1
|
Mograss M, Frimpong E, Vilcourt F, Chouchou F, Zvionow T, Dang-Vu TT. The effects of acute exercise and a nap on heart rate variability and memory in young sedentary adults. Psychophysiology 2024; 61:e14454. [PMID: 37855092 DOI: 10.1111/psyp.14454] [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: 05/04/2023] [Revised: 08/29/2023] [Accepted: 09/20/2023] [Indexed: 10/20/2023]
Abstract
Recent evidence suggests that the autonomic nervous system can contribute to memory consolidation during sleep. Whether fluctuations in cardiac autonomic activity during sleep following physical exercise contribute to the process of memory consolidation has not been studied. We assessed the effects of a non-rapid eye movement (NREM) nap following acute exercise on cardiac autonomic regulation assessed with heart rate variability (HRV) to examine if HRV influences memory processes. Fifty-six (59% female) healthy young adults (23.14 ± 3.74 years) were randomly allocated to either the exercise plus nap (ExNap, n = 27) or nap alone (NoExNap, n = 29) groups. The ExNap group performed a 40-minute moderate-intensity cycling, while the NoExNap group was sedentary prior to learning 45 neutral pictures for a later test. Subsequently, participants underwent a 60-minute NREM nap while measuring EKG, followed by a visual recognition test. Our results indicated that heart rate did not significantly differ between the groups (p = .243), whereas vagally mediated HRV indices were lower in the ExNap group compared to the NoExNap group (p < .05). There were no significant differences in sleep variables between the groups (p > .05). Recognition accuracy was significantly higher in the ExNap group than in the NoExNap group (p = .027). In addition, the recognition accuracy of the ExNap group was negatively associated with vagally mediated HRV (p < .05). Pre-nap acute exercise appears to attenuate parasympathetic activity and to alter the relationship between memory and cardiac autonomic activity.
Collapse
Affiliation(s)
- Melodee Mograss
- Sleep, Cognition and Neuroimaging Laboratory, Concordia University, Montreal, Quebec, Canada
- Department of Health, Kinesiology & Applied Physiology, Concordia University, Montreal, Quebec, Canada
- Department of Psychology, Concordia University, Montreal, Quebec, Canada
- PERFORM Centre, Concordia University, Montreal, Quebec, Canada
| | - Emmanuel Frimpong
- Sleep, Cognition and Neuroimaging Laboratory, Concordia University, Montreal, Quebec, Canada
- Department of Health, Kinesiology & Applied Physiology, Concordia University, Montreal, Quebec, Canada
- PERFORM Centre, Concordia University, Montreal, Quebec, Canada
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, Quebec, Canada
| | - Franck Vilcourt
- IRISSE Laboratory (EA4075), UFR SHE, University of La Réunion, Le Tampon, France
| | - Florian Chouchou
- IRISSE Laboratory (EA4075), UFR SHE, University of La Réunion, Le Tampon, France
| | - Tehila Zvionow
- Sleep, Cognition and Neuroimaging Laboratory, Concordia University, Montreal, Quebec, Canada
- Department of Health, Kinesiology & Applied Physiology, Concordia University, Montreal, Quebec, Canada
| | - Thien Thanh Dang-Vu
- Sleep, Cognition and Neuroimaging Laboratory, Concordia University, Montreal, Quebec, Canada
- Department of Health, Kinesiology & Applied Physiology, Concordia University, Montreal, Quebec, Canada
- PERFORM Centre, Concordia University, Montreal, Quebec, Canada
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Montreal, Quebec, Canada
| |
Collapse
|
2
|
Fan Z, Suzuki Y, Jiang L, Okabe S, Honda S, Endo J, Watanabe T, Abe T. Peripheral blood flow estimated by laser doppler flowmetry provides additional information about sleep state beyond that provided by pulse rate variability. Front Physiol 2023; 14:1040425. [PMID: 36776965 PMCID: PMC9908953 DOI: 10.3389/fphys.2023.1040425] [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: 09/21/2022] [Accepted: 01/13/2023] [Indexed: 01/28/2023] Open
Abstract
Pulse rate variability (PRV), derived from Laser Doppler flowmetry (LDF) or photoplethysmography, has recently become widely used for sleep state assessment, although it cannot identify all the sleep stages. Peripheral blood flow (BF), also estimated by LDF, may be modulated by sleep stages; however, few studies have explored its potential for assessing sleep state. Thus, we aimed to investigate whether peripheral BF could provide information about sleep stages, and thus improve sleep state assessment. We performed electrocardiography and simultaneously recorded BF signals by LDF from the right-index finger and ear concha of 45 healthy participants (13 women; mean age, 22.5 ± 3.4 years) during one night of polysomnographic recording. Time- and frequency-domain parameters of peripheral BF, and time-domain, frequency-domain, and non-linear indices of PRV and heart rate variability (HRV) were calculated. Finger-BF parameters in the time and frequency domains provided information about different sleep stages, some of which (such as the difference between N1 and rapid eye movement sleep) were not revealed by finger-PRV. In addition, finger-PRV patterns and HRV patterns were similar for most parameters. Further, both finger- and ear-BF results showed 0.2-0.3 Hz oscillations that varied with sleep stages, with a significant increase in N3, suggesting a modulation of respiration within this frequency band. These results showed that peripheral BF could provide information for different sleep stages, some of which was complementary to the information provided by PRV. Furthermore, the combination of peripheral BF and PRV may be more advantageous than HRV alone in assessing sleep states and related autonomic nervous activity.
Collapse
Affiliation(s)
- Zhiwei Fan
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Japan,The Japan Society for the Promotion of Science (JSPS) Foreign Researcher, Tokyo, Japan
| | - Yoko Suzuki
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Japan
| | - Like Jiang
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Japan,Graduate School of Comprehensive Human Science, University of Tsukuba, Tsukuba, Japan
| | - Satomi Okabe
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Japan,Graduate School of Comprehensive Human Science, University of Tsukuba, Tsukuba, Japan
| | | | | | | | - Takashi Abe
- International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Japan,*Correspondence: Takashi Abe,
| |
Collapse
|
3
|
Chen PC, Zhang J, Thayer JF, Mednick SC. Understanding the roles of central and autonomic activity during sleep in the improvement of working memory and episodic memory. Proc Natl Acad Sci U S A 2022; 119:e2123417119. [PMID: 36279428 PMCID: PMC9636982 DOI: 10.1073/pnas.2123417119] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
The last decade has seen significant progress in identifying sleep mechanisms that support cognition. Most of these studies focus on the link between electrophysiological events of the central nervous system during sleep and improvements in different cognitive domains, while the dynamic shifts of the autonomic nervous system across sleep have been largely overlooked. Recent studies, however, have identified significant contributions of autonomic inputs during sleep to cognition. Yet, there remain considerable gaps in understanding how central and autonomic systems work together during sleep to facilitate cognitive improvement. In this article we examine the evidence for the independent and interactive roles of central and autonomic activities during sleep and wake in cognitive processing. We specifically focus on the prefrontal-subcortical structures supporting working memory and mechanisms underlying the formation of hippocampal-dependent episodic memory. Our Slow Oscillation Switch Model identifies separate and competing underlying mechanisms supporting the two memory domains at the synaptic, systems, and behavioral levels. We propose that sleep is a competitive arena in which both memory domains vie for limited resources, experimentally demonstrated when boosting one system leads to a functional trade-off in electrophysiological and behavioral outcomes. As these findings inevitably lead to further questions, we suggest areas of future research to better understand how the brain and body interact to support a wide range of cognitive domains during a single sleep episode.
Collapse
Affiliation(s)
- Pin-Chun Chen
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA 19104
| | - Jing Zhang
- Department of Cognitive Sciences, University of California, Irvine, CA 92697
| | - Julian F. Thayer
- Department of Psychological Sciences, University of California, Irvine, CA 92697
| | - Sara C. Mednick
- Department of Cognitive Sciences, University of California, Irvine, CA 92697
| |
Collapse
|
4
|
Seok SC, McDevitt E, Mednick SC, Malerba P. Global and non-Global slow oscillations differentiate in their depth profiles. FRONTIERS IN NETWORK PHYSIOLOGY 2022; 2:947618. [PMID: 36926094 PMCID: PMC10013040 DOI: 10.3389/fnetp.2022.947618] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 10/10/2022] [Indexed: 03/18/2023]
Abstract
Sleep slow oscillations (SOs, 0.5-1.5 Hz) are thought to organize activity across cortical and subcortical structures, leading to selective synaptic changes that mediate consolidation of recent memories. Currently, the specific mechanism that allows for this selectively coherent activation across brain regions is not understood. Our previous research has shown that SOs can be classified on the scalp as Global, Local or Frontal, where Global SOs are found in most electrodes within a short time delay and gate long-range information flow during NREM sleep. The functional significance of space-time profiles of SOs hinges on testing if these differential SOs scalp profiles are mirrored by differential depth structure of SOs in the brain. In this study, we built an analytical framework to allow for the characterization of SO depth profiles in space-time across cortical and sub-cortical regions. To test if the two SO types could be differentiated in their cortical-subcortical activity, we trained 30 machine learning classification algorithms to distinguish Global and non-Global SOs within each individual, and repeated this analysis for light (Stage 2, S2) and deep (slow wave sleep, SWS) NREM stages separately. Multiple algorithms reached high performance across all participants, in particular algorithms based on k-nearest neighbors classification principles. Univariate feature ranking and selection showed that the most differentiating features for Global vs. non-Global SOs appeared around the trough of the SO, and in regions including cortex, thalamus, caudate nucleus, and brainstem. Results also indicated that differentiation during S2 required an extended network of current from cortical-subcortical regions, including all regions found in SWS and other basal ganglia regions, and amygdala and hippocampus, suggesting a potential functional differentiation in the role of Global SOs in S2 vs. SWS. We interpret our results as supporting the potential functional difference of Global and non-Global SOs in sleep dynamics.
Collapse
Affiliation(s)
- Sang-Cheol Seok
- Battelle Center for Mathematical Medicine, Nationwide Children’s Hospital, Columbus, OH, United States
| | | | - Sara C. Mednick
- Department of Cognitive Sciences, University of California, Irvine, Irvine, CA, United States
| | - Paola Malerba
- Battelle Center for Mathematical Medicine, Nationwide Children’s Hospital, Columbus, OH, United States
- Center for Biobehavioral Health, Abigail Wexner Research Institute, Nationwide Children’s Hospital, Columbus, OH, United States
- School of Medicine, The Ohio State University, Columbus, OH, United States
| |
Collapse
|
5
|
Koo-Poeggel P, Neuwerk S, Petersen E, Grasshoff J, Mölle M, Martinetz T, Marshall L. Closed-loop acoustic stimulation during an afternoon nap to modulate subsequent encoding. J Sleep Res 2022; 31:e13734. [PMID: 36123957 DOI: 10.1111/jsr.13734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 11/27/2022]
Abstract
Sleep is able to contribute not only to memory consolidation, but also to post-sleep learning. The notion exists that either synaptic downscaling or another process during sleep increase post-sleep learning capacity. A correlation between augmentation of the sleep slow oscillation and hippocampal activation at encoding support the contribution of sleep to encoding of declarative memories. In the present study, the effect of closed-loop acoustic stimulation during an afternoon nap on post-sleep encoding of two verbal (word pairs, verbal learning and memory test) and non-verbal (figural pairs) tasks and on electroencephalogram during sleep and learning were investigated in young healthy adults (N = 16). Closed-loop acoustic stimulation enhanced slow oscillatory and spindle activity, but did not affect encoding at the group level. Subgroup analyses and comparisons with similar studies lead us to the tentative conclusion that further parameters such as time of day and subjects' cognitive ability influenced responses to closed-loop acoustic stimulation.
Collapse
Affiliation(s)
- Ping Koo-Poeggel
- Center of Brain, Behavior and Metabolism, University of Luebeck, Luebeck, Germany.,Institute for Experimental and Clinical Pharmacology and Toxicology, University of Luebeck, Luebeck, Germany
| | - Soé Neuwerk
- Institute for Experimental and Clinical Pharmacology and Toxicology, University of Luebeck, Luebeck, Germany
| | - Eike Petersen
- Institute for Electrical and Engineering in Medicine, University of Luebeck, Luebeck, Germany.,DTU Compute, Technical University of Denmark, Denmark
| | - Jan Grasshoff
- Fraunhofer IMTE, Fraunhofer Research Institution for Individualized and Cell-Based Medical Engineering, Lübeck, Germany
| | - Matthias Mölle
- Center of Brain, Behavior and Metabolism, University of Luebeck, Luebeck, Germany
| | - Thomas Martinetz
- Institute for Neuro- and Bioinformatics, University of Luebeck, Luebeck, Germany
| | - Lisa Marshall
- Center of Brain, Behavior and Metabolism, University of Luebeck, Luebeck, Germany.,Institute for Experimental and Clinical Pharmacology and Toxicology, University of Luebeck, Luebeck, Germany
| |
Collapse
|
6
|
Liu H, Yu X, Wang G, Han Y, Wang W. Effects of 24-h acute total sleep deprivation on physiological coupling in healthy young adults. Front Neurosci 2022; 16:952329. [PMID: 36161147 PMCID: PMC9493191 DOI: 10.3389/fnins.2022.952329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Accepted: 08/22/2022] [Indexed: 11/15/2022] Open
Abstract
Sleep deprivation is associated with dysregulation of the autonomic nervous system, adverse cardiovascular events, cognitive and complex motor performance impairment. Less is known about the effects of acute total sleep deprivation (ATSD) on physiological coupling. We aimed to determine the effects of 24-h ATSD on the physiological coupling between complex subsystems by evaluating the cardiorespiratory, cardiovascular and cortico-cardiac interactions. This study enrolled 38 young healthy participants aged 23.2 ± 2.4 years. Multiple synchronous physiological signals including electrocardiography, photoplethysmography, bio-electrical impedance, electroencephalography, and continuous hemodynamic data, were performed over a baseline night after regular sleep and after a night with 24-h ATSD in the supine position. The magnitude squared coherence, phase synchronization index, and heartbeat evoked potential amplitudes, were obtained from 10-min synchronous physiological recordings to estimate the coupling strength between two time series. Parameters of hemodynamic characteristics and heart rate variability were also calculated to quantify autonomic regulation. Results indicated that the magnitude squared coherence (0.38 ± 0.17 vs. 0.29 ± 0.12, p = 0.015) between respiration and heart rate variability along with the magnitude squared coherence (0.36 ± 0.18 vs. 0.27 ± 0.13, p = 0.012) between respiration and pulse transit time were significantly decreased after 24-h ATSD. There were no significant differences (all p > 0.05) in phase synchronization indices, heartbeat evoked potential amplitudes as well as other analyzed measurements between baseline and 24-h ATSD states. We conclude that exposure to 24-h ATSD appears to weaken the cardiorespiratory and respiratory-cardiovascular coupling strength of young healthy adults. These findings suggest that physiological coupling analysis may serve as a complementary approach for characterizing and understanding the complex effects of sleep deprivation.
Collapse
Affiliation(s)
- Hongyun Liu
- Medical Innovation Research Division, Research Center for Biomedical Engineering, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
- *Correspondence: Hongyun Liu,
| | - Xiaohua Yu
- Medical Innovation Research Division, Research Center for Biomedical Engineering, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
| | - Guojing Wang
- Medical Innovation Research Division, Research Center for Biomedical Engineering, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
| | - Yi Han
- Medical Innovation Research Division, Research Center for Biomedical Engineering, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
| | - Weidong Wang
- Medical Innovation Research Division, Research Center for Biomedical Engineering, Chinese PLA General Hospital, Beijing, China
- Key Laboratory of Biomedical Engineering and Translational Medicine, Ministry of Industry and Information Technology, Beijing, China
- Weidong Wang,
| |
Collapse
|
7
|
Autonomic Central Coupling during Daytime Sleep Differs between Older and Younger People. Neurobiol Learn Mem 2022; 193:107646. [PMID: 35671980 DOI: 10.1016/j.nlm.2022.107646] [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: 06/26/2021] [Revised: 04/12/2022] [Accepted: 05/28/2022] [Indexed: 11/24/2022]
Abstract
Decreased functioning in the elderly is mirrored by independent changes in central and autonomic nervous systems. Additionally, recent work suggests that the coupling of these systems may also serve an important role. In young adults, Autonomic and Central Events (ACEs), measured in the temporal coincidence of heart rate bursts (HRBs) and increased slow-wave-activity (SWA, 0.5-1Hz) and sigma activity (12-15Hz), followed by parasympathetic surge (RRHF) during non-rapid eye movement (NREM) sleep, predicted cognitive improvements. However, ACEs have not been examined in the elderly. Thus, the current study compared ACEs during wake and daytime sleep in older and younger adults and examined associations with working memory improvement before and after a nap. Compared to youngers, older adults showed lower amplitude of ACEs during NREM sleep, but not during wake. Furthermore, while younger adults demonstrated a parasympathetic surge after HRBs, older adults showed an earlier rise and longer maintenance of the RRHF. Taken together, our results demonstrate that autonomic-central coupling declines with age. Pathological aging implicates independent roles for decreased autonomic and central nervous system functioning, the current findings suggest that the coupling of these systems may also deserve attention.
Collapse
|
8
|
Simon KC, Whitehurst LN, Zhang J, Mednick SC. Zolpidem Maintains Memories for Negative Emotions Across a Night of Sleep. AFFECTIVE SCIENCE 2022; 3:389-399. [PMID: 35791418 PMCID: PMC9249708 DOI: 10.1007/s42761-021-00079-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 09/01/2021] [Indexed: 11/27/2022]
Abstract
Zolpidem, a common medication for sleep complaints, also shows secondary, unexpected memory benefits. We previously found that zolpidem prior to a nap enhanced negative, highly arousing picture memory. As zolpidem is typically administered at night, how it affects overnight emotional memory processing is relevant. We used a double-blind, placebo-controlled, within-subject, cross-over design to investigate if zolpidem boosted negative compared to neutral picture memory. Subjects learned both pictures sets in the morning. That evening, subjects were administered zolpidem or placebo and slept in the lab. Recognition was tested that evening and the following morning. We found that zolpidem maintained negative picture memory compared to forgetting in the placebo condition. Furthermore, zolpidem increased slow-wave sleep time, decreased rapid eye movement sleep time, and increased the fast spindle range in NREM. Our results suggest that zolpidem may enhance negative memory longevity and salience. These findings raise concerns for zolpidem administration to certain clinical populations.
Collapse
Affiliation(s)
- Katharine C. Simon
- Department of Cognitive Science, University of California, Irvine, 2201 Social & Behavioral Sciences Gateway, Irvine, CA 92697 USA
| | | | - Jing Zhang
- Department of Cognitive Science, University of California, Irvine, 2201 Social & Behavioral Sciences Gateway, Irvine, CA 92697 USA
| | - Sara C. Mednick
- Department of Cognitive Science, University of California, Irvine, 2201 Social & Behavioral Sciences Gateway, Irvine, CA 92697 USA
| |
Collapse
|
9
|
Cardiac sympathetic-vagal activity initiates a functional brain-body response to emotional arousal. Proc Natl Acad Sci U S A 2022; 119:e2119599119. [PMID: 35588453 PMCID: PMC9173754 DOI: 10.1073/pnas.2119599119] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023] Open
Abstract
We investigate the temporal dynamics of brain and cardiac activities in healthy subjects who underwent an emotional elicitation through videos. We demonstrate that, within the first few seconds, emotional stimuli modulate heartbeat activity, which in turn stimulates an emotion intensity (arousal)–specific cortical response. The emotional processing is then sustained by a bidirectional brain–heart interplay, where the perceived arousal level modulates the amplitude of ascending heart-to-brain neural information flow. These findings may constitute fundamental knowledge linking neurophysiology and psychiatric disorders, including the link between depressive symptoms and cardiovascular disorders. A century-long debate on bodily states and emotions persists. While the involvement of bodily activity in emotion physiology is widely recognized, the specificity and causal role of such activity related to brain dynamics has not yet been demonstrated. We hypothesize that the peripheral neural control on cardiovascular activity prompts and sustains brain dynamics during an emotional experience, so these afferent inputs are processed by the brain by triggering a concurrent efferent information transfer to the body. To this end, we investigated the functional brain–heart interplay under emotion elicitation in publicly available data from 62 healthy subjects using a computational model based on synthetic data generation of electroencephalography and electrocardiography signals. Our findings show that sympathovagal activity plays a leading and causal role in initiating the emotional response, in which ascending modulations from vagal activity precede neural dynamics and correlate to the reported level of arousal. The subsequent dynamic interplay observed between the central and autonomic nervous systems sustains the processing of emotional arousal. These findings should be particularly revealing for the psychophysiology and neuroscience of emotions.
Collapse
|
10
|
Whitehurst LN, Subramoniam A, Krystal A, Prather AA. Links between the brain and body during sleep: implications for memory processing. Trends Neurosci 2022; 45:212-223. [PMID: 35074220 DOI: 10.1016/j.tins.2021.12.007] [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: 08/09/2021] [Revised: 11/30/2021] [Accepted: 12/21/2021] [Indexed: 10/19/2022]
Abstract
Sleep is intimately related to memory processes. The established view is that the transformation of experiences into long-term memories is linked to sleep-related CNS function. However, there is increasing evidence that the autonomic nervous system (ANS), long recognized to modulate cognition during waking, can impact memory processing during sleep. Here, we review human research that examines the role of autonomic activity and sleep in memory formation. We argue that autonomic activity during sleep may set the stage for the CNS dynamics associated with sleep and memory stability and integration. Further, we consider how the link between ANS activity and polysomnographic markers of sleep may help elucidate both healthy and pathological cognitive aging in humans.
Collapse
Affiliation(s)
| | | | - Andrew Krystal
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| | - Aric A Prather
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
| |
Collapse
|
11
|
Ghorbani S, Golkashani HA, Chee NIYN, Teo TB, Dicom AR, Yilmaz G, Leong RLF, Ong JL, Chee MWL. Multi-Night at-Home Evaluation of Improved Sleep Detection and Classification with a Memory-Enhanced Consumer Sleep Tracker. Nat Sci Sleep 2022; 14:645-660. [PMID: 35444483 PMCID: PMC9015046 DOI: 10.2147/nss.s359789] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 03/31/2022] [Indexed: 12/13/2022] Open
Abstract
PURPOSE To evaluate the benefits of applying an improved sleep detection and staging algorithm on minimally processed multi-sensor wearable data collected from older generation hardware. PATIENTS AND METHODS 58 healthy, East Asian adults aged 23-69 years (M = 37.10, SD = 13.03, 32 males), each underwent 3 nights of PSG at home, wearing 2nd Generation Oura Rings equipped with additional memory to store raw data from accelerometer, infra-red photoplethysmography and temperature sensors. 2-stage and 4-stage sleep classifications using a new machine-learning algorithm (Gen3) trained on a diverse and independent dataset were compared to the existing consumer algorithm (Gen2) for whole-night and epoch-by-epoch metrics. RESULTS Gen 3 outperformed its predecessor with a mean (SD) accuracy of 92.6% (0.04), sensitivity of 94.9% (0.03), and specificity of 78.5% (0.11); corresponding to a 3%, 2.8% and 6.2% improvement from Gen2 across the three nights, with Cohen's d values >0.39, t values >2.69, and p values <0.01. Notably, Gen 3 showed robust performance comparable to PSG in its assessment of sleep latency, light sleep, rapid eye movement (REM), and wake after sleep onset (WASO) duration. Participants <40 years of age benefited more from the upgrade with less measurement bias for total sleep time (TST), WASO, light sleep and sleep efficiency compared to those ≥40 years. Males showed greater improvements on TST and REM sleep measurement bias compared to females, while females benefitted more for deep sleep measures compared to males. CONCLUSION These results affirm the benefits of applying machine learning and a diverse training dataset to improve sleep measurement of a consumer wearable device. Importantly, collecting raw data with appropriate hardware allows for future advancements in algorithm development or sleep physiology to be retrospectively applied to enhance the value of longitudinal sleep studies.
Collapse
Affiliation(s)
- Shohreh Ghorbani
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Hosein Aghayan Golkashani
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Nicholas I Y N Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Teck Boon Teo
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Andrew Roshan Dicom
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Gizem Yilmaz
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ruth L F Leong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Ju Lynn Ong
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Michael W L Chee
- Centre for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| |
Collapse
|
12
|
Abstract
The spontaneous dynamics of the brain modulate its function from moment to moment, shaping neural computation and cognition. Functional MRI (fMRI), while classically used as a tool for spatial localization, is increasingly being used to identify the temporal dynamics of brain activity. fMRI analyses focused on the temporal domain have revealed important new information about the dynamics underlying states such as arousal, attention, and sleep. Dense temporal sampling – either by using fast fMRI acquisition, or multiple repeated scan sessions within individuals – can further enrich the information present in these studies. This review focuses on recent developments in using fMRI to identify dynamics across brain states, particularly vigilance and sleep states, and the potential for highly temporally sampled fMRI to answer these questions.
Collapse
Affiliation(s)
- Zinong Yang
- Graduate Program in Neuroscience, Boston University, Boston MA, United States
| | - Laura D Lewis
- Department of Biomedical Engineering, Boston University, Boston MA, United States.,Center for Systems Neuroscience, Boston University, Boston MA, United States
| |
Collapse
|
13
|
Mikutta C, Wenke M, Spiegelhalder K, Hertenstein E, Maier JG, Schneider CL, Fehér K, Koenig J, Altorfer A, Riemann D, Nissen C, Feige B. Co-ordination of brain and heart oscillations during non-rapid eye movement sleep. J Sleep Res 2021; 31:e13466. [PMID: 34467582 PMCID: PMC9285890 DOI: 10.1111/jsr.13466] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 05/26/2021] [Accepted: 07/23/2021] [Indexed: 12/25/2022]
Abstract
Oscillatory activities of the brain and heart show a strong variation across wakefulness and sleep. Separate lines of research indicate that non‐rapid eye movement (NREM) sleep is characterised by electroencephalographic slow oscillations (SO), sleep spindles, and phase–amplitude coupling of these oscillations (SO–spindle coupling), as well as an increase in high‐frequency heart rate variability (HF‐HRV), reflecting enhanced parasympathetic activity. The present study aimed to investigate further the potential coordination between brain and heart oscillations during NREM sleep. Data were derived from one sleep laboratory night with polysomnographic monitoring in 45 healthy participants (22 male, 23 female; mean age 37 years). The associations between the strength (modulation index [MI]) and phase direction of SO–spindle coupling (circular measure) and HF‐HRV during NREM sleep were investigated using linear modelling. First, a significant SO–spindle coupling (MI) was observed for all participants during NREM sleep, with spindle peaks preferentially occurring during the SO upstate (phase direction). Second, linear model analyses of NREM sleep showed a significant relationship between the MI and HF‐HRV (F = 20.1, r2 = 0.30, p < 0.001) and a tentative circular‐linear correlation between phase direction and HF‐HRV (F = 3.07, r2 = 0.12, p = 0.056). We demonstrated a co‐ordination between SO–spindle phase–amplitude coupling and HF‐HRV during NREM sleep, presumably related to parallel central nervous and peripheral vegetative arousal systems regulation. Further investigating the fine‐graded co‐ordination of brain and heart oscillations might improve our understanding of the links between sleep and cardiovascular health.
Collapse
Affiliation(s)
- Christian Mikutta
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland.,Privatklinik Meiringen, Meiringen, Switzerland
| | - Marion Wenke
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Kai Spiegelhalder
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Elisabeth Hertenstein
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Jonathan G Maier
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Carlotta L Schneider
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Kristoffer Fehér
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Julian Koenig
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | - Andreas Altorfer
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland
| | - Dieter Riemann
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Christoph Nissen
- University Hospital of Psychiatry and Psychotherapy, University of Bern, Switzerland.,Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Bernd Feige
- Department of Psychiatry and Psychotherapy, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| |
Collapse
|
14
|
Farhadian N, Khazaie H, Nami M, Khazaie S. The role of daytime napping in declarative memory performance: a systematic review. Sleep Med 2021; 84:134-141. [PMID: 34148000 DOI: 10.1016/j.sleep.2021.05.019] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Revised: 04/25/2021] [Accepted: 05/20/2021] [Indexed: 10/21/2022]
Abstract
Sleep plays an important role in stabilizing and reinforcing memory of newly acquired information. Like nocturnal sleep, a daytime nap is shown to effectively contribute to memory processing. However, studies are often focused on nocturnal sleep. This review has aimed at systematically compiling the results of studies which have examined the effects of napping on declarative memory performance in healthy adults. Such studies have focused on different aspects of memory reinforcement following a diurnal nap including the involved mechanisms in memory reconsolidation, type of declarative tasks, cross-gender differences, the role of age, duration of nap and its delayed onset. One of the reviewed studies reported that even as short as 6 min of napping exerts a positive effect on memory function. Evidence from these studies indicates hippocampal-dependent enhancement of the learned information. Diurnal naps predominantly include non-rapid eye movement sleep with slow waves yielding potential effects on declarative memory. Evidence has shown that the empowered learning and retrieval depends upon spindle density during the nap. Moreover, the role of coordinated autonomic and central events in enhancing declarative memory has also been reported. Slow waves and sleep spindles are known to fuel declarative memory function during the NREM-2 (N2) stage of sleep.
Collapse
Affiliation(s)
- Negin Farhadian
- Substance Abuse Prevention Research Center, Health Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran; Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Habibolah Khazaie
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mohammad Nami
- Department of Neuroscience, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran; Neuroscience Center, INDICASAT, Panama City, Republic of Panama; Society for Brain Mapping and Therapeutics and Brain Mapping Foundation, Los Angeles, CA, USA
| | - Sepideh Khazaie
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran; Student Research Committee, University of Medical Sciences, Kermanshah, Iran.
| |
Collapse
|
15
|
Simon KC, Malerba P, Nakra N, Harrison A, Mednick SC, Nagel M. Slow oscillation density and amplitude decrease across development in pediatric Duchenne and Becker muscular dystrophy. Sleep 2021; 44:5986496. [PMID: 33202016 DOI: 10.1093/sleep/zsaa240] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2020] [Revised: 10/21/2020] [Indexed: 11/14/2022] Open
Abstract
STUDY OBJECTIVES From childhood through adolescence, brain rhythms during non-rapid eye movement (NREM) sleep show dramatic development that mirror underlying brain maturation. For example, the function and characteristics of slow oscillations (SOs, <1 Hz) in healthy children are linked to brain development, motor skill, and cognition. However, little is known of possible changes in pediatric populations with neurologic abnormalities. METHODS We measured slow oscillations in 28 Duchenne and Becker muscular dystrophy male patients from age 4 to 20 years old during overnight in-lab clinical sleep studies. We compared our pediatric patients by age to evaluate the developmental changes of SOs from childhood to early and late adolescence. RESULTS Consistent with the current neuro- and physically typical literature, we found greater slow oscillation density (count of SOs per minute of each sleep stage) in NREM N3 than N2, and significantly greater slow oscillation density in frontal compared to central and occipital regions. However, separating patients into age-defined groups (child, early adolescent, and late adolescent) revealed a significant age effect, with a specific decline in the rate and amplitude of SOs. CONCLUSIONS We found that with age, pediatric patients with Duchenne muscular dystrophy show a significant decline in slow oscillation density. Given the role that slow oscillations play in memory formation and retention, it is critical to developmentally characterize these brain rhythms in medically complex populations. Our work converges with previous pediatric sleep literature that promotes the use of sleep electroencephalographic markers as prognostic tools and identifies potential targets to promote our patients' quality of life.
Collapse
Affiliation(s)
- Katharine C Simon
- Cognitive Science Department, University of California, Irvine, Irvine, CA
| | - Paola Malerba
- Battelle Center for Mathematical Medicine, Nationwide's Children Hospital, Columbus, OH
| | - Neal Nakra
- Pulmonology Department, Children's Hospital of Orange County, Orange, CA
| | - Amy Harrison
- Pulmonology Department, Children's Hospital of Orange County, Orange, CA
| | - Sara C Mednick
- Cognitive Science Department, University of California, Irvine, Irvine, CA
| | - Marni Nagel
- Pulmonology Department, Children's Hospital of Orange County, Orange, CA.,Psychology Department, Children's Hospital of Orange County, Orange, CA
| |
Collapse
|
16
|
Zhang J, Yetton B, Whitehurst LN, Naji M, Mednick SC. The effect of zolpidem on memory consolidation over a night of sleep. Sleep 2021; 43:5824815. [PMID: 32330272 DOI: 10.1093/sleep/zsaa084] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 04/17/2020] [Indexed: 11/13/2022] Open
Abstract
STUDY OBJECTIVES Nonrapid eye movement sleep boosts hippocampus-dependent, long-term memory formation more so than wake. Studies have pointed to several electrophysiological events that likely play a role in this process, including thalamocortical sleep spindles (12-15 Hz). However, interventional studies that directly probe the causal role of spindles in consolidation are scarce. Previous studies have used zolpidem, a GABA-A agonist, to increase sleep spindles during a daytime nap and promote hippocampal-dependent episodic memory. The current study investigated the effect of zolpidem on nighttime sleep and overnight improvement of episodic memories. METHODS We used a double-blind, placebo-controlled within-subject design to test the a priori hypothesis that zolpidem would lead to increased memory performance on a word-paired associates task by boosting spindle activity. We also explored the impact of zolpidem across a range of other spectral sleep features, including slow oscillations (0-1 Hz), delta (1-4 Hz), theta (4-8 Hz), sigma (12-15 Hz), as well as spindle-SO coupling. RESULTS We showed greater memory improvement after a night of sleep with zolpidem, compared to placebo, replicating a prior nap study. Additionally, zolpidem increased sigma power, decreased theta and delta power, and altered the phase angle of spindle-SO coupling, compared to placebo. Spindle density, theta power, and spindle-SO coupling were associated with next-day memory performance. CONCLUSIONS These results are consistent with the hypothesis that sleep, specifically the timing and amount of sleep spindles, plays a causal role in the long-term formation of episodic memories. Furthermore, our results emphasize the role of nonrapid eye movement theta activity in human memory consolidation.
Collapse
Affiliation(s)
- Jing Zhang
- Department of Cognitive Sciences, University of California, Irvine
| | - Ben Yetton
- Department of Cognitive Sciences, University of California, Irvine
| | | | - Mohsen Naji
- Department of Medicine, University of California, San Diego
| | - Sara C Mednick
- Department of Cognitive Sciences, University of California, Irvine
| |
Collapse
|
17
|
Huang MX, Huang CW, Harrington DL, Robb-Swan A, Angeles-Quinto A, Nichols S, Huang JW, Le L, Rimmele C, Matthews S, Drake A, Song T, Ji Z, Cheng CK, Shen Q, Foote E, Lerman I, Yurgil KA, Hansen HB, Naviaux RK, Dynes R, Baker DG, Lee RR. Resting-state magnetoencephalography source magnitude imaging with deep-learning neural network for classification of symptomatic combat-related mild traumatic brain injury. Hum Brain Mapp 2021; 42:1987-2004. [PMID: 33449442 PMCID: PMC8046098 DOI: 10.1002/hbm.25340] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2020] [Revised: 11/16/2020] [Accepted: 12/23/2020] [Indexed: 12/20/2022] Open
Abstract
Combat‐related mild traumatic brain injury (cmTBI) is a leading cause of sustained physical, cognitive, emotional, and behavioral disabilities in Veterans and active‐duty military personnel. Accurate diagnosis of cmTBI is challenging since the symptom spectrum is broad and conventional neuroimaging techniques are insensitive to the underlying neuropathology. The present study developed a novel deep‐learning neural network method, 3D‐MEGNET, and applied it to resting‐state magnetoencephalography (rs‐MEG) source‐magnitude imaging data from 59 symptomatic cmTBI individuals and 42 combat‐deployed healthy controls (HCs). Analytic models of individual frequency bands and all bands together were tested. The All‐frequency model, which combined delta‐theta (1–7 Hz), alpha (8–12 Hz), beta (15–30 Hz), and gamma (30–80 Hz) frequency bands, outperformed models based on individual bands. The optimized 3D‐MEGNET method distinguished cmTBI individuals from HCs with excellent sensitivity (99.9 ± 0.38%) and specificity (98.9 ± 1.54%). Receiver‐operator‐characteristic curve analysis showed that diagnostic accuracy was 0.99. The gamma and delta‐theta band models outperformed alpha and beta band models. Among cmTBI individuals, but not controls, hyper delta‐theta and gamma‐band activity correlated with lower performance on neuropsychological tests, whereas hypo alpha and beta‐band activity also correlated with lower neuropsychological test performance. This study provides an integrated framework for condensing large source‐imaging variable sets into optimal combinations of regions and frequencies with high diagnostic accuracy and cognitive relevance in cmTBI. The all‐frequency model offered more discriminative power than each frequency‐band model alone. This approach offers an effective path for optimal characterization of behaviorally relevant neuroimaging features in neurological and psychiatric disorders.
Collapse
Affiliation(s)
- Ming-Xiong Huang
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| | - Charles W Huang
- Department of Bioengineering, Stanford University, Stanford, California, USA
| | - Deborah L Harrington
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| | - Ashley Robb-Swan
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| | - Annemarie Angeles-Quinto
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| | - Sharon Nichols
- Department of Neurosciences, University of California, San Diego, California, USA
| | - Jeffrey W Huang
- Department of Computer Science, Columbia University, New York, New York, USA
| | - Lu Le
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, California, USA
| | - Carl Rimmele
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, California, USA
| | - Scott Matthews
- ASPIRE Center, VASDHS Residential Rehabilitation Treatment Program, San Diego, California, USA
| | - Angela Drake
- Cedar Sinai Medical Group Chronic Pain Program, Beverly Hills, California, USA
| | - Tao Song
- Department of Radiology, University of California, San Diego, California, USA
| | - Zhengwei Ji
- Department of Radiology, University of California, San Diego, California, USA
| | - Chung-Kuan Cheng
- Department of Computer Science and Engineering, University of California, San Diego, California, USA
| | - Qian Shen
- Department of Radiology, University of California, San Diego, California, USA
| | - Ericka Foote
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA
| | - Imanuel Lerman
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA
| | - Kate A Yurgil
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Psychological Sciences, Loyola University New Orleans, Louisiana, USA
| | - Hayden B Hansen
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA
| | - Robert K Naviaux
- Department of Medicine, University of California, San Diego, California, USA.,Department of Pediatrics, University of California, San Diego, California, USA.,Department of Pathology, University of California, San Diego, California, USA
| | - Robert Dynes
- Department of Physics, University of California, San Diego, California, USA
| | - Dewleen G Baker
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,VA Center of Excellence for Stress and Mental Health, San Diego, California, USA.,Department of Psychiatry, University of California, San Diego, California, USA
| | - Roland R Lee
- Radiology, Research, and Psychiatry Services, VA San Diego Healthcare System, San Diego, California, USA.,Department of Radiology, University of California, San Diego, California, USA
| |
Collapse
|
18
|
Yang J, Pan Y, Wang T, Zhang X, Wen J, Luo Y. Sleep-Dependent Directional Interactions of the Central Nervous System-Cardiorespiratory Network. IEEE Trans Biomed Eng 2020; 68:639-649. [PMID: 32746063 DOI: 10.1109/tbme.2020.3009950] [Citation(s) in RCA: 2] [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
OBJECTIVE We investigated the nature of interactions between the central nervous system (CNS) and the cardiorespiratory system during sleep. METHODS Overnight polysomnography recordings were obtained from 33 healthy individuals. The relative spectral powers of five frequency bands, three ECG morphological features and respiratory rate were obtained from six EEG channels, ECG, and oronasal airflow, respectively. The synchronous feature series were interpolated to 1 Hz to retain the high time-resolution required to detect rapid physiological variations. CNS-cardiorespiratory interaction networks were built for each EEG channel and a directionality analysis was conducted using multivariate transfer entropy. Finally, the difference in interaction between Deep, Light, and REM sleep (DS, LS, and REM) was studied. RESULTS Bidirectional interactions existed in central-cardiorespiratory networks, and the dominant direction was from the cardiorespiratory system to the brain during all sleep stages. Sleep stages had evident influence on these interactions, with the strength of information transfer from heart rate and respiration rate to the brain gradually increasing with the sequence of REM, LS, and DS. Furthermore, the occipital lobe appeared to receive the most input from the cardiorespiratory system during LS. Finally, different ECG morphological features were found to be involved with various central-cardiac and cardiac-respiratory interactions. CONCLUSION These findings reveal detailed information regarding CNS-cardiorespiratory interactions during sleep and provide new insights into understanding of sleep control mechanisms. SIGNIFICANCE Our approach may facilitate the investigation of the pathological cardiorespiratory complications of sleep disorders.
Collapse
|
19
|
Yang J, Pan Y, Luo Y. Investigation of brain-heart network during sleep. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3343-3346. [PMID: 33018720 DOI: 10.1109/embc44109.2020.9175305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Interactions between brain and heart play an important role for sleep quality and control. However, the influence mechanism was still unclear. This study aimed to further investigate this mechanism according to build an information transfer network of brain-heart coupling. This study included 24 healthy individuals and both of them underwent overnight polysomnography. The relative spectral powers of five frequency bands and the high frequency power of heart rate variability were extracted from six electroencephalogram (EEG) channels and electrocardiography (ECG) respectively. For each EEG channel, brain-heart interaction networks were built and a directionality analysis was conducted by using multivariate transfer entropy. Results revealed the bidirectionality of information transfer between brain and heart during sleep, and the information was dominantly transfer from heart to brain. The information transfer strength between brain and heart were significantly stronger than which between frequency bands in each EEG channels. Besides, the frequency bands and EEG channels had evident influence on these interactions. This study exposed more detailed characteristics of brain-heart interaction, which will facilitate the future study about the sleep control and the diagnose of sleep related disease.
Collapse
|
20
|
Chen PC, Whitehurst LN, Naji M, Mednick SC. Autonomic/central coupling benefits working memory in healthy young adults. Neurobiol Learn Mem 2020; 173:107267. [PMID: 32535198 DOI: 10.1016/j.nlm.2020.107267] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Revised: 05/13/2020] [Accepted: 06/08/2020] [Indexed: 02/01/2023]
Abstract
Working memory (WM) is an executive function that can improve with training. However, the precise mechanism for this improvement is not known. Studies have shown greater WM gains after a period of sleep than a similar period of wake, and correlations between WM improvement and slow wave activity (SWA; 0.5-1 Hz) during slow wave sleep (SWS). A different body of literature has suggested an important role for autonomic activity during wake for WM. A recent study from our group reported that the temporal coupling of Autonomic/CentralEvents (ACEs) during sleep was associated with memory consolidation. We found that heart rate bursts (HR bursts) during non-rapid eye movement (NREM) sleep are accompanied by increases in SWA and sigma (12-15 Hz) power, as well as increases in the high-frequency (HF) component of the RR interval, reflecting vagal rebound. In addition, ACEs predict long-term, episodic memory improvement. Building on these previous results, we examined whether ACEs also contribute to gains in WM. We tested 104 young adults in an operation span task (OSPAN) in the morning and evening, with either a nap (n = 53; with electroencephalography (EEG) and electrocardiography (ECG)) or wake (n = 51) between testing sessions. We identified HR bursts in the ECG and replicated the increases in SWA and sigma prior to peak of the HR burst, as well as vagal rebound after the peak. Furthermore, we showed sleep-dependent WM improvement, which was predicted by ACE activity. Using regression analyses, we discovered that significantly more variance in WM improvement could be explained with ACE variables than with overall sleep activity not time-locked with ECG. These results provide the first evidence that coordinated autonomic and central events play a significant role in sleep-related WM improvement and implicate the potential of autonomic interventions during sleep for cognitive enhancement.
Collapse
Affiliation(s)
- Pin-Chun Chen
- Department of Cognitive Science, University of California, Irvine USA
| | | | - Mohsen Naji
- Department of Medicine, University of California, San Diego, CA, USA
| | - Sara C Mednick
- Department of Cognitive Science, University of California, Irvine USA.
| |
Collapse
|
21
|
|
22
|
van Schalkwijk FJ, Hauser T, Hoedlmoser K, Ameen MS, Wilhelm FH, Sauter C, Klösch G, Moser D, Gruber G, Anderer P, Saletu B, Parapatics S, Zeitlhofer J, Schabus M. Procedural memory consolidation is associated with heart rate variability and sleep spindles. J Sleep Res 2019; 29:e12910. [PMID: 31454120 PMCID: PMC7317359 DOI: 10.1111/jsr.12910] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 08/02/2019] [Accepted: 08/05/2019] [Indexed: 11/30/2022]
Abstract
Sleep and memory studies often focus on overnight rather than long‐term memory changes, traditionally associating overnight memory change (OMC) with sleep architecture and sleep patterns such as spindles. In addition, (para‐)sympathetic innervation has been associated with OMC after a daytime nap using heart rate variability (HRV). In this study we investigated overnight and long‐term performance changes for procedural memory and evaluated associations with sleep architecture, spindle activity (SpA) and HRV measures (R‐R interval [RRI], standard deviation of R‐R intervals [SDNN], as well as spectral power for low [LF] and high frequencies [HF]). All participants (N = 20, Mage = 23.40 ± 2.78 years) were trained on a mirror‐tracing task and completed a control (normal vision) and learning (mirrored vision) condition. Performance was evaluated after training (R1), after a full‐night sleep (R2) and 7 days thereafter (R3). Overnight changes (R2‐R1) indicated significantly higher accuracy after sleep, whereas a significant long‐term (R3‐R2) improvement was only observed for tracing speed. Sleep architecture measures were not associated with OMC after correcting for multiple comparisons. However, individual SpA change from the control to the learning night indicated that only “SpA enhancers” exhibited overnight improvements for accuracy and long‐term improvements for speed. HRV analyses revealed that lower SDNN and LF power was associated with better OMC for the procedural speed measure. Altogether, this study indicates that overnight improvement for procedural memory is specific for spindle enhancers, and is associated with HRV during sleep following procedural learning.
Collapse
Affiliation(s)
- Frank J van Schalkwijk
- Laboratory for Sleep, Cognition and Consciousness Research, Centre for Cognitive Neuroscience (CCNS), University of Salzburg, Salzburg, Austria
| | - Theresa Hauser
- Laboratory for Sleep, Cognition and Consciousness Research, Centre for Cognitive Neuroscience (CCNS), University of Salzburg, Salzburg, Austria
| | - Kerstin Hoedlmoser
- Laboratory for Sleep, Cognition and Consciousness Research, Centre for Cognitive Neuroscience (CCNS), University of Salzburg, Salzburg, Austria
| | - Mohamed S Ameen
- Laboratory for Sleep, Cognition and Consciousness Research, Centre for Cognitive Neuroscience (CCNS), University of Salzburg, Salzburg, Austria
| | - Frank H Wilhelm
- Clinical Stress and Emotion Laboratory, Division of Clinical Psychology, Psychotherapy and Health Psychology, Department of Psychology, University of Salzburg, Salzburg, Austria
| | - Cornelia Sauter
- Department of Neurology, Medical University of Vienna, Vienna, Austria.,Competence Center of Sleep Medicine, Charité - University Medicine, Berlin, Germany
| | - Gerhard Klösch
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Doris Moser
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Georg Gruber
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Peter Anderer
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Bernd Saletu
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Silvia Parapatics
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Josef Zeitlhofer
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Manuel Schabus
- Laboratory for Sleep, Cognition and Consciousness Research, Centre for Cognitive Neuroscience (CCNS), University of Salzburg, Salzburg, Austria
| |
Collapse
|