Donald J Noble1, Camden J MacDowell1, Michael L McKinnon1, Tamra I Neblett1, William N Goolsby2, Shawn Hochman3. 1. Department of Physiology, Emory University School of Medicine, 30322 Atlanta, GA, United States. 2. Department of Cell Biology, Emory University School of Medicine, 30322 Atlanta, GA, United States. 3. Department of Physiology, Emory University School of Medicine, 30322 Atlanta, GA, United States. Electronic address: shochm2@emory.edu.
Abstract
BACKGROUND: Numerous environmental and genetic factors can contribute significantly to behavioral and cardiorespiratory variability observed experimentally. Affordable technologies that allow for noninvasive home cage capture of physio-behavioral variables should enhance understanding of inter-animal variability including after experimental interventions. NEW METHOD: We assessed whether EPIC electric field sensors (Plessey Semiconductors) embedded within or attached externally to a rodent's home cage could accurately record respiration, heart rate, and motor behaviors. COMPARISON WITH EXISTING METHODS: Current systems for quantification of behavioral variables require expensive specialty equipment, while measures of respiratory and heart rate are often provided by surgically implanted or chronically affixed devices. RESULTS: Sensors accurately encoded imposed sinusoidal changes in electric field tested at frequencies ranging from 0.5-100Hz. Mini-metronome arm movements were easily detected, but response magnitude was highly distance dependent. Sensors accurately reported respiration during whole-body plethysmography. In anesthetized rodents, PVC tube-embedded sensors provided accurate mechanical detection of both respiratory and heart rate. Comparable success was seen in naturally behaving animals at rest or sleeping when sensors were attached externally. Video-verified motor behaviors (sniffing, grooming, chewing, and rearing) were detectable and largely separable by their characteristic voltage fluctuations. Larger movement-related events had comparably larger voltage dynamics that easily allowed for a broad approximation of overall motor activity. Spectrograms were used to quickly depict characteristic frequencies in long-lasting recordings, while filtering and thresholding software allowed for detection and quantification of movement-related physio-behavioral events. CONCLUSIONS: EPIC electric field sensors provide a means for affordable non-contact home cage detection of physio-behavioral variables.
BACKGROUND: Numerous environmental and genetic factors can contribute significantly to behavioral and cardiorespiratory variability observed experimentally. Affordable technologies that allow for noninvasive home cage capture of physio-behavioral variables should enhance understanding of inter-animal variability including after experimental interventions. NEW METHOD: We assessed whether EPIC electric field sensors (Plessey Semiconductors) embedded within or attached externally to a rodent's home cage could accurately record respiration, heart rate, and motor behaviors. COMPARISON WITH EXISTING METHODS: Current systems for quantification of behavioral variables require expensive specialty equipment, while measures of respiratory and heart rate are often provided by surgically implanted or chronically affixed devices. RESULTS: Sensors accurately encoded imposed sinusoidal changes in electric field tested at frequencies ranging from 0.5-100Hz. Mini-metronome arm movements were easily detected, but response magnitude was highly distance dependent. Sensors accurately reported respiration during whole-body plethysmography. In anesthetized rodents, PVC tube-embedded sensors provided accurate mechanical detection of both respiratory and heart rate. Comparable success was seen in naturally behaving animals at rest or sleeping when sensors were attached externally. Video-verified motor behaviors (sniffing, grooming, chewing, and rearing) were detectable and largely separable by their characteristic voltage fluctuations. Larger movement-related events had comparably larger voltage dynamics that easily allowed for a broad approximation of overall motor activity. Spectrograms were used to quickly depict characteristic frequencies in long-lasting recordings, while filtering and thresholding software allowed for detection and quantification of movement-related physio-behavioral events. CONCLUSIONS: EPIC electric field sensors provide a means for affordable non-contact home cage detection of physio-behavioral variables.
Authors: H Kloefkorn; L M Aiani; A Lakhani; S Nagesh; A Moss; W Goolsby; J M Rehg; N P Pedersen; S Hochman Journal: J Neurosci Methods Date: 2020-06-30 Impact factor: 2.390
Authors: Thomas E Nichols; Samir Das; Simon B Eickhoff; Alan C Evans; Tristan Glatard; Michael Hanke; Nikolaus Kriegeskorte; Michael P Milham; Russell A Poldrack; Jean-Baptiste Poline; Erika Proal; Bertrand Thirion; David C Van Essen; Tonya White; B T Thomas Yeo Journal: Nat Neurosci Date: 2017-02-23 Impact factor: 24.884
Authors: Donald J Noble; William N Goolsby; Sandra M Garraway; Karmarcha K Martin; Shawn Hochman Journal: Front Physiol Date: 2017-10-30 Impact factor: 4.566