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Pecevski D, Natschläger T, Schuch K - Front Neuroinform (2009)

Bottom Line: Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle.The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof.Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations.

View Article: PubMed Central - PubMed

Affiliation: Institute for Theoretical Computer Science, Graz University of Technology Graz, Austria.

ABSTRACT
The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations.

No MeSH data available.


A diagram of the most important concepts within the network construction interface. The arrows indicate a “uses” relationship between the concepts.
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Figure 4: A diagram of the most important concepts within the network construction interface. The arrows indicate a “uses” relationship between the concepts.

Mentions: Figure 4 shows the basic concepts of PCSIM's construction framework together with their interactions during the construction process. This framework allows model specification in terms of populations of neurons connected by probabilistically defined connectivity patterns called projections.


[Not Available].

Pecevski D, Natschläger T, Schuch K - Front Neuroinform (2009)

A diagram of the most important concepts within the network construction interface. The arrows indicate a “uses” relationship between the concepts.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2698777&req=5

Figure 4: A diagram of the most important concepts within the network construction interface. The arrows indicate a “uses” relationship between the concepts.
Mentions: Figure 4 shows the basic concepts of PCSIM's construction framework together with their interactions during the construction process. This framework allows model specification in terms of populations of neurons connected by probabilistically defined connectivity patterns called projections.

Bottom Line: Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle.The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof.Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations.

View Article: PubMed Central - PubMed

Affiliation: Institute for Theoretical Computer Science, Graz University of Technology Graz, Austria.

ABSTRACT
The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations.

No MeSH data available.