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Alipour M, Rausch J, Mednick SC, Cook JD, Plante DT, Malerba P. The Space-Time Organisation of Sleep Slow Oscillations as Potential Biomarker for Hypersomnolence. J Sleep Res 2025:e70059. [PMID: 40170232 DOI: 10.1111/jsr.70059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2024] [Revised: 02/21/2025] [Accepted: 03/24/2025] [Indexed: 04/03/2025]
Abstract
Research suggests that the spatial profile of slow wave activity (SWA) could be altered in hypersomnolence. Slow oscillations (SOs; 0.5-1.5 Hz), single waveform events contributing to SWA, can be labelled as Global, Frontal, or Local depending on their presentation on the scalp. We showed that SO space-time types differentiate in their amplitudes, coordination with sleep spindles, and propagation patterns. This study applies our data-driven analysis to the nocturnal sleep of adults with and without hypersomnolence and major depressive disorder (MDD) to explore the potential relevance of SO space-time patterns as hypersomnolence signatures in the sleep EEG. We leverage an existing dataset of nocturnal polysomnography with high-density EEG in 83 adults, organised in four groups depending on the presence/absence of hypersomnolence and on the presence/absence of MDD. Group comparisons were conducted considering either two groups (hypersomnolence status) or the four groups separately. Data shows enhanced Frontal SO activity compared with Global activity in hypersomnolence, with or without MDD, and a loss of Global SO amplitude at central regions in hypersomnolence without MDD compared to controls. As Global SOs travel fronto-parietally, we interpret these results as likely driven by a loss of coordination of Global SO activity in hypersomnolence without MDD, resulting in an overabundance of Frontal SOs. This study suggests that characteristics of Frontal SO and Global SOs may have the potential to differentiate individuals with hypersomnolence without MDD, and that the space-time organisation of SOs could be a mechanistically relevant indicator of changes in sleep brain dynamics related to hypersomnolence.
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Affiliation(s)
- Mahmoud Alipour
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio, USA
- The Ohio State University, College of Medicine, Columbus, Ohio, USA
| | - Joseph Rausch
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio, USA
- The Ohio State University, College of Medicine, Columbus, Ohio, USA
| | - Sara C Mednick
- Department of Cognitive Sciences, University of California, Irvine, California, USA
| | - Jesse D Cook
- Department of Psychiatry, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - David T Plante
- Department of Psychiatry, University of Wisconsin-Madison, School of Medicine and Public Health, Madison, Wisconsin, USA
| | - Paola Malerba
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio, USA
- The Ohio State University, College of Medicine, Columbus, Ohio, USA
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Alipour M, Seok S, Mednick SC, Malerba P. A classification-based generative approach to selective targeting of global slow oscillations during sleep. Front Hum Neurosci 2024; 18:1342975. [PMID: 38415278 PMCID: PMC10896842 DOI: 10.3389/fnhum.2024.1342975] [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: 11/22/2023] [Accepted: 01/30/2024] [Indexed: 02/29/2024] Open
Abstract
Background Given sleep's crucial role in health and cognition, numerous sleep-based brain interventions are being developed, aiming to enhance cognitive function, particularly memory consolidation, by improving sleep. Research has shown that Transcranial Alternating Current Stimulation (tACS) during sleep can enhance memory performance, especially when used in a closed-loop (cl-tACS) mode that coordinates with sleep slow oscillations (SOs, 0.5-1.5Hz). However, sleep tACS research is characterized by mixed results across individuals, which are often attributed to individual variability. Objective/Hypothesis This study targets a specific type of SOs, widespread on the electrode manifold in a short delay ("global SOs"), due to their close relationship with long-term memory consolidation. We propose a model-based approach to optimize cl-tACS paradigms, targeting global SOs not only by considering their temporal properties but also their spatial profile. Methods We introduce selective targeting of global SOs using a classification-based approach. We first estimate the current elicited by various stimulation paradigms, and optimize parameters to match currents found in natural sleep during a global SO. Then, we employ an ensemble classifier trained on sleep data to identify effective paradigms. Finally, the best stimulation protocol is determined based on classification performance. Results Our study introduces a model-driven cl-tACS approach that specifically targets global SOs, with the potential to extend to other brain dynamics. This method establishes a connection between brain dynamics and stimulation optimization. Conclusion Our research presents a novel approach to optimize cl-tACS during sleep, with a focus on targeting global SOs. This approach holds promise for improving cl-tACS not only for global SOs but also for other physiological events, benefiting both research and clinical applications in sleep and cognition.
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Affiliation(s)
- Mahmoud Alipour
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
- The Ohio State University School of Medicine, Columbus, OH, United States
| | - SangCheol Seok
- Center for Gene Therapy, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
| | - Sara C. Mednick
- Department of Cognitive Sciences, University of California, Irvine, Irvine CA, United States
| | - Paola Malerba
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
- The Ohio State University School of Medicine, Columbus, OH, United States
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Dehnavi F, Koo-Poeggel PC, Ghorbani M, Marshall L. Memory ability and retention performance relate differentially to sleep depth and spindle type. iScience 2023; 26:108154. [PMID: 37876817 PMCID: PMC10590735 DOI: 10.1016/j.isci.2023.108154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 08/09/2023] [Accepted: 10/03/2023] [Indexed: 10/26/2023] Open
Abstract
Temporal interactions between non-rapid eye movement (NREM) sleep rhythms especially the coupling between cortical slow oscillations (SO, ∼1 Hz) and thalamic spindles (∼12 Hz) have been proposed to contribute to multi-regional interactions crucial for memory processing and cognitive ability. We investigated relationships between NREM sleep depth, sleep spindles and SO-spindle coupling regarding memory ability and memory consolidation in healthy humans. Findings underscore the functional relevance of spindle dynamics (slow versus fast), SO-phase, and most importantly NREM sleep depth for cognitive processing. Cross-frequency coupling analyses demonstrated stronger precise temporal coordination of slow spindles to SO down-state in N2 for subjects with higher general memory ability. A GLM model underscored this relationship, and furthermore that fast spindle properties were predictive of overnight memory consolidation. Our results suggest cognitive fingerprints dependent on conjoint fine-tuned SO-spindle temporal coupling, spindle properties, and brain sleep state.
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Affiliation(s)
- Fereshteh Dehnavi
- Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran
- Center for International Scientific Studies & Collaborations (CISSC), Shahid Azodi Street, Karim-Khane Zand Boulevard, Tehran 15875-7788, Iran
| | - Ping Chai Koo-Poeggel
- Institute of Experimental and Clinical Pharmacology and Toxicology, University of Luebeck, Ratzeburger Allee 160, Bldg. 66, 23562 Luebeck, Germany
- Center for Brain, Behavior and Metabolism, University of Luebeck, 23562 Luebeck, Germany
| | - Maryam Ghorbani
- Department of Electrical Engineering, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran
- Rayan Center for Neuroscience and Behavior, Ferdowsi University of Mashhad, Mashhad 9177948974, Iran
- Center for International Scientific Studies & Collaborations (CISSC), Shahid Azodi Street, Karim-Khane Zand Boulevard, Tehran 15875-7788, Iran
| | - Lisa Marshall
- Institute of Experimental and Clinical Pharmacology and Toxicology, University of Luebeck, Ratzeburger Allee 160, Bldg. 66, 23562 Luebeck, Germany
- Center for Brain, Behavior and Metabolism, University of Luebeck, 23562 Luebeck, Germany
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Rizzo R, Wang JWJL, DePold Hohler A, Holsapple JW, Vaou OE, Ivanov PC. Dynamic networks of cortico-muscular interactions in sleep and neurodegenerative disorders. FRONTIERS IN NETWORK PHYSIOLOGY 2023; 3:1168677. [PMID: 37744179 PMCID: PMC10512188 DOI: 10.3389/fnetp.2023.1168677] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 08/09/2023] [Indexed: 09/26/2023]
Abstract
The brain plays central role in regulating physiological systems, including the skeleto-muscular and locomotor system. Studies of cortico-muscular coordination have primarily focused on associations between movement tasks and dynamics of specific brain waves. However, the brain-muscle functional networks of synchronous coordination among brain waves and muscle activity rhythms that underlie locomotor control remain unknown. Here we address the following fundamental questions: what are the structure and dynamics of cortico-muscular networks; whether specific brain waves are main network mediators in locomotor control; how the hierarchical network organization relates to distinct physiological states under autonomic regulation such as wake, sleep, sleep stages; and how network dynamics are altered with neurodegenerative disorders. We study the interactions between all physiologically relevant brain waves across cortical locations with distinct rhythms in leg and chin muscle activity in healthy and Parkinson's disease (PD) subjects. Utilizing Network Physiology framework and time delay stability approach, we find that 1) each physiological state is characterized by a unique network of cortico-muscular interactions with specific hierarchical organization and profile of links strength; 2) particular brain waves play role as main mediators in cortico-muscular interactions during each state; 3) PD leads to muscle-specific breakdown of cortico-muscular networks, altering the sleep-stage stratification pattern in network connectivity and links strength. In healthy subjects cortico-muscular networks exhibit a pronounced stratification with stronger links during wake and light sleep, and weaker links during REM and deep sleep. In contrast, network interactions reorganize in PD with decline in connectivity and links strength during wake and non-REM sleep, and increase during REM, leading to markedly different stratification with gradual decline in network links strength from wake to REM, light and deep sleep. Further, we find that wake and sleep stages are characterized by specific links strength profiles, which are altered with PD, indicating disruption in the synchronous activity and network communication among brain waves and muscle rhythms. Our findings demonstrate the presence of previously unrecognized functional networks and basic principles of brain control of locomotion, with potential clinical implications for novel network-based biomarkers for early detection of Parkinson's and neurodegenerative disorders, movement, and sleep disorders.
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Affiliation(s)
- Rossella Rizzo
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
- Department of Engineering, University of Palermo, Palermo, Italy
| | - Jilin W. J. L. Wang
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
| | - Anna DePold Hohler
- Department of Neurology, Steward St. Elizabeth’s Medical Center, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - James W. Holsapple
- Department of Neurosurgery, Boston University School of Medicine, Boston, MA, United States
| | - Okeanis E. Vaou
- Department of Neurology, Steward St. Elizabeth’s Medical Center, Boston, MA, United States
- Department of Neurology, Boston University School of Medicine, Boston, MA, United States
| | - Plamen Ch. Ivanov
- Keck Laboratory for Network Physiology, Department of Physics, Boston University, Boston, MA, United States
- Harvard Medical School and Division of Sleep Medicine, Brigham and Women Hospital, Boston, MA, United States
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Sofia, Bulgaria
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