A model of computation in neocortical architecture

We propose that the specific architecture of the neocortex reflects the organization principles of neocortical computation. In this paper, we place the anatomically defined concept of columns into a functional context. It is provided by a large-scale computational hypothesis on visual recognition, w...

Full description

Saved in:
Bibliographic Details
Published inNeural networks Vol. 12; no. 7; pp. 989 - 1005
Main Authors Körner, E., Gewaltig, M.-O., Körner, U., Richter, A., Rodemann, T.
Format Journal Article
LanguageEnglish
Published United States Elsevier Ltd 01.10.1999
Subjects
Bidirectional processing
Brain models
Columnar architecture
Computational methods
Computational neuroscience
Computer simulation
Gamma oscillations
Mathematical models
Neocortex
Neurophysiology
Pattern recognition
Spiking neurons
Ventral visual pathway
Vision
Visual perception
Bidirectional processing
Spiking neurons
Ventral visual pathway
Computational neuroscience
Columnar architecture
Gamma oscillations
Neocortex
Visual perception
Online AccessGet full text

Cover

More Information
Summary:We propose that the specific architecture of the neocortex reflects the organization principles of neocortical computation. In this paper, we place the anatomically defined concept of columns into a functional context. It is provided by a large-scale computational hypothesis on visual recognition, which includes both, rapid parallel forward recognition, independent of any feedback prediction, and a feedback controlled refinement system. Short epochs of periodic clocking define a global reference time and introduce a discrete time for cortical processing which enables the combination of parallel categorization and sequential refinement. The presented model differs significantly from conventional neural network architectures and suggests a novel interpretation of the role of gamma oscillations and cognitive binding.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ObjectType-Article-2
ObjectType-Feature-1
ISSN:0893-6080
1879-2782
DOI:10.1016/S0893-6080(99)00049-0