Cerasuolo, Mariangela (2018) The effect of cognitive training on subsequent sleep characteristics. [Tesi di dottorato]

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Tipologia del documento:	Tesi di dottorato
Lingua:	English
Titolo:	The effect of cognitive training on subsequent sleep characteristics
Autori:	Autore Email Cerasuolo, Mariangela mariangela.cerasuolo@gmail.com
Data:	8 Dicembre 2018
Numero di pagine:	101
Istituzione:	Università degli Studi di Napoli Federico II
Dipartimento:	Studi Umanistici
Dottorato:	Mind, Gender and Language
Ciclo di dottorato:	31
Coordinatore del Corso di dottorato:	nome email Bacchini, Dario dario.bacchini@unina.it
Tutor:	nome email Ficca, Gianluca [non definito]
Data:	8 Dicembre 2018
Numero di pagine:	101
Parole chiave:	sleep; memory
Settori scientifico-disciplinari del MIUR:	Area 11 - Scienze storiche, filosofiche, pedagogiche e psicologiche > M-PSI/01 - Psicologia generale
Depositato il:	22 Dic 2018 12:06
Ultima modifica:	27 Giu 2020 04:59
URI:	http://www.fedoa.unina.it/id/eprint/12515

Abstract

Introduction: Several studies have consistently shown that pre-sleep learning produces changes in sleep structure. Whereas the majority of these studies has mainly focused on post-training changes in sleep states (namely REM and NREM sleep amount) and, more recently, in specific electrophysiological features (e.g., sleep spindles, slow wave activity), very little attention has been paid to the hypothesis that pre-sleep learning might improve sleep quality, as expressed by sleep continuity, stability and cyclic organization measures. Furthermore, studies addressing the relationship between sleep and learning usually employ purely declarative or procedural tasks, neglecting that everyday life learning processes depend on the simultaneous activation of different memory systems. Recently, we have reported that a complex ecological learning task (requiring the simultaneous activation of several cognitive functions), intensively administered at bedtime, improves daytime sleep continuity and stability, possibly as a result of ongoing memory processes. To follow up our previous study, here we aimed to extend these findings to a night paradigm and to test whether a similar post-training sleep improvement may be obtained in a sample of individuals with sleep complaints. Specifically, our focus was on post-training changes in objective and subjective sleep quality. Furthermore, we compared overnight performance changes with those obtained over a wake retention period, in order to address the possible differential effect of sleep and wake on memory processes. Method: After a habituation night, twenty-one subjects (F=15, mean age: 27.5±7.7 years, all bad sleepers according to the Pittsburgh Sleep Quality Index) underwent conventional polygraphic recording under three conditions: 1) BL, baseline night sleep; 2) post-active control sleep (AC), a sleep episode preceded by a non-learning control task; 3) post-training sleep (TR), a sleep episode preceded by a complex ecological task. The same task as in TR was administered in a Wake condition (W), in which the retention period between training sessions corresponded to the duration of the subject’s baseline sleep time. Subjects underwent AC, TR and W conditions in balanced order. The complex cognitive task consisted in a slightly modified version of the famous word game “Ruzzle”. In this game, the player has two minutes to form as many words as possible and reach the highest score achievable with the 16 letters available in a 4x4 grid on an iPad screen. Performance measures were R-WORDS%, i.e., the number of detected words over total available words, and R-SCORE%, i.e., the global score achieved, depending on the number of words found, on their length and on the ability to use the coloured bonus letters which multiply letter or word values. Results: Post-training sleep (TR) showed a reduction in Stage 1 proportion (F=4.39, p=.021; TR<BL and AC) and a significant improvement in sleep continuity, stability and organization, as expressed by: a decrease of total (F=4.90, p=.014, BL>TR and AC) and brief awakenings frequency (F=5.89, p=.007, BL>TR and AC), decreased frequency of arousals (F=6.25, p=.005; TR<BL and AC), microarousals (F=3.63, p=.050; TR<BL), state transitions (F=10.16, p<.001; BL>TR and AC) and functional uncertainty (FU) periods (F=14.23, p<.001; BL>TR and AC), as well as a reduction of time spent in FU periods (F=515.33, p<.001; BL>TR and AC); an increase in the number of NREM-REM cycles (F=4.51, p=.019; TR>BL and AC), and of time spent in cycles (F=4.77, p=.015; TR>BL and AC). This improvement in objective sleep quality was paralleled by that in subjective ratings, assessed through the Self-Rating Scale for Sleep and Awakenings Quality (χ2=9.13, p=.010; TR<BL). No other sleep measure displayed significant changes between conditions. Furthermore, the comparison of R-SCORE% changes between the TR and W conditions yielded a significant sleep effect (t=5.38, p<.001; TR>W), while the opposite effect emerged for the R-WORDS% (t=-2.96, p=.01; W>TR). Conclusions: Our results extend previous findings on post-training changes in sleep continuity, stability and organization to a sample of bad sleepers; also, they show that objective sleep improvement may be reflected in subjective sleep quality perception. Interestingly, the active control task also produced improvements in some of these features, prompting future investigations on the contribution to post-training sleep changes of additional factors not specifically linked to learning processes. As for performance, the finding of a significant sleep effect for the more complex performance measure (R-SCORE%) suggests that sleep preferentially promotes effective learning of elaborate cognitive strategies rather than that of simpler cognitive processes. In conclusion, in light of the importance of non-pharmacological treatments for sleep disturbances, this study offers the possibility to further explore planned cognitive training as a low-cost treatment strategy to improve sleep quality.

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