title: Sleep-dependent consolidation of face recognition and its relationship to REM sleep duration, REM density and Stage 2 sleep spindles.
abstract: Face recognition is a highly specialized capability that has implicit and explicit memory components. Studies show that learning tasks with facial components are dependent on rapid eye movement and non-rapid eye movement sleep features, including rapid eye movement sleep density and fast sleep spindles. This study aimed to investigate the relationship between sleep-dependent consolidation of memory for faces and partial rapid eye movement sleep deprivation, rapid eye movement density, and fast and slow non-rapid eye movement sleep spindles. Fourteen healthy participants spent 1 night each in the laboratory. Prior to bed they completed a virtual reality task in which they interacted with computer-generated characters. Half of the participants (REMD group) underwent a partial rapid eye movement sleep deprivation protocol and half (CTL group) had a normal amount of rapid eye movement sleep. Upon awakening, they completed a face recognition task that contained a mixture of previously encountered faces from the task and new faces. Rapid eye movement density and fast and slow sleep spindles were detected using in-house software. The REMD group performed worse than the CTL group on the face recognition task; however, rapid eye movement duration and rapid eye movement density were not related to task performance. Fast and slow sleep spindles showed differential relationships to task performance, with fast spindles being positively and slow spindles negatively correlated with face recognition. The results support the notion that rapid eye movement and non-rapid eye movement sleep characteristics play complementary roles in face memory consolidation. This study also raises the possibility that fast and slow spindles contribute in opposite ways to sleep-dependent memory consolidation.
authors.affiliation: Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, Canada.|Biomedical Sciences, University of Montreal, Montreal, Canada.
authors.forename: Elizaveta
authors.identifier: 0000-0002-3733-8676
authors.initials: E
authors.lastname: Solomonova
authors.affiliation: Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, Canada.
authors.forename: Philippe
authors.initials: P
authors.lastname: Stenstrom
authors.affiliation: Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, Canada.|Institut d'Enseignement à Distance de l'Université Paris 8, Saint-Denis, France.
authors.forename: Emilie
authors.initials: E
authors.lastname: Schon
authors.affiliation: Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, Canada.|Institut d'Enseignement à Distance de l'Université Paris 8, Saint-Denis, France.
authors.forename: Alexandra
authors.initials: A
authors.lastname: Duquette
authors.affiliation: Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, Canada.|Psychology, Concordia University, Montreal, Canada.
authors.forename: Simon
authors.initials: S
authors.lastname: Dubé
authors.affiliation: Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, Canada.|École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
authors.forename: Christian
authors.identifier: 0000-0002-3149-4934
authors.initials: C
authors.lastname: O'Reilly
authors.affiliation: Center for Advanced Research in Sleep Medicine, University of Montreal, Montreal, Canada.|Psychiatry, University of Montreal, Montreal, Canada.
authors.forename: Tore
authors.identifier: 0000-0002-9372-8652
authors.initials: T
authors.lastname: Nielsen
mesh_terms: D000066499:Facial Recognition / Q000502:physiology*; D064368:Healthy Volunteers; D006801:Humans; D000069077:Memory Consolidation / Q000502:physiology*; D017286:Polysomnography; D012892:Sleep Deprivation / Q000503:physiopathology; D012894:Sleep Stages / Q000502:physiology*; D012895:Sleep, REM / Q000502:physiology*; D013997:Time Factors
keywords: NREM sleep; REM deprivation; computer-generated characters; learning; sleep microarchitecture