Background: Current software tools for electrophysiological experiments are limited in flexibility and rarely offer adequate support for advanced techniques such as dynamic clamp and hybrid experiments, which are therefore limited to laboratories with a significant expertise in neuroinformatics. New method: We have developed lcg, a software suite based on a command-line interface (CLI) that allows performing both standard and advanced electrophysiological experiments. Stimulation protocols for classical voltage and current clamp experiments are defined by a concise and flexible meta description that allows representing complex waveforms as a piece-wise parametric decomposition of elementary sub-waveforms, abstracting the stimulation hardware. To perform complex experiments lcg provides a set of elementary building blocks that can be interconnected to yield a large variety of experimental paradigms. Results: We present various cellular electrophysiological experiments in which lcg has been employed, ranging from the automated application of current clamp protocols for characterizing basic electrophysiological properties of neurons, to dynamic clamp, response clamp, and hybrid experiments. We finally show how the scripting capabilities behind a CLI are suited for integrating experimental trials into complex workflows, where actual experiment, online data analysis and computational modeling seamlessly integrate. Comparison with existing methods: We compare lcg with two open source toolboxes, RTXI and RELACS. Conclusions: We believe that lcg will greatly contribute to the standardization and reproducibility of both simple and complex experiments. Additionally, on the long run the increased efficiency due to a CLI will prove a great benefit for the experimental community. © 2014 Elsevier B.V.

Command-line cellular electrophysiology for conventional and real-time closed-loop experiments / Linaro, D.; Couto, J.; Giugliano, M.. - In: JOURNAL OF NEUROSCIENCE METHODS. - ISSN 1872-678X. - 230:jun(2014), pp. 5-19. [10.1016/j.jneumeth.2014.04.003]

Command-line cellular electrophysiology for conventional and real-time closed-loop experiments

Giugliano, M.
2014

Abstract

Background: Current software tools for electrophysiological experiments are limited in flexibility and rarely offer adequate support for advanced techniques such as dynamic clamp and hybrid experiments, which are therefore limited to laboratories with a significant expertise in neuroinformatics. New method: We have developed lcg, a software suite based on a command-line interface (CLI) that allows performing both standard and advanced electrophysiological experiments. Stimulation protocols for classical voltage and current clamp experiments are defined by a concise and flexible meta description that allows representing complex waveforms as a piece-wise parametric decomposition of elementary sub-waveforms, abstracting the stimulation hardware. To perform complex experiments lcg provides a set of elementary building blocks that can be interconnected to yield a large variety of experimental paradigms. Results: We present various cellular electrophysiological experiments in which lcg has been employed, ranging from the automated application of current clamp protocols for characterizing basic electrophysiological properties of neurons, to dynamic clamp, response clamp, and hybrid experiments. We finally show how the scripting capabilities behind a CLI are suited for integrating experimental trials into complex workflows, where actual experiment, online data analysis and computational modeling seamlessly integrate. Comparison with existing methods: We compare lcg with two open source toolboxes, RTXI and RELACS. Conclusions: We believe that lcg will greatly contribute to the standardization and reproducibility of both simple and complex experiments. Additionally, on the long run the increased efficiency due to a CLI will prove a great benefit for the experimental community. © 2014 Elsevier B.V.
230
jun
5
19
https://doi.org/10.1016/j.jneumeth.2014.04.003
Linaro, D.; Couto, J.; Giugliano, M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/102910
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