A model of computation in neocortical architecture.
basic_science · Level V
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Abstract
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.