Anna Bálint, Vivien Reicher, Barbara Csibra, Márta Gácsi
{"title":"Noninvasive EEG measurement of sleep in the family cat and comparison with the dog","authors":"Anna Bálint, Vivien Reicher, Barbara Csibra, Márta Gácsi","doi":"10.1093/jmammal/gyad122","DOIUrl":null,"url":null,"abstract":"We have successfully measured the sleep electroencephalogram (EEG) of 12 family cats during an afternoon nap using a completely noninvasive methodology originally developed and validated for family dogs. Extracting both macrostructural and spectral sleep variables from the acquired data, we: (1) provided a descriptive analysis of sleep structure in cats and the power spectral density (PSD) distribution considering 3 sleep stages—drowsiness, non-rapid eye movement (NREM), and rapid eye movement (REM) sleep; and (2) compared the results to those obtained in family dogs measured under the same conditions and using the same methodology. Importantly, our description of sleep structure and PSD distribution in cats proved to be comparable to those of earlier invasive studies, highlighting that appropriate noninvasive methodologies may provide a viable alternative to those that are invasive in some cases. While no macrostructural differences were found between the sleep of cats and dogs, and the characteristic PSDs were mostly similar across sleep stages within the 2 species, the high-frequency resolution comparison of PSD distributions revealed differences between the 2 species in all sleep stages (concerning the delta, theta, alpha, sigma, and beta bands in drowsiness and NREM sleep; and the delta, alpha, and sigma bands in REM sleep). Potential factors underlying these differences are discussed, including differences in circadian rhythms, sleep homeostatic regulation, experienced stress, or even differential attitudes toward owners—highlighting important links between sleep characteristics and often more complex neural and behavioral features.","PeriodicalId":50157,"journal":{"name":"Journal of Mammalogy","volume":"1 1","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2024-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mammalogy","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/jmammal/gyad122","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ZOOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
We have successfully measured the sleep electroencephalogram (EEG) of 12 family cats during an afternoon nap using a completely noninvasive methodology originally developed and validated for family dogs. Extracting both macrostructural and spectral sleep variables from the acquired data, we: (1) provided a descriptive analysis of sleep structure in cats and the power spectral density (PSD) distribution considering 3 sleep stages—drowsiness, non-rapid eye movement (NREM), and rapid eye movement (REM) sleep; and (2) compared the results to those obtained in family dogs measured under the same conditions and using the same methodology. Importantly, our description of sleep structure and PSD distribution in cats proved to be comparable to those of earlier invasive studies, highlighting that appropriate noninvasive methodologies may provide a viable alternative to those that are invasive in some cases. While no macrostructural differences were found between the sleep of cats and dogs, and the characteristic PSDs were mostly similar across sleep stages within the 2 species, the high-frequency resolution comparison of PSD distributions revealed differences between the 2 species in all sleep stages (concerning the delta, theta, alpha, sigma, and beta bands in drowsiness and NREM sleep; and the delta, alpha, and sigma bands in REM sleep). Potential factors underlying these differences are discussed, including differences in circadian rhythms, sleep homeostatic regulation, experienced stress, or even differential attitudes toward owners—highlighting important links between sleep characteristics and often more complex neural and behavioral features.