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dc.contributor.authorQuiñones, Darío R.
dc.contributor.authorFernández-Mollá, Luis Miguel
dc.contributor.authorPacheco-Torres, Jesús
dc.contributor.authorCaramés-Tejedor, José María 
dc.contributor.authorCanals-Gamoneda, Santiago
dc.contributor.authorMoratal, David
dc.date.accessioned2024-09-26T11:06:29Z
dc.date.available2024-09-26T11:06:29Z
dc.date.created2024
dc.date.issued2019
dc.identifier.urihttps://hdl.handle.net/10630/33451
dc.description.abstractIntroduction: 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 micro- controller, 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.es_ES
dc.description.sponsorshipThis work was supported in part by the Spanish Ministerio de Economía y Competitividad (MINECO) and FEDER funds under grants BFU2015-64380-C2-2-R (D.M.) and BFU2015-64380-C2-1-R and EU Horizon 2020 Program 668863-SyBil-AA grant (S.C.). S.C. acknowl- edges financial support from the Spanish State Research Agency, through the “Severo Ochoa” Programme for Centres of Excellence in R& D (ref. SEV-2013-0317). D.R.Q. was supported by grant “Ayudas para la formación de personal investigador (FPI)” from the Vicerrectorado de Investigación, Innovación y Transferencia of the Universitat Politècnica de València.es_ES
dc.language.isoenges_ES
dc.publisherElsevier
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectImágenes por resonancia magnéticaes_ES
dc.subjectAnestésicoses_ES
dc.subjectRatones de laboratorioes_ES
dc.subject.otherAnesthetices_ES
dc.subject.otherArduinoes_ES
dc.subject.otherBOLDes_ES
dc.subject.otherfMRIes_ES
dc.subject.otherMicees_ES
dc.subject.otherPIDes_ES
dc.titleTherMouseDuino: an affordable Open-Source temperature control system for functional magnetic resonance imaging experimentation with micees_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.centroFacultad de Psicología y Logopediaes_ES
dc.identifier.orcid10.1016/j.mri.2019.01.009
dc.identifier.doi10.1016/j.mri.2019.01.009
dc.type.hasVersioninfo:eu-repo/semantics/submittedVersiones_ES


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