Abstract
There is growing need for multichannel electrophysiological systems that record from and interact with neuronal systems in near real-time. Such systems are needed, for example, for closed loop, multichannel electrophysiological/optogenetic experimentation in vivo and in a variety of other neuronal preparations, or for developing and testing neuro-prosthetic devices, to name a few. Furthermore, there is a need for such systems to be inexpensive, reliable, user friendly, easy to set-up, open and expandable, and possess long life cycles in face of rapidly changing computing environments. Finally, they should provide powerful, yet reasonably easy to implement facilities for developing closed-loop protocols for interacting with neuronal systems. Here, we survey commercial and open source systems that address these needs to varying degrees. We then present our own solution, which we refer to as Closed Loop Experiments Manager (CLEM). CLEM is an open source, soft real-time, Microsoft Windows desktop application that is based on a single generic personal computer (PC) and an inexpensive, general-purpose data acquisition board. CLEM provides a fully functional, user-friendly graphical interface, possesses facilities for recording, presenting and logging electrophysiological data from up to 64 analog channels, and facilities for controlling external devices, such as stimulators, through digital and analog interfaces. Importantly, it includes facilities for running closed-loop protocols written in any programming language that can generate dynamic link libraries (DLLs). We describe the application, its architecture and facilities. We then demonstrate, using networks of cortical neurons growing on multielectrode arrays (MEA) that despite its reliance on generic hardware, its performance is appropriate for flexible, closed-loop experimentation at the neuronal network level.
Highlights
A common manner for studying complex dynamic systems is to use closed-loop systems that fix or control one or more interdependent variables; by uncoupling interdependent variables, such closed-loop systems allow these interdependencies to be resolved
We describe our own solution and examine its performance using networks of cortical neurons growing on multielectrode array (MEA) dishes
Multiple closed loop platforms for neurophysiological studies have been put forward. It might be asked why yet another platform is necessary? many excellent platforms are available, with the performance of some of them exceeding that of Closed Loop Experiments Manager (CLEM)
Summary
A common manner for studying complex dynamic systems is to use closed-loop systems that fix or control one or more interdependent variables; by uncoupling interdependent variables, such closed-loop systems allow these interdependencies to be resolved. The use of closed-loop control systems, has expanded far beyond this purpose (reviewed in Wallach, 2013; Krook-Magnuson et al, 2015; Wright et al, 2016; see Potter et al, 2014 and references therein). Quite a few systems, based on different platforms, have been developed for this purpose Such systems would be inexpensive, expandable, and customizable, easy to use, and provide user-friendly interfaces and development environments. This is not always the case, and many of such systems represent tradeoffs between performance, complexity, ease of development, ease of use, expandability, dependence on specialized vs common platforms, and cost
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