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Yang B, Liu H, Jiang T, Yu S. Fluctuation in cortical excitation/inhibition modulates capability of attention across time scales ranging from hours to seconds. Cereb Cortex 2024; 34:bhae309. [PMID: 39076112 DOI: 10.1093/cercor/bhae309] [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: 05/13/2024] [Revised: 07/04/2024] [Accepted: 07/13/2024] [Indexed: 07/31/2024] Open
Abstract
Sustained attention, as the basis of general cognitive ability, naturally varies across different time scales, spanning from hours, e.g. from wakefulness to drowsiness state, to seconds, e.g. trial-by-trail fluctuation in a task session. Whether there is a unified mechanism underneath such trans-scale variability remains unclear. Here we show that fluctuation of cortical excitation/inhibition (E/I) is a strong modulator to sustained attention in humans across time scales. First, we observed the ability to attend varied across different brain states (wakefulness, postprandial somnolence, sleep deprived), as well as within any single state with larger swings. Second, regardless of the time scale involved, we found highly attentive state was always linked to more balanced cortical E/I characterized by electroencephalography (EEG) features, while deviations from the balanced state led to temporal decline in attention, suggesting the fluctuation of cortical E/I as a common mechanism underneath trans-scale attentional variability. Furthermore, we found the variations of both sustained attention and cortical E/I indices exhibited fractal structure in the temporal domain, exhibiting features of self-similarity. Taken together, these results demonstrate that sustained attention naturally varies across different time scales in a more complex way than previously appreciated, with the cortical E/I as a shared neurophysiological modulator.
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Affiliation(s)
- Binghao Yang
- Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan District, Beijing 100049, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, No. 230, Yueyang Road, Shanghai 200031, China
| | - Hao Liu
- Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, No. 230, Yueyang Road, Shanghai 200031, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan District, Beijing 100049, China
| | - Tianzi Jiang
- Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, No. 230, Yueyang Road, Shanghai 200031, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan District, Beijing 100049, China
- Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, No. 151, Xiaoshui West Road, Lingling District, Yongzhou 425000, Hunan Province, China
| | - Shan Yu
- Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan District, Beijing 100049, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, No. 230, Yueyang Road, Shanghai 200031, China
- Lead contact. Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
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Chatburn A, Lushington K, Cross ZR. Considerations towards a neurobiologically-informed EEG measurement of sleepiness. Brain Res 2024; 1841:149088. [PMID: 38879143 DOI: 10.1016/j.brainres.2024.149088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Revised: 05/30/2024] [Accepted: 06/12/2024] [Indexed: 06/18/2024]
Abstract
Sleep is a daily experience across humans and other species, yet our understanding of how and why we sleep is presently incomplete. This is particularly prevalent in research examining the neurophysiological measurement of sleepiness in humans, where several electroencephalogram (EEG) phenomena have been linked with prolonged wakefulness. This leaves researchers without a solid basis for the measurement of homeostatic sleep need and complicates our understanding of the nature of sleep. Recent theoretical and technical advances may allow for a greater understanding of the neurobiological basis of homeostatic sleep need: this may result from increases in neuronal excitability and shifts in excitation/inhibition balance in neuronal circuits and can potentially be directly measured via the aperiodic component of the EEG. Here, we review the literature on EEG-derived markers of sleepiness in humans and argue that changes in these electrophysiological markers may actually result from neuronal activity represented by changes in aperiodic markers. We argue for the use of aperiodic markers derived from the EEG in predicting sleepiness and suggest areas for future research based on these.
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Affiliation(s)
- Alex Chatburn
- Cognitive Neuroscience Laboratory, University of South Australia, Adelaide, Australia.
| | - Kurt Lushington
- Cognitive Neuroscience Laboratory, University of South Australia, Adelaide, Australia; Centre for Behaviour-Brain-Body: Justice and Society Unit, University of South Australia, Adelaide, South Australia, Australia
| | - Zachariah R Cross
- Cognitive Neuroscience Laboratory, University of South Australia, Adelaide, Australia; Feinberg School of Medicine, Northwestern University, USA
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Demiral S, Lildharrie C, Lin E, Benveniste H, Volkow N. Blink-related arousal network surges are shaped by cortical vigilance states. RESEARCH SQUARE 2024:rs.3.rs-4271439. [PMID: 38766129 PMCID: PMC11100883 DOI: 10.21203/rs.3.rs-4271439/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
The vigilance state and the excitability of cortical networks impose wide-range effects on brain dynamics that arousal surges could promptly modify. We previously reported an association between spontaneous eye-blinks and BOLD activation in the brain arousal ascending network (AAN) and in thalamic nuclei based on 3T MR resting state brain images. Here we aimed to replicate our analyses using 7T MR images in a larger cohort of participants collected from the Human Connectome Project (HCP), which also contained simultaneous eye-tracking recordings, and to assess the interaction between the blink-associated arousal surges and the vigilance states. For this purpose, we compared blink associated BOLD activity under a vigilant versus a drowsy state, a classification made based on the pupillary data obtained during the fMRI scans. We conducted two main analyses: i) Cross-correlation analysis between the BOLD signal and blink events (eye blink time-series were convolved with the canonical and also with the temporal derivative of the Hemodynamic Response Function, HRF) within preselected regions of interests (ROIs) (i.e., brainstem AAN, thalamic and cerebellar nuclei) together with an exploratory voxel-wise analyses to assess the whole-brain, and ii) blink-event analysis of the BOLD signals to reveal the signal changes onset to the blinks in the preselected ROIs. Consistent with our prior findings on 3T MRI, we showed significant positive cross correlations between BOLD peaks in brainstem and thalamic nuclei that preceded or were overlapping with blink moments and that sharply decreased post-blink. Whole brain analysis revealed blink-related activation that was strongest in cerebellum, insula, lateral geniculate nucleus (LGN) and visual cortex. Drowsiness impacted HRF BOLD (enhancing it), time-to-peak (delaying it) and post-blink BOLD activity (accentuating decreases). Responses in the drowsy state could be related to the differences in the excitability of cortical, subcortical and cerebellar tissue, such that cerebellar and thalamic regions involved in visual attention processing were more responsive for the vigilant state, but AAN ROIs, as well as cerebellar and thalamic ROIs connected to pre-motor, frontal, temporal and DMN regions were less responsive. Such qualitative and quantitative differences in the blink related BOLD signal changes could reflect delayed cortical processing and the ineffectiveness of arousal surges during states of drowsiness. Future studies that manipulate arousal are needed to corroborate a mechanistic interaction of arousal surges with vigilance states and cortical excitability.
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Affiliation(s)
- Sukru Demiral
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health
| | - Christina Lildharrie
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health
| | - Esther Lin
- National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health
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Weiss JT, Blundell MZ, Singh P, Donlea JM. Sleep deprivation drives brain-wide changes in cholinergic presynapse abundance in Drosophila melanogaster. Proc Natl Acad Sci U S A 2024; 121:e2312664121. [PMID: 38498719 PMCID: PMC10990117 DOI: 10.1073/pnas.2312664121] [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: 07/24/2023] [Accepted: 02/19/2024] [Indexed: 03/20/2024] Open
Abstract
Sleep is an evolutionarily conserved state that supports brain functions, including synaptic plasticity, in species across the animal kingdom. Here, we examine the neuroanatomical and cell-type distribution of presynaptic scaling in the fly brain after sleep loss. We previously found that sleep loss drives accumulation of the active zone scaffolding protein Bruchpilot (BRP) within cholinergic Kenyon cells of the Drosophila melanogaster mushroom body (MB), but not in other classes of MB neurons. To test whether similar cell type-specific trends in plasticity occur broadly across the brain, we used a flp-based genetic reporter to label presynaptic BRP in cholinergic, dopaminergic, GABAergic, or glutamatergic neurons. We then collected whole-brain confocal image stacks of BRP intensity to systematically quantify BRP, a marker of presynapse abundance, across 37 neuropil regions of the central fly brain. Our results indicate that sleep loss, either by overnight (12-h) mechanical stimulation or chronic sleep disruption in insomniac mutants, broadly elevates cholinergic synapse abundance across the brain, while synapse abundance in neurons that produce other neurotransmitters undergoes weaker, if any, changes. Extending sleep deprivation to 24 h drives brain-wide upscaling in glutamatergic, but not other, synapses. Finally, overnight male-male social pairings induce increased BRP in excitatory synapses despite male-female pairings eliciting more waking activity, suggesting experience-specific plasticity. Within neurotransmitter class and waking context, BRP changes are similar across the 37 neuropil domains, indicating that similar synaptic scaling rules may apply across the brain during acute sleep loss and that sleep need may broadly alter excitatory-inhibitory balance in the central brain.
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Affiliation(s)
- Jacqueline T. Weiss
- Department of Neurobiology, David Geffen School of Medicine at University of California, Los Angeles, CA90095
- Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California, Los Angeles, CA90095
| | - Mei Z. Blundell
- Department of Neurobiology, David Geffen School of Medicine at University of California, Los Angeles, CA90095
| | - Prabhjit Singh
- Department of Neurobiology, David Geffen School of Medicine at University of California, Los Angeles, CA90095
| | - Jeffrey M. Donlea
- Department of Neurobiology, David Geffen School of Medicine at University of California, Los Angeles, CA90095
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Mroczek M, de Grado A, Pia H, Nochi Z, Tankisi H. Effects of sleep deprivation on cortical excitability: A threshold-tracking TMS study and review of the literature. Clin Neurophysiol Pract 2023; 9:13-20. [PMID: 38223850 PMCID: PMC10787222 DOI: 10.1016/j.cnp.2023.12.001] [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: 08/27/2023] [Revised: 11/09/2023] [Accepted: 12/01/2023] [Indexed: 01/16/2024] Open
Abstract
Objective Insufficient sleep is linked to several health problems. Previous studies on the effects of sleep deprivation on cortical excitability using conventional transcranial magnetic stimulation (TMS) included a limited number of modalities, and few inter-stimulus intervals (ISIs) and showed conflicting results. This study aimed to investigate the effects of sleep deprivation on cortical excitability through threshold-tracking TMS, using a wide range of protocols at multiple ISIs. Methods Fifteen healthy subjects (mean age ± SD: 36 ± 3.34 years) were included. The following tests were performed before and after 24 h of sleep deprivation using semi-automated threshold-tacking TMS protocols: short-interval intracortical inhibition (SICI) and intracortical facilitation (ICF) at 11 ISIs between 1 and 30 ms, short interval intracortical facilitation (SICF) at 14 ISIs between 1 and 4.9 ms, long interval intracortical inhibition (LICI) at 6 ISIs between 50 and 300 ms, and short-latency afferent inhibition (SAI) at 12 ISIs between 16 and 30 ms. Results No significant differences were observed between pre- and post-sleep deprivation measurements for SICI, ICF, SICF, or LICI at any ISIs (p < 0.05). As for SAI, we found a difference at 28 ms (p = 0.007) and 30 ms (p = 0.04) but not at other ISIs. Conclusions Sleep deprivation does not affect cortical excitability except for SAI. Significance This study confirms some of the previous studies while contradicting others.
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Affiliation(s)
- Magdalena Mroczek
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Amedeo de Grado
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
- Neurophysiology Unit, IRCCS Fondazione Istituto Neurologico “Carlo Besta”, Università degli Studi di Milano, Milano, Italy
| | - Hossain Pia
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
| | - Zahra Nochi
- Danish Pain Research Center, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Hatice Tankisi
- Department of Clinical Neurophysiology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Faculty of Health, Aarhus University, Aarhus, Denmark
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Sun X, Yuan H. Promising applications of non-invasive brain stimulation on military cognition enhancement: a long way to go. Gen Psychiatr 2023; 36:e101264. [PMID: 37920407 PMCID: PMC10618962 DOI: 10.1136/gpsych-2023-101264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 10/09/2023] [Indexed: 11/04/2023] Open
Affiliation(s)
- Xiaolong Sun
- Department of Rehabilitation Medicine, Xijing Hospital, Xi'an, China
| | - Hua Yuan
- Department of Rehabilitation Medicine, Xijing Hospital, Xi'an, China
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Yang B, Zhang H, Jiang T, Yu S. Natural brain state change with E/I balance shifting toward inhibition is associated with vigilance impairment. iScience 2023; 26:107963. [PMID: 37822500 PMCID: PMC10562778 DOI: 10.1016/j.isci.2023.107963] [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: 04/20/2023] [Revised: 07/25/2023] [Accepted: 09/15/2023] [Indexed: 10/13/2023] Open
Abstract
The delicate balance between cortical excitation and inhibition (E/I) plays a pivotal role in brain state changes. While previous studies have associated cortical hyperexcitability with brain state changes induced by sleep deprivation, whether cortical hypoexcitability is also linked to brain state changes and, if so, how it could affect cognitive performance remain unknown. Here, we address these questions by examining the brain state change occurring after meals, i.e., postprandial somnolence, and comparing it with that induced by sleep deprivation. By analyzing features representing network excitability based on electroencephalogram (EEG) signals, we confirmed cortical hyperexcitability under sleep deprivation but revealed hypoexcitability under postprandial somnolence. In addition, we found that both sleep deprivation and postprandial somnolence adversely affected the level of vigilance. These results indicate that cortical E/I balance toward inhibition is associated with brain state changes, and deviation from the balanced state, regardless of its direction, could impair cognitive performance.
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Affiliation(s)
- Binghao Yang
- Brainnetome Center, Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Haoran Zhang
- Brainnetome Center, Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Tianzi Jiang
- Brainnetome Center, Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 101408, China
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311121, China
| | - Shan Yu
- Brainnetome Center, Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China
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Cardone P, Bodart O, Kirsch M, Sanfilippo J, Virgillito A, Martial C, Simon J, Wannez S, Sanders RD, Laureys S, Massimini M, Vandewalle G, Bonhomme V, Gosseries O. Depth of sedation with dexmedetomidine increases transcranial magnetic stimulation-evoked potential amplitude non-linearly. Br J Anaesth 2023; 131:715-725. [PMID: 37596183 DOI: 10.1016/j.bja.2023.05.030] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 05/09/2023] [Accepted: 05/30/2023] [Indexed: 08/20/2023] Open
Abstract
BACKGROUND Cortical excitability is higher in unconsciousness than in wakefulness, but it is unclear how this relates to anaesthesia. We investigated cortical excitability in response to dexmedetomidine, the effects of which are not fully known. METHODS We recorded transcranial magnetic stimulation (TMS) and EEG in frontal and parietal cortex of 20 healthy subjects undergoing dexmedetomidine sedation in four conditions (baseline, light sedation, deep sedation, recovery). We used the first component (0-30 ms) of the TMS-evoked potential (TEP) to measure cortical excitability (amplitude), slope, and positive and negative peak latencies (collectively, TEP indices). We used generalised linear mixed models to test the effect of condition, brain region, and responsiveness on TEP indices. RESULTS Compared with baseline, amplitude in the frontal cortex increased by 6.52 μV (P<0.001) in light sedation, 4.55 μV (P=0.003) in deep sedation, and 5.03 μV (P<0.001) in recovery. Amplitude did not change in the parietal cortex. Compared with baseline, slope increased in all conditions (P<0.02) in the frontal but not parietal cortex. The frontal cortex showed 5.73 μV higher amplitude (P<0.001), 0.63 μV ms-1 higher slope (P<0.001), and 2.2 ms shorter negative peak latency (P=0.001) than parietal areas. Interactions between dexmedetomidine and region had effects over amplitude (P=0.004) and slope (P=0.009), with both being higher in light sedation, deep sedation, and recovery compared with baseline. CONCLUSIONS Transcranial magnetic stimulation-evoked potential amplitude changes non-linearly as a function of depth of sedation by dexmedetomidine, with a region-specific paradoxical increase. Future research should investigate other anaesthetics to elucidate the link between cortical excitability and depth of sedation.
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Affiliation(s)
- Paolo Cardone
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium
| | - Olivier Bodart
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium; Department of Neurology, University of Liège, Liège, Belgium
| | - Murielle Kirsch
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, University of Liège, Liège, Belgium; Department of Anaesthesia and Intensive Care Medicine, University of Liège, Liège, Belgium
| | - Julien Sanfilippo
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, University of Liège, Liège, Belgium
| | | | - Charlotte Martial
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium
| | - Jessica Simon
- Psychology and Neuroscience of Cognition, University of Liège, Liège, Belgium
| | - Sarah Wannez
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
| | - Robert D Sanders
- Specialty of Anaesthetics, University of Sydney, Camperdown, Australia; Department of Anaesthetics & Institute of Academic Surgery, Royal Prince Alfred Hospital, Camperdown, Australia
| | - Steven Laureys
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium; Joint International Research Unit on Consciousness, CERVO Brain Research Centre, CIUSS, University Laval, Québec City, QC, Canada
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy; IRCCS Fondazione Don Gnocchi, Milan, Italy
| | - Gilles Vandewalle
- Sleep and Chronobiology Lab, GIGA-Cyclotron Research Centre-In Vivo Imaging, University of Liège, Liège, Belgium
| | - Vincent Bonhomme
- Anesthesia and Perioperative Neuroscience Laboratory, GIGA-Consciousness, University of Liège, Liège, Belgium; Department of Anaesthesia and Intensive Care Medicine, University of Liège, Liège, Belgium; University Department of Anaesthesia and Intensive Care Medicine, Centre Hospitalier Régional de la Citadelle (CHR Citadelle), Liège, Belgium.
| | - Olivia Gosseries
- Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium; Centre du Cerveau, University of Liège, Liège, Belgium.
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