Description
The human brain is the most complex object created by evolution in the known universe. Yet, how much of this complexity is devoted to exclusively carrying out its algorithmic capabilities and how much of it has been inherited from biological paths of evolution in order to work properly in its physical environment? What if the information processing properties of the brain could be reduced to a few simple columnar rules replicated throughout the neocortex? In our research project we seek for those principles by means of the elaboration of computational models of the neocortex.
| Date made available | Mar 1 2019 |
|---|---|
| Publisher | Loyola University Chicago |
Disciplines
- Artificial Intelligence and Robotics
- Computer Sciences
Keywords
- early language acquisition
- sparse distributed representations
- unsupervised learning
- neural networks
- biologically inspired computational models
- incidental phonetic acquisition
- cortical dynamics