Vertical meridian representation on the prelunate gyrus in area V4 of macaque

2001 ◽  
Vol 56 (2) ◽  
pp. 93-100 ◽  
Author(s):  
M. Youakim ◽  
D.B. Bender ◽  
J.S. Baizer
Keyword(s):  
Vertical Meridian ◽  
Area V4 ◽  
Prelunate Gyrus

DECODING GRATING ORIENTATION FROM MICROELECTRODE ARRAY RECORDINGS IN MONKEY CORTICAL AREA V4

2010 ◽  
Vol 20 (02) ◽  
pp. 95-108 ◽  
Author(s):  
NIKOLAY V. MANYAKOV ◽  
MARC M. VAN HULLE
Keyword(s):  
Feature Selection ◽  
Microelectrode Array ◽  
Pyramidal Cells ◽  
Support Vector ◽  
Selection Procedures ◽  
Linear Discriminant ◽  
Area V4 ◽  
Prelunate Gyrus ◽  
Machine Interface ◽  
Selection Algorithms

We propose an invasive brain-machine interface (BMI) that decodes the orientation of a visual grating from spike train recordings made with a 96 microelectrodes array chronically implanted into the prelunate gyrus (area V4) of a rhesus monkey. The orientation is decoded irrespective of the grating's spatial frequency. Since pyramidal cells are less prominent in visual areas, compared to (pre)motor areas, the recordings contain spikes with smaller amplitudes, compared to the noise level. Hence, rather than performing spike decoding, feature selection algorithms are applied to extract the required information for the decoder. Two types of feature selection procedures are compared, filter and wrapper. The wrapper is combined with a linear discriminant analysis classifier, and the filter is followed by a radial-basis function support vector machine classifier. In addition, since we have a multiclass classification problen, different methods for combining pairwise classifiers are compared.

scholarly journals Laminar microcircuitry of visual cortex producing attention-associated electric fields

2021 ◽  
Author(s):  
Jacob A. Westerberg ◽  
Michelle S. Schall ◽  
Alexander Maier ◽  
Geoffrey F. Woodman ◽  
Jeffrey D. Schall
Keyword(s):  
Electric Field ◽  
Electric Fields ◽  
Synaptic Activity ◽  
Cortical Layers ◽  
Functional Architecture ◽  
Attention Task ◽  
Area V4 ◽  
Relative Contribution ◽  
Visual Cortical Area ◽  
Prelunate Gyrus

AbstractCognitive operations are widely studied by measuring electric fields through EEG and ECoG. However, despite their widespread use, the component neural circuitry giving rise to these signals remains unknown. Specifically, the functional architecture of cortical columns which results in attention-associated electric fields has not been explored. Here we detail the laminar cortical circuitry underlying an attention-associated electric field often measured over posterior regions of the brain in humans and monkeys. First, we identified visual cortical area V4 as one plausible contributor to this attention-associated electric field through inverse modeling of cranial EEG in macaque monkeys performing a visual attention task. Next, we performed laminar neurophysiological recordings on the prelunate gyrus and identified the electric-field-producing dipoles as synaptic activity in distinct cortical layers of area V4. Specifically, activation in the extragranular layers of cortex resulted in the generation of the attention-associated dipole. Feature selectivity of a given cortical column determined the overall contribution to this electric field. Columns selective for the attended feature contributed more to the electric field than columns selective for a different feature. Lastly, the laminar profile of synaptic activity generated by V4 was sufficient to produce an attention-associated signal measurable outside of the column. These findings suggest that the top-down recipient cortical layers produce an attention-associated electric field capable of being measured extracranially and the relative contribution of each column depends upon the underlying functional architecture.

Is there a high concentration of color-selective cells in area V4 of monkey visual cortex?

1982 ◽  
Vol 47 (2) ◽  
pp. 193-213 ◽  
Author(s):  
S. J. Schein ◽  
R. T. Marrocco ◽  
F. M. de Monasterio
Keyword(s):  
Visual Cortex ◽  
Central Field ◽  
High Concentration ◽  
Field Representation ◽  
Area V4 ◽  
Area V2 ◽  
Sufficient Detail ◽  
Prelunate Gyrus ◽  
Color Selectivity ◽  
Monkey Visual Cortex

1. Recordings were made from neurons located within the central-field representation of the V4 area of extrastriate visual cortex using a semichronic, nitrous-oxide preparation; the properties of 174 cells were examined in sufficient detail to permit their classification. Cyto- and myeloarchitectural studies confirmed the identification of the area. 2. Color-selective cells with either color-biased or color-opponent properties represented about 20% of the examined population. Their incidence was not significantly different from that of similar cells encountered in penetrations into the central-field representation of area V2. 3. Most color-selective cells had color-biased properties, responding best to wave-lengths shorter than 460 nm, or longer than 580 n, or both. No examples of "green-biased" cells were found. Some color-biased cells responded to photopically matched white light, while others did not. Very few cells showed overt color-opponent responses. The spectral sensitivity of color-selective cells was not unusually narrow. 4. Cells lacking color selectivity and responding equally well to chromatic and achromatic lights of equal photopic luminosity, were the most commonly encountered cell type in penetrations of different parts of the V4 area (56%). Other than color, these cells showed stimulus preferences like those of color-selective cells. 5. One-fourth of V4 cells could not be systematically driven with the various stimuli used. This finding is consistent with recent results of recordings from the prelunate gyrus of the behaving monkey suggesting that some V4 cells receive extraretinal signals. 6. Our results do not support recent claims that V4 is specialized in the detailed analysis of color information.

scholarly journals The Correlations between Horizontal and Vertical Peripheral Refractions and Human Eye Shape Using Magnetic Resonance Imaging in Highly Myopic Eyes

Healthcare ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 966
Author(s):  
Hui-Ying Kuo ◽  
John Ching-Jen Hsiao ◽  
Jing-Jie Chen ◽  
Chi-Hung Lee ◽  
Chun-Chao Chuang ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Shape Deformation ◽  
Spherical Equivalent ◽  
Horizontal Meridian ◽  
Resonance Imaging ◽  
Vertical Meridian ◽  
Useful Knowledge ◽  
Human Eye ◽  
The Relationship

The aim of this study was to determine the relationship between relative peripheral refraction and retinal shape by 2-D magnetic resonance imaging in high myopes. Thirty-five young adults aged 20 to 30 years participated in this study with 16 high myopes (spherical equivalent < −6.00 D) and 19 emmetropes (+0.50 to −0.50 D). An open field autorefractor was used to measure refractions from the center out to 60° in the horizontal meridian and out to around 20° in the vertical meridian, with a step of 3 degrees. Axial length was measured by using A-scan ultrasonography. In addition, images of axial, sagittal, and tangential sections were obtained using 2-D magnetic resonance imaging. The highly myopic group had a significantly relative peripheral hyperopic refraction and showed a prolate ocular shape compared to the emmetropic group. The highly myopic group had relative peripheral hyperopic refraction and showed a prolate ocular form. Significant differences in the ratios of height/axial (1.01 ± 0.02 vs. 0.94 ± 0.03) and width/axial (0.99 ± 0.17 vs. 0.93 ± 0.04) were found from the MRI images between the emmetropic and the highly myopic eyes (p < 0.001). There was a negative correlation between the retina’s curvature and relative peripheral refraction for both temporal (Pearson r = −0.459; p < 0.01) and nasal (Pearson r = −0.277; p = 0.011) retina. For the highly myopic eyes, the amount of peripheral hyperopic defocus is correlated to its ocular shape deformation. This could be the first study investigating the relationship between peripheral refraction and ocular dimension in high myopes, and it is hoped to provide useful knowledge of how the development of myopia changes human eye shape.

scholarly journals Rapid shape detection signals in area V4

2014 ◽  
Vol 8 ◽  
Author(s):  
Katherine F. Weiner ◽  
Geoffrey M. Ghose
Keyword(s):  
Shape Detection ◽  
Area V4
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