Literature DB >> 17715598

How does the cerebral cortex work? Development, learning, attention, and 3-D vision by laminar circuits of visual cortex.

Stephen Grossberg1.   

Abstract

A key goal of behavioral and cognitive neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress toward explaining how the visual cortex sees. Visual cortex, like many parts of perceptual and cognitive neocortex, is organized into six main layers of cells, as well as characteristic sublamina. Here it is proposed how these layered circuits help to realize processes of development, learning, perceptual grouping, attention, and 3-D vision through a combination of bottom-up, horizontal, and top-down interactions. A main theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. These results thus begin to unify three fields: infant cortical development, adult cortical neurophysiology and anatomy, and adult visual perception. The identified cortical mechanisms promise to generalize to explain how other perceptual and cognitive processes work.

Entities:  

Mesh:

Year:  2003        PMID: 17715598     DOI: 10.1177/1534582303002001003

Source DB:  PubMed          Journal:  Behav Cogn Neurosci Rev        ISSN: 1534-5823


  15 in total

1.  Running as fast as it can: how spiking dynamics form object groupings in the laminar circuits of visual cortex.

Authors:  Jasmin Léveillé; Massimiliano Versace; Stephen Grossberg
Journal:  J Comput Neurosci       Date:  2010-01-29       Impact factor: 1.621

2.  Binocular fusion and invariant category learning due to predictive remapping during scanning of a depthful scene with eye movements.

Authors:  Stephen Grossberg; Karthik Srinivasan; Arash Yazdanbakhsh
Journal:  Front Psychol       Date:  2015-01-14

Review 3.  Cortical and subcortical predictive dynamics and learning during perception, cognition, emotion and action.

Authors:  Stephen Grossberg
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2009-05-12       Impact factor: 6.237

4.  A network approach to assessing cognition in disorders of consciousness.

Authors:  D Rodriguez Moreno; N D Schiff; J Giacino; K Kalmar; J Hirsch
Journal:  Neurology       Date:  2010-10-27       Impact factor: 9.910

5.  A neural model of normal and abnormal learning and memory consolidation: adaptively timed conditioning, hippocampus, amnesia, neurotrophins, and consciousness.

Authors:  Daniel J Franklin; Stephen Grossberg
Journal:  Cogn Affect Behav Neurosci       Date:  2017-02       Impact factor: 3.282

6.  After-hyperpolarization currents and acetylcholine control sigmoid transfer functions in a spiking cortical model.

Authors:  Jesse Palma; Massimiliano Versace; Stephen Grossberg
Journal:  J Comput Neurosci       Date:  2011-07-21       Impact factor: 1.621

7.  Computational aspects of feedback in neural circuits.

Authors:  Wolfgang Maass; Prashant Joshi; Eduardo D Sontag
Journal:  PLoS Comput Biol       Date:  2006-10-24       Impact factor: 4.475

8.  From Grouping to Coupling: A New Perceptual Organization in Vision, Psychology, and Biology.

Authors:  Baingio Pinna; Daniele Porcheddu; Katia Deiana
Journal:  Front Psychol       Date:  2016-07-14

9.  A stable biologically motivated learning mechanism for visual feature extraction to handle facial categorization.

Authors:  Karim Rajaei; Seyed-Mahdi Khaligh-Razavi; Masoud Ghodrati; Reza Ebrahimpour; Mohammad Ebrahim Shiri Ahmad Abadi
Journal:  PLoS One       Date:  2012-06-13       Impact factor: 3.240

10.  Laminar Neural Field Model of Laterally Propagating Waves of Orientation Selectivity.

Authors:  Paul C Bressloff; Samuel R Carroll
Journal:  PLoS Comput Biol       Date:  2015-10-22       Impact factor: 4.475

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