2010
DOI: 10.1590/s0100-879x2010007500047
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Long-term social recognition memory in adult male rats: factor analysis of the social and non-social behaviors

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Cited by 20 publications
(7 citation statements)
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“…In two different social contexts, they exhibited increased non-anogenital and decreased anogenital exploration, accompanied with a different profile of ultrasonic vocalizations. We cannot offer a definitive explanation for the different behavioral profile, but it should be noted that anogenital sniffing and licking is the major source of information enabling individual recognition in rats (Moura et al, 2010). We therefore hypothesize that the McGill rats were less motivated to establish the identity of their social partners, although otherwise willing to interact with them.…”
Section: Discussionmentioning
confidence: 89%
“…In two different social contexts, they exhibited increased non-anogenital and decreased anogenital exploration, accompanied with a different profile of ultrasonic vocalizations. We cannot offer a definitive explanation for the different behavioral profile, but it should be noted that anogenital sniffing and licking is the major source of information enabling individual recognition in rats (Moura et al, 2010). We therefore hypothesize that the McGill rats were less motivated to establish the identity of their social partners, although otherwise willing to interact with them.…”
Section: Discussionmentioning
confidence: 89%
“…PCA was used to examine patterns of intercorrelations between the variables studied as reported recently by our group (Menard et al, 2014b) and others (Chujo et al, 2013;Moura et al, 2010;van der Staay et al, 2009). Principal components produced by the orthogonal linear transformation of PCA are linear combinations of the original measures, on a new coordinate system, reflecting independent characteristics or dimensions underlying the correlation matrix (Menard et al, 2014b,van der Staay et al, 2009).…”
Section: Discussionmentioning
confidence: 99%
“…Principal component analysis (PCA) was used to examine patterns of intercorrelations between the variables (Moura et al, 2010). Principal components produced by PCA are linear combinations of the original measures reflecting independent characteristics (or dimensions) underlying the correlation matrix.…”
Section: Methodsmentioning
confidence: 99%