Literature DB >> 14580117

Complex receptive fields in primary visual cortex.

Luis M Martinez1, Jose-Manuel Alonso.   

Abstract

In the early 1960s, Hubel and Wiesel reported the first physiological description of cells in cat primary visual cortex. They distinguished two main cell types: simple cells and complex cells. Based on their distinct response properties, they suggested that the two cell types could represent two consecutive stages in receptive-field construction. Since the 1960s, new experimental and computational evidence provided serious alternatives to this hierarchical model. Parallel models put forward the idea that both simple and complex receptive fields could be built in parallel by direct geniculate inputs. Recurrent models suggested that simple cells and complex cells may not be different cell types after all. To this day, a consensus among hierarchical, parallel, and recurrent models has been difficult to attain; however, the circuitry used by all models is becoming increasingly similar. The authors review theoretical and experimental evidence for each line of models emphasizing their strengths and weaknesses.

Mesh:

Year:  2003        PMID: 14580117      PMCID: PMC2556291          DOI: 10.1177/1073858403252732

Source DB:  PubMed          Journal:  Neuroscientist        ISSN: 1073-8584            Impact factor:   7.519


  162 in total

1.  Physiological and morphological properties of identified basket cells in the cat's visual cortex.

Authors:  K A Martin; P Somogyi; D Whitteridge
Journal:  Exp Brain Res       Date:  1983       Impact factor: 1.972

2.  An intracellular analysis of geniculo-cortical connectivity in area 17 of the cat.

Authors:  D Ferster; S Lindström
Journal:  J Physiol       Date:  1983-09       Impact factor: 5.182

3.  Organization of cat visual cortex as investigated by cross-correlation technique.

Authors:  K Toyama; M Kimura; K Tanaka
Journal:  J Neurophysiol       Date:  1981-08       Impact factor: 2.714

4.  Cross-Correlation Analysis of Interneuronal Connectivity in cat visual cortex.

Authors:  K Toyama; M Kimura; K Tanaka
Journal:  J Neurophysiol       Date:  1981-08       Impact factor: 2.714

5.  Activity of cells in area 17 of the cat in absence of input from layer a of lateral geniculate nucleus.

Authors:  J G Malpeli
Journal:  J Neurophysiol       Date:  1983-03       Impact factor: 2.714

6.  Cross-correlation analysis of geniculostriate neuronal relationships in cats.

Authors:  K Tanaka
Journal:  J Neurophysiol       Date:  1983-06       Impact factor: 2.714

7.  Comparison of response of properties of three types of monosynaptic S-cell in cat striate cortex.

Authors:  M J Mustari; J Bullier; G H Henry
Journal:  J Neurophysiol       Date:  1982-03       Impact factor: 2.714

8.  Receptive-field transformations between LGN neurons and S-cells of cat-striate cortex.

Authors:  J Bullier; M J Mustari; G H Henry
Journal:  J Neurophysiol       Date:  1982-03       Impact factor: 2.714

9.  Spatial frequency selectivity of cells in macaque visual cortex.

Authors:  R L De Valois; D G Albrecht; L G Thorell
Journal:  Vision Res       Date:  1982       Impact factor: 1.886

10.  Receptive field organization of complex cells in cat striate cortex.

Authors:  P Heggelund
Journal:  Exp Brain Res       Date:  1981       Impact factor: 1.972

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  25 in total

Review 1.  Mapping receptive fields in primary visual cortex.

Authors:  Dario L Ringach
Journal:  J Physiol       Date:  2004-05-21       Impact factor: 5.182

2.  Visual object categorization in birds and primates: integrating behavioral, neurobiological, and computational evidence within a "general process" framework.

Authors:  Fabian A Soto; Edward A Wasserman
Journal:  Cogn Affect Behav Neurosci       Date:  2012-03       Impact factor: 3.282

3.  Dependence of visual cell properties on intracortical synapses among hypercolumns: analysis by a computer model.

Authors:  Mauro Ursino; Giuseppe-Emiliano La Cara
Journal:  J Comput Neurosci       Date:  2005-12       Impact factor: 1.621

4.  Laminar diversity of dynamic sound processing in cat primary auditory cortex.

Authors:  Craig A Atencio; Christoph E Schreiner
Journal:  J Neurophysiol       Date:  2009-10-28       Impact factor: 2.714

5.  From receptive profiles to a metric model of V1.

Authors:  Noemi Montobbio; Giovanna Citti; Alessandro Sarti
Journal:  J Comput Neurosci       Date:  2019-04-12       Impact factor: 1.621

Review 6.  The development of vision between nature and nurture: clinical implications from visual neuroscience.

Authors:  Giulia Purpura; Francesca Tinelli
Journal:  Childs Nerv Syst       Date:  2020-03-05       Impact factor: 1.475

7.  Feed-forward hierarchical model of the ventral visual stream applied to functional brain image classification.

Authors:  David B Keator; James H Fallon; Anita Lakatos; Charless C Fowlkes; Steven G Potkin; Alexander Ihler
Journal:  Hum Brain Mapp       Date:  2012-07-30       Impact factor: 5.038

8.  Neural computation of visual imaging based on Kronecker product in the primary visual cortex.

Authors:  Zhao Songnian; Zou Qi; Jin Zhen; Yao Guozheng; Yao Li
Journal:  BMC Neurosci       Date:  2010-03-26       Impact factor: 3.288

9.  Projection-Specific Visual Feature Encoding by Layer 5 Cortical Subnetworks.

Authors:  Gyorgy Lur; Martin A Vinck; Lan Tang; Jessica A Cardin; Michael J Higley
Journal:  Cell Rep       Date:  2016-03-10       Impact factor: 9.423

10.  A computational theory of visual receptive fields.

Authors:  Tony Lindeberg
Journal:  Biol Cybern       Date:  2013-11-07       Impact factor: 2.086

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