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Elements of neurogeometryfunctional ...
~
Petitot, Jean.
Elements of neurogeometryfunctional architectures of vision /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Elements of neurogeometryby Jean Petitot.
Reminder of title:
functional architectures of vision /
Author:
Petitot, Jean.
Published:
Cham :Springer International Publishing :2017.
Description:
xv, 379 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
Visual cortexMathematical models.
Online resource:
http://dx.doi.org/10.1007/978-3-319-65591-8
ISBN:
9783319655918$q(electronic bk.)
Elements of neurogeometryfunctional architectures of vision /
Petitot, Jean.
Elements of neurogeometry
functional architectures of vision /[electronic resource] :by Jean Petitot. - Cham :Springer International Publishing :2017. - xv, 379 p. :ill., digital ;24 cm. - Lecture notes in morphogenesis,2195-1934. - Lecture notes in morphogenesis..
Preface -- Introdcution -- Receptive Fields and Profiles, and Wavelet Analysis -- Pinwheels of V1 Horizontal Connections and Contact Structure -- Transition to Volume II -- References.
This book describes several mathematical models of the primary visual cortex, referring them to a vast ensemble of experimental data and putting forward an original geometrical model for its functional architecture, that is, the highly specific organization of its neural connections. The book spells out the geometrical algorithms implemented by this functional architecture, or put another way, the "neurogeometry" immanent in visual perception. Focusing on the neural origins of our spatial representations, it demonstrates three things: firstly, the way the visual neurons filter the optical signal is closely related to a wavelet analysis; secondly, the contact structure of the 1-jets of the curves in the plane (the retinal plane here) is implemented by the cortical functional architecture; and lastly, the visual algorithms for integrating contours from what may be rather incomplete sensory data can be modelled by the sub-Riemannian geometry associated with this contact structure. As such, it provides readers with the first systematic interpretation of a number of important neurophysiological observations in a well-defined mathematical framework. The book's neuromathematical exploration appeals to graduate students and researchers in integrative-functional-cognitive neuroscience with a good mathematical background, as well as those in applied mathematics with an interest in neurophysiology.
ISBN: 9783319655918$q(electronic bk.)
Standard No.: 10.1007/978-3-319-65591-8doiSubjects--Topical Terms:
797580
Visual cortex
--Mathematical models.
LC Class. No.: QP383
Dewey Class. No.: 510
Elements of neurogeometryfunctional architectures of vision /
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This book describes several mathematical models of the primary visual cortex, referring them to a vast ensemble of experimental data and putting forward an original geometrical model for its functional architecture, that is, the highly specific organization of its neural connections. The book spells out the geometrical algorithms implemented by this functional architecture, or put another way, the "neurogeometry" immanent in visual perception. Focusing on the neural origins of our spatial representations, it demonstrates three things: firstly, the way the visual neurons filter the optical signal is closely related to a wavelet analysis; secondly, the contact structure of the 1-jets of the curves in the plane (the retinal plane here) is implemented by the cortical functional architecture; and lastly, the visual algorithms for integrating contours from what may be rather incomplete sensory data can be modelled by the sub-Riemannian geometry associated with this contact structure. As such, it provides readers with the first systematic interpretation of a number of important neurophysiological observations in a well-defined mathematical framework. The book's neuromathematical exploration appeals to graduate students and researchers in integrative-functional-cognitive neuroscience with a good mathematical background, as well as those in applied mathematics with an interest in neurophysiology.
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EB QP383 .P491 2017 2017
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http://dx.doi.org/10.1007/978-3-319-65591-8
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