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Journal Article
Research Support, Non-U.S. Gov't
TherMouseDuino: An affordable Open-Source temperature control system for functional magnetic resonance imaging experimentation with mice.
Magnetic Resonance Imaging 2019 May
INTRODUCTION: Functional magnetic resonance imaging (fMRI) is one of the most highly regarded techniques in the neuroimaging field. This technique is based on vascular responses to neuronal activation and is extensively used in clinical and animal research studies. In preclinical settings, fMRI is usually applied to anesthetized animals. However, anesthetics cause alterations, e.g. hypothermia, in the physiology of the animals and this has the potential to disrupt fMRI signals. The current temperature control method involves a technician, as well as monitoring the acquisition MRI sequences, also controlling the temperature of the animal; this is inefficient.
METHODS: In order to avoid hypothermia in anesthetized rodents an Open-Source automatic temperature control device is presented. It takes signals from an intrarectal temperature sensor, as well as signals from a thermal bath, which warms up the body of the animal under study, in order to determine the mathematical model of the thermal response of the animal.
RESULTS: A Proportional-Integral-Derivative (PID) algorithm, which was discretized in an Arduino microcontroller, was developed to automatically keep stable the body temperature of the animal under study. The PID algorithm has been shown to be accurate in preserving the body temperature of the animal.
CONCLUSION: This work presents the TherMouseDuino. It is an Open-Source automatic temperature control system and reduces temperature fluctuations, thus providing robust conditions in which to perform fMRI experiments. Furthermore, our device frees up the technician to focus solely on monitoring the MRI sequences.
METHODS: In order to avoid hypothermia in anesthetized rodents an Open-Source automatic temperature control device is presented. It takes signals from an intrarectal temperature sensor, as well as signals from a thermal bath, which warms up the body of the animal under study, in order to determine the mathematical model of the thermal response of the animal.
RESULTS: A Proportional-Integral-Derivative (PID) algorithm, which was discretized in an Arduino microcontroller, was developed to automatically keep stable the body temperature of the animal under study. The PID algorithm has been shown to be accurate in preserving the body temperature of the animal.
CONCLUSION: This work presents the TherMouseDuino. It is an Open-Source automatic temperature control system and reduces temperature fluctuations, thus providing robust conditions in which to perform fMRI experiments. Furthermore, our device frees up the technician to focus solely on monitoring the MRI sequences.
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