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Schreiner T, Griffiths BJ, Kutlu M, Vollmar C, Kaufmann E, Quach S, Remi J, Noachtar S, Staudigl T. Spindle-locked ripples mediate memory reactivation during human NREM sleep. Nat Commun 2024; 15:5249. [PMID: 38898100 DOI: 10.1038/s41467-024-49572-8] [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: 10/30/2023] [Accepted: 06/11/2024] [Indexed: 06/21/2024] Open
Abstract
Memory consolidation relies in part on the reactivation of previous experiences during sleep. The precise interplay of sleep-related oscillations (slow oscillations, spindles and ripples) is thought to coordinate the information flow between relevant brain areas, with ripples mediating memory reactivation. However, in humans empirical evidence for a role of ripples in memory reactivation is lacking. Here, we investigated the relevance of sleep oscillations and specifically ripples for memory reactivation during human sleep using targeted memory reactivation. Intracranial electrophysiology in epilepsy patients and scalp EEG in healthy participants revealed that elevated levels of slow oscillation - spindle activity coincided with the read-out of experimentally induced memory reactivation. Importantly, spindle-locked ripples recorded intracranially from the medial temporal lobe were found to be correlated with the identification of memory reactivation during non-rapid eye movement sleep. Our findings establish ripples as key-oscillation for sleep-related memory reactivation in humans and emphasize the importance of the coordinated interplay of the cardinal sleep oscillations.
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Affiliation(s)
- Thomas Schreiner
- Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Benjamin J Griffiths
- Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Merve Kutlu
- Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Christian Vollmar
- Epilepsy Center, Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Elisabeth Kaufmann
- Epilepsy Center, Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Stefanie Quach
- Department of Neurosurgery, University Hospital Munich, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Jan Remi
- Epilepsy Center, Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Soheyl Noachtar
- Epilepsy Center, Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Tobias Staudigl
- Department of Psychology, Ludwig-Maximilians-Universität München, Munich, Germany.
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2
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Zhong Z, Yan F, Xie C. Waking Up Brain with Electrical Stimulation to Boost Memory in Sleep: A Neuroscience Exploration. Neurosci Bull 2024; 40:852-854. [PMID: 38573557 PMCID: PMC11178686 DOI: 10.1007/s12264-024-01200-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 01/06/2024] [Indexed: 04/05/2024] Open
Affiliation(s)
- Zhe Zhong
- Department of Neurology, School of Medicine, Affiliated Zhongda Hospital, Southeast University, Nanjing, 210009, China
| | - Fuling Yan
- Department of Neurology, School of Medicine, Affiliated Zhongda Hospital, Southeast University, Nanjing, 210009, China
| | - Chunming Xie
- Department of Neurology, School of Medicine, Affiliated Zhongda Hospital, Southeast University, Nanjing, 210009, China.
- Institute of Neuropsychiatry, Affiliated Zhongda Hospital, Southeast University, Nanjing, 210009, China.
- The Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing, 210009, China.
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3
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Shin JD, Jadhav SP. Prefrontal cortical ripples mediate top-down suppression of hippocampal reactivation during sleep memory consolidation. Curr Biol 2024:S0960-9822(24)00616-X. [PMID: 38834064 DOI: 10.1016/j.cub.2024.05.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Revised: 04/17/2024] [Accepted: 05/09/2024] [Indexed: 06/06/2024]
Abstract
Consolidation of initially encoded hippocampal representations in the neocortex through reactivation is crucial for long-term memory formation and is facilitated by the coordination of hippocampal sharp-wave ripples (SWRs) with cortical slow and spindle oscillations during non-REM sleep. Recent evidence suggests that high-frequency cortical ripples can also coordinate with hippocampal SWRs in support of consolidation; however, the contribution of cortical ripples to reactivation remains unclear. We used high-density, continuous recordings in the hippocampus (area CA1) and prefrontal cortex (PFC) over the course of spatial learning and show that independent PFC ripples dissociated from SWRs are prevalent in NREM sleep and predominantly suppress hippocampal activity. PFC ripples paradoxically mediate top-down suppression of hippocampal reactivation rather than coordination, and this suppression is stronger for assemblies that are reactivated during coordinated CA1-PFC ripples for consolidation of recent experiences. Further, we show non-canonical, serial coordination of independent cortical ripples with slow and spindle oscillations, which are known signatures of memory consolidation. These results establish a role for prefrontal cortical ripples in top-down regulation of behaviorally relevant hippocampal representations during consolidation.
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Affiliation(s)
- Justin D Shin
- Neuroscience Program, Department of Psychology, and Volen National Center for Complex Systems, Brandeis University, 415 South Street, Waltham, MA 02453, USA
| | - Shantanu P Jadhav
- Neuroscience Program, Department of Psychology, and Volen National Center for Complex Systems, Brandeis University, 415 South Street, Waltham, MA 02453, USA.
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Hong J, Choi K, Fuccillo MV, Chung S, Weber F. Infralimbic activity during REM sleep facilitates fear extinction memory. Curr Biol 2024; 34:2247-2255.e5. [PMID: 38714199 PMCID: PMC11111341 DOI: 10.1016/j.cub.2024.04.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/03/2024] [Accepted: 04/08/2024] [Indexed: 05/09/2024]
Abstract
Rapid eye movement (REM) sleep is known to facilitate fear extinction and play a protective role against fearful memories.1,2 Consequently, disruption of REM sleep after a traumatic event may increase the risk for developing PTSD.3,4 However, the underlying mechanisms by which REM sleep promotes extinction of aversive memories remain largely unknown. The infralimbic cortex (IL) is a key brain structure for the consolidation of extinction memory.5 Using calcium imaging, we found in mice that most IL pyramidal neurons are intensively activated during REM sleep. Optogenetically suppressing the IL specifically during REM sleep within a 4-h window after auditory-cued fear conditioning impaired extinction memory consolidation. In contrast, REM-specific IL inhibition after extinction learning did not affect the extinction memory. Whole-cell patch-clamp recordings demonstrated that inactivating IL neurons during REM sleep depresses their excitability. Together, our findings suggest that REM sleep after fear conditioning facilitates fear extinction by enhancing IL excitability and highlight the importance of REM sleep in the aftermath of traumatic events for protecting against traumatic memories.
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Affiliation(s)
- Jiso Hong
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Chronobiology and Sleep Institute, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kyuhyun Choi
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marc V Fuccillo
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Shinjae Chung
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Chronobiology and Sleep Institute, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Franz Weber
- Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Chronobiology and Sleep Institute, University of Pennsylvania, Philadelphia, PA 19104, USA.
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5
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Yin Z, Yu H, Yuan T, Smyth C, Anjum MF, Zhu G, Ma R, Xu Y, An Q, Gan Y, Merk T, Qin G, Xie H, Zhang N, Wang C, Jiang Y, Meng F, Yang A, Neumann WJ, Starr P, Little S, Li L, Zhang J. Generalized sleep decoding with basal ganglia signals in multiple movement disorders. NPJ Digit Med 2024; 7:122. [PMID: 38729977 PMCID: PMC11087561 DOI: 10.1038/s41746-024-01115-7] [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: 12/23/2023] [Accepted: 04/23/2024] [Indexed: 05/12/2024] Open
Abstract
Sleep disturbances profoundly affect the quality of life in individuals with neurological disorders. Closed-loop deep brain stimulation (DBS) holds promise for alleviating sleep symptoms, however, this technique necessitates automated sleep stage decoding from intracranial signals. We leveraged overnight data from 121 patients with movement disorders (Parkinson's disease, Essential Tremor, Dystonia, Essential Tremor, Huntington's disease, and Tourette's syndrome) in whom synchronized polysomnograms and basal ganglia local field potentials were recorded, to develop a generalized, multi-class, sleep specific decoder - BGOOSE. This generalized model achieved 85% average accuracy across patients and across disease conditions, even in the presence of recordings from different basal ganglia targets. Furthermore, we also investigated the role of electrocorticography on decoding performances and proposed an optimal decoding map, which was shown to facilitate channel selection for optimal model performances. BGOOSE emerges as a powerful tool for generalized sleep decoding, offering exciting potentials for the precision stimulation delivery of DBS and better management of sleep disturbances in movement disorders.
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Affiliation(s)
- Zixiao Yin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Campus Mitte, Charite-Universitatsmedizin Berlin, Chariteplatz 1, 10117, Berlin, Germany.
| | - Huiling Yu
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, 100084, Beijing, China
| | - Tianshuo Yuan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Clay Smyth
- Department of Bioengineering, University of California, San Francisco, UCSF Byers Hall Box 2520, 1700 Fourth St Ste 203, San Francisco, CA, 94143, USA
| | - Md Fahim Anjum
- Department of Neurology, University of California, San Francisco, 1651 4th Street, San Francisco, CA, 94158, USA
| | - Guanyu Zhu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Campus Mitte, Charite-Universitatsmedizin Berlin, Chariteplatz 1, 10117, Berlin, Germany
| | - Ruoyu Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yichen Xu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Qi An
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yifei Gan
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Timon Merk
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Campus Mitte, Charite-Universitatsmedizin Berlin, Chariteplatz 1, 10117, Berlin, Germany
| | - Guofan Qin
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Hutao Xie
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Ning Zhang
- Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunxue Wang
- Department of Neuropsychiatry, Behavioral Neurology and Sleep Center, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Yin Jiang
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Fangang Meng
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Anchao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Campus Mitte, Charite-Universitatsmedizin Berlin, Chariteplatz 1, 10117, Berlin, Germany
| | - Philip Starr
- Department of Neurosurgery, University of California, San Francisco, Eighth Floor, 400 Parnassus Ave, San Francisco, CA, 94143, USA
| | - Simon Little
- Department of Neurology, University of California, San Francisco, 1651 4th Street, San Francisco, CA, 94158, USA.
| | - Luming Li
- National Engineering Research Center of Neuromodulation, School of Aerospace Engineering, Tsinghua University, 100084, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, 100084, Beijing, China
| | - Jianguo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
- Beijing Key Laboratory of Neurostimulation, Beijing, China.
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6
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Suárez-Grimalt R, Grunwald Kadow IC, Scheunemann L. An integrative sensor of body states: how the mushroom body modulates behavior depending on physiological context. Learn Mem 2024; 31:a053918. [PMID: 38876486 DOI: 10.1101/lm.053918.124] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Accepted: 04/08/2024] [Indexed: 06/16/2024]
Abstract
The brain constantly compares past and present experiences to predict the future, thereby enabling instantaneous and future behavioral adjustments. Integration of external information with the animal's current internal needs and behavioral state represents a key challenge of the nervous system. Recent advancements in dissecting the function of the Drosophila mushroom body (MB) at the single-cell level have uncovered its three-layered logic and parallel systems conveying positive and negative values during associative learning. This review explores a lesser-known role of the MB in detecting and integrating body states such as hunger, thirst, and sleep, ultimately modulating motivation and sensory-driven decisions based on the physiological state of the fly. State-dependent signals predominantly affect the activity of modulatory MB input neurons (dopaminergic, serotoninergic, and octopaminergic), but also induce plastic changes directly at the level of the MB intrinsic and output neurons. Thus, the MB emerges as a tightly regulated relay station in the insect brain, orchestrating neuroadaptations due to current internal and behavioral states leading to short- but also long-lasting changes in behavior. While these adaptations are crucial to ensure fitness and survival, recent findings also underscore how circuit motifs in the MB may reflect fundamental design principles that contribute to maladaptive behaviors such as addiction or depression-like symptoms.
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Affiliation(s)
- Raquel Suárez-Grimalt
- Institute for Biology/Genetics, Freie Universität Berlin, 14195 Berlin, Germany
- Institut für Neurophysiologie and NeuroCure Cluster of Excellence, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
| | | | - Lisa Scheunemann
- Institute for Biology/Genetics, Freie Universität Berlin, 14195 Berlin, Germany
- Institut für Neurophysiologie and NeuroCure Cluster of Excellence, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany
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7
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Yeung D, Talukder A, Shi M, Umbach DM, Li Y, Motsinger-Reif A, Fan Z, Li L. Differences in sleep spindle wave density between patients with diabetes mellitus and matched controls: implications for sensing and regulation of peripheral blood glucose. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.11.24305676. [PMID: 38645123 PMCID: PMC11030297 DOI: 10.1101/2024.04.11.24305676] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Background Brain waves during sleep are involved in sensing and regulating peripheral glucose level. Whether brain waves in patients with diabetes differ from those of healthy subjects is unknown. We examined the hypothesis that patients with diabetes have reduced sleep spindle waves, a form of brain wave implicated in periphery glucose regulation during sleep. Methods From a retrospective analysis of polysomnography (PSG) studies on patients who underwent sleep apnea evaluation, we identified 1,214 studies of patients with diabetes mellitus (>66% type 2) and included a sex- and age-matched control subject for each within the scope of our analysis. We similarly identified 376 patients with prediabetes and their matched controls. We extracted spindle characteristics from artifact-removed PSG electroencephalograms and other patient data from records. We used rank-based statistical methods to test hypotheses. We validated our finding on an external PSG dataset. Results Patients with diabetes mellitus exhibited on average about half the spindle density (median=0.38 spindles/min) during sleep as their matched control subjects (median=0.70 spindles/min) (P<2.2e-16). Compared to controls, spindle loss was more pronounced in female patients than in male patients in the frontal regions of the brain (P=0.04). Patients with prediabetes also exhibited signs of lower spindle density compared to matched controls (P=0.01-0.04). Conclusions Patients with diabetes have fewer spindle waves that are implicated in glucose regulation than matched controls during sleep. Besides offering a possible explanation for neurological complications from diabetes, our findings open the possibility that reversing/reducing spindle loss could improve the overall health of patients with diabetes mellitus.
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Affiliation(s)
- Deryck Yeung
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States
| | - Amlan Talukder
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States
| | - Min Shi
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States
| | - David M. Umbach
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States
| | - Yuanyuan Li
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States
| | - Alison Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States
| | - Zheng Fan
- Division of Sleep Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
- Department of Neurology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States
| | - Leping Li
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, United States
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8
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Wang M, Lassers SB, Vakilna YS, Mander BA, Tang WC, Brewer GJ. Spindle oscillations in communicating axons within a reconstituted hippocampal formation are strongest in CA3 without thalamus. Sci Rep 2024; 14:8384. [PMID: 38600114 PMCID: PMC11006914 DOI: 10.1038/s41598-024-58002-0] [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: 11/07/2023] [Accepted: 03/25/2024] [Indexed: 04/12/2024] Open
Abstract
Spindle-shaped waves of oscillations emerge in EEG scalp recordings during human and rodent non-REM sleep. The association of these 10-16 Hz oscillations with events during prior wakefulness suggests a role in memory consolidation. Human and rodent depth electrodes in the brain record strong spindles throughout the cortex and hippocampus, with possible origins in the thalamus. However, the source and targets of the spindle oscillations from the hippocampus are unclear. Here, we employed an in vitro reconstruction of four subregions of the hippocampal formation with separate microfluidic tunnels for single axon communication between subregions assembled on top of a microelectrode array. We recorded spontaneous 400-1000 ms long spindle waves at 10-16 Hz in single axons passing between subregions as well as from individual neurons in those subregions. Spindles were nested within slow waves. The highest amplitudes and most frequent occurrence suggest origins in CA3 neurons that send feed-forward axons into CA1 and feedback axons into DG. Spindles had 50-70% slower conduction velocities than spikes and were not phase-locked to spikes suggesting that spindle mechanisms are independent of action potentials. Therefore, consolidation of declarative-cognitive memories in the hippocampus may be separate from the more easily accessible consolidation of memories related to thalamic motor function.
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Affiliation(s)
- Mengke Wang
- Department of Biomedical Engineering, University of California, Irvine, CA, 92697, USA
| | - Samuel B Lassers
- Department of Biomedical Engineering, University of California, Irvine, CA, 92697, USA
| | - Yash S Vakilna
- Texas Institute of Restorative Neurotechnologies (TIRN), The University of Texas Health Science Center (UTHealth), Houston, TX, 77030, USA
| | - Bryce A Mander
- Center for Neurobiology of Learning and Memory and MIND Center, University of California, Irvine, CA, 92697, USA
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, 92697, USA
- Department of Psychiatry and Human Behavior, University of California, Irvine, CA, 92868, USA
| | - William C Tang
- Department of Biomedical Engineering, University of California, Irvine, CA, 92697, USA
| | - Gregory J Brewer
- Department of Biomedical Engineering, University of California, Irvine, CA, 92697, USA.
- Center for Neurobiology of Learning and Memory and MIND Center, University of California, Irvine, CA, 92697, USA.
- Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, CA, 92697, USA.
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9
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Yadav N, Toader A, Rajasethupathy P. Beyond hippocampus: Thalamic and prefrontal contributions to an evolving memory. Neuron 2024; 112:1045-1059. [PMID: 38272026 DOI: 10.1016/j.neuron.2023.12.021] [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: 08/04/2023] [Revised: 11/07/2023] [Accepted: 12/22/2023] [Indexed: 01/27/2024]
Abstract
The hippocampus has long been at the center of memory research, and rightfully so. However, with emerging technological capabilities, we can increasingly appreciate memory as a more dynamic and brain-wide process. In this perspective, our goal is to begin developing models to understand the gradual evolution, reorganization, and stabilization of memories across the brain after their initial formation in the hippocampus. By synthesizing studies across the rodent and human literature, we suggest that as memory representations initially form in hippocampus, parallel traces emerge in frontal cortex that cue memory recall, and as they mature, with sustained support initially from limbic then diencephalic then cortical circuits, they become progressively independent of hippocampus and dependent on a mature cortical representation. A key feature of this model is that, as time progresses, memory representations are passed on to distinct circuits with progressively longer time constants, providing the opportunity to filter, forget, update, or reorganize memories in the process of committing to long-term storage.
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Affiliation(s)
- Nakul Yadav
- Laboratory of Neural Dynamics & Cognition, The Rockefeller University, New York, NY, USA
| | - Andrew Toader
- Laboratory of Neural Dynamics & Cognition, The Rockefeller University, New York, NY, USA
| | - Priya Rajasethupathy
- Laboratory of Neural Dynamics & Cognition, The Rockefeller University, New York, NY, USA.
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10
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Staresina BP. Coupled sleep rhythms for memory consolidation. Trends Cogn Sci 2024; 28:339-351. [PMID: 38443198 DOI: 10.1016/j.tics.2024.02.002] [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: 10/11/2023] [Revised: 02/02/2024] [Accepted: 02/02/2024] [Indexed: 03/07/2024]
Abstract
How do passing moments turn into lasting memories? Sheltered from external tasks and distractions, sleep constitutes an optimal state for the brain to reprocess and consolidate previous experiences. Recent work suggests that consolidation is governed by the intricate interaction of slow oscillations (SOs), spindles, and ripples - electrophysiological sleep rhythms that orchestrate neuronal processing and communication within and across memory circuits. This review describes how sequential SO-spindle-ripple coupling provides a temporally and spatially fine-tuned mechanism to selectively strengthen target memories across hippocampal and cortical networks. Coupled sleep rhythms might be harnessed not only to enhance overnight memory retention, but also to combat memory decline associated with healthy ageing and neurodegenerative diseases.
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Affiliation(s)
- Bernhard P Staresina
- Department of Experimental Psychology, University of Oxford, Oxford, UK; Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK.
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11
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Slutsky I. Linking activity dyshomeostasis and sleep disturbances in Alzheimer disease. Nat Rev Neurosci 2024; 25:272-284. [PMID: 38374463 DOI: 10.1038/s41583-024-00797-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/30/2024] [Indexed: 02/21/2024]
Abstract
The presymptomatic phase of Alzheimer disease (AD) starts with the deposition of amyloid-β in the cortex and begins a decade or more before the emergence of cognitive decline. The trajectory towards dementia and neurodegeneration is shaped by the pathological load and the resilience of neural circuits to the effects of this pathology. In this Perspective, I focus on recent advances that have uncovered the vulnerability of neural circuits at early stages of AD to hyperexcitability, particularly when the brain is in a low-arousal states (such as sleep and anaesthesia). Notably, this hyperexcitability manifests before overt symptoms such as sleep and memory deficits. Using the principles of control theory, I analyse the bidirectional relationship between homeostasis of neuronal activity and sleep and propose that impaired activity homeostasis during sleep leads to hyperexcitability and subsequent sleep disturbances, whereas sleep disturbances mitigate hyperexcitability via negative feedback. Understanding the interplay among activity homeostasis, neuronal excitability and sleep is crucial for elucidating the mechanisms of vulnerability to and resilience against AD pathology and for identifying new therapeutic avenues.
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Affiliation(s)
- Inna Slutsky
- Department of Physiology and Pharmacology, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
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12
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Dadarlat MC, Sun YJ, Stryker MP. Activity-dependent recruitment of inhibition and excitation in the awake mammalian cortex during electrical stimulation. Neuron 2024; 112:821-834.e4. [PMID: 38134920 PMCID: PMC10949925 DOI: 10.1016/j.neuron.2023.11.022] [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: 11/17/2022] [Revised: 08/04/2023] [Accepted: 11/22/2023] [Indexed: 12/24/2023]
Abstract
Electrical stimulation is an effective tool for mapping and altering brain connectivity, with applications ranging from treating pharmacology-resistant neurological disorders to providing sensory feedback for neural prostheses. Paramount to the success of these applications is the ability to manipulate electrical currents to precisely control evoked neural activity patterns. However, little is known about stimulation-evoked responses in inhibitory neurons nor how stimulation-evoked activity patterns depend on ongoing neural activity. In this study, we used 2-photon imaging and cell-type specific labeling to measure single-cell responses of excitatory and inhibitory neurons to electrical stimuli in the visual cortex of awake mice. Our data revealed strong interactions between electrical stimulation and pre-stimulus activity of single neurons in awake animals and distinct recruitment and response patterns for excitatory and inhibitory neurons. This work demonstrates the importance of cell-type-specific labeling of neurons in future studies.
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Affiliation(s)
- Maria C Dadarlat
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158, USA; Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN 47906, USA.
| | - Yujiao Jennifer Sun
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158, USA; Institute of Ophthalmology, University College London, London EC1V 9EL, UK
| | - Michael P Stryker
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94158, USA
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13
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Navas-Olive A, Rubio A, Abbaspoor S, Hoffman KL, de la Prida LM. A machine learning toolbox for the analysis of sharp-wave ripples reveals common waveform features across species. Commun Biol 2024; 7:211. [PMID: 38438533 PMCID: PMC10912113 DOI: 10.1038/s42003-024-05871-w] [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: 07/02/2023] [Accepted: 01/29/2024] [Indexed: 03/06/2024] Open
Abstract
The study of sharp-wave ripples has advanced our understanding of memory function, and their alteration in neurological conditions such as epilepsy is considered a biomarker of dysfunction. Sharp-wave ripples exhibit diverse waveforms and properties that cannot be fully characterized by spectral methods alone. Here, we describe a toolbox of machine-learning models for automatic detection and analysis of these events. The machine-learning architectures, which resulted from a crowdsourced hackathon, are able to capture a wealth of ripple features recorded in the dorsal hippocampus of mice across awake and sleep conditions. When applied to data from the macaque hippocampus, these models are able to generalize detection and reveal shared properties across species. We hereby provide a user-friendly open-source toolbox for model use and extension, which can help to accelerate and standardize analysis of sharp-wave ripples, lowering the threshold for its adoption in biomedical applications.
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Affiliation(s)
| | | | - Saman Abbaspoor
- Psychological Sciences, Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Kari L Hoffman
- Psychological Sciences, Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Biomedical Engineering, Vanderbilt University, Nashville, TN, USA
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14
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Jacob LPL, Bailes SM, Williams SD, Stringer C, Lewis LD. Distributed fMRI dynamics predict distinct EEG rhythms across sleep and wakefulness. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.29.577429. [PMID: 38352426 PMCID: PMC10862763 DOI: 10.1101/2024.01.29.577429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The brain exhibits rich oscillatory dynamics that vary across tasks and states, such as the EEG oscillations that define sleep. These oscillations play critical roles in cognition and arousal, but the brainwide mechanisms underlying them are not yet described. Using simultaneous EEG and fast fMRI in subjects drifting between sleep and wakefulness, we developed a machine learning approach to investigate which brainwide fMRI dynamics predict alpha (8-12 Hz) and delta (1-4 Hz) rhythms. We predicted moment-by-moment EEG power from fMRI activity in held-out subjects, and found that information about alpha power was represented by a remarkably small set of regions, segregated in two distinct networks linked to arousal and visual systems. Conversely, delta rhythms were diffusely represented on a large spatial scale across the cortex. These results identify distributed networks that predict delta and alpha rhythms, and establish a computational framework for investigating fMRI brainwide dynamics underlying EEG oscillations.
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Affiliation(s)
- Leandro P L Jacob
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sydney M Bailes
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Boston University, Boston, MA, USA
| | - Stephanie D Williams
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Boston University, Boston, MA, USA
| | | | - Laura D Lewis
- Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston MA USA
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15
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Yu H, Kim W, Park DK, Phi JH, Lim BC, Chae JH, Kim SK, Kim KJ, Provenzano FA, Khodagholy D, Gelinas JN. Interaction of interictal epileptiform activity with sleep spindles is associated with cognitive deficits and adverse surgical outcome in pediatric focal epilepsy. Epilepsia 2024; 65:190-203. [PMID: 37983643 PMCID: PMC10873110 DOI: 10.1111/epi.17810] [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: 05/25/2023] [Revised: 10/20/2023] [Accepted: 10/20/2023] [Indexed: 11/22/2023]
Abstract
OBJECTIVE Temporal coordination between oscillations enables intercortical communication and is implicated in cognition. Focal epileptic activity can affect distributed neural networks and interfere with these interactions. Refractory pediatric epilepsies are often accompanied by substantial cognitive comorbidity, but mechanisms and predictors remain mostly unknown. Here, we investigate oscillatory coupling across large-scale networks in the developing brain. METHODS We analyzed large-scale intracranial electroencephalographic recordings in children with medically refractory epilepsy undergoing presurgical workup (n = 25, aged 3-21 years). Interictal epileptiform discharges (IEDs), pathologic high-frequency oscillations (HFOs), and sleep spindles were detected. Spatiotemporal metrics of oscillatory coupling were determined and correlated with age, cognitive function, and postsurgical outcome. RESULTS Children with epilepsy demonstrated significant temporal coupling of both IEDs and HFOs to sleep spindles in discrete brain regions. HFOs were associated with stronger coupling patterns than IEDs. These interactions involved tissue beyond the clinically identified epileptogenic zone and were ubiquitous across cortical regions. Increased spatial extent of coupling was most prominent in older children. Poor neurocognitive function was significantly correlated with high IED-spindle coupling strength and spatial extent; children with strong pathologic interactions additionally had decreased likelihood of postoperative seizure freedom. SIGNIFICANCE Our findings identify pathologic large-scale oscillatory coupling patterns in the immature brain. These results suggest that such intercortical interactions could predict risk for adverse neurocognitive and surgical outcomes, with the potential to serve as novel therapeutic targets to restore physiologic development.
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Affiliation(s)
- Han Yu
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Woojoong Kim
- Division of Pediatric Neurology, Department of Pediatrics, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - David K. Park
- Department of Biomedical Engineering, Columbia University, New York, NY, USA
| | - Ji Hoon Phi
- Division of Pediatric Neurosurgery, Department of Neurosurgery, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - Byung Chan Lim
- Division of Pediatric Neurology, Department of Pediatrics, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - Jong-Hee Chae
- Division of Pediatric Neurology, Department of Pediatrics, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - Seung-Ki Kim
- Division of Pediatric Neurosurgery, Department of Neurosurgery, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | - Ki Joong Kim
- Division of Pediatric Neurology, Department of Pediatrics, Pediatric Clinical Neuroscience Center, Seoul National University Children's Hospital, Seoul, South Korea
| | | | - Dion Khodagholy
- Department of Electrical Engineering, Columbia University, New York, NY, USA
| | - Jennifer N. Gelinas
- Departments of Neurology, Columbia University, New York, NY, USA
- Institute for Genomic Medicine, Columbia University Medical Center, New York, NY, USA
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16
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Pulver RL, Kronberg E, Medenblik LM, Kheyfets VO, Ramos AR, Holtzman DM, Morris JC, Toedebusch CD, Sillau SH, Bettcher BM, Lucey BP, McConnell BV. Mapping sleep's oscillatory events as a biomarker of Alzheimer's disease. Alzheimers Dement 2024; 20:301-315. [PMID: 37610059 PMCID: PMC10840635 DOI: 10.1002/alz.13420] [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: 04/26/2023] [Revised: 07/05/2023] [Accepted: 07/10/2023] [Indexed: 08/24/2023]
Abstract
INTRODUCTION Memory-associated neural circuits produce oscillatory events including theta bursts (TBs), sleep spindles (SPs), and slow waves (SWs) in sleep electroencephalography (EEG). Changes in the "coupling" of these events may indicate early Alzheimer's disease (AD) pathogenesis. METHODS We analyzed 205 aging adults using single-channel sleep EEG, cerebrospinal fluid (CSF) AD biomarkers, and Clinical Dementia Rating® (CDR®) scale. We mapped SW-TB and SW-SP neural circuit coupling precision to amyloid positivity, cognitive impairment, and CSF AD biomarkers. RESULTS Cognitive impairment correlated with lower TB spectral power in SW-TB coupling. Cognitively unimpaired, amyloid positive individuals demonstrated lower precision in SW-TB and SW-SP coupling compared to amyloid negative individuals. Significant biomarker correlations were found in oscillatory event coupling with CSF Aβ42 /Aβ40 , phosphorylated- tau181 , and total-tau. DISCUSSION Sleep-dependent memory processing integrity in neural circuits can be measured for both SW-TB and SW-SP coupling. This breakdown associates with amyloid positivity, increased AD pathology, and cognitive impairment. HIGHLIGHTS At-home sleep EEG is a potential biomarker of neural circuits linked to memory. Circuit precision is associated with amyloid positivity in asymptomatic aging adults. Levels of CSF amyloid and tau also correlate with circuit precision in sleep EEG. Theta burst EEG power is decreased in very early mild cognitive impairment. This technique may enable inexpensive wearable EEGs for monitoring brain health.
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Affiliation(s)
- Rachelle L. Pulver
- Department of NeurologyUniversity of Colorado School of MedicineAuroraColoradoUSA
- University of Colorado Alzheimer's and Cognition CenterUniversity of Colorado School of MedicineAuroraColoradoUSA
| | - Eugene Kronberg
- Department of NeurologyUniversity of Colorado School of MedicineAuroraColoradoUSA
| | - Lindsey M. Medenblik
- Department of NeurologyUniversity of Colorado School of MedicineAuroraColoradoUSA
- University of Colorado Alzheimer's and Cognition CenterUniversity of Colorado School of MedicineAuroraColoradoUSA
| | - Vitaly O. Kheyfets
- Department of Pediatric Critical Care MedicineUniversity of Colorado School of MedicineAuroraColoradoUSA
| | - Alberto R. Ramos
- Department of NeurologyUniversity of Miami Miller School of MedicineMiamiFloridaUSA
| | - David M. Holtzman
- Department of NeurologyWashington University School of MedicineSt LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt LouisMissouriUSA
| | - John C. Morris
- Department of NeurologyWashington University School of MedicineSt LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt LouisMissouriUSA
| | | | - Stefan H Sillau
- Department of NeurologyUniversity of Colorado School of MedicineAuroraColoradoUSA
- University of Colorado Alzheimer's and Cognition CenterUniversity of Colorado School of MedicineAuroraColoradoUSA
| | - Brianne M. Bettcher
- Department of NeurologyUniversity of Colorado School of MedicineAuroraColoradoUSA
- University of Colorado Alzheimer's and Cognition CenterUniversity of Colorado School of MedicineAuroraColoradoUSA
| | - Brendan P. Lucey
- Department of NeurologyWashington University School of MedicineSt LouisMissouriUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt LouisMissouriUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt LouisMissouriUSA
| | - Brice V. McConnell
- Department of NeurologyUniversity of Colorado School of MedicineAuroraColoradoUSA
- University of Colorado Alzheimer's and Cognition CenterUniversity of Colorado School of MedicineAuroraColoradoUSA
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Denis D, Cairney SA. Neural reactivation during human sleep. Emerg Top Life Sci 2023; 7:487-498. [PMID: 38054531 PMCID: PMC10754334 DOI: 10.1042/etls20230109] [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: 09/05/2023] [Revised: 11/20/2023] [Accepted: 11/23/2023] [Indexed: 12/07/2023]
Abstract
Sleep promotes memory consolidation: the process by which newly acquired memories are stabilised, strengthened, and integrated into long-term storage. Pioneering research in rodents has revealed that memory reactivation in sleep is a primary mechanism underpinning sleep's beneficial effect on memory. In this review, we consider evidence for memory reactivation processes occurring in human sleep. Converging lines of research support the view that memory reactivation occurs during human sleep, and is functionally relevant for consolidation. Electrophysiology studies have shown that memory reactivation is tightly coupled to the cardinal neural oscillations of non-rapid eye movement sleep, namely slow oscillation-spindle events. In addition, functional imaging studies have found that brain regions recruited during learning become reactivated during post-learning sleep. In sum, the current evidence paints a strong case for a mechanistic role of neural reactivation in promoting memory consolidation during human sleep.
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Affiliation(s)
- Dan Denis
- Department of Psychology, University of York, York YO10 5DD, U.K
| | - Scott A. Cairney
- Department of Psychology, University of York, York YO10 5DD, U.K
- York Biomedical Research Institute, University of York, York YO10 5DD, U.K
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18
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Shin JD, Jadhav SP. Cortical ripples mediate top-down suppression of hippocampal reactivation during sleep memory consolidation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.12.571373. [PMID: 38168420 PMCID: PMC10760112 DOI: 10.1101/2023.12.12.571373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Consolidation of initially encoded hippocampal representations in the neocortex through reactivation is crucial for long-term memory formation, and is facilitated by the coordination of hippocampal sharp-wave ripples (SWRs) with cortical oscillations during non-REM sleep. However, the contribution of high-frequency cortical ripples to consolidation is still unclear. We used continuous recordings in the hippocampus and prefrontal cortex (PFC) over the course of spatial learning and show that independent PFC ripples, when dissociated from SWRs, predominantly suppress hippocampal activity in non-REM sleep. PFC ripples paradoxically mediate top-down suppression of hippocampal reactivation, which is inversely related to reactivation strength during coordinated CA1-PFC ripples. Further, we show non-canonical, serial coordination of ripples with cortical slow and spindle oscillations. These results establish a role for cortical ripples in regulating consolidation.
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Affiliation(s)
- Justin D. Shin
- Neuroscience Program, Department of Psychology, and Volen National Center for Complex Systems, Brandeis University, Waltham, MA 02453, USA
| | - Shantanu P. Jadhav
- Neuroscience Program, Department of Psychology, and Volen National Center for Complex Systems, Brandeis University, Waltham, MA 02453, USA
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Salgado-Puga K, Rothschild G. Exposure to sounds during sleep impairs hippocampal sharp wave ripples and memory consolidation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.22.568283. [PMID: 38045371 PMCID: PMC10690295 DOI: 10.1101/2023.11.22.568283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Sleep is critical for the consolidation of recent experiences into long-term memories. As a key underlying neuronal mechanism, hippocampal sharp-wave ripples (SWRs) occurring during sleep define periods of hippocampal reactivation of recent experiences and have been causally linked with memory consolidation. Hippocampal SWR-dependent memory consolidation during sleep is often referred to as occurring during an "offline" state, dedicated to processing internally generated neural activity patterns rather than external stimuli. However, the brain is not fully disconnected from the environment during sleep. In particular, sounds heard during sleep are processed by a highly active auditory system which projects to brain regions in the medial temporal lobe, reflecting an anatomical pathway for sound modulation of hippocampal activity. While neural processing of salient sounds during sleep, such as those of a predator or an offspring, is evolutionarily adaptive, whether ongoing processing of environmental sounds during sleep interferes with SWR-dependent memory consolidation remains unknown. To address this question, we used a closed-loop system to deliver non-waking sound stimuli during or following SWRs in sleeping rats. We found that exposure to sounds during sleep suppressed the ripple power and reduced the rate of SWRs. Furthermore, sounds delivered during SWRs (On-SWR) suppressed ripple power significantly more than sounds delivered 2 seconds after SWRs (Off-SWR). Next, we tested the influence of sound presentation during sleep on memory consolidation. To this end, SWR-triggered sounds were applied during sleep sessions following learning of a conditioned place preference paradigm, in which rats learned a place-reward association. We found that On-SWR sound pairing during post-learning sleep induced a complete abolishment of memory retention 24 h following learning, while leaving memory retention immediately following sleep intact. In contrast, Off-SWR pairing weakened memory 24 h following learning as well as immediately following learning. Notably, On-SWR pairing induced a significantly larger impairment in memory 24 h after learning as compared to Off-SWR pairing. Together, these findings suggest that sounds heard during sleep suppress SWRs and memory consolidation, and that the magnitude of these effects are dependent on sound-SWR timing. These results suggest that exposure to environmental sounds during sleep may pose a risk for memory consolidation processes.
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Lemus HN, Sarkis RA. Interictal epileptiform discharges in Alzheimer's disease: prevalence, relevance, and controversies. Front Neurol 2023; 14:1261136. [PMID: 37808503 PMCID: PMC10551146 DOI: 10.3389/fneur.2023.1261136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 09/08/2023] [Indexed: 10/10/2023] Open
Abstract
Alzheimer's disease (AD) is the most common type of dementia and remains an incurable, progressive disease with limited disease-modifying interventions available. In patients with AD, interictal epileptiform discharges (IEDs) have been identified in up to 54% of combined cohorts of mild cognitive impairment (MCI) or mild dementia and are a marker of a more aggressive disease course. Studies assessing the role of IEDs in AD are limited by the lack of standardization in the definition of IEDs or the different neurophysiologic techniques used to capture them. IEDs are an appealing treatment target given the availability of EEG and anti-seizure medications. There remains uncertainty regarding when to treat IEDs, the optimal drug and dose for treatment, and the impact of treatment on disease course. This review covers the state of knowledge of the field of IEDs in AD, and the steps needed to move the field forward.
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Affiliation(s)
| | - Rani A. Sarkis
- Department of Neurology, Brigham and Women’s Hospital, Boston, MA, United States
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21
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Staresina BP, Niediek J, Borger V, Surges R, Mormann F. How coupled slow oscillations, spindles and ripples coordinate neuronal processing and communication during human sleep. Nat Neurosci 2023; 26:1429-1437. [PMID: 37429914 PMCID: PMC10400429 DOI: 10.1038/s41593-023-01381-w] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 06/13/2023] [Indexed: 07/12/2023]
Abstract
Learning and plasticity rely on fine-tuned regulation of neuronal circuits during offline periods. An unresolved puzzle is how the sleeping brain, in the absence of external stimulation or conscious effort, coordinates neuronal firing rates (FRs) and communication within and across circuits to support synaptic and systems consolidation. Using intracranial electroencephalography combined with multiunit activity recordings from the human hippocampus and surrounding medial temporal lobe (MTL) areas, we show that, governed by slow oscillation (SO) up-states, sleep spindles set a timeframe for ripples to occur. This sequential coupling leads to a stepwise increase in (1) neuronal FRs, (2) short-latency cross-correlations among local neuronal assemblies and (3) cross-regional MTL interactions. Triggered by SOs and spindles, ripples thus establish optimal conditions for spike-timing-dependent plasticity and systems consolidation. These results unveil how the sequential coupling of specific sleep rhythms orchestrates neuronal processing and communication during human sleep.
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Affiliation(s)
- Bernhard P Staresina
- Department of Experimental Psychology, University of Oxford, Oxford, UK.
- Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK.
| | - Johannes Niediek
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
- Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Valeri Borger
- Department of Neurosurgery, University of Bonn Medical Center, Bonn, Germany
| | - Rainer Surges
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
| | - Florian Mormann
- Department of Epileptology, University of Bonn Medical Center, Bonn, Germany
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Navas-Olive A, Rubio A, Abbaspoor S, Hoffman KL, de la Prida LM. A machine learning toolbox for the analysis of sharp-wave ripples reveal common features across species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.02.547382. [PMID: 37461661 PMCID: PMC10349962 DOI: 10.1101/2023.07.02.547382] [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: 07/24/2023]
Abstract
The study of sharp-wave ripples (SWRs) has advanced our understanding of memory function, and their alteration in neurological conditions such as epilepsy and Alzheimer's disease is considered a biomarker of dysfunction. SWRs exhibit diverse waveforms and properties that cannot be fully characterized by spectral methods alone. Here, we describe a toolbox of machine learning (ML) models for automatic detection and analysis of SWRs. The ML architectures, which resulted from a crowdsourced hackathon, are able to capture a wealth of SWR features recorded in the dorsal hippocampus of mice. When applied to data from the macaque hippocampus, these models were able to generalize detection and revealed shared SWR properties across species. We hereby provide a user-friendly open-source toolbox for model use and extension, which can help to accelerate and standardize SWR research, lowering the threshold for its adoption in biomedical applications.
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Affiliation(s)
| | | | - Saman Abbaspoor
- Psychological Sciences, Vanderbilt Brain Institute, Vanderbilt University, USA
| | - Kari L. Hoffman
- Psychological Sciences, Vanderbilt Brain Institute, Vanderbilt University, USA
- Biomedical Engineering, Vanderbilt University, USA
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