The dynamic clamp paper may be downloaded from the eNeuro website (http://www.eneuro.org/content/4/5/ENEURO.0250-17.2017).
The software may be downloaded from the Github website (http://github.com/nsdesai/dynamic_clamp).
The dynamic clamp should be a standard part of every cellular electrophysiologist’s toolbox. That it is not, even 25 years after its introduction, comes down to three issues: money, the disruption that adding dynamic clamp to an existing electrophysiology rig entails, and the technical prowess required of experimenters. These have been valid and limiting issues in the past, but no longer. Technological advances associated with the so-called “maker movement” render them moot. We demonstrate this by implementing a fast (~100 kHz) dynamic clamp system using an inexpensive microcontroller (Teensy 3.6). The overall cost of the system is less than USD$100, and assembling it requires no prior electronics experience. Modifying it – for example, to add Hodgkin-Huxley-style conductances – requires no prior programming experience. The system works together with existing electrophysiology data acquisition systems (for Macintosh, Windows, and Linux); it does not attempt to supplant them. Moreover, the process of assembling, modifying, and using the system constitutes a useful pedagogical exercise for students and researchers with no background but an interest in electronics and programming. We demonstrate the system’s utility by implementing conductances as fast as a transient sodium conductance and as complex as the Ornstein-Uhlenbeck conductances of the “point conductance” model of synaptic background activity.
UPDATES (July 2019): I have been working on a somewhat improved hardware design that: (1) uses a 3.3 V voltage regulator (https://www.sparkfun.com/products/526) to provide a reference voltage for the circuits of Figures 2B and 2D rather than relying on the output of the rail splitter for this purpose (the rail splitter continues to provide the ± 9 V needed to power the op-amps); (2) includes diodes to protect the Teensy ADC in case of an accidental over-voltage; and (3) rearranges the resistors so that it is simpler to find values that will capture most of the dynamic range of the amplifier and/or digitizer. The main advantage of these changes is that, by using a stable and (relatively) exact 3.3 V as the reference, imperfections in the 18 V power supply (“wall wart”) and some of the other components don’t matter as much. In fact, the system may not need calibration at all.
I haven’t written up the changes yet, but for those who like electronic circuits, you can find the designs in the CircuitLab section, indicated in the menu. As the name suggests, each of the designs has a link to a CircuitLab simulation (www.circuitlab.com), so that you can test how it works.
If you are interested in the these new circuit designs but run into trouble in making them, please do not hesitate to write to me. — Niraj Desai (firstname.lastname@example.org).
UPDATES (May 2019): Added a section (dyClamp & pyClamp) with a description of and links to a software project by Christian Rickert (GitHub) that (1) provides an alternative Arduino sketch with robust serial communication between microcontroller and host computer (dyClamp) and (2) a Python interface to control simulations (pyClamp).
UPDATES (January 2018): Added a Media section to hold videos and pictures. Refined the description of the calibration procedure and edited the associated Processing sketch (processing_calibration.pde); now measurements will be plotted as they’re obtained.
UPDATES (December 2017): Added a section on troubleshooting and one on using externally-generated or saved conductances. The latter describes how to send the Teensy microcontroller analog signals representing up to three separate conductance trains, so that the Teensy can inject these conductances into a neuron. A typical use case would be when an experimenter, having previously recorded excitatory and inhibitory synaptic currents in voltage clamp mode (perhaps in vivo or in culture), would like to feed conductances derived from these recordings into a different neuron (perhaps in a brain slice). The added section also describes how to save conductance waveforms in the Teensy’s memory so that they can be read out element by element at run-time, rather than being generated by numerical integration.
RELATED WEBSITE: Andrew Scallon at the University of Colorado has refined the design to make the dynamic clamp system more compact and rugged. Here is his website: ONEdynamicclamp