOAJ |
| description | 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 |
| first_indexed | 2024-12-14T10:03:04Z |
| format | Article |
| id | doaj.art-32b47e86ac284faf8e5feb62898dc24d |
| institution | Directory Open Access Journal |
| issn | 0716-9760 0717-6287 |
| language | English |
| last_indexed | 2024-12-14T10:03:04Z |
| publishDate | 2007-01-01 |
| publisher | BMC |
| record_format | Article |
| series | Biological Research |
| spelling | doaj.art-32b47e86ac284faf8e5feb62898dc24d2022-12-21T23:07:13ZengBMCBiological Research0716-97600717-62872007-01-01404479485Dynamical Complexity in Cognitive Neural NetworksERIC GOLESADRIÁN G PALACIOSIn 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 complexityhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602007000500009ArtificialNeural NetBrainDynamical ComplexityComputational NeurosciencesCellular Automata |
| spellingShingle | ERIC GOLES ADRIÁN G PALACIOS Dynamical Complexity in Cognitive Neural Networks Biological Research Artificial Neural Net Brain Dynamical Complexity Computational Neurosciences Cellular Automata |
| title | Dynamical Complexity in Cognitive Neural Networks |
| title_full | Dynamical Complexity in Cognitive Neural Networks |
| title_fullStr | Dynamical Complexity in Cognitive Neural Networks |
| title_full_unstemmed | Dynamical Complexity in Cognitive Neural Networks |
| title_short | Dynamical Complexity in Cognitive Neural Networks |
| title_sort | dynamical complexity in cognitive neural networks |
| topic | Artificial Neural Net Brain Dynamical Complexity Computational Neurosciences Cellular Automata |
| url | http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602007000500009 |
| work_keys_str_mv | AT ericgoles dynamicalcomplexityincognitiveneuralnetworks AT adriangpalacios dynamicalcomplexityincognitiveneuralnetworks |