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Cumming D, Kozhemiako N, Thurm AE, Farmer CA, Purcell S, Buckley AW. Spindle chirp and other sleep oscillatory features in young children with autism. Sleep Med 2024; 119:320-328. [PMID: 38733760 DOI: 10.1016/j.sleep.2024.05.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 05/01/2024] [Accepted: 05/02/2024] [Indexed: 05/13/2024]
Abstract
OBJECTIVES To determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism. METHODS Automated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD). RESULTS Posterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient. CONCLUSIONS For the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.
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Affiliation(s)
- Drew Cumming
- National Institute of Mental Health, NIH, Bethesda, MD, USA
| | | | - Audrey E Thurm
- National Institute of Mental Health, NIH, Bethesda, MD, USA
| | | | - Shaun Purcell
- Brigham and Women's Hospital & Harvard Medical School, Boston, MA, USA
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2
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Gorgoni M, Giuliani G, Fratino M, Di Piero V. The objective assessment of sleep in cluster headache: State of the art and future directions. J Sleep Res 2024; 33:e14103. [PMID: 37963453 DOI: 10.1111/jsr.14103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 10/10/2023] [Accepted: 10/30/2023] [Indexed: 11/16/2023]
Abstract
Several lines of evidence suggest that cluster headache is related to chronobiology and sleep. Nevertheless, the nature of such a relationship is unclear. In this view, the objective evaluation of sleep in cluster headache has strong theoretical and clinical relevance. Here, we provide an in-depth narrative review of the literature on objective sleep assessment in cluster headache. We found that only a small number of studies (N = 12) focused on this topic. The key research aims were directed to assess: (a) the relationship between cluster headache and sleep breathing disorders; (b) the temporal relationship between sleep stages/events and cluster headache attacks; (c) sleep macrostructure in patients with cluster headache. No studies considered sleep microstructure. The reviewed studies are heterogeneous, conducted by a few research groups, and often characterised by relevant methodological flaws. Results are substantially inconclusive considering the main hypothesis. We outline several methodological points that should be considered for future research, and suggest that evaluating sleep microstructure, local sleep electrophysiology and actigraphic measures may strongly increase knowledge on the relationship between sleep and cluster headache.
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Affiliation(s)
- Maurizio Gorgoni
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- Body and Action Lab, IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Giada Giuliani
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Mariangela Fratino
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
| | - Vittorio Di Piero
- Department of Human Neurosciences, Sapienza University of Rome, Rome, Italy
- University Consortium for Adaptive Disorders and Head Pain (UCADH), Pavia, Italy
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3
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Kozhemiako N, Buckley AW, Chervin RD, Redline S, Purcell SM. Mapping neurodevelopment with sleep macro- and micro-architecture across multiple pediatric populations. Neuroimage Clin 2023; 41:103552. [PMID: 38150746 PMCID: PMC10788305 DOI: 10.1016/j.nicl.2023.103552] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 10/30/2023] [Accepted: 12/12/2023] [Indexed: 12/29/2023]
Abstract
Profiles of sleep duration and timing and corresponding electroencephalographic activity reflect brain changes that support cognitive and behavioral maturation and may provide practical markers for tracking typical and atypical neurodevelopment. To build and evaluate a sleep-based, quantitative metric of brain maturation, we used whole-night polysomnography data, initially from two large National Sleep Research Resource samples, spanning childhood and adolescence (total N = 4,013, aged 2.5 to 17.5 years): the Childhood Adenotonsillectomy Trial (CHAT), a research study of children with snoring without neurodevelopmental delay, and Nationwide Children's Hospital (NCH) Sleep Databank, a pediatric sleep clinic cohort. Among children without neurodevelopmental disorders (NDD), sleep metrics derived from the electroencephalogram (EEG) displayed robust age-related changes consistently across datasets. During non-rapid eye movement (NREM) sleep, spindles and slow oscillations further exhibited characteristic developmental patterns, with respect to their rate of occurrence, temporal coupling and morphology. Based on these metrics in NCH, we constructed a model to predict an individual's chronological age. The model performed with high accuracy (r = 0.93 in the held-out NCH sample and r = 0.85 in a second independent replication sample - the Pediatric Adenotonsillectomy Trial for Snoring (PATS)). EEG-based age predictions reflected clinically meaningful neurodevelopmental differences; for example, children with NDD showed greater variability in predicted age, and children with Down syndrome or intellectual disability had significantly younger brain age predictions (respectively, 2.1 and 0.8 years less than their chronological age) compared to age-matched non-NDD children. Overall, our results indicate that sleep architectureoffers a sensitive window for characterizing brain maturation, suggesting the potential for scalable, objective sleep-based biomarkers to measure neurodevelopment.
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Affiliation(s)
- N Kozhemiako
- Brigham and Women's Hospital & Harvard Medical School, Boston, MA, USA
| | - A W Buckley
- Sleep & Neurodevelopment Core, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - R D Chervin
- Sleep Disorders Center and Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - S Redline
- Brigham and Women's Hospital & Harvard Medical School, Boston, MA, USA; Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - S M Purcell
- Brigham and Women's Hospital & Harvard Medical School, Boston, MA, USA.
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Lucarini V, Alouit A, Yeh D, Le Coq J, Savatte R, Charre M, Louveau C, Houamri MB, Penaud S, Gaston-Bellegarde A, Rio S, Drouet L, Elbaz M, Becchio J, Pourchet S, Pruvost-Robieux E, Marchi A, Moyal M, Lefebvre A, Chaumette B, Grice M, Lindberg PG, Dupin L, Piolino P, Lemogne C, Léger D, Gavaret M, Krebs MO, Iftimovici A. Neurophysiological explorations across the spectrum of psychosis, autism, and depression, during wakefulness and sleep: protocol of a prospective case-control transdiagnostic multimodal study (DEMETER). BMC Psychiatry 2023; 23:860. [PMID: 37990173 PMCID: PMC10662684 DOI: 10.1186/s12888-023-05347-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 11/03/2023] [Indexed: 11/23/2023] Open
Abstract
BACKGROUND Quantitative electroencephalography (EEG) analysis offers the opportunity to study high-level cognitive processes across psychiatric disorders. In particular, EEG microstates translate the temporal dynamics of neuronal networks throughout the brain. Their alteration may reflect transdiagnostic anomalies in neurophysiological functions that are impaired in mood, psychosis, and autism spectrum disorders, such as sensorimotor integration, speech, sleep, and sense of self. The main questions this study aims to answer are as follows: 1) Are EEG microstate anomalies associated with clinical and functional prognosis, both in resting conditions and during sleep, across psychiatric disorders? 2) Are EEG microstate anomalies associated with differences in sensorimotor integration, speech, sense of self, and sleep? 3) Can the dynamic of EEG microstates be modulated by a non-drug intervention such as light hypnosis? METHODS This prospective cohort will include a population of adolescents and young adults, aged 15 to 30 years old, with ultra-high-risk of psychosis (UHR), first-episode psychosis (FEP), schizophrenia (SCZ), autism spectrum disorder (ASD), and major depressive disorder (MDD), as well as healthy controls (CTRL) (N = 21 × 6), who will be assessed at baseline and after one year of follow-up. Participants will undergo deep phenotyping based on psychopathology, neuropsychological assessments, 64-channel EEG recordings, and biological sampling at the two timepoints. At baseline, the EEG recording will also be coupled to a sensorimotor task and a recording of the characteristics of their speech (prosody and turn-taking), a one-night polysomnography, a self-reference effect task in virtual reality (only in UHR, FEP, and CTRL). An interventional ancillary study will involve only healthy controls, in order to assess whether light hypnosis can modify the EEG microstate architecture in a direction opposite to what is seen in disease. DISCUSSION This transdiagnostic longitudinal case-control study will provide a multimodal neurophysiological assessment of clinical dimensions (sensorimotor integration, speech, sleep, and sense of self) that are disrupted across mood, psychosis, and autism spectrum disorders. It will further test the relevance of EEG microstates as dimensional functional biomarkers. TRIAL REGISTRATION ClinicalTrials.gov Identifier NCT06045897.
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Affiliation(s)
- Valeria Lucarini
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Pathophysiology of psychiatric disorders", GDR 3557-Institut de Psychiatrie, 102-108 Rue de la Santé, Paris, 75014, France
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Anaëlle Alouit
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Stroke: from prognostic determinants and translational research to personalized interventions", Paris, 75014, France
| | - Delphine Yeh
- Laboratoire Mémoire, Cerveau et Cognition, UR7536, Université Paris Cité, Boulogne-Billancourt, F-92100, France
| | - Jeanne Le Coq
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Romane Savatte
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Mylène Charre
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Cécile Louveau
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Meryem Benlaifa Houamri
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Sylvain Penaud
- Laboratoire Mémoire, Cerveau et Cognition, UR7536, Université Paris Cité, Boulogne-Billancourt, F-92100, France
| | - Alexandre Gaston-Bellegarde
- Laboratoire Mémoire, Cerveau et Cognition, UR7536, Université Paris Cité, Boulogne-Billancourt, F-92100, France
| | - Stéphane Rio
- Centre du Sommeil et de la Vigilance, AP-HP, Hôtel-Dieu, Paris, France
| | - Laurent Drouet
- Centre du Sommeil et de la Vigilance, AP-HP, Hôtel-Dieu, Paris, France
| | - Maxime Elbaz
- Centre du Sommeil et de la Vigilance, AP-HP, Hôtel-Dieu, Paris, France
| | - Jean Becchio
- Collège International de Thérapies d'orientation de l'Attention et de la Conscience (CITAC), Paris, France
| | - Sylvain Pourchet
- Collège International de Thérapies d'orientation de l'Attention et de la Conscience (CITAC), Paris, France
| | - Estelle Pruvost-Robieux
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Stroke: from prognostic determinants and translational research to personalized interventions", Paris, 75014, France
- Service de Neurophysiologie Clinique, GHU Paris Psychiatrie et Neurosciences, Paris, France
| | - Angela Marchi
- Epileptology and Cerebral Rhythmology, APHM, Timone Hospital, Marseille, France
| | - Mylène Moyal
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Pathophysiology of psychiatric disorders", GDR 3557-Institut de Psychiatrie, 102-108 Rue de la Santé, Paris, 75014, France
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Aline Lefebvre
- Department of Child and Adolescent Psychiatry, Fondation Vallee, UNIACT Neurospin CEA - INSERM UMR 1129, Universite Paris Saclay, Gentilly, France
| | - Boris Chaumette
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Pathophysiology of psychiatric disorders", GDR 3557-Institut de Psychiatrie, 102-108 Rue de la Santé, Paris, 75014, France
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Martine Grice
- IfL-Phonetics, University of Cologne, Cologne, Germany
| | - Påvel G Lindberg
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Stroke: from prognostic determinants and translational research to personalized interventions", Paris, 75014, France
| | - Lucile Dupin
- INCC UMR 8002, CNRS, Université Paris Cité, Paris, F-75006, France
| | - Pascale Piolino
- Laboratoire Mémoire, Cerveau et Cognition, UR7536, Université Paris Cité, Boulogne-Billancourt, F-92100, France
| | - Cédric Lemogne
- Inserm, INRAE, Center for Research in Epidemiology and StatisticS (CRESS), Service de Psychiatrie de l'adulte, AP-HP, Hôpital Hôtel-Dieu, Université Paris Cité and Université Sorbonne Paris Nord, Paris, France
| | - Damien Léger
- Centre du Sommeil et de la Vigilance, AP-HP, Hôtel-Dieu, Paris, France
- VIFASOM, ERC 7330, Université Paris Cité, Paris, France
| | - Martine Gavaret
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Stroke: from prognostic determinants and translational research to personalized interventions", Paris, 75014, France
- Service de Neurophysiologie Clinique, GHU Paris Psychiatrie et Neurosciences, Paris, France
| | - Marie-Odile Krebs
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Pathophysiology of psychiatric disorders", GDR 3557-Institut de Psychiatrie, 102-108 Rue de la Santé, Paris, 75014, France
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France
| | - Anton Iftimovici
- Université Paris Cité, Institute of Psychiatry and Neuroscience of Paris (IPNP), INSERM U1266, Team "Pathophysiology of psychiatric disorders", GDR 3557-Institut de Psychiatrie, 102-108 Rue de la Santé, Paris, 75014, France.
- GHU Paris Psychiatrie et Neurosciences, Pôle Hospitalo-Universitaire d'évaluation, Prévention, et Innovation Thérapeutique (PEPIT), Paris, France.
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5
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Cumming D, Kozhemiako N, Thurm AE, Farmer CA, Purcell SW, Buckley AW. Spindle Chirp and other Sleep Oscillatory Features in Young Children with Autism. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.15.545095. [PMID: 37398218 PMCID: PMC10312722 DOI: 10.1101/2023.06.15.545095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Objectives To determine whether spindle chirp and other sleep oscillatory features differ in young children with and without autism. Methods Automated processing software was used to re-assess an extant set of polysomnograms representing 121 children (91 with autism [ASD], 30 typically-developing [TD]), with an age range of 1.35-8.23 years. Spindle metrics, including chirp, and slow oscillation (SO) characteristics were compared between groups. SO and fast and slow spindle (FS, SS) interactions were also investigated. Secondary analyses were performed assessing behavioural data associations, as well as exploratory cohort comparisons to children with non-autism developmental delay (DD). Results Posterior FS and SS chirp was significantly more negative in ASD than TD. Both groups had comparable intra-spindle frequency range and variance. Frontal and central SO amplitude were decreased in ASD. In contrast to previous manual findings, no differences were detected in other spindle or SO metrics. The ASD group displayed a higher parietal coupling angle. No differences were observed in phase-frequency coupling. The DD group demonstrated lower FS chirp and higher coupling angle than TD. Parietal SS chirp was positively associated with full developmental quotient. Conclusions For the first time spindle chirp was investigated in autism and was found to be significantly more negative than in TD in this large cohort of young children. This finding strengthens previous reports of spindle and SO abnormalities in ASD. Further investigation of spindle chirp in healthy and clinical populations across development will help elucidate the significance of this difference and better understand this novel metric.
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Affiliation(s)
- D Cumming
- National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - N Kozhemiako
- Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA
| | - AE Thurm
- National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - CA Farmer
- National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - SW Purcell
- Brigham and Women’s Hospital & Harvard Medical School, Boston, MA, USA
| | - AW Buckley
- National Institute of Mental Health, NIH, Bethesda, MD, USA
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6
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Lukarski D, Petkoski S, Ji P, Stankovski T. Delta-alpha cross-frequency coupling for different brain regions. CHAOS (WOODBURY, N.Y.) 2023; 33:103126. [PMID: 37844293 DOI: 10.1063/5.0157979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2023] [Accepted: 09/26/2023] [Indexed: 10/18/2023]
Abstract
Neural interactions occur on different levels and scales. It is of particular importance to understand how they are distributed among different neuroanatomical and physiological relevant brain regions. We investigated neural cross-frequency couplings between different brain regions according to the Desikan-Killiany brain parcellation. The adaptive dynamic Bayesian inference method was applied to EEG measurements of healthy resting subjects in order to reconstruct the coupling functions. It was found that even after averaging over all subjects, the mean coupling function showed a characteristic waveform, confirming the direct influence of the delta-phase on the alpha-phase dynamics in certain brain regions and that the shape of the coupling function changes for different regions. While the averaged coupling function within a region was of similar form, the region-averaged coupling function was averaged out, which implies that there is a common dependence within separate regions across the subjects. It was also found that for certain regions the influence of delta on alpha oscillations is more pronounced and that oscillations that influence other are more evenly distributed across brain regions than the influenced oscillations. When presenting the information on brain lobes, it was shown that the influence of delta emanating from the brain as a whole is greatest on the alpha oscillations of the cingulate frontal lobe, and at the same time the influence of delta from the cingulate parietal brain lobe is greatest on the alpha oscillations of the whole brain.
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Affiliation(s)
- Dushko Lukarski
- Faculty of Medicine, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia
- University Clinic for Radiotherapy and Oncology, 1000 Skopje, Macedonia
| | - Spase Petkoski
- Aix Marseille Univ, INSERM, Inst Neurosci Syst (INS), 13005 Marseille, France
| | - Peng Ji
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, 200433 Shanghai, China
| | - Tomislav Stankovski
- Faculty of Medicine, Ss. Cyril and Methodius University, 1000 Skopje, Macedonia
- Department of Physics, Lancaster University, LA1 4YB Lancaster, United Kingdom
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7
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Giambersio D, Marzulli L, Margari L, Matera E, Nobili L, De Grandis E, Cordani R, Barbieri A, Peschechera A, Margari A, Petruzzelli MG. Correlations between Sleep Features and Iron Status in Children with Neurodevelopmental Disorders: A Cross-Sectional Study. J Clin Med 2023; 12:4949. [PMID: 37568350 PMCID: PMC10420017 DOI: 10.3390/jcm12154949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 07/24/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023] Open
Abstract
A high prevalence of sleep disturbances has been reported in children with neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and intellectual disability (ID). The etiology of sleep disorders in these children is heterogeneous and, recently, iron deficiency has received increasing attention. This study aims to investigate sleep features in children with NDDs and to explore a possible correlation between serum iron status biomarkers and qualitative features of sleep. We included 4- to 12-year-old children with a diagnosis of ASD, ADHD, or ID and assessed their sleep features through the children's sleep habits questionnaire (CSHQ). Venous blood samples were collected to investigate ferritin, transferrin, and iron levels. The mean CSHQ total score exceeds the cut-off in all groups of children. In the ASD group, the Parasomnias subscale negatively correlated with serum ferritin levels (Rho = 0.354; p = 0.029). Our findings may suggest the existence of an association between iron status, sleep quality, and neurodevelopmental processes. In clinical practice, sleep assessment should be included in the routine assessment for patients with NDDs. Furthermore, a routine assessment of iron status biomarkers should be recommended for children with NDDs who have sleep disturbances.
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Affiliation(s)
- Donatella Giambersio
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy; (D.G.); (E.D.G.); (R.C.)
- Department of Precision and Regenerative Medicine and Ionian Area (DIMEPRE-J), University of Studies of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Lucia Marzulli
- Department of Translational Biomedicine and Neuroscience (DIBRAIN), University of Studies of Bari “Aldo Moro”, 70124 Bari, Italy (M.G.P.)
| | - Lucia Margari
- Department of Precision and Regenerative Medicine and Ionian Area (DIMEPRE-J), University of Studies of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Emilia Matera
- Department of Precision and Regenerative Medicine and Ionian Area (DIMEPRE-J), University of Studies of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Lino Nobili
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy; (D.G.); (E.D.G.); (R.C.)
- Child Neuropsychiatry Unit, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
| | - Elisa De Grandis
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy; (D.G.); (E.D.G.); (R.C.)
- Child Neuropsychiatry Unit, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
| | - Ramona Cordani
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy; (D.G.); (E.D.G.); (R.C.)
- Child Neuropsychiatry Unit, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
| | - Antonella Barbieri
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health (DINOGMI), University of Genoa, 16132 Genoa, Italy; (D.G.); (E.D.G.); (R.C.)
- Child Neuropsychiatry Unit, IRCCS Istituto Giannina Gaslini, 16147 Genoa, Italy
| | - Antonia Peschechera
- Department of Precision and Regenerative Medicine and Ionian Area (DIMEPRE-J), University of Studies of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Anna Margari
- Interdisciplinary Department of Medicine (DIM), University of Studies of Bari “Aldo Moro”, 70124 Bari, Italy
| | - Maria Giuseppina Petruzzelli
- Department of Translational Biomedicine and Neuroscience (DIBRAIN), University of Studies of Bari “Aldo Moro”, 70124 Bari, Italy (M.G.P.)
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8
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Manasova D, Stankovski T. Neural Cross-Frequency Coupling Functions in Sleep. Neuroscience 2023:S0306-4522(23)00227-0. [PMID: 37225051 DOI: 10.1016/j.neuroscience.2023.05.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 04/27/2023] [Accepted: 05/16/2023] [Indexed: 05/26/2023]
Abstract
The human brain presents a heavily connected complex system. From a relatively fixed anatomy, it can enable a vast repertoire of functions. One important brain function is the process of natural sleep, which alters consciousness and voluntary muscle activity. On neural level, these alterations are accompanied by changes of the brain connectivity. In order to reveal the changes of connectivity associated with sleep, we present a methodological framework for reconstruction and assessment of functional interaction mechanisms. By analyzing EEG (electroencephalogram) recordings from human whole night sleep, first, we applied a time-frequency wavelet transform to study the existence and strength of brainwave oscillations. Then we applied a dynamical Bayesian inference on the phase dynamics in the presence of noise. With this method we reconstructed the cross-frequency coupling functions, which revealed the mechanism of how the interactions occur and manifest. We focus our analysis on the delta-alpha coupling function and observe how this cross-frequency coupling changes during the different sleep stages. The results demonstrated that the delta-alpha coupling function was increasing gradually from Awake to NREM3 (non-rapid eye movement), but only during NREM2 and NREM3 deep sleep it was significant in respect of surrogate data testing. The analysis on the spatially distributed connections showed that this significance is strong only for within the single electrode region and in the front-to-back direction. The presented methodological framework is for the whole-night sleep recordings, but it also carries general implications for other global neural states.
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Affiliation(s)
- Dragana Manasova
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, Paris, France; Université Paris Cité, Paris, France
| | - Tomislav Stankovski
- Faculty of Medicine, Ss Cyril and Methodius University, Skopje 1000, North Macedonia; Department of Physics, Lancaster University, Lancaster LA1 4YB, United Kingdom.
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9
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Wright CJ, Milosavljevic S, Pocivavsek A. The stress of losing sleep: Sex-specific neurobiological outcomes. Neurobiol Stress 2023; 24:100543. [PMID: 37252645 PMCID: PMC10209346 DOI: 10.1016/j.ynstr.2023.100543] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 03/20/2023] [Accepted: 05/06/2023] [Indexed: 05/31/2023] Open
Abstract
Sleep is a vital and evolutionarily conserved process, critical to daily functioning and homeostatic balance. Losing sleep is inherently stressful and leads to numerous detrimental physiological outcomes. Despite sleep disturbances affecting everyone, women and female rodents are often excluded or underrepresented in clinical and pre-clinical studies. Advancing our understanding of the role of biological sex in the responses to sleep loss stands to greatly improve our ability to understand and treat health consequences of insufficient sleep. As such, this review discusses sex differences in response to sleep deprivation, with a focus on the sympathetic nervous system stress response and activation of the hypothalamic-pituitary-adrenal (HPA) axis. We review sex differences in several stress-related consequences of sleep loss, including inflammation, learning and memory deficits, and mood related changes. Focusing on women's health, we discuss the effects of sleep deprivation during the peripartum period. In closing, we present neurobiological mechanisms, including the contribution of sex hormones, orexins, circadian timing systems, and astrocytic neuromodulation, that may underlie potential sex differences in sleep deprivation responses.
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Affiliation(s)
| | | | - Ana Pocivavsek
- Corresponding author. Pharmacology, Physiology, and Neuroscience, USC School of Medicine, Columbia, SC, 29208, USA.
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10
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Mintz Hemed N, Melosh NA. An integrated perspective for the diagnosis and therapy of neurodevelopmental disorders - From an engineering point of view. Adv Drug Deliv Rev 2023; 194:114723. [PMID: 36746077 DOI: 10.1016/j.addr.2023.114723] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/14/2022] [Accepted: 01/29/2023] [Indexed: 02/05/2023]
Abstract
Neurodevelopmental disorders (NDDs) are complex conditions with largely unknown pathophysiology. While many NDD symptoms are familiar, the cause of these disorders remains unclear and may involve a combination of genetic, biological, psychosocial, and environmental risk factors. Current diagnosis relies heavily on behaviorally defined criteria, which may be biased by the clinical team's professional and cultural expectations, thus a push for new biological-based biomarkers for NDDs diagnosis is underway. Emerging new research technologies offer an unprecedented view into the electrical, chemical, and physiological activity in the brain and with further development in humans may provide clinically relevant diagnoses. These could also be extended to new treatment options, which can start to address the underlying physiological issues. When combined with current speech, language, occupational therapy, and pharmacological treatment these could greatly improve patient outcomes. The current review will discuss the latest technologies that are being used or may be used for NDDs diagnosis and treatment. The aim is to provide an inspiring and forward-looking view for future research in the field.
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Affiliation(s)
- Nofar Mintz Hemed
- Department of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA.
| | - Nicholas A Melosh
- Department of Materials Science and Engineering, Stanford University, Stanford, CA 94305, USA
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11
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Lin Y, Wing-Kuen Ling B, Wang W, Hu L, Xu N, Zhou X. Fusion of electroencephalograms at different channels and different activities via multivariate quaternion valued singular spectrum analysis for intellectual and developmental disorder recognition. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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12
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Donnelly NA, Bartsch U, Moulding HA, Eaton C, Marston H, Hall JH, Hall J, Owen MJ, van den Bree MBM, Jones MW. Sleep EEG in young people with 22q11.2 deletion syndrome: A cross-sectional study of slow-waves, spindles and correlations with memory and neurodevelopmental symptoms. eLife 2022; 11:75482. [PMID: 36039635 PMCID: PMC9477499 DOI: 10.7554/elife.75482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 08/12/2022] [Indexed: 11/20/2022] Open
Abstract
Background Young people living with 22q11.2 Deletion Syndrome (22q11.2DS) are at increased risk of schizophrenia, intellectual disability, attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). In common with these conditions, 22q11.2DS is also associated with sleep problems. We investigated whether abnormal sleep or sleep-dependent network activity in 22q11.2DS reflects convergent, early signatures of neural circuit disruption also evident in associated neurodevelopmental conditions. Methods In a cross-sectional design, we recorded high-density sleep EEG in young people (6-20 years) with 22q11.2DS (n=28) and their unaffected siblings (n=17), quantifying associations between sleep architecture, EEG oscillations (spindles and slow waves) and psychiatric symptoms. We also measured performance on a memory task before and after sleep. Results 22q11.2DS was associated with significant alterations in sleep architecture, including a greater proportion of N3 sleep and lower proportions of N1 and REM sleep than in siblings. During sleep, deletion carriers showed broadband increases in EEG power with increased slow-wave and spindle amplitudes, increased spindle frequency and density, and stronger coupling between spindles and slow-waves. Spindle and slow-wave amplitudes correlated positively with overnight memory in controls, but negatively in 22q11.2DS. Mediation analyses indicated that genotype effects on anxiety, ADHD and ASD were partially mediated by sleep EEG measures. Conclusions This study provides a detailed description of sleep neurophysiology in 22q11.2DS, highlighting alterations in EEG signatures of sleep which have been previously linked to neurodevelopment, some of which were associated with psychiatric symptoms. Sleep EEG features may therefore reflect delayed or compromised neurodevelopmental processes in 22q11.2DS, which could inform our understanding of the neurobiology of this condition and be biomarkers for neuropsychiatric disorders. Funding This research was funded by a Lilly Innovation Fellowship Award (UB), the National Institute of Mental Health (NIMH 5UO1MH101724; MvdB), a Wellcome Trust Institutional Strategic Support Fund (ISSF) award (MvdB), the Waterloo Foundation (918-1234; MvdB), the Baily Thomas Charitable Fund (2315/1; MvdB), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment (IMAGINE) (MR/L011166/1; JH, MvdB and MO), MRC grant Intellectual Disability and Mental Health: Assessing Genomic Impact on Neurodevelopment 2 (IMAGINE-2) (MR/T033045/1; MvdB, JH and MO); Wellcome Trust Strategic Award 'Defining Endophenotypes From Integrated Neurosciences' Wellcome Trust (100202/Z/12/Z MO, JH). NAD was supported by a National Institute for Health Research Academic Clinical Fellowship in Mental Health and MWJ by a Wellcome Trust Senior Research Fellowship in Basic Biomedical Science (202810/Z/16/Z). CE and HAM were supported by Medical Research Council Doctoral Training Grants (C.B.E. 1644194, H.A.M MR/K501347/1). HMM and UB were employed by Eli Lilly & Co during the study; HMM is currently an employee of Boehringer Ingelheim Pharma GmbH & Co KG. The views and opinions expressed are those of the author(s), and not necessarily those of the NHS, the NIHR or the Department of Health funders.
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Affiliation(s)
- Nicholas A Donnelly
- Centre for Academic Mental Health, University of Bristol, Bristol, United Kingdom.,Avon and Wiltshire Partnership NHS Mental Health Trust, Avon, United Kingdom
| | - Ullrich Bartsch
- School of Physiology, Pharmacology and Neuroscience, University of Bristol, Bristol, United Kingdom.,Translational Neuroscience, Eli Lilly, Windlesham, United States
| | - Hayley A Moulding
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Christopher Eaton
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Hugh Marston
- Translational Neuroscience, Eli Lilly, Windlesham, United States
| | - Jessica H Hall
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Jeremy Hall
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Michael J Owen
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
| | - Marianne B M van den Bree
- Medical Research Council Centre for Neuropsychiatric Genetics and Genomics, Cardiff University, Cardiff, United Kingdom
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13
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Levin Y, Hosamane NS, McNair TE, Kunnam SS, Philpot BD, Fan Z, Sidorov MS. Evaluation of electroencephalography biomarkers for Angelman syndrome during overnight sleep. Autism Res 2022; 15:1031-1042. [PMID: 35304979 PMCID: PMC9227959 DOI: 10.1002/aur.2709] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2021] [Revised: 01/31/2022] [Accepted: 03/10/2022] [Indexed: 11/13/2022]
Abstract
Angelman syndrome (AS) is a neurodevelopmental disorder caused by loss‐of‐function mutations in the maternal copy of the UBE3A gene. AS is characterized by intellectual disability, impaired speech and motor skills, epilepsy, and sleep disruptions. Multiple treatment strategies to re‐express functional neuronal UBE3A from the dormant paternal allele were successful in rodent models of AS and have now moved to early phase clinical trials in children. Developing reliable and objective AS biomarkers is essential to guide the design and execution of current and future clinical trials. Our prior work quantified short daytime electroencephalograms (EEGs) to define promising biomarkers for AS. Here, we asked whether overnight sleep is better suited to detect AS EEG biomarkers. We retrospectively analyzed EEGs from 12 overnight sleep studies from individuals with AS with age and sex‐matched Down syndrome and neurotypical controls, focusing on low frequency (2–4 Hz) delta rhythms and sleep spindles. Delta EEG rhythms were increased in individuals with AS during all stages of overnight sleep, but overnight sleep did not provide additional benefit over wake in the ability to detect increased delta. Abnormal sleep spindles were not reliably detected in EEGs from individuals with AS during overnight sleep, suggesting that delta rhythms represent a more reliable biomarker. Overall, we conclude that periods of wakefulness are sufficient, and perhaps ideal, to quantify delta EEG rhythms for use as AS biomarkers.
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Affiliation(s)
- Yuval Levin
- Center for Neuroscience Research, Children's National Medical Center, Washington, District of Columbia, USA.,The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA
| | - Nishitha S Hosamane
- Center for Neuroscience Research, Children's National Medical Center, Washington, District of Columbia, USA
| | - Taylor E McNair
- Center for Neuroscience Research, Children's National Medical Center, Washington, District of Columbia, USA
| | - Shrujana S Kunnam
- Center for Neuroscience Research, Children's National Medical Center, Washington, District of Columbia, USA
| | - Benjamin D Philpot
- Department of Cell Biology & Physiology, Carolina Institute for Developmental Disabilities, and UNC Neuroscience Center, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Zheng Fan
- Department of Neurology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Michael S Sidorov
- Center for Neuroscience Research, Children's National Medical Center, Washington, District of Columbia, USA.,Departments of Pediatrics and Pharmacology & Physiology, The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, USA
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14
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Mylonas D, Machado S, Larson O, Patel R, Cox R, Vangel M, Maski K, Stickgold R, Manoach DS. Dyscoordination of non-rapid eye movement sleep oscillations in autism spectrum disorder. Sleep 2022; 45:6505127. [DOI: 10.1093/sleep/zsac010] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 12/13/2021] [Indexed: 11/14/2022] Open
Abstract
Abstract
Study Objectives
Converging evidence from neuroimaging, sleep, and genetic studies suggest that dysregulation of thalamocortical interactions mediated by the thalamic reticular nucleus (TRN) contribute to autism spectrum disorder (ASD). Sleep spindles assay TRN function, and their coordination with cortical slow oscillations (SOs) indexes thalamocortical communication. These oscillations mediate memory consolidation during sleep. In the present study, we comprehensively characterized spindles and their coordination with SOs in relation to memory and age in children with ASD.
Methods
Nineteen children and adolescents with ASD, without intellectual disability, and 18 typically developing (TD) peers, aged 9–17, completed a home polysomnography study with testing on a spatial memory task before and after sleep. Spindles, SOs, and their coordination were characterized during stages 2 (N2) and 3 (N3) non-rapid eye movement sleep.
Results
ASD participants showed disrupted SO-spindle coordination during N2 sleep. Spindles peaked later in SO upstates and their timing was less consistent. They also showed a spindle density (#/min) deficit during N3 sleep. Both groups showed significant sleep-dependent memory consolidation, but their relations with spindle density differed. While TD participants showed the expected positive correlations, ASD participants showed the opposite.
Conclusions
The disrupted SO-spindle coordination and spindle deficit provide further evidence of abnormal thalamocortical interactions and TRN dysfunction in ASD. The inverse relations of spindle density with memory suggest a different function for spindles in ASD than TD. We propose that abnormal sleep oscillations reflect genetically mediated disruptions of TRN-dependent thalamocortical circuit development that contribute to the manifestations of ASD and are potentially treatable.
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Affiliation(s)
- Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Sasha Machado
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Olivia Larson
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychology, University of Pennsylvania, Philadelphia, PA,USA
| | - Rudra Patel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Roy Cox
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Department of Sleep and Cognition, Netherlands Institute for Neuroscience, Amsterdam,The Netherlands
| | - Mark Vangel
- Department of Biostatistics, Massachusetts General Hospital, Harvard Medical School, Boston, MA,USA
| | - Kiran Maski
- Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
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15
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Ricci A, Calhoun SL, He F, Fang J, Vgontzas AN, Liao D, Bixler EO, Younes M, Fernandez-Mendoza J. Association of a novel EEG metric of sleep depth/intensity with attention-deficit/hyperactivity, learning, and internalizing disorders and their pharmacotherapy in adolescence. Sleep 2022; 45:zsab287. [PMID: 34888687 PMCID: PMC8919202 DOI: 10.1093/sleep/zsab287] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 11/17/2021] [Indexed: 01/08/2023] Open
Abstract
STUDY OBJECTIVES Psychiatric/learning disorders are associated with sleep disturbances, including those arising from abnormal cortical activity. The odds ratio product (ORP) is a standardized electroencephalogram metric of sleep depth/intensity validated in adults, while ORP data in youth are lacking. We tested ORP as a measure of sleep depth/intensity in adolescents with and without psychiatric/learning disorders. METHODS Four hundred eighteen adolescents (median 16 years) underwent a 9-hour, in-lab polysomnography. Of them, 263 were typically developing (TD), 89 were unmedicated, and 66 were medicated for disorders including attention-deficit/hyperactivity (ADHD), learning (LD), and internalizing (ID). Central ORP during non-rapid eye movement (NREM) sleep was the primary outcome. Secondary/exploratory outcomes included central and frontal ORP during NREM stages, in the 9-seconds following arousals (ORP-9), in the first and second halves of the night, during REM sleep and wakefulness. RESULTS Unmedicated youth with ADHD/LD had greater central ORP than TD during stage 3 and in central and frontal regions during stage 2 and the second half of the sleep period, while ORP in youth with ADHD/LD on stimulants did not significantly differ from TD. Unmedicated youth with ID did not significantly differ from TD in ORP, while youth with ID on antidepressants had greater central and frontal ORP than TD during NREM and REM sleep, and higher ORP-9. CONCLUSIONS The greater ORP in unmedicated youth with ADHD/LD, and normalized levels in those on stimulants, suggests ORP is a useful metric of decreased NREM sleep depth/intensity in ADHD/LD. Antidepressants are associated with greater ORP/ORP-9, suggesting these medications induce cortical arousability.
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Affiliation(s)
- Anna Ricci
- Sleep Research and Treatment Center, Department of Psychiatry and Behavioral Health, Penn State College of Medicine, Hershey, PA,USA
| | - Susan L Calhoun
- Sleep Research and Treatment Center, Department of Psychiatry and Behavioral Health, Penn State College of Medicine, Hershey, PA,USA
| | - Fan He
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Jidong Fang
- Sleep Research and Treatment Center, Department of Psychiatry and Behavioral Health, Penn State College of Medicine, Hershey, PA,USA
| | - Alexandros N Vgontzas
- Sleep Research and Treatment Center, Department of Psychiatry and Behavioral Health, Penn State College of Medicine, Hershey, PA,USA
| | - Duanping Liao
- Department of Public Health Sciences, Penn State College of Medicine, Hershey, PA, USA
| | - Edward O Bixler
- Sleep Research and Treatment Center, Department of Psychiatry and Behavioral Health, Penn State College of Medicine, Hershey, PA,USA
| | - Magdy Younes
- Sleep Disorders Centre, Department of Medicine, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Julio Fernandez-Mendoza
- Sleep Research and Treatment Center, Department of Psychiatry and Behavioral Health, Penn State College of Medicine, Hershey, PA,USA
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16
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Castelnovo A, Lividini A, Bernardi G, Pezzoli V, Foderaro G, Ramelli GP, Manconi M, Miano S. Sleep Power Topography in Children with Attention Deficit Hyperactivity Disorder (ADHD). CHILDREN (BASEL, SWITZERLAND) 2022; 9:children9020197. [PMID: 35204918 PMCID: PMC8870029 DOI: 10.3390/children9020197] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 01/24/2022] [Accepted: 01/28/2022] [Indexed: 12/20/2022]
Abstract
OBJECTIVE Recent years saw an increasing interest towards sleep microstructure abnormalities in attention-deficit/hyperactivity disorder (ADHD). However, the existing literature on sleep electroencephalographic (EEG) power in ADHD is still controversial, often based on single electrode recordings, and mainly focused on slow wave activity (SWA) during NREM sleep. This study aimed to systematically investigate sleep power topography in all traditional frequency bands, in all sleep stages and across sleep cycles using high-density EEG (HD-EEG). METHOD Thirty drug-naïve children with ADHD (10.5 ± 2.1 years, 21 male) and 23 typically developing (TD) control participants (mean age: 10.2 ± 1.6 years, 13 male) were included in the current analysis. Signal power topography was computed in classical frequency bands during sleep, contrasted between groups and sleep cycles, and correlated with measures of ADHD severity, cognitive functioning and estimated total sleep time. RESULTS Compared to TD subjects, patients with ADHD consistently displayed a widespread increase in low-frequency activity (between 3 and 10 Hz) during NREM sleep, but not during REM sleep and wake before sleep onset. Such a difference involved a wide centro-posterior cluster of channels in the upper SWA range, in Theta, and low-Alpha. Between-group difference was maximal in sleep stage N3 in the first sleep cycle, and positively correlated with average total sleep time. CONCLUSIONS These results support the concept that children with ADHD, compared to TD peers, have a higher sleep pressure and altered sleep homeostasis, which possibly interfere with (and delay) cortical maturation.
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Affiliation(s)
- Anna Castelnovo
- Sleep Medicine Unit, Neurocenter of Southern Switzerland, Ospedale Civico, 6900 Lugano, Switzerland;
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, 6900 Lugano, Switzerland
- University Hospital of Psychiatry and Psychotherapy, University of Bern, 3011 Bern, Switzerland
- Correspondence: (A.C.); (S.M.)
| | - Althea Lividini
- Department of Medical and Surgical Sciences, University of Bologna, 40126 Bologna, Italy;
| | - Giulio Bernardi
- MoMiLab Research Unit, IMT School for Advanced Studies Lucca, 55100 Lucca, Italy;
| | - Valdo Pezzoli
- Department of Pediatrics, Ospedale Civico, 6900 Lugano, Switzerland; (V.P.); (G.F.)
| | - Giuseppe Foderaro
- Department of Pediatrics, Ospedale Civico, 6900 Lugano, Switzerland; (V.P.); (G.F.)
| | - Gian Paolo Ramelli
- Department of Pediatrics, San Giovanni Hospital, 6500 Bellinzona, Switzerland;
| | - Mauro Manconi
- Sleep Medicine Unit, Neurocenter of Southern Switzerland, Ospedale Civico, 6900 Lugano, Switzerland;
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, 6900 Lugano, Switzerland
- Department of Neurology, University Hospital, Inselspital, 3010 Bern, Switzerland
| | - Silvia Miano
- Sleep Medicine Unit, Neurocenter of Southern Switzerland, Ospedale Civico, 6900 Lugano, Switzerland;
- Correspondence: (A.C.); (S.M.)
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17
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Evidence of a maturational disruption in non-rapid eye movement sleep slow wave activity in youth with attention-deficit/hyperactivity, learning and internalizing disorders. Sleep Med 2022; 90:230-237. [PMID: 35217303 PMCID: PMC8923949 DOI: 10.1016/j.sleep.2022.01.026] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 01/13/2022] [Accepted: 01/31/2022] [Indexed: 11/23/2022]
Abstract
BACKGROUND Sleep slow wave activity (SWA) peaks during childhood and declines in the transition to adolescence during typical development (TD). It remains unknown whether this trajectory differs in youth with neuropsychiatric disorders. METHODS We analyzed sleep EEGs of 664 subjects 6 to 21 y (449 TD, 123 unmedicated, 92 medicated) and 114 subjects 7-12 y (median 10.5 y) followed-up at 18-22 y (median 19 y). SWA (0.4-4 Hz) power was calculated during non-rapid eye movement sleep. RESULTS TD and unmedicated youth showed cubic central and frontal SWA trajectories from 6 to 21 y (p-cubic<0.05), with TD youth showing peaks in central SWA at 6.8 y and frontal at 8.2 y. Unmedicated attention-deficit/hyperactivity (ADHD) and/or learning disorders (LD) showed peak central SWA 2 y later (at 9.6 y, coinciding with peak frontal SWA) than TD, followed by a 67% steeper slope by 19 y. Frontal SWA peak and slope in unmedicated ADHD/LD, and that of central and frontal in internalizing disorders (ID), were similar to TD. Unmedicated ADHD/LD did not differ in the longitudinal SWA percent change by 18-22 y; unmedicated ID showed a lower longitudinal change in frontal SWA than TD. Medicated youth showed a linear decline in central and frontal SWA from 6 to 21 y (p-linear<0.05). CONCLUSIONS ADHD/LD youth show a maturational delay and potential topographical disruption in SWA during childhood and steeper decline throughout adolescence, suggesting faster synaptic pruning. Youth with ID experience less changes in frontal SWA by late adolescence. Psychotropic medications may impact the maturational trajectory of SWA, but not the magnitude of developmental decline by late adolescence.
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18
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Covering the Gap Between Sleep and Cognition – Mechanisms and Clinical Examples. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1384:17-29. [PMID: 36217076 DOI: 10.1007/978-3-031-06413-5_2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
A growing number of studies have shown the strong relationship between sleep and different cognitive processes, especially those that involve memory consolidation. Traditionally, these processes were attributed to mechanisms related to the macroarchitecture of sleep, as sleep cycles or the duration of specific stages, such as the REM stage. More recently, the relationship between different cognitive traits and specific waves (sleep spindles or slow oscillations) has been studied. We here present the most important physiological processes induced by sleep, with particular focus on brain electrophysiology. In addition, recent and classical literature were reviewed to cover the gap between sleep and cognition, while illustrating this relationship by means of clinical examples. Finally, we propose that future studies may focus not only on analyzing specific waves, but also on the relationship between their characteristics as potential biomarkers for multiple diseases.
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19
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Page J, Wakschlag LS, Norton ES. Nonrapid eye movement sleep characteristics and relations with motor, memory, and cognitive ability from infancy to preadolescence. Dev Psychobiol 2021; 63:e22202. [PMID: 34813099 PMCID: PMC8898567 DOI: 10.1002/dev.22202] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Revised: 07/31/2021] [Accepted: 09/13/2021] [Indexed: 01/25/2023]
Abstract
Sleep plays a critical role in neural neurodevelopment. Hallmarks of sleep reflected in the electroencephalogram during nonrapid eye movement (NREM) sleep are associated with learning processes, cognitive ability, memory, and motor functioning. Research in adults is well-established; however, the role of NREM sleep in childhood is less clear. Growing evidence suggests the importance of two NREM sleep features: slow-wave activity and sleep spindles. These features may be critical for understanding maturational change and the functional role of sleep during development. Here, we review the literature on NREM sleep from infancy to preadolescence to provide insight into the network dynamics of the developing brain. The reviewed findings show distinct relations between topographical and maturational aspects of slow waves and sleep spindles; however, the direction and consistency of these relationships vary, and associations with cognitive ability remain unclear. Future research investigating the role of NREM sleep and development would benefit from longitudinal approaches, increased control for circadian and homeostatic influences, and in early childhood, studies recording daytime naps and overnight sleep to yield increased precision for detecting age-related change. Such evidence could help explicate the role of NREM sleep and provide putative physiological markers of neurodevelopment.
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Affiliation(s)
- Jessica Page
- Roxelyn and Richard Pepper Department of Communication
Sciences and Disorders, Northwestern University, Evanston, Illinois, USA
- Northwestern University Institute for Innovations in
Developmental Sciences, Chicago, Illinois, USA
| | - Lauren S. Wakschlag
- Northwestern University Institute for Innovations in
Developmental Sciences, Chicago, Illinois, USA
- Department of Medical Social Sciences, Feinberg School of
Medicine, Northwestern, University, Chicago, Illinois, USA
| | - Elizabeth S. Norton
- Roxelyn and Richard Pepper Department of Communication
Sciences and Disorders, Northwestern University, Evanston, Illinois, USA
- Northwestern University Institute for Innovations in
Developmental Sciences, Chicago, Illinois, USA
- Department of Medical Social Sciences, Feinberg School of
Medicine, Northwestern, University, Chicago, Illinois, USA
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20
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Ventura S, Mathieson SR, O'Toole JM, Livingstone V, Ryan MA, Boylan GB. EEG sleep macrostructure and sleep spindles in early infancy. Sleep 2021; 45:6424963. [PMID: 34755881 PMCID: PMC8754499 DOI: 10.1093/sleep/zsab262] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 09/22/2021] [Indexed: 11/29/2022] Open
Abstract
Study Objectives Sleep features in infancy are potential biomarkers for brain maturation but poorly characterized. We describe normative values for sleep macrostructure and sleep spindles at 4–5 months of age. Methods Healthy term infants were recruited at birth and had daytime sleep electroencephalograms (EEGs) at 4–5 months. Sleep staging was performed and five features were analyzed. Sleep spindles were annotated and seven quantitative features were extracted. Features were analyzed across sex, recording time (am/pm), infant age, and from first to second sleep cycles. Results We analyzed sleep recordings from 91 infants, 41% females. Median (interquartile range [IQR]) macrostructure results: sleep duration 49.0 (37.8–72.0) min (n = 77); first sleep cycle duration 42.8 (37.0–51.4) min; rapid eye movement (REM) percentage 17.4 (9.5–27.7)% (n = 68); latency to REM 36.0 (30.5–41.1) min (n = 66). First cycle median (IQR) values for spindle features: number 241.0 (193.0–286.5), density 6.6 (5.7–8.0) spindles/min (n = 77); mean frequency 13.0 (12.8–13.3) Hz, mean duration 2.9 (2.6–3.6) s, spectral power 7.8 (4.7–11.4) µV2, brain symmetry index 0.20 (0.16–0.29), synchrony 59.5 (53.2–63.8)% (n = 91). In males, spindle spectral power (µV2) was 24.5% lower (p = .032) and brain symmetry index 24.2% higher than females (p = .011) when controlling for gestational and postnatal age and timing of the nap. We found no other significant associations between studied sleep features and sex, recording time (am/pm), or age. Spectral power decreased (p < .001) on the second cycle. Conclusion This normative data may be useful for comparison with future studies of sleep dysfunction and atypical neurodevelopment in infancy. Clinical Trial Registration: BABY SMART (Study of Massage Therapy, Sleep And neurodevelopMenT) (BabySMART) URL: https://clinicaltrials.gov/ct2/show/results/NCT03381027?view=results. ClinicalTrials.gov Identifier: NCT03381027
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Affiliation(s)
- Soraia Ventura
- Department of Paediatrics & Child Health, University College Cork, Cork, Ireland.,INFANT Research Centre, University College Cork, Ireland
| | - Sean R Mathieson
- Department of Paediatrics & Child Health, University College Cork, Cork, Ireland.,INFANT Research Centre, University College Cork, Ireland
| | - John M O'Toole
- Department of Paediatrics & Child Health, University College Cork, Cork, Ireland.,INFANT Research Centre, University College Cork, Ireland
| | - Vicki Livingstone
- Department of Paediatrics & Child Health, University College Cork, Cork, Ireland.,INFANT Research Centre, University College Cork, Ireland
| | - Mary-Anne Ryan
- Department of Paediatrics & Child Health, University College Cork, Cork, Ireland.,INFANT Research Centre, University College Cork, Ireland
| | - Geraldine B Boylan
- Department of Paediatrics & Child Health, University College Cork, Cork, Ireland.,INFANT Research Centre, University College Cork, Ireland
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21
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Noorbasha SK, Florence Sudha G. Novel approach to remove Electrical Shift and Linear Trend artifact from single channel EEG. Biomed Phys Eng Express 2021; 7. [PMID: 34584019 DOI: 10.1088/2057-1976/ac2aee] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 09/28/2021] [Indexed: 11/12/2022]
Abstract
Electroencephalogram (EEG) signals are crucial to Brain-Computer Interfacing (BCI). However, these are vulnerable to a variety of unintended artifacts that could negatively impact the precise brain function assessment. This paper provides a new algorithm to eliminate Electrical Shift and Linear Trend artifact (ESLT) in EEG using Singular Spectrum Analysis (SSA) and Enhanced local Polynomial (LP) Approximation-based Total Variation (EPATV). The contaminated single channel EEG is subdivided into multiple bands of frequency components by SSA. In order to acquire all LP and TV components, EPATV filtering is applied over the contaminated component frequency band. Filtered sub-signal is collected by subtracting both the LP and TV components from the component contaminated frequency band. Then, the addition of filtered sub-signal and remaining SSA frequency band components yield the final denoised EEG signal. The effectiveness of the proposed method in this paper is evaluated using the data obtained from three databases and compared with the existing methods. From the extensive simulation results, it is inferred that the algorithm discussed in the paper is effective when compared the existing methods, exhibiting a highest averaged Correlation Coefficient (CC) of 0.9534, averaged Signal to Noise Ratio (SNR) of 10.2208dB, lowest averaged Relative Root Mean Square Error (RRMSE) value 0.2787 and averaged Mean absolute Error (MAE) inαband value of 0.0557. The algorithm presented in this paper may be a viable choice for extracting ESLT artifact from a small streaming section of the EEG without requirement of the initial calibration or enormous EEG data.
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Affiliation(s)
- Sayedu Khasim Noorbasha
- Department of Electronics and Communication Engineering, Pondicherry Engineering College, Puducherry-605014, India
| | - Gnanou Florence Sudha
- Department of Electronics and Communication Engineering, Pondicherry Engineering College, Puducherry-605014, India
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22
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Subjective and Electroencephalographic Sleep Parameters in Children and Adolescents with Autism Spectrum Disorder: A Systematic Review. J Clin Med 2021; 10:jcm10173893. [PMID: 34501341 PMCID: PMC8432113 DOI: 10.3390/jcm10173893] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 08/18/2021] [Accepted: 08/26/2021] [Indexed: 01/01/2023] Open
Abstract
Background: Sleep problems have commonly manifested in children and adolescents with autism spectrum disorder (ASD) with a complex and multifactorial interaction between clinical and etiological components. These disorders are associated with functional impairment, and provoke significant physical and mental affliction. The purpose of this study is to update the existing literature about objective and subjective sleep parameters in children and adolescents with ASD, extrapolating information from polysomnography or sleep electroencephalography, and sleep related questionnaires. Methods: We have conducted a systematic review of case-control studies on this topic, performing a web-based search on PubMed, Scopus and the Web of Science databases according to the Preferred Reporting items for Systematic Review and Meta-analyses (PRISMA) guidelines. Results: Data collected from 20 survey result reports showed that children and adolescents with ASD experienced a higher rate of sleep abnormalities than in typically developing children. The macrostructural sleep parameters that were consistent with subjective parent reported measures unveil a greater percentage of nighttime signs of insomnia. Sleep microstructure patterns, in addition, pointed towards the bidirectional relationship between brain dysfunctions and sleep problems in children with ASD. Conclusions: Today’s literature acknowledges that objective and subjective sleep difficulties are more often recognized in individuals with ASD, so clinicians should assess sleep quality in the ASD clinical population, taking into consideration the potential implications on treatment strategies. It would be worthwhile in future studies to examine how factors, such as age, cognitive level or ASD severity could be related to ASD sleep abnormalities. Future research should directly assess whether sleep alterations could represent a specific marker for atypical brain development in ASD.
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23
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Kurz EM, Conzelmann A, Barth GM, Renner TJ, Zinke K, Born J. How do children with autism spectrum disorder form gist memory during sleep? A study of slow oscillation-spindle coupling. Sleep 2021; 44:zsaa290. [PMID: 33367905 PMCID: PMC8193554 DOI: 10.1093/sleep/zsaa290] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 10/28/2020] [Indexed: 12/12/2022] Open
Abstract
Sleep is assumed to support memory through an active systems consolidation process that does not only strengthen newly encoded representations but also facilitates the formation of more abstract gist memories. Studies in humans and rodents indicate a key role of the precise temporal coupling of sleep slow oscillations (SO) and spindles in this process. The present study aimed at bolstering these findings in typically developing (TD) children, and at dissecting particularities in SO-spindle coupling underlying signs of enhanced gist memory formation during sleep found in a foregoing study in children with autism spectrum disorder (ASD) without intellectual impairment. Sleep data from 19 boys with ASD and 20 TD boys (9-12 years) were analyzed. Children performed a picture-recognition task and the Deese-Roediger-McDermott (DRM) task before nocturnal sleep (encoding) and in the next morning (retrieval). Sleep-dependent benefits for visual-recognition memory were comparable between groups but were greater for gist abstraction (recall of DRM critical lure words) in ASD than TD children. Both groups showed a closely comparable SO-spindle coupling, with fast spindle activity nesting in SO-upstates, suggesting that a key mechanism of memory processing during sleep is fully functioning already at childhood. Picture-recognition at retrieval after sleep was positively correlated to frontocortical SO-fast-spindle coupling in TD children, and less in ASD children. Critical lure recall did not correlate with SO-spindle coupling in TD children but showed a negative correlation (r = -.64, p = .003) with parietal SO-fast-spindle coupling in ASD children, suggesting other mechanisms specifically conveying gist abstraction, that may even compete with SO-spindle coupling.
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Affiliation(s)
- Eva-Maria Kurz
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Psychiatry and Psychotherapy, Tübingen, Germany
- Graduate Training Centre of Neuroscience, International Max Planck Research School, University of Tübingen, Tübingen, Germany
| | - Annette Conzelmann
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Psychiatry and Psychotherapy, Tübingen, Germany
- PFH – Private University of Applied Sciences, Department of Psychology (Clinical Psychology II), Göttingen, Germany
| | - Gottfried Maria Barth
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Psychiatry and Psychotherapy, Tübingen, Germany
| | - Tobias J Renner
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital of Psychiatry and Psychotherapy, Tübingen, Germany
| | - Katharina Zinke
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Jan Born
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
- Werner Reichardt Centre for Integrative Neuroscience, University of Tübingen, Tübingen, Germany
- German Center for Diabetes Research (DZD), Institute for Diabetes Research & Metabolic Diseases of the Helmholtz Center Munich at the University Tübingen (IDM), Tübingen, Germany
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24
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Gagnon K, Bolduc C, Bastien L, Godbout R. REM Sleep EEG Activity and Clinical Correlates in Adults With Autism. Front Psychiatry 2021; 12:659006. [PMID: 34168578 PMCID: PMC8217632 DOI: 10.3389/fpsyt.2021.659006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Accepted: 05/06/2021] [Indexed: 12/02/2022] Open
Abstract
We tested the hypothesis of an atypical scalp distribution of electroencephalography (EEG) activity during Rapid Eye Movement (REM) sleep in young autistic adults. EEG spectral activity and ratios along the anteroposterior axis and across hemispheres were compared in 16 neurotypical (NT) young adults and 17 individuals with autism spectrum disorder (ASD). EEG spectral power was lower in the ASD group over the bilateral central and right parietal (beta activity) as well as bilateral occipital (beta, theta, and total activity) recording sites. The NT group displayed a significant posterior polarity of intra-hemispheric EEG activity while EEG activity was more evenly or anteriorly distributed in ASD participants. No significant inter-hemispheric EEG lateralization was found. Correlations between EEG distribution and ASD symptoms using the Autism Diagnostic Interview-Revised (ADI-R) showed that a higher posterior ratio was associated with a better ADI-R score on communication skills, whereas a higher anterior ratio was related to more restricted interests and repetitive behaviors. EEG activity thus appears to be atypically distributed over the scalp surface in young adults with autism during REM sleep within cerebral hemispheres, and this correlates with some ASD symptoms. These suggests the existence in autism of a common substrate between some of the symptoms of ASD and an atypical organization and/or functioning of the thalamo-cortical loop during REM sleep.
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Affiliation(s)
- Katia Gagnon
- Sleep Laboratory and Clinic, Hôpital en santé mentale Rivière-des-Prairies, Montréal, QC, Canada.,Departement of Psychiatry, Université de Montréal, Montréal, QC, Canada
| | - Christianne Bolduc
- Sleep Laboratory and Clinic, Hôpital en santé mentale Rivière-des-Prairies, Montréal, QC, Canada
| | - Laurianne Bastien
- Sleep Laboratory and Clinic, Hôpital en santé mentale Rivière-des-Prairies, Montréal, QC, Canada.,Departement of Psychology, Université de Montréal, Montréal, QC, Canada
| | - Roger Godbout
- Sleep Laboratory and Clinic, Hôpital en santé mentale Rivière-des-Prairies, Montréal, QC, Canada.,Departement of Psychiatry, Université de Montréal, Montréal, QC, Canada
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25
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Jacobs MM, Merlo S, Briley PM. Sleep duration, insomnia, and stuttering: The relationship in adolescents and young adults. JOURNAL OF COMMUNICATION DISORDERS 2021; 91:106106. [PMID: 34015644 DOI: 10.1016/j.jcomdis.2021.106106] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Revised: 03/31/2021] [Accepted: 04/27/2021] [Indexed: 06/12/2023]
Abstract
PURPOSE Evidence of a linkage between neurodevelopmental stuttering and sleep difficulties has been suggested in studies involving children and adolescents. To further examine the relationship between stuttering and sleep, the current study explored both hours of sleep and insomnia in a longitudinal sample of adolescents and young adults living with stuttering. METHOD The data for this study came from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative survey study following 13,564 US respondents over the course of 20 years. In each of the five survey waves, respondents noted their average hours of sleep. In addition, Wave IV, respondents indicated whether they suffered from insomnia (i.e., difficulty falling or staying asleep). Respondents who indicated stuttering at ages 18-26 (Wave III) and 24-32 (Wave IV) are considered as those with persistent stuttering-the focus of this analysis. Regression analysis assessed the association between stuttering, hours of sleep and insomnia controlling for sex, age, race, education and other demographic characteristics. RESULTS The sample included 261 participants (1.7% of total respondents) who identified themselves as people who stutter, comprised of 169 males and 92 females. Compared to their fluent counterparts, individuals who stutter reported to sleep, on average, 20 min less per night. Additionally, 15% of those who stutter reported difficulties falling or staying asleep almost every day or every day, which is twice as likely as controls. Results were robust to demographic characteristics and co-occurring conditions. CONCLUSIONS Speech-language pathologists should be aware of the association between stuttering and insomnia, as well as the lower average hours of sleep among adolescents and young adults who stutter. The possibility that lower sleep duration and insomnia may affect stuttering daily variability and impair improvement from stuttering are discussed.
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Affiliation(s)
- Molly M Jacobs
- Department of Health Services & Information Management, East Carolina University, 4340E Health Sciences Building, MS 668, Greenville, NC, United States.
| | | | - Patrick M Briley
- Department of Communication Sciences & Disorders, East Carolina University, Greenville, NC, United States
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26
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Gomez-Pilar J, Gutiérrez-Tobal GC, Poza J, Fogel S, Doyon J, Northoff G, Hornero R. Spectral and temporal characterization of sleep spindles-methodological implications. J Neural Eng 2021; 18. [PMID: 33618345 DOI: 10.1088/1741-2552/abe8ad] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Accepted: 02/22/2021] [Indexed: 11/12/2022]
Abstract
Objective. Nested into slow oscillations (SOs) and modulated by their up-states, spindles are electrophysiological hallmarks of N2 sleep stage that present a complex hierarchical architecture. However, most studies have only described spindles in basic statistical terms, which were limited to the spindle itself without analyzing the characteristics of the pre-spindle moments in which the SOs are originated. The aim of this study was twofold: (a) to apply spectral and temporal measures to the pre-spindle and spindle periods, as well as analyze the correlation between them, and (b) to evaluate the potential of these spectral and temporal measures in future automatic detection algorithms.Approach. An automatic spindle detection algorithm was applied to the overnight electroencephalographic recordings of 26 subjects. Ten complementary features (five spectral and five temporal parameters) were computed in the pre-spindle and spindle periods after their segmentation. These features were computed independently in each period and in a time-resolved way (sliding window). After the statistical comparison of both periods, a correlation analysis was used to assess their interrelationships. Finally, a receiver operating-characteristic (ROC) analysis along with a bootstrap procedure was conducted to further evaluate the degree of separability between the pre-spindle and spindle periods.Main results. The results show important time-varying changes in spectral and temporal parameters. The features calculated in pre-spindle and spindle periods are strongly and significantly correlated, demonstrating the association between the pre-spindle characteristics and the subsequent spindle. The ROC analysis exposes that the typical feature used in automatic spindle detectors, i.e. the power in the sigma band, is outperformed by other features, such as the spectral entropy in this frequency range.Significance. The novel features applied here demonstrate their utility as predictors of spindles that could be incorporated into novel algorithms of automatic spindle detectors, in which the analysis of the pre-spindle period becomes relevant for improving their performance. From the clinical point of view, these features may serve as novel precision therapeutic targets to enhance spindle production with the aim of improving memory, cognition, and sleep quality in healthy and clinical populations. The results evidence the need for characterizing spindles in terms beyond power and the spindle period itself to more dynamic measures and the pre-spindle period. Physiologically, these findings suggest that spindles are more than simple oscillations, but nonstable oscillatory bursts embedded in the complex pre-spindle dynamics.
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Affiliation(s)
- Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid, Spain
| | - Gonzalo C Gutiérrez-Tobal
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid, Spain
| | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid, Spain.,IMUVA, Mathematics Research Institute, University of Valladolid, Valladolid, Spain
| | - Stuart Fogel
- School of Psychology, University of Ottawa, Ottawa, Canada.,Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
| | - Julien Doyon
- Functional Neuroimaging Unit, Centre de Recherche de l'institut Universitaire de Gériatrie de 8 Montréal, Montreal, Canada.,McConnell Brain Imaging Centre and Department of Neurology and Neurosurgery, McGill University, Montreal, Canada
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics, Institute of Mental Health Research, University of Ottawa, Ottawa, Canada.,Mental Health Center, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China
| | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, 47011 Valladolid, Spain.,Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid, Spain.,IMUVA, Mathematics Research Institute, University of Valladolid, Valladolid, Spain
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27
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Shahbakhti M, Rodrigues AS, Augustyniak P, Broniec-Wójcik A, Sološenko A, Beiramvand M, Marozas V. SWT-kurtosis based algorithm for elimination of electrical shift and linear trend from EEG signals. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2020.102373] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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28
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Darchia N, Campbell IG, Basishvili T, Eliozishvili M, Tchintcharauli T, Oniani N, Sakhelashvili I, Shetekauri T, Oniani T, Feinberg I. Longitudinal assessment of NREM sleep EEG in typically developing and medication-free ADHD adolescents: first year results. Sleep Med 2021; 80:171-175. [PMID: 33601229 DOI: 10.1016/j.sleep.2021.01.052] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 01/23/2021] [Accepted: 01/25/2021] [Indexed: 10/22/2022]
Abstract
OBJECTIVE Clinical observation and structural MRI studies suggest that delayed brain maturation is a major cause of attention deficit hyperactivity disorder (ADHD). Sleep electroencephalogram (EEG) which exhibits major changes across adolescence provides an opportunity to investigate brain electrophysiology evidence for maturational delay. We present data from an ongoing longitudinal study of sleep EEG in medication-free ADHD and typically developing adolescents to investigate brain electrophysiological evidence for this maturational delay. METHODS Nine adolescents diagnosed with ADHD (combined presentation, DSM-V criteria, mean age 12.39 ± 0.61 years, 2 females), and nine typically developing controls (12.08 ± 0.35 years, 4 females) were recruited. Subjects underwent an adaptation night and all night polysomnography twice yearly at the Laboratory. RESULTS Basic sleep structure did not differ between the ADHD and control groups. In addition, we found no group differences on delta power (p = 0.77), but found a possible trend toward higher theta power (p = 0.057) for the ADHD group. The decline of standardized delta power across the 4 non-rapid eye movement (NREM) periods differed by group (p < 0.05) with the percent delta power in the first NREM period being lower in the ADHD group. CONCLUSIONS Our data support the preponderant evidence that basic sleep structure is unaltered with ADHD. Our data do suggest altered sleep homeostatic recuperative processes in ADHD. The theta findings from the first two recordings are suggestive of a maturational delay associated with ADHD, but follow-up data-points are needed.
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Affiliation(s)
- Nato Darchia
- Tengiz Oniani Laboratory of Sleep-Wakefulness Cycle Study, Ilia State University, Tbilisi, Georgia.
| | - Ian Glenn Campbell
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, USA
| | - Tamar Basishvili
- Tengiz Oniani Laboratory of Sleep-Wakefulness Cycle Study, Ilia State University, Tbilisi, Georgia
| | - Marine Eliozishvili
- Tengiz Oniani Laboratory of Sleep-Wakefulness Cycle Study, Ilia State University, Tbilisi, Georgia
| | | | - Nikoloz Oniani
- Tengiz Oniani Laboratory of Sleep-Wakefulness Cycle Study, Ilia State University, Tbilisi, Georgia
| | - Irine Sakhelashvili
- Tengiz Oniani Laboratory of Sleep-Wakefulness Cycle Study, Ilia State University, Tbilisi, Georgia
| | - Tamar Shetekauri
- Tengiz Oniani Laboratory of Sleep-Wakefulness Cycle Study, Ilia State University, Tbilisi, Georgia
| | - Tengiz Oniani
- Tengiz Oniani Laboratory of Sleep-Wakefulness Cycle Study, Ilia State University, Tbilisi, Georgia
| | - Irwin Feinberg
- Department of Psychiatry and Behavioral Sciences, University of California, Davis, USA
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Sleep-Related Declarative Memory Consolidation in Children and Adolescents with Developmental Dyslexia. Brain Sci 2021; 11:brainsci11010073. [PMID: 33429959 PMCID: PMC7826880 DOI: 10.3390/brainsci11010073] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Revised: 12/31/2020] [Accepted: 01/04/2021] [Indexed: 02/05/2023] Open
Abstract
Sleep has a crucial role in memory processes, and maturational changes in sleep electrophysiology are involved in cognitive development. Albeit both sleep and memory alterations have been observed in Developmental Dyslexia (DD), their relation in this population has been scarcely investigated, particularly concerning topographical aspects. The study aimed to compare sleep topography and associated sleep-related declarative memory consolidation in participants with DD and normal readers (NR). Eleven participants with DD and 18 NR (9–14 years old) underwent a whole-night polysomnography. They were administered a word pair task before and after sleep to assess for declarative memory consolidation. Memory performance and sleep features (macro and microstructural) were compared between the groups, and the intercorrelations between consolidation rate and sleep measures were assessed. DD showed a deeper worsening in memory after sleep compared to NR and reduced slow spindles in occipito-parietal and left fronto-central areas. Our results suggest specific alterations in local sleep EEG (i.e., sleep spindles) and in sleep-dependent memory consolidation processes in DD. We highlight the importance of a topographical approach, which might shed light on potential alteration in regional cortical oscillation dynamics in DD. The latter might represent a target for therapeutic interventions aimed at enhancing cognitive functioning in DD.
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30
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Ruiz-Herrera N, Guillén-Riquelme A, Díaz-Román A, Buela-Casal G. Sleep, academic achievement, and cognitive performance in children with attention-deficit hyperactivity disorder: A polysomnographic study. J Sleep Res 2021; 30:e13275. [PMID: 33410226 DOI: 10.1111/jsr.13275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Revised: 12/20/2020] [Accepted: 12/21/2020] [Indexed: 11/28/2022]
Abstract
The objective of this study was to examine the influence of parent-reported and polysomnography (PSG)-measured sleep patterns on the academic and cognitive performance of children with attention-deficit hyperactivity disorder (ADHD). We assessed 91 children (18 girls) diagnosed with ADHD aged 7-11 years (29 ADHD-Inattentive, 32 ADHD-Hyperactive/Impulsive, and 31 ADHD-Combined). The Paediatric Sleep Questionnaire (PSQ) and Paediatric Daytime Sleepiness Scale (PDSS) were used to assess subjective sleep quality, as perceived by parents, and objective sleep variables were assessed by PSG. Cognitive performance was evaluated using the Wechsler Intelligence Scale for Children (WISC), and the final average grade of the last school year was used as a measure of academic performance. Academic performance was predicted by the following sleep variables: Sleep time, time in bed, night awakenings, and daytime sleepiness. The best predictors of cognitive performance in children with ADHD were rapid eye movement latency, light sleep, periodic limb movements index (PLMs), awakenings, and daytime sleepiness. In conclusion, sleep parameters are closely associated with the academic and cognitive functioning of children with ADHD.
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Affiliation(s)
- Noelia Ruiz-Herrera
- Sleep and Health Promotion Laboratory, Mind, Brain, and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain
| | | | - Amparo Díaz-Román
- Sleep and Health Promotion Laboratory, Mind, Brain, and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain
| | - Gualberto Buela-Casal
- Sleep and Health Promotion Laboratory, Mind, Brain, and Behavior Research Center (CIMCYC), University of Granada, Granada, Spain
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31
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Affiliation(s)
- Sandra Doria Xavier
- Departamento de Psicobiologia, Universidade Federal de São Paulo (UNIFESP), São Paulo, Brazil.,Corresponding author: Sandra Doria Xavier. E-mail:
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32
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Prehn-Kristensen A, Ngo HVV, Lentfer L, Berghäuser J, Brandes L, Schulze L, Göder R, Mölle M, Baving L. Acoustic closed-loop stimulation during sleep improves consolidation of reward-related memory information in healthy children but not in children with attention-deficit hyperactivity disorder. Sleep 2020; 43:5731400. [DOI: 10.1093/sleep/zsaa017] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 01/17/2020] [Indexed: 12/11/2022] Open
Abstract
Abstract
Study Objectives
Slow oscillations (SO) during slow-wave sleep foster the consolidation of declarative memory. Children with attention-deficit hyperactivity disorder (ADHD) display deficits in the sleep-associated consolidation of declarative memory, possibly due to an altered function of SO. The present study aimed at enhancing SO activity using closed-looped acoustic stimulation during slow-wave sleep in children with ADHD.
Methods
A total of 29 male children (14 with ADHD; aged 8–12 years) participated in a double-blind, placebo-controlled study trial. Children spent two experimental nights in a sleep lab, one stimulation night and one sham night. A declarative learning task (word-pair learning) with a reward condition was used as a primary outcome. Secondary outcome variables were a procedural memory (serial reaction time) and working memory (WM; n-back) task. Encoding of declarative and procedural memory took place in the evening before sleep. After sleep, the retrieval took place followed by the n-back task.
Results
The stimulation successfully induced SO activity during sleep in children with and without ADHD. After stimulation, only healthy children performed better on high-rewarded memory items (primary outcome). In contrast, there were indications that only children with ADHD benefitted from the stimulation with respect to procedural as well as WM performance (secondary outcome).
Conclusions
We were able to show that the acoustic closed-loop stimulation can be applied to enhance SO activity in children with and without ADHD. Our data indicate that SO activity during sleep interacts with subsequent memory performance (primary outcome: rewarded declarative memory; secondary outcome: procedural and WM) in children with and without ADHD.
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Affiliation(s)
- Alexander Prehn-Kristensen
- Department of Child and Adolescent Psychiatry and Psychotherapy, Center for Integrative Psychiatry, School of Medicine, Christian-Albrechts-University, Kiel, Germany
| | - Hong-Viet V Ngo
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Luisa Lentfer
- Department of Child and Adolescent Psychiatry and Psychotherapy, Center for Integrative Psychiatry, School of Medicine, Christian-Albrechts-University, Kiel, Germany
| | - Julia Berghäuser
- Department of Child and Adolescent Psychiatry and Psychotherapy, Center for Integrative Psychiatry, School of Medicine, Christian-Albrechts-University, Kiel, Germany
- Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Lena Brandes
- Department of Child and Adolescent Psychiatry and Psychotherapy, Center for Integrative Psychiatry, School of Medicine, Christian-Albrechts-University, Kiel, Germany
| | - Larissa Schulze
- Department of Child and Adolescent Psychiatry and Psychotherapy, Center for Integrative Psychiatry, School of Medicine, Christian-Albrechts-University, Kiel, Germany
| | - Robert Göder
- Department of Psychiatry and Psychotherapy, Center for Integrative Psychiatry, School of Medicine, Christian-Albrechts-University, Kiel, Germany
| | - Matthias Mölle
- Center of Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
| | - Lioba Baving
- Department of Child and Adolescent Psychiatry and Psychotherapy, Center for Integrative Psychiatry, School of Medicine, Christian-Albrechts-University, Kiel, Germany
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