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Schreiner T, Petzka M, Staudigl T, Staresina BP. Respiration modulates sleep oscillations and memory reactivation in humans. Nat Commun 2023; 14:8351. [PMID: 38110418 PMCID: PMC10728072 DOI: 10.1038/s41467-023-43450-5] [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: 04/04/2023] [Accepted: 11/09/2023] [Indexed: 12/20/2023] Open
Abstract
The beneficial effect of sleep on memory consolidation relies on the precise interplay of slow oscillations and spindles. However, whether these rhythms are orchestrated by an underlying pacemaker has remained elusive. Here, we tested the relationship between respiration, which has been shown to impact brain rhythms and cognition during wake, sleep-related oscillations and memory reactivation in humans. We re-analysed an existing dataset, where scalp electroencephalography and respiration were recorded throughout an experiment in which participants (N = 20) acquired associative memories before taking a nap. Our results reveal that respiration modulates the emergence of sleep oscillations. Specifically, slow oscillations, spindles as well as their interplay (i.e., slow-oscillation_spindle complexes) systematically increase towards inhalation peaks. Moreover, the strength of respiration - slow-oscillation_spindle coupling is linked to the extent of memory reactivation (i.e., classifier evidence in favour of the previously learned stimulus category) during slow-oscillation_spindles. Our results identify a clear association between respiration and memory consolidation in humans and highlight the role of brain-body interactions during sleep.
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Affiliation(s)
- Thomas Schreiner
- Department of Psychology, Ludwig-Maximilians-Universität München, München, Germany.
| | - Marit Petzka
- Max Planck Institute for Human Development, Berlin, Germany
- Institute of Psychology, University of Hamburg, Hamburg, Germany
| | - Tobias Staudigl
- Department of Psychology, Ludwig-Maximilians-Universität München, München, Germany
| | - 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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2
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Santos JL, Petsidou E, Saraogi P, Bartsch U, Gerber AP, Seibt J. Effect of Acute Enriched Environment Exposure on Brain Oscillations and Activation of the Translation Initiation Factor 4E-BPs at Synapses across Wakefulness and Sleep in Rats. Cells 2023; 12:2320. [PMID: 37759542 PMCID: PMC10528220 DOI: 10.3390/cells12182320] [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: 07/31/2023] [Revised: 09/15/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
Brain plasticity is induced by learning during wakefulness and is consolidated during sleep. But the molecular mechanisms involved are poorly understood and their relation to experience-dependent changes in brain activity remains to be clarified. Localised mRNA translation is important for the structural changes at synapses supporting brain plasticity consolidation. The translation mTOR pathway, via phosphorylation of 4E-BPs, is known to be activate during sleep and contributes to brain plasticity, but whether this activation is specific to synapses is not known. We investigated this question using acute exposure of rats to an enriched environment (EE). We measured brain activity with EEGs and 4E-BP phosphorylation at cortical and cerebellar synapses with Western blot analyses. Sleep significantly increased the conversion of 4E-BPs to their hyperphosphorylated forms at synapses, especially after EE exposure. EE exposure increased oscillations in the alpha band during active exploration and in the theta-to-beta (4-30 Hz) range, as well as spindle density, during NREM sleep. Theta activity during exploration and NREM spindle frequency predicted changes in 4E-BP hyperphosphorylation at synapses. Hence, our results suggest a functional link between EEG and molecular markers of plasticity across wakefulness and sleep.
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Affiliation(s)
- José Lucas Santos
- Surrey Sleep Research Centre, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XP, UK; (J.L.S.); (U.B.)
- Department of Microbial Sciences, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK;
- Department of Physiology, Development and Neuroscience, University of Cambridge, Physiological Laboratory, Downing Street, Cambridge CB2 3EG, UK
| | - Evlalia Petsidou
- Undergraduate Programme in Biological Science, University of Surrey, Guildford GU2 7XH, UK
- Postgraduate Programme in Neuroscience (MSc), Cyprus Institute of Neurology and Genetics, Iroon Avenue 6, Egkomi 2371, Cyprus
| | - Pallavi Saraogi
- Undergraduate Programme in Biological Science, University of Surrey, Guildford GU2 7XH, UK
| | - Ullrich Bartsch
- Surrey Sleep Research Centre, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XP, UK; (J.L.S.); (U.B.)
- UK Dementia Research Institute, Care Research & Technology Centre at Imperial College London and University of Surrey, Guildford GU2 7XH, UK
| | - André P. Gerber
- Department of Microbial Sciences, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XH, UK;
| | - Julie Seibt
- Surrey Sleep Research Centre, School of Biosciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford GU2 7XP, UK; (J.L.S.); (U.B.)
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3
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Miao X, Müller C, Lutz ND, Yang Q, Waszak F, Born J, Rauss K. Sleep consolidates stimulus-response learning. Learn Mem 2023; 30:175-184. [PMID: 37726140 PMCID: PMC10547380 DOI: 10.1101/lm.053753.123] [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: 02/21/2023] [Accepted: 05/15/2023] [Indexed: 09/21/2023]
Abstract
Performing a motor response to a sensory stimulus creates a memory trace whose behavioral correlates are classically investigated in terms of repetition priming effects. Such stimulus-response learning entails two types of associations that are partly independent: (1) an association between the stimulus and the motor response and (2) an association between the stimulus and the classification task in which it is encountered. Here, we tested whether sleep supports long-lasting stimulus-response learning on a task requiring participants (1) for establishing stimulus-classification associations to classify presented objects along two different dimensions ("size" and "mechanical") and (2) as motor response (action) to respond with either the left or right index finger. Moreover, we examined whether strengthening of stimulus-classification associations is preferentially linked to nonrapid eye movement (non-REM) sleep and strengthening of stimulus-action associations to REM sleep. We tested 48 healthy volunteers in a between-subjects design comparing postlearning retention periods of nighttime sleep versus daytime wakefulness. At postretention testing, we found that sleep supports consolidation of both stimulus-action and stimulus-classification associations, as indicated by increased reaction times in "switch conditions"; that is, when, at test, the acutely instructed classification task and/or correct motor response for a given stimulus differed from that during original learning. Polysomnographic recordings revealed that both kinds of associations were correlated with non-REM spindle activity. Our results do not support the view of differential roles for non-REM and REM sleep in the consolidation of stimulus-classification and stimulus-action associations, respectively.
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Affiliation(s)
- Xiu Miao
- Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls-Universität, Tübingen 72076, Germany
| | - Carolin Müller
- Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls-Universität, Tübingen 72076, Germany
| | - Nicolas D Lutz
- Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls-Universität, Tübingen 72076, Germany
- Institute of Medical Psychology, Ludwig-Maximilians-Universität, Munich 80336, Germany
| | - Qing Yang
- Université Paris Cité, Integrative Neuroscience and Cognition Center, UMR 8002, Centre National de la Recherche Scientifique, Paris 75006, France
| | - Florian Waszak
- Université Paris Cité, Integrative Neuroscience and Cognition Center, UMR 8002, Centre National de la Recherche Scientifique, Paris 75006, France
| | - Jan Born
- Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls-Universität, Tübingen 72076, Germany
- Center for Integrative Neuroscience, Eberhard-Karls-Universität, Tübingen 72076, Germany
| | - Karsten Rauss
- Institute of Medical Psychology and Behavioral Neurobiology, Eberhard-Karls-Universität, Tübingen 72076, Germany
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4
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Brodt S, Inostroza M, Niethard N, Born J. Sleep-A brain-state serving systems memory consolidation. Neuron 2023; 111:1050-1075. [PMID: 37023710 DOI: 10.1016/j.neuron.2023.03.005] [Citation(s) in RCA: 40] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/23/2023] [Accepted: 03/06/2023] [Indexed: 04/08/2023]
Abstract
Although long-term memory consolidation is supported by sleep, it is unclear how it differs from that during wakefulness. Our review, focusing on recent advances in the field, identifies the repeated replay of neuronal firing patterns as a basic mechanism triggering consolidation during sleep and wakefulness. During sleep, memory replay occurs during slow-wave sleep (SWS) in hippocampal assemblies together with ripples, thalamic spindles, neocortical slow oscillations, and noradrenergic activity. Here, hippocampal replay likely favors the transformation of hippocampus-dependent episodic memory into schema-like neocortical memory. REM sleep following SWS might balance local synaptic rescaling accompanying memory transformation with a sleep-dependent homeostatic process of global synaptic renormalization. Sleep-dependent memory transformation is intensified during early development despite the immaturity of the hippocampus. Overall, beyond its greater efficacy, sleep consolidation differs from wake consolidation mainly in that it is supported, rather than impaired, by spontaneous hippocampal replay activity possibly gating memory formation in neocortex.
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Affiliation(s)
- Svenja Brodt
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany; Max-Planck-Institute for Biological Cybernetics, Tübingen, Germany
| | - Marion Inostroza
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Niels Niethard
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany
| | - Jan Born
- Institute of Medical Psychology and Behavioral Neurobiology, University of Tübingen, Tübingen, Germany; Werner Reichert Center for Integrative Neuroscience, University of Tübingen, Tübingen, Germany.
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5
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Xu F, Zhao J, Liu M, Yu X, Wang C, Lou Y, Shi W, Liu Y, Gao L, Yang Q, Zhang B, Lu S, Tang J, Leng J. Exploration of sleep function connection and classification strategies based on sub-period sleep stages. Front Neurosci 2023; 16:1088116. [PMID: 36760796 PMCID: PMC9906994 DOI: 10.3389/fnins.2022.1088116] [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: 11/03/2022] [Accepted: 12/30/2022] [Indexed: 01/26/2023] Open
Abstract
Background As a medium for developing brain-computer interface systems, EEG signals are complex and difficult to identify due to their complexity, weakness, and differences between subjects. At present, most of the current research on sleep EEG signals are single-channel and dual-channel, ignoring the research on the relationship between different brain regions. Brain functional connectivity is considered to be closely related to brain activity and can be used to study the interaction relationship between brain areas. Methods Phase-locked value (PLV) is used to construct a functional connection network. The connection network is used to analyze the connection mechanism and brain interaction in different sleep stages. Firstly, the entire EEG signal is divided into multiple sub-periods. Secondly, Phase-locked value is used for feature extraction on the sub-periods. Thirdly, the PLV of multiple sub-periods is used for feature fusion. Fourthly, the classification performance optimization strategy is used to discuss the impact of different frequency bands on sleep stage classification performance and to find the optimal frequency band. Finally, the brain function network is constructed by using the average value of the fusion features to analyze the interaction of brain regions in different frequency bands during sleep stages. Results The experimental results have shown that when the number of sub-periods is 30, the α (8-13 Hz) frequency band has the best classification effect, The classification result after 10-fold cross-validation reaches 92.59%. Conclusion The proposed algorithm has good sleep staging performance, which can effectively promote the development and application of an EEG sleep staging system.
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Affiliation(s)
- Fangzhou Xu
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China,*Correspondence: Fangzhou Xu,
| | - Jinzhao Zhao
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Ming Liu
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Xin Yu
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Chongfeng Wang
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Yitai Lou
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Weiyou Shi
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Yanbing Liu
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Licai Gao
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Qingbo Yang
- School of Mathematics and Statistics, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China
| | - Baokun Zhang
- Department of Neurology, Shandong Institute of Neuroimmunology, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, The First Affliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Jinan, China
| | - Shanshan Lu
- Department of Neurology, Shandong Institute of Neuroimmunology, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, The First Affliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Jinan, China,Department of Neurology, Cheeloo College of Medicine, Shandong Qianfoshan Hospital, Shandong University, Jinan, Shandong, China,Shanshan Lu,
| | - Jiyou Tang
- Department of Neurology, Shandong Institute of Neuroimmunology, Shandong Key Laboratory of Rheumatic Disease and Translational Medicine, The First Affliated Hospital of Shandong First Medical University, Shandong Provincial Qianfoshan Hospital, Jinan, China,Department of Neurology, Cheeloo College of Medicine, Shandong Qianfoshan Hospital, Shandong University, Jinan, Shandong, China,Jiyou Tang,
| | - Jiancai Leng
- International School for Optoelectronic Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China,Jiancai Leng,
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Sleep Spindle Characteristics and Relationship with Memory Ability in Patients with Obstructive Sleep Apnea-Hypopnea Syndrome. J Clin Med 2023; 12:jcm12020634. [PMID: 36675563 PMCID: PMC9864739 DOI: 10.3390/jcm12020634] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/23/2022] [Accepted: 01/04/2023] [Indexed: 01/15/2023] Open
Abstract
Obstructive sleep apnea syndrome (OSAS) causes intermittent hypoxia and sleep disruption in the brain, resulting in cognitive dysfunction, but its pathogenesis is unclear. The sleep spindle wave is a transient neural event involved in sleep memory consolidation and synaptic plasticity. This study aimed to investigate the characteristics of sleep spindle activity and its relationship with memory ability in patients with OSAS. A total of 119 patients, who were divided into the OSAS group (n = 59, AHI ≥ 15) and control group (n = 60, AHI < 15) according to the Apnea Hypopnea Index (AHI), were enrolled and underwent polysomnography. Power spectral density (PSD) and omega complexity were used to analyze the characteristics of single and different brain regions of sleep spindles. Memory-related cognitive functions were assessed in all subjects, including logical memory, digit ordering, pattern recognition, spatial recognition and spatial working memory. The spindle PSD of the OSAS group was significantly slower than the control group, regardless of the slow, fast, or total spindle. The complexity of the spindles in the prefrontal and central region decreased significantly, whereas it increased in the occipital region. Sleep spindle PSD was positively correlated with logical memory and working memory. Spindle complexity was positively correlated with immediate logical and visual memory in the prefrontal region and positively correlated with immediate/delayed logical and working memory in the central region. In contrast, spindle complexity in the occipital region negatively correlated with delayed logical memory. Spindle hyperconnectivity in the prefrontal and central regions underlies declines in logical, visual and working memory and weak connections in the occipital spindles underlie the decline in delayed logical memory.
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7
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Muñoz-Torres Z, Corsi-Cabrera M, Velasco F, Velasco AL. Amygdala and hippocampus dialogue with neocortex during human sleep and wakefulness. Sleep 2023; 46:6702585. [PMID: 36124713 DOI: 10.1093/sleep/zsac224] [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: 01/28/2022] [Revised: 09/03/2022] [Indexed: 01/13/2023] Open
Abstract
ABSTRACT Previous studies have described synchronic electroencephalographic (EEG) patterns of the background activity that is characteristic of several vigilance states. STUDY OBJECTIVES To explore whether the background synchronous activity of the amygdala-hippocampal-neocortical circuit is modified during sleep in the delta, theta, alpha, sigma, beta, and gamma bands characteristic of each sleep state. METHODS By simultaneously recording intracranial and noninvasive scalp EEG (10-20 system) in epileptic patients who were candidates for neurosurgery, we explored synchronous activity among the amygdala, hippocampus, and neocortex during wakefulness (W), Non-Rapid Eye Movement (NREM), and Rapid-Eye Movement (REM) sleep. RESULTS Our findings reveal that hippocampal-cortical synchrony in the sleep spindle frequencies was spread across the cortex and was higher during NREM versus W and REM, whereas the amygdala showed punctual higher synchronization with the temporal lobe. Contrary to expectations, delta synchrony between the amygdala and frontal lobe and between the hippocampus and temporal lobe was higher during REM than NREM. Gamma and alpha showed higher synchrony between limbic structures and the neocortex during wakefulness versus sleep, while synchrony among deep structures showed a mixed pattern. On the one hand, amygdala-hippocampal synchrony resembled cortical activity (i.e. higher gamma and alpha synchrony in W); on the other, it showed its own pattern in slow frequency oscillations. CONCLUSIONS This is the first study to depict diverse patterns of synchronic interaction among the frequency bands during distinct vigilance states in a broad human brain circuit with direct anatomical and functional connections that play a crucial role in emotional processes and memory.
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Affiliation(s)
- Zeidy Muñoz-Torres
- Psychobiology and Neuroscience, Faculty of Psychology, Universidad Nacional Autónoma de México, Mexico, Mexico.,Neural Dynamics Group, Center for the Sciences of Complexity, Universidad Nacional Autónoma de México, Mexico, Mexico
| | - María Corsi-Cabrera
- Unit of Neurodevelopment, Institute of Neurobiology, Universidad Nacional Autónoma de México, Queretaro, Mexico.,Laboratory of Sleep, Faculty of Psychology, Universidad Nacional Autónoma de México, Mexico, Mexico
| | - Francisco Velasco
- Clinic of Epilepsy, Unit of Functional Neurosurgery, Stereotaxy and Radiosurgery, Hospital General de México, Mexico, Mexico
| | - Ana Luisa Velasco
- Clinic of Epilepsy, Unit of Functional Neurosurgery, Stereotaxy and Radiosurgery, Hospital General de México, Mexico, Mexico
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Liu L, Ren J, Li Z, Yang C. A review of MEG dynamic brain network research. Proc Inst Mech Eng H 2022; 236:763-774. [PMID: 35465768 DOI: 10.1177/09544119221092503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The dynamic description of neural networks has attracted the attention of researchers for dynamic networks may carry more information compared with resting-state networks. As a non-invasive electrophysiological data with high temporal and spatial resolution, magnetoencephalogram (MEG) can provide rich information for the analysis of dynamic functional brain networks. In this review, the development of MEG brain network was summarized. Several analysis methods such as sliding window, Hidden Markov model, and time-frequency based methods used in MEG dynamic brain network studies were discussed. Finally, the current research about multi-modal brain network analysis and their applications with MEG neurophysiology, which are prospected to be one of the research directions in the future, were concluded.
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Affiliation(s)
- Lu Liu
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
| | - Jiechuan Ren
- Department of Internal Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Zhimei Li
- Department of Internal Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Chunlan Yang
- Faculty of Environment and Life, Beijing University of Technology, Beijing, China
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9
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Yi C, Qiu Y, Chen W, Chen C, Wang Y, Li P, Yang L, Zhang X, Jiang L, Yao D, Li F, Xu P. Constructing Time-varying Directed EEG network by Multivariate Nonparametric Dynamical Granger Causality. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1412-1421. [PMID: 35576427 DOI: 10.1109/tnsre.2022.3175483] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Time-varying directed electroencephalography (EEG) network is the potential tool for studying the dynamical causality among brain areas at a millisecond level; which conduces to understanding how our brain effectively adapts to information processing, giving inspiration to causality- and brain-inspired machine learning. Currently, its construction still mainly relies on the parametric approach such as multivariate adaptive autoregressive (MVAAR), represented by the most widely used adaptive directed transfer function (ADTF). Restricted by the model assumption, the corresponding performance largely depends on the MVAAR modeling which usually encounters difficulty in fitting complex spectral features. In this study, we proposed to construct EEG directed network with multivariate nonparametric dynamical Granger causality (mndGC) method that infers the causality of a network, instead, in a data-driven way directly and therefore avoids the trap in the model-dependent parametric approach. Comparisons between mndGC and ADTF were conducted both with simulation and real data application. Simulation study demonstrated the superiority of mndGC both in noise resistance and capturing the instantaneous directed network changes. When applying to the real motor imagery (MI) data set, distinguishable network characters between left- and right-hand MI during different MI stages were better revealed by mndGC. Our study extends the nonparametric causality exploration and provides practical suggestions for the time-varying directed EEG network analysis.
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10
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Bastian L, Samanta A, Ribeiro de Paula D, Weber FD, Schoenfeld R, Dresler M, Genzel L. Spindle-slow oscillation coupling correlates with memory performance and connectivity changes in a hippocampal network after sleep. Hum Brain Mapp 2022; 43:3923-3943. [PMID: 35488512 PMCID: PMC9374888 DOI: 10.1002/hbm.25893] [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: 10/28/2021] [Revised: 02/28/2022] [Accepted: 04/06/2022] [Indexed: 11/10/2022] Open
Abstract
After experiences are encoded, post‐encoding reactivations during sleep have been proposed to mediate long‐term memory consolidation. Spindle–slow oscillation coupling during NREM sleep is a candidate mechanism through which a hippocampal‐cortical dialogue may strengthen a newly formed memory engram. Here, we investigated the role of fast spindle‐ and slow spindle–slow oscillation coupling in the consolidation of spatial memory in humans with a virtual watermaze task involving allocentric and egocentric learning strategies. Furthermore, we analyzed how resting‐state functional connectivity evolved across learning, consolidation, and retrieval of this task using a data‐driven approach. Our results show task‐related connectivity changes in the executive control network, the default mode network, and the hippocampal network at post‐task rest. The hippocampal network could further be divided into two subnetworks of which only one showed modulation by sleep. Decreased functional connectivity in this subnetwork was associated with higher spindle–slow oscillation coupling power, which was also related to better memory performance at test. Overall, this study contributes to a more holistic understanding of the functional resting‐state networks and the mechanisms during sleep associated to spatial memory consolidation.
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Affiliation(s)
- Lisa Bastian
- Donders Institute for Brain Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Anumita Samanta
- Donders Institute for Brain Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Demetrius Ribeiro de Paula
- Donders Institute for Brain Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Frederik D Weber
- Donders Institute for Brain Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | | | - Martin Dresler
- Donders Institute for Brain Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Lisa Genzel
- Donders Institute for Brain Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
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Hiraishi H, Ikeda T, Saito DN, Hasegawa C, Kitagawa S, Takahashi T, Kikuchi M, Ouchi Y. Regional and Temporal Differences in Brain Activity With Morally Good or Bad Judgments in Men: A Magnetoencephalography Study. Front Neurosci 2021; 15:596711. [PMID: 33911998 PMCID: PMC8072487 DOI: 10.3389/fnins.2021.596711] [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: 08/20/2020] [Accepted: 03/19/2021] [Indexed: 12/02/2022] Open
Abstract
Many neuroimaging studies on morality focus on functional brain areas that relate to moral judgment specifically in morally negative situations. To date, there have been few studies on differences in brain activity under conditions of being morally good and bad along a continuum. To explore not only the brain regions involved but also their functional connections during moral judgments, we used magnetoencephalography (MEG), which is superior to other imaging modalities for analyzing time-dependent brain activities; only men were recruited because sex differences might be a confounding factor. While analyses showed that general patterns of brain activation and connectivity were similar between morally good judgments (MGJs) and morally bad judgments (MBJs), activation in brain areas that subserve emotion and “theory of mind” on the right hemisphere was larger in MGJ than MBJ conditions. In the left local temporal region, the connectivity between brain areas related to emotion and reward/punishment was stronger in MBJ than MGJ conditions. The time-frequency analysis showed distinct laterality (left hemisphere dominant) occurring during early moral information processing in MBJ conditions compared to MGJ conditions and phase-dependent differences in the appearance of theta waves between MBJ and MGJ conditions. During MBJs, connections within the hemispheric regions were more robust than those between hemispheric regions. These results suggested that the local temporal region on the left hemisphere is more important in the execution of MBJs during early moral valence processing than in that with MGJs. Shorter neuronal connections within the hemisphere may allow to make MBJs punctual.
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Affiliation(s)
- Hirotoshi Hiraishi
- Department of Biofunctional Imaging, Preeminent Medical Photonics Education and Research Center, Hamamatsu University School of Medicine, Hamamatsu, Japan.,Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Takashi Ikeda
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan.,United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui, Japan
| | - Daisuke N Saito
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan.,Department of Psychology, Yasuda Women's University, Hiroshima, Japan
| | - Chiaki Hasegawa
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Sachiko Kitagawa
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Tetsuya Takahashi
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan
| | - Mitsuru Kikuchi
- Research Center for Child Mental Development, Kanazawa University, Kanazawa, Japan.,United Graduate School of Child Development, Osaka University, Kanazawa University, Hamamatsu University School of Medicine, Chiba University and University of Fukui, Fukui, Japan.,Department of Psychiatry and Behavioral Science, Kanazawa University, Kanazawa, Japan
| | - Yasuomi Ouchi
- Department of Biofunctional Imaging, Preeminent Medical Photonics Education and Research Center, Hamamatsu University School of Medicine, Hamamatsu, Japan
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