PLATO: Data-oriented approach to collaborative large-scale brain system modeling

Takayuki Kannon, Keiichiro Inagaki, Nilton L. Kamiji, Kouji Makimura, Shiro Usui

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

The brain is a complex information processing system, which can be divided into sub-systems, such as the sensory organs, functional areas in the cortex, and motor control systems. In this sense, most of the mathematical models developed in the field of neuroscience have mainly targeted a specific sub-system. In order to understand the details of the brain as a whole, such sub-system models need to be integrated toward the development of a neurophysiologically plausible large-scale system model. In the present work, we propose a model integration library where models can be connected by means of a common data format. Here, the common data format should be portable so that models written in any programming language, computer architecture, and operating system can be connected. Moreover, the library should be simple so that models can be adapted to use the common data format without requiring any detailed knowledge on its use. Using this library, we have successfully connected existing models reproducing certain features of the visual system, toward the development of a large-scale visual system model. This library will enable users to reuse and integrate existing and newly developed models toward the development and simulation of a large-scale brain system model. The resulting model can also be executed on high performance computers using Message Passing Interface (MPI).

Original languageEnglish
Pages (from-to)918-926
Number of pages9
JournalNeural Networks
Volume24
Issue number9
DOIs
Publication statusPublished - 11-2011
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Cognitive Neuroscience
  • Artificial Intelligence

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