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This article is part of the supplement: Nineteenth Annual Computational Neuroscience Meeting: CNS*2010

Open Access Open Badges Poster Presentation

Realtime tuning and verification of compartmental cell models using RTXI and GENESIS

Hugo Cornelis1* and Allan D Coop2

Author Affiliations

1 Department of Epidemiology and Biostatistics, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA

2 Research Imaging Institute, University of Texas Health Sciences Center at San Antonio, San Antonio, TX 78229, USA

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BMC Neuroscience 2010, 11(Suppl 1):P68  doi:10.1186/1471-2202-11-S1-P68

The electronic version of this article is the complete one and can be found online at:

Published:20 July 2010

© 2010 Cornelis and Coop; licensee BioMed Central Ltd.

Poster Presentation

The GEneral NEural SImulation System (GENESIS) has recently been reconfigured to resolve problems resulting from the rapidly increasing complexity of neural modeling software. Modularization of GENESIS according to the Computational Biology Initiative (CBI–[1]) functional software architecture has provided important advantages by facilitating the easy integration of new simulator functionality while maintaining an open developer community. The complexity of individual software modules is greatly reduced from that of a complete simulation system, documentation is simplified when modules are independent, they can be more easily tested, added or removed, and the scope of a new module is clearly delineated. Unlike GENESIS versions 1 and 2, the modular construction of GENESIS-3 (G-3) is designed to greatly facilitate the development of new tools to support simulation-based education, collaboration, and model publication.

The Real-Time eXperimental Interface (RTXI) is a mature modular dynamic clamp implementation growing out of previous work by Butera [2] and White [3] for hard realtime (RT) data acquisition. RTXI is modular to the extent that user-supplied function-specific code models can be combined to build custom experimental protocols and interfaces. RTXI provides an event delivery system that allows these plug-ins to signal the occurrence of user-defined events amongst themselves as required.

We report on our efforts to interface G-3 with RTXI to develop an integrated software platform. This platform will greatly increase the power of dynamic clamp technology and in return deliver RT quantification and ’tuning’ of the parameters of cell and tissue models. Figure 1.


This research was supported by a NSF grant (HRD-0932339) to the University of Texas at San Antonio.


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