Simulation Systems
CANNES laboratory, in conjunction with the Brain Lab at the University
of Southern California are developing tools, NSL/ASL,
for the simulation of distributed and hierarchical neural networks.
This goes in hand with research in diverse related areas, such as
visualization, robotics and modeling methodologies (Computer-Aided
Neural Networks Engineering Systems - CANNES).
Databases and Simulation
Databases supporting simulation systems are a related aspect currently
developed as part of HBP (Human Brain Project) at the University
of Southern California in order to offer access to distributed experimental
data. Among the issues being addressed are the development of models
for multi-media data (e.g., structured text describing experimental
protocols; time series from neurophysiological recordings; and 2D
and 3D anatomical data); how to match data from brain slices to
"standard slices" in an electronic atlas of neuroanatomy;
integration of visualization with database construction and retrieval;
and the merging of simulation tools and database tools into an integrated
environment which (a) lets experimenters learn of well-substantiated
predictions ready for testing, (b) links model assumptions to supporting
empirical data, and (c) provides tools to test models against available
data, and develop versions of extra models which better meet new
data as they become available.
To tie neural modeling with the database project, we dwell on the
issue of "conceptual modeling", and the way in which it
will provide part of the integrative thrust for the whole project.
The issue is this: a given body of data can be seen either as an
uninterpreted array of bits, or as a highly structured set of records,
with explicit representation of relations between these records,
some of which may be at different levels of hierarchical detail.
The problem is to find the appropriate concepts with which to structure
a given set of data, balancing off the costs of structuring data
with the costs of trying to answer questions using terminology which
is not well related to the structure of the database. Briefly, conceptual
modeling will be applied to the data gathering process in the project
and will guide the design of appropriate data structures for the
simulation tools.
The project Multi-Level Modeling
in Neural Networks: A Computational and Experimental Approach,
has as an important component in the extension of NSL to provide
a multi-level methodology for linking simulations and databases
to facilitate the construction, testing, and validation of complex
neural systems.
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