UCL Discovery
UCL home » Library Services » Electronic resources » UCL Discovery

Modeling the sensory computations of the olfactory bulb

Zhaoping, L.; (1994) Modeling the sensory computations of the olfactory bulb. In: Domany, E. and van Hemmen, J.L. and Schulten, K., (eds.) Models of Neural Networks II: Temporal Aspects of Coding and Information Processing in Biological Systems. (pp. 221-251). Springer Verlag: New York, US. Green open access

[thumbnail of 18224.pdf]
Preview
PDF
18224.pdf

Download (327kB)

Abstract

Book description: The theory of neural nets has two new paradigms: information coding through coherent firing of the neurons and structural feedback. As compared to traditional neural nets, spiking neurons provide an extra degree of freedom: time; this degree of freedom is realized by a coherent spiking of extensively many neurons in the network, a nonlinear phenomenon. The other paradigm, feedback, is a dominant feature of the structural organization of the brain. This volume provides an in-depth analysis of both paradigms starting with an extensive introduction to the ideas used in the subsequent chapters. In addition, one finds a detailed discussion of salient features such as coherent oscillations and their detection, associative binding and segregation, Hebbian learning, and sensory computations in the visual and olfactory cortex. The style and level of this book make it particularly useful for advanced students and researchers looking for an accessible survey of today's theory of neuronal networks.

Type: Book chapter
Title: Modeling the sensory computations of the olfactory bulb
ISBN-13: 9780387943626
Open access status: An open access version is available from UCL Discovery
Publisher version: http://www.springer.com/physics/biophysics/book/97...
Language: English
Additional information: The original publication is available at www.springerlink.com
UCL classification: UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neurosci Unit
URI: https://discovery.ucl.ac.uk/id/eprint/18224
Downloads since deposit
182Downloads
Download activity - last month
Download activity - last 12 months
Downloads by country - last 12 months

Archive Staff Only

View Item View Item