An Incremental Hebbian Learning Model of the Primary Visual Cortex with Lateral Plasticity and Real Input Patterns

We present a simplified binocular neural network model of the primary visual cortex with separate ON/OFF-pathways and modifiable afferent as well as intracortical synaptic couplings. Random as well as natural image stimuli drive the weight adaptation which follows Hebbian learning rules stabilized with constant norm and constant sum constraints. The simulations consider the development of orientation and ocular dominance maps under different conditions concerning stimulus patterns and lateral couplings. With random input patterns realistic orientation maps with ± 1/2-vortices mostly develop and plastic lateral couplings self-organize into mexican hat type structures on average. Using natural greyscale images as input patterns, realistic orientation maps develop as well and the lateral coupling profiles of the cortical neurons represent the two point correlations of the input image used

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Influence of Lateral Connections on the Structure of Cortical Maps

Journal of Neurophysiology ◽

10.1152/jn.00281.2004 ◽

2004 ◽

Vol 92 (5) ◽

pp. 2947-2959 ◽

Cited By ~ 30

Author(s):

Miguel Á. Carreira-Perpiñán ◽

Geoffrey J. Goodhill

Keyword(s):

Visual Cortex ◽

Computational Model ◽

Primary Visual Cortex ◽

Short Range ◽

Ocular Dominance ◽

Characteristic Structure ◽

Interaction Function ◽

Mexican Hat ◽

Visual Cortical ◽

Cortical Map

Maps of ocular dominance and orientation in primary visual cortex have a highly characteristic structure. The factors that determine this structure are still largely unknown. In particular, it is unclear how short-range excitatory and inhibitory connections between nearby neurons influence structure both within and between maps. Using a generalized version of a well-known computational model of visual cortical map development, we show that the number of excitatory and inhibitory oscillations in this interaction function critically influences map structure. Specifically, we demonstrate that functions that oscillate more than once do not produce maps closely resembling those seen biologically. This strongly suggests that local lateral connections in visual cortex oscillate only once and have the form of a Mexican hat.

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Elastic Net Model of Ocular Dominance: Overall Stripe Pattern and Monocular Deprivation

Neural Computation ◽

10.1162/neco.1994.6.4.615 ◽

1994 ◽

Vol 6 (4) ◽

pp. 615-621 ◽

Cited By ~ 29

Author(s):

Geoffrey J. Goodhill ◽

David J. Willshaw

Keyword(s):

Visual Cortex ◽

Lateral Geniculate Nucleus ◽

Primary Visual Cortex ◽

Ocular Dominance ◽

Monocular Deprivation ◽

Elastic Net ◽

Global Order ◽

Stripe Pattern ◽

Lateral Geniculate ◽

Stripe Width

The elastic net (Durbin and Willshaw 1987) can account for the development of both topography and ocular dominance in the mapping from the lateral geniculate nucleus to primary visual cortex (Goodhill and Willshaw 1990). Here it is further shown for this model that (1) the overall pattern of stripes produced is strongly influenced by the shape of the cortex: in particular, stripes with a global order similar to that seen biologically can be produced under appropriate conditions, and (2) the observed changes in stripe width associated with monocular deprivation are reproduced in the model.

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Homeostatic plasticity mechanisms in mouse V1

Philosophical Transactions of the Royal Society B Biological Sciences ◽

10.1098/rstb.2016.0504 ◽

2017 ◽

Vol 372 (1715) ◽

pp. 20160504 ◽

Cited By ~ 10

Author(s):

Megumi Kaneko ◽

Michael P. Stryker

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Neuronal Activity ◽

Dynamic Range ◽

Ocular Dominance ◽

Homeostatic Plasticity ◽

Ocular Dominance Plasticity ◽

The Brain

Mechanisms thought of as homeostatic must exist to maintain neuronal activity in the brain within the dynamic range in which neurons can signal. Several distinct mechanisms have been demonstrated experimentally. Three mechanisms that act to restore levels of activity in the primary visual cortex of mice after occlusion and restoration of vision in one eye, which give rise to the phenomenon of ocular dominance plasticity, are discussed. The existence of different mechanisms raises the issue of how these mechanisms operate together to converge on the same set points of activity. This article is part of the themed issue ‘Integrating Hebbian and homeostatic plasticity’.

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Postnatal Development of Onset Transient Responses in Macaque V1 and V2 Neurons

Journal of Neurophysiology ◽

10.1152/jn.90446.2008 ◽

2008 ◽

Vol 100 (3) ◽

pp. 1476-1487 ◽

Cited By ~ 11

Author(s):

Bin Zhang ◽

Earl L. Smith ◽

Yuzo M. Chino

Keyword(s):

Visual Cortex ◽

Eye Movements ◽

Primary Visual Cortex ◽

Cortical Neurons ◽

Newborn Infants ◽

Neuronal Firing ◽

Transient Responses ◽

Visual Cortical ◽

Better Than

Vision of newborn infants is limited by immaturities in their visual brain. In adult primates, the transient onset discharges of visual cortical neurons are thought to be intimately involved with capturing the rapid succession of brief images in visual scenes. Here we sought to determine the responsiveness and quality of transient responses in individual neurons of the primary visual cortex (V1) and visual area 2 (V2) of infant monkeys. We show that the transient component of neuronal firing to 640-ms stationary gratings was as robust and as reliable as in adults only 2 wk after birth, whereas the sustained component was more sluggish in infants than in adults. Thus the cortical circuitry supporting onset transient responses is functionally mature near birth, and our findings predict that neonates, known for their “impoverished vision,” are capable of initiating relatively mature fixating eye movements and of performing in detection of simple objects far better than traditionally thought.

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Spatial Distribution of Contextual Interactions in Primary Visual Cortex and in Visual Perception

Journal of Neurophysiology ◽

10.1152/jn.2000.84.4.2048 ◽

2000 ◽

Vol 84 (4) ◽

pp. 2048-2062 ◽

Cited By ~ 198

Author(s):

Mitesh K. Kapadia ◽

Gerald Westheimer ◽

Charles D. Gilbert

Keyword(s):

Spatial Distribution ◽

Visual Cortex ◽

Primary Visual Cortex ◽

Cortical Neurons ◽

Receptive Fields ◽

Human Perception ◽

Spatial Arrangement ◽

Orthogonal Axis ◽

V1 Neurons ◽

Contextual Interactions

To examine the role of primary visual cortex in visuospatial integration, we studied the spatial arrangement of contextual interactions in the response properties of neurons in primary visual cortex of alert monkeys and in human perception. We found a spatial segregation of opposing contextual interactions. At the level of cortical neurons, excitatory interactions were located along the ends of receptive fields, while inhibitory interactions were strongest along the orthogonal axis. Parallel psychophysical studies in human observers showed opposing contextual interactions surrounding a target line with a similar spatial distribution. The results suggest that V1 neurons can participate in multiple perceptual processes via spatially segregated and functionally distinct components of their receptive fields.

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Orientation Tuning, But Not Direction Selectivity, Is Invariant to Temporal Frequency in Primary Visual Cortex

Journal of Neurophysiology ◽

10.1152/jn.01224.2004 ◽

2005 ◽

Vol 94 (2) ◽

pp. 1336-1345 ◽

Cited By ~ 21

Author(s):

Bartlett D. Moore ◽

Henry J. Alitto ◽

W. Martin Usrey

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Visual Stimulus ◽

Visual Processing ◽

Cortical Neurons ◽

Temporal Frequency ◽

Direction Selectivity ◽

Orientation Tuning ◽

Orientation Contrast ◽

Wide Range

The activity of neurons in primary visual cortex is influenced by the orientation, contrast, and temporal frequency of a visual stimulus. This raises the question of how these stimulus properties interact to shape neuronal responses. While past studies have shown that the bandwidth of orientation tuning is invariant to stimulus contrast, the influence of temporal frequency on orientation-tuning bandwidth is unknown. Here, we investigate the influence of temporal frequency on orientation tuning and direction selectivity in area 17 of ferret visual cortex. For both simple cells and complex cells, measures of orientation-tuning bandwidth (half-width at half-maximum response) are ∼20–25° across a wide range of temporal frequencies. Thus cortical neurons display temporal-frequency invariant orientation tuning. In contrast, direction selectivity is typically reduced, and occasionally reverses, at nonpreferred temporal frequencies. These results show that the mechanisms contributing to the generation of orientation tuning and direction selectivity are differentially affected by the temporal frequency of a visual stimulus and support the notion that stability of orientation tuning is an important aspect of visual processing.

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Self-Organization of Local Cortical Circuits and Cortical Orientation Maps: A Nonlinear Hebbian Model of the Visual Cortex with Adaptive Lateral Couplings

Zeitschrift für Naturforschung C ◽

10.1515/znc-2001-5-622 ◽

2001 ◽

Vol 56 (5-6) ◽

pp. 464-478 ◽

Cited By ~ 1

Author(s):

Thomas Burger ◽

Wolfgang Lang

Keyword(s):

Neural Network ◽

Visual Cortex ◽

Recurrent Neural Network ◽

Neural Network Model ◽

Self Organization ◽

Cortical Circuits ◽

Random Input ◽

Intracortical Circuits ◽

Orientation Maps ◽

Lateral Coupling

A nonlinear, recurrent neural network model of the visual cortex is presented. Orientation maps emerge from adaptable afferent as well as plastic local intracortical circuits driven by random input stimuli. Lateral coupling structures self-organize into DOG profiles under the influence of pronounced emerging cortical activity blobs. The model’s simplified architecture and features are modeled to largely mimik neurobiological findings.

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Relationship between the Ocular Dominance and Orientation Maps in Visual Cortex of Monocularly Deprived Cats

Neuron ◽

10.1016/s0896-6273(00)80941-1 ◽

1997 ◽

Vol 19 (2) ◽

pp. 307-318 ◽

Cited By ~ 64

Author(s):

Michael C Crair ◽

Edward S Ruthazer ◽

Deda C Gillespie ◽

Michael P Stryker

Keyword(s):

Visual Cortex ◽

Ocular Dominance ◽

Orientation Maps

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Learning Invariance from Natural Images Inspired by Observations in the Primary Visual Cortex

Neural Computation ◽

10.1162/neco_a_00268 ◽

2012 ◽

Vol 24 (5) ◽

pp. 1271-1296 ◽

Cited By ~ 5

Author(s):

Michael Teichmann ◽

Jan Wiltschut ◽

Fred Hamker

Keyword(s):

Visual Cortex ◽

Primary Visual Cortex ◽

Hebbian Learning ◽

Natural Images ◽

Complex Cells ◽

Cell Responses ◽

Feature Detectors ◽

Learning Rules ◽

Static Images ◽

Good Interpretation

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

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