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Wan W, Gu Z, Peng CK, Cui X. Beyond Frequency Bands: Complementary-Ensemble-Empirical-Mode-Decomposition-Enhanced Microstate Sequence Non-Randomness Analysis for Aiding Diagnosis and Cognitive Prediction of Dementia. Brain Sci 2024; 14:487. [PMID: 38790465 PMCID: PMC11118442 DOI: 10.3390/brainsci14050487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2024] [Revised: 05/01/2024] [Accepted: 05/09/2024] [Indexed: 05/26/2024] Open
Abstract
Exploring the spatiotemporal dynamic patterns of multi-channel electroencephalography (EEG) is crucial for interpreting dementia and related cognitive decline. Spatiotemporal patterns of EEG can be described through microstate analysis, which provides a discrete approximation of the continuous electric field patterns generated by the brain cortex. Here, we propose a novel microstate spatiotemporal dynamic indicator, termed the microstate sequence non-randomness index (MSNRI). The essence of the method lies in initially generating a sequence of microstate transition patterns through state space compression of EEG data using microstate analysis. Following this, we assess the non-randomness of these microstate patterns using information-based similarity analysis. The results suggest that this MSNRI metric is a potential marker for distinguishing between health control (HC) and frontotemporal dementia (FTD) (HC vs. FTD: 6.958 vs. 5.756, p < 0.01), as well as between HC and populations with Alzheimer's disease (AD) (HC vs. AD: 6.958 vs. 5.462, p < 0.001). Healthy individuals exhibit more complex macroscopic structures and non-random spatiotemporal patterns of microstates, whereas dementia disorders lead to more random spatiotemporal patterns. Additionally, we extend the proposed method by integrating the Complementary Ensemble Empirical Mode Decomposition (CEEMD) method to explore spatiotemporal dynamic patterns of microstates at specific frequency scales. Moreover, we assessed the effectiveness of this innovative method in predicting cognitive scores. The results demonstrate that the incorporation of CEEMD-enhanced microstate dynamic indicators significantly improved the prediction accuracy of Mini-Mental State Examination (MMSE) scores (R2 = 0.940). The CEEMD-enhanced MSNRI method not only aids in the exploration of large-scale neural changes in populations with dementia but also offers a robust tool for characterizing the dynamics of EEG microstate transitions and their impact on cognitive function.
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Affiliation(s)
- Wang Wan
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China; (W.W.); (Z.G.)
- Center for Nonlinear Dynamics in Medicine, Southeast University, Nanjing 210096, China;
| | - Zhongze Gu
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China; (W.W.); (Z.G.)
| | - Chung-Kang Peng
- Center for Nonlinear Dynamics in Medicine, Southeast University, Nanjing 210096, China;
- Key Laboratory of Child Development and Learning Science, Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
| | - Xingran Cui
- Center for Nonlinear Dynamics in Medicine, Southeast University, Nanjing 210096, China;
- Key Laboratory of Child Development and Learning Science, Ministry of Education, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China
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2
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Zhou X, He Y, Xu T, Wu Z, Guo W, Xu X, Liu Y, Zhang Y, Shang H, Huang L, Yao Z, Li Z, Su L, Li Z, Feng T, Zhang S, Monteiro O, Cunha RA, Huang ZL, Zhang K, Li Y, Cai X, Qu J, Chen JF. 40 Hz light flickering promotes sleep through cortical adenosine signaling. Cell Res 2024; 34:214-231. [PMID: 38332199 PMCID: PMC10907382 DOI: 10.1038/s41422-023-00920-1] [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: 10/17/2023] [Accepted: 12/20/2023] [Indexed: 02/10/2024] Open
Abstract
Flickering light stimulation has emerged as a promising non-invasive neuromodulation strategy to alleviate neuropsychiatric disorders. However, the lack of a neurochemical underpinning has hampered its therapeutic development. Here, we demonstrate that light flickering triggered an immediate and sustained increase (up to 3 h after flickering) in extracellular adenosine levels in the primary visual cortex (V1) and other brain regions, as a function of light frequency and intensity, with maximal effects observed at 40 Hz frequency and 4000 lux. We uncovered cortical (glutamatergic and GABAergic) neurons, rather than astrocytes, as the cellular source, the intracellular adenosine generation from AMPK-associated energy metabolism pathways (but not SAM-transmethylation or salvage purine pathways), and adenosine efflux mediated by equilibrative nucleoside transporter-2 (ENT2) as the molecular pathway responsible for extracellular adenosine generation. Importantly, 40 Hz (but not 20 and 80 Hz) light flickering for 30 min enhanced non-rapid eye movement (non-REM) and REM sleep for 2-3 h in mice. This somnogenic effect was abolished by ablation of V1 (but not superior colliculus) neurons and by genetic deletion of the gene encoding ENT2 (but not ENT1), but recaptured by chemogenetic inhibition of V1 neurons and by focal infusion of adenosine into V1 in a dose-dependent manner. Lastly, 40 Hz light flickering for 30 min also promoted sleep in children with insomnia by decreasing sleep onset latency, increasing total sleep time, and reducing waking after sleep onset. Collectively, our findings establish the ENT2-mediated adenosine signaling in V1 as the neurochemical basis for 40 Hz flickering-induced sleep and unravel a novel and non-invasive treatment for insomnia, a condition that affects 20% of the world population.
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Affiliation(s)
- Xuzhao Zhou
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Oujiang Laboratory (Zhejiang Laboratory for Regenerative Medicine, Vision and Brain Health), School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yan He
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Tao Xu
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhaofa Wu
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
| | - Wei Guo
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Xi Xu
- Department of Pediatrics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yuntao Liu
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Yi Zhang
- Oujiang Laboratory (Zhejiang Laboratory for Regenerative Medicine, Vision and Brain Health), School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
- Institute of Genomic Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Huiping Shang
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Libin Huang
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhimo Yao
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zewen Li
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Lingya Su
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Zhihui Li
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China
| | - Tao Feng
- Key Laboratory of Biomedical Engineering of Ministry of Education, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shaomin Zhang
- Key Laboratory of Biomedical Engineering of Ministry of Education, Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, Zhejiang, China
| | - Olivia Monteiro
- Faculty of Medicine, Macau University of Science and Technology, Taipa, Macau, China
| | - Rodrigo A Cunha
- CNC-Center for Neuroscience and Cell Biology, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Zhi-Li Huang
- Department of Pharmacology, School of Basic Medical Sciences; State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, and Institutes of Brain Science, Fudan University, Shanghai, China
| | - Kang Zhang
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
- Faculty of Medicine, Macau University of Science and Technology, Taipa, Macau, China.
| | - Yulong Li
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing, China
| | - Xiaohong Cai
- Department of Pediatrics, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China.
| | - Jia Qu
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
- Oujiang Laboratory (Zhejiang Laboratory for Regenerative Medicine, Vision and Brain Health), School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
| | - Jiang-Fan Chen
- The Eye and Brain Center, State Key Laboratory of Ophthalmology, Optometry and Visual Science, Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
- Oujiang Laboratory (Zhejiang Laboratory for Regenerative Medicine, Vision and Brain Health), School of Ophthalmology & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang, China.
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3
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Blanco-Duque C, Chan D, Kahn MC, Murdock MH, Tsai LH. Audiovisual gamma stimulation for the treatment of neurodegeneration. J Intern Med 2024; 295:146-170. [PMID: 38115692 PMCID: PMC10842797 DOI: 10.1111/joim.13755] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Alzheimer's disease (AD) is the most common type of neurodegenerative disease and a health challenge with major social and economic consequences. In this review, we discuss the therapeutic potential of gamma stimulation in treating AD and delve into the possible mechanisms responsible for its positive effects. Recent studies reveal that it is feasible and safe to induce 40 Hz brain activity in AD patients through a range of 40 Hz multisensory and noninvasive electrical or magnetic stimulation methods. Although research into the clinical potential of these interventions is still in its nascent stages, these studies suggest that 40 Hz stimulation can yield beneficial effects on brain function, disease pathology, and cognitive function in individuals with AD. Specifically, we discuss studies involving 40 Hz light, auditory, and vibrotactile stimulation, as well as noninvasive techniques such as transcranial alternating current stimulation and transcranial magnetic stimulation. The precise mechanisms underpinning the beneficial effects of gamma stimulation in AD are not yet fully elucidated, but preclinical studies have provided relevant insights. We discuss preclinical evidence related to both neuronal and nonneuronal mechanisms that may be involved, touching upon the relevance of interneurons, neuropeptides, and specific synaptic mechanisms in translating gamma stimulation into widespread neuronal activity within the brain. We also explore the roles of microglia, astrocytes, and the vasculature in mediating the beneficial effects of gamma stimulation on brain function. Lastly, we examine upcoming clinical trials and contemplate the potential future applications of gamma stimulation in the management of neurodegenerative disorders.
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Affiliation(s)
- Cristina Blanco-Duque
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Diane Chan
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Martin C Kahn
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mitchell H Murdock
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
- Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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4
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Wang C, Lin C, Zhao Y, Samantzis M, Sedlak P, Sah P, Balbi M. 40-Hz optogenetic stimulation rescues functional synaptic plasticity after stroke. Cell Rep 2023; 42:113475. [PMID: 37979173 DOI: 10.1016/j.celrep.2023.113475] [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: 06/19/2023] [Revised: 10/18/2023] [Accepted: 11/03/2023] [Indexed: 11/20/2023] Open
Abstract
Evoked brain oscillations in the gamma range have been shown to assist in stroke recovery. However, the causal relationship between evoked oscillations and neuroprotection is not well understood. We have used optogenetic stimulation to investigate how evoked gamma oscillations modulate cortical dynamics in the acute phase after stroke. Our results reveal that stimulation at 40 Hz drives activity in interneurons at the stimulation frequency and phase-locked activity in principal neurons at a lower frequency, leading to increased cross-frequency coupling. In addition, 40-Hz stimulation after stroke enhances interregional communication. These effects are observed up to 24 h after stimulation. Our stimulation protocol also rescues functional synaptic plasticity 24 h after stroke and leads to an upregulation of plasticity genes and a downregulation of cell death genes. Together these results suggest that restoration of cortical dynamics may confer neuroprotection after stroke.
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Affiliation(s)
- Cong Wang
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia; Engineering Research Centre of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai 201203, China
| | - Caixia Lin
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Yue Zhao
- Departments of Thoracic Surgery and State Key Laboratory of Genetic Engineering, Fudan University Shanghai Cancer Centre, Shanghai 200032, China; Institute of Thoracic Oncology, Fudan University, Shanghai 200032, China; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Montana Samantzis
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Petra Sedlak
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Pankaj Sah
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia
| | - Matilde Balbi
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD 4067, Australia.
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5
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Yu F, Gao Y, Li F, Zhang X, Hu F, Jia W, Li X. Resting-state EEG microstates as electrophysiological biomarkers in post-stroke disorder of consciousness. Front Neurosci 2023; 17:1257511. [PMID: 37849891 PMCID: PMC10577186 DOI: 10.3389/fnins.2023.1257511] [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: 07/12/2023] [Accepted: 09/18/2023] [Indexed: 10/19/2023] Open
Abstract
Introduction Ischemic stroke patients commonly experience disorder of consciousness (DOC), leading to poorer discharge outcomes and higher mortality risks. Therefore, the identification of applicable electrophysiological biomarkers is crucial for the rapid diagnosis and evaluation of post-stroke disorder of consciousness (PS-DOC), while providing supportive evidence for cerebral neurology. Methods In our study, we conduct microstate analysis on resting-state electroencephalography (EEG) of 28 post-stroke patients with awake consciousness and 28 patients with PS-DOC, calculating the temporal features of microstates. Furthermore, we extract the Lempel-Ziv complexity of microstate sequences and the delta/alpha power ratio of EEG on spectral. Statistical analysis is performed to examine the distinctions in features between the two groups, followed by inputting the distinctive features into a support vector machine for the classification of PS-DOC. Results Both groups obtain four optimal topographies of EEG microstates, but notable distinctions are observed in microstate C. Within the PS-DOC group, there is a significant increase in the mean duration and coverage of microstates B and C, whereas microstate D displays a contrasting trend. Additionally, noteworthy variations are found in the delta/alpha ratio and Lempel-Ziv complexity between the two groups. The integration of the delta/alpha ratio with microstates' temporal and Lempel-Ziv complexity features demonstrates the highest performance in the classifier (Accuracy = 91.07%). Discussion Our results suggest that EEG microstates can provide insights into the abnormal brain network dynamics in DOC patients post-stroke. Integrating the temporal and Lempel-Ziv complexity microstate features with spectral features offers a deeper understanding of the neuro mechanisms underlying brain damage in patients with DOC, holding promise as effective electrophysiological biomarkers for diagnosing PS-DOC.
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Affiliation(s)
- Fang Yu
- College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, China
| | - Yanzhe Gao
- College of Life Sciences, Nankai University, Tianjin, China
| | - Fenglian Li
- College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, China
| | - Xueying Zhang
- College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, China
| | - Fengyun Hu
- The Fifth Clinical Medical College of Shanxi Medical University, Department of Neurology, Shanxi Provincial People’s Hospital, Taiyuan, China
| | - Wenhui Jia
- The Fifth Clinical Medical College of Shanxi Medical University, Department of Neurology, Shanxi Provincial People’s Hospital, Taiyuan, China
| | - Xiaohui Li
- College of Electronic Information and Optical Engineering, Taiyuan University of Technology, Taiyuan, China
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6
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Lassi M, Fabbiani C, Mazzeo S, Burali R, Vergani AA, Giacomucci G, Moschini V, Morinelli C, Emiliani F, Scarpino M, Bagnoli S, Ingannato A, Nacmias B, Padiglioni S, Micera S, Sorbi S, Grippo A, Bessi V, Mazzoni A. Degradation of EEG microstates patterns in subjective cognitive decline and mild cognitive impairment: Early biomarkers along the Alzheimer's Disease continuum? Neuroimage Clin 2023; 38:103407. [PMID: 37094437 PMCID: PMC10149415 DOI: 10.1016/j.nicl.2023.103407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 03/29/2023] [Accepted: 04/14/2023] [Indexed: 04/26/2023]
Abstract
Alzheimer's disease (AD) pathological changes may begin up to decades earlier than the appearance of the first symptoms of cognitive decline. Subjective cognitive decline (SCD) could be the first pre-clinical sign of possible AD, which might be followed by mild cognitive impairment (MCI), the initial stage of clinical cognitive decline. However, the neural correlates of these prodromic stages are not completely clear yet. Recent studies suggest that EEG analysis tools characterizing the cortical activity as a whole, such as microstates and cortical regions connectivity, might support a characterization of SCD and MCI conditions. Here we test this approach by performing a broad set of analyses to identify the prominent EEG markers differentiating SCD (n = 57), MCI (n = 46) and healthy control subjects (HC, n = 19). We found that the salient differences were in the temporal structure of the microstates patterns, with MCI being associated with less complex sequences due to the altered transition probability, frequency and duration of canonic microstate C. Spectral content of EEG, network connectivity, and spatial arrangement of microstates were instead largely similar in the three groups. Interestingly, comparing properties of EEG microstates in different cerebrospinal fluid (CSF) biomarkers profiles, we found that canonic microstate C displayed significant differences in topography in AD-like profile. These results show that the progression of dementia might be associated with a degradation of the cortical organization captured by microstates analysis, and that this leads to altered transitions between cortical states. Overall, our approach paves the way for the use of non-invasive EEG recordings in the identification of possible biomarkers of progression to AD from its prodromal states.
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Affiliation(s)
- Michael Lassi
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy
| | - Carlo Fabbiani
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Salvatore Mazzeo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Rachele Burali
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Alberto Arturo Vergani
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Valentina Moschini
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Carmen Morinelli
- Dipartimento Neuromuscolo-scheletrico e degli organi di senso, Careggi University Hospital, 50134 Florence, Italy
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Maenia Scarpino
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Benedetta Nacmias
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Sonia Padiglioni
- Regional Referral Centre for Relational Criticalities - Tuscany Region, 50139 Florence, Italy
| | - Silvestro Micera
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy; Bertarelli Foundation Chair in Translational Neuroengineering, Centre for Neuroprosthetics and Institute of Bioengineering, School of Engineering, École Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
| | - Sandro Sorbi
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy; Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Antonello Grippo
- IRCCS Fondazione Don Carlo Gnocchi, via di Scandicci, 269, 50143 Florence, Italy
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Careggi University Hospital, viale Gaetano Pieraccini, 6, 50139 Florence, Italy
| | - Alberto Mazzoni
- The BioRobotics Institute and Department of Excellence in Robotics and AI, Sant'Anna School of Advanced Studies, viale Rinaldo Piaggio 34, 56025 Pisa, Italy.
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7
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Chen X, Shi X, Wu Y, Zhou Z, Chen S, Han Y, Shan C. Gamma oscillations and application of 40-Hz audiovisual stimulation to improve brain function. Brain Behav 2022; 12:e2811. [PMID: 36374520 PMCID: PMC9759142 DOI: 10.1002/brb3.2811] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 10/06/2022] [Accepted: 10/20/2022] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Audiovisual stimulation, such as auditory stimulation, light stimulation, and audiovisual combined stimulation, as a non-invasive stimulation, which can induce gamma oscillation, has received increased attention in recent years, and it has been preliminarily applied in the clinical rehabilitation of brain dysfunctions, such as cognitive, language, motor, mood, and sleep dysfunctions. However, the exact mechanism underlying the therapeutic effect of 40-Hz audiovisual stimulation remains unclear; the clinical applications of 40-Hz audiovisual stimulation in brain dysfunctions rehabilitation still need further research. OBJECTIVE In order to provide new insights into brain dysfunction rehabilitation, this review begins with a discussion of the mechanism underlying 40-Hz audiovisual stimulation, followed by a brief evaluation of its clinical application in the rehabilitation of brain dysfunctions. RESULTS Currently, 40-Hz audiovisual stimulation was demonstrated to affect synaptic plasticity and modify the connection status of related brain networks in animal experiments and clinical trials. Although its promising efficacy has been shown in the treatment of cognitive, mood, and sleep impairment, research studies into its application in language and motor dysfunctions are still ongoing. CONCLUSIONS Although 40-Hz audiovisual stimulation seems to be effective in treating cognitive, mood, and sleep disorders, its role in language and motor dysfunctions has yet to be determined.
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Affiliation(s)
- Xixi Chen
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Xiaolong Shi
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yuwei Wu
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhiqing Zhou
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Songmei Chen
- School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Department of Rehabilitation Medicine, Shanghai No.3 Rehabilitation Hospital, Shanghai, China
| | - Yan Han
- Department of Neurology, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Chunlei Shan
- Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,School of Rehabilitation Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Engineering Research Center of Traditional Chinese Medicine Intelligent Rehabilitation, Ministry of Education, Shanghai, China
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8
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Cariani P, Baker JM. Time Is of the Essence: Neural Codes, Synchronies, Oscillations, Architectures. Front Comput Neurosci 2022; 16:898829. [PMID: 35814343 PMCID: PMC9262106 DOI: 10.3389/fncom.2022.898829] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 05/04/2022] [Indexed: 11/25/2022] Open
Abstract
Time is of the essence in how neural codes, synchronies, and oscillations might function in encoding, representation, transmission, integration, storage, and retrieval of information in brains. This Hypothesis and Theory article examines observed and possible relations between codes, synchronies, oscillations, and types of neural networks they require. Toward reverse-engineering informational functions in brains, prospective, alternative neural architectures incorporating principles from radio modulation and demodulation, active reverberant circuits, distributed content-addressable memory, signal-signal time-domain correlation and convolution operations, spike-correlation-based holography, and self-organizing, autoencoding anticipatory systems are outlined. Synchronies and oscillations are thought to subserve many possible functions: sensation, perception, action, cognition, motivation, affect, memory, attention, anticipation, and imagination. These include direct involvement in coding attributes of events and objects through phase-locking as well as characteristic patterns of spike latency and oscillatory response. They are thought to be involved in segmentation and binding, working memory, attention, gating and routing of signals, temporal reset mechanisms, inter-regional coordination, time discretization, time-warping transformations, and support for temporal wave-interference based operations. A high level, partial taxonomy of neural codes consists of channel, temporal pattern, and spike latency codes. The functional roles of synchronies and oscillations in candidate neural codes, including oscillatory phase-offset codes, are outlined. Various forms of multiplexing neural signals are considered: time-division, frequency-division, code-division, oscillatory-phase, synchronized channels, oscillatory hierarchies, polychronous ensembles. An expandable, annotative neural spike train framework for encoding low- and high-level attributes of events and objects is proposed. Coding schemes require appropriate neural architectures for their interpretation. Time-delay, oscillatory, wave-interference, synfire chain, polychronous, and neural timing networks are discussed. Some novel concepts for formulating an alternative, more time-centric theory of brain function are discussed. As in radio communication systems, brains can be regarded as networks of dynamic, adaptive transceivers that broadcast and selectively receive multiplexed temporally-patterned pulse signals. These signals enable complex signal interactions that select, reinforce, and bind common subpatterns and create emergent lower dimensional signals that propagate through spreading activation interference networks. If memory traces share the same kind of temporal pattern forms as do active neuronal representations, then distributed, holograph-like content-addressable memories are made possible via temporal pattern resonances.
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Affiliation(s)
- Peter Cariani
- Hearing Research Center, Boston University, Boston, MA, United States
- Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA, United States
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Artoni F, Maillard J, Britz J, Seeber M, Lysakowski C, Bréchet L, Tramèr MR, Michel CM. EEG microstate dynamics indicate a U-shaped path to propofol-induced loss of consciousness. Neuroimage 2022; 256:119156. [PMID: 35364276 DOI: 10.1016/j.neuroimage.2022.119156] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 03/22/2022] [Accepted: 03/27/2022] [Indexed: 11/16/2022] Open
Abstract
Evidence suggests that the stream of consciousness is parsed into transient brain states manifesting themselves as discrete spatiotemporal patterns of global neuronal activity. Electroencephalographical (EEG) microstates are proposed as the neurophysiological correlates of these transiently stable brain states that last for fractions of seconds. To further understand the link between EEG microstate dynamics and consciousness, we continuously recorded high-density EEG in 23 surgical patients from their awake state to unconsciousness, induced by step-wise increasing concentrations of the intravenous anesthetic propofol. Besides the conventional parameters of microstate dynamics, we introduce a new implementation of a method to estimate the complexity of microstate sequences. The brain activity under the surgical anesthesia showed a decreased sequence complexity of the stereotypical microstates, which became sparser and longer-lasting. However, we observed an initial increase in microstates' temporal dynamics and complexity with increasing depth of sedation leading to a distinctive "U-shape" that may be linked to the paradoxical excitation induced by moderate levels of propofol. Our results support the idea that the brain is in a metastable state under normal conditions, balancing between order and chaos in order to flexibly switch from one state to another. The temporal dynamics of EEG microstates indicate changes of this critical balance between stability and transition that lead to altered states of consciousness.
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Affiliation(s)
- Fiorenzo Artoni
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland.
| | - Julien Maillard
- Division of Anesthesiology, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Juliane Britz
- Department of Psychology, University of Fribourg, Fribourg, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Geneva, Switzerland
| | - Martin Seeber
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland
| | - Christopher Lysakowski
- Division of Anesthesiology, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Lucie Bréchet
- CIBM Center for Biomedical Imaging, Lausanne, Geneva, Switzerland; Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland
| | - Martin R Tramèr
- Division of Anesthesiology, Department of Anesthesiology, Clinical Pharmacology, Intensive Care and Emergency Medicine, Geneva University Hospitals, Geneva, Switzerland
| | - Christoph M Michel
- Functional Brain Mapping Laboratory, Department of Basic Neurosciences, University of Geneva, Campus Biotech, Switzerland; CIBM Center for Biomedical Imaging, Lausanne, Geneva, Switzerland.
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Classifying EEG Signals of Mind-Wandering Across Different Styles of Meditation. Brain Inform 2022. [DOI: 10.1007/978-3-031-15037-1_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022] Open
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