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Mayeli A, Sanguineti C, Ferrarelli F. Recent Evidence of Non-Rapid Eye Movement Sleep Oscillation Abnormalities in Psychiatric Disorders. Curr Psychiatry Rep 2024:10.1007/s11920-024-01544-x. [PMID: 39400693 DOI: 10.1007/s11920-024-01544-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/20/2024] [Indexed: 10/15/2024]
Abstract
PURPOSE OF REVIEW We review recent studies published from 2019 to 2024 examining slow waves and sleep spindles abnormalities across neurodevelopmental, mood, trauma-related, and psychotic disorders using polysomnography and Electroencephalogram (EEG). RECENT FINDINGS Individuals with attention-deficit/hyperactivity disorder (ADHD) showed higher slow-spindle activity, while findings on slow-wave activity were mixed. Individuals with autism spectrum disorder (ASD) showed inconsistent results with some evidence of lower spindle chirp and slow-wave amplitude. Individuals with depression displayed lower slow-wave and spindle parameters mostly in medicated patients. Individuals with post-traumatic stress disorder (PTSD) showed higher spindle frequency and activity, which were associated with their clinical symptoms. Psychotic disorders demonstrated the most consistent alterations, with lower spindle density, amplitude, and duration across illness stages that correlated with patients' symptom severity and cognitive deficits, whereas lower slow-wave measures were present in the early phases of the disorders. Sleep spindle and slow-wave abnormalities are present across psychiatric populations, with the most consistent alterations observed in psychotic disorders. Larger studies with standardized methodologies and longitudinal assessments are needed to establish the potential of these oscillations as neurophysiological biomarkers and/or treatment targets.
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Affiliation(s)
- Ahmad Mayeli
- Department of Psychiatry, University of Pittsburgh, 3501 Forbes Ave, Suite 456, Pittsburgh, PA, 15213, USA
| | - Claudio Sanguineti
- Department of Psychiatry, University of Pittsburgh, 3501 Forbes Ave, Suite 456, Pittsburgh, PA, 15213, USA
- Department of Health Sciences, University of Milan, Milan, Italy
| | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, 3501 Forbes Ave, Suite 456, Pittsburgh, PA, 15213, USA.
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2
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Mayeli A, Ferrarelli F. Respiratory modulation of sleep oscillations: A new frontier in sleep research. Clin Neurophysiol 2024; 166:250-251. [PMID: 39097470 DOI: 10.1016/j.clinph.2024.07.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Accepted: 07/17/2024] [Indexed: 08/05/2024]
Affiliation(s)
- Ahmad Mayeli
- University of Pittsburgh, Department of Psychiatry, United States
| | - Fabio Ferrarelli
- University of Pittsburgh, Department of Psychiatry, United States.
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3
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Ortiz-Cruz EE, Ayala-Guerrero F, Mateos-Salgado EL, Bernal-Hernández J, Carillo-Calvet HA, Jiménez-Andrade JL. Artificial neural network for evaluating sleep spindles and slow waves after transcranial magnetic stimulation in a child with autism. Neurocase 2024; 30:189-197. [PMID: 39629846 DOI: 10.1080/13554794.2024.2436208] [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: 07/20/2023] [Accepted: 11/25/2024] [Indexed: 12/10/2024]
Abstract
Sleep spindles (SS) and slow waves (SW) serve as indicators of the integrity of thalamocortical connections, which are often compromised in individuals with autism spectrum disorder (ASD). Transcranial magnetic stimulation (TMS) can modulate brain activity associated with ASD. This study evaluated the effects of TMS on SS and SW in an 11-year-old male with ASD who received 17 sessions of TMS on the dorsolateral prefrontal cortex. Both SS and SW were detected before and after TMS and were analyzed using self-organizing maps (SOM). Using the SOM, a subset of SS and SW was identified that exhibited structural changes after TMS.
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Affiliation(s)
| | | | | | | | | | - José Luis Jiménez-Andrade
- Faculty of Science, UNAM, Ciudad de México, México
- Complexity Sciences Center, UNAM, Ciudad de México, México
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Ng T, Noh E, Spencer RMC. Does slow oscillation-spindle coupling contribute to sleep-dependent memory consolidation? A Bayesian meta-analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.28.610060. [PMID: 39257832 PMCID: PMC11383665 DOI: 10.1101/2024.08.28.610060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2024]
Abstract
The active system consolidation theory suggests that information transfer between the hippocampus and cortex during sleep underlies memory consolidation. Neural oscillations during sleep, including the temporal coupling between slow oscillations (SO) and sleep spindles (SP), may play a mechanistic role in memory consolidation. However, differences in analytical approaches and the presence of physiological and behavioral moderators have led to inconsistent conclusions. This meta-analysis, comprising 23 studies and 297 effect sizes, focused on four standard phase-amplitude coupling measures including coupling phase, strength, percentage, and SP amplitude, and their relationship with memory retention. We developed a standardized approach to incorporate non-normal circular-linear correlations. We found strong evidence supporting that precise and strong SO-fast SP coupling in the frontal lobe predicts memory consolidation. The strength of this association is mediated by memory type, aging, and dynamic spatio-temporal features, including SP frequency and cortical topography. In conclusion, SO-SP coupling should be considered as a general physiological mechanism for memory consolidation.
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Affiliation(s)
- Thea Ng
- Neuroscience & Behavior Program, Mount Holyoke College
- Department of Mathematics & Statistics, Mount Holyoke College
| | - Eunsol Noh
- Neuroscience & Behavior Program, University of Massachusetts, Amherst
| | - Rebecca M. C. Spencer
- Neuroscience & Behavior Program, University of Massachusetts, Amherst
- Department of Psychological & Brain Sciences, University of Massachusetts, Amherst
- Institute of Applied Life Sciences, University of Massachusetts, Amherst
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5
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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 PMCID: PMC11348284 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] [Grants] [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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Herrera CG, Tarokh L. A Thalamocortical Perspective on Sleep Spindle Alterations in Neurodevelopmental Disorders. CURRENT SLEEP MEDICINE REPORTS 2024; 10:103-118. [PMID: 38764858 PMCID: PMC11096120 DOI: 10.1007/s40675-024-00284-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/01/2024] [Indexed: 05/21/2024]
Abstract
Purpose of Review Neurodevelopmental disorders are a group of conditions that affect the development and function of the nervous system, typically arising early in life. These disorders can have various genetic, environmental, and/or neural underpinnings, which can impact the thalamocortical system. Sleep spindles, brief bursts of oscillatory activity that occur during NREM sleep, provide a unique in vivo measure of the thalamocortical system. In this manuscript, we review the development of the thalamocortical system and sleep spindles in rodent models and humans. We then utilize this as a foundation to discuss alterations in sleep spindle activity in four of the most pervasive neurodevelopmental disorders-intellectual disability, attention deficit hyperactivity disorder, autism, and schizophrenia. Recent Findings Recent work in humans has shown alterations in sleep spindles across several neurodevelopmental disorders. Simultaneously, rodent models have elucidated the mechanisms which may underlie these deficits in spindle activity. This review merges recent findings from these two separate lines of research to draw conclusions about the pathogenesis of neurodevelopmental disorders. Summary We speculate that deficits in the thalamocortical system associated with neurodevelopmental disorders are exquisitely reflected in sleep spindle activity. We propose that sleep spindles may represent a promising biomarker for drug discovery, risk stratification, and treatment monitoring.
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Affiliation(s)
- Carolina Gutierrez Herrera
- Department of Neurology, Inselspital, Bern University Hospital and University of Bern, Rosenbühlgasse 25, Bern, Switzerland
- Center for Experimental Neurology, Department of Neurology, Inselspital University Hospital Bern, University of Bern, Rosenbühlgasse 17, Bern, Switzerland
- Department of Biomedical Research (DBMR), Inselspital University Hospital Bern, University of Bern, Murtenstrasse 24 CH-3008 Bern, Bern, Switzerland
| | - Leila Tarokh
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bolligenstrasse 111, Haus A, 3000, Bern, Switzerland
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bolligenstrasse 111, Haus A, 3000, Bern, Switzerland
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Hong X, Farmer C, Kozhemiako N, Holmes GL, Thompson L, Manwaring S, Thurm A, Buckley A. Differences in Sleep EEG Coherence and Spindle Metrics in Toddlers With and Without Language Delay: A Prospective Observational Study. RESEARCH SQUARE 2024:rs.3.rs-3904113. [PMID: 38410470 PMCID: PMC10896365 DOI: 10.21203/rs.3.rs-3904113/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Background Sleep plays a crucial role in early language development, and sleep disturbances are common in children with neurodevelopmental disorders. Examining sleep microarchitecture in toddlers with and without language delays can offer key insights into neurophysiological abnormalities associated with atypical neurodevelopmental trajectories and potentially aid in early detection and intervention. Methods Here, we investigated electroencephalogram (EEG) coherence and sleep spindles in 16 toddlers with language delay (LD) compared with a group of 39 typically developing (TD) toddlers. The sample was majority male (n = 34, 62%). Participants were aged 12-to-22 months at baseline, and 34 (LD, n=11; TD, n=23) participants were evaluated again at 36 months of age. Results LD toddlers demonstrated increased EEG coherence compared to TD toddlers, with differences most prominent during slow-wave sleep. Within the LD group, lower expressive language skills were associated with higher coherence in REM sleep. Within the TD group, lower expressive language skills were associated with higher coherence in slow-wave sleep. Sleep spindle density, duration, and frequency changed between baseline and follow-up for both groups, with the LD group demonstrating a smaller magnitude of change than the TD group. The direction of change was frequency-dependent for both groups. Conclusions These findings indicate that atypical sleep EEG connectivity and sleep spindle development can be detected in toddlers between 12 and 36 months and offers insights into neurophysiological mechanisms underlying the etiology of neurodevelopmental disorders. Trial registration https://clinicaltrials.gov/study/NCT01339767; Registration date: 4/20/2011.
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Affiliation(s)
- Xinyi Hong
- National Institute of Mental Health Division of Intramural Research Programs: National Institute of Mental Health Intramural Research Program
| | - Cristan Farmer
- National Institute of Mental Health Intramural Research Program
| | | | | | - Lauren Thompson
- Washington State University Elson S Floyd College of Medicine
| | - Stacy Manwaring
- University of Utah Department of Communication Sciences and Disorders
| | - Audrey Thurm
- National Institute of Mental Health Intramural Research Program
| | - Ashura Buckley
- National Institute of Mental Health Intramural Research Program
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Tapia-Rivas NI, Estévez PA, Cortes-Briones JA. A robust deep learning detector for sleep spindles and K-complexes: towards population norms. Sci Rep 2024; 14:263. [PMID: 38167626 PMCID: PMC10762090 DOI: 10.1038/s41598-023-50736-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 12/24/2023] [Indexed: 01/05/2024] Open
Abstract
Sleep spindles (SSs) and K-complexes (KCs) are brain patterns involved in cognitive functions that appear during sleep. Large-scale sleep studies would benefit from precise and robust automatic sleep event detectors, capable of adapting the variability in both electroencephalography (EEG) signals and expert annotation rules. We introduce the Sleep EEG Event Detector (SEED), a deep learning system that outperforms existing approaches in SS and KC detection, reaching an F1-score of 80.5% and 83.7%, respectively, on the MASS2 dataset. SEED transfers well and requires minimal fine-tuning for new datasets and annotation styles. Remarkably, SEED substantially reduces the required amount of annotated data by using a novel pretraining approach that leverages the rule-based detector A7. An analysis of 11,224 subjects revealed that SEED's detections provide better estimates of SS population statistics than existing approaches. SEED is a powerful resource for obtaining sleep-event statistics that could be useful for establishing population norms.
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Affiliation(s)
| | - Pablo A Estévez
- Department of Electrical Engineering, University of Chile, Santiago, Chile.
- Millennium Institute of Intelligent Healthcare Engineering, Santiago, Chile.
- IMPACT, Center of Interventional Medicine for Precision and Advanced Cellular Therapy, Santiago, Chile.
| | - José A Cortes-Briones
- Schizophrenia and Neuropharmacology Research Group at Yale (SNRGY), Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
- Abraham Ribicoff Research Facilities, Connecticut Mental Health Center, New Haven, CT, USA
- VA Connecticut Healthcare System, West Haven, CT, USA
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9
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Myers AM, Rech ME, Baran B, Palmer C, Mylonas D, Alfano CA. Sleep spindle activity is associated with state- and trait-based emotion in healthy school-aged children. Sleep Med 2024; 113:56-60. [PMID: 37984018 DOI: 10.1016/j.sleep.2023.11.009] [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: 07/20/2023] [Revised: 10/12/2023] [Accepted: 11/03/2023] [Indexed: 11/22/2023]
Abstract
BACKGROUND While connections between children's sleep and their daytime functioning are well established, less is known about the microstructural features of sleep that support emotional wellbeing. Investigating these relationships in healthy children may provide insight into adaptive emotional development. We therefore examined associations between non-rapid eye movement (N2) sleep spindles and both state- and trait-based measures of emotion. METHODS A sample of 30 children (7-11 years) without psychiatric disorders completed a baseline assessment, one night of at-home polysomnography (PSG), and an in-lab emotional state assessment the next day including self-reported arousal in response to affective images. Trait-based measures of anxiety and depression as well as savoring, a positive emotion regulatory strategy, were also completed. N2 sleep spindle parameters, including spindle density (number/min) and peak frequency in central regions, were detected using an automated algorithm. RESULTS Greater spindle density was significantly associated with decreased state-based emotional arousal towards negative affective images, and greater spindle peak frequency was associated with greater trait-based use of savoring. However, neither spindle parameter was associated with child anxiety or depressive symptoms. CONCLUSIONS Findings align with and expand on prior research to suggest that N2 sleep spindles support adaptive emotional functioning in school-aged children.
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Affiliation(s)
- Annika M Myers
- Department of Psychology, University of Houston, Health and Biomedical Sciences Building, 4349 Martin Luther King Boulevard, Houston, TX, 77204, USA
| | - Megan E Rech
- Department of Psychology, University of Houston, Health and Biomedical Sciences Building, 4349 Martin Luther King Boulevard, Houston, TX, 77204, USA
| | - Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, 340 Iowa Ave, Iowa City, IA, 52242, USA
| | - Cara Palmer
- Department of Psychology, Montana State University, A.J.M. Johnson Hall, Bozeman, MT, 59715, USA
| | - Dimitrios Mylonas
- Massachusetts General Hospital, Harvard Medical School, 275 Cambridge St., Boston, MA, 02114, USA
| | - Candice A Alfano
- Department of Psychology, University of Houston, Health and Biomedical Sciences Building, 4349 Martin Luther King Boulevard, Houston, TX, 77204, USA.
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Gardner KJ, Wang W, Klerman EB. Altered sleep architecture in children and adolescents with Down syndrome. AMERICAN JOURNAL OF MEDICAL GENETICS. PART C, SEMINARS IN MEDICAL GENETICS 2023; 193:e32073. [PMID: 37870492 PMCID: PMC10905642 DOI: 10.1002/ajmg.c.32073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 10/04/2023] [Accepted: 10/10/2023] [Indexed: 10/24/2023]
Abstract
OBJECTIVE Children with Down syndrome (DS) may experience changes in sleep architecture (i.e., different sleep stages) that then affect waketime functioning, including learning, mood, and disruptive behavior. For designing and testing interventions, it is important to document any differences in sleep architecture in children with DS with and without co-occurring diagnoses, including neuropsychiatric diagnoses and obstructive sleep apnea (OSA). METHODS A retrospective cohort study was performed at Massachusetts General Hospital for children and adolescents with DS who underwent polysomnography (PSG) between August 2016 and July 2022. Patient data collected from the electronic medical record included diagnoses, age at PSG, and PSG report. Statistical analysis included unpaired T tests to test hypotheses about differences in sleep architecture within age groups, and differences between children with DS and a co-occurring diagnosis. One way ANOVA was used to determine statistical significance of OSA severity within patients with DS. RESULTS When compared by age group, those with DS had negative changes in sleep architecture (e.g., less sleep and more wake) when compared to normative data. Within this cohort, having a co-occurring diagnosis of autism resulted in further, negative effects on sleep architecture. 89% of those with DS had diagnosed OSA but only those with severe OSA experienced negative effects on sleep architecture. CONCLUSION Age is an important covariate when studying the sleep of children with DS and neurotypical children. Studies are needed to test whether minimizing the observed differences in sleep architecture will translate to improved learning, mood, and behavioral outcomes, and how treating OSA affects sleep architecture.
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Affiliation(s)
- Kelly J Gardner
- Massachusetts General Hospital/MassGeneral for Children, Boston, Massachusetts, USA
| | - Wei Wang
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Elizabeth B Klerman
- Division of Sleep Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
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11
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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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12
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Baxter BS, Mylonas D, Kwok KS, Talbot CE, Patel R, Zhu L, Vangel M, Stickgold R, Manoach DS. The effects of closed-loop auditory stimulation on sleep oscillatory dynamics in relation to motor procedural memory consolidation. Sleep 2023; 46:zsad206. [PMID: 37531587 PMCID: PMC11009689 DOI: 10.1093/sleep/zsad206] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/13/2023] [Indexed: 08/04/2023] Open
Abstract
STUDY OBJECTIVES Healthy aging and many disorders show reduced sleep-dependent memory consolidation and corresponding alterations in non-rapid eye movement sleep oscillations. Yet sleep physiology remains a relatively neglected target for improving memory. We evaluated the effects of closed-loop auditory stimulation during sleep (CLASS) on slow oscillations (SOs), sleep spindles, and their coupling, all in relation to motor procedural memory consolidation. METHODS Twenty healthy young adults had two afternoon naps: one with auditory stimulation during SO upstates and another with no stimulation. Twelve returned for a third nap with stimulation at variable times in relation to SO upstates. In all sessions, participants trained on the motor sequence task prior to napping and were tested afterward. RESULTS Relative to epochs with no stimulation, upstate stimuli disrupted sleep and evoked SOs, spindles, and SO-coupled spindles. Stimuli that successfully evoked oscillations were delivered closer to the peak of the SO upstate and when spindle power was lower than stimuli that failed to evoke oscillations. Across conditions, participants showed similar significant post-nap performance improvement that correlated with the density of SO-coupled spindles. CONCLUSIONS Despite its strong effects on sleep physiology, CLASS failed to enhance motor procedural memory. Our findings suggest methods to overcome this failure, including better sound calibration to preserve sleep continuity and the use of real-time predictive algorithms to more precisely target SO upstates and to avoid disrupting endogenous SO-coupled spindles and their mnemonic function. They motivate continued development of CLASS as an intervention to manipulate sleep oscillatory dynamics and improve memory.
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Affiliation(s)
- Bryan S Baxter
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Kristi S Kwok
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Christine E Talbot
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Rudra Patel
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Lin Zhu
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mark Vangel
- Department of Biostatistics, Massachusetts General Hospital, Harvard Medical School, 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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13
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O'Hora KP, Schleifer CH, Bearden CE. Sleep in 22q11.2 Deletion Syndrome: Current Findings, Challenges, and Future Directions. Curr Psychiatry Rep 2023; 25:479-491. [PMID: 37721640 PMCID: PMC10627929 DOI: 10.1007/s11920-023-01444-6] [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] [Accepted: 07/28/2023] [Indexed: 09/19/2023]
Abstract
PURPOSE OF REVIEW To summarize current literature available on sleep in 22q11.2 Deletion Syndrome (22q11.2DS; Velocardiofacial or DiGeorge Syndrome), a neurogenetic disorder caused by a hemizygous deletion in a genomic region critical for neurodevelopment. Due to the greatly increased risk of developmental psychiatric disorders (e.g., autism and schizophrenia) in 22q11.2DS, this review focuses on clinical correlates of sleep disturbances and potential neurobiological underpinnings of these relationships. RECENT FINDINGS Sleep disturbances are widely prevalent in 22q11.2DS and are associated with worse behavioral, psychiatric, and physical health outcomes. There are reports of sleep architecture and sleep neurophysiology differences, but the literature is limited by logistical challenges posed by objective sleep measures, resulting in small study samples to date. Sleep disturbances in 22q11.2DS are prevalent and have a substantial impact on well-being. Further investigation of sleep in 22q11.2DS utilizing multimodal sleep assessments has the potential to provide new insight into neurobiological mechanisms and a potential trans-diagnostic treatment target in 22q11.2DS.
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Affiliation(s)
- Kathleen P O'Hora
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, 760 Westwood Plaza, Los Angeles, CA, 90095, USA
- Neuroscience Interdepartmental Program, University of California, Los Angeles, CA, USA
| | - Charles H Schleifer
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, 760 Westwood Plaza, Los Angeles, CA, 90095, USA
- Neuroscience Interdepartmental Program, University of California, Los Angeles, CA, USA
- David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | - Carrie E Bearden
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, University of California, 760 Westwood Plaza, Los Angeles, CA, 90095, USA.
- Department of Psychology, University of California, Los Angeles, CA, USA.
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Yamada T, Watanabe T, Sasaki Y. Are sleep disturbances a cause or consequence of autism spectrum disorder? Psychiatry Clin Neurosci 2023; 77:377-385. [PMID: 36949621 PMCID: PMC10871071 DOI: 10.1111/pcn.13550] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/10/2023] [Accepted: 03/17/2023] [Indexed: 03/24/2023]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core symptoms such as atypical social communication, stereotyped behaviors, and restricted interests. One of the comorbid symptoms of individuals with ASD is sleep disturbance. There are two major hypotheses regarding the neural mechanism underlying ASD, i.e., the excitation/inhibition (E/I) imbalance and the altered neuroplasticity hypotheses. However, the pathology of ASD remains unclear due to inconsistent research results. This paper argues that sleep is a confounding factor, thus, must be considered when examining the pathology of ASD because sleep plays an important role in modulating the E/I balance and neuroplasticity in the human brain. Investigation of the E/I balance and neuroplasticity during sleep might enhance our understanding of the neural mechanisms of ASD. It may also lead to the development of neurobiologically informed interventions to supplement existing psychosocial therapies.
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Affiliation(s)
- Takashi Yamada
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, 02912, USA
| | - Takeo Watanabe
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, 02912, USA
| | - Yuka Sasaki
- Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, Providence, 02912, USA
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Yazdanbakhsh A, Barbas H, Zikopoulos B. Sleep spindles in primates: Modeling the effects of distinct laminar thalamocortical connectivity in core, matrix, and reticular thalamic circuits. Netw Neurosci 2023; 7:743-768. [PMID: 37397882 PMCID: PMC10312265 DOI: 10.1162/netn_a_00311] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 03/01/2023] [Indexed: 10/16/2023] Open
Abstract
Sleep spindles are associated with the beginning of deep sleep and memory consolidation and are disrupted in schizophrenia and autism. In primates, distinct core and matrix thalamocortical (TC) circuits regulate sleep spindle activity through communications that are filtered by the inhibitory thalamic reticular nucleus (TRN); however, little is known about typical TC network interactions and the mechanisms that are disrupted in brain disorders. We developed a primate-specific, circuit-based TC computational model with distinct core and matrix loops that can simulate sleep spindles. We implemented novel multilevel cortical and thalamic mixing, and included local thalamic inhibitory interneurons, and direct layer 5 projections of variable density to TRN and thalamus to investigate the functional consequences of different ratios of core and matrix node connectivity contribution to spindle dynamics. Our simulations showed that spindle power in primates can be modulated based on the level of cortical feedback, thalamic inhibition, and engagement of model core versus matrix, with the latter having a greater role in spindle dynamics. The study of the distinct spatial and temporal dynamics of core-, matrix-, and mix-generated sleep spindles establishes a framework to study disruption of TC circuit balance underlying deficits in sleep and attentional gating seen in autism and schizophrenia.
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Affiliation(s)
- Arash Yazdanbakhsh
- Computational Neuroscience and Vision Lab, Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston, MA, USA
| | - Helen Barbas
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston, MA, USA
- Neural Systems Laboratory, Program in Human Physiology, Department of Health Sciences, College of Health and Rehabilitation Sciences (Sargent College), Boston University, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston University, Boston, MA, USA
| | - Basilis Zikopoulos
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston, MA, USA
- Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston University, Boston, MA, USA
- Human Systems Neuroscience Laboratory, Program in Human Physiology, Department of Health Sciences, College of Health and Rehabilitation Sciences (Sargent College), Boston University, Boston, MA, USA
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Maurer JJ, Choi A, An I, Sathi N, Chung S. Sleep disturbances in autism spectrum disorder: Animal models, neural mechanisms, and therapeutics. Neurobiol Sleep Circadian Rhythms 2023; 14:100095. [PMID: 37188242 PMCID: PMC10176270 DOI: 10.1016/j.nbscr.2023.100095] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 03/16/2023] [Accepted: 04/08/2023] [Indexed: 05/17/2023] Open
Abstract
Sleep is crucial for brain development. Sleep disturbances are prevalent in children with autism spectrum disorder (ASD). Strikingly, these sleep problems are positively correlated with the severity of ASD core symptoms such as deficits in social skills and stereotypic behavior, indicating that sleep problems and the behavioral characteristics of ASD may be related. In this review, we will discuss sleep disturbances in children with ASD and highlight mouse models to study sleep disturbances and behavioral phenotypes in ASD. In addition, we will review neuromodulators controlling sleep and wakefulness and how these neuromodulatory systems are disrupted in animal models and patients with ASD. Lastly, we will address how the therapeutic interventions for patients with ASD improve various aspects of sleep. Together, gaining mechanistic insights into the neural mechanisms underlying sleep disturbances in children with ASD will help us to develop better therapeutic interventions.
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17
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Baran B, Trang Huong Nguyen Q, Mylonas D, Santangelo SL, Manoach DS. Increased resting-state thalamocortical functional connectivity in children and young adults with autism spectrum disorder. Autism Res 2023; 16:271-279. [PMID: 36546577 PMCID: PMC10619334 DOI: 10.1002/aur.2875] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022]
Abstract
There is converging evidence that abnormal thalamocortical interactions contribute to attention deficits and sensory sensitivities in autism spectrum disorder (ASD). However, previous functional MRI studies of thalamocortical connectivity in ASD have produced inconsistent findings in terms of both the direction (hyper vs. hypoconnectivity) and location of group differences. This may reflect, in part, the confounding effects of head motion during scans. In the present study, we investigated resting-state thalamocortical functional connectivity in 8-25 year-olds with ASD and their typically developing (TD) peers. We used pre-scan training, on-line motion correction, and rigorous data quality assurance protocols to minimize motion confounds. ASD participants showed increased thalamic connectivity with temporal cortex relative to TD. Both groups showed similar age-related decreases in thalamic connectivity with occipital cortex, consistent with a process of circuit refinement. Findings of thalamocortical hyperconnectivity in ASD are consistent with other evidence that decreased thalamic inhibition leads to increase and less filtered sensory information reaching the cortex where it disrupts attention and contributes to sensory sensitivity. This literature motivates studies of mechanisms, functional consequences, and treatment of thalamocortical circuit dysfunction in ASD.
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Affiliation(s)
- Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA
| | | | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Susan L. Santangelo
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
- Maine Medical Center Research Institute, Scarborough, ME
- Tufts University School of Medicine, Department of Psychiatry, Boston, MA
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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