Laminar Development of Receptive Fields, Maps and Columns in Visual Cortex: The Coordinating Role of the Subplate

Correlation-based learning (CBL) has been suggested as the mechanism that underlies the development of simple-cell receptive fields in the primary visual cortex of cats, including orientation preference (OR) and ocular dominance (OD) (Linsker, 1986; Miller, Keller, & Stryker, 1989). CBL has been applied successfully to the development of OR and OD individually (Miller, Keller, & Stryker, 1989; Miller, 1994; Miyashita & Tanaka, 1991; Erwin, Obermayer, & Schulten, 1995), but the conditions for their joint development have not been studied (but see Erwin & Miller, 1995, for independent work on the same question) in contrast to competitive Hebbian models (Obermayer, Blasdel, & Schulten, 1992). In this article, we provide insight into why this has been the case: OR and OD decouple in symmetric CBL models, and a joint development of OR and OD is possible only in a parameter regime that depends on nonlinear mechanisms.

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A Ring Model for Direction-Selective Simple Cells in the Visual Cortex

Perception ◽

10.1068/v970164 ◽

1997 ◽

Vol 26 (1_suppl) ◽

pp. 164-164

Author(s):

T Hamada ◽

K Kato ◽

M Yamashima

Keyword(s):

Visual Cortex ◽

Experimental Studies ◽

Receptive Fields ◽

Lateral Geniculate Body ◽

Neural Model ◽

Cortical Cells ◽

Simple Cells ◽

Ring Model ◽

Gabor Functions

Experimental studies have shown that (1) direction-selective simple cells in the visual cortex have spatiotemporally inseparable receptive fields, whose spatial profiles at a given time are described by Gabor functions: a sinusoid multiplied by a Gaussian, with a phase parameter; (2) among simple cells, the phases are distributed not merely at 0 and pi/2 as for sine and cosine Gabor functions, but uniformly between 0 and 2pi (DeAngelis et al, 1993 Journal of Neurophysiology69 1091 – 1117); (3) anatomically, these simple cells receive inputs more from other cortical cells than from the lateral geniculate body (LGN) (Ahmed et al, 1994 Journal of Comparative Neurology341 39 – 49). We accordingly propose here a neural model for the simple cells whose receptive fields are assumed to be of the same spatial position and orientation. In the model, several cortical cells are arranged in a ring with mutual excitatory and inhibitory connections, and receive afferent signals from lagged and nonlagged cells in LGN (Saul and Humphrey, 1990 Journal of Neurophysiology64 206 – 224). Computer simulation shows that the cortical cells have spatiotemporally inseparable receptive fields with spatial profiles described by Gabor functions, and are directionally selective to a moving grating. The cells are found to be arranged so that their Gabor phases vary regularly from 0 to 2pi with rotation along the ring. The connection among the cortical cells has a role of amplification as in the canonical microcircuit model (Douglas et al, 1989 Neural Computation1 480 – 488).

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One-generation Lamarckism: The role of environment in genetic development

Behavioral and Brain Sciences ◽

10.1017/s0140525x07002257 ◽

2007 ◽

Vol 30 (4) ◽

pp. 367-368 ◽

Cited By ~ 1

Author(s):

Bruce Bridgeman

Keyword(s):

Visual Cortex ◽

Receptive Fields ◽

Environmental Information ◽

Genetic Development

AbstractEnvironment can provide information used in development – information that can appear to be genetically given and that was previously assumed to be so. Examples include growth of the eye until it achieves good focus, and structuring of receptive fields in the visual cortex by environmental information. The process can be called one-generation Lamarckism because information acquired from the environment is used to structure the organism and because the capacity to acquire this information is inherited.

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Receptive Fields of Dendritic Potentials from Within the Visual Cortex of the Cat

PsycEXTRA Dataset ◽

10.1037/e469432008-086 ◽

1965 ◽

Author(s):

John A. Satterberg ◽

Leo Ganz

Keyword(s):

Visual Cortex ◽

Receptive Fields

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The Effect of Dynamic Synapses on Spatio-temporal Receptive Fields in Visual Cortex

10.21236/ada333497 ◽

1997 ◽

Author(s):

Omer B. Artun ◽

Harel Z. Shouval ◽

Leon N. Cooper

Keyword(s):

Visual Cortex ◽

Receptive Fields ◽

Dynamic Synapses ◽

Spatio Temporal

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The role of activity in corpus callosum development in the visual cortex

9th International Conference on Artificial Neural Networks: ICANN '99 ◽

10.1049/cp:19991144 ◽

1999 ◽

Author(s):

T. Hely

Keyword(s):

Visual Cortex ◽

Corpus Callosum

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Adaptive Integration in the Visual Cortex by Depressing Recurrent Cortical Circuits

Neural Computation ◽

10.1162/neco.2008.06-07-546 ◽

2008 ◽

Vol 20 (7) ◽

pp. 1847-1872 ◽

Cited By ~ 24

Author(s):

Mark C. W. van Rossum ◽

Matthijs A. A. van der Meer ◽

Dengke Xiao ◽

Mike W. Oram

Keyword(s):

Visual Cortex ◽

Physiological Data ◽

High Contrast ◽

Cortical Circuits ◽

Response Latencies ◽

Low Contrast ◽

Visual Areas ◽

Higher Visual Areas ◽

Recurrent Connections

Neurons in the visual cortex receive a large amount of input from recurrent connections, yet the functional role of these connections remains unclear. Here we explore networks with strong recurrence in a computational model and show that short-term depression of the synapses in the recurrent loops implements an adaptive filter. This allows the visual system to respond reliably to deteriorated stimuli yet quickly to high-quality stimuli. For low-contrast stimuli, the model predicts long response latencies, whereas latencies are short for high-contrast stimuli. This is consistent with physiological data showing that in higher visual areas, latencies can increase more than 100 ms at low contrast compared to high contrast. Moreover, when presented with briefly flashed stimuli, the model predicts stereotypical responses that outlast the stimulus, again consistent with physiological findings. The adaptive properties of the model suggest that the abundant recurrent connections found in visual cortex serve to adapt the network's time constant in accordance with the stimulus and normalizes neuronal signals such that processing is as fast as possible while maintaining reliability.

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