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Shimizu R, Wu HT. Unveil sleep spindles with concentration of frequency and time (ConceFT). Physiol Meas 2024; 45:085003. [PMID: 39042095 DOI: 10.1088/1361-6579/ad66aa] [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: 03/12/2024] [Accepted: 07/19/2024] [Indexed: 07/24/2024]
Abstract
Objective.Sleep spindles contain crucial brain dynamics information. We introduce the novel non-linear time-frequency (TF) analysis tool 'Concentration of Frequency and Time' (ConceFT) to create an interpretable automated algorithm for sleep spindle annotation in EEG data and to measure spindle instantaneous frequencies (IFs).Approach.ConceFT effectively reduces stochastic EEG influence, enhancing spindle visibility in the TF representation. Our automated spindle detection algorithm, ConceFT-Spindle (ConceFT-S), is compared to A7 (non-deep learning) and SUMO (deep learning) using Dream and Montreal Archive of Sleep Studies (MASS) benchmark databases. We also quantify spindle IF dynamics.Main results.ConceFT-S achieves F1 scores of 0.765 in Dream and 0.791 in MASS, which surpass A7 and SUMO. We reveal that spindle IF is generally nonlinear.Significance.ConceFT offers an accurate, interpretable EEG-based sleep spindle detection algorithm and enables spindle IF quantification.
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Affiliation(s)
- Riki Shimizu
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, United States of America
| | - Hau-Tieng Wu
- Courant Institute of Mathematical Sciences, New York University, New York, NY 10012, United States of America
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2
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Dwyer GE, Johnsen E, Hugdahl K. NMDAR dysfunction and the regulation of dopaminergic transmission in schizophrenia. Schizophr Res 2024; 271:19-27. [PMID: 39002526 DOI: 10.1016/j.schres.2024.07.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 02/27/2024] [Accepted: 07/07/2024] [Indexed: 07/15/2024]
Abstract
A substantial body of evidence implicates dysfunction in N-methyl-d-aspartate receptors (NMDARs) in the pathophysiology of schizophrenia. This article illustrates how NMDAR dysfunction may give rise to many of the neurobiological phenomena frequently associated with schizophrenia with a particular focus on how NMDAR dysfunction affects the thalamic reticular nucleus (nRT) and pedunculopontine tegmental nucleus (PPTg). Furthermore, this article presents a model for schizophrenia illustrating how dysfunction in the nRT may interrupt prefrontal regulation of midbrain dopaminergic neurons, and how dysfunction in the PPTg may drive increased, irregular burst firing.
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Affiliation(s)
- Gerard Eric Dwyer
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; NORMENT Centre of Excellence, Haukeland University Hospital, Bergen, Norway.
| | - Erik Johnsen
- NORMENT Centre of Excellence, Haukeland University Hospital, Bergen, Norway; Division of Psychiatry, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Kenneth Hugdahl
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway; Division of Psychiatry, Haukeland University Hospital, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway
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3
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Kafashan M, Gupte G, Kang P, Hyche O, Luong AH, Prateek GV, Ju YES, Palanca BJA. A personalized semi-automatic sleep spindle detection (PSASD) framework. J Neurosci Methods 2024; 407:110064. [PMID: 38301832 PMCID: PMC11219251 DOI: 10.1016/j.jneumeth.2024.110064] [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: 07/27/2023] [Revised: 01/19/2024] [Accepted: 01/27/2024] [Indexed: 02/03/2024]
Abstract
BACKGROUND Sleep spindles are distinct electroencephalogram (EEG) patterns of brain activity that have been posited to play a critical role in development, learning, and neurological disorders. Manual scoring for sleep spindles is labor-intensive and tedious but could supplement automated algorithms to resolve challenges posed with either approaches alone. NEW METHODS A Personalized Semi-Automatic Sleep Spindle Detection (PSASD) framework was developed to combine the strength of automated detection algorithms and visual expertise of human scorers. The underlying model in the PSASD framework assumes a generative model for EEG sleep spindles as oscillatory components, optimized to EEG amplitude, with remaining signals distributed into transient and low-frequency components. RESULTS A single graphical user interface (GUI) allows both manual scoring of sleep spindles (model training data) and verification of automatically detected spindles. A grid search approach allows optimization of parameters to balance tradeoffs between precision and recall measures. COMPARISON WITH EXISTING METHODS PSASD outperformed DETOKS in F1-score by 19% and 4% on the DREAMS and P-DROWS-E datasets, respectively. It also outperformed YASA in F1-score by 25% in the P-DROWS-E dataset. Further benchmarking analysis showed that PSASD outperformed four additional widely used sleep spindle detectors in F1-score in the P-DROWS-E dataset. Titration analysis revealed that four 30-second epochs are sufficient to fine-tune the model parameters of PSASD. Associations of frequency, duration, and amplitude of detected sleep spindles matched those previously reported with automated approaches. CONCLUSIONS Overall, PSASD improves detection of sleep spindles in EEG data acquired from both younger healthy and older adult patient populations.
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Affiliation(s)
- MohammadMehdi Kafashan
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Center on Biological Rhythms and Sleep, Washington University in St. Louis, St. Louis, MO, USA.
| | - Gaurang Gupte
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Paul Kang
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Orlandrea Hyche
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Anhthi H Luong
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - G V Prateek
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | - Yo-El S Ju
- Center on Biological Rhythms and Sleep, Washington University in St. Louis, St. Louis, MO, USA; Department of Neurology, Division of Sleep Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Ben Julian A Palanca
- Department of Anesthesiology, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Center on Biological Rhythms and Sleep, Washington University in St. Louis, St. Louis, MO, USA; Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA; Division of Biology and Biomedical Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
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4
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Mana L, Schwartz-Pallejà M, Vila-Vidal M, Deco G. Overview on cognitive impairment in psychotic disorders: From impaired microcircuits to dysconnectivity. Schizophr Res 2024; 269:132-143. [PMID: 38788432 DOI: 10.1016/j.schres.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: 01/15/2024] [Revised: 05/09/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024]
Abstract
Schizophrenia's cognitive deficits, often overshadowed by positive symptoms, significantly contribute to the disorder's morbidity. Increasing attention highlights these deficits as reflections of neural circuit dysfunction across various cortical regions. Numerous connectivity alterations linked to cognitive symptoms in psychotic disorders have been reported, both at the macroscopic and microscopic level, emphasizing the potential role of plasticity and microcircuits impairment during development and later stages. However, the heterogeneous clinical presentation of cognitive impairment and diverse connectivity findings pose challenges in summarizing them into a cohesive picture. This review aims to synthesize major cognitive alterations, recent insights into network structural and functional connectivity changes and proposed mechanisms and microcircuit alterations underpinning these symptoms, particularly focusing on neurodevelopmental impairment, E/I balance, and sleep disturbances. Finally, we will also comment on some of the most recent and promising therapeutic approaches that aim to target these mechanisms to address cognitive symptoms. Through this comprehensive exploration, we strive to provide an updated and nuanced overview of the multiscale connectivity impairment underlying cognitive impairment in psychotic disorders.
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Affiliation(s)
- L Mana
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain.
| | - M Schwartz-Pallejà
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Department of Experimental and Health Science, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Eurecat, Technology Center of Catalonia, Multimedia Technologies, Barcelona, Spain.
| | - M Vila-Vidal
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Computational Biology and Complex Systems Group, Department of Physics, Universitat Politècnica de Catalunya, Barcelona, Spain.
| | - G Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain.
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5
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Wang J, Jiang C, Guo Z, Chapman S, Kozhemiako N, Mylonas D, Su Y, Zhou L, Shen L, Qin S, Murphy M, Tan S, Manoach DS, Stickgold R, Huang H, Zhou Z, Purcell SM, Hall M, Hyman SE, Pan JQ. Study Protocol: Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project. BMC Psychiatry 2024; 24:433. [PMID: 38858652 PMCID: PMC11165775 DOI: 10.1186/s12888-024-05882-1] [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: 01/25/2024] [Accepted: 05/31/2024] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project. METHODS The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain. CONCLUSION Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.
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Affiliation(s)
- Jun Wang
- The Affiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi, China
| | - Chenguang Jiang
- The Affiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi, China
| | - Zhenglin Guo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Sinéad Chapman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Nataliia Kozhemiako
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
| | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Yi Su
- Psychiatry Research Center, Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Lin Zhou
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Lu Shen
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Shengying Qin
- Bio-X Institutes, Shanghai Jiao Tong University, Shanghai, China
| | - Michael Murphy
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, United States
| | - Shuping Tan
- Psychiatry Research Center, Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Robert Stickgold
- Beth Israel Deaconess Medical Center, Boston, United States
- Department of Psychiatry, Harvard Medical School, Boston, United States
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Harvard Medical School, Boston, United States
| | - Zhenhe Zhou
- The Affiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi, China
| | - Shaun M Purcell
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, United States
- Department of Psychiatry, Harvard Medical School, Boston, United States
| | - Meihua Hall
- Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, United States
| | - Steven E Hyman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States
| | - Jen Q Pan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, United States.
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Samona EA, Chowdury A, Kopchick J, Thomas P, Rajan U, Khatib D, Zajac-Benitez C, Amirsadri A, Haddad L, Stanley JA, Diwadkar VA. The importance of covert memory consolidation in schizophrenia: Dysfunctional network profiles of the hippocampus and the dorsolateral prefrontal cortex. Psychiatry Res Neuroimaging 2024; 340:111805. [PMID: 38447230 PMCID: PMC11188056 DOI: 10.1016/j.pscychresns.2024.111805] [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: 05/31/2023] [Revised: 01/24/2024] [Accepted: 02/20/2024] [Indexed: 03/08/2024]
Abstract
Altered brain network profiles in schizophrenia (SCZ) during memory consolidation are typically observed during task-active periods such as encoding or retrieval. However active processes are also sub served by covert periods of memory consolidation. These periods are active in that they allow memories to be recapitulated even in the absence of overt sensorimotor processing. It is plausible that regions central to memory formation like the dlPFC and the hippocampus, exert network signatures during covert periods. Are these signatures altered in patients? The question is clinically relevant because real world learning and memory is facilitated by covert processing, and may be impaired in schizophrenia. Here, we compared network signatures of the dlPFC and the hippocampus during covert periods of a learning and memory task. Because behavioral proficiency increased non-linearly, functional connectivity of the dlPFC and hippocampus [psychophysiological interaction (PPI)] was estimated for each of the Early (linear increases in performance) and Late (asymptotic performance) covert periods. During Early periods, we observed hypo-modulation by the hippocampus but hyper-modulation by dlPFC. Conversely, during Late periods, we observed hypo-modulation by both the dlPFC and the hippocampus. We stitch these results into a conceptual model of network deficits during covert periods of memory consolidation.
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Affiliation(s)
- Elias A Samona
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Asadur Chowdury
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - John Kopchick
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Patricia Thomas
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Usha Rajan
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Dalal Khatib
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Caroline Zajac-Benitez
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Alireza Amirsadri
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Luay Haddad
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Jeffrey A Stanley
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Vaibhav A Diwadkar
- Department of Psychiatry & Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States.
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7
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Baran B, Lee EE. Age-Related Changes in Sleep and Its Implications for Cognitive Decline in Aging Persons With Schizophrenia: A Critical Review. Schizophr Bull 2024:sbae059. [PMID: 38713085 DOI: 10.1093/schbul/sbae059] [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] [Indexed: 05/08/2024]
Abstract
BACKGROUND AND HYPOTHESIS Cognitive impairment is a core feature of schizophrenia that worsens with aging and interferes with quality of life. Recent work identifies sleep as an actionable target to alleviate cognitive deficits. Cardinal non-rapid eye movement (NREM) sleep oscillations such as sleep spindles and slow oscillations are critical for cognition. People living with schizophrenia (PLWS) and their first-degree relatives have a specific reduction in sleep spindles and an abnormality in their temporal coordination with slow oscillations that predict impaired memory consolidation. While NREM oscillatory activity is reduced in typical aging, it is not known how further disruption in these oscillations contributes to cognitive decline in older PLWS. Another understudied risk factor for cognitive deficits among older PLWS is obstructive sleep apnea (OSA) which may contribute to cognitive decline. STUDY DESIGN We conducted a narrative review to examine the published literature on aging, OSA, and NREM sleep oscillations in PLWS. STUDY RESULTS Spindles are propagated via thalamocortical feedback loops, and this circuitry shows abnormal hyperconnectivity in schizophrenia as revealed by structural and functional MRI studies. While the risk and severity of OSA increase with age, older PLWS are particularly vulnerable to OSA-related cognitive deficits because OSA is often underdiagnosed and undertreated, and OSA adds further damage to the circuitry that generates NREM sleep oscillations. CONCLUSIONS We highlight the critical need to study NREM sleep in older PWLS and propose that identifying and treating OSA in older PLWS will provide an avenue to potentially mitigate and prevent cognitive decline.
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Affiliation(s)
- Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, USA
- Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
- Iowa Neuroscience Institute, Carver College of Medicine, University of Iowa, Iowa City, IA, USA
| | - Ellen E Lee
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Desert-Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
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8
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Guttesen AÁV, Denis D, Gaskell MG, Cairney SA. Delineating memory reactivation in sleep with verbal and non-verbal retrieval cues. Cereb Cortex 2024; 34:bhae183. [PMID: 38745557 PMCID: PMC11094403 DOI: 10.1093/cercor/bhae183] [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: 03/09/2023] [Revised: 04/12/2024] [Accepted: 04/16/2024] [Indexed: 05/16/2024] Open
Abstract
Sleep supports memory consolidation via the reactivation of newly formed memory traces. One way to investigate memory reactivation in sleep is by exposing the sleeping brain to auditory retrieval cues; a paradigm known as targeted memory reactivation. To what extent the acoustic properties of memory cues influence the effectiveness of targeted memory reactivation, however, has received limited attention. We addressed this question by exploring how verbal and non-verbal memory cues affect oscillatory activity linked to memory reactivation in sleep. Fifty-one healthy male adults learned to associate visual stimuli with spoken words (verbal cues) and environmental sounds (non-verbal cues). Subsets of the verbal and non-verbal memory cues were then replayed during sleep. The voice of the verbal cues was either matched or mismatched to learning. Memory cues (relative to unheard control cues) prompted an increase in theta/alpha and spindle power, which have been heavily implicated in sleep-associated memory processing. Moreover, verbal memory cues were associated with a stronger increase in spindle power than non-verbal memory cues. There were no significant differences between the matched and mismatched verbal cues. Our findings suggest that verbal memory cues may be most effective for triggering memory reactivation in sleep, as indicated by an amplified spindle response.
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Affiliation(s)
- Anna á V Guttesen
- Department of Psychology, University of York, York YO10 5DD, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 9DU, United Kingdom
| | - Dan Denis
- Department of Psychology, University of York, York YO10 5DD, United Kingdom
- York Biomedical Research Institute, University of York, York YO10 5DD, United Kingdom
| | - M Gareth Gaskell
- Department of Psychology, University of York, York YO10 5DD, United Kingdom
- York Biomedical Research Institute, University of York, York YO10 5DD, United Kingdom
| | - Scott A Cairney
- Department of Psychology, University of York, York YO10 5DD, United Kingdom
- York Biomedical Research Institute, University of York, York YO10 5DD, United Kingdom
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9
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Denis D, Payne JD. Targeted Memory Reactivation during Nonrapid Eye Movement Sleep Enhances Neutral, But Not Negative, Components of Memory. eNeuro 2024; 11:ENEURO.0285-23.2024. [PMID: 38769012 PMCID: PMC11140657 DOI: 10.1523/eneuro.0285-23.2024] [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: 08/08/2023] [Revised: 03/14/2024] [Accepted: 04/18/2024] [Indexed: 05/22/2024] Open
Abstract
Emotionally salient components of memory are preferentially remembered at the expense of accompanying neutral information. This emotional memory trade-off is enhanced over time, and possibly sleep, through a process of memory consolidation. Sleep is believed to benefit memory through a process of reactivation during nonrapid eye movement sleep (NREM). Here, targeted memory reactivation (TMR) was used to manipulate the reactivation of negative and neutral memories during NREM sleep. Thirty-one male and female participants encoded composite scenes containing either a negative or neutral object superimposed on an always neutral background. During NREM sleep, sounds associated with the scene object were replayed, and memory for object and background components was tested the following morning. We found that TMR during NREM sleep improved memory for neutral, but not negative scene objects. This effect was associated with sleep spindle activity, with a larger spindle response following TMR cues predicting TMR effectiveness for neutral items only. These findings therefore do not suggest a role of NREM memory reactivation in enhancing the emotional memory trade-off across a 12 h period but do align with growing evidence of spindle-mediated memory reactivation in service of neutral declarative memory.
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Affiliation(s)
- Dan Denis
- Department of Psychology, University of York, York YO10 5DD, United Kingdom,
| | - Jessica D Payne
- Department of Psychology, University of Notre Dame, Notre Dame, Indiana 46556
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10
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Ferrarelli F. Sleep spindles as neurophysiological biomarkers of schizophrenia. Eur J Neurosci 2024; 59:1907-1917. [PMID: 37885306 DOI: 10.1111/ejn.16178] [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: 06/11/2023] [Revised: 09/17/2023] [Accepted: 10/11/2023] [Indexed: 10/28/2023]
Abstract
Schizophrenia (SCZ) is a complex psychiatric disorder characterized by a wide range of clinical symptoms, including disrupted sleep. In recent years, there has been growing interest in assessing alterations in sleep parameters in patients with SCZ. Sleep spindles are brief (0.5-2 s) bursts of 12- to 16-Hz rhythmic electroencephalogram (EEG) oscillatory activity occurring during non-rapid eye movement (NREM) sleep. Spindles have been implicated in several critical brain functions, including learning, memory and plasticity, and are thought to reflect the integrity of underlying thalamocortical circuits. This review aims to provide an overview of the current research investigating sleep spindles in SCZ. After briefly describing the neurophysiological features of sleep spindles, I will discuss alterations in spindle characteristics observed in SCZ, their associations with the clinical symptomatology of these patients and their putative underlying neuronal and molecular mechanisms. I will then discuss the utility of sleep spindle measures as predictors of treatment response and disease progression. Finally, I will highlight future directions for research in this emerging field, including the prospect of utilizing sleep spindles as neurophysiological biomarkers of SCZ.
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Affiliation(s)
- Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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11
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Kammerer MK, Bott A, Strakeljahn F, Lincoln TM. Sleep spindle activity and psychotic experiences: Examining the mediating roles of attentional performance and perceptual distortions in a daytime nap study. Sleep Med 2024; 116:43-50. [PMID: 38422784 DOI: 10.1016/j.sleep.2024.02.023] [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: 10/28/2023] [Revised: 02/10/2024] [Accepted: 02/11/2024] [Indexed: 03/02/2024]
Abstract
Decreased sleep spindle activity in individuals with psychotic disorders is well studied, but its contribution to psychotic symptom formation is not well understood. This study explored potential underlying mechanisms explaining the association between decreased sleep spindle activity and psychotic symptoms. To this end, we analysed the links between sleep spindle activity and psychotic experiences and probed for the mediating roles of attentional performance and perceptual distortions in a community sample of young adults (N = 70; 26.33 ± 4.84 years). Polysomnography was recorded during a 90-min daytime nap and duration, amplitude, and density from slow (10-13 Hz) and fast (13-16 Hz) spindles were extracted. Attentional performance was assessed via a test battery and with an antisaccadic eye movement task. Psychotic experiences (i.e., paranoid thoughts; hallucinatory experiences) and perceptual distortions (i.e., anomalous perceptions; sensory gating deficits) were assessed via self-report questionnaires. We conducted sequential mediation analyses with spindle activity as predictor, psychotic experiences as dependent variable, and attentional performance and perceptual distortions as mediators. We found reduced right central spindle amplitude to be associated with paranoid thoughts. Increased antisaccadic error rate was associated with anomalous perceptions and perceptual distortions were associated with psychotic experiences. We did not find significant mediation effects. The findings support the notion that reduced sleep spindle activity is involved in the formation of paranoid thoughts and that decreased antisaccadic performance is indicative of perceptual distortions as potential precursors for psychotic experiences. However, further research is needed to corroborate the proposed mediation hypothesis.
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Affiliation(s)
- Mathias K Kammerer
- Clinical Psychology and Psychotherapy, Institute of Psychology, Faculty of Psychology and Movement Sciences, Universität Hamburg, Germany.
| | - Antonia Bott
- Clinical Psychology and Psychotherapy, Institute of Psychology, Faculty of Psychology and Movement Sciences, Universität Hamburg, Germany
| | - Felix Strakeljahn
- Clinical Psychology and Psychotherapy, Institute of Psychology, Faculty of Psychology and Movement Sciences, Universität Hamburg, Germany
| | - Tania M Lincoln
- Clinical Psychology and Psychotherapy, Institute of Psychology, Faculty of Psychology and Movement Sciences, Universität Hamburg, Germany
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Castelnovo A, Casetta C, Cavallotti S, Marcatili M, Del Fabro L, Canevini MP, Sarasso S, D'Agostino A. Proof-of-concept evidence for high-density EEG investigation of sleep slow wave traveling in First-Episode Psychosis. Sci Rep 2024; 14:6826. [PMID: 38514761 PMCID: PMC10958040 DOI: 10.1038/s41598-024-57476-2] [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: 12/16/2022] [Accepted: 03/18/2024] [Indexed: 03/23/2024] Open
Abstract
Schizophrenia is thought to reflect aberrant connectivity within cortico-cortical and reentrant thalamo-cortical loops, which physiologically integrate and coordinate the function of multiple cortical and subcortical structures. Despite extensive research, reliable biomarkers of such "dys-connectivity" remain to be identified at the onset of psychosis, and before exposure to antipsychotic drugs. Because slow waves travel across the brain during sleep, they represent an ideal paradigm to study pathological conditions affecting brain connectivity. Here, we provide proof-of-concept evidence for a novel approach to investigate slow wave traveling properties in First-Episode Psychosis (FEP) with high-density electroencephalography (EEG). Whole-night sleep recordings of 5 drug-naïve FEP and 5 age- and gender-matched healthy control subjects were obtained with a 256-channel EEG system. One patient was re-recorded after 6 months and 3 years of continuous clozapine treatment. Slow wave detection and traveling properties were obtained with an open-source toolbox. Slow wave density and slow wave traveled distance (measured as the line of longest displacement) were significantly lower in patients (p < 0.05). In the patient who was tested longitudinally during effective clozapine treatment, slow wave density normalized, while traveling distance only partially recovered. These preliminary findings suggest that slow wave traveling could be employed in larger samples to detect cortical "dys-connectivity" at psychosis onset.
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Affiliation(s)
- Anna Castelnovo
- Sleep Medicine Unit, Neurocenter of Italian Switzerland, Ente Ospedaliero Cantonale (EOC), Via Tesserete 46, 6900, Lugano, Switzerland.
- Faculty of Biomedical Sciences, University of Italian Switzerland, Lugano, Switzerland.
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.
| | - Cecilia Casetta
- Department of Mental Health and Addiction, ASST Santi Paolo e Carlo, Via A. Di Rudinì 8, 20142, Milan, Italy
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Simone Cavallotti
- Department of Mental Health and Addiction, ASST Santi Paolo e Carlo, Via A. Di Rudinì 8, 20142, Milan, Italy
| | - Matteo Marcatili
- Psychiatric Department, ASST Monza, San Gerardo Hospital, Monza, Italy
| | - Lorenzo Del Fabro
- Department of Pathophysiology and Transplantation, Università degli Studi di Milano, Milan, Italy
- Department of Neurosciences and Mental Health, IRCCS Fondazione Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Maria Paola Canevini
- Department of Mental Health and Addiction, ASST Santi Paolo e Carlo, Via A. Di Rudinì 8, 20142, Milan, Italy
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Via G.B. Grassi 74, 20157, Milan, Italy.
| | - Armando D'Agostino
- Department of Mental Health and Addiction, ASST Santi Paolo e Carlo, Via A. Di Rudinì 8, 20142, Milan, Italy.
- Department of Health Sciences, Università degli Studi di Milano, Milan, Italy.
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Simon KC, Cadle C, Nakra N, Nagel MC, Malerba P. Age-associated sleep spindle characteristics in Duchenne muscular dystrophy. SLEEP ADVANCES : A JOURNAL OF THE SLEEP RESEARCH SOCIETY 2024; 5:zpae015. [PMID: 38525359 PMCID: PMC10960605 DOI: 10.1093/sleepadvances/zpae015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 12/18/2023] [Indexed: 03/26/2024]
Abstract
Brain oscillations of non-rapid eye movement sleep, including slow oscillations (SO, 0.5-1.5 Hz) and spindles (10-16 Hz), mirror underlying brain maturation across development and are associated with cognition. Hence, age-associated emergence and changes in the electrophysiological properties of these rhythms can lend insight into cortical development, specifically in comparisons between pediatric populations and typically developing peers. We previously evaluated age-associated changes in SOs in male patients with Duchenne muscular dystrophy (DMD), finding a significant age-related decline between 4 and 18 years. While primarily a muscle disorder, male patients with DMD can also have sleep, cognitive, and cortical abnormalities, thought to be driven by altered dystrophin expression in the brain. In this follow-up study, we characterized the age-associated changes in sleep spindles. We found that age-dependent spindle characteristics in patients with DMD, including density, frequency, amplitude, and duration, were consistent with age-associated trends reported in the literature for typically developing controls. Combined with our prior finding of age-associated decline in SOs, our results suggest that SOs, but not spindles, are a candidate intervention target to enhance sleep in patients with DMD.
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Affiliation(s)
- Katharine C Simon
- Department of Pediatrics, School of Medicine, University of California, Irvine, Irvine, CA, USA
- Pulmonology Department, Children’s Hospital of Orange County, Orange, CA, USA
| | - Chelsea Cadle
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, USA
| | - Neal Nakra
- Pulmonology Department, Children’s Hospital of Orange County, Orange, CA, USA
| | - Marni C Nagel
- Department of Pediatric Psychology, Children’s Hospital of Orange County, Orange, CA, USA
| | - Paola Malerba
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, USA
- Department of Pediatrics, School of Medicine, The Ohio State University, Columbus, OH, USA
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14
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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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15
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Chen S, He M, Brown RE, Eden UT, Prerau MJ. Individualized temporal patterns dominate cortical upstate and sleep depth in driving human sleep spindle timing. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.22.581592. [PMID: 38464146 PMCID: PMC10925076 DOI: 10.1101/2024.02.22.581592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Sleep spindles are critical for memory consolidation and strongly linked to neurological disease and aging. Despite their significance, the relative influences of factors like sleep depth, cortical up/down states, and spindle temporal patterns on individual spindle production remain poorly understood. Moreover, spindle temporal patterns are typically ignored in favor of an average spindle rate. Here, we analyze spindle dynamics in 1008 participants from the Multi-Ethnic Study of Atherosclerosis using a point process framework. Results reveal fingerprint-like temporal patterns, characterized by a refractory period followed by a period of increased spindle activity, which are highly individualized yet consistent night-to-night. We observe increased timing variability with age and distinct gender/age differences. Strikingly, and in contrast to the prevailing notion, individualized spindle patterns are the dominant determinant of spindle timing, accounting for over 70% of the statistical deviance explained by all of the factors we assessed, surpassing the contribution of slow oscillation (SO) phase (~14%) and sleep depth (~16%). Furthermore, we show spindle/SO coupling dynamics with sleep depth are preserved across age, with a global negative shift towards the SO rising slope. These findings offer novel mechanistic insights into spindle dynamics with direct experimental implications and applications to individualized electroencephalography biomarker identification.
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Affiliation(s)
- Shuqiang Chen
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
| | - Mingjian He
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ritchie E. Brown
- VA Boston Healthcare System and Harvard Medical School, Department of Psychiatry, West Roxbury, MA, USA
| | - Uri T. Eden
- Department of Mathematics and Statistics, Boston University, Boston, MA, USA
| | - Michael J. Prerau
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
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Zapata IA, Wen P, Jones E, Fjaagesund S, Li Y. Automatic sleep spindles identification and classification with multitapers and convolution. Sleep 2024; 47:zsad159. [PMID: 37294908 PMCID: PMC10782498 DOI: 10.1093/sleep/zsad159] [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: 01/17/2023] [Revised: 05/08/2023] [Indexed: 06/11/2023] Open
Abstract
Sleep spindles are isolated transient surges of oscillatory neural activity present during sleep stages 2 and 3 in the nonrapid eye movement (NREM). They can indicate the mechanisms of memory consolidation and plasticity in the brain. Spindles can be identified across cortical areas and classified as either slow or fast. There are spindle transients across different frequencies and power, yet most of their functions remain a mystery. Using several electroencephalogram (EEG) databases, this study presents a new method, called the "spindles across multiple channels" (SAMC) method, for identifying and categorizing sleep spindles in EEGs during the NREM sleep. The SAMC method uses a multitapers and convolution (MT&C) approach to extract the spectral estimation of different frequencies present in sleep EEGs and graphically identify spindles across multiple channels. The characteristics of spindles, such as duration, power, and event areas, are also extracted by the SAMC method. Comparison with other state-of-the-art spindle identification methods demonstrated the superiority of the proposed method with an agreement rate, average positive predictive value, and sensitivity of over 90% for spindle classification across the three databases used in this paper. The computing cost was found to be, on average, 0.004 seconds per epoch. The proposed method can potentially improve the understanding of the behavior of spindles across the scalp and accurately identify and categories sleep spindles.
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Affiliation(s)
- Ignacio A Zapata
- School of Mathematics, Physics and Computing, University of Southern Queensland, Darling Heights, Australia
| | - Peng Wen
- School of Engineering, University of Southern Queensland, Toowoomba, Australia
| | - Evan Jones
- Health Hub Doctors Morayfield, Queensland, 4506, The University of the Sunshine Coast, Queensland, 4556, Australia
| | - Shauna Fjaagesund
- Health Developments Corporation, Health Hub Morayfield, Queensland, 4506, University of the Sunshine Coast, Sippy Downs, Queensland, 4556, Australia
| | - Yan Li
- School of Mathematics, Physics and Computing, University of Southern Queensland, Darling Heights, Australia
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17
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Wernette EMD, Fenn KM. Factors influencing sleep-dependent consolidation: Sleep strengths memory based on encoding depth but not repetition. J Sleep Res 2024:e14091. [PMID: 38196130 DOI: 10.1111/jsr.14091] [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: 04/12/2023] [Revised: 10/10/2023] [Accepted: 10/23/2023] [Indexed: 01/11/2024]
Abstract
Sleep consolidates declarative memory after deep but not shallow incidental encoding, but little is known about this form of consolidation. One unexplored area is the extent to which the amount of exposure to incidentally encoded information affects consolidation processes. In two experiments, we manipulated the number of times information was presented. In Experiment 1, participants encoded words either one or three times in a deep or shallow incidental encoding task and completed a surprise recognition test after sleep or wake. Sleep consolidated information after deep encoding after one and three exposures, but not after shallow encoding. In Experiment 2, we explored the relationship between sleep architecture and memory after deep encoding. There was a trend for accuracy to be negatively related to N1 sleep, and reaction time to be negatively related to slow-wave sleep for words encoded once; however, the correlations did not survive corrections for multiple comparisons. These results are discussed with respect to active and passive consolidation processes.
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Affiliation(s)
- Elle M D Wernette
- Department of Psychology, Michigan State University, East Lansing, Michigan, USA
| | - Kimberly M Fenn
- Department of Psychology, Michigan State University, East Lansing, Michigan, USA
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18
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Bergamo D, Handjaras G, Petruso F, Talami F, Ricciardi E, Benuzzi F, Vaudano AE, Meletti S, Bernardi G, Betta M. Maturation-dependent changes in cortical and thalamic activity during sleep slow waves: Insights from a combined EEG-fMRI study. Sleep Med 2024; 113:357-369. [PMID: 38113618 DOI: 10.1016/j.sleep.2023.12.001] [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: 08/19/2023] [Revised: 11/24/2023] [Accepted: 12/02/2023] [Indexed: 12/21/2023]
Abstract
INTRODUCTION Studies using scalp EEG have shown that slow waves (0.5-4 Hz), the most prominent hallmark of NREM sleep, undergo relevant changes from childhood to adulthood, mirroring brain structural modifications and the acquisition of cognitive skills. Here we used simultaneous EEG-fMRI to investigate the cortical and subcortical correlates of slow waves in school-age children and determine their relative developmental changes. METHODS We analyzed data from 14 school-age children with self-limited focal epilepsy of childhood who fell asleep during EEG-fMRI recordings. Brain regions associated with slow-wave occurrence were identified using a voxel-wise regression that also modelled interictal epileptic discharges and sleep spindles. At the group level, a mixed-effects linear model was used. The results were qualitatively compared with those obtained from 2 adolescents with epilepsy and 17 healthy adults. RESULTS Slow waves were associated with hemodynamic-signal decreases in bilateral somatomotor areas. Such changes extended more posteriorly relative to those in adults. Moreover, the involvement of areas belonging to the default mode network changes as a function of age. No significant hemodynamic responses were observed in subcortical structures. However, we identified a significant correlation between age and thalamic hemodynamic changes. CONCLUSIONS Present findings indicate that the somatomotor cortex may have a key role in slow-wave expression throughout the lifespan. At the same time, they are consistent with a posterior-to-anterior shift in slow-wave distribution mirroring brain maturational changes. Finally, our results suggest that slow-wave changes may not reflect only neocortical modifications but also the maturation of subcortical structures, including the thalamus.
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Affiliation(s)
- Damiana Bergamo
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | | | - Flavia Petruso
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy; Sant'Anna School of Advanced Studies, Pisa, Italy
| | - Francesca Talami
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | | | - Francesca Benuzzi
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
| | - Anna Elisabetta Vaudano
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | - Stefano Meletti
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy; Neurology Dept., Azienda Ospedaliera Universitaria di Modena, Italy
| | - Giulio Bernardi
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy
| | - Monica Betta
- MoMiLab, IMT School for Advanced Studies Lucca, Lucca, Italy.
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Kozhemiako N, Jiang C, Sun Y, Guo Z, Chapman S, Gai G, Wang Z, Zhou L, Li S, Law RG, Wang LA, Mylonas D, Shen L, Murphy M, Qin S, Zhu W, Zhou Z, Stickgold R, Huang H, Tan S, Manoach DS, Wang J, Hall MH, Pan JQ, Purcell SM. A spectrum of altered non-rapid eye movement sleep in schizophrenia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.28.573548. [PMID: 38234726 PMCID: PMC10793442 DOI: 10.1101/2023.12.28.573548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Background Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations (SO), are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses which treat all patients as a unitary set, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, illness duration and ageing, cognitive profiles and medication regimens. Using newly collected high density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported (Kozhemiako et. al, 2022) group-level mean differences between patients and controls (original N=130). Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability in NREM neurophysiology. Results We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (Area Under the ROC Curve, AUC = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics, with patterns only partially recapitulating those for group-level mean differences. Although multiple clinical and cognitive factors were associated with NREM metrics including spindle density, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regimen was a greater (albeit still partial) contributor to variability, although original group mean differences persisted after controlling for medications. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on an independent model of ageing and the sleep EEG. Conclusion We demonstrated robust and replicable alterations in sleep neurophysiology in individuals with SCZ and highlighted distinct patterns of effects contrasting between-group means versus within-group variances. We further documented and controlled for a major effect of medication use, and pointed to greater age-related change in NREM sleep in patients. That increased NREM heterogeneity was not explained by standard clinical or cognitive patient assessments suggests the sleep EEG provides novel, nonredundant information to support the goals of personalized medicine. Collectively, our results point to a spectrum of NREM sleep deficits among SCZ patients that can be measured objectively and at scale, and that may offer a unique window on the etiological and genetic diversity that underlies SCZ risk, treatment response and prognosis.
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Affiliation(s)
- Nataliia Kozhemiako
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School; Boston, USA
| | - Chenguang Jiang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Yifan Sun
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Zhenglin Guo
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Sinéad Chapman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Guanchen Gai
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Zhe Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Lin Zhou
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Shen Li
- Department of Psychiatry, McLean Hospital, Harvard Medical School; Boston, USA
| | - Robert G. Law
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School; Boston, USA
| | - Lei A. Wang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School; Boston, USA
| | - Lu Shen
- Bio-X Institutes, Shanghai Jiao Tong University; Shanghai China
| | - Michael Murphy
- Department of Psychiatry, McLean Hospital, Harvard Medical School; Boston, USA
| | - Shengying Qin
- Bio-X Institutes, Shanghai Jiao Tong University; Shanghai China
| | - Wei Zhu
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Zhenhe Zhou
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Robert Stickgold
- Beth Israel Deaconess Medical Center; Boston, USA
- Department of Psychiatry, Harvard Medical School; Boston, USA
| | - Hailiang Huang
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
- ATGU, MGH, Harvard Medical School; Boston, USA
| | - Shuping Tan
- Huilong Guan Hospital, Beijing University; Beijing China
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School; Boston, USA
| | - Jun Wang
- The Affiliated Wuxi Mental Health Center of Nanjing Medical University; Wuxi, China
| | - Mei-Hua Hall
- Department of Psychiatry, McLean Hospital, Harvard Medical School; Boston, USA
| | - Jen Q. Pan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard; Boston, USA
| | - Shaun M. Purcell
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School; Boston, USA
- Department of Psychiatry, Harvard Medical School; Boston, USA
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Roy B, Amemasor E, Hussain S, Castro K. UBE3A: The Role in Autism Spectrum Disorders (ASDs) and a Potential Candidate for Biomarker Studies and Designing Therapeutic Strategies. Diseases 2023; 12:7. [PMID: 38248358 PMCID: PMC10814747 DOI: 10.3390/diseases12010007] [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: 11/13/2023] [Revised: 12/14/2023] [Accepted: 12/15/2023] [Indexed: 01/23/2024] Open
Abstract
Published reports from the CDC's Autism and Development Disabilities Monitoring Networks have shown that an average of 1 in every 44 (2.3%) 8-year-old children were estimated to have ASD in 2018. Many of the ASDs exhibiting varying degrees of autism-like phenotypes have chromosomal anomalies in the Chr15q11-q13 region. Numerous potential candidate genes linked with ASD reside in this chromosomal segment. However, several clinical, in vivo, and in vitro studies selected one gene more frequently than others randomly and unbiasedly. This gene codes for UBE3A or Ubiquitin protein ligase E3A [also known as E6AP ubiquitin-protein ligase (E6AP)], an enzyme involved in the cellular degradation of proteins. This gene has been listed as one of the several genes with a high potential of causing ASD in the Autism Database. The gain of function mutations, triplication, or duplication in the UBE3A gene is also associated with ASDs like Angelman Syndrome (AS) and Dup15q Syndrome. The genetic imprinting of UBE3A in the brain and a preference for neuronal maternal-specific expression are the key features of various ASDs. Since the UBE3A gene is involved in two main important diseases associated with autism-like symptoms, there has been widespread research going on in understanding the link between this gene and autism. Additionally, since no universal methodology or mechanism exists for identifying UBE3A-mediated ASD, it continues to be challenging for neurobiologists, neuroscientists, and clinicians to design therapies or diagnostic tools. In this review, we focus on the structure and functional aspects of the UBE3A protein, discuss the primary relevance of the 15q11-q13 region in the cause of ASDs, and highlight the link between UBE3A and ASD. We try to broaden the knowledge of our readers by elaborating on the possible mechanisms underlying UBE3A-mediated ASDs, emphasizing the usage of UBE3A as a prospective biomarker in the preclinical diagnosis of ASDs and discuss the positive outcomes, advanced developments, and the hurdles in the field of therapeutic strategies against UBE3A-mediated ASDs. This review is novel as it lays a very detailed and comprehensive platform for one of the most important genes associated with diseases showing autistic-like symptoms. Additionally, this review also attempts to lay optimistic feedback on the possible steps for the diagnosis, prevention, and therapy of these UBE3A-mediated ASDs in the upcoming years.
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Affiliation(s)
- Bidisha Roy
- Life Science Centre, Department of Biological Sciences, Rutgers University-Newark, Newark, NJ 07102, USA; (E.A.); (S.H.); (K.C.)
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Bender AC, Jaleel A, Pellerin KR, Moguilner S, Sarkis RA, Cash SS, Lam AD. Altered Sleep Microarchitecture and Cognitive Impairment in Patients With Temporal Lobe Epilepsy. Neurology 2023; 101:e2376-e2387. [PMID: 37848332 PMCID: PMC10752648 DOI: 10.1212/wnl.0000000000207942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 08/28/2023] [Indexed: 10/19/2023] Open
Abstract
BACKGROUND AND OBJECTIVES To investigate the spatiotemporal characteristics of sleep waveforms in temporal lobe epilepsy (TLE) and examine their association with cognition. METHODS In this retrospective, cross-sectional study, we examined overnight EEG data from adult patients with TLE and nonepilepsy comparisons (NECs) admitted to the epilepsy monitoring unit at Mass General Brigham hospitals. Automated algorithms were used to characterize sleep macroarchitecture (sleep stages) and microarchitecture (spindles, slow oscillations [SOs]) on scalp EEG and to detect hippocampal interictal epileptiform discharges (hIEDs) from foramen ovale electrodes simultaneously recorded in a subset of patients with TLE. We examined the association of sleep features and hIEDs with memory and executive function from clinical neuropsychological evaluations. RESULTS A total of 81 adult patients with TLE and 28 NEC adult patients were included with similar mean ages. There were no significant differences in sleep macroarchitecture between groups, including relative time spent in each sleep stage, sleep efficiency, and sleep fragmentation. By contrast, the spatiotemporal characteristics of sleep microarchitecture were altered in TLE compared with NEC and were associated with cognitive impairments. Specifically, we observed a ∼30% reduction in spindle density in patients with TLE compared with NEC, which was significantly associated with worse memory performance. Spindle-SO coupling strength was also reduced in TLE and, in contrast to spindles, was associated with diminished executive function. We found no significant association between sleep macroarchitectural and microarchitectural parameters and hIEDs. DISCUSSION There is a fundamental alteration of sleep microarchitecture in TLE, characterized by a reduction in spindle density and spindle-SO coupling, and these changes may contribute to neurocognitive comorbidity in this disorder.
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Affiliation(s)
- Alex C Bender
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA.
| | - Afareen Jaleel
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Kyle R Pellerin
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Sebastian Moguilner
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Rani A Sarkis
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Sydney S Cash
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
| | - Alice D Lam
- From the Epilepsy Service (A.C.B., A.J., K.R.P., S.M., S.S.C., A.D.L.), Department of Neurology, Massachusetts General Hospital & Harvard Medical School, Boston; and Epilepsy Service (R.A.S.), Department of Neurology, Brigham and Women's Hospital & Harvard Medical School, Boston, MA
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22
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Denis D, Baran B, Mylonas D, Spitzer C, Raymond N, Talbot C, Kohnke E, Stickgold R, Keshavan M, Manoach DS. NREM sleep oscillations and their relations with sleep-dependent memory consolidation in early course psychosis and first-degree relatives. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.30.564703. [PMID: 37961668 PMCID: PMC10634996 DOI: 10.1101/2023.10.30.564703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Sleep spindles are believed to mediate sleep-dependent memory consolidation, particularly when coupled to neocortical slow oscillations. Schizophrenia is characterized by a deficit in sleep spindles that correlates with reduced overnight memory consolidation. Here, we examined sleep spindle activity, slow oscillation-spindle coupling, and both motor procedural and verbal declarative memory consolidation in early course, minimally medicated psychosis patients and non-psychotic first-degree relatives. Using a four-night experimental procedure, we observed significant deficits in spindle density and amplitude in patients relative to controls that were driven by individuals with schizophrenia. Schizophrenia patients also showed reduced sleep-dependent consolidation of motor procedural memory, which correlated with spindle density. Contrary to expectations, there were no group differences in the consolidation of declarative memory on a word pairs task. Nor did the relatives of patients differ in spindle activity or memory consolidation compared with controls, however increased consistency in the timing of SO-spindle coupling were seen in both patient and relatives. Our results extend prior work by demonstrating correlated deficits in sleep spindles and sleep-dependent motor procedural memory consolidation in early course, minimally medicated patients with schizophrenia, but not in first-degree relatives. This is consistent with other work in suggesting that impaired sleep-dependent memory consolidation has some specificity for schizophrenia and is a core feature rather than reflecting the effects of medication or chronicity.
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Affiliation(s)
- Dan Denis
- Department of Psychology, University of York, York, UK
| | - Bengi Baran
- Department of Psychological and Brain Sciences, University of Iowa, Iowa City, IA, USA
- Department of Psychiatry, University of Iowa, Iowa City, IA, USA
| | - Dimitrios Mylonas
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | | | | | - Christine Talbot
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Erin Kohnke
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
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23
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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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24
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Palepu K, Sadeghi K, Kleinschmidt DF, Donoghue J, Chapman S, Arslan AR, Westover MB, Cash SS, Pathmanathan J. An examination of sleep spindle metrics in the Sleep Heart Health Study: superiority of automated spindle detection over total sigma power in assessing age-related spindle decline. BMC Neurol 2023; 23:359. [PMID: 37803266 PMCID: PMC10557170 DOI: 10.1186/s12883-023-03376-3] [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: 07/06/2022] [Accepted: 09/08/2023] [Indexed: 10/08/2023] Open
Abstract
BACKGROUND Sleep spindle activity is commonly estimated by measuring sigma power during stage 2 non-rapid eye movement (NREM2) sleep. However, spindles account for little of the total NREM2 interval and therefore sigma power over the entire interval may be misleading. This study compares derived spindle measures from direct automated spindle detection with those from gross power spectral analyses for the purposes of clinical trial design. METHODS We estimated spindle activity in a set of 8,440 overnight electroencephalogram (EEG) recordings from 5,793 patients from the Sleep Heart Health Study using both sigma power and direct automated spindle detection. Performance of the two methods was evaluated by determining the sample size required to detect decline in age-related spindle coherence with each method in a simulated clinical trial. RESULTS In a simulated clinical trial, sigma power required a sample size of 115 to achieve 95% power to identify age-related changes in sigma coherence, while automated spindle detection required a sample size of only 60. CONCLUSIONS Measurements of spindle activity utilizing automated spindle detection outperformed conventional sigma power analysis by a wide margin, suggesting that many studies would benefit from incorporation of automated spindle detection. These results further suggest that some previous studies which have failed to detect changes in sigma power or coherence may have failed simply because they were underpowered.
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Affiliation(s)
- Kalyan Palepu
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA
| | - Kolia Sadeghi
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA
| | - Dave F Kleinschmidt
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA
| | - Jacob Donoghue
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA
| | - Seth Chapman
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA
| | - Alexander R Arslan
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA
| | - M Brandon Westover
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA
- Beth Israel Deaconess Medical Center, 330 Brookline Ave, Boston, MA, 02215, USA
| | - Sydney S Cash
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA
- Clinical Data Animation Center (CDAC), Massachusetts General Hospital, 50 Staniford Street, Fruit St, Boston, MA, 02114, USA
| | - Jay Pathmanathan
- Beacon Biosignals, 22 Boston Wharf Rd 7th Floor, Suite 41, Boston, MA, 02210, USA.
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25
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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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26
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He M, Das P, Hotan G, Purdon PL. Switching state-space modeling of neural signal dynamics. PLoS Comput Biol 2023; 19:e1011395. [PMID: 37639391 PMCID: PMC10491408 DOI: 10.1371/journal.pcbi.1011395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 09/08/2023] [Accepted: 07/28/2023] [Indexed: 08/31/2023] Open
Abstract
Linear parametric state-space models are a ubiquitous tool for analyzing neural time series data, providing a way to characterize the underlying brain dynamics with much greater statistical efficiency than non-parametric data analysis approaches. However, neural time series data are frequently time-varying, exhibiting rapid changes in dynamics, with transient activity that is often the key feature of interest in the data. Stationary methods can be adapted to time-varying scenarios by employing fixed-duration windows under an assumption of quasi-stationarity. But time-varying dynamics can be explicitly modeled by switching state-space models, i.e., by using a pool of state-space models with different dynamics selected by a probabilistic switching process. Unfortunately, exact solutions for state inference and parameter learning with switching state-space models are intractable. Here we revisit a switching state-space model inference approach first proposed by Ghahramani and Hinton. We provide explicit derivations for solving the inference problem iteratively after applying a variational approximation on the joint posterior of the hidden states and the switching process. We introduce a novel initialization procedure using an efficient leave-one-out strategy to compare among candidate models, which significantly improves performance compared to the existing method that relies on deterministic annealing. We then utilize this state inference solution within a generalized expectation-maximization algorithm to estimate model parameters of the switching process and the linear state-space models with dynamics potentially shared among candidate models. We perform extensive simulations under different settings to benchmark performance against existing switching inference methods and further validate the robustness of our switching inference solution outside the generative switching model class. Finally, we demonstrate the utility of our method for sleep spindle detection in real recordings, showing how switching state-space models can be used to detect and extract transient spindles from human sleep electroencephalograms in an unsupervised manner.
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Affiliation(s)
- Mingjian He
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America
| | - Proloy Das
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Anesthesia, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, United States of America
| | - Gladia Hotan
- Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore
| | - Patrick L. Purdon
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Anesthesia, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, United States of America
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27
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Park KS, Choi SH, Yoon H. Modulation of sleep using noninvasive stimulations during sleep. Biomed Eng Lett 2023; 13:329-341. [PMID: 37519871 PMCID: PMC10382438 DOI: 10.1007/s13534-023-00298-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/06/2023] [Accepted: 06/18/2023] [Indexed: 08/01/2023] Open
Abstract
Among the various sleep modulation methods for improving sleep, three methods using noninvasive stimulation during sleep have been reviewed and summarized. The first method involves noninvasive direct brain stimulation to induce a current directly in the brain cortex. Electrically or magnetically applied stimulations trigger electrical events such as slow oscillations or sleep spindles, which can also be recorded by an electroencephalogram. The second method involves sensory stimulation during sleep, which provides stimulation through the sensory pathway to invoke equivalent brain activity like direct brain stimulation. Olfactory, vestibular, and auditory stimulation methods have been used, resulting in several sleep-modulating effects, which are characteristic and depend on the experimental paradigm. The third method is to modulate sleep by shifting the autonomic balance affecting sleep homeostasis. To strengthen parasympathetic dominance, stimulation was applied to decrease heart rate by synchronizing the heart rhythm. These noninvasive stimulation methods can strengthen slow-wave sleep, consolidate declarative or procedural memory, and modify sleep macrostructure. These stimulation methods provide evidence and possibility for sleep modulation in our daily life as an alternative method for the treatment of disturbed sleep and enhancing sleep quality and performance beyond the average level.
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Affiliation(s)
- Kwang Suk Park
- Department of Biomedical Engineering, College of Medicine, Seoul National University, Seoul, 03080 Korea
| | - Sang Ho Choi
- School of Computer and Information Engineering, Kwangwoon University, Seoul, 01897 Korea
| | - Heenam Yoon
- Department of Human-Centered Artificial Intelligence, Sangmyung University, Seoul, 03016 Korea
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28
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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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29
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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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30
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Dimitriades ME, Markovic A, Gefferie SR, Buckley A, Driver DI, Rapoport JL, Nosadini M, Rostasy K, Sartori S, Suppiej A, Kurth S, Franscini M, Walitza S, Huber R, Tarokh L, Bölsterli BK, Gerstenberg M. Sleep spindles across youth affected by schizophrenia or anti- N-methyl-D-aspartate-receptor encephalitis. Front Psychiatry 2023; 14:1055459. [PMID: 37377467 PMCID: PMC10292628 DOI: 10.3389/fpsyt.2023.1055459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 05/19/2023] [Indexed: 06/29/2023] Open
Abstract
Background Sleep disturbances are intertwined with the progression and pathophysiology of psychotic symptoms in schizophrenia. Reductions in sleep spindles, a major electrophysiological oscillation during non-rapid eye movement sleep, have been identified in patients with schizophrenia as a potential biomarker representing the impaired integrity of the thalamocortical network. Altered glutamatergic neurotransmission within this network via a hypofunction of the N-methyl-D-aspartate receptor (NMDAR) is one of the hypotheses at the heart of schizophrenia. This pathomechanism and the symptomatology are shared by anti-NMDAR encephalitis (NMDARE), where antibodies specific to the NMDAR induce a reduction of functional NMDAR. However, sleep spindle parameters have yet to be investigated in NMDARE and a comparison of these rare patients with young individuals with schizophrenia and healthy controls (HC) is lacking. This study aims to assess and compare sleep spindles across young patients affected by Childhood-Onset Schizophrenia (COS), Early-Onset Schizophrenia, (EOS), or NMDARE and HC. Further, the potential relationship between sleep spindle parameters in COS and EOS and the duration of the disease is examined. Methods Sleep EEG data of patients with COS (N = 17), EOS (N = 11), NMDARE (N = 8) aged 7-21 years old, and age- and sex-matched HC (N = 36) were assessed in 17 (COS, EOS) or 5 (NMDARE) electrodes. Sleep spindle parameters (sleep spindle density, maximum amplitude, and sigma power) were analyzed. Results Central sleep spindle density, maximum amplitude, and sigma power were reduced when comparing all patients with psychosis to all HC. Between patient group comparisons showed no differences in central spindle density but lower central maximum amplitude and sigma power in patients with COS compared to patients with EOS or NMDARE. Assessing the topography of spindle density, it was significantly reduced over 15/17 electrodes in COS, 3/17 in EOS, and 0/5 in NMDARE compared to HC. In the pooled sample of COS and EOS, a longer duration of illness was associated with lower central sigma power. Conclusions Patients with COS demonstrated more pronounced impairments of sleep spindles compared to patients with EOS and NMDARE. In this sample, there is no strong evidence that changes in NMDAR activity are related to spindle deficits.
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Affiliation(s)
- Maria E. Dimitriades
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
| | - Andjela Markovic
- Department of Pulmonology, University Hospital Zurich, Zurich, Switzerland
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Department of Psychology, University of Fribourg, Fribourg, Switzerland
| | - Silvano R. Gefferie
- Stichting Epilepsie Instellingen Nederland, Heemstede, Netherlands
- Department of Neurology, Leiden University Medical Center, Leiden, Netherlands
| | - Ashura Buckley
- Pediatrics and Neurodevelopmental Neuroscience, National Institute of Mental Health, Bethesda, MD, United States
| | - David I. Driver
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, United States
| | - Judith L. Rapoport
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, United States
| | - Margherita Nosadini
- Paediatric Neurology and Neurophysiology Unit, Department of Women's and Children's Health, University Hospital of Padova, Padova, Italy
- Neuroimmunology Group, Paediatric Research Institute Città della Speranza, Padova, Italy
| | - Kevin Rostasy
- Department of Pediatric Neurology, Children's Hospital Datteln, Witten/Herdecke University, Datteln, Germany
| | - Stefano Sartori
- Paediatric Neurology and Neurophysiology Unit, Department of Women's and Children's Health, University Hospital of Padova, Padova, Italy
- Neuroimmunology Group, Paediatric Research Institute Città della Speranza, Padova, Italy
| | - Agnese Suppiej
- Department of Medical Sciences, Pediatric Section, University of Ferrara, Ferrara, Italy
| | - Salome Kurth
- Department of Psychology, University of Fribourg, Fribourg, Switzerland
| | - Maurizia Franscini
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Reto Huber
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University of Zurich and Swiss Federal Institute of Technology Zurich, Zurich, Switzerland
| | - Leila Tarokh
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Bigna K. Bölsterli
- Child Development Center, University Children's Hospital Zurich, Zurich, Switzerland
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
- Department of Pediatric Neurology, University Children's Hospital Zurich, Zurich, Switzerland
- Department of Pediatric Neurology, Children's Hospital of Eastern Switzerland, St. Gallen, Switzerland
| | - Miriam Gerstenberg
- Children's Research Center, University Children's Hospital Zurich, Zurich, Switzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
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Lee EE, Adamowicz DH, Frangou S. An NIMH Workshop on Non-Affective Psychosis in Midlife and Beyond: Research Agenda on Phenomenology, Clinical Trajectories, Underlying Mechanisms, and Intervention Targets. Am J Geriatr Psychiatry 2023; 31:353-365. [PMID: 36858928 PMCID: PMC10990076 DOI: 10.1016/j.jagp.2023.01.019] [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: 11/15/2022] [Revised: 01/05/2023] [Accepted: 01/23/2023] [Indexed: 02/05/2023]
Abstract
We present a review of the state of the research in the phenomenology, clinical trajectories, biological mechanisms, aging biomarkers, and treatments for middle-aged and older people with schizophrenia (PwS) discussed at the NIMH sponsored workshop "Non-affective Psychosis in Midlife and Beyond." The growing population of PwS has specific clinical needs that require tailored and mechanistically derived interventions. Differentiating between the effects of aging and disease progression is a key challenge of studying older PwS. This review of the workshop highlights the recent findings in this understudied clinical population and the critical gaps in knowledge and consensus for research priorities. This review showcases the major challenges and opportunities for research to advance clinical care for this growing and understudied population.
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Affiliation(s)
- Ellen E Lee
- Department of Psychiatry (EEL, DA), University of California San Diego, La Jolla, CA; Sam and Rose Stein Institute for Research on Aging (EEL, DA), University of California San Diego, La Jolla, CA; Desert-Pacific Mental Illness Research Education and Clinical Center, Veterans Affairs San Diego Healthcare System (EEL), San Diego, CA.
| | - David H Adamowicz
- Department of Psychiatry (EEL, DA), University of California San Diego, La Jolla, CA; Sam and Rose Stein Institute for Research on Aging (EEL, DA), University of California San Diego, La Jolla, CA
| | - Sophia Frangou
- Department of Psychiatry (SF), University of British Columbia, Vancouver, British Columbia, Canada; Icahn School of Medicine at Mount Sinai (SF), New York, NY
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Lo LLH, Lee EHM, Hui CLM, Chong CSY, Chang WC, Chan SKW, Lin JJ, Lo WTL, Chen EYH. Effect of high-endurance exercise intervention on sleep-dependent procedural memory consolidation in individuals with schizophrenia: a randomized controlled trial. Psychol Med 2023; 53:1708-1720. [PMID: 34615565 DOI: 10.1017/s0033291721003196] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Little is known about the effects of physical exercise on sleep-dependent consolidation of procedural memory in individuals with schizophrenia. We conducted a randomized controlled trial (RCT) to assess the effectiveness of physical exercise in improving this cognitive function in schizophrenia. METHODS A three-arm parallel open-labeled RCT took place in a university hospital. Participants were randomized and allocated into either the high-intensity-interval-training group (HIIT), aerobic-endurance exercise group (AE), or psychoeducation group for 12 weeks, with three sessions per week. Seventy-nine individuals with schizophrenia spectrum disorder were contacted and screened for their eligibility. A total of 51 were successfully recruited in the study. The primary outcome was sleep-dependent procedural memory consolidation performance as measured by the finger-tapping motor sequence task (MST). Assessments were conducted during baseline and follow-up on week 12. RESULTS The MST performance scored significantly higher in the HIIT (n = 17) compared to the psychoeducation group (n = 18) after the week 12 intervention (p < 0.001). The performance differences between the AE (n = 16) and the psychoeducation (p = 0.057), and between the AE and the HIIT (p = 0.999) were not significant. Yet, both HIIT (p < 0.0001) and AE (p < 0.05) showed significant within-group post-intervention improvement. CONCLUSIONS Our results show that HIIT and AE were effective at reverting the defective sleep-dependent procedural memory consolidation in individuals with schizophrenia. Moreover, HIIT had a more distinctive effect compared to the control group. These findings suggest that HIIT may be a more effective treatment to improve sleep-dependent memory functions in individuals with schizophrenia than AE alone.
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Affiliation(s)
| | - Edwin Ho Ming Lee
- Department of Psychiatry, University of Hong Kong, Pok Fu Lam, Hong Kong
| | | | | | - Wing Chung Chang
- Department of Psychiatry, University of Hong Kong, Pok Fu Lam, Hong Kong
- State Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Sherry Kit Wa Chan
- Department of Psychiatry, University of Hong Kong, Pok Fu Lam, Hong Kong
- State Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Jessie Jingxia Lin
- Neuroscience and Neurological Rehabilitation, The Hong Kong Polytechnic University, Hung Hom, Hong Kong
| | | | - Eric Yu Hai Chen
- Department of Psychiatry, University of Hong Kong, Pok Fu Lam, Hong Kong
- State Key Laboratory of Brain and Cognitive Sciences, University of Hong Kong, Pok Fu Lam, Hong Kong
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Chen C, Wang K, Belkacem AN, Lu L, Yi W, Liang J, Huang Z, Ming D. A comparative analysis of sleep spindle characteristics of sleep-disordered patients and normal subjects. Front Neurosci 2023; 17:1110320. [PMID: 37065923 PMCID: PMC10098120 DOI: 10.3389/fnins.2023.1110320] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 01/24/2023] [Indexed: 03/31/2023] Open
Abstract
Spindles differ in density, amplitude, and frequency, and these variations reflect different physiological processes. Sleep disorders are characterized by difficulty in falling asleep and maintaining sleep. In this study, we proposed a new spindle wave detection algorithm, which was more effective compared with traditional detection algorithms such as wavelet algorithm. Besides, we recorded EEG data from 20 subjects with sleep disorders and 10 normal subjects, and then we compared the spindle characteristics of sleep-disordered subjects and normal subjects (those without any sleep disorder) to assess the spindle activity during human sleep. Specifically, we scored 30 subjects on the Pittsburgh Sleep Quality Index and then analyzed the association between their sleep quality scores and spindle characteristics, reflecting the effect of sleep disorders on spindle characteristics. We found a significant correlation between the sleep quality score and spindle density (p = 1.84 × 10−8, p-value <0.05 was considered statistically significant.). We, therefore, concluded that the higher the spindle density, the better the sleep quality. The correlation analysis between the sleep quality score and mean frequency of spindles yielded a p-value of 0.667, suggesting that the spindle frequency and sleep quality score were not significantly correlated. The p-value between the sleep quality score and spindle amplitude was 1.33 × 10−4, indicating that the mean amplitude of the spindle decreases as the score increases, and the mean spindle amplitude is generally slightly higher in the normal population than in the sleep-disordered population. The normal and sleep-disordered groups did not show obvious differences in the number of spindles between symmetric channels C3/C4 and F3/F4. The difference in the density and amplitude of the spindles proposed in this paper can be a reference characteristic for the diagnosis of sleep disorders and provide valuable objective evidence for clinical diagnosis. In summary, our proposed detection method can effectively improve the accuracy of sleep spindle wave detection with stable performance. Meanwhile, our study shows that the spindle density, frequency and amplitude are different between the sleep-disordered and normal populations.
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Affiliation(s)
- Chao Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Key Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin, China
| | - Kun Wang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Abdelkader Nasreddine Belkacem
- Department of Computer and Network Engineering, College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Lin Lu
- Zhonghuan Information College Tianjin University of Technology, Tianjin, China
| | - Weibo Yi
- Beijing Machine and Equipment Institute, Beijing, China
| | - Jun Liang
- Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhaoyang Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neuromodulation, Beijing, China
- *Correspondence: Zhaoyang Huang,
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Dong Ming,
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Laniepce A, Segobin S, André C, Bertran F, Boudehent C, Lahbairi N, Maillard A, Mary A, Urso L, Vabret F, Cabé N, Pitel AL, Rauchs G. Distinct Sleep Alterations in Alcohol Use Disorder Patients with and without Korsakoff's Syndrome: Relationship with Episodic Memory. J Clin Med 2023; 12:jcm12062440. [PMID: 36983439 PMCID: PMC10058993 DOI: 10.3390/jcm12062440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 03/30/2023] Open
Abstract
Alcohol Use Disorder (AUD) results in sleep disturbances that may have deleterious impacts on cognition, especially on memory. However, little is known about the sleep architecture in patients with Korsakoff's syndrome (KS). This study aims at characterizing sleep disturbances in KS compared to AUD without KS and at specifying the relationships with cognitive impairments. Twenty-nine AUD patients (22 without KS and 7 with KS) and 15 healthy controls underwent a neuropsychological assessment and a polysomnography. The severity of sleep-disordered breathing and sleep fragmentation was similar in AUD and KS patients compared to controls. Sleep architecture differed between both patient groups: the proportion of slow-wave sleep was reduced in AUD patients only, while a lower proportion of rapid-eye movement (REM) sleep was specifically observed in KS patients. The proportion of REM sleep correlated with the severity of episodic memory deficits when AUD and KS were examined together. These data provide evidence for both similarities and specificities regarding sleep alterations in AUD patients with and without KS. They also indicate that altered sleep architecture may contribute to the pathophysiology of alcohol-related memory disorders.
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Affiliation(s)
- Alice Laniepce
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
- Normandie Univ, UNIROUEN, CRFDP (EA 7475), 76000 Rouen, France
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Team NeuroPresage, Institut Blood and Brain @ Caen-Normandie, Cyceron, 14074 Caen, France
| | - Shailendra Segobin
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
| | - Claire André
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Team NeuroPresage, Institut Blood and Brain @ Caen-Normandie, Cyceron, 14074 Caen, France
| | - Françoise Bertran
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
- Unité D'exploration et de Traitement des Troubles du Sommeil, CHU de Caen, 14000 Caen, France
| | - Céline Boudehent
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
- Addiction Department, CHU de Caen, 14000 Caen, France
| | - Najlaa Lahbairi
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
| | - Angéline Maillard
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
| | - Alison Mary
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
| | - Laurent Urso
- Addiction Department, Centre Hospitalier de Roubaix, 59100 Roubaix, France
| | - François Vabret
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
| | - Nicolas Cabé
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Team NeuroPresage, Institut Blood and Brain @ Caen-Normandie, Cyceron, 14074 Caen, France
- Addiction Department, CHU de Caen, 14000 Caen, France
| | - Anne-Lise Pitel
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Team NeuroPresage, Institut Blood and Brain @ Caen-Normandie, Cyceron, 14074 Caen, France
- Institut Universitaire de France (IUF), 75231 Paris, France
| | - Géraldine Rauchs
- Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, 14000 Caen, France
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Team NeuroPresage, Institut Blood and Brain @ Caen-Normandie, Cyceron, 14074 Caen, France
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Chen C, Meng J, Belkacem AN, Lu L, Liu F, Yi W, Li P, Liang J, Huang Z, Ming D. Hierarchical fusion detection algorithm for sleep spindle detection. Front Neurosci 2023; 17:1105696. [PMID: 36968486 PMCID: PMC10035334 DOI: 10.3389/fnins.2023.1105696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 02/07/2023] [Indexed: 03/11/2023] Open
Abstract
BackgroundSleep spindles are a vital sign implying that human beings have entered the second stage of sleep. In addition, they can effectively reflect a person’s learning and memory ability, and clinical research has shown that their quantity and density are crucial markers of brain function. The “gold standard” of spindle detection is based on expert experience; however, the detection cost is high, and the detection time is long. Additionally, the accuracy of detection is influenced by subjectivity.MethodsTo improve detection accuracy and speed, reduce the cost, and improve efficiency, this paper proposes a layered spindle detection algorithm. The first layer used the Morlet wavelet and RMS method to detect spindles, and the second layer employed an improved k-means algorithm to improve spindle detection efficiency. The fusion algorithm was compared with other spindle detection algorithms to prove its effectiveness.ResultsThe hierarchical fusion spindle detection algorithm showed good performance stability, and the fluctuation range of detection accuracy was minimal. The average value of precision was 91.6%, at least five percentage points higher than other methods. The average value of recall could reach 89.1%, and the average value of specificity was close to 95%. The mean values of accuracy and F1-score in the subject sample data were 90.4 and 90.3%, respectively. Compared with other methods, the method proposed in this paper achieved significant improvement in terms of precision, recall, specificity, accuracy, and F1-score.ConclusionA spindle detection method with high steady-state accuracy and fast detection speed is proposed, which combines the Morlet wavelet with window RMS and an improved k-means algorithm. This method provides a powerful tool for the automatic detection of spindles and improves the efficiency of spindle detection. Through simulation experiments, the sampled data were analyzed and verified to prove the feasibility and effectiveness of this method.
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Affiliation(s)
- Chao Chen
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Key Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin, China
| | - Jiayuan Meng
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Abdelkader Nasreddine Belkacem
- Department of Computer and Network Engineering, College of Information Technology, United Arab Emirates University, Al Ain, United Arab Emirates
| | - Lin Lu
- Zhonghuan Information College Tianjin University of Technology, Tianjin, China
| | - Fengyue Liu
- Key Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin, China
| | - Weibo Yi
- Beijing Machine and Equipment Institute, Beijing, China
| | - Penghai Li
- Key Laboratory of Complex System Control Theory and Application, Tianjin University of Technology, Tianjin, China
| | - Jun Liang
- Department of Rehabilitation, Tianjin Medical University General Hospital, Tianjin, China
| | - Zhaoyang Huang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neuromodulation, Beijing, China
- *Correspondence: Zhaoyang Huang,
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
- Dong Ming,
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Demirlek C, Bora E. Sleep-dependent memory consolidation in schizophrenia: A systematic review and meta-analysis. Schizophr Res 2023; 254:146-154. [PMID: 36889181 DOI: 10.1016/j.schres.2023.02.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 02/06/2023] [Accepted: 02/27/2023] [Indexed: 03/10/2023]
Abstract
Sleep disturbances and cognitive impairment are both persistent and common features of schizophrenia. Accumulating evidence indicates that sleep-dependent memory consolidation might be impaired in patients with schizophrenia compared to healthy controls. The current systematic review was performed in accordance with PRISMA guidelines. A random-effects model was used to calculate effect sizes (Hedge's g). In the quantitative review, three separate meta-analyses were conducted for procedural memory in healthy controls, schizophrenia, and comparison between healthy controls and schizophrenia. Additionally, separate meta-analyses were conducted for the studies using finger tapping motor sequence task, as it is the most commonly used task. The current systematic review included 14 studies including 304 patients with schizophrenia and 209 healthy controls. The random-effects model analyses for sleep-dependent procedural memory consolidation resulted in a small effect size in schizophrenia (g = 0.26), a large effect size in healthy controls (g = 0.98), a moderate effect size in healthy controls vs schizophrenia (g = 0.64). For the studies using finger tapping motor sequence task, meta-analyses resulted in a small effect size in schizophrenia (g = 0.19), a large effect size in healthy controls (g = 1.07), a moderate effect size in healthy controls vs schizophrenia (g = 0.70). In the qualitative review, there was also impaired sleep-dependent declarative memory consolidation in schizophrenia compared to healthy controls. Current findings support that sleep improves memory consolidation in healthy adults, but there is a deficit in sleep-dependent memory consolidation in people with schizophrenia. Future studies investigating sleep-dependent consolidation of different memory subtypes with polysomnography in different stages of psychotic disorders are needed.
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Affiliation(s)
- Cemal Demirlek
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey.
| | - Emre Bora
- Department of Neurosciences, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey; Department of Psychiatry, Dokuz Eylul University Medical School, Izmir, Turkey; Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Carlton South, Victoria 3053, Australia
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The Feature of Sleep Spindle Deficits in Patients With Schizophrenia With and Without Auditory Verbal Hallucinations. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:331-342. [PMID: 34380082 DOI: 10.1016/j.bpsc.2021.07.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 06/10/2021] [Accepted: 07/29/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Previous sleep electroencephalography studies have detected abnormalities in sleep architecture and sleep spindle deficits in schizophrenia (SCZ), but the consistency of these results was not robust, which might be due to the small sample size and the influence of clinical factors such as the various medication therapies and symptom heterogeneity. This study aimed to regard auditory verbal hallucinations (AVHs) as a pointcut to downscale the heterogeneity of SCZ and explore whether some sleep architecture and spindle parameters were more severely impaired in SCZ patients with AVHs compared with those without AVHs. METHODS A total of 90 SCZ patients with AVHs, 92 SCZ patients without AVHs, and 91 healthy control subjects were recruited, and parameters of sleep architecture and spindle activities were compared between groups. The correlation between significant sleep parameters and clinical indicators was analyzed. RESULTS Deficits of sleep spindle activities at prefrontal electrodes and intrahemispheric spindle coherence were observed in both AVH and non-AVH groups, several of which were more serious in the AVH group. In addition, deficits of spindle activities at central and occipital electrodes and interhemispheric spindle coherence mainly manifested accompanying AVH symptoms, most of which were retained in the medication-naive first-episode patients, and were associated with Auditory Hallucination Rating Scale scores. CONCLUSIONS Our results suggest that the underlying mechanism of spindle deficits might be different between SCZ patients with and without AVHs. In the future, the sleep feature of SCZ patients with different symptoms and the influence of clinical factors, such as medication therapy, should be further illustrated.
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Zhang W, Xin M, Song G, Liang J. Childhood absence epilepsy patients with cognitive impairment have decreased sleep spindle density. Sleep Med 2023; 103:89-97. [PMID: 36773472 DOI: 10.1016/j.sleep.2023.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Revised: 12/22/2022] [Accepted: 01/15/2023] [Indexed: 01/20/2023]
Abstract
OBJECTIVE To explore the differences in sleep spindle (SS) characteristics during stage N2 sleep between children with childhood absence epilepsy and healthy controls, and between children with childhood absence epilepsy with or without cognitive impairment. METHODS We recruited 29 children (14 females, 15 males, mean age: 8 (2.5) years) with childhood absence epilepsy who did not undergone antiseizure treatments previously and 30 age-matched controls (14 females, 16 males, mean age: 9 (3.0) years). For all patients, data on medical history were collected. Each child was monitored overnight by long-term video electroencephalography and was evaluated by the Wechsler Intelligence Scale for Children-Fourth Edition. Next, we compared anterior SS characteristics, including density, frequency, cycle length, duration, amplitude, and percentage of sleep stages. RESULTS The childhood absence epilepsy group exhibited lower spindle density and duration in the first 37.5 min of stage N2 sleep than the control group (P < 0.01). A decrease in spindle density could be observed in the childhood absence epilepsy group with aggravated cognition impairment. The spindle density was substantially lower in the cognitively impaired group than in the cognitively unimpaired group (P < 0.01). No significant differences were observed in SS amplitude, SS frequency, SS cycle length, and the distribution of sleep stages. CONCLUSIONS Reduction in spindle density and duration is associated with the mechanisms underlying childhood absence epilepsy. The deficit in SS density is related with impaired cognition. This deficiency in SSs may be a useful predictive indicator of cognitive impairment in children with absence epilepsy, indicating that SSs may become a useful biomarker and potential adjuvant anti-seizure target for cognitive impairment caused by childhood absence epilepsy.
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Affiliation(s)
- Wei Zhang
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, China.
| | - Meiying Xin
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, China.
| | - Ge Song
- Department of Neurology and Neuroscience Center, The First Hospital of Jilin University, Changchun, China
| | - Jianmin Liang
- Department of Pediatric Neurology, The First Hospital of Jilin University, Changchun, China; Jilin Provincial Key Laboratory of Pediatric Neurology, Changchun, China.
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McLean RT, Buist E, St Clair D, Wei J. An examination of plasma autoantibodies against voltage gated calcium channels in schizophrenia. Brain Behav Immun Health 2023; 28:100603. [PMID: 36865984 PMCID: PMC9972490 DOI: 10.1016/j.bbih.2023.100603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 02/11/2023] [Indexed: 02/15/2023] Open
Abstract
Autoantibodies targeting the central nervous system have been shown to induce psychiatric symptoms resembling schizophrenia. Concurrently, genetic studies have characterised a number of risk variants associated with schizophrenia although their functional implications are largely unknown. Any biological effects of functional variants on protein function may potentially be replicated by the presence of autoantibodies against such proteins. Recent research has demonstrated that the R1346H variant in the CACNA1I gene coding for the Cav 3.3 protein results in a synaptic reduction of Cav3.3 voltage gated calcium channels and, consequently, sleep spindles, which have been shown to correlate with several symptom domains in patients with schizophrenia. The present study measured plasma levels of IgG against two peptides derived from CACNA1I and CACNA1C, respectively, in patients with schizophrenia and healthy controls. The results demonstrated that increased anti-CACNA1I IgG levels were associated with schizophrenia but not associated with any symptom domain related to the reduction of sleep spindles. In contrast to previously published work indicating that inflammation may be a marker for a depressive phenotype, plasma levels of IgG against either CACNA1I or CACNA1C peptides were not associated with depressive symptoms, suggesting that anti-Cav3.3 autoantibodies may function independently of pro-inflammatory processes.
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Affiliation(s)
- Ryan Thomas McLean
- Institute of Health Research and Innovation, University of the Highlands and Islands, Inverness, UK
| | - Elizabeth Buist
- Institute of Health Research and Innovation, University of the Highlands and Islands, Inverness, UK
- New Craigs Hospital, Inverness, UK
| | - David St Clair
- Department of Medicine and Dentistry, University of Aberdeen, Aberdeen, UK
| | - Jun Wei
- Institute of Health Research and Innovation, University of the Highlands and Islands, Inverness, UK
- Corresponding author. Institute of Health Research and Innovation, University of the Highlands and Islands, Centre for Health Science, Old Perth Road, Inverness, IV2 3JH, UK.
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Sleep spindles, stress and PTSD: The state of the science and future directions. Neurobiol Stress 2023; 23:100516. [PMID: 36861030 PMCID: PMC9969071 DOI: 10.1016/j.ynstr.2023.100516] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 01/16/2023] [Accepted: 01/17/2023] [Indexed: 01/27/2023] Open
Abstract
Sleep spindles are a signature feature of non-REM (NREM) sleep, with demonstrated relationships to sleep maintenance and learning and memory. Because PTSD is characterized by disturbances in sleep maintenance and in stress learning and memory, there is now a growing interest in examining the role of sleep spindles in the neurobiology of PTSD. This review provides an overview of methods for measuring and detecting sleep spindles as they pertain to human PTSD and stress research, presents a critical review of early findings examining sleep spindles in PTSD and stress neurobiology, and proposes several directions for future research. In doing so, this review underscores the extensive heterogeneity in sleep spindle measurement and detection methods, the wide range of spindle features that may be and have been examined, the many persisting unknowns about the clinical and functional relevance of those features, and the problems considering PTSD as a homogeneous group in between-group comparisons. This review also highlights the progress that has been made in this field and underscores the strong rationale for ongoing work in this area.
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Marshall FA. Temporal-lobe Epilepsy: Harmonic and Anharmonic Periodicity in Microeletrode Voltage. ARXIV 2023:arXiv:2301.06337v1. [PMID: 36713241 PMCID: PMC9882567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Temporal-lobe epilepsy in humans is often associated with widespread, synchronized neuron firing that co-occurs with traveling waves in local field potential. These traveling waves generate stochastic oscillations in a time series of microelectrode voltage, and previous work has deemed it informative for traveling-wave analysis to study the mean periodicity. This manuscript reveals that: a) mean voltage (i.e., traveling-wave periodicity) adequately explains the observed voltage periodicity only for a select few time intervals during seizure; and b) mean voltage has a 7 Hz cosine-series representation indicative of a nonlinear system response given alpha-rhythm input. The a) result implies that residual noise should be modelled explicitly, while b) motivates a departure from the conventional plane-wave modeling regime in source-localization efforts. The 7 Hz fundamental frequency is unsurprising given the relative transparency of the brain to 14 Hz alpha rhythms in neurophysiological diseases (14 Hz being a subharmonic frequency of the 7 Hz signal).
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Affiliation(s)
- François A Marshall
- Mathematics and Statistics Boston University, 111 Cummington Mall #140C, Boston, MA 02215, United States
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Holter KM, Pierce BE, Gould RW. Metabotropic glutamate receptor function and regulation of sleep-wake cycles. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2023; 168:93-175. [PMID: 36868636 DOI: 10.1016/bs.irn.2022.11.002] [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] [Indexed: 01/15/2023]
Abstract
Metabotropic glutamate (mGlu) receptors are the most abundant family of G-protein coupled receptors and are widely expressed throughout the central nervous system (CNS). Alterations in glutamate homeostasis, including dysregulations in mGlu receptor function, have been indicated as key contributors to multiple CNS disorders. Fluctuations in mGlu receptor expression and function also occur across diurnal sleep-wake cycles. Sleep disturbances including insomnia are frequently comorbid with neuropsychiatric, neurodevelopmental, and neurodegenerative conditions. These often precede behavioral symptoms and/or correlate with symptom severity and relapse. Chronic sleep disturbances may also be a consequence of primary symptom progression and can exacerbate neurodegeneration in disorders including Alzheimer's disease (AD). Thus, there is a bidirectional relationship between sleep disturbances and CNS disorders; disrupted sleep may serve as both a cause and a consequence of the disorder. Importantly, comorbid sleep disturbances are rarely a direct target of primary pharmacological treatments for neuropsychiatric disorders even though improving sleep can positively impact other symptom clusters. This chapter details known roles of mGlu receptor subtypes in both sleep-wake regulation and CNS disorders focusing on schizophrenia, major depressive disorder, post-traumatic stress disorder, AD, and substance use disorder (cocaine and opioid). In this chapter, preclinical electrophysiological, genetic, and pharmacological studies are described, and, when possible, human genetic, imaging, and post-mortem studies are also discussed. In addition to reviewing the important relationships between sleep, mGlu receptors, and CNS disorders, this chapter highlights the development of selective mGlu receptor ligands that hold promise for improving both primary symptoms and sleep disturbances.
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Affiliation(s)
- Kimberly M Holter
- Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Bethany E Pierce
- Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, NC, United States
| | - Robert W Gould
- Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, NC, United States.
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Bozic I, Rusterholz T, Mikutta C, Del Rio-Bermudez C, Nissen C, Adamantidis A. Coupling between the prelimbic cortex, nucleus reuniens, and hippocampus during NREM sleep remains stable under cognitive and homeostatic demands. Eur J Neurosci 2023; 57:106-128. [PMID: 36310348 DOI: 10.1111/ejn.15853] [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: 02/02/2022] [Revised: 09/28/2022] [Accepted: 10/05/2022] [Indexed: 02/02/2023]
Abstract
The interplay between the medial prefrontal cortex and hippocampus during non-rapid eye movement (NREM) sleep contributes to the consolidation of contextual memories. To assess the role of the thalamic nucleus reuniens (Nre) in this interaction, we investigated the coupling of neuro-oscillatory activities among prelimbic cortex, Nre, and hippocampus across sleep states and their role in the consolidation of contextual memories using multi-site electrophysiological recordings and optogenetic manipulations. We showed that ripples are time-locked to the Up state of cortical slow waves, the transition from UP to DOWN state in thalamic slow waves, the troughs of cortical spindles, and the peaks of thalamic spindles during spontaneous sleep, rebound sleep and sleep following a fear conditioning task. In addition, spiking activity in Nre increased before hippocampal ripples, and the phase-locking of hippocampal ripples and thalamic spindles during NREM sleep was stronger after acquisition of a fear memory. We showed that optogenetic inhibition of Nre neurons reduced phase-locking of ripples to cortical slow waves in the ventral hippocampus whilst their activation altered the preferred phase of ripples to slow waves in ventral and dorsal hippocampi. However, none of these optogenetic manipulations of Nre during sleep after acquisition of fear conditioning did alter sleep-dependent memory consolidation. Collectively, these results showed that Nre is central in modulating hippocampus and cortical rhythms during NREM sleep.
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Affiliation(s)
- Ivan Bozic
- Zentrum für Experimentelle Neurologie, Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland.,Department of Biomedical Research, University of Bern, Bern, Switzerland
| | - Thomas Rusterholz
- Zentrum für Experimentelle Neurologie, Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland.,Department of Biomedical Research, University of Bern, Bern, Switzerland
| | - Christian Mikutta
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Privatklinik Meiringen, Meiringen, Switzerland.,Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
| | - Carlos Del Rio-Bermudez
- Zentrum für Experimentelle Neurologie, Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland.,Department of Biomedical Research, University of Bern, Bern, Switzerland
| | - Christoph Nissen
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Antoine Adamantidis
- Zentrum für Experimentelle Neurologie, Department of Neurology, Inselspital University Hospital Bern, Bern, Switzerland.,Department of Biomedical Research, University of Bern, Bern, Switzerland.,Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK
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Petit JM, Strippoli MPF, Stephan A, Ranjbar S, Haba-Rubio J, Solelhac G, Heinzer R, Preisig M, Siclari F, Do KQ. Sleep spindles in people with schizophrenia, schizoaffective disorders or bipolar disorders: a pilot study in a general population-based cohort. BMC Psychiatry 2022; 22:758. [PMID: 36463186 PMCID: PMC9719140 DOI: 10.1186/s12888-022-04423-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Accepted: 11/24/2022] [Indexed: 12/04/2022] Open
Abstract
BACKGROUND Sleep spindles have been involved in sleep stabilization and sleep-related memory mechanisms and their deficit emerged as possible biomarker in schizophrenia. However, whether this sleep phenotype is also present in other disorders that share psychotic symptoms remains unclear. To address this gap, we assessed sleep spindles in participants of a prospective population-based cohort who underwent psychiatric assessment (CoLaus|PsyCoLaus) and polysomnographic recording (HypnoLaus). METHODS Sleep was recorded using ambulatory polysomnography in participants (N = 1037) to the PsyCoLaus study. Sleep spindle parameters were measured in people with a lifelong diagnosis of schizophrenia (SZ), schizoaffective depressive (SAD), schizoaffective manic (SAM), bipolar disorder type I (BP-I) and type II (BP-II). The associations between lifetime diagnostic status (independent variables, SZ, SAD, SAM, BPD-I, BPD-II, controls) and spindle parameters (dependent variables) including density, duration, frequency and maximum amplitude, for all (slow and fast), slow- and fast-spindle were assessed using linear mixed models. Pairwise comparisons of the different spindle parameters between the SZ group and each of the other psychiatric groups was performed using a contrast testing framework from our multiple linear mixed models. RESULTS Our results showed a deficit in the density and duration of sleep spindles in people with SZ. They also indicated that participants with a diagnosis of SAD, SAM, BP-I and BP-II exhibited different sleep spindle phenotypes. Interestingly, spindle densities and frequencies were different in people with a history of manic symptoms (SAM, BP-I, and BP-II) from those without (SZ, SAD). CONCLUSIONS Although carried out on a very small number of participants due to the low prevalence of these disorders in general population, this pilot study brought new elements that argued in favor of a deficit of sleep spindles density and duration in people with schizophrenia. In addition, while we could expect a gradual change in intensity of the same sleep spindle parameters through psychotic diagnoses, our results seem to indicate a more complex situation in which the frequency of sleep spindles might be more impacted by diagnoses including a history of mania or hypomania. Further studies with a larger number of participants are required to confirm these effects.
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Affiliation(s)
- Jean-Marie Petit
- Center for Psychiatric Neuroscience (CNP), CHUV, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Route de Cery 11c, CH-1008, Prilly, Switzerland.
| | - Marie-Pierre F. Strippoli
- grid.9851.50000 0001 2165 4204Center for Psychiatric Epidemiology and Psychopathology (CEPP), Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Aurélie Stephan
- grid.8515.90000 0001 0423 4662Center for Sleep Research and Investigation (CIRS), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Serateh Ranjbar
- grid.9851.50000 0001 2165 4204Center for Psychiatric Epidemiology and Psychopathology (CEPP), Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - José Haba-Rubio
- grid.8515.90000 0001 0423 4662Center for Sleep Research and Investigation (CIRS), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Geoffroy Solelhac
- grid.8515.90000 0001 0423 4662Center for Sleep Research and Investigation (CIRS), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Raphaël Heinzer
- grid.8515.90000 0001 0423 4662Center for Sleep Research and Investigation (CIRS), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Martin Preisig
- grid.9851.50000 0001 2165 4204Center for Psychiatric Epidemiology and Psychopathology (CEPP), Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Prilly, Switzerland
| | - Francesca Siclari
- grid.8515.90000 0001 0423 4662Center for Sleep Research and Investigation (CIRS), Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - Kim Q. Do
- grid.414250.60000 0001 2181 4933Center for Psychiatric Neuroscience (CNP), CHUV, Department of Psychiatry, Lausanne University Hospital and University of Lausanne, Route de Cery 11c, CH-1008 Prilly, Switzerland
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Bovy L, Weber FD, Tendolkar I, Fernández G, Czisch M, Steiger A, Zeising M, Dresler M. Non-REM sleep in major depressive disorder. Neuroimage Clin 2022; 36:103275. [PMID: 36451376 PMCID: PMC9723407 DOI: 10.1016/j.nicl.2022.103275] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 11/07/2022] [Accepted: 11/21/2022] [Indexed: 11/26/2022]
Abstract
Disturbed sleep is a key symptom in major depressive disorder (MDD). REM sleep alterations are well described in the current literature, but little is known about non-REM sleep alterations. Additionally, sleep disturbances relate to a variety of cognitive symptoms in MDD, but which features of non-REM sleep EEG contribute to this, remains unknown. We comprehensively analyzed non-REM sleep EEG features in two central channels in three independently collected datasets (N = 284 recordings of 216 participants). This exploratory and descriptive study included MDD patients with a broad age range, varying duration and severity of depression, unmedicated or medicated, age- and gender-matched to healthy controls. We explored changes in sleep architecture including sleep stages and cycles, spectral power, sleep spindles, slow waves (SW), and SW-spindle coupling. Next, we analyzed the association of these sleep features with acute measures of depression severity and overnight consolidation of procedural memory. Overall, no major systematic alterations in non-REM sleep architecture were found in patients compared to controls. For the microstructure of non-REM sleep, we observed a higher spindle amplitude in unmedicated patients compared to controls, and after the start of antidepressant medication longer SWs with lower amplitude and a more dispersed SW-spindle coupling. In addition, long-term, but not short-term medication seemed to lower spindle density. Overnight procedural memory consolidation was impaired in medicated patients and associated with lower sleep spindle density. Our results suggest that alterations of non-REM sleep EEG in MDD might be more subtle than previously reported. We discuss these findings in the context of antidepressant medication intake and age.
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Affiliation(s)
- Leonore Bovy
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center
| | - Frederik D. Weber
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center,Corresponding author.
| | - Indira Tendolkar
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center
| | - Guillén Fernández
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center
| | | | - Axel Steiger
- Max Planck Institute of Psychiatry, Munich, Germany
| | - Marcel Zeising
- Klinikum Ingolstadt, Centre of Mental Health, Ingolstadt, Germany
| | - Martin Dresler
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center
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Hassan U, Feld GB, Bergmann TO. Automated real-time EEG sleep spindle detection for brain-state-dependent brain stimulation. J Sleep Res 2022; 31:e13733. [PMID: 36130730 DOI: 10.1111/jsr.13733] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 10/14/2022]
Abstract
Sleep spindles are a hallmark electroencephalographic feature of non-rapid eye movement sleep, and are believed to be instrumental for sleep-dependent memory reactivation and consolidation. However, direct proof of their causal relevance is hard to obtain, and our understanding of their immediate neurophysiological consequences is limited. To investigate their causal role, spindles need to be targeted in real-time with sensory or non-invasive brain-stimulation techniques. While fully automated offline detection algorithms are well established, spindle detection in real-time is highly challenging due to their spontaneous and transient nature. Here, we present the real-time spindle detector, a robust multi-channel electroencephalographic signal-processing algorithm that enables the automated triggering of stimulation during sleep spindles in a phase-specific manner. We validated the real-time spindle detection method by streaming pre-recorded sleep electroencephalographic datasets to a real-time computer system running a Simulink® Real-Time™ implementation of the algorithm. Sleep spindles were detected with high levels of Sensitivity (~83%), Precision (~78%) and a convincing F1-Score (~81%) in reference to state-of-the-art offline algorithms (which reached similar or lower levels when compared with each other), for both naps and full nights, and largely independent of sleep scoring information. Detected spindles were comparable in frequency, duration, amplitude and symmetry, and showed the typical time-frequency characteristics as well as a centroparietal topography. Spindles were detected close to their centre and reliably at the predefined target phase. The real-time spindle detection algorithm therefore empowers researchers to target spindles during human sleep, and apply the stimulation method and experimental paradigm of their choice.
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Affiliation(s)
- Umair Hassan
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Mainz, Germany.,Leibniz Institute for Resilience Research, Mainz, Germany
| | - Gordon B Feld
- Department of Clinical Psychology, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Til Ole Bergmann
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Mainz, Germany.,Leibniz Institute for Resilience Research, Mainz, Germany.,Department of Neurology & Stroke, Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
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Stokes PA, Rath P, Possidente T, He M, Purcell S, Manoach DS, Stickgold R, Prerau MJ. Transient oscillation dynamics during sleep provide a robust basis for electroencephalographic phenotyping and biomarker identification. Sleep 2022; 46:6701543. [PMID: 36107467 PMCID: PMC9832519 DOI: 10.1093/sleep/zsac223] [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: 07/28/2022] [Revised: 08/30/2022] [Indexed: 01/19/2023] Open
Abstract
Transient oscillatory events in the sleep electroencephalogram represent short-term coordinated network activity. Of particular importance, sleep spindles are transient oscillatory events associated with memory consolidation, which are altered in aging and in several psychiatric and neurodegenerative disorders. Spindle identification, however, currently contains implicit assumptions derived from what waveforms were historically easiest to discern by eye, and has recently been shown to select only a high-amplitude subset of transient events. Moreover, spindle activity is typically averaged across a sleep stage, collapsing continuous dynamics into discrete states. What information can be gained by expanding our view of transient oscillatory events and their dynamics? In this paper, we develop a novel approach to electroencephalographic phenotyping, characterizing a generalized class of transient time-frequency events across a wide frequency range using continuous dynamics. We demonstrate that the complex temporal evolution of transient events during sleep is highly stereotyped when viewed as a function of slow oscillation power (an objective, continuous metric of depth-of-sleep) and phase (a correlate of cortical up/down states). This two-fold power-phase representation has large intersubject variability-even within healthy controls-yet strong night-to-night stability for individuals, suggesting a robust basis for phenotyping. As a clinical application, we then analyze patients with schizophrenia, confirming established spindle (12-15 Hz) deficits as well as identifying novel differences in transient non-rapid eye movement events in low-alpha (7-10 Hz) and theta (4-6 Hz) ranges. Overall, these results offer an expanded view of transient activity, describing a broad class of events with properties varying continuously across spatial, temporal, and phase-coupling dimensions.
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Affiliation(s)
- Patrick A Stokes
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Preetish Rath
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA,Department of Computer Science, Tufts University, Medford, MA, USA
| | - Thomas Possidente
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Mingjian He
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA,Harvard-MIT Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Shaun Purcell
- Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA, USA
| | - Dara S Manoach
- Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA
| | - Robert Stickgold
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Michael J Prerau
- Corresponding author. Michael J. Prerau, Brigham and Women's Hospital, Division of Sleep and Circadian Disorders, 221 Longwood Avenue, Boston, MA, 02115, USA.
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Perrottelli A, Giordano GM, Brando F, Giuliani L, Pezzella P, Mucci A, Galderisi S. Unveiling the Associations between EEG Indices and Cognitive Deficits in Schizophrenia-Spectrum Disorders: A Systematic Review. Diagnostics (Basel) 2022; 12:diagnostics12092193. [PMID: 36140594 PMCID: PMC9498272 DOI: 10.3390/diagnostics12092193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2022] [Revised: 09/05/2022] [Accepted: 09/06/2022] [Indexed: 11/16/2022] Open
Abstract
Cognitive dysfunctions represent a core feature of schizophrenia-spectrum disorders due to their presence throughout different illness stages and their impact on functioning. Abnormalities in electrophysiology (EEG) measures are highly related to these impairments, but the use of EEG indices in clinical practice is still limited. A systematic review of articles using Pubmed, Scopus and PsychINFO was undertaken in November 2021 to provide an overview of the relationships between EEG indices and cognitive impairment in schizophrenia-spectrum disorders. Out of 2433 screened records, 135 studies were included in a qualitative review. Although the results were heterogeneous, some significant correlations were identified. In particular, abnormalities in alpha, theta and gamma activity, as well as in MMN and P300, were associated with impairments in cognitive domains such as attention, working memory, visual and verbal learning and executive functioning during at-risk mental states, early and chronic stages of schizophrenia-spectrum disorders. The review suggests that machine learning approaches together with a careful selection of validated EEG and cognitive indices and characterization of clinical phenotypes might contribute to increase the use of EEG-based measures in clinical settings.
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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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The Portiloop: A deep learning-based open science tool for closed-loop brain stimulation. PLoS One 2022; 17:e0270696. [PMID: 35994482 PMCID: PMC9394839 DOI: 10.1371/journal.pone.0270696] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Accepted: 06/15/2022] [Indexed: 12/01/2022] Open
Abstract
Closed-loop brain stimulation refers to capturing neurophysiological measures such as electroencephalography (EEG), quickly identifying neural events of interest, and producing auditory, magnetic or electrical stimulation so as to interact with brain processes precisely. It is a promising new method for fundamental neuroscience and perhaps for clinical applications such as restoring degraded memory function; however, existing tools are expensive, cumbersome, and offer limited experimental flexibility. In this article, we propose the Portiloop, a deep learning-based, portable and low-cost closed-loop stimulation system able to target specific brain oscillations. We first document open-hardware implementations that can be constructed from commercially available components. We also provide a fast, lightweight neural network model and an exploration algorithm that automatically optimizes the model hyperparameters to the desired brain oscillation. Finally, we validate the technology on a challenging test case of real-time sleep spindle detection, with results comparable to off-line expert performance on the Massive Online Data Annotation spindle dataset (MODA; group consensus). Software and plans are available to the community as an open science initiative to encourage further development and advance closed-loop neuroscience research [https://github.com/Portiloop].
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