Conformal Model of Hypercolumns in V1 Cortex and the Möbius Group. Application to the Visual Stability Problem
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62690094%3A18470%2F21%3A50018349" target="_blank" >RIV/62690094:18470/21:50018349 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/content/pdf/10.1007%2F978-3-030-80209-7.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007%2F978-3-030-80209-7.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-80209-7_8" target="_blank" >10.1007/978-3-030-80209-7_8</a>
Alternative languages
Result language
angličtina
Original language name
Conformal Model of Hypercolumns in V1 Cortex and the Möbius Group. Application to the Visual Stability Problem
Original language description
A conformal spherical model of hypercolumns of primary visual cortex V1 is proposed. It is a modification of the Bressloff-Cowan Riemannian spherical model. The main assumption is that simple neurons of a hypercolumn, considered as Gabor filters, obtained for the mother Gabor filter by transformations from the Möbius group Sl(2, C). It is shown that in a small neighborhood of a pinwheel, which is responsible for detection of high (resp., low) frequency stimuli, it reduces to the Sarti-Citti-Petitot symplectic model of V1 cortex. Application to the visual stability problem is discussed. © 2021, Springer Nature Switzerland AG.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10102 - Applied mathematics
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISBN
978-3-030-80208-0
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
8
Pages from-to
65-72
Publisher name
Springer Science and Business Media Deutschland GmbH
Place of publication
Paríž
Event location
Paríž
Event date
Jun 21, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000709366400010