title: Trains of sleep sequences are indices of learning capacity in rats.
abstract: In previous work dealing with the identification of four sleep sequences (SS-->W, SS-->PS, SS-->TS-->W and SS-->TS-->PS) in the baseline session of adult male Wistar rats [Mandile P, Vescia S, Montagnese P, Romano F, Giuditta A. Characterization of transition sleep episodes in baseline EEG recordings of adults rats, Physiol Behav 1996;60:1435-1439], we have shown that those containing an intervening episode of transition sleep (TS) strongly correlate with the number of avoidances scored the following day [Vescia S, Mandile P, Montagnese P, Romano F, Cataldo G, Cotugno M, Giuditta A. Baseline transition sleep and associated sleep episodes are related to the learning ability of rats, Physiol Behav 1996;60:1513-152]. More recently, clusters of sleep sequences (trains) separated by waking intervals longer than 60 s have been identified in the baseline session of the same rats [Piscopo S, Mandile P, Montagnese P, Cotugno M, Giuditta A, Vescia S. Identification of trains of sleep sequences in adult rats, Behav Brain Res, this volume], and distinguished in homogeneous or mixed trains according to the presence of a single sleep sequence or more than one sequence. Mixed trains have been further separated into trains containing the SS-->TS-->W sequence (+TSW trains) and trains lacking it (-TSW trains). Analysis of the distribution of variables of baseline trains (and of their sleep sequences and components) among fast learning (FL), slow learning (SL), or non-learning (NL) rats, indicates that variables of +TSW trains prevail in FL rats, while variables of -TSW trains prevail in NL rats. In addition, variables of +TSW trains correlate with the number of avoidances of the training session, while variables of -TSW trains do not significantly correlate, or show inverse correlations. Interestingly, sleep sequences such as SS-->W or SS-->TS-->W show direct or inverse correlations with avoidances depending on whether they are included in +TSW trains or in -TSW trains. The data are interpreted to suggest that the outcome of brain operations performed during a sleep sequence may selectively condition the appearance of later sequences within a time interval shorter than a given threshold. An analogous mechanism may be responsible for the aggregation of sleep components in sleep sequences.
authors.affiliation: Dipartimento di Fisiologia Generale e Ambientale, Università di Napoli 'Federico II', Via Mezzocannone 8, 80134, Naples, Italy.
authors.forename: S
authors.initials: S
authors.lastname: Piscopo
authors.forename: P
authors.initials: P
authors.lastname: Mandile
authors.forename: P
authors.initials: P
authors.lastname: Montagnese
authors.forename: M
authors.initials: M
authors.lastname: Cotugno
authors.forename: A
authors.initials: A
authors.lastname: Giuditta
authors.forename: S
authors.initials: S
authors.lastname: Vescia
mesh_terms: D000704:Analysis of Variance; D000818:Animals; D001362:Avoidance Learning / Q000502:physiology*; D003214:Conditioning, Classical; D004569:Electroencephalography; D007858:Learning / Q000502:physiology; D008297:Male; D008568:Memory / Q000502:physiology; D008959:Models, Neurological; D011897:Random Allocation; D051381:Rats; D017208:Rats, Wistar; D012894:Sleep Stages / Q000502:physiology*