Neuro-Signals - Invertebrate Neural Networks - Y. Wong, J. Wong (Karger, 2004) WW.pdf - Bio Med 19 - hilakku

Invertebrate

Neural

Networks

Editors

Yung Hou Wong, Hong Kong

Joseph T.Y. Wong, Hong Kong

26 ﬁ gures, 2 in color, 2004

Basel • Freiburg • Paris • London • New York •

Bangalore • Bangkok • Singapore • Tokyo • Sydney

S. Karger

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Vol. 13, No. 1–2, 2004

Contents

4 Editorial

Wong Y.H.; Wong, J.T.Y. (Hong Kong)

Reviews

5 Central Neural Circuitry in the Jellyﬁ sh Aglantha . A Model ‘Simple

Nervous System‘

Mackie, G.O. (Victoria)

20 The Insect Frontal Ganglion and Stomatogastric Pattern Generator

Networks

Ayali, A. (Tel Aviv)

37 Molecular Mechanisms for Drosophila Neuronetwork Formation

Furrer, M.-P.; Chiba, A. (Urbana, Ill.)

50 Crustacean Motor Pattern Generator Networks

Hooper, S.L.; DiCaprio, R.A. (Athens, Ohio)

70 Feeding Neural Networks in the Mollusc Aplysia

Cropper, E.C.; Evans, C.G.; Hurwitz, I.; Jing, J.; Proekt, A.; Romero, A.; Rosen, S.C.

(New York, N.Y.)

87 Cephalopod Neural Networks

Williamson, R.; Chrachri, A. (Plymouth)

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Access to full text and tables of contents,

including tentative ones for forthcoming issues:

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Neurosignals 2004;13:4

DOI: 10.1159/000076154

Editorial

Neural networking forms the basis of learning and memory, which in turn

are the foundation of intelligence. As early as the 1970s, studies in invertebrate

systems revealed that structural changes at synapses are related to learning and

memory storage. Invertebrate models not only provide simple systems for the

studies of complex behavior, many systems are also amenable for genetic stud-

ies. While neural networking is now synonymous with computational ap-

proaches, we have yet to explore the full potential of what invertebrate neuro-

nal systems can provide. With the advent of genomics and proteomics, it is

now pertinent to have a fresh look at some of the invertebrate systems. We

have gathered reviews across a wide spectrum of invertebrate systems. The

cnidarians consist of organisms capable of behavior generated from simple

neural net, or from centralized system, as in the case of the jellyfish. Crusta-

ceans and insects have been useful models of understanding rhythmic behav-

ior. Synaptic plasticity, in relation to memory, was first discovered in Alphy-

sia. Cephalopods are well known for their capacity of intelligence behavior.

Drosophila , with the advantage of genetics, is useful for the molecular study of

network guidance and formation.

Yung Hou Wong, Hong Kong

Joseph T.Y. Wong, Hong Kong

ABC

Fax +41 61 306 12 34

E-Mail karger@karger.ch

www.karger.com

1424–862X/04/0132–0004$21.00/0

Accessible online at:

www.karger.com/nsg

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