Emergence of Functional Circuits in the Early Visual Pathway [electronic resource] / by Jaeson Jang, Se-Bum Paik.

By:

Jang, Jaeson [author.]

Contributor(s):

Material type: Text

TextLanguage: İngilizce Series: KAIST Research SeriesPublisher: Singapore : Springer Nature Singapore : Imprint: Springer, 2022Edition: 1st ed. 2022Description: 1 online resourceContent type:

text

Media type:

computer

Carrier type:

online resource

ISBN:

9789811900310

Subject(s):

LOC classification:

QP475

Online resources:

Springer eBooks Online access link to the resource

Contents:

Introduction -- Topographical consistency of cortical maps -- Orthogonal organization of visual cortex -- Parametric classifications of cortical organization -- Discussion: Biological plausibility of the model.

Summary: This book discusses the emergence of diverse functional organizations in the visual pathway which could be spontaneously and solely initiated by the random feedforward wiring of neural circuits. It demonstrates that the structure of ON and OFF retinal ganglion cell (RGC) mosaics is projected onto V1 by retino-cortical feedforward mapping to induce higher cognitive functions. This book will be beneficial for both theoretical and experimental neuroscientists, as well as for researchers using brain-inspired neural network models.

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Holdings
Item type	Current library	Home library	Collection	Call number	Copy number	Status	Notes	Date due	Barcode
E-Book	Merkez Kütüphane	Merkez Kütüphane	E-Kitap Koleksiyonu	QP475EBK (Browse shelf(Opens below))	1	Geçerli değil-e-Kitap / Not applicable-e-Book			EBK02985

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This book discusses the emergence of diverse functional organizations in the visual pathway which could be spontaneously and solely initiated by the random feedforward wiring of neural circuits. It demonstrates that the structure of ON and OFF retinal ganglion cell (RGC) mosaics is projected onto V1 by retino-cortical feedforward mapping to induce higher cognitive functions. This book will be beneficial for both theoretical and experimental neuroscientists, as well as for researchers using brain-inspired neural network models.

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