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Kayabekir M, Yağanoğlu M. SPINDILOMETER: a model describing sleep spindles on EEG signals for polysomnography. Phys Eng Sci Med 2024:10.1007/s13246-024-01428-7. [PMID: 38819611 DOI: 10.1007/s13246-024-01428-7] [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: 10/01/2023] [Accepted: 04/16/2024] [Indexed: 06/01/2024]
Abstract
This paper aims to present a model called SPINDILOMETER, which we propose to be integrated into polysomnography (PSG) devices for researchers focused on electrophysiological signals in PSG, physicians, and technicians practicing sleep in clinics, by examining the methods of the sleep electroencephalogram (EEG) signal analysis in recent years. For this purpose, an assist diagnostic model for PSG has been developed that measures the number and density of sleep spindles by analyzing EEG signals in PSG. EEG signals of 72 volunteers, 51 males and 21 females (age; 51.7 ± 3.42 years and body mass index; 37.6 ± 4.21) diagnosed with sleep-disordered breathing by PSG were analyzed by machine learning methods. The number and density of sleep spindles were compared between the classical method (EEG monitoring with the naked eye in PSG) ('method with naked eye') and the model (SPINDILOMETER). A strong positive correlation was found between 'method with naked eye' and SPINDILOMETER results (correlation coefficient: 0.987), and this correlation was statistically significant (p = 0.000). Confusion matrix (accuracy (94.61%), sensitivity (94.61%), specificity (96.60%)), and ROC analysis (AUC: 0.95) were performed to prove the adequacy of SPINDILOMETER (p = 0.000). In conclusion SPINDILOMETER can be included in PSG analysis performed in sleep laboratories. At the same time, this model provides diagnostic convenience to the physician in understanding the neurological events associated with sleep spindles and sheds light on research for thalamocortical regions in the fields of neurophysiology and electrophysiology.
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Affiliation(s)
- Murat Kayabekir
- Department of Physiology, Medical School, Atatürk University, 25240, Erzurum, Turkey.
| | - Mete Yağanoğlu
- Department of Computer Engineering, Faculty of Engineering, Atatürk University, Erzurum, Turkey
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2
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Bódizs R, Schneider B, Ujma PP, Horváth CG, Dresler M, Rosenblum Y. Fundamentals of sleep regulation: Model and benchmark values for fractal and oscillatory neurodynamics. Prog Neurobiol 2024; 234:102589. [PMID: 38458483 DOI: 10.1016/j.pneurobio.2024.102589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 01/26/2024] [Accepted: 03/05/2024] [Indexed: 03/10/2024]
Abstract
Homeostatic, circadian and ultradian mechanisms play crucial roles in the regulation of sleep. Evidence suggests that ratios of low-to-high frequency power in the electroencephalogram (EEG) spectrum indicate the instantaneous level of sleep pressure, influenced by factors such as individual sleep-wake history, current sleep stage, age-related differences and brain topography characteristics. These effects are well captured and reflected in the spectral exponent, a composite measure of the constant low-to-high frequency ratio in the periodogram, which is scale-free and exhibits lower interindividual variability compared to slow wave activity, potentially serving as a suitable standardization and reference measure. Here we propose an index of sleep homeostasis based on the spectral exponent, reflecting the level of membrane hyperpolarization and/or network bistability in the central nervous system in humans. In addition, we advance the idea that the U-shaped overnight deceleration of oscillatory slow and fast sleep spindle frequencies marks the biological night, providing somnologists with an EEG-index of circadian sleep regulation. Evidence supporting this assertion comes from studies based on sleep replacement, forced desynchrony protocols and high-resolution analyses of sleep spindles. Finally, ultradian sleep regulatory mechanisms are indicated by the recurrent, abrupt shifts in dominant oscillatory frequencies, with spindle ranges signifying non-rapid eye movement and non-spindle oscillations - rapid eye movement phases of the sleep cycles. Reconsidering the indicators of fundamental sleep regulatory processes in the framework of the new Fractal and Oscillatory Adjustment Model (FOAM) offers an appealing opportunity to bridge the gap between the two-process model of sleep regulation and clinical somnology.
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Affiliation(s)
- Róbert Bódizs
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary.
| | - Bence Schneider
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary
| | - Péter P Ujma
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary
| | - Csenge G Horváth
- Institute of Behavioural Sciences, Semmelweis University, Budapest, Hungary
| | - Martin Dresler
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, the Netherlands
| | - Yevgenia Rosenblum
- Radboud University Medical Centre, Donders Institute for Brain, Cognition and Behavior, Nijmegen, the Netherlands
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3
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Silva Pereira S, Özer EE, Sebastian-Galles N. Complexity of STG signals and linguistic rhythm: a methodological study for EEG data. Cereb Cortex 2024; 34:bhad549. [PMID: 38236741 DOI: 10.1093/cercor/bhad549] [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: 08/01/2023] [Revised: 12/29/2023] [Accepted: 12/30/2023] [Indexed: 02/06/2024] Open
Abstract
The superior temporal and the Heschl's gyri of the human brain play a fundamental role in speech processing. Neurons synchronize their activity to the amplitude envelope of the speech signal to extract acoustic and linguistic features, a process known as neural tracking/entrainment. Electroencephalography has been extensively used in language-related research due to its high temporal resolution and reduced cost, but it does not allow for a precise source localization. Motivated by the lack of a unified methodology for the interpretation of source reconstructed signals, we propose a method based on modularity and signal complexity. The procedure was tested on data from an experiment in which we investigated the impact of native language on tracking to linguistic rhythms in two groups: English natives and Spanish natives. In the experiment, we found no effect of native language but an effect of language rhythm. Here, we compare source projected signals in the auditory areas of both hemispheres for the different conditions using nonparametric permutation tests, modularity, and a dynamical complexity measure. We found increasing values of complexity for decreased regularity in the stimuli, giving us the possibility to conclude that languages with less complex rhythms are easier to track by the auditory cortex.
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Affiliation(s)
- Silvana Silva Pereira
- Center for Brain and Cognition, Department of Information and Communications Technologies, Universitat Pompeu Fabra, 08005 Barcelona, Spain
| | - Ege Ekin Özer
- Center for Brain and Cognition, Department of Information and Communications Technologies, Universitat Pompeu Fabra, 08005 Barcelona, Spain
| | - Nuria Sebastian-Galles
- Center for Brain and Cognition, Department of Information and Communications Technologies, Universitat Pompeu Fabra, 08005 Barcelona, Spain
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Simpson BK, Rangwani R, Abbasi A, Chung JM, Reed CM, Gulati T. Disturbed laterality of non-rapid eye movement sleep oscillations in post-stroke human sleep: a pilot study. Front Neurol 2023; 14:1243575. [PMID: 38099067 PMCID: PMC10719949 DOI: 10.3389/fneur.2023.1243575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Accepted: 11/08/2023] [Indexed: 12/17/2023] Open
Abstract
Sleep is known to promote recovery post-stroke. However, there is a paucity of data profiling sleep oscillations in the post-stroke human brain. Recent rodent work showed that resurgence of physiologic spindles coupled to sleep slow oscillations (SOs) and concomitant decrease in pathological delta (δ) waves is associated with sustained motor performance gains during stroke recovery. The goal of this study was to evaluate bilaterality of non-rapid eye movement (NREM) sleep-oscillations (namely SOs, δ-waves, spindles, and their nesting) in post-stroke patients vs. healthy control subjects. We analyzed NREM-marked electroencephalography (EEG) data in hospitalized stroke-patients (n = 5) and healthy subjects (n = 3). We used a laterality index to evaluate symmetry of NREM oscillations across hemispheres. We found that stroke subjects had pronounced asymmetry in the oscillations, with a predominance of SOs, δ-waves, spindles, and nested spindles in affected hemisphere, when compared to the healthy subjects. Recent preclinical work classified SO-nested spindles as restorative post-stroke and δ-wave-nested spindles as pathological. We found that the ratio of SO-nested spindles laterality index to δ-wave-nested spindles laterality index was lower in stroke subjects. Using linear mixed models (which included random effects of concurrent pharmacologic drugs), we found large and medium effect size for δ-wave nested spindle and SO-nested spindle, respectively. Our results in this pilot study indicate that considering laterality index of NREM oscillations might be a useful metric for assessing recovery post-stroke and that factoring in pharmacologic drugs may be important when targeting sleep modulation for neurorehabilitation post-stroke.
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Affiliation(s)
- Benjamin K. Simpson
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Rohit Rangwani
- Department of Biomedical Sciences, Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Bioengineering Graduate Program, Department of Bioengineering, Henry Samueli School of Engineering, University of California, Los Angeles, Los Angeles, CA, United States
| | - Aamir Abbasi
- Department of Biomedical Sciences, Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Jeffrey M. Chung
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Chrystal M. Reed
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
| | - Tanuj Gulati
- Department of Neurology, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Department of Biomedical Sciences, Center for Neural Science and Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, United States
- Bioengineering Graduate Program, Department of Bioengineering, Henry Samueli School of Engineering, University of California, Los Angeles, Los Angeles, CA, United States
- Department of Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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Denis D, Bottary R, Cunningham TJ, Drummond SPA, Straus LD. Beta spectral power during sleep is associated with impaired recall of extinguished fear. Sleep 2023; 46:zsad209. [PMID: 37542729 PMCID: PMC10566240 DOI: 10.1093/sleep/zsad209] [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: 02/27/2023] [Revised: 07/13/2023] [Indexed: 08/07/2023] Open
Abstract
The failure to retain memory for extinguished fear plays a major role in the maintenance of posttraumatic stress disorder (PTSD), with successful extinction recall necessary for symptom reduction. Disturbed sleep, a hallmark symptom of PTSD, impairs fear extinction recall. However, our understanding of the electrophysiological mechanisms underpinning sleep's role in extinction retention remains underdetermined. We examined the relationship between the microarchitecture of sleep and extinction recall in healthy humans (n = 71, both male and females included) and a pilot study in individuals with PTSD (n = 12). Participants underwent a fear conditioning and extinction protocol over 2 days, with sleep recording occurring between conditioning and extinction. Twenty-four hours after extinction learning, participants underwent extinction recall. Power spectral density (PSD) was computed for pre- and post-extinction learning sleep. Increased beta-band PSD (~17-26 Hz) during pre-extinction learning sleep was associated with worse extinction recall in healthy participants (r = 0.41, p = .004). Beta PSD was highly stable across three nights of sleep (intraclass correlation coefficients > 0.92). Results suggest beta-band PSD is specifically implicated in difficulties recalling extinguished fear.
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Affiliation(s)
- Dan Denis
- Department of Psychology, University of York, York, UK
| | - Ryan Bottary
- Institute for Graduate Clinical Psychology, Widener University, Chester, PA, USA
| | - Tony J Cunningham
- Center for Sleep and Cognition, Psychiatry Department, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Sean P A Drummond
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Clayton, VIC, Australia
| | - Laura D Straus
- Mental Health Service, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Department of Psychiatry, University of California, San Francisco, CA, USA
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Kumral D, Matzerath A, Leonhart R, Schönauer M. Spindle-dependent memory consolidation in healthy adults: A meta-analysis. Neuropsychologia 2023; 189:108661. [PMID: 37597610 DOI: 10.1016/j.neuropsychologia.2023.108661] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 06/23/2023] [Accepted: 08/12/2023] [Indexed: 08/21/2023]
Abstract
Accumulating evidence suggests a central role for sleep spindles in the consolidation of new memories. However, no meta-analysis of the association between sleep spindles and memory performance has been conducted so far. Here, we report meta-analytical evidence for spindle-memory associations and investigate how multiple factors, including memory type, spindle type, spindle characteristics, and EEG topography affect this relationship. The literature search yielded 53 studies reporting 1427 effect sizes, resulting in a small to moderate effect for the average association. We further found that spindle-memory associations were significantly stronger for procedural memory than for declarative memory. Neither spindle types nor EEG scalp topography had an impact on the strength of the spindle-memory relation, but we observed a distinct functional role of global and fast sleep spindles, especially for procedural memory. We also found a moderation effect of spindle characteristics, with power showing the largest effect sizes. Collectively, our findings suggest that sleep spindles are involved in learning, thereby representing a general physiological mechanism for memory consolidation.
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Affiliation(s)
- Deniz Kumral
- Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg Im Breisgau, Germany; Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
| | - Alina Matzerath
- Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg Im Breisgau, Germany
| | - Rainer Leonhart
- Institute of Psychology, Social Psychology and Methodology, University of Freiburg, Freiburg Im Breisgau, Germany
| | - Monika Schönauer
- Institute of Psychology, Neuropsychology, University of Freiburg, Freiburg Im Breisgau, Germany; Bernstein Center Freiburg, Freiburg Im Breisgau, Germany
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Golkashani HA, Ghorbani S, Leong RLF, Ong JL, Chee MWL. Advantage conferred by overnight sleep on schema-related memory may last only a day. SLEEP ADVANCES : A JOURNAL OF THE SLEEP RESEARCH SOCIETY 2023; 4:zpad019. [PMID: 37193282 PMCID: PMC10155747 DOI: 10.1093/sleepadvances/zpad019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 03/07/2023] [Indexed: 05/18/2023]
Abstract
Study Objectives Sleep contributes to declarative memory consolidation. Independently, schemas benefit memory. Here we investigated how sleep compared with active wake benefits schema consolidation 12 and 24 hours after initial learning. Methods Fifty-three adolescents (age: 15-19 years) randomly assigned into sleep and active wake groups participated in a schema-learning protocol based on transitive inference (i.e. If B > C and C > D then B > D). Participants were tested immediately after learning and following 12-, and 24-hour intervals of wake or sleep for both the adjacent (e.g. B-C, C-D; relational memory) and inference pairs: (e.g.: B-D, B-E, and C-E). Memory performance following the respective 12- and 24-hour intervals were analyzed using a mixed ANOVA with schema (schema, no-schema) as the within-participant factor, and condition (sleep, wake) as the between-participant factor. Results Twelve hours after learning, there were significant main effects of condition (sleep, wake) and schema, as well as a significant interaction, whereby schema-related memory was significantly better in the sleep condition compared to wake. Higher sleep spindle density was most consistently associated with greater overnight schema-related memory benefit. After 24 hours, the memory advantage of initial sleep was diminished. Conclusions Overnight sleep preferentially benefits schema-related memory consolidation following initial learning compared with active wake, but this advantage may be eroded after a subsequent night of sleep. This is possibly due to delayed consolidation that might occur during subsequent sleep opportunities in the wake group. Clinical Trial Information Name: Investigating Preferred Nap Schedules for Adolescents (NFS5) URL: https://clinicaltrials.gov/ct2/show/NCT04044885. Registration: NCT04044885.
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Affiliation(s)
- Hosein Aghayan Golkashani
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Shohreh Ghorbani
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ruth L F Leong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ju Lynn Ong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael W L Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
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8
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Liu H, Liang H, Yu X, Wang G, Han Y, Yan M, Li S, Wang W. Enhanced external counterpulsation modulates the heartbeat evoked potential. Front Physiol 2023; 14:1144073. [PMID: 37078023 PMCID: PMC10106756 DOI: 10.3389/fphys.2023.1144073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Accepted: 03/23/2023] [Indexed: 04/05/2023] Open
Abstract
Introduction: Accumulating evidence suggests that enhanced external counterpulsation (EECP) influences cardiac functions, hemodynamic characteristics and cerebral blood flow. However, little is known about whether or how the EECP affects the brain-heart coupling to produce these physiological and functional changes. We aimed to determine if the brain-heart coupling is altered during or after EECP intervention by assessing the heartbeat evoked potential (HEP) in healthy adults.Methods: Based on a random sham-controlled design, simultaneous electroencephalography and electrocardiography signals as well as blood pressure and flow status data were recorded before, during and after two consecutive 30-min EECP in 40 healthy adults (female/male: 17/23; age: 23.1 ± 2.3 years). HEP amplitude, frequency domain heart rate variability, electroencephalographic power and hemodynamic measurements of 21 subjects (female/male: 10/11; age: 22.7 ± 2.1 years) receiving active EECP were calculated and compared with those of 19 sham control subjects (female/male: 7/12; age: 23.6 ± 2.5 years).Results: EECP intervention caused immediate obvious fluctuations of HEP from 100 to 400 ms after T-peak and increased HEP amplitudes in the (155–169) ms, (354–389) ms and (367–387) ms time windows after T-peak in the region of the frontal pole lobe. The modifications in HEP amplitude were not associated with changes in the analyzed significant physiological measurements and hemodynamic variables.Discussion: Our study provides evidence that the HEP is modulated by immediate EECP stimuli. We speculate that the increased HEP induced by EECP may be a marker of enhanced brain-heart coupling. HEP may serve as a candidate biomarker for the effects and responsiveness to EECP.
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Affiliation(s)
- Hongyun Liu
- Research Center for Biomedical Engineering, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
- *Correspondence: Hongyun Liu, ; Muyang Yan, ; Shijun Li, ; Weidong Wang,
| | - Hui Liang
- Department of Hyperbaric Oxygen, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Xiaohua Yu
- Research Center for Biomedical Engineering, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
| | - Guojing Wang
- Research Center for Biomedical Engineering, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
| | - Yi Han
- Research Center for Biomedical Engineering, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
| | - Muyang Yan
- Department of Hyperbaric Oxygen, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- *Correspondence: Hongyun Liu, ; Muyang Yan, ; Shijun Li, ; Weidong Wang,
| | - Shijun Li
- Department of Diagnostic Radiology, The First Medical Center, Chinese PLA General Hospital, Beijing, China
- *Correspondence: Hongyun Liu, ; Muyang Yan, ; Shijun Li, ; Weidong Wang,
| | - Weidong Wang
- Research Center for Biomedical Engineering, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
- *Correspondence: Hongyun Liu, ; Muyang Yan, ; Shijun Li, ; Weidong Wang,
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EEG Network Analysis in Epilepsy with Generalized Tonic–Clonic Seizures Alone. Brain Sci 2022; 12:brainsci12111574. [DOI: 10.3390/brainsci12111574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 11/14/2022] [Accepted: 11/15/2022] [Indexed: 11/22/2022] Open
Abstract
Many contradictory theories regarding epileptogenesis in idiopathic generalized epilepsy have been proposed. This study aims to define the network that takes part in the formation of the spike-wave discharges in patients with generalized tonic–clonic seizures alone (GTCSa) and elucidate the network characteristics. Furthermore, we intend to define the most influential brain areas and clarify the connectivity pattern among them. The data were collected from 23 patients with GTCSa utilizing low-density electroencephalogram (EEG). The source localization of generalized spike-wave discharges (GSWDs) was conducted using the Standardized low-resolution brain electromagnetic tomography (sLORETA) methodology. Cortical connectivity was calculated utilizing the imaginary part of coherence. The network characteristics were investigated through small-world propensity and the integrated value of influence (IVI). Source localization analysis estimated that most sources of GSWDs were in the superior frontal gyrus and anterior cingulate. Graph theory analysis revealed that epileptic sources created a network that tended to be regularized during generalized spike-wave activity. The IVI analysis concluded that the most influential nodes were the left insular gyrus and the left inferior parietal gyrus at 3 and 4 Hz, respectively. In conclusion, some nodes acted mainly as generators of GSWDs and others as influential ones across the whole network.
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10
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Schneider B, Szalárdy O, Ujma PP, Simor P, Gombos F, Kovács I, Dresler M, Bódizs R. Scale-free and oscillatory spectral measures of sleep stages in humans. Front Neuroinform 2022; 16:989262. [PMID: 36262840 PMCID: PMC9574340 DOI: 10.3389/fninf.2022.989262] [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: 07/08/2022] [Accepted: 09/14/2022] [Indexed: 11/13/2022] Open
Abstract
Power spectra of sleep electroencephalograms (EEG) comprise two main components: a decaying power-law corresponding to the aperiodic neural background activity, and spectral peaks present due to neural oscillations. “Traditional” band-based spectral methods ignore this fundamental structure of the EEG spectra and thus are susceptible to misrepresenting the underlying phenomena. A fitting method that attempts to separate and parameterize the aperiodic and periodic spectral components called “fitting oscillations and one over f” (FOOOF) was applied to a set of annotated whole-night sleep EEG recordings of 251 subjects from a wide age range (4–69 years). Most of the extracted parameters exhibited sleep stage sensitivity; significant main effects and interactions of sleep stage, age, sex, and brain region were found. The spectral slope (describing the steepness of the aperiodic component) showed especially large and consistent variability between sleep stages (and low variability between subjects), making it a candidate indicator of sleep states. The limitations and arisen problems of the FOOOF method are also discussed, possible solutions for some of them are suggested.
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Affiliation(s)
- Bence Schneider
- Department of Cognitive Science, Budapest University of Technology and Economics, Budapest, Hungary
- Institute of Behavioural Sciences, Semmelweis University Budapest, Budapest, Hungary
- *Correspondence: Bence Schneider
| | - Orsolya Szalárdy
- Institute of Behavioural Sciences, Semmelweis University Budapest, Budapest, Hungary
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest, Hungary
| | - Péter P. Ujma
- Institute of Behavioural Sciences, Semmelweis University Budapest, Budapest, Hungary
| | - Péter Simor
- Institute of Psychology, ELTE, Eötvös Loránd University, Budapest, Hungary
| | - Ferenc Gombos
- Department of General Psychology, Pázmány Péter Catholic University, Budapest, Hungary
- MTA—PPKE Adolescent Development Research Group, Budapest, Hungary
| | - Ilona Kovács
- Department of General Psychology, Pázmány Péter Catholic University, Budapest, Hungary
| | - Martin Dresler
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, Netherlands
| | - Róbert Bódizs
- Institute of Behavioural Sciences, Semmelweis University Budapest, Budapest, Hungary
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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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12
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Cunningham TJ, Stickgold R, Kensinger EA. Investigating the effects of sleep and sleep loss on the different stages of episodic emotional memory: A narrative review and guide to the future. Front Behav Neurosci 2022; 16:910317. [PMID: 36105652 PMCID: PMC9466000 DOI: 10.3389/fnbeh.2022.910317] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 08/03/2022] [Indexed: 11/29/2022] Open
Abstract
For two decades, sleep has been touted as one of the primary drivers for the encoding, consolidation, retention, and retrieval of episodic emotional memory. Recently, however, sleep’s role in emotional memory processing has received renewed scrutiny as meta-analyses and reviews have indicated that sleep may only contribute a small effect that hinges on the content or context of the learning and retrieval episodes. On the one hand, the strong perception of sleep’s importance in maintaining memory for emotional events may have been exacerbated by publication bias phenomena, such as the “winner’s curse” and “file drawer problem.” On the other hand, it is plausible that there are sets of circumstances that lead to consistent and reliable effects of sleep on emotional memory; these circumstances may depend on factors such as the placement and quality of sleep relative to the emotional experience, the content and context of the emotional experience, and the probes and strategies used to assess memory at retrieval. Here, we review the literature on how sleep (and sleep loss) influences each stage of emotional episodic memory. Specifically, we have separated previous work based on the placement of sleep and sleep loss in relation to the different stages of emotional memory processing: (1) prior to encoding, (2) immediately following encoding during early consolidation, (3) during extended consolidation, separated from initial learning, (4) just prior to retrieval, and (5) post-retrieval as memories may be restructured and reconsolidated. The goals of this review are three-fold: (1) examine phases of emotional memory that sleep may influence to a greater or lesser degree, (2) explicitly identify problematic overlaps in traditional sleep–wake study designs that are preventing the ability to better disentangle the potential role of sleep in the different stages of emotional memory processing, and (3) highlight areas for future research by identifying the stages of emotional memory processing in which the effect of sleep and sleep loss remains under-investigated. Here, we begin the task of better understanding the contexts and factors that influence the relationship between sleep and emotional memory processing and aim to be a valuable resource to facilitate hypothesis generation and promote important future research.
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Affiliation(s)
- Tony J. Cunningham
- Center for Sleep and Cognition, Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States
- Department of Psychology and Neuroscience, Boston College, Chestnut Hill, MA, United States
- *Correspondence: Tony J. Cunningham,
| | - Robert Stickgold
- Center for Sleep and Cognition, Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, United States
| | - Elizabeth A. Kensinger
- Department of Psychology and Neuroscience, Boston College, Chestnut Hill, MA, United States
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13
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Schreiner SJ, Werth E, Ballmer L, Valko PO, Schubert KM, Imbach LL, Baumann CR, Maric A, Baumann-Vogel H. Sleep spindle and slow wave activity in Parkinson disease with excessive daytime sleepiness. Sleep 2022; 46:6649751. [PMID: 35877159 DOI: 10.1093/sleep/zsac165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
Study Objectives
Excessive daytime sleepiness (EDS) is a common and devastating symptom in Parkinson disease (PD), but surprisingly most studies showed that EDS is independent from nocturnal sleep disturbance measured with polysomnography. Quantitative electroencephalography (EEG) may reveal additional insights by measuring the EEG hallmarks of non-rapid eye movement (NREM) sleep, namely slow waves and spindles. Here, we tested the hypothesis that EDS in PD is associated with nocturnal sleep disturbance revealed by quantitative NREM sleep EEG markers.
Methods
Patients with PD (n = 130) underwent polysomnography followed by spectral analysis to calculate spindle frequency activity, slow-wave activity (SWA), and overnight SWA decline, which reflects the dissipation of homeostatic sleep pressure. We used the Epworth Sleepiness Scale (ESS) to assess subjective daytime sleepiness and define EDS (ESS > 10). All examinations were part of an evaluation for deep brain stimulation.
Results
Patients with EDS (n = 46) showed reduced overnight decline of SWA (p = 0.036) and reduced spindle frequency activity (p = 0.032) compared with patients without EDS. Likewise, more severe daytime sleepiness was associated with reduced SWA decline (ß= −0.24 p = 0.008) and reduced spindle frequency activity (ß= −0.42, p < 0.001) across all patients. Reduced SWA decline, but not daytime sleepiness, was associated with poor sleep quality and continuity at polysomnography.
Conclusions
Our data suggest that daytime sleepiness in PD patients is associated with sleep disturbance revealed by quantitative EEG, namely reduced overnight SWA decline and reduced spindle frequency activity. These findings could indicate that poor sleep quality, with incomplete dissipation of homeostatic sleep pressure, may contribute to EDS in PD.
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Affiliation(s)
- Simon J Schreiner
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Sleep and Health Zurich (SHZ), University of Zurich , Zurich , Switzerland
| | - Esther Werth
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Sleep and Health Zurich (SHZ), University of Zurich , Zurich , Switzerland
| | - Leonie Ballmer
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
| | - Philipp O Valko
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Sleep and Health Zurich (SHZ), University of Zurich , Zurich , Switzerland
| | - Kai M Schubert
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
| | - Lukas L Imbach
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Swiss Epilepsy Center, Klinik Lengg , Zurich , Switzerland
| | - Christian R Baumann
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Sleep and Health Zurich (SHZ), University of Zurich , Zurich , Switzerland
| | - Angelina Maric
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Sleep and Health Zurich (SHZ), University of Zurich , Zurich , Switzerland
| | - Heide Baumann-Vogel
- Department of Neurology, University Hospital Zurich, University of Zurich , Zurich , Switzerland
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich , Zurich , Switzerland
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14
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Jeong JH, Cho JH, Lee YE, Lee SH, Shin GH, Kweon YS, Millán JDR, Müller KR, Lee SW. 2020 International brain-computer interface competition: A review. Front Hum Neurosci 2022; 16:898300. [PMID: 35937679 PMCID: PMC9354666 DOI: 10.3389/fnhum.2022.898300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 07/01/2022] [Indexed: 11/16/2022] Open
Abstract
The brain-computer interface (BCI) has been investigated as a form of communication tool between the brain and external devices. BCIs have been extended beyond communication and control over the years. The 2020 international BCI competition aimed to provide high-quality neuroscientific data for open access that could be used to evaluate the current degree of technical advances in BCI. Although there are a variety of remaining challenges for future BCI advances, we discuss some of more recent application directions: (i) few-shot EEG learning, (ii) micro-sleep detection (iii) imagined speech decoding, (iv) cross-session classification, and (v) EEG(+ear-EEG) detection in an ambulatory environment. Not only did scientists from the BCI field compete, but scholars with a broad variety of backgrounds and nationalities participated in the competition to address these challenges. Each dataset was prepared and separated into three data that were released to the competitors in the form of training and validation sets followed by a test set. Remarkable BCI advances were identified through the 2020 competition and indicated some trends of interest to BCI researchers.
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Affiliation(s)
- Ji-Hoon Jeong
- School of Computer Science, Chungbuk National University, Cheongju, South Korea
| | - Jeong-Hyun Cho
- Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea
| | - Young-Eun Lee
- Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea
| | - Seo-Hyun Lee
- Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea
| | - Gi-Hwan Shin
- Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea
| | - Young-Seok Kweon
- Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea
| | - José del R. Millán
- Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, United States
| | - Klaus-Robert Müller
- Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea
- Machine Learning Group, Department of Computer Science, Berlin Institute of Technology, Berlin, Germany
- Max Planck Institute for Informatics, Saarbrucken, Germany
- Department of Artificial Intelligence, Korea University, Seoul, South Korea
| | - Seong-Whan Lee
- Department of Brain and Cognitive Engineering, Korea University, Seoul, South Korea
- Department of Artificial Intelligence, Korea University, Seoul, South Korea
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15
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Aghayan Golkashani H, Leong RLF, Ghorbani S, Ong JL, Fernández G, Chee MWL. A sleep schedule incorporating naps benefits the transformation of hierarchical knowledge. Sleep 2022; 45:6516991. [PMID: 35090173 PMCID: PMC8996033 DOI: 10.1093/sleep/zsac025] [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: 09/24/2021] [Revised: 12/14/2021] [Indexed: 11/14/2022] Open
Abstract
Abstract
Study Objectives
The learning brain establishes schemas (knowledge structures) that benefit subsequent learning. We investigated how sleep and having a schema might benefit initial learning followed by rearranged and expanded memoranda. We concurrently examined the contributions of sleep spindles and slow-wave sleep to learning outcomes.
Methods
Fifty-three adolescents were randomly assigned to an 8 h Nap schedule (6.5 h nocturnal sleep with a 90-minute daytime nap) or an 8 h No-Nap, nocturnal-only sleep schedule. The study spanned 14 nights, simulating successive school weeks. We utilized a transitive inference task involving hierarchically ordered faces. Initial learning to set up the schema was followed by rearrangement of the hierarchy (accommodation) and hierarchy expansion (assimilation). The expanded sequence was restudied. Recall of hierarchical knowledge was tested after initial learning and at multiple points for all subsequent phases. As a control, both groups underwent a No-schema condition where the hierarchy was introduced and modified without opportunity to set up a schema. Electroencephalography accompanied the multiple sleep opportunities.
Results
There were main effects of Nap schedule and Schema condition evidenced by superior recall of initial learning, reordered and expanded memoranda. Improved recall was consistently associated with higher fast spindle density but not slow-wave measures. This was true for both nocturnal sleep and daytime naps.
Conclusion
A sleep schedule incorporating regular nap opportunities compared to one that only had nocturnal sleep benefited building of robust and flexible schemas, facilitating recall of the subsequently rearranged and expanded structured knowledge. These benefits appear to be strongly associated with fast spindles.
Clinical Trial registration
NCT04044885 (https://clinicaltrials.gov/ct2/show/NCT04044885).
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Affiliation(s)
- Hosein Aghayan Golkashani
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ruth L F Leong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Shohreh Ghorbani
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ju Lynn Ong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Guillén Fernández
- Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, Nijmegen, Netherlands
| | - Michael W L Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
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16
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Zis P, Liampas A, Artemiadis A, Tsalamandris G, Neophytou P, Unwin Z, Kimiskidis VK, Hadjigeorgiou GM, Varrassi G, Zhao Y, Sarrigiannis PG. EEG Recordings as Biomarkers of Pain Perception: Where Do We Stand and Where to Go? Pain Ther 2022; 11:369-380. [PMID: 35322392 PMCID: PMC9098726 DOI: 10.1007/s40122-022-00372-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Accepted: 03/07/2022] [Indexed: 11/25/2022] Open
Abstract
Introduction The universality and complexity of pain, which is highly prevalent, yield its significance to both patients and researchers. Developing a non-invasive tool that can objectively measure pain is of the utmost importance for clinical and research purposes. Traditionally electroencephalography (EEG) has been mostly used in epilepsy; however, over the recent years EEG has become an important non-invasive clinical tool that has helped increase our understanding of brain network complexities and for the identification of areas of dysfunction. This review aimed to investigate the role of EEG recordings as potential biomarkers of pain perception. Methods A systematic search of the PubMed database led to the identification of 938 papers, of which 919 were excluded as a result of not meeting the eligibility criteria, and one article was identified through screening of the reference lists of the 19 eligible studies. Ultimately, 20 papers were included in this systematic review. Results Changes of the cortical activation have potential, though the described changes are not always consistent. The most consistent finding is the increase in the delta and gamma power activity. Only a limited number of studies have looked into brain networks encoding pain perception. Conclusion Although no robust EEG biomarkers of pain perception have been identified yet, EEG has potential and future research should be attempted. Designing strong research protocols, controlling for potential risk of biases, as well as investigating brain networks rather than isolated cortical changes will be crucial in this attempt. Supplementary Information The online version contains supplementary material available at 10.1007/s40122-022-00372-2.
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Affiliation(s)
- Panagiotis Zis
- Medical School, University of Cyprus, Nicosia, Cyprus
- Medical School, University of Sheffield, Sheffield, UK
- Department of Neurology, Nicosia General Hospital, Nicosia, Cyprus
| | - Andreas Liampas
- Department of Neurology, Nicosia General Hospital, Nicosia, Cyprus
| | - Artemios Artemiadis
- Medical School, University of Cyprus, Nicosia, Cyprus
- Department of Neurology, Nicosia General Hospital, Nicosia, Cyprus
| | | | | | - Zoe Unwin
- Department of Clinical Neurophysiology, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
| | - Vasilios K. Kimiskidis
- 1st Department of Neurology, AHEPA University Hospital, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Georgios M. Hadjigeorgiou
- Medical School, University of Cyprus, Nicosia, Cyprus
- Department of Neurology, Nicosia General Hospital, Nicosia, Cyprus
| | | | - Yifan Zhao
- School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield, UK
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17
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Gutiérrez-Tobal GC, Gomez-Pilar J, Kheirandish-Gozal L, Martín-Montero A, Poza J, Álvarez D, del Campo F, Gozal D, Hornero R. Pediatric Sleep Apnea: The Overnight Electroencephalogram as a Phenotypic Biomarker. Front Neurosci 2021; 15:644697. [PMID: 34803578 PMCID: PMC8595944 DOI: 10.3389/fnins.2021.644697] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Accepted: 10/07/2021] [Indexed: 12/02/2022] Open
Abstract
Pediatric obstructive sleep apnea (OSA) is a prevalent disorder that disrupts sleep and is associated with neurocognitive and behavioral negative consequences, potentially hampering the development of children for years. However, its relationships with sleep electroencephalogram (EEG) have been scarcely investigated. Here, our main objective was to characterize the overnight EEG of OSA-affected children and its putative relationships with polysomnographic measures and cognitive functions. A two-step analysis involving 294 children (176 controls, 57% males, age range: 5-9 years) was conducted for this purpose. First, the activity and irregularity of overnight EEG spectrum were characterized in the typical frequency bands by means of relative spectral power and spectral entropy, respectively: δ1 (0.1-2 Hz), δ2 (2-4 Hz), θ (4-8 Hz), α (8-13 Hz), σ (10-16 Hz), β1 (13-19 Hz), β2 (19-30 Hz), and γ (30-70 Hz). Then, a correlation network analysis was conducted to evaluate relationships between them, six polysomnography variables (apnea-hypopnea index, respiratory arousal index, spontaneous arousal index, overnight minimum blood oxygen saturation, wake time after sleep onset, and sleep efficiency), and six cognitive scores (differential ability scales, Peabody picture vocabulary test, expressive vocabulary test, design copying, phonological processing, and tower test). We found that as the severity of the disease increases, OSA broadly affects sleep EEG to the point that the information from the different frequency bands becomes more similar, regardless of activity or irregularity. EEG activity and irregularity information from the most severely affected children were significantly associated with polysomnographic variables, which were coherent with both micro and macro sleep disruptions. We hypothesize that the EEG changes caused by OSA could be related to the occurrence of respiratory-related arousals, as well as thalamic inhibition in the slow oscillation generation due to increases in arousal levels aimed at recovery from respiratory events. Furthermore, relationships between sleep EEG and cognitive scores emerged regarding language, visual-spatial processing, and executive function with pronounced associations found with EEG irregularity in δ1 (Peabody picture vocabulary test and expressive vocabulary test maximum absolute correlations 0.61 and 0.54) and β2 (phonological processing, 0.74; design copying, 0.65; and Tow 0.52). Our results show that overnight EEG informs both sleep alterations and cognitive effects of pediatric OSA. Moreover, EEG irregularity provides new information that complements and expands the classic EEG activity analysis. These findings lay the foundation for the use of sleep EEG to assess cognitive changes in pediatric OSA.
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Affiliation(s)
- Gonzalo C. Gutiérrez-Tobal
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Leila Kheirandish-Gozal
- Department of Child Health, Child Health Research Institute, The University of Missouri School of Medicine, Columbia, MO, United States
| | | | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
| | - Daniel Álvarez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
- Pneumology Service, Río Hortega University Hospital, Valladolid, Spain
| | - Félix del Campo
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
- Pneumology Service, Río Hortega University Hospital, Valladolid, Spain
| | - David Gozal
- Department of Child Health, Child Health Research Institute, The University of Missouri School of Medicine, Columbia, MO, United States
| | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Valladolid, Spain
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18
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Real-Time Excitation of Slow Oscillations during Deep Sleep Using Acoustic Stimulation. SENSORS 2021; 21:s21155169. [PMID: 34372405 PMCID: PMC8347755 DOI: 10.3390/s21155169] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Revised: 07/27/2021] [Accepted: 07/28/2021] [Indexed: 11/20/2022]
Abstract
Slow-wave synchronous acoustic stimulation is a promising research and therapeutic tool. It is essential to clearly understand the principles of the synchronization methods, to know their performances and limitations, and, most importantly, to have a clear picture of the effect of stimulation on slow-wave activity (SWA). This paper covers the mentioned and currently missing parts of knowledge that are essential for the appropriate development of the method itself and future applications. Artificially streamed real sleep EEG data were used to quantitatively compare the two currently used real-time methods: the phase-locking loop (PLL) and the fixed-step stimulus in our own implementation. The fixed-step stimulation method was concluded to be more reliable and practically applicable compared to the PLL method. The sleep experiment with chronic insomnia patients in our sleep laboratory was analyzed in order to precisely characterize the effect of sound stimulation during deep sleep. We found that there is a significant phase synchronization of delta waves, which were shown to be the most sensitive metric of the effect of acoustic stimulation compared to commonly used averaged signal and power analyses. This finding may change the understanding of the effect and function of the SWA stimulation described in the literature.
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19
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Schreiner T, Petzka M, Staudigl T, Staresina BP. Endogenous memory reactivation during sleep in humans is clocked by slow oscillation-spindle complexes. Nat Commun 2021; 12:3112. [PMID: 34035303 PMCID: PMC8149676 DOI: 10.1038/s41467-021-23520-2] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 05/04/2021] [Indexed: 02/04/2023] Open
Abstract
Sleep is thought to support memory consolidation via reactivation of prior experiences, with particular electrophysiological sleep signatures (slow oscillations (SOs) and sleep spindles) gating the information flow between relevant brain areas. However, empirical evidence for a role of endogenous memory reactivation (i.e., without experimentally delivered memory cues) for consolidation in humans is lacking. Here, we devised a paradigm in which participants acquired associative memories before taking a nap. Multivariate decoding was then used to capture endogenous memory reactivation during non-rapid eye movement (NREM) sleep in surface EEG recordings. Our results reveal reactivation of learning material during SO-spindle complexes, with the precision of SO-spindle coupling predicting reactivation strength. Critically, reactivation strength (i.e. classifier evidence in favor of the previously studied stimulus category) in turn predicts the level of consolidation across participants. These results elucidate the memory function of sleep in humans and emphasize the importance of SOs and spindles in clocking endogenous consolidation processes.
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Affiliation(s)
- Thomas Schreiner
- Department of Psychology, Ludwig-Maximilians-University, Munich, Germany
| | - Marit Petzka
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Tobias Staudigl
- Department of Psychology, Ludwig-Maximilians-University, Munich, Germany
| | - Bernhard P Staresina
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK.
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20
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Yoon JE, Oh D, Hwang I, Park JA, Im HJ, Lee SK, Jung KY, Park SH, Thomas RJ, Shin C, Yun CH. Sleep structure and electroencephalographic spectral power of middle-aged or older adults: Normative values by age and sex in the Korean population. J Sleep Res 2021; 30:e13358. [PMID: 33949014 DOI: 10.1111/jsr.13358] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 03/23/2021] [Accepted: 03/29/2021] [Indexed: 11/28/2022]
Abstract
The fine structure of sleep electrocortical activity reflects health and disease. The current study provides normative data for sleep structure and electroencephalography (EEG) spectral power measures derived from overnight polysomnography (PSG) and examines the effect of age and sex among Korean middle-aged and older adults with or without obstructive sleep apnea (OSA). We analysed home PSG data from 1,153 adult participants of an ongoing population-based cohort study, the Korean Genome and Epidemiology Study. Sleep stages were visually scored and spectral power was measured on a single-channel EEG (C4-A1). We computed spectral power for five frequency ranges. The EEG power was reported in relative (%) and log-transformed absolute values (µV2 ). With ageing, the proportion of N1 sleep increased, whereas N3 decreased, which is more noticeable in men than in women. The amount of N3 was relatively low in this cohort. With ageing, relative delta power decreased and alpha and sigma power increased for the whole sleep period, which was more pronounced during REM sleep in non-OSA. For men compared with women, relative theta power was lower during REM and sigma and beta were higher during N1 sleep. The differences of relative powers by age and sex in OSA were comparable to those in non-OSA. In a community-based Korean population, we present normative data of sleep structure and spectral power for middle-aged or older adults of a non-Caucasian ethnicity. The values varied with age and sex and were not influenced by sleep apnea.
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Affiliation(s)
- Jee-Eun Yoon
- Department of Neurology, Uijeongbu Eulji Medical Center, Uijeongbu, Korea
| | - Dana Oh
- Department of Neurology, Seoul Medical Center, Seoul, Korea
| | - Inha Hwang
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Jung Ah Park
- Department of Neurology, School of Medicine, Catholic University of Daegu, Daegu, Korea
| | - Hee-Jin Im
- Department of Neurology, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Korea
| | - Seung Ku Lee
- Institute of Human Genomic Study, Korea University Ansan Hospital, Ansan, Korea
| | - Ki-Young Jung
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Korea
| | - Seong-Ho Park
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea
| | - Robert J Thomas
- Division of Pulmonary Critical Care and Sleep Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, USA
| | - Chol Shin
- Institute of Human Genomic Study, Korea University Ansan Hospital, Ansan, Korea.,Division of Pulmonary, Sleep and Critical Care Medicine, Department of Internal Medicine, Korea University Ansan Hospital, Ansan, Korea
| | - Chang-Ho Yun
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea
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21
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Ruch S, Fehér K, Homan S, Morishima Y, Mueller SM, Mueller SV, Dierks T, Grieder M. Bi-Temporal Anodal Transcranial Direct Current Stimulation during Slow-Wave Sleep Boosts Slow-Wave Density but Not Memory Consolidation. Brain Sci 2021; 11:brainsci11040410. [PMID: 33805063 PMCID: PMC8064104 DOI: 10.3390/brainsci11040410] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 03/15/2021] [Accepted: 03/22/2021] [Indexed: 12/31/2022] Open
Abstract
Slow-wave sleep (SWS) has been shown to promote long-term consolidation of episodic memories in hippocampo–neocortical networks. Previous research has aimed to modulate cortical sleep slow-waves and spindles to facilitate episodic memory consolidation. Here, we instead aimed to modulate hippocampal activity during slow-wave sleep using transcranial direct current stimulation in 18 healthy humans. A pair-associate episodic memory task was used to evaluate sleep-dependent memory consolidation with face–occupation stimuli. Pre- and post-nap retrieval was assessed as a measure of memory performance. Anodal stimulation with 2 mA was applied bilaterally over the lateral temporal cortex, motivated by its particularly extensive connections to the hippocampus. The participants slept in a magnetic resonance (MR)-simulator during the recordings to test the feasibility for a future MR-study. We used a sham-controlled, double-blind, counterbalanced randomized, within-subject crossover design. We show that stimulation vs. sham significantly increased slow-wave density and the temporal coupling of fast spindles and slow-waves. While retention of episodic memories across sleep was not affected across the entire sample of participants, it was impaired in participants with below-average pre-sleep memory performance. Hence, bi-temporal anodal direct current stimulation applied during sleep enhanced sleep parameters that are typically involved in memory consolidation, but it failed to improve memory consolidation and even tended to impair consolidation in poor learners. These findings suggest that artificially enhancing memory-related sleep parameters to improve memory consolidation can actually backfire in those participants who are in most need of memory improvement.
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Affiliation(s)
- Simon Ruch
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, 3012 Bern, Switzerland;
- Department of Neurosurgery and Neurotechnology, Institute for Neuromodulation and Neurotechnology, University of Tübingen, 72076 Tübingen, Germany
| | - Kristoffer Fehér
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (K.F.); (S.H.); (Y.M.); (S.M.M.); (S.V.M.); (T.D.)
| | - Stephanie Homan
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (K.F.); (S.H.); (Y.M.); (S.M.M.); (S.V.M.); (T.D.)
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry, University of Zurich, 8032 Zurich, Switzerland
| | - Yosuke Morishima
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (K.F.); (S.H.); (Y.M.); (S.M.M.); (S.V.M.); (T.D.)
| | - Sarah Maria Mueller
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (K.F.); (S.H.); (Y.M.); (S.M.M.); (S.V.M.); (T.D.)
| | - Stefanie Verena Mueller
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (K.F.); (S.H.); (Y.M.); (S.M.M.); (S.V.M.); (T.D.)
| | - Thomas Dierks
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (K.F.); (S.H.); (Y.M.); (S.M.M.); (S.V.M.); (T.D.)
| | - Matthias Grieder
- Translational Research Center, University Hospital of Psychiatry and Psychotherapy, University of Bern, 3000 Bern, Switzerland; (K.F.); (S.H.); (Y.M.); (S.M.M.); (S.V.M.); (T.D.)
- Correspondence:
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Fehér KD, Wunderlin M, Maier JG, Hertenstein E, Schneider CL, Mikutta C, Züst MA, Klöppel S, Nissen C. Shaping the slow waves of sleep: A systematic and integrative review of sleep slow wave modulation in humans using non-invasive brain stimulation. Sleep Med Rev 2021; 58:101438. [PMID: 33582581 DOI: 10.1016/j.smrv.2021.101438] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2020] [Revised: 10/14/2020] [Accepted: 11/10/2020] [Indexed: 01/19/2023]
Abstract
The experimental study of electroencephalographic slow wave sleep (SWS) stretches over more than half a century and has corroborated its importance for basic physiological processes, such as brain plasticity, metabolism and immune system functioning. Alterations of SWS in aging or pathological conditions suggest that modulating SWS might constitute a window for clinically relevant interventions. This work provides a systematic and integrative review of SWS modulation through non-invasive brain stimulation in humans. A literature search using PubMed, conducted in May 2020, identified 3220 studies, of which 82 fulfilled inclusion criteria. Three approaches have been adopted to modulate the macro- and microstructure of SWS, namely auditory, transcranial electrical and transcranial magnetic stimulation. Our current knowledge about the modulatory mechanisms, the space of stimulation parameters and the physiological and behavioral effects are reported and evaluated. The integration of findings suggests that sleep slow wave modulation bears the potential to promote our understanding of the functions of SWS and to develop new treatments for conditions of disrupted SWS.
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Affiliation(s)
- Kristoffer D Fehér
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Marina Wunderlin
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Jonathan G Maier
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Elisabeth Hertenstein
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Carlotta L Schneider
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Christian Mikutta
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland; Privatklinik Meiringen, Meiringen, Switzerland
| | - Marc A Züst
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Christoph Nissen
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland.
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