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Dataset
Neurocomputational cortical memory for spectro-temporal phonetic abstraction.
Computer Science: Faculty Publications and Other Works
  • Dario Dematties, University of Buenos Aires
  • George K. Thiruvathukal, Loyola University Chicago
  • Silvio Rizzi, Argonne National Laboratory
  • Alejandro Javier Wainselboim, University of Buenos Aires
  • Bonifacio Silvano Zanutto, University of Buenos Aires
Document Type
Data Set
Publication Date
3-1-2019
Publisher Name
Zenodo
Abstract

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.

Identifier
10.5281/zenodo.2584864
Creative Commons License
Creative Commons Attribution-Noncommercial-Share Alike 4.0
Citation Information
Dematties, Dario, Thiruvathukal, George K., Rizzi, Silvio, Wainselboim, Alejandro Javier, & Zanutto, Bonifacio Silvano. (2019, February 28). neurophon/neurophon: Release for PLOS submission (Version v1.0). Zenodo. http://doi.org/10.5281/zenodo.2580396