CALL FOR PAPERS [Neural Networks 1999 Special Issue]

[Mieko Namba]

Dear members,

We are glad to inform you that the Japanese Neural Networks Society will
edit the NEURAL NETWORKS 1999 Special Issue  as below.  NEURAL NETWORKS is
an official international compilation of the  Journal of the International
Neural Networks Society, the European Neural Networks Society and the
Japanese Neural Networks Society.  
We are looking forward to receiving your contributions.

Mitsuo Kawato
Co-Editor-in-Chief
Neural Networks
(ATR Human Information Proc. Res. Labs.)

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                                           CALL FOR PAPERS
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                              Neural Networks 1999 Special Issue
                 "Organisation of Computation in Brain-like Systems"
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Co-Editors:
Professor Gen Matsumoto, BSI, RIKEN, Japan
Professor Edgar Koerner, HONDA R&D, Europe
Dr. Mitsuo Kawato, ATR Human Information Processing Res. Labs., Japan

Submission:
Deadline for submission: December 1st, 1998
Notification of acceptance: March 1st, 1999

Format: 
as for normal papers in the journal (APA format)  and no longer than 10,000
words

Address for Papers:
Dr. Mitsuo Kawato
ATR Human Information Processing Research Laboratories
2-2 Hikaridai, Seika-cho Soraku-gun, Kyoto 619-0288,  Japan.
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In the recent years, neuroscience has made a big leap forward regarding
both investigation methodology and insights in local mechanisms of
processing of sensory information in the brain. The fact that we still do
not know much better than before what happens in the brain when one
recognises a familiar person, or moves around navigating seemingly
effortless through a busy street, points to the fact that our models still
do not describe essential aspects of how the brain organises computation.
The investigation of the behaviour of fairly homogeneous ANS (artificial
neural systems) composed of simple elementary nodes fostered the awareness
that architecture matters: Algorithms implemented by the respective neural
system are expressed by its architecture. Consequently, the focus is
shifting to better understanding of the architecture of the brain and of
its subsystems, since the structure of those highly modularised systems
represents the way the brain organises computation.
Approaching the algorithms expressed by those architectures may offer us
the capability to not only understand the representation of knowledge in a
neural system made under well defined constraints, but to understand the
control that forces the neural system to make representations of
behaviourally relevant knowledge by generating dynamic constraints. This
special issue will bring together invited papers and contributed articles
that illustrate the shifting emphasis in neural systems modelling to more
neuroarchitecture-motivated systems that include this type of control
architectures.
Local and global control algorithms for organisation of computation in
brain-like systems cover a wide field of topics. Abduction of control
principles inherent in the architectures that mediate interaction within
the cortex, between cortex -thalamus, cortex-hippocampus and other parts of
the limbic system is one of the targets. Of particular importance are the
rapid access to stored knowledge and the management of conflicts in
response to sensory input, the coding and representation in a basically
asynchronous mode of processing, the decomposition of problems into a
reasonable number of simpler sub-problems, and the control of learning --
including the control which specifies what should be learned, and how to
integrate the new knowledge into the relational architecture of the already
acquired knowledge representation. Another target of that approach is the
attempt to understand how these controls and the respective architectures
emerged in the process of self-organisation in the phylogenetic and
ontogenetic development. Setting the cognitive behaviour of neural systems
in the focus of investigation is a prerequisite for the described approach
that will promote both creating computational hypotheses for neurobiology
and implementing robust and flexible computation in ANS.

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end.
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Mieko Namba
Secretary to Dr. Mitsuo Kawato
Editorial Administrator of NEURAL NETWORKS

ATR Human Information Processing Research Laboratories
2-2 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288, Japan
TEL +81-774-95-1058    FAX +81-774-95-1008
E-MAIL mieko at hip.atr.co.jp
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