Comparative analysis of orientation maps in areas 17 and 18 of the cat primary visual cortex following adaptation

2014 ◽  
Vol 40 (3) ◽  
pp. 2554-2563 ◽  
Author(s):  
Sarah Cattan ◽  
Lyes Bachatene ◽  
Vishal Bharmauria ◽  
Jeyadarshan Jeyabalaratnam ◽  
Chantal Milleret ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Comparative Analysis ◽  
Primary Visual Cortex ◽  
Orientation Maps ◽  
Areas 17 And 18

scholarly journals Optimizing the Representation of Orientation Preference Maps in Visual Cortex

2015 ◽  
Vol 27 (1) ◽  
pp. 32-41
Author(s):  
Nicholas J. Hughes ◽  
Geoffrey J. Goodhill
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Color Space ◽  
Orientation Preference ◽  
Color Mapping ◽  
Functional Brain ◽  
Standard Representation ◽  
Visual Impression ◽  
Orientation Maps ◽  
True Structure

The colorful representation of orientation preference maps in primary visual cortex has become iconic. However, the standard representation is misleading because it uses a color mapping to indicate orientations based on the HSV (hue, saturation, value) color space, for which important perceptual features such as brightness, and not just hue, vary among orientations. This means that some orientations stand out more than others, conveying a distorted visual impression. This is particularly problematic for visualizing subtle biases caused by slight overrepresentation of some orientations due to, for example, stripe rearing. We show that displaying orientation maps with a color mapping based on a slightly modified version of the HCL (hue, chroma, lightness) color space, so that primarily only hue varies between orientations, leads to a more balanced visual impression. This makes it easier to perceive the true structure of this seminal example of functional brain architecture.

scholarly journals Functional organization of the primary visual cortex (areas 17 and 18) of the tree shrew revealed by optical brain imaging

2010 ◽  
Vol 9 (8) ◽  
pp. 770-770 ◽  
Author(s):  
M. Vanni ◽  
M. Villeneuve ◽  
M. Bickford ◽  
H. Petry ◽  
C. Casanova
Keyword(s):  
Visual Cortex ◽  
Brain Imaging ◽  
Primary Visual Cortex ◽  
Functional Organization ◽  
Tree Shrew ◽  
Areas 17 And 18

scholarly journals Lack of Patchy Horizontal Connectivity in Primary Visual Cortex of a Mammal without Orientation Maps

2006 ◽  
Vol 26 (29) ◽  
pp. 7680-7692 ◽  
Author(s):  
S. D. Van Hooser ◽  
J. A. Heimel ◽  
S. Chung ◽  
S. B. Nelson
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Orientation Maps

scholarly journals Functional implications of orientation maps in primary visual cortex

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Erin Koch ◽  
Jianzhong Jin ◽  
Jose M. Alonso ◽  
Qasim Zaidi
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Orientation Maps ◽  
Functional Implications

scholarly journals Mechanisms for Stable, Robust, and Adaptive Development of Orientation Maps in the Primary Visual Cortex

2013 ◽  
Vol 33 (40) ◽  
pp. 15747-15766 ◽  
Author(s):  
J.-L. R. Stevens ◽  
J. S. Law ◽  
J. Antolik ◽  
J. A. Bednar
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Orientation Maps ◽  
Adaptive Development

The role of ipsilateral and contralateral inputs from primary cortex in responses of area 21a neurons in cats

1994 ◽  
Vol 11 (5) ◽  
pp. 839-849 ◽  
Author(s):  
A. Michalski ◽  
B. M. Wimborne ◽  
G. H. Henry
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Tuning Curve ◽  
Excitatory Input ◽  
Direction Selectivity ◽  
Orientation Tuning ◽  
Inhibitory Input ◽  
Area 21A ◽  
Areas 17 And 18 ◽  
Orientation Specificity

AbstractNeuronal responses in cat visual area 21a were analyzed when the primary visual cortex (areas 17 and 18) was deactivated by cooling. Ipsilateral and contralateral cortices were deactivated separately. Results established that (1) cooling the ipsilateral primary cortex diminished the activity of all area 21a cells and, in 30%, blocked responsiveness altogether, and (2) cooling the contralateral primary cortex initially increased activity in area 21a cells but, with further cooling, reduced it to below the original level although only 9% of cells ceased responding. These findings were then compared to earlier results in which bilateral deactivation of the primary cortex greatly reduced and, in most cases, blocked the activity of area 21a cells (Michalski et al., 1993). Despite the response attenuation following cooling of the primary visual cortex (either ipsilateral or contralateral), neurons of area 21a retained their original orientation specificity and sharpness of tuning (measured as the half-width at half-height of the orientation tuning curve). Direction selectivity also tended to remain unchanged. We concluded that for area 21a cells (1) the ipsilateral primary cortex provides the main excitatory input; (2) the contralateral primary cortex supplies a large inhibitory input; and (3) the nature of orientation specificity, sharpness of orientation tuning, and direction selectivity are largely unaffected by removal of the ipsilateral hemisphere excitatory input or the contralateral hemisphere inhibitory input.

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

1999 ◽  
Vol 54 (1-2) ◽  
pp. 128-140 ◽  
Author(s):  
Thomas Burger ◽  
Elmar W. Lang
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Cortical Neurons ◽  
Hebbian Learning ◽  
Ocular Dominance ◽  
Input Image ◽  
Natural Image ◽  
Mexican Hat ◽  
Orientation Maps ◽  
Lateral Coupling

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

Sign in / Sign up

Export Citation Format

Share Document