scholarly journals Clustered Organization of Neurons with Similar Extra-Receptive Field Properties in the Primary Visual Cortex

Neuron ◽  
2002 ◽  
Vol 35 (3) ◽  
pp. 547-553 ◽  
Author(s):  
Haishan Yao ◽  
Chao-Yi Li
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Receptive Field Properties

scholarly journals Replicating Receptive Fields of Simple and Complex Cells in Primary Visual Cortex in a Neuronal Network Model with Temporal and Population Sparseness and Reliability

2012 ◽  
Vol 24 (10) ◽  
pp. 2700-2725 ◽  
Author(s):  
Takuma Tanaka ◽  
Toshio Aoyagi ◽  
Takeshi Kaneko
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Learning Rule ◽  
Simple Cell ◽  
Complex Cells ◽  
Receptive Field Properties ◽  
Output Neurons ◽  
Simple And Complex Cells

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

scholarly journals Scale-invariance of receptive field properties in primary visual cortex

2007 ◽  
Vol 8 (1) ◽  
Author(s):  
Tobias Teichert ◽  
Thomas Wachtler ◽  
Frank Michler ◽  
Alexander Gail ◽  
Reinhard Eckhorn
Keyword(s):  
Visual Cortex ◽  
Receptive Field ◽  
Primary Visual Cortex ◽  
Scale Invariance ◽  
Receptive Field Properties
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