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Carro‐Domínguez M, Huwiler S, Stich FM, Sala R, Aziri F, Trippel A, Heimhofer C, Huber R, Meissner SN, Wenderoth N, Lustenberger C. Overnight changes in performance fatigability and their relationship to modulated deep sleep oscillations via auditory stimulation. J Sleep Res 2025; 34:e14371. [PMID: 39420437 PMCID: PMC12069738 DOI: 10.1111/jsr.14371] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2024] [Revised: 09/11/2024] [Accepted: 09/16/2024] [Indexed: 10/19/2024]
Abstract
Deep sleep oscillations are proposed to be central in restoring brain function and to affect different aspects of motor performance such as facilitating the consolidation of motor sequences resulting in faster and more accurate sequence tapping. Yet, whether deep sleep modulates performance fatigability during fatiguing tasks remains unexplored. We investigated overnight changes in tapping speed and resistance against performance fatigability via a finger tapping task. During fast tapping, fatigability manifests as a reduction in speed (or "motor slowing") which affects all tapping tasks, including motor sequences used to study motor memory formation. We further tested whether overnight changes in performance fatigability are influenced by enhancing deep sleep oscillations using auditory stimulation. We found an overnight increase in tapping speed alongside a reduction in performance fatigability and perceived workload. Auditory stimulation led to a global enhancement of slow waves and both slow and fast spindles during the stimulation window and a local increase in slow spindles in motor areas across the night. However, overnight performance improvements were not significantly modulated by auditory stimulation and changes in tapping speed or performance fatigability were not predicted by individual changes in deep sleep oscillations. Our findings demonstrate overnight changes in fatigability but revealed no evidence suggesting that this effect is causally linked to temporary augmentation of slow waves or sleep spindles. Our results are important for future studies using tapping tasks to test the relationship between sleep and motor memory consolidation, as overnight changes in objectively measured and subjectively perceived fatigue likely impact behavioural outcomes.
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Affiliation(s)
- Manuel Carro‐Domínguez
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Stephanie Huwiler
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Fabia M. Stich
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Rossella Sala
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Florent Aziri
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Anna Trippel
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Caroline Heimhofer
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Reto Huber
- Centre of Competence Sleep & Health ZurichUniversity of ZurichZurichSwitzerland
- Neuroscience Centre Zurich (ZNZ)University of Zurich, ETH ZurichZurichSwitzerland
- Child Development CentreUniversity Children's Hospital, University of ZurichZurichSwitzerland
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital ZurichUniversity of ZurichZurichSwitzerland
| | - Sarah Nadine Meissner
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
| | - Nicole Wenderoth
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
- Neuroscience Centre Zurich (ZNZ)University of Zurich, ETH ZurichZurichSwitzerland
- Future Health Technologies, Singapore‐ETH CenterCampus for Research Excellence and Technological Enterprise (CREATE)Singapore
| | - Caroline Lustenberger
- Neural Control of Movement Laboratory, Institute of Human Movement Sciences and Sport, Department of Health Sciences and TechnologyETH ZurichZurichSwitzerland
- Centre of Competence Sleep & Health ZurichUniversity of ZurichZurichSwitzerland
- Neuroscience Centre Zurich (ZNZ)University of Zurich, ETH ZurichZurichSwitzerland
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Lee M, Hong JK, Lee Y, Yoon IY. Transcranial alternating current stimulation in subjects with insomnia symptoms: A randomized, double-blind and controlled study. J Psychiatr Res 2025; 186:129-136. [PMID: 40239389 DOI: 10.1016/j.jpsychires.2025.04.020] [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: 01/20/2025] [Revised: 04/09/2025] [Accepted: 04/10/2025] [Indexed: 04/18/2025]
Abstract
BACKGROUND This study evaluated whether transcranial alternating current stimulation (tACS), a non-invasive brain stimulation technique, could alleviate insomnia symptoms. METHODS Participants exhibiting insomnia symptoms without meeting the criteria for insomnia disorder were recruited and randomized into 0.5 Hz, 100 Hz, or a sham group. To maximize the delivery of intracranial stimulation, a carrier frequency of 10 kHz was utilized. Participants were required to use the device for 30 min, twice daily for six weeks. RESULTS Eighty-seven participants (74 females, mean age = 54.15 ± 0.73 years) were randomized and completed the trial. The Insomnia Severity Index scores showed significant improvement across all three groups without a significant difference between groups (sham: 13.83 to 8.45, p < 0.05; 0.5 Hz: 12.03 to 8.79, p < 0.05; 100 Hz: 12.38 to 7.83, p < 0.05). In the average sleep diary over four days, sleep latency (SL) and wake after sleep onset (WASO) decreased in all three groups (sham, 0.5 Hz, 100 Hz) without significant group by visit interaction (SL: -5.74 min, -8.94 min, -16.53 min, respectively, p = 0.345; WASO: -10.74 min, -23.62 min, -16.73 min, respectively, p = 0.431). No significant improvements were observed in actigraphy-based sleep measures. CONCLUSIONS tACS did not demonstrate greater efficacy than sham treatment in ameliorating symptoms of insomnia. Future studies should account for the potent placebo effect on sleep and the potential for high carrier frequencies to obscure the target frequencies.
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Affiliation(s)
- Minji Lee
- Department of Psychiatry, Soonchunhyang University Seoul Hospital, Seoul, 04401, Republic of Korea; Department of Psychiatry, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea
| | - Jung Kyung Hong
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, Republic of Korea
| | - Yeaeun Lee
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, Republic of Korea
| | - In-Young Yoon
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, Republic of Korea; Department of Psychiatry, Seoul National University College of Medicine, Seoul, 03080, Republic of Korea.
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Ross G, Huang WA, Reiling J, Zhang M, Park J, Radtke-Schuller S, Hopfinger J, Zuberer A, Frohlich F. Switching state to engage and sustain attention: Dynamic synchronization of the frontoparietal network. Prog Neurobiol 2025; 250:102777. [PMID: 40389123 DOI: 10.1016/j.pneurobio.2025.102777] [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: 11/01/2024] [Revised: 05/09/2025] [Accepted: 05/12/2025] [Indexed: 05/21/2025]
Abstract
Sustained attention (SA) is essential for maintaining focus over time, with disruptions linked to various neurological and psychiatric disorders. The oscillatory dynamics and functional connectivity in the dorsal frontoparietal network (dFPN) are crucial in SA. However, the neuronal mechanisms that control the level of SA, especially in response to heightened attentional demands, remain poorly understood. To examine the role of rhythmic synchronization in the dFPN in SA, we recorded local field potential and single unit activity in ferrets that performed the 5-Choice Serial Reaction Time Task (5-CSRTT) under both low and high attentional load. Under high attentional load, dFPN exhibited a pronounced state shift that corresponded with behavioral changes in the animal. Prior to the onset of the target stimulus, animals transitioned from a stationary state, characterized by frontal theta oscillations and dFPN theta connectivity, to an active exploration state associated with sensory processing. This shift was indexed by a suppression of inhibitory alpha oscillations and an increase in excitatory theta and gamma oscillations in parietal cortex. We further show that dFPN theta connectivity predicts performance fluctuations under high attentional load. Together, these results suggest that behavioral strategies for maintaining SA are tightly linked to neuronal state dynamics in the dFPN. Importantly, these findings identify rhythmic synchronization within the FPN as a potential neural target for novel therapeutic strategies for disrupted attention.
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Affiliation(s)
- Grace Ross
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA
| | - Wei A Huang
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA
| | - Jared Reiling
- Department of Computational Mathematics, Science, and Engineering, Michigan State University, East Lansing, MI, USA
| | - Mengsen Zhang
- Department of Computational Mathematics, Science, and Engineering, Michigan State University, East Lansing, MI, USA
| | - Jimin Park
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Susanne Radtke-Schuller
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joseph Hopfinger
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Agnieszka Zuberer
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Carolina Center for Neurostimulation, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA; Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, USA; Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, USA; Department of Neurology, University of North Carolina, Chapel Hill, NC, USA.
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4
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Hu X, Gao Y, Song Y, Yang X, Liu K, Luo B, Sun Y, Li L. The Effect of Mattress Firmness on Sleep Architecture and PSG Characteristics. Nat Sci Sleep 2025; 17:865-878. [PMID: 40365263 PMCID: PMC12071755 DOI: 10.2147/nss.s503222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2024] [Accepted: 03/22/2025] [Indexed: 05/15/2025] Open
Abstract
Background The influence of sleep environments on sleep quality is well-established; however, the specific role of mattress design remains underexplored. Existing studies focus primarily on ergonomic aspects, such as pressure relief and spinal support, yet lack conclusive evidence linking these features to improved sleep quality. Objective and Methods This study aimed to evaluate the effects of mattress firmness on sleep quality. Twelve participants with a moderate body mass index (BMI) were tested across three levels of mattress firmness: soft (32.6 HA), medium (64.6 HA), and firm (83.8 HA). Sleep architecture and neurophysiological activity were assessed using polysomnography (PSG), with EEG-derived features, including power spectral characteristics, sleep spindle activity, and slow-wave parameters, further analyzed. Results Our findings indicate that a medium-firm mattress provides better sleep quality, reflected in a narrower range (Range=xmax-xmin) of sleep duration, efficiency, and sleep latency, as well as increased sleep spindle activity. A repeated-measures ANOVA revealed a significant effect of mattress type on sleep latency (p < 0.05, partial η²=0.26), with sleep latency being longer on the soft mattress (12.42 ± 1.94 min) than the medium mattress (7.71 ± 1.31 min, p < 0.05). Another repeated-measures ANOVA showed significant differences in stage transitions (p < 0.05, partial η²=0.32), with more transitions on the soft mattress (29.17 ± 2.35) compared to the firm mattress (21.75 ± 2.13, p < 0.05). The firm mattress yielded mixed results, suggesting suitability for some individuals but not universally. Post-sleep vigilance differences were not statistically significant. Conclusion This study provides evidence that mattress firmness significantly influences sleep quality, with medium firmness offering optimal outcomes for individuals with a moderate BMI. The findings contribute to the development of scientifically informed mattress designs, including smart mattresses aimed at improving sleep quality.
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Affiliation(s)
- Xiaohong Hu
- College of Material Science and Technology, Beijing Forestry University, Beijing, 100083, People’s Republic of China
- School of Management, Yulin University, Yulin, Shaanxi, 719000, People’s Republic of China
| | - Yuhong Gao
- College of Material Science and Technology, Beijing Forestry University, Beijing, 100083, People’s Republic of China
| | - Yixuan Song
- National Institute on Drug Dependence, Peking University, Beijing, 100191, People’s Republic of China
| | - Xiaoqin Yang
- National Institute on Drug Dependence, Peking University, Beijing, 100191, People’s Republic of China
| | - Keyang Liu
- College of Material Science and Technology, Beijing Forestry University, Beijing, 100083, People’s Republic of China
- College of Fashion and Design Art, Sichuan Normal University, Chengdu, Sichuan, 610101, People’s Republic of China
| | - Bin Luo
- College of Material Science and Technology, Beijing Forestry University, Beijing, 100083, People’s Republic of China
| | - Yan Sun
- National Institute on Drug Dependence, Peking University, Beijing, 100191, People’s Republic of China
| | - Li Li
- College of Material Science and Technology, Beijing Forestry University, Beijing, 100083, People’s Republic of China
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Moyne M, Durand-Ruel M, Park CH, Salamanca-Giron R, Sterpenich V, Schwartz S, Hummel FC, Morishita T. Impact of spindle-inspired transcranial alternating current stimulation during a nap on sleep-dependent motor memory consolidation in healthy older adults. SLEEP ADVANCES : A JOURNAL OF THE SLEEP RESEARCH SOCIETY 2025; 6:zpaf022. [PMID: 40365529 PMCID: PMC12070486 DOI: 10.1093/sleepadvances/zpaf022] [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: 08/20/2024] [Revised: 03/10/2025] [Indexed: 05/15/2025]
Abstract
With the increase in life expectancy and the rapid evolution of daily life technologies, older adults must constantly learn new skills to adapt to society. Sleep reinforces skills acquired during the day and is associated with the occurrence of specific oscillations such as spindles. However, with age, spindles deteriorate and thus likely contribute to memory impairments observed in older adults. The application of electric currents by means of transcranial alternating current stimulation (tACS) with spindle-like waveform, applied during the night, was found to enhance spindles and motor memory consolidation in young adults. Here, we tested whether tACS bursts inspired by spindles applied during daytime naps may (i) increase spindle density and (ii) foster motor memory consolidation in older adults. Twenty-six healthy older participants performed a force modulation task at 10:00, were retested at 16:30, and the day after the initial training. They had 90-minute opportunity to take a nap while verum or placebo spindle-inspired tACS bursts were applied with similar temporal parameters to those observed in young adults and independently of natural spindles, which are reduced in the elderly. We show that the density of natural spindles correlates with the magnitude of memory consolidation, thus confirming that spindles are promising physiological targets for enhancing memory consolidation in older adults. However, spindle-inspired tACS, as used in the present study, did not enhance either spindles or memory consolidation. We therefore suggest that applying tACS time-locked to natural spindles might be required to entrain them and improve their related functions.
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Affiliation(s)
- Maëva Moyne
- Defitech Chair of Clinical Neuroengineering, Neuro X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
- Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland
| | - Manon Durand-Ruel
- Defitech Chair of Clinical Neuroengineering, Neuro X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
| | - Chang-Hyun Park
- Defitech Chair of Clinical Neuroengineering, Neuro X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
| | - Roberto Salamanca-Giron
- Defitech Chair of Clinical Neuroengineering, Neuro X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
| | - Virgine Sterpenich
- Fondation Campus Biotech Geneva, Geneva, Switzerland
- Department of Basic Neurosciences, University of Geneva Medical School, Geneva, Switzerland and
- Swiss Center for Affective Sciences, University of Geneva, Geneva, Switzerland
| | - Sophie Schwartz
- Department of Basic Neurosciences, University of Geneva Medical School, Geneva, Switzerland and
- Swiss Center for Affective Sciences, University of Geneva, Geneva, Switzerland
| | - Friedhelm C Hummel
- Defitech Chair of Clinical Neuroengineering, Neuro X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
- Clinical Neuroscience, University of Geneva Medical School, Geneva, Switzerland
| | - Takuya Morishita
- Defitech Chair of Clinical Neuroengineering, Neuro X Institute (INX), École Polytechnique Fédérale de Lausanne (EPFL), Geneva, Switzerland
- Defitech Chair of Clinical Neuroengineering, INX, EPFL Valais, Clinique Romande de Réadaptation, Sion, Switzerland
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6
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Liu XY, Wang WL, Liu M, Chen MY, Pereira T, Doda DY, Ke YF, Wang SY, Wen D, Tong XG, Li WG, Yang Y, Han XD, Sun YL, Song X, Hao CY, Zhang ZH, Liu XY, Li CY, Peng R, Song XX, Yasi A, Pang MJ, Zhang K, He RN, Wu L, Chen SG, Chen WJ, Chao YG, Hu CG, Zhang H, Zhou M, Wang K, Liu PF, Chen C, Geng XY, Qin Y, Gao DR, Song EM, Cheng LL, Chen X, Ming D. Recent applications of EEG-based brain-computer-interface in the medical field. Mil Med Res 2025; 12:14. [PMID: 40128831 PMCID: PMC11931852 DOI: 10.1186/s40779-025-00598-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Accepted: 02/21/2025] [Indexed: 03/26/2025] Open
Abstract
Brain-computer interfaces (BCIs) represent an emerging technology that facilitates direct communication between the brain and external devices. In recent years, numerous review articles have explored various aspects of BCIs, including their fundamental principles, technical advancements, and applications in specific domains. However, these reviews often focus on signal processing, hardware development, or limited applications such as motor rehabilitation or communication. This paper aims to offer a comprehensive review of recent electroencephalogram (EEG)-based BCI applications in the medical field across 8 critical areas, encompassing rehabilitation, daily communication, epilepsy, cerebral resuscitation, sleep, neurodegenerative diseases, anesthesiology, and emotion recognition. Moreover, the current challenges and future trends of BCIs were also discussed, including personal privacy and ethical concerns, network security vulnerabilities, safety issues, and biocompatibility.
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Affiliation(s)
- Xiu-Yun Liu
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, 300380, China
- School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, 300072, China
| | - Wen-Long Wang
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Miao Liu
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Ming-Yi Chen
- Department of Micro/Nano Electronics, Shanghai Jiaotong University, Shanghai, 200240, China
| | - Tânia Pereira
- Institute for Systems and Computer Engineering, Technology and Science, 4099-002, Porto, Portugal
| | - Desta Yakob Doda
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Yu-Feng Ke
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Shou-Yan Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 200433, China
| | - Dong Wen
- School of Intelligence Science and Technology, University of Sciences and Technology Beijing, Beijing, 100083, China
| | | | - Wei-Guang Li
- The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong SAR, 999077, China
- State Key Laboratory for Quality Ensurance and Sustainable Use of Dao-Di Herbs, Artemisinin Research Center, and Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing, 100700, China
| | - Yi Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX1 3TH, UK
| | - Xiao-Di Han
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
| | - Yu-Lin Sun
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Xin Song
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Cong-Ying Hao
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Zi-Hua Zhang
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Xin-Yang Liu
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Chun-Yang Li
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Rui Peng
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Xiao-Xin Song
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Abi Yasi
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Mei-Jun Pang
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Kuo Zhang
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Run-Nan He
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Le Wu
- Department of Electric Engineering and Information Science, University of Science and Technology of China, Hefei, 230026, China
| | - Shu-Geng Chen
- Department of Rehabilitation, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Wen-Jin Chen
- Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Yan-Gong Chao
- The First Hospital of Tsinghua University, Beijing, 100016, China
| | - Cheng-Gong Hu
- Department of Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, 610041, China
| | - Heng Zhang
- Department of Neurosurgery, The First Hospital of China Medical University, Beijing, 110122, China
| | - Min Zhou
- Department of Critical Care Medicine, Division of Life Sciences and Medicine, The First Affiliated Hospital of University of Science and Technology of China, University of Science and Technology of China, Hefei, 230031, China
| | - Kun Wang
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Peng-Fei Liu
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China
| | - Chen Chen
- School of Computer Science, Fudan University, Shanghai, 200438, China
| | - Xin-Yi Geng
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Yun Qin
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - Dong-Rui Gao
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 611731, China
| | - En-Ming Song
- Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception, Institute of Optoelectronics, Fudan University, Shanghai, 200433, China
| | - Long-Long Cheng
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China.
| | - Xun Chen
- Department of Electric Engineering and Information Science, University of Science and Technology of China, Hefei, 230026, China.
| | - Dong Ming
- State Key Laboratory of Advanced Medical Materials and Devices, Medical School, Tianjin University, Tianjin, 300072, China.
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, 300380, China.
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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 2025; 51:513-521. [PMID: 38713085 PMCID: PMC11908868 DOI: 10.1093/schbul/sbae059] [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] [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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Hassan U, Okyere P, Masouleh MA, Zrenner C, Ziemann U, Bergmann TO. Pulsed inhibition of corticospinal excitability by the thalamocortical sleep spindle. Brain Stimul 2025; 18:265-275. [PMID: 39986374 DOI: 10.1016/j.brs.2025.02.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2024] [Revised: 01/30/2025] [Accepted: 02/18/2025] [Indexed: 02/24/2025] Open
Abstract
Thalamocortical sleep spindles, i.e., oscillatory bursts at ∼12-15 Hz of waxing and waning amplitude, are a hallmark feature of non-rapid eye movement (NREM) sleep and believed to play a key role in memory reactivation and consolidation. Generated in the thalamus and projecting to neocortex and hippocampus, they are phasically modulated by neocortical slow oscillations (<1 Hz) and in turn phasically modulate hippocampal sharp-wave ripples (>80 Hz). This hierarchical cross-frequency nesting, where slower oscillations group faster ones into certain excitability phases, may enable phase-dependent plasticity in the neocortex, and spindles have thus been considered windows of plasticity in the sleeping brain. However, the assumed phasic excitability modulation had not yet been demonstrated for spindles. Utilizing a recently developed real-time spindle detection algorithm, we applied spindle phase-triggered transcranial magnetic stimulation (TMS) to the primary motor cortex (M1) hand area to characterize the corticospinal excitability profile of spindles via motor evoked potentials (MEP). MEPs showed net suppression during spindles, driven by a "pulse of inhibition" during its falling flank with no inhibition or facilitation during its peak, rising flank, or trough. This unidirectional ("asymmetric") modulation occurred on top of the general sleep-related inhibition during spindle-free NREM sleep and did not extend into the refractory post-spindle periods. We conclude that spindles exert "asymmetric pulsed inhibition" on corticospinal excitability. These findings and the developed real-time spindle targeting methods enable future studies to investigate the causal role of spindles in phase-dependent synaptic plasticity and systems memory consolidation during sleep by repetitively targeting relevant spindle phases.
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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 (LIR), Mainz, Germany; Department of Psychiatry and Behavioral Sciences, Stanford School of Medicine, Stanford University, USA; Wu-Tsai Neurosciences Institute, Stanford University, USA.
| | - Prince Okyere
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Mainz, Germany; School of Psychology, University of Surrey, Guildford, UK
| | - Milad Amini Masouleh
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Mainz, Germany; Department of Psychology and Neurosciences, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystraße 67, Dortmund, Germany; Psychology Department, Ruhr University Bochum, Bochum, Germany
| | - Christoph Zrenner
- Temerty Centre for Therapeutic Brain Intervention, Centre for Addiction and Mental Health, Toronto, Canada; Department of Psychiatry, Faculty of Medicine, And Institute for Biomedical Engineering, And Institute of Medical Science, University of Toronto, Toronto, Canada
| | - Ulf Ziemann
- Department of Neurology & Stroke, Eberhard Karls University of Tübingen, Tübingen, Germany; Hertie Institute for Clinical Brain Research, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Til Ole Bergmann
- Neuroimaging Center (NIC), Focus Program Translational Neuroscience (FTN), Johannes Gutenberg University Medical Center, Mainz, Germany; Leibniz Institute for Resilience Research (LIR), Mainz, Germany.
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9
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Bolló H, Carreiro C, Iotchev IB, Gombos F, Gácsi M, Topál J, Kis A. The Effect of Targeted Memory Reactivation on Dogs' Visuospatial Memory. eNeuro 2025; 12:ENEURO.0304-20.2024. [PMID: 39933919 PMCID: PMC11827548 DOI: 10.1523/eneuro.0304-20.2024] [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: 10/12/2024] [Revised: 12/11/2024] [Accepted: 12/16/2024] [Indexed: 02/13/2025] Open
Abstract
The role of sleep in memory consolidation is a widely discussed but still debated area of research. In light of the fact that memory consolidation during sleep is an evolutionary adaptive function, investigating the same phenomenon in nonhuman model species is highly relevant for its understanding. One such species, which has acquired human-analog sociocognitive skills through convergent evolution, is the domestic dog. Family dogs have surfaced as an outstanding animal model in sleep research, and their learning skills (in a social context) are subject to sleep-dependent memory consolidation. These results, however, are correlational, and the next challenge is to establish causality. In the present study, we aimed to adapt a TMR (targeted memory reactivation) paradigm in dogs and investigate its effect on sleep parameters. Dogs (N = 16) learned new commands associated with different locations and afterward took part in a sleep polysomnography recording when they were re-exposed to one of the previously learned commands. The results did not indicate a cueing benefit on choice performance. However, there was evidence for a decrease in choice latency after sleep, while the density (occurrence/minute) of fast sleep spindles was also notably higher during TMR recordings than adaptation recordings from the same animals and even compared with a larger reference sample from a previous work. Our study provides empirical evidence that TMR is feasible with family dogs, even during a daytime nap. Furthermore, the present study highlights several methodological and conceptual challenges for future research.
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Affiliation(s)
- Henrietta Bolló
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest 1117, Hungary
| | - Cecília Carreiro
- Department of Ethology, ELTE Eötvös Loránd University, Budapest 1117, Hungary
| | | | - Ferenc Gombos
- Laboratory for Psychological Research, Pázmány Péter Catholic University, Budapest 1088, Hungary
- HUN-REN-ELTE-PPKE Adolescent Development Research Group Budapest, Budapest 1075, Hungary
| | - Márta Gácsi
- Department of Ethology, ELTE Eötvös Loránd University, Budapest 1117, Hungary
- HUN-REN-ELTE Comparative Ethology Research Group, Budapest 1117, Hungary
| | - József Topál
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest 1117, Hungary
| | - Anna Kis
- Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Budapest 1117, Hungary
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10
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Shi Y, Tian X, Li T, Hu Y, Xie Y, Li H, Li Y, Jiang N, Tang X, Wang Y. The influence of transcranial alternating current stimulation on EEG spectral power during subsequent sleep: A randomized crossover study. Sleep Med 2025; 126:185-193. [PMID: 39689403 DOI: 10.1016/j.sleep.2024.12.011] [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: 09/30/2024] [Revised: 11/30/2024] [Accepted: 12/08/2024] [Indexed: 12/19/2024]
Abstract
OBJECTIVE To evaluate the instant impact of transcranial alternating current stimulation (tACS) on sleep brain oscillations. METHODS Thirty-six healthy subjects were randomly assigned to receive tACS and sham stimulation in a crossover design separated by a one-week washout period. After stimulation, a 2-h nap polysomnography (PSG) was performed to obtain Electroencephalogram (EEG) data and objective sleep variables, and self-reported subjective sleep parameters were collected at the end of the nap. EEG spectral analyses were conducted on the EEG data to obtain the absolute and relative power for each sleep stage during the nap. The associations between power values and objective and subjective measurements were analyzed using Spearman or Pearson correlation coefficients. RESULTS The tACS group presented higher power in slow wave activity (SWA) and delta frequency bands and lower alpha, sigma and beta power values compared to the sham group during the N2 and N3 sleep stages. SWA and delta power were positively associated with sleep duration and sleep efficiency relevant parameters; while alpha, sigma and beta power were positively associated with prolonged sleep latency and wakefulness related variables. PSG, self-reported and sleep diary measured objective and subjective sleep parameters were comparable between the tACS and the sham groups. CONCLUSION Our results support that tACS could promote sleep depth in microstructure of sleep EEG, manifesting as an increase in EEG spectral power in low frequency bands and a decrease in high frequency bands. The registration number of this study is ChiCTR2200063729.
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Affiliation(s)
- Yuan Shi
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Xin Tian
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Taomei Li
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Yuexia Hu
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Yuqing Xie
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Huixian Li
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Yun Li
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China; SDIC HEALTH INDUSTRY INVESTMENT CO., LTD, Beijing, PR China.
| | - Ning Jiang
- National Clinical Research Center for Geriatrics, West China Hospital, The Med-X Center for Manufacturing, Sichuan University, Chengdu, 610041, PR China.
| | - Xiangdong Tang
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
| | - Yanyan Wang
- West China School of Nursing, Sleep Medicine Center, Mental Health Center, National Clinical Research Center for Geriatrics, Nursing Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, 610041, PR China.
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11
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Shao Y, Guo Y, Chen Y, Zou G, Chen J, Gao X, Lu P, Tong Y, Li Y, Yao P, Liu J, Zhou S, Xu J, Gao JH, Zou Q, Sun H. Increased spindle-related brain activation in right middle temporal gyrus during N2 than N3 among healthy sleepers: Initial discovery and independent sample replication. Neuroimage 2025; 305:120976. [PMID: 39681244 DOI: 10.1016/j.neuroimage.2024.120976] [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: 09/25/2024] [Revised: 12/01/2024] [Accepted: 12/14/2024] [Indexed: 12/18/2024] Open
Abstract
The association between spindle metrics and sleep architecture differs during N2 vs. N3 sleep, the underlying neural mechanism is not clearly illustrated. Here, we tested the discrepancy in spindle-related brain activation between N2 and N3 within healthy college students (dataset 1: n = 27, 59 % females, median age 23 years), using simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI). To assess the replicability of the finding, we repeated the analysis among normal adults (independent dataset 2: n = 30, 50 % females, median age 32 years). The finding from dataset 1 indicated significantly increased blood-oxygen level-dependent signal in the right middle temporal gyrus during N2 compared with N3, which was well replicated in dataset 2. Furthermore, correlation analysis was performed to explore the association between this spindle-related brain activation and N2, N3 sleep duration during EEG-fMRI. We conducted the correlation analysis in N2 and N3, respectively. The negative association between spindle-related brain activation in the right middle temporal gyrus and sleep duration was only observed in N2. Our findings emphasize the unique role of spindle-related brain activation in the right middle temporal gyrus during N2 in shortening N2 sleep duration.
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Affiliation(s)
- Yan Shao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China
| | - Yupeng Guo
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China
| | - Yun Chen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China
| | - Guangyuan Zou
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, PR China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, PR China
| | - Jie Chen
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China
| | - Xuejiao Gao
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China
| | - Panpan Lu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China
| | - Yujie Tong
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China
| | - Yuezhen Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China; Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tian Tan Hospital, Capital Medical University, Beijing, PR China
| | - Ping Yao
- Mental Health Institute of Inner Mongolia Autonomous Region, The Third Hospital of Inner Mongolia Autonomous Region, Hohhot 010010, PR China
| | - Jiayi Liu
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, PR China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, PR China
| | - Shuqin Zhou
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, PR China
| | - Jing Xu
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, PR China; Laboratory of Applied Brain and Cognitive Sciences, College of International Business, Shanghai International Studies University, Shanghai, PR China
| | - Jia-Hong Gao
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, PR China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, PR China; McGovern Institute for Brain Research, Peking University, Beijing, PR China.
| | - Qihong Zou
- Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, PR China; Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, PR China.
| | - Hongqiang Sun
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Peking University, Beijing, PR China.
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12
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Iotchev IB, Szabó D, Turcsán B, Bognár Z, Kubinyi E. Sleep-spindles as a marker of attention and intelligence in dogs. Neuroimage 2024; 303:120916. [PMID: 39505225 DOI: 10.1016/j.neuroimage.2024.120916] [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: 07/08/2024] [Revised: 10/24/2024] [Accepted: 11/04/2024] [Indexed: 11/08/2024] Open
Abstract
The sleep spindle-generating thalamo-cortical circuitry supports attention capacity in awake humans and animals, but using sleep spindles to predict differences in attention has not been tried in either. Of the more commonly examined cognitive correlates of spindle occurrence and amplitude, post-sleep recall, and general intelligence, only post-sleep recall had been studied in dogs, rats and mice. Here, we examined a sample of companion dogs (N = 58) for whom polysomnographic recordings and several cognitive tests were performed on two occasions each, with a three-month break in-between. Five of the tests were used to extract a factor analogous to human g (general mental ability). A sixth test in the battery measured sustained attention. Both attention and g-factor scores were linked to higher slow spindle occurrence and absolute sigma power detected in polysomnographic recordings over the central electrode. These effects persisted across measurement occasions. Higher intrinsic spindle frequency was, in turn, linked to lower g-factor scores but displayed no relationship with attention scores. The overlap in localization and direction for the effects of slow spindle density (spindles/minute) and sigma power supports that they tap into the same underlying cognition-relevant aspects of spindling. Given earlier large sample and meta-analysis validations of sigma power as a reliable predictor of cognitive performance in humans, we thus conclude that the currently handled method for quantifying spindle density in dogs indeed measures cognition-relevant spindle activity by virtue of its agreement with the sigma power alternative.
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Affiliation(s)
- Ivaylo Borislavov Iotchev
- Department of Ethology, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/c, Budapest 1117, Hungary.
| | - Dóra Szabó
- Department of Ethology, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/c, Budapest 1117, Hungary
| | - Borbála Turcsán
- Department of Ethology, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/c, Budapest 1117, Hungary; MTA-ELTE, Lendület "Momentum" Companion Animal Research Group, Budapest 1117, Hungary
| | - Zsófia Bognár
- Department of Ethology, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/c, Budapest 1117, Hungary; MTA-ELTE, Lendület "Momentum" Companion Animal Research Group, Budapest 1117, Hungary
| | - Eniko Kubinyi
- Department of Ethology, ELTE Eötvös Loránd University, Pázmány Péter sétány 1/c, Budapest 1117, Hungary; MTA-ELTE, Lendület "Momentum" Companion Animal Research Group, Budapest 1117, Hungary; ELTE NAP Canine Brain Research Group, Budapest, Hungary
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13
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Li S, Wang C, Wu S. Spindle oscillations emerge at the critical state of electrically coupled networks in the thalamic reticular nucleus. Cell Rep 2024; 43:114790. [PMID: 39356636 DOI: 10.1016/j.celrep.2024.114790] [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: 03/05/2024] [Revised: 07/31/2024] [Accepted: 09/07/2024] [Indexed: 10/04/2024] Open
Abstract
Spindle oscillation is a waxing-and-waning neural oscillation observed in the brain, initiated at the thalamic reticular nucleus (TRN) and typically occurring at 7-15 Hz. Experiments have shown that in the adult brain, electrical synapses, rather than chemical synapses, dominate between TRN neurons, suggesting that the traditional view of spindle generation via chemical synapses may need reconsideration. Based on known experimental data, we develop a computational model of the TRN network, where heterogeneous neurons are connected by electrical synapses. The model shows that the interplay between synchronizing electrical synapses and desynchronizing heterogeneity leads to multiple synchronized clusters with slightly different oscillation frequencies whose summed-up activity produces spindle oscillation as seen in local field potentials. Our results suggest that during spindle oscillation, the network operates at the critical state, which is known for facilitating efficient information processing. This study provides insights into the underlying mechanism of spindle oscillation and its functional significance.
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Affiliation(s)
- Shangyang Li
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Center of Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong 519031, China
| | - Chaoming Wang
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Center of Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong 519031, China
| | - Si Wu
- School of Psychological and Cognitive Sciences, Beijing Key Laboratory of Behavior and Mental Health, IDG/McGovern Institute for Brain Research, Center of Quantitative Biology, Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, Guangdong 519031, China.
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14
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Kumar D, Yanagisawa M, Funato H. Sleep-dependent memory consolidation in young and aged brains. AGING BRAIN 2024; 6:100124. [PMID: 39309405 PMCID: PMC11416671 DOI: 10.1016/j.nbas.2024.100124] [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: 05/31/2024] [Revised: 08/29/2024] [Accepted: 09/02/2024] [Indexed: 09/25/2024] Open
Abstract
Young children and aged individuals are more prone to memory loss than young adults. One probable reason is insufficient sleep-dependent memory consolidation. Sleep timing and sleep-stage duration differ between children and aged individuals compared to adults. Frequent daytime napping and fragmented sleep architecture are common in children and older individuals. Moreover, sleep-dependent oscillations that play crucial roles in long-term memory storage differ among age groups. Notably, the frontal cortex, which is important for long-term memory storage undergoes major structural changes in children and aged subjects. The similarities in sleep dynamics between children and aged subjects suggest that a deficit in sleep-dependent consolidation contributes to memory loss in both age groups.
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Affiliation(s)
- Deependra Kumar
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Tsukuba, Ibaraki 305-0006, Japan
| | - Masashi Yanagisawa
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Tsukuba, Ibaraki 305-0006, Japan
| | - Hiromasa Funato
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Tsukuba, Ibaraki 305-0006, Japan
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15
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Blanco-Duque C, Bond SA, Krone LB, Dufour JP, Gillen ECP, Purple RJ, Kahn MC, Bannerman DM, Mann EO, Achermann P, Olbrich E, Vyazovskiy VV. Oscillatory-Quality of sleep spindles links brain state with sleep regulation and function. SCIENCE ADVANCES 2024; 10:eadn6247. [PMID: 39241075 PMCID: PMC11378912 DOI: 10.1126/sciadv.adn6247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Accepted: 07/30/2024] [Indexed: 09/08/2024]
Abstract
Here, we characterized the dynamics of sleep spindles, focusing on their damping, which we estimated using a metric called oscillatory-Quality (o-Quality), derived by fitting an autoregressive model to electrophysiological signals, recorded from the cortex in mice. The o-Quality of sleep spindles correlates weakly with their amplitude, shows marked laminar differences and regional topography across cortical regions, reflects the level of synchrony within and between cortical networks, is strongly modulated by sleep-wake history, reflects the degree of sensory disconnection, and correlates with the strength of coupling between spindles and slow waves. As most spindle events are highly localized and not detectable with conventional low-density recording approaches, o-Quality thus emerges as a valuable metric that allows us to infer the spread and dynamics of spindle activity across the brain and directly links their spatiotemporal dynamics with local and global regulation of brain states, sleep regulation, and function.
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Affiliation(s)
- Cristina Blanco-Duque
- Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Rd, Oxford OX1 3PT, UK
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, MA 02139, USA
| | - Suraya A. Bond
- Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Rd, Oxford OX1 3PT, UK
- UK Dementia Research Institute at UCL, University College London, WC1E 6BT London, UK
| | - Lukas B. Krone
- Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Rd, Oxford OX1 3PT, UK
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bolligenstrasse 111, 3000 Bern 60, Switzerland
| | - Jean-Phillipe Dufour
- Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Rd, Oxford OX1 3PT, UK
| | - Edward C. P. Gillen
- Astrophysics Group, Cavendish Laboratory, J.J. Thomson Avenue, Cambridge CB30HE, UK
- Astronomy Unit, Queen Mary University of London, Mile End Road, London E14NS, UK
| | - Ross J. Purple
- Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Rd, Oxford OX1 3PT, UK
- School of Physiology Pharmacology and Neuroscience, University of Bristol, Bristol BS8 1TD, UK
| | - Martin C. Kahn
- Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Rd, Oxford OX1 3PT, UK
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar St, Cambridge, MA 02139, USA
| | - David M. Bannerman
- Department of Experimental Psychology, University of Oxford, Oxford OX2 6GG, UK
| | - Edward O. Mann
- Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Rd, Oxford OX1 3PT, UK
| | - Peter Achermann
- Institute of Pharmacology and Toxicology, University of Zurich, Winterthurerstrasse 190, Zurich CH-8057, Switzerland
| | - Eckehard Olbrich
- Max Planck Institute for Mathematics in the Sciences, Inselstraße 22, 04103 Leipzig, Germany
| | - Vladyslav V. Vyazovskiy
- Department of Physiology, Anatomy and Genetics, University of Oxford, Sherrington Building, Sherrington Rd, Oxford OX1 3PT, UK
- Sleep and Circadian Neuroscience Institute, University of Oxford, Sherrington Rd, Oxford OX1 3QU, UK
- The Kavli Institute for Nanoscience Discovery, University of Oxford, Sherrington Rd, Oxford OX1 3QU, UK
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16
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Cappon DB, Pascual-Leone A. Toward Precision Noninvasive Brain Stimulation. Am J Psychiatry 2024; 181:795-805. [PMID: 39217436 DOI: 10.1176/appi.ajp.20240643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/04/2024]
Affiliation(s)
- Davide B Cappon
- Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston; Department of Neurology, Harvard Medical School, Boston
| | - Alvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Deanna and Sidney Wolk Center for Memory Health, Hebrew SeniorLife, Boston; Department of Neurology, Harvard Medical School, Boston
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17
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Schwippel T, Pupillo F, Feldman Z, Walker C, Townsend L, Rubinow D, Frohlich F. Closed-Loop Transcranial Alternating Current Stimulation for the Treatment of Major Depressive Disorder: An Open-Label Pilot Study. Am J Psychiatry 2024; 181:842-845. [PMID: 39108159 DOI: 10.1176/appi.ajp.20230838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/02/2024]
Affiliation(s)
- Tobias Schwippel
- Department of Psychiatry, University of North Carolina Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Rubinow, Frohlich); Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Frohlich); Electromedical Products International, Inc., Mineral Wells, Tex. (Townsend); Pulvinar Neuro, LLC., Durham, N.C. (Townsend, Walker)
| | - Francesca Pupillo
- Department of Psychiatry, University of North Carolina Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Rubinow, Frohlich); Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Frohlich); Electromedical Products International, Inc., Mineral Wells, Tex. (Townsend); Pulvinar Neuro, LLC., Durham, N.C. (Townsend, Walker)
| | - Zachary Feldman
- Department of Psychiatry, University of North Carolina Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Rubinow, Frohlich); Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Frohlich); Electromedical Products International, Inc., Mineral Wells, Tex. (Townsend); Pulvinar Neuro, LLC., Durham, N.C. (Townsend, Walker)
| | - Christopher Walker
- Department of Psychiatry, University of North Carolina Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Rubinow, Frohlich); Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Frohlich); Electromedical Products International, Inc., Mineral Wells, Tex. (Townsend); Pulvinar Neuro, LLC., Durham, N.C. (Townsend, Walker)
| | - Leah Townsend
- Department of Psychiatry, University of North Carolina Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Rubinow, Frohlich); Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Frohlich); Electromedical Products International, Inc., Mineral Wells, Tex. (Townsend); Pulvinar Neuro, LLC., Durham, N.C. (Townsend, Walker)
| | - David Rubinow
- Department of Psychiatry, University of North Carolina Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Rubinow, Frohlich); Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Frohlich); Electromedical Products International, Inc., Mineral Wells, Tex. (Townsend); Pulvinar Neuro, LLC., Durham, N.C. (Townsend, Walker)
| | - Flavio Frohlich
- Department of Psychiatry, University of North Carolina Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Rubinow, Frohlich); Carolina Center for Neurostimulation, University of North Carolina, Chapel Hill, N.C. (Schwippel, Pupillo, Feldman, Frohlich); Electromedical Products International, Inc., Mineral Wells, Tex. (Townsend); Pulvinar Neuro, LLC., Durham, N.C. (Townsend, Walker)
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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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19
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Sharon O, Ben Simon E, Shah VD, Desel T, Walker MP. The new science of sleep: From cells to large-scale societies. PLoS Biol 2024; 22:e3002684. [PMID: 38976664 PMCID: PMC11230563 DOI: 10.1371/journal.pbio.3002684] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2024] Open
Abstract
In the past 20 years, more remarkable revelations about sleep and its varied functions have arguably been made than in the previous 200. Building on this swell of recent findings, this essay provides a broad sampling of selected research highlights across genetic, molecular, cellular, and physiological systems within the body, networks within the brain, and large-scale social dynamics. Based on this raft of exciting new discoveries, we have come to realize that sleep, in this moment of its evolution, is very much polyfunctional (rather than monofunctional), yet polyfunctional for reasons we had never previously considered. Moreover, these new polyfunctional insights powerfully reaffirm sleep as a critical biological, and thus health-sustaining, requisite. Indeed, perhaps the only thing more impressive than the unanticipated nature of these newly emerging sleep functions is their striking divergence, from operations of molecular mechanisms inside cells to entire group societal dynamics.
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Affiliation(s)
- Omer Sharon
- Department of Psychology, University of California, Berkeley, California, United States of America
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America
| | - Eti Ben Simon
- Department of Psychology, University of California, Berkeley, California, United States of America
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America
| | - Vyoma D. Shah
- Department of Psychology, University of California, Berkeley, California, United States of America
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America
| | - Tenzin Desel
- Department of Psychology, University of California, Berkeley, California, United States of America
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America
| | - Matthew P. Walker
- Department of Psychology, University of California, Berkeley, California, United States of America
- Helen Wills Neuroscience Institute, University of California, Berkeley, California, United States of America
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20
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Caravati E, Barbeni F, Chiarion G, Raggi M, Mesin L. Closed-Loop Transcranial Electrical Neurostimulation for Sustained Attention Enhancement: A Pilot Study towards Personalized Intervention Strategies. Bioengineering (Basel) 2024; 11:467. [PMID: 38790334 PMCID: PMC11118513 DOI: 10.3390/bioengineering11050467] [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: 04/06/2024] [Revised: 05/03/2024] [Accepted: 05/06/2024] [Indexed: 05/26/2024] Open
Abstract
Sustained attention is pivotal for tasks like studying and working for which focus and low distractions are necessary for peak productivity. This study explores the effectiveness of adaptive transcranial direct current stimulation (tDCS) in either the frontal or parietal region to enhance sustained attention. The research involved ten healthy university students performing the Continuous Performance Task-AX (AX-CPT) while receiving either frontal or parietal tDCS. The study comprised three phases. First, we acquired the electroencephalography (EEG) signal to identify the most suitable metrics related to attention states. Among different spectral and complexity metrics computed on 3 s epochs of EEG, the Fuzzy Entropy and Multiscale Sample Entropy Index of frontal channels were selected. Secondly, we assessed how tDCS at a fixed 1.0 mA current affects attentional performance. Finally, a real-time experiment involving continuous metric monitoring allowed personalized dynamic optimization of the current amplitude and stimulation site (frontal or parietal). The findings reveal statistically significant improvements in mean accuracy (94.04 vs. 90.82%) and reaction times (262.93 vs. 302.03 ms) with the adaptive tDCS compared to a non-stimulation condition. Average reaction times were statistically shorter during adaptive stimulation compared to a fixed current amplitude condition (262.93 vs. 283.56 ms), while mean accuracy stayed similar (94.04 vs. 93.36%, improvement not statistically significant). Despite the limited number of subjects, this work points out the promising potential of adaptive tDCS as a tailored treatment for enhancing sustained attention.
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Affiliation(s)
| | | | | | | | - Luca Mesin
- Mathematical Biology and Physiology, Department Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy; (E.C.); (F.B.); (G.C.); (M.R.)
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21
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Liu Y, Luo Y, Zhang N, Zhang X, Liu S. A scientometric review of the growing trends in transcranial alternating current stimulation (tACS). Front Hum Neurosci 2024; 18:1362593. [PMID: 38510513 PMCID: PMC10950919 DOI: 10.3389/fnhum.2024.1362593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Accepted: 02/19/2024] [Indexed: 03/22/2024] Open
Abstract
Objective The aim of the current study was to provide a comprehensive picture of tACS-related research in the last decade through a bibliometric approach in order to systematically analyze the current status and cutting-edge trends in this field. Methods Articles and review articles related to tACS from 2013 to 2022 were searched on the Web of Science platform. A bibliometric analysis of authors, journals, countries, institutions, references, and keywords was performed using CiteSpace (6.2.R2), VOSviewer (1.6.19), Scimago Graphica (1.0.30), and Bibliometrix (4.2.2). Results A total of 602 papers were included. There was an overall increase in annual relevant publications in the last decade. The most contributing author was Christoph S. Herrmann. Brain Stimulation was the most prolific journal. The most prolific countries and institutions were Germany and Harvard University, respectively. Conclusion The findings reveal the development prospects and future directions of tACS and provide valuable references for researchers in the field. In recent years, the keywords "gamma," "transcranial direct current simulation," and "Alzheimer's disease" that have erupted, as well as many references cited in the outbreak, have provided certain clues for the mining of research prefaces. This will act as a guide for future researchers in determining the path of tACS research.
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Affiliation(s)
- Yuanli Liu
- Department of Psychology, School of Humanities and Social Sciences, Anhui Agricultural University, Hefei, China
| | - Yulin Luo
- Department of Psychology, School of Humanities and Social Sciences, Anhui Agricultural University, Hefei, China
| | - Na Zhang
- Department of Information Management, Anhui Vocational College of Police Officers, Hefei, China
| | - Xiaochu Zhang
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, Anhui, China
- Hefei National Research Center for Physical Sciences at the Microscale, and Department of Radiology, the First Affiliated Hospital of USTC, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
- Application Technology Center of Physical Therapy to Brain Disorders, Institute of Advanced Technology, University of Science & Technology of China, Hefei, China
- Key Laboratory of Brain-Machine Intelligence for Information Behavior (Ministry of Education and Shanghai), School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Shen Liu
- Department of Psychology, School of Humanities and Social Sciences, Anhui Agricultural University, Hefei, China
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Meyer N, Lok R, Schmidt C, Kyle SD, McClung CA, Cajochen C, Scheer FAJL, Jones MW, Chellappa SL. The sleep-circadian interface: A window into mental disorders. Proc Natl Acad Sci U S A 2024; 121:e2214756121. [PMID: 38394243 PMCID: PMC10907245 DOI: 10.1073/pnas.2214756121] [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] [Indexed: 02/25/2024] Open
Abstract
Sleep, circadian rhythms, and mental health are reciprocally interlinked. Disruption to the quality, continuity, and timing of sleep can precipitate or exacerbate psychiatric symptoms in susceptible individuals, while treatments that target sleep-circadian disturbances can alleviate psychopathology. Conversely, psychiatric symptoms can reciprocally exacerbate poor sleep and disrupt clock-controlled processes. Despite progress in elucidating underlying mechanisms, a cohesive approach that integrates the dynamic interactions between psychiatric disorder with both sleep and circadian processes is lacking. This review synthesizes recent evidence for sleep-circadian dysfunction as a transdiagnostic contributor to a range of psychiatric disorders, with an emphasis on biological mechanisms. We highlight observations from adolescent and young adults, who are at greatest risk of developing mental disorders, and for whom early detection and intervention promise the greatest benefit. In particular, we aim to a) integrate sleep and circadian factors implicated in the pathophysiology and treatment of mood, anxiety, and psychosis spectrum disorders, with a transdiagnostic perspective; b) highlight the need to reframe existing knowledge and adopt an integrated approach which recognizes the interaction between sleep and circadian factors; and c) identify important gaps and opportunities for further research.
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Affiliation(s)
- Nicholas Meyer
- Insomnia and Behavioural Sleep Medicine Clinic, University College London Hospitals NHS Foundation Trust, LondonWC1N 3HR, United Kingdom
- Department of Psychosis Studies, Institute of Psychology, Psychiatry, and Neuroscience, King’s College London, LondonSE5 8AF, United Kingdom
| | - Renske Lok
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA94305
| | - Christina Schmidt
- Sleep & Chronobiology Group, GIGA-Institute, CRC-In Vivo Imaging Unit, University of Liège, Liège, Belgium
- Psychology and Neuroscience of Cognition Research Unit, Faculty of Psychology, Speech and Language, University of Liège, Liège4000, Belgium
| | - Simon D. Kyle
- Sir Jules Thorn Sleep and Circadian Neuroscience Institute, Nuffield Department of Clinical Neurosciences, University of Oxford, OxfordOX1 3QU, United Kingdom
| | - Colleen A. McClung
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA15219
| | - Christian Cajochen
- Centre for Chronobiology, Department for Adult Psychiatry, Psychiatric Hospital of the University of Basel, BaselCH-4002, Switzerland
- Research Cluster Molecular and Cognitive Neurosciences, Department of Biomedicine, University of Basel, BaselCH-4055, Switzerland
| | - Frank A. J. L. Scheer
- Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women’s Hospital, Boston, MA02115
- Medical Chronobiology Program, Division of Sleep and Circadian Disorders, Department of Neurology, Brigham and Women’s Hospital, Boston, MA02115
- Division of Sleep Medicine, Harvard Medical School, Boston, MA02115
| | - Matthew W. Jones
- School of Physiology, Pharmacology and Neuroscience, Faculty of Health and Life Sciences, University of Bristol, BristolBS8 1TD, United Kingdom
| | - Sarah L. Chellappa
- School of Psychology, Faculty of Environmental and Life Sciences, University of Southampton, SouthamptonSO17 1BJ, United Kingdom
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23
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Zhu X, Ren Y, Tan S, Ma X. Efficacy of transcranial alternating current stimulation in treating chronic insomnia and the impact of age on its effectiveness: A multisite randomized, double-blind, parallel-group, placebo-controlled study. J Psychiatr Res 2024; 170:253-261. [PMID: 38176353 DOI: 10.1016/j.jpsychires.2023.12.037] [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: 09/11/2023] [Revised: 12/01/2023] [Accepted: 12/27/2023] [Indexed: 01/06/2024]
Abstract
OBJECTIVE Insomnia is a significant health issue associated with various systemic diseases. Transcranial alternating current stimulation (tACS) has been proposed as a potential intervention for insomnia. However, the efficacy and mechanisms of tACS in chronic insomnia remain unclear. Accordingly, this study aimed to investigate the efficacy of tACS in treating chronic insomnia in adults and assess the impact of age on its effectiveness using a large sample from two centers. METHODS A total of 120 participants with chronic insomnia underwent 20 daily sessions of tACS (duration: 40 min, frequency: 77.5 Hz, and intensity: 15 mA) or sham tACS targeting the forehead and both mastoid areas over 4 weeks. Assessments were conducted at baseline, post-treatment, and 4-week follow-up. Primary outcomes included sleep quality and efficiency, onset latency, total sleep time, and daily disturbances. Secondary outcomes included depression, anxiety, and clinical impression. RESULTS Compared with the control group, the tACS group demonstrated improved sleep quality and efficiency, increased total sleep time, and reduced daily disturbance (all ps < 0.01). Moreover, tACS had a significant effect on clinical impression (p < 0.001), but not depression and anxiety scores. Subgroup analyses revealed that older participants experienced significant benefits from tACS in sleep quality, efficiency, and overall insomnia reduction at post-treatment and follow-up (p < 0.001). Notably, improved insomnia correlated with attenuated depressive and anxiety symptoms. CONCLUSIONS These findings suggest that tACS may be an effective intervention for chronic insomnia within an eight-week timeframe, and age affects the response to tACS in terms of insomnia improvement.
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Affiliation(s)
- Xiaolin Zhu
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, 100096, China
| | - Yanping Ren
- Being An-ding Hospital, Capital Medical University, 5 Ankang Lane, Deshengmenwai Avenue, Xicheng District, Beijing, 100088, China
| | - Shuping Tan
- Beijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, 100096, China.
| | - Xin Ma
- Being An-ding Hospital, Capital Medical University, 5 Ankang Lane, Deshengmenwai Avenue, Xicheng District, Beijing, 100088, China.
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24
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Mayeli A, Donati FL, Ferrarelli F. Altered Sleep Oscillations as Neurophysiological Biomarkers of Schizophrenia. ADVANCES IN NEUROBIOLOGY 2024; 40:351-383. [PMID: 39562451 DOI: 10.1007/978-3-031-69491-2_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/21/2024]
Abstract
Sleep spindles and slow waves are the two main oscillatory activities occurring during nonrapid eye movement (NREM) sleep. Here, we will first describe the electrophysiological characteristics of these sleep oscillations along with the neurophysiological and molecular mechanisms underlying their generation and synchronization in the healthy brain. We will then review the extant evidence of deficits in sleep spindles and, to a lesser extent, slow waves, including in slow wave-spindle coupling, in patients with Schizophrenia (SCZ) across the course of the disorder, from at-risk to chronic stages. Next, we will discuss how these sleep oscillatory deficits point to defects in neuronal circuits within the thalamocortical network as well as to alterations in molecular neurotransmission implicating the GABAergic and glutamatergic systems in SCZ. Finally, after explaining how spindle and slow waves may represent neurophysiological biomarkers with predictive, diagnostic, and prognostic potential, we will present novel pharmacological and neuromodulatory interventions aimed at restoring sleep oscillatory deficits in SCZ, which in turn may serve as target engagement biomarkers to ameliorate the clinical symptoms and the quality of life of individuals affected by this devastating brain disorder.
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Affiliation(s)
- Ahmad Mayeli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA.
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25
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Wodeyar A, Marshall FA, Chu CJ, Eden UT, Kramer MA. Different Methods to Estimate the Phase of Neural Rhythms Agree But Only During Times of Low Uncertainty. eNeuro 2023; 10:ENEURO.0507-22.2023. [PMID: 37833061 PMCID: PMC10626504 DOI: 10.1523/eneuro.0507-22.2023] [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: 12/16/2022] [Revised: 08/25/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
Rhythms are a common feature of brain activity. Across different types of rhythms, the phase has been proposed to have functional consequences, thus requiring its accurate specification from noisy data. Phase is conventionally specified using techniques that presume a frequency band-limited rhythm. However, in practice, observed brain rhythms are typically nonsinusoidal and amplitude modulated. How these features impact methods to estimate phase remains unclear. To address this, we consider three phase estimation methods, each with different underlying assumptions about the rhythm. We apply these methods to rhythms simulated with different generative mechanisms and demonstrate inconsistency in phase estimates across the different methods. We propose two improvements to the practice of phase estimation: (1) estimating confidence in the phase estimate, and (2) examining the consistency of phase estimates between two (or more) methods.
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Affiliation(s)
- Anirudh Wodeyar
- Department of Mathematics & Statistics, Boston University, Boston, MA 02215
| | | | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA 02215
- Harvard Medical School, Boston, MA 02114
| | - Uri T Eden
- Department of Mathematics & Statistics, Boston University, Boston, MA 02215
- Center for Systems Neuroscience, Boston University, Boston, MA 02215
| | - Mark A Kramer
- Department of Mathematics & Statistics, Boston University, Boston, MA 02215
- Center for Systems Neuroscience, Boston University, Boston, MA 02215
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26
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Crespo EL, Pal A, Prakash M, Silvagnoli AD, Zaidi Z, Gomez-Ramirez M, Tree MO, Shaner NC, Lipscombe D, Moore C, Hochgeschwender U. A Bioluminescent Activity Dependent (BLADe) Platform for Converting Neuronal Activity to Photoreceptor Activation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.25.546469. [PMID: 37425742 PMCID: PMC10327117 DOI: 10.1101/2023.06.25.546469] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
We developed a platform that utilizes a calcium-dependent luciferase to convert neuronal activity into activation of light sensing domains within the same cell. The platform is based on a Gaussia luciferase variant with high light emission split by calmodulin-M13 sequences that depends on influx of calcium ions (Ca2+) for functional reconstitution. In the presence of its luciferin, coelenterazine (CTZ), Ca2+ influx results in light emission that drives activation of photoreceptors, including optogenetic channels and LOV domains. Critical features of the converter luciferase are light emission low enough to not activate photoreceptors under baseline condition and high enough to activate photosensing elements in the presence of Ca2+ and luciferin. We demonstrate performance of this activity-dependent sensor and integrator for changing membrane potential and driving transcription in individual and populations of neurons in vitro and in vivo.
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Affiliation(s)
- Emmanuel L. Crespo
- College of Medicine, Central Michigan University, Mount Pleasant, MI 48859, USA
- Biochemistry, Cell and Molecular Biology Graduate Program, Central Michigan University, Mount Pleasant, MI 48859, USA
| | - Akash Pal
- College of Medicine, Central Michigan University, Mount Pleasant, MI 48859, USA
- Program in Neuroscience, Central Michigan University, Mount Pleasant, MI 48859, USA
| | - Mansi Prakash
- College of Medicine, Central Michigan University, Mount Pleasant, MI 48859, USA
| | - Alexander D. Silvagnoli
- College of Medicine, Central Michigan University, Mount Pleasant, MI 48859, USA
- Program in Neuroscience, Central Michigan University, Mount Pleasant, MI 48859, USA
| | - Zohair Zaidi
- Duke University, Undergraduate Neuroscience Program, Durham, NC 27710
| | | | - Maya O. Tree
- College of Medicine, Central Michigan University, Mount Pleasant, MI 48859, USA
| | - Nathan C. Shaner
- University of California, San Diego, School of Medicine, Department of Neuroscience, 9500 Gilman Drive La Jolla, CA 92093-0662, USA
| | - Diane Lipscombe
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
- Carney Institute for Brain Science, Brown University, Providence, RI 02906, USA
| | - Christopher Moore
- Department of Neuroscience, Brown University, Providence, RI 02912, USA
- Carney Institute for Brain Science, Brown University, Providence, RI 02906, USA
| | - Ute Hochgeschwender
- College of Medicine, Central Michigan University, Mount Pleasant, MI 48859, USA
- Biochemistry, Cell and Molecular Biology Graduate Program, Central Michigan University, Mount Pleasant, MI 48859, USA
- Program in Neuroscience, Central Michigan University, Mount Pleasant, MI 48859, USA
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27
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Wang M, Lou K, Liu Z, Wei P, Liu Q. Multi-objective optimization via evolutionary algorithm (MOVEA) for high-definition transcranial electrical stimulation of the human brain. Neuroimage 2023; 280:120331. [PMID: 37604295 DOI: 10.1016/j.neuroimage.2023.120331] [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: 04/03/2023] [Revised: 07/01/2023] [Accepted: 08/14/2023] [Indexed: 08/23/2023] Open
Abstract
Designing a transcranial electrical stimulation (tES) strategy requires considering multiple objectives, such as intensity in the target area, focality, stimulation depth, and avoidance zone. These objectives are often mutually exclusive. In this paper, we propose a general framework, called multi-objective optimization via evolutionary algorithm (MOVEA), which solves the non-convex optimization problem in designing tES strategies without a predefined direction. MOVEA enables simultaneous optimization of multiple targets through Pareto optimization, generating a Pareto front after a single run without manual weight adjustment and allowing easy expansion to more targets. This Pareto front consists of optimal solutions that meet various requirements while respecting trade-off relationships between conflicting objectives such as intensity and focality. MOVEA is versatile and suitable for both transcranial alternating current stimulation (tACS) and transcranial temporal interference stimulation (tTIS) based on high definition (HD) and two-pair systems. We comprehensively compared tACS and tTIS in terms of intensity, focality, and steerability for targets at different depths. Our findings reveal that tTIS enhances focality by reducing activated volume outside the target by 60%. HD-tTIS and HD-tDCS can achieve equivalent maximum intensities, surpassing those of two-pair tTIS, such as 0.51 V/m under HD-tACS/HD-tTIS and 0.42 V/m under two-pair tTIS for the motor area as a target. Analysis of variance in eight subjects highlights individual differences in both optimal stimulation policies and outcomes for tACS and tTIS, emphasizing the need for personalized stimulation protocols. These findings provide guidance for designing appropriate stimulation strategies for tACS and tTIS. MOVEA facilitates the optimization of tES based on specific objectives and constraints, advancing tTIS and tACS-based neuromodulation in understanding the causal relationship between brain regions and cognitive functions and treating diseases. The code for MOVEA is available at https://github.com/ncclabsustech/MOVEA.
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Affiliation(s)
- Mo Wang
- Department of Biomedical Engineering, Southern University of Science and Technology, China.
| | - Kexin Lou
- Department of Biomedical Engineering, Southern University of Science and Technology, China; School of Electrical Engineering and Computer Science, University of Queensland, Australia.
| | - Zeming Liu
- Department of Biomedical Engineering, Southern University of Science and Technology, China.
| | - Pengfei Wei
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China.
| | - Quanying Liu
- Department of Biomedical Engineering, Southern University of Science and Technology, China.
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28
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Esfahani MJ, Farboud S, Ngo HVV, Schneider J, Weber FD, Talamini LM, Dresler M. Closed-loop auditory stimulation of sleep slow oscillations: Basic principles and best practices. Neurosci Biobehav Rev 2023; 153:105379. [PMID: 37660843 DOI: 10.1016/j.neubiorev.2023.105379] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 08/25/2023] [Accepted: 08/30/2023] [Indexed: 09/05/2023]
Abstract
Sleep is essential for our physical and mental well-being. During sleep, despite the paucity of overt behavior, our brain remains active and exhibits a wide range of coupled brain oscillations. In particular slow oscillations are characteristic for sleep, however whether they are directly involved in the functions of sleep, or are mere epiphenomena, is not yet fully understood. To disentangle the causality of these relationships, experiments utilizing techniques to detect and manipulate sleep oscillations in real-time are essential. In this review, we first overview the theoretical principles of closed-loop auditory stimulation (CLAS) as a method to study the role of slow oscillations in the functions of sleep. We then describe technical guidelines and best practices to perform CLAS and analyze results from such experiments. We further provide an overview of how CLAS has been used to investigate the causal role of slow oscillations in various sleep functions. We close by discussing important caveats, open questions, and potential topics for future research.
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Affiliation(s)
| | - Soha Farboud
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, the Netherlands
| | - Hong-Viet V Ngo
- Department of Psychology, University of Essex, United Kingdom; Department of Psychology, University of Lübeck, Germany; Center for Brain, Behaviour and Metabolism, University of Lübeck, Germany
| | - Jules Schneider
- Department of Psychiatry and Psychotherapy, University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany; Department of Neurology, University Hospital Carl Gustav Carus, Technische Universität Dresden, Germany
| | - Frederik D Weber
- Donders Institute for Brain, Cognition and Behaviour, Radboudumc, the Netherlands; Department of Sleep and Cognition, Netherlands Institute for Neuroscience, an institute of the Royal Netherlands Academy of Arts and Sciences, Amsterdam, the Netherlands
| | - Lucia M Talamini
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands; Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - Martin Dresler
- Donders Institute for Brain, Cognition and Behaviour, Radboudumc, the Netherlands.
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29
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Pan R, Ye S, Zhong Y, Chen Q, Cai Y. Transcranial alternating current stimulation for the treatment of major depressive disorder: from basic mechanisms toward clinical applications. Front Hum Neurosci 2023; 17:1197393. [PMID: 37731669 PMCID: PMC10507344 DOI: 10.3389/fnhum.2023.1197393] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Accepted: 08/22/2023] [Indexed: 09/22/2023] Open
Abstract
Non-pharmacological treatment is essential for patients with major depressive disorder (MDD) that is medication resistant or who are unable to take medications. Transcranial alternating current stimulation (tACS) is a non-invasive brain stimulation method that manipulates neural oscillations. In recent years, tACS has attracted substantial attention for its potential as an MDD treatment. This review summarizes the latest advances in tACS treatment for MDD and outlines future directions for promoting its clinical application. We first introduce the neurophysiological mechanism of tACS and its novel developments. In particular, two well-validated tACS techniques have high application potential: high-definition tACS targeting local brain oscillations and bifocal tACS modulating interarea functional connectivity. Accordingly, we summarize the underlying mechanisms of tACS modulation for MDD. We sort out the local oscillation abnormalities within the reward network and the interarea oscillatory synchronizations among multiple MDD-related networks in MDD patients, which provide potential modulation targets of tACS interventions. Furthermore, we review the latest clinical studies on tACS treatment for MDD, which were based on different modulation mechanisms and reported alleviations in MDD symptoms. Finally, we discuss the main challenges of current tACS treatments for MDD and outline future directions to improve intervention target selection, tACS implementation, and clinical validations.
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Affiliation(s)
- Ruibo Pan
- Department of Psychiatry, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Shengfeng Ye
- Department of Psychology and Behavioral Science, Zhejiang University, Hangzhou, China
| | - Yun Zhong
- Department of Psychology and Behavioral Science, Zhejiang University, Hangzhou, China
| | - Qiaozhen Chen
- Department of Psychiatry, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Key Laboratory of Medical Molecular Imaging of Zhejiang Province, Hangzhou, China
| | - Ying Cai
- Department of Psychology and Behavioral Science, Zhejiang University, Hangzhou, China
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30
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McLaren JR, Luo Y, Kwon H, Shi W, Kramer MA, Chu CJ. Preliminary evidence of a relationship between sleep spindles and treatment response in epileptic encephalopathy. Ann Clin Transl Neurol 2023; 10:1513-1524. [PMID: 37363864 PMCID: PMC10502632 DOI: 10.1002/acn3.51840] [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: 05/24/2023] [Accepted: 06/12/2023] [Indexed: 06/28/2023] Open
Abstract
OBJECTIVE Epileptic encephalopathy with spike-wave activation in sleep (EE-SWAS) is a challenging neurodevelopmental disease characterized by abundant epileptiform spikes during non-rapid eye movement (NREM) sleep accompanied by cognitive dysfunction. The mechanism of cognitive dysfunction is unknown, but treatment with high-dose diazepam may improve symptoms. Spike rate does not predict treatment response, but spikes may disrupt sleep spindles. We hypothesized that in patients with EE-SWAS: (1) spikes and spindles would be anti-correlated, (2) high-dose diazepam would increase spindles and decrease spikes, and (3) spindle response would be greater in those with cognitive improvement. METHODS Consecutive EE-SWAS patients treated with high-dose diazepam that met the criteria were included. Using a validated automated spindle detector, spindle rate, duration, and percentage were computed in pre- and post-treatment NREM sleep. Spikes were quantified using a validated automated spike detector. The cognitive response was determined from a chart review. RESULTS Spindle rate was anti-correlated with the spike rate in the channel with the maximal spike rate (p = 0.002) and averaged across all channels (p = 0.0005). Spindle rate, duration, and percentage each increased, and spike rate decreased, after high-dose diazepam treatment (p ≤ 2e-5, all tests). Spindle rate, duration, and percentage (p ≤ 0.004, all tests) were increased in patients with cognitive improvement after treatment, but not those without. Changes in spindle rate but not changes in spike rate distinguished between groups. INTERPRETATION These findings confirm thalamocortical disruption in EE-SWAS, identify a mechanism through which benzodiazepines may support cognitive recovery, and introduce sleep spindles as a promising mechanistic biomarker to detect treatment response in severe epileptic encephalopathies.
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Affiliation(s)
- John R. McLaren
- Department of NeurologyMassachusetts General HospitalBoston02114MassachusettsUSA
- Harvard Medical SchoolBoston02115MassachusettsUSA
| | - Yancheng Luo
- Department of NeurologyMassachusetts General HospitalBoston02114MassachusettsUSA
- Harvard Medical SchoolBoston02115MassachusettsUSA
| | - Hunki Kwon
- Department of NeurologyMassachusetts General HospitalBoston02114MassachusettsUSA
- Harvard Medical SchoolBoston02115MassachusettsUSA
| | - Wen Shi
- Department of NeurologyMassachusetts General HospitalBoston02114MassachusettsUSA
- Harvard Medical SchoolBoston02115MassachusettsUSA
| | - Mark A. Kramer
- Department of Mathematics and Statistics & Center for Systems NeuroscienceBoston UniversityBoston02215MassachusettsUSA
| | - Catherine J. Chu
- Department of NeurologyMassachusetts General HospitalBoston02114MassachusettsUSA
- Harvard Medical SchoolBoston02115MassachusettsUSA
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31
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Wodeyar A, Marshall FA, Chu CJ, Eden UT, Kramer MA. Different methods to estimate the phase of neural rhythms agree, but only during times of low uncertainty. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522914. [PMID: 37693592 PMCID: PMC10491120 DOI: 10.1101/2023.01.05.522914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Rhythms are a common feature of brain activity. Across different types of rhythms, the phase has been proposed to have functional consequences, thus requiring its accurate specification from noisy data. Phase is conventionally specified using techniques that presume a frequency band-limited rhythm. However, in practice, observed brain rhythms are typically non-sinusoidal and amplitude modulated. How these features impact methods to estimate phase remains unclear. To address this, we consider three phase estimation methods, each with different underlying assumptions about the rhythm. We apply these methods to rhythms simulated with different generative mechanisms and demonstrate inconsistency in phase estimates across the different methods. We propose two improvements to the practice of phase estimation: (1) estimating confidence in the phase estimate, and (2) examining the consistency of phase estimates between two (or more) methods.
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Affiliation(s)
- Anirudh Wodeyar
- Department of Mathematics & Statistics, Boston University, Boston MA, USA, 02215
| | - François A. Marshall
- Department of Mathematics & Statistics, Boston University, Boston MA, USA, 02215
| | - Catherine J. Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA; USA, 02215
- Harvard Medical School, Boston, MA, USA, 02114
| | - Uri T. Eden
- Department of Mathematics & Statistics, Boston University, Boston MA, USA, 02215
- Center for Systems Neuroscience, Boston University, Boston MA, USA, 02215
| | - Mark A. Kramer
- Department of Mathematics & Statistics, Boston University, Boston MA, USA, 02215
- Center for Systems Neuroscience, Boston University, Boston MA, USA, 02215
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32
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Conessa A, Debarnot U, Siegler I, Boutin A. Sleep-related motor skill consolidation and generalizability after physical practice, motor imagery, and action observation. iScience 2023; 26:107314. [PMID: 37520714 PMCID: PMC10374463 DOI: 10.1016/j.isci.2023.107314] [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: 03/03/2023] [Revised: 05/15/2023] [Accepted: 07/04/2023] [Indexed: 08/01/2023] Open
Abstract
Sleep benefits the consolidation of motor skills learned by physical practice, mainly through periodic thalamocortical sleep spindle activity. However, motor skills can be learned without overt movement through motor imagery or action observation. Here, we investigated whether sleep spindle activity also supports the consolidation of non-physically learned movements. Forty-five electroencephalographic sleep recordings were collected during a daytime nap after motor sequence learning by physical practice, motor imagery, or action observation. Our findings reveal that a temporal cluster-based organization of sleep spindles underlies motor memory consolidation in all groups, albeit with distinct behavioral outcomes. A daytime nap offers an early sleep window promoting the retention of motor skills learned by physical practice and motor imagery, and its generalizability toward the inter-manual transfer of skill after action observation. Findings may further have practical impacts with the development of non-physical rehabilitation interventions for patients having to remaster skills following peripherical or brain injury.
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Affiliation(s)
- Adrien Conessa
- Université Paris-Saclay, CIAMS, 91405 Orsay, France
- Université d’Orléans, CIAMS, 45067 Orléans, France
| | - Ursula Debarnot
- University Lyon, UCBL-Lyon 1, Inter-University Laboratory of Human Movement Biology, EA7424, 69622 Villeurbanne, France
- Institut Universitaire de France, Paris, France
| | - Isabelle Siegler
- Université Paris-Saclay, CIAMS, 91405 Orsay, France
- Université d’Orléans, CIAMS, 45067 Orléans, France
| | - Arnaud Boutin
- Université Paris-Saclay, CIAMS, 91405 Orsay, France
- Université d’Orléans, CIAMS, 45067 Orléans, France
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Soleimani G, Nitsche MA, Bergmann TO, Towhidkhah F, Violante IR, Lorenz R, Kuplicki R, Tsuchiyagaito A, Mulyana B, Mayeli A, Ghobadi-Azbari P, Mosayebi-Samani M, Zilverstand A, Paulus MP, Bikson M, Ekhtiari H. Closing the loop between brain and electrical stimulation: towards precision neuromodulation treatments. Transl Psychiatry 2023; 13:279. [PMID: 37582922 PMCID: PMC10427701 DOI: 10.1038/s41398-023-02565-5] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 07/06/2023] [Accepted: 07/20/2023] [Indexed: 08/17/2023] Open
Abstract
One of the most critical challenges in using noninvasive brain stimulation (NIBS) techniques for the treatment of psychiatric and neurologic disorders is inter- and intra-individual variability in response to NIBS. Response variations in previous findings suggest that the one-size-fits-all approach does not seem the most appropriate option for enhancing stimulation outcomes. While there is a growing body of evidence for the feasibility and effectiveness of individualized NIBS approaches, the optimal way to achieve this is yet to be determined. Transcranial electrical stimulation (tES) is one of the NIBS techniques showing promising results in modulating treatment outcomes in several psychiatric and neurologic disorders, but it faces the same challenge for individual optimization. With new computational and methodological advances, tES can be integrated with real-time functional magnetic resonance imaging (rtfMRI) to establish closed-loop tES-fMRI for individually optimized neuromodulation. Closed-loop tES-fMRI systems aim to optimize stimulation parameters based on minimizing differences between the model of the current brain state and the desired value to maximize the expected clinical outcome. The methodological space to optimize closed-loop tES fMRI for clinical applications includes (1) stimulation vs. data acquisition timing, (2) fMRI context (task-based or resting-state), (3) inherent brain oscillations, (4) dose-response function, (5) brain target trait and state and (6) optimization algorithm. Closed-loop tES-fMRI technology has several advantages over non-individualized or open-loop systems to reshape the future of neuromodulation with objective optimization in a clinically relevant context such as drug cue reactivity for substance use disorder considering both inter and intra-individual variations. Using multi-level brain and behavior measures as input and desired outcomes to individualize stimulation parameters provides a framework for designing personalized tES protocols in precision psychiatry.
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Affiliation(s)
- Ghazaleh Soleimani
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Michael A Nitsche
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
- Bielefeld University, University Hospital OWL, Protestant Hospital of Bethel Foundation, University Clinic of Psychiatry and Psychotherapy, and University Clinic of Child and Adolescent Psychiatry and Psychotherapy, Bielefeld, Germany
| | - Til Ole Bergmann
- Neuroimaging Center, Focus Program Translational Neuroscience, Johannes Gutenberg University Medical Center Mainz, Mainz, Germany
- Leibniz Institute for Resilience Research, Mainz, Germany
| | - Farzad Towhidkhah
- Department of Biomedical Engineering, Amirkabir University of Technology, Tehran, Iran
| | - Ines R Violante
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guilford, UK
| | - Romy Lorenz
- Department of Psychology, Stanford University, Stanford, CA, USA
- MRC CBU, University of Cambridge, Cambridge, UK
- Department of Neurophysics, MPI, Leipzig, Germany
| | | | | | - Beni Mulyana
- Laureate Institute for Brain Research, Tulsa, OK, USA
- School of Electrical and Computer Engineering, University of Oklahoma, Tulsa, OK, USA
| | - Ahmad Mayeli
- University of Pittsburgh Medical Center, Pittsburg, PA, USA
| | - Peyman Ghobadi-Azbari
- Department of Biomedical Engineering, Shahed University, Tehran, Iran
- Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Mosayebi-Samani
- Department of Psychology and Neuroscience, Leibniz Research Center for Working Environment and Human Factors, Dortmund, Germany
| | - Anna Zilverstand
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA
| | | | | | - Hamed Ekhtiari
- Department of Psychiatry & Behavioral Sciences, University of Minnesota, Minneapolis, MN, USA.
- Laureate Institute for Brain Research, Tulsa, OK, USA.
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34
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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: 6] [Impact Index Per Article: 3.0] [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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35
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Herrero Babiloni A, Brazeau D, De Koninck BP, Lavigne GJ, De Beaumont L. The Utility of Non-invasive Brain Stimulation in Relieving Insomnia Symptoms and Sleep Disturbances Across Different Sleep Disorders: a Topical Review. CURRENT SLEEP MEDICINE REPORTS 2023; 9:124-132. [DOI: 10.1007/s40675-023-00254-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/20/2023] [Indexed: 01/03/2025]
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36
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McLaren JR, Luo Y, Kwon H, Shi W, Kramer MA, Chu CJ. Preliminary evidence of a relationship between sleep spindles and treatment response in epileptic encephalopathy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.22.537937. [PMID: 37163098 PMCID: PMC10168273 DOI: 10.1101/2023.04.22.537937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Objective Epileptic encephalopathy with spike wave activation in sleep (EE-SWAS) is a challenging neurodevelopmental disease characterized by abundant epileptiform spikes during non-rapid eye movement (NREM) sleep accompanied by cognitive dysfunction. The mechanism of cognitive dysfunction is unknown, but treatment with high-dose diazepam may improve symptoms. Spike rate does not predict treatment response, but spikes may disrupt sleep spindles. We hypothesized that in patients with EE-SWAS: 1) spikes and spindles would be anticorrelated, 2) high-dose diazepam would increase spindles and decrease spikes, and 3) spindle response would be greater in those with cognitive improvement. Methods Consecutive EE-SWAS patients treated with high-dose diazepam that met criteria were included. Using a validated automated spindle detector, spindle rate, duration, and percentage were computed in pre- and post-treatment NREM sleep. Spikes were quantified using a validated automated spike detector. Cognitive response was determined from chart review. Results Spindle rate was anticorrelated with spike rate in the channel with the maximal spike rate ( p =0.002) and averaged across all channels ( p =0.0005). Spindle rate, duration, and percentage each increased, and spike rate decreased, after high-dose diazepam treatment ( p≤ 2e-5, all tests). Spindle rate, duration, and percentage ( p ≤0.004, all tests) were increased in patients with cognitive improvement after treatment, but not those without. Changes in spike rate did not distinguish between groups. Interpretation These findings confirm thalamocortical disruption in EE-SWAS, identify a mechanism through which benzodiazepines may support cognitive recovery, and introduce sleep spindles as a promising mechanistic biomarker to detect treatment response in severe epileptic encephalopathies.
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Affiliation(s)
- John R McLaren
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA 02114
- Harvard Medical School, Boston, MA, USA 02115
| | - Yancheng Luo
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA 02114
- Harvard Medical School, Boston, MA, USA 02115
| | - Hunki Kwon
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA 02114
- Harvard Medical School, Boston, MA, USA 02115
| | - Wen Shi
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA 02114
- Harvard Medical School, Boston, MA, USA 02115
| | - Mark A Kramer
- Department of Mathematics and Statistics & Center for Systems Neuroscience, Boston University, Boston, MA, USA 02215
| | - Catherine J Chu
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA 02114
- Harvard Medical School, Boston, MA, USA 02115
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37
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Jaramillo V, Schoch SF, Markovic A, Kohler M, Huber R, Lustenberger C, Kurth S. An infant sleep electroencephalographic marker of thalamocortical connectivity predicts behavioral outcome in late infancy. Neuroimage 2023; 269:119924. [PMID: 36739104 DOI: 10.1016/j.neuroimage.2023.119924] [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: 10/10/2022] [Revised: 01/24/2023] [Accepted: 02/01/2023] [Indexed: 02/05/2023] Open
Abstract
Infancy represents a critical period during which thalamocortical brain connections develop and mature. Deviations in the maturation of thalamocortical connectivity are linked to neurodevelopmental disorders. There is a lack of early biomarkers to detect and localize neuromaturational deviations, which can be overcome with mapping through high-density electroencephalography (hdEEG) assessed in sleep. Specifically, slow waves and spindles in non-rapid eye movement (NREM) sleep are generated by the thalamocortical system, and their characteristics, slow wave slope and spindle density, are closely related to neuroplasticity and learning. Spindles are often subdivided into slow (11.0-13.0 Hz) and fast (13.5-16.0 Hz) frequencies, for which not only different functions have been proposed, but for which also distinctive developmental trajectories have been reported across the first years of life. Recent studies further suggest that information processing during sleep underlying sleep-dependent learning is promoted by the temporal coupling of slow waves and spindles, yet slow wave-spindle coupling remains unexplored in infancy. Thus, we evaluated three potential biomarkers: 1) slow wave slope, 2) spindle density, and 3) the temporal coupling of slow waves with spindles. We use hdEEG to first examine the occurrence and spatial distribution of these three EEG features in healthy infants and second to evaluate a predictive relationship with later behavioral outcomes. We report four key findings: First, infants' EEG features appear locally: slow wave slope is maximal in occipital and frontal areas, whereas slow and fast spindle density is most pronounced frontocentrally. Second, slow waves and spindles are temporally coupled in infancy, with maximal coupling strength in the occipital areas of the brain. Third, slow wave slope, fast spindle density, and slow wave-spindle coupling are not associated with concurrent behavioral status (6 months). Fourth, fast spindle density in central and frontocentral regions at age 6 months predicts overall developmental status at age 12 months, and motor skills at age 12 and 24 months. Neither slow wave slope nor slow wave-spindle coupling predict later behavioral development. We further identified spindle frequency as a determinant of slow and fast spindle density, which accordingly, also predicts motor skills at 24 months. Our results propose fast spindle density, or alternatively spindle frequency, as early EEG biomarker for identifying thalamocortical maturation, which can potentially be used for early diagnosis of neurodevelopmental disorders in infants. These findings are in support of a role of sleep spindles in sensorimotor microcircuitry development. A crucial next step will be to evaluate whether early therapeutic interventions may be effective to reverse deviations in identified individuals at risk.
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Affiliation(s)
- Valeria Jaramillo
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Surrey Sleep Research Centre, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom; Neuromodulation Laboratory, School of Psychology, University of Surrey, Guildford, United Kingdom
| | - Sarah F Schoch
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, NL
| | - Andjela Markovic
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Department of Psychology, University of Fribourg, Fribourg, CH
| | - Malcolm Kohler
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH
| | - Reto Huber
- Child Development Center, University Children's Hospital Zurich, Zurich, CH; Children's Research Center, University Children's Hospital Zurich, University of Zurich (UZH), Zürich, Switzerland; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric Hospital, University of Zurich, CH
| | - Caroline Lustenberger
- Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Neural Control of Movement Lab, Institute of Human Movement Sciences and Sport, Department of Health Sciences and Technology, ETH Zurich, 8092 Zurich, Switzerland
| | - Salome Kurth
- Department of Pulmonology, University Hospital Zurich, Zurich, CH; Center of Competence Sleep & Health Zurich, University of Zurich, Zurich, CH; Department of Psychology, University of Fribourg, Fribourg, CH.
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38
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Bagautdinova J, Mayeli A, Wilson JD, Donati FL, Colacot RM, Meyer N, Fusar-Poli P, Ferrarelli F. Sleep Abnormalities in Different Clinical Stages of Psychosis: A Systematic Review and Meta-analysis. JAMA Psychiatry 2023; 80:202-210. [PMID: 36652243 PMCID: PMC9857809 DOI: 10.1001/jamapsychiatry.2022.4599] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Accepted: 11/11/2022] [Indexed: 01/19/2023]
Abstract
Importance Abnormal sleep is frequent in psychosis; however, sleep abnormalities in different stages (ie, clinical high risk for psychosis [CHR-P], early psychosis [EP], and chronic psychosis [CP]) have not been characterized. Objective To identify sleep abnormalities across psychosis stages. Data Sources Web of Science and PubMed were searched between inception and June 15, 2022. Studies written in English were included. Study Selection Sleep disturbance prevalence studies and case-control studies reporting sleep quality, sleep architecture, or sleep electroencephalography oscillations in CHR-P, EP, or CP. Data Extraction and Synthesis This systematic review and meta-analysis followed Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Stage-specific and pooled random-effects meta-analyses were conducted, along with the assessment of heterogeneity, study quality, and meta-regressions (clinical stage, sex, age, medication status, and psychotic symptoms). Main Outcomes and Measures Sleep disturbance prevalence, self-reported sleep quality, sleep architecture (total sleep time, sleep latency, sleep efficiency, nonrapid eye movement, rapid eye movement stages, and number of arousals), and sleep electroencephalography oscillations (spindle density, amplitude, and duration, and slow wave density). Results Fifty-nine studies with up to 6710 patients (n = 5135 for prevalence) and 977 controls were included. Sleep disturbance prevalence in pooled cases was 50% (95% CI, 40%-61%) and it was similar in each psychosis stage. Sleep quality was worse in pooled cases vs controls (standardized mean difference [SMD], 1.00 [95% CI, 0.70-1.30]). Sleep architecture alterations included higher sleep onset latency (SMD [95% CI]: pooled cases, 0.96 [0.62-1.30]; EP, 0.72 [0.52-0.92]; CP, 1.36 [0.66-2.05]), higher wake after sleep onset (SMD [95% CI]: pooled cases, 0.5 [0.29-0.71]; EP, 0.62 [0.34-0.89]; CP, 0.51 [0.09-0.93]), higher number of arousals (SMD [95% CI]: pooled cases, 0.45 [0.07-0.83]; CP, 0.81 [0.30-1.32]), higher stage 1 sleep (SMD [95% CI]: pooled cases, 0.23 [0.06-0.40]; EP, 0.34 [0.15-0.53]), lower sleep efficiency (SMD [95% CI]: pooled cases, -0.75 [-0.98 to -0.52]; EP, -0.90 [-1.20 to -0.60]; CP, -0.73 [-1.14 to -0.33]), and lower rapid eye movement density (SMD [95% CI]: pooled cases, 0.37 [0.14-0.60]; CP, 0.4 [0.19-0.77]). Spindle parameter deficits included density (SMD [95% CI]: pooled cases, -1.06 [-1.50 to -0.63]; EP, -0.80 [-1.22 to -0.39]; CP, -1.39 [-2.05 to -0.74]; amplitude: pooled cases, -1.08 [-1.33 to -0.82]; EP, -0.86 [-1.24 to -0.47]; CP, -1.25 [-1.58 to -0.91]; and duration: pooled cases: -1.2 [-1.69 to -0.73]; EP, -0.71 [-1.08 to -0.34]; CP, -1.74 [-2.10 to -1.38]). Individuals with CP had more frequent arousals vs CHR-P (z = 2.24, P = .02) and reduced spindle duration vs EP (z = -3.91, P < .001). Conclusions and Relevance In this systematic review and meta-analysis, sleep disturbances were found to be prevalent throughout the course of psychosis, and different psychosis stages showed both shared and distinct abnormalities in sleep quality, architecture, and spindles. These findings suggest that sleep should become a core clinical target and research domain from at-risk to early and chronic stages of psychosis.
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Affiliation(s)
| | - Ahmad Mayeli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - James D. Wilson
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Francesco L. Donati
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Health Sciences, University of Milan, Milan, Italy
| | - Rebekah M. Colacot
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Nicholas Meyer
- Department of Psychosis Studies, Institute of Psychology, Psychiatry and Neuroscience, King's College London, London, United Kingdom
| | - Paolo Fusar-Poli
- Early Psychosis: Interventions and Clinical-detection (EPIC) Lab, Department of Psychosis Studies, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, United Kingdom
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Fabio Ferrarelli
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
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39
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Fehér KD, Omlin X, Tarokh L, Schneider CL, Morishima Y, Züst MA, Wunderlin M, Koenig T, Hertenstein E, Ellenberger B, Ruch S, Schmidig F, Mikutta C, Trinca E, Senn W, Feige B, Klöppel S, Nissen C. Feasibility, efficacy, and functional relevance of automated auditory closed-loop suppression of slow-wave sleep in humans. J Sleep Res 2023:e13846. [PMID: 36806335 DOI: 10.1111/jsr.13846] [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: 10/26/2022] [Revised: 12/22/2022] [Accepted: 01/23/2023] [Indexed: 02/22/2023]
Abstract
Slow-wave sleep (SWS) is a fundamental physiological process, and its modulation is of interest for basic science and clinical applications. However, automatised protocols for the suppression of SWS are lacking. We describe the development of a novel protocol for the automated detection (based on the whole head topography of frontal slow waves) and suppression of SWS (through closed-loop modulated randomised pulsed noise), and assessed the feasibility, efficacy and functional relevance compared to sham stimulation in 15 healthy young adults in a repeated-measure sleep laboratory study. Auditory compared to sham stimulation resulted in a highly significant reduction of SWS by 30% without affecting total sleep time. The reduction of SWS was associated with an increase in lighter non-rapid eye movement sleep and a shift of slow-wave activity towards the end of the night, indicative of a homeostatic response and functional relevance. Still, cumulative slow-wave activity across the night was significantly reduced by 23%. Undisturbed sleep led to an evening to morning reduction of wake electroencephalographic theta activity, thought to reflect synaptic downscaling during SWS, while suppression of SWS inhibited this dissipation. We provide evidence for the feasibility, efficacy, and functional relevance of a novel fully automated protocol for SWS suppression based on auditory closed-loop stimulation. Future work is needed to further test for functional relevance and potential clinical applications.
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Affiliation(s)
- Kristoffer D Fehér
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Division of Psychiatric Specialties, Geneva University Hospitals (HUG), Geneva, Switzerland
| | - Ximena Omlin
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Division of Psychiatric Specialties, Geneva University Hospitals (HUG), Geneva, Switzerland
| | - Leila Tarokh
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Carlotta L Schneider
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Yosuke Morishima
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Marc A Züst
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Marina Wunderlin
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Department of Social Neuroscience and Social Psychology, Institute of Psychology, University of Bern, Bern, Switzerland
| | - Thomas Koenig
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Elisabeth Hertenstein
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Simon Ruch
- Institute for Neuromodulation and Neurotechnology, Department of Neurosurgery and Neurotechnology, University Hospital and University of Tübingen, Tübingen, Germany
| | - Flavio Schmidig
- Cognitive Neuroscience of Memory and Consciousness, Institute of Psychology, University of Bern, Bern, Switzerland
| | - Christian Mikutta
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Privatklinik Meiringen, Meiringen, Switzerland
| | - Ersilia Trinca
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Walter Senn
- Institute of Physiology, University of Bern, Bern, Switzerland
| | - Bernd Feige
- University of Freiburg Medical Center, Freiburg, Germany
| | - Stefan Klöppel
- University Hospital of Old Age Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Christoph Nissen
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland.,Division of Psychiatric Specialties, Geneva University Hospitals (HUG), Geneva, Switzerland
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40
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Chen X, Ma R, Zhang W, Zeng GQ, Wu Q, Yimiti A, Xia X, Cui J, Liu Q, Meng X, Bu J, Chen Q, Pan Y, Yu NX, Wang S, Deng ZD, Sack AT, Laughlin MM, Zhang X. Alpha oscillatory activity is causally linked to working memory retention. PLoS Biol 2023; 21:e3001999. [PMID: 36780560 PMCID: PMC9983870 DOI: 10.1371/journal.pbio.3001999] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 03/03/2023] [Accepted: 01/12/2023] [Indexed: 02/15/2023] Open
Abstract
Although previous studies have reported correlations between alpha oscillations and the "retention" subprocess of working memory (WM), causal evidence has been limited in human neuroscience due to the lack of delicate modulation of human brain oscillations. Conventional transcranial alternating current stimulation (tACS) is not suitable for demonstrating the causal evidence for parietal alpha oscillations in WM retention because of its inability to modulate brain oscillations within a short period (i.e., the retention subprocess). Here, we developed an online phase-corrected tACS system capable of precisely correcting for the phase differences between tACS and concurrent endogenous oscillations. This system permits the modulation of brain oscillations at the target stimulation frequency within a short stimulation period and is here applied to empirically demonstrate that parietal alpha oscillations causally relate to WM retention. Our experimental design included both in-phase and anti-phase alpha-tACS applied to participants during the retention subprocess of a modified Sternberg paradigm. Compared to in-phase alpha-tACS, anti-phase alpha-tACS decreased both WM performance and alpha activity. These findings strongly support a causal link between alpha oscillations and WM retention and illustrate the broad application prospects of phase-corrected tACS.
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Affiliation(s)
- Xueli Chen
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
- Department of Social and Behavioural Sciences, City University of Hong Kong, Hong Kong, People’s Republic of China
| | - Ru Ma
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Wei Zhang
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Ginger Qinghong Zeng
- Application Technology Center of Physical Therapy to Brain Disorders, Institute of Advanced Technology, University of Science & Technology of China, Hefei, China
| | - Qianying Wu
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
- Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, California, United States of America
| | - Ajiguli Yimiti
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Xinzhao Xia
- Centers for Biomedical Engineering, School of Information Science and Technology, University of Science & Technology of China, Hefei, China
| | - Jiangtian Cui
- Centers for Biomedical Engineering, School of Information Science and Technology, University of Science & Technology of China, Hefei, China
- School of Optometry and Vision Science, Cardiff University, Cardiff, United Kingdom
| | - Qiongwei Liu
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Xueer Meng
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
| | - Junjie Bu
- School of Biomedical Engineering, Anhui Medical University, Hefei, China
| | - Qi Chen
- School of Psychology, South China Normal University, Guangzhou, China
| | - Yu Pan
- Shanghai Key Laboratory of Brain-Machine Intelligence for Information Behavior, School of Business and Management, Shanghai International Studies University, Shanghai, China
| | - Nancy Xiaonan Yu
- Department of Social and Behavioural Sciences, City University of Hong Kong, Hong Kong, People’s Republic of China
| | - Shouyan Wang
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Zhi-De Deng
- Noninvasive Neuromodulation Unit, Experimental Therapeutics & Pathophysiology Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, Bethesda, USA
| | - Alexander T. Sack
- Department of Cognitive Neuroscience, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Myles Mc Laughlin
- Exp ORL, Department of Neuroscience, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Xiaochu Zhang
- Department of Radiology, the First Affiliated Hospital of USTC, Hefei National Research Center for Physical Sciences at the Microscale and School of Life Science, Division of Life Science and Medicine, University of Science & Technology of China, Hefei, China
- Application Technology Center of Physical Therapy to Brain Disorders, Institute of Advanced Technology, University of Science & Technology of China, Hefei, China
- Department of Psychology, School of Humanities & Social Science, University of Science & Technology of China, Hefei, China
- Institute of Health and Medicine, Hefei Comprehensive National Science Center, Hefei, China
- * E-mail:
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41
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Wischnewski M, Alekseichuk I, Opitz A. Neurocognitive, physiological, and biophysical effects of transcranial alternating current stimulation. Trends Cogn Sci 2023; 27:189-205. [PMID: 36543610 PMCID: PMC9852081 DOI: 10.1016/j.tics.2022.11.013] [Citation(s) in RCA: 80] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 11/23/2022] [Accepted: 11/26/2022] [Indexed: 12/23/2022]
Abstract
Transcranial alternating current stimulation (tACS) can modulate human neural activity and behavior. Accordingly, tACS has vast potential for cognitive research and brain disorder therapies. The stimulation generates oscillating electric fields in the brain that can bias neural spike timing, causing changes in local neural oscillatory power and cross-frequency and cross-area coherence. tACS affects cognitive performance by modulating underlying single or nested brain rhythms, local or distal synchronization, and metabolic activity. Clinically, stimulation tailored to abnormal neural oscillations shows promising results in alleviating psychiatric and neurological symptoms. We summarize the findings of tACS mechanisms, its use for cognitive applications, and novel developments for personalized stimulation.
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Affiliation(s)
- Miles Wischnewski
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA
| | - Ivan Alekseichuk
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA.
| | - Alexander Opitz
- Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN, USA.
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42
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Gebodh N, Miskovic V, Laszlo S, Datta A, Bikson M. A Scalable Framework for Closed-Loop Neuromodulation with Deep Learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.18.524615. [PMID: 36712027 PMCID: PMC9882307 DOI: 10.1101/2023.01.18.524615] [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] [Indexed: 01/22/2023]
Abstract
Closed-loop neuromodulation measures dynamic neural or physiological activity to optimize interventions for clinical and nonclinical behavioral, cognitive, wellness, attentional, or general task performance enhancement. Conventional closed-loop stimulation approaches can contain biased biomarker detection (decoders and error-based triggering) and stimulation-type application. We present and verify a novel deep learning framework for designing and deploying flexible, data-driven, automated closed-loop neuromodulation that is scalable using diverse datasets, agnostic to stimulation technology (supporting multi-modal stimulation: tACS, tDCS, tFUS, TMS), and without the need for personalized ground-truth performance data. Our approach is based on identified periods of responsiveness - detected states that result in a change in performance when stimulation is applied compared to no stimulation. To demonstrate our framework, we acquire, analyze, and apply a data-driven approach to our open sourced GX dataset, which includes concurrent physiological (ECG, EOG) and neuronal (EEG) measures, paired with continuous vigilance/attention-fatigue tracking, and High-Definition transcranial electrical stimulation (HD-tES). Our framework's decision process for intervention application identified 88.26% of trials as correct applications, showed potential improvement with varying stimulation types, or missed opportunities to stimulate, whereas 11.25% of trials were predicted to stimulate at inopportune times. With emerging datasets and stimulation technologies, our unifying and integrative framework; leveraging deep learning (Convolutional Neural Networks - CNNs); demonstrates the adaptability and feasibility of automated multimodal neuromodulation for both clinical and nonclinical applications.
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Affiliation(s)
- Nigel Gebodh
- The Department of Biomedical Engineering, The City College of New York, The City University of New York, New York USA
| | | | | | | | - Marom Bikson
- The Department of Biomedical Engineering, The City College of New York, The City University of New York, New York USA
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43
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Ngo HVV, Antony JW, Rasch B. Real-time stimulation during sleep: prior findings, novel developments, and future perspectives. J Sleep Res 2022; 31:e13735. [PMID: 36180062 DOI: 10.1111/jsr.13735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 09/05/2022] [Indexed: 11/30/2022]
Abstract
Real-time brain stimulation is a powerful technique that continues to gain importance in the field of sleep and cognition. In this special issue, we collected 14 articles about real-time stimulation during sleep, including one review, 12 research articles and one letter covering both human and rodent research from various fields. We hope this special issue sparks greater interest and inspires fellow sleep researchers and clinicians to develop new ideas in the exciting topic of real-time stimulation.
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Affiliation(s)
- Hong-Viet V Ngo
- Department of Psychology, University of Lübeck, Lübeck, Germany
- Center for Brain, Behavior and Metabolism, University of Lübeck, Lübeck, Germany
| | - James W Antony
- Department of Psychology and Child Development, California Polytechnic State University, San Luis Obispo, California, USA
| | - Björn Rasch
- Department of Psychology, University of Fribourg, Fribourg, Switzerland
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44
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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: 1.0] [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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45
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Mander BA, Dave A, Lui KK, Sprecher KE, Berisha D, Chappel-Farley MG, Chen IY, Riedner BA, Heston M, Suridjan I, Kollmorgen G, Zetterberg H, Blennow K, Carlsson CM, Okonkwo OC, Asthana S, Johnson SC, Bendlin BB, Benca RM. Inflammation, tau pathology, and synaptic integrity associated with sleep spindles and memory prior to β-amyloid positivity. Sleep 2022; 45:zsac135. [PMID: 35670275 PMCID: PMC9758508 DOI: 10.1093/sleep/zsac135] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Revised: 05/17/2022] [Indexed: 01/25/2023] Open
Abstract
STUDY OBJECTIVES Fast frequency sleep spindles are reduced in aging and Alzheimer's disease (AD), but the mechanisms and functional relevance of these deficits remain unclear. The study objective was to identify AD biomarkers associated with fast sleep spindle deficits in cognitively unimpaired older adults at risk for AD. METHODS Fifty-eight cognitively unimpaired, β-amyloid-negative, older adults (mean ± SD; 61.4 ± 6.3 years, 38 female) enriched with parental history of AD (77.6%) and apolipoprotein E (APOE) ε4 positivity (25.9%) completed the study. Cerebrospinal fluid (CSF) biomarkers of central nervous system inflammation, β-amyloid and tau proteins, and neurodegeneration were combined with polysomnography (PSG) using high-density electroencephalography and assessment of overnight memory retention. Parallelized serial mediation models were used to assess indirect effects of age on fast frequency (13 to <16Hz) sleep spindle measures through these AD biomarkers. RESULTS Glial activation was associated with prefrontal fast frequency sleep spindle expression deficits. While adjusting for sex, APOE ε4 genotype, apnea-hypopnea index, and time between CSF sampling and sleep study, serial mediation models detected indirect effects of age on fast sleep spindle expression through microglial activation markers and then tau phosphorylation and synaptic degeneration markers. Sleep spindle expression at these electrodes was also associated with overnight memory retention in multiple regression models adjusting for covariates. CONCLUSIONS These findings point toward microglia dysfunction as associated with tau phosphorylation, synaptic loss, sleep spindle deficits, and memory impairment even prior to β-amyloid positivity, thus offering a promising candidate therapeutic target to arrest cognitive decline associated with aging and AD.
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Affiliation(s)
- Bryce A Mander
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
| | - Abhishek Dave
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
- Department of Cognitive Sciences, University of California, Irvine, CA, USA
| | - Kitty K Lui
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
- San Diego State University/University of California San Diego, Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
| | - Katherine E Sprecher
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Destiny Berisha
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Miranda G Chappel-Farley
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Ivy Y Chen
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
| | - Brady A Riedner
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
| | - Margo Heston
- Department of Medicine, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
| | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital
, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital
, Mölndal, Sweden
| | - Cynthia M Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Ozioma C Okonkwo
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Barbara B Bendlin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison, Madison, WI, USA
- Wisconsin Alzheimer’s Institute, Madison, WI, USA
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Veterans Hospital, Madison, WI, USA
| | - Ruth M Benca
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California, Irvine, CA, USA
- Neuroscience Training Program, University of Wisconsin-Madison, Madison, WI, USA
- Department of Neurobiology and Behavior, University of California, Irvine, CA, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, USA
- Department of Psychiatry and Behavioral Medicine, Wake Forest University, Winston-Salem, NC, USA
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Abstract
Over the past few decades, the importance of sleep has become increasingly recognized for many physiologic functions, including cognition. Many studies have reported the deleterious effect of sleep loss or sleep disruption on cognitive performance. Beyond ensuring adequate sleep quality and duration, discovering methods to enhance sleep to augment its restorative effects is important to improve learning in many populations, such as the military, students, age-related cognitive decline, and cognitive disorders.
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Affiliation(s)
- Roneil G Malkani
- Division of Sleep Medicine, Department of Neurology, Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, 710 North Lake Shore Drive, Suite 525, Chicago, IL 60611, USA; Jesse Brown Veterans Affairs Medical Center, Chicago, IL 60612, USA.
| | - Phyllis C Zee
- Division of Sleep Medicine, Department of Neurology, Center for Circadian and Sleep Medicine, Northwestern University Feinberg School of Medicine, 710 North Lake Shore Drive, Suite 520, Chicago, IL 60611, USA
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47
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Malerba P, Whitehurst L, Mednick SC. The space-time profiles of sleep spindles and their coordination with slow oscillations on the electrode manifold. Sleep 2022; 45:6603295. [PMID: 35666552 PMCID: PMC9366646 DOI: 10.1093/sleep/zsac132] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/19/2022] [Indexed: 11/17/2022] Open
Abstract
Sleep spindles are important for sleep quality and cognitive functions, with their coordination with slow oscillations (SOs) potentially organizing cross-region reactivation of memory traces. Here, we describe the organization of spindles on the electrode manifold and their relation to SOs. We analyzed the sleep night EEG of 34 subjects and detected spindles and SOs separately at each electrode. We compared spindle properties (frequency, duration, and amplitude) in slow wave sleep (SWS) and Stage 2 sleep (S2); and in spindles that coordinate with SOs or are uncoupled. We identified different topographical spindle types using clustering analysis that grouped together spindles co-detected across electrodes within a short delay (±300 ms). We then analyzed the properties of spindles of each type, and coordination to SOs. We found that SWS spindles are shorter than S2 spindles, and spindles at frontal electrodes have higher frequencies in S2 compared to SWS. Furthermore, S2 spindles closely following an SO (about 10% of all spindles) show faster frequency, shorter duration, and larger amplitude than uncoupled ones. Clustering identified Global, Local, Posterior, Frontal-Right and Left spindle types. At centro-parietal locations, Posterior spindles show faster frequencies compared to other types. Furthermore, the infrequent SO-spindle complexes are preferentially recruiting Global SO waves coupled with fast Posterior spindles. Our results suggest a non-uniform participation of spindles to complexes, especially evident in S2. This suggests the possibility that different mechanisms could initiate an SO-spindle complex compared to SOs and spindles separately. This has implications for understanding the role of SOs-spindle complexes in memory reactivation.
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Affiliation(s)
- Paola Malerba
- Battelle Center for Mathematical Medicine, The Research Institute at Nationwide Children’s Hospital , Columbus, OH , USA
- School of Medicine, The Ohio State University , Columbus, OH , USA
| | - Lauren Whitehurst
- Department of Psychology, University of Kentucky , Lexington, KY , USA
| | - Sara C Mednick
- Department of Cognitive Science, University of California Irvine , Irvine, CA , USA
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48
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Sale MV, Kuzovina A. Motor training is improved by concurrent application of slow oscillating transcranial alternating current stimulation to motor cortex. BMC Neurosci 2022; 23:45. [PMID: 35840886 PMCID: PMC9287859 DOI: 10.1186/s12868-022-00731-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 07/04/2022] [Indexed: 11/17/2022] Open
Abstract
Physical exercise and neurorehabilitation involve repetitive training that can induce changes in motor performance arising from neuroplasticity. Retention of these motor changes occurs via an encoding process, during which rapid neuroplastic changes occur in response to training. Previous studies show that transcranial alternating current stimulation (tACS), a form of non-invasive brain stimulation, can enhance encoding of a cognitive learning task during wakefulness. However, the effect of tACS on motor processes in the awake brain is unknown. In this study, forty-two healthy 18–35 year old participants received either 0.75 Hz (active) tACS (or sham stimulation) for 30 min during a ballistic thumb abduction motor training task. Training-related behavioural effects were quantified by assessing changes in thumb abduction acceleration, and neuroplastic changes were quantified by measuring motor evoked potential (MEP) amplitude of the abductor pollicis brevis muscle. These measures were reassessed immediately after the motor training task to quantify short-term changes, and then 24 h later to assess longer-term changes. Thumb abduction acceleration in both active and sham stimulation conditions increased immediately after the motor learning, consistent with effective training. Critically, participants in the active group maintained significantly higher thumb acceleration 24 h later (t40 = 2.810, P = 0.044). There were no significant changes or inter-group differences in MEPs for both conditions. The results suggest that 0.75 Hz tACS applied during motor training enhances the effectiveness of motor training, which manifests as enhancement in longer-term task benefits.
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Affiliation(s)
- Martin V Sale
- School of Health and Rehabilitation Sciences, The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia.
| | - Anastasiia Kuzovina
- School of Health and Rehabilitation Sciences, The University of Queensland, St Lucia, Brisbane, QLD, 4072, Australia
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49
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Affiliation(s)
- Juan Facundo Morici
- Institut du Fer à Moulin, UMRS 1270, Inserm, Sorbonne Université, Paris, France
| | - Gabrielle Girardeau
- Institut du Fer à Moulin, UMRS 1270, Inserm, Sorbonne Université, Paris, France.
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50
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Mylonas D, Sjøgård M, Shi Z, Baxter B, Hämäläinen M, Manoach DS, Khan S. A Novel Approach to Estimating the Cortical Sources of Sleep Spindles Using Simultaneous EEG/MEG. Front Neurol 2022; 13:871166. [PMID: 35785365 PMCID: PMC9243385 DOI: 10.3389/fneur.2022.871166] [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: 02/07/2022] [Accepted: 05/18/2022] [Indexed: 11/15/2022] Open
Abstract
Sleep spindles, defining oscillations of stage II non-rapid eye movement sleep (N2), mediate sleep-dependent memory consolidation. Spindles are disrupted in several neurodevelopmental, neuropsychiatric, and neurodegenerative disorders characterized by cognitive impairment. Increasing spindles can improve memory suggesting spindles as a promising physiological target for the development of cognitive enhancing therapies. This effort would benefit from more comprehensive and spatially precise methods to characterize spindles. Spindles, as detected with electroencephalography (EEG), are often widespread across electrodes. Available evidence, however, suggests that they act locally to enhance cortical plasticity in the service of memory consolidation. Here, we present a novel method to enhance the spatial specificity of cortical source estimates of spindles using combined EEG and magnetoencephalography (MEG) data constrained to the cortex based on structural MRI. To illustrate this method, we used simultaneous EEG and MEG recordings from 25 healthy adults during a daytime nap. We first validated source space spindle detection using only EEG data by demonstrating strong temporal correspondence with sensor space EEG spindle detection (gold standard). We then demonstrated that spindle source estimates using EEG alone, MEG alone and combined EEG/MEG are stable across nap sessions. EEG detected more source space spindles than MEG and each modality detected non-overlapping spindles that had distinct cortical source distributions. Source space EEG was more sensitive to spindles in medial frontal and lateral prefrontal cortex, while MEG was more sensitive to spindles in somatosensory and motor cortices. By combining EEG and MEG data this method leverages the differential spatial sensitivities of the two modalities to obtain a more comprehensive and spatially specific source estimation of spindles than possible with either modality alone.
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Affiliation(s)
- Dimitrios Mylonas
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Martin Sjøgård
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Zhaoyue Shi
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Carle Illinois Advanced Imaging Center, Carle Foundation Hospital, Urbana, IL, United States
| | - Bryan Baxter
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Matti Hämäläinen
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
| | - Dara S. Manoach
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
| | - Sheraz Khan
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, United States
- Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, United States
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