TY - JOUR
T1 - A Teensy microcontroller-based interface for optical imaging camera control during behavioral experiments
AU - Romano, Michael
AU - Bucklin, Mark
AU - Gritton, Howard
AU - Mehrotra, Dev
AU - Kessel, Robb
AU - Han, Xue
N1 - Funding Information:
X.H. acknowledges funding from the National Institutes of Health ( 1DP2NS082126 , R01NS109794-01 ), National Science Foundation CBET-1848029 , 1835270 ).
Publisher Copyright:
© 2019 Elsevier B.V.
Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.
PY - 2019/5/15
Y1 - 2019/5/15
N2 - Background: Systems neuroscience experiments often require the integration of precisely timed data acquisition and behavioral monitoring. While specialized commercial systems have been designed to meet various needs of data acquisition and device control, they often fail to offer flexibility to interface with new instruments and variable behavioral experimental designs. New method: We developed a Teensy 3.2 microcontroller-based interface that is easily programmable, and offers high-speed, precisely timed behavioral data acquisition and digital and analog outputs for controlling sCMOS cameras and other devices. Results: We demonstrate the flexibility and the temporal precision of the Teensy interface in two experimental settings. In one example, we used the Teensy interface to record an animal's directional movement on a spherical treadmill, while delivering repeated digital pulses that can be used to control image acquisition from a sCMOS camera. In another example, we used the Teensy interface to deliver an auditory stimulus and a gentle eye puff at precise times in a trace conditioning eye blink behavioral paradigm, while delivering repeated digital pulses to trigger camera image acquisition. Comparison with existing methods: This interface allows high-speed and temporally precise digital data acquisition and device control during diverse behavioral experiments. Conclusion: The Teensy interface, consisting of a Teensy 3.2 and custom software functions, provides a temporally precise, low-cost, and flexible platform to integrate sCMOS camera control into behavioral experiments.
AB - Background: Systems neuroscience experiments often require the integration of precisely timed data acquisition and behavioral monitoring. While specialized commercial systems have been designed to meet various needs of data acquisition and device control, they often fail to offer flexibility to interface with new instruments and variable behavioral experimental designs. New method: We developed a Teensy 3.2 microcontroller-based interface that is easily programmable, and offers high-speed, precisely timed behavioral data acquisition and digital and analog outputs for controlling sCMOS cameras and other devices. Results: We demonstrate the flexibility and the temporal precision of the Teensy interface in two experimental settings. In one example, we used the Teensy interface to record an animal's directional movement on a spherical treadmill, while delivering repeated digital pulses that can be used to control image acquisition from a sCMOS camera. In another example, we used the Teensy interface to deliver an auditory stimulus and a gentle eye puff at precise times in a trace conditioning eye blink behavioral paradigm, while delivering repeated digital pulses to trigger camera image acquisition. Comparison with existing methods: This interface allows high-speed and temporally precise digital data acquisition and device control during diverse behavioral experiments. Conclusion: The Teensy interface, consisting of a Teensy 3.2 and custom software functions, provides a temporally precise, low-cost, and flexible platform to integrate sCMOS camera control into behavioral experiments.
KW - ADNS-9800 gaming sensor
KW - Arduino
KW - Microcontroller
KW - Open-source
KW - sCMOS camera
KW - Spherical treadmill
KW - Teensy
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U2 - 10.1016/j.jneumeth.2019.03.019
DO - 10.1016/j.jneumeth.2019.03.019
M3 - Article
C2 - 30946877
AN - SCOPUS:85063869926
SN - 0165-0270
VL - 320
SP - 107
EP - 115
JO - Journal of Neuroscience Methods
JF - Journal of Neuroscience Methods
ER -