Literature DB >> 12766428

Computational constraints that may have favoured the lamination of sensory cortex.

Alessandro Treves1.   

Abstract

At the transition from early reptilian ancestors to primordial mammals, the areas of sensory cortex that process topographic modalities acquire the laminar structure of isocortex. A prominent step in lamination is granulation, whereby the formerly unique principal layer of pyramidal cells is split by the insertion of a new layer of excitatory, but intrinsic, granule cells, layer IV. I consider the hypothesis that granulation, and the differentiation between supra- and infra-granular pyramidal layers, may be advantageous to support fine topography in their sensory maps. Fine topography implies a generic distinction between "where" information, explicitly mapped on the cortical sheet, and "what" information, represented in a distributed fashion as a distinct firing pattern across neurons. These patterns can be stored on recurrent collaterals in the cortex, and such memory can help substantially in the analysis of current sensory input. The simulation of a simplified network model demonstrates that a non-laminated patch of cortex must compromise between transmitting "where" information or retrieving "what" information. The simulation of a modified model including differentiation of a granular layer shows a modest but significant quantitative advantage, expressed as a less severe trade-off between "what" and "where". The further connectivity differentiation between infra-granular and supra-granular pyramidal layers is shown to match the mix of "what" and "where" information optimal for their respective target structures.

Mesh:

Year:  2003        PMID: 12766428     DOI: 10.1023/a:1023213010875

Source DB:  PubMed          Journal:  J Comput Neurosci        ISSN: 0929-5313            Impact factor:   1.621


  33 in total

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Authors:  H Supèr; H B Uylings
Journal:  Cereb Cortex       Date:  2001-12       Impact factor: 5.357

5.  Intrinsic lattice connections of macaque monkey visual cortical area V4.

Authors:  T Yoshioka; J B Levitt; J S Lund
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Review 6.  Distributed hierarchical processing in the primate cerebral cortex.

Authors:  D J Felleman; D C Van Essen
Journal:  Cereb Cortex       Date:  1991 Jan-Feb       Impact factor: 5.357

Review 7.  Viewpoint: the core and matrix of thalamic organization.

Authors:  E G Jones
Journal:  Neuroscience       Date:  1998-07       Impact factor: 3.590

8.  Cortical structure predicts the pattern of corticocortical connections.

Authors:  H Barbas; N Rempel-Clower
Journal:  Cereb Cortex       Date:  1997 Oct-Nov       Impact factor: 5.357

9.  Disruption of layers 3 and 4 during development results in altered thalamocortical projections in ferret somatosensory cortex.

Authors:  S C Noctor; S L Palmer; D F McLaughlin; S L Juliano
Journal:  J Neurosci       Date:  2001-05-01       Impact factor: 6.167

10.  Neural networks and physical systems with emergent collective computational abilities.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1982-04       Impact factor: 11.205

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  3 in total

Review 1.  Learning to predict through adaptation.

Authors:  Alessandro Treves
Journal:  Neuroinformatics       Date:  2004

2.  Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks.

Authors:  Marijn B Martens; Arthur R Houweling; Paul H E Tiesinga
Journal:  J Comput Neurosci       Date:  2016-11-04       Impact factor: 1.621

3.  Representing where along with what information in a model of a cortical patch.

Authors:  Yasser Roudi; Alessandro Treves
Journal:  PLoS Comput Biol       Date:  2008-03-21       Impact factor: 4.475

  3 in total

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