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 |
| Summary: | 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 |
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| ISSN: | 0716-9760 0717-6287 |