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Wang J, Lai Q, Han J, Qin P, Wu H. Neuroimaging biomarkers for the diagnosis and prognosis of patients with disorders of consciousness. Brain Res 2024; 1843:149133. [PMID: 39084451 DOI: 10.1016/j.brainres.2024.149133] [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: 10/23/2023] [Revised: 05/29/2024] [Accepted: 07/25/2024] [Indexed: 08/02/2024]
Abstract
The progress in neuroimaging and electrophysiological techniques has shown substantial promise in improving the clinical assessment of disorders of consciousness (DOC). Through the examination of both stimulus-induced and spontaneous brain activity, numerous comprehensive investigations have explored variations in brain activity patterns among patients with DOC, yielding valuable insights for clinical diagnosis and prognostic purposes. Nonetheless, reaching a consensus on precise neuroimaging biomarkers for patients with DOC remains a challenge. Therefore, in this review, we begin by summarizing the empirical evidence related to neuroimaging biomarkers for DOC using various paradigms, including active, passive, and resting-state approaches, by employing task-based fMRI, resting-state fMRI (rs-fMRI), electroencephalography (EEG), and positron emission tomography (PET) techniques. Subsequently, we conducted a review of studies examining the neural correlates of consciousness in patients with DOC, with the findings holding potential value for the clinical application of DOC. Notably, previous research indicates that neuroimaging techniques have the potential to unveil covert awareness that conventional behavioral assessments might overlook. Furthermore, when integrated with various task paradigms or analytical approaches, this combination has the potential to significantly enhance the accuracy of both diagnosis and prognosis in DOC patients. Nonetheless, the stability of these neural biomarkers still needs additional validation, and future directions may entail integrating diagnostic and prognostic methods with big data and deep learning approaches.
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Affiliation(s)
- Jiaying Wang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Qiantu Lai
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Junrong Han
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Pengmin Qin
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Center for Studies of Psychological Application, School of Psychology, South China Normal University, Guangzhou 510631, China; Pazhou Lab, Guangzhou 510330, China.
| | - Hang Wu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China.
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Egawa S, Ader J, Claassen J. Recovery of consciousness after acute brain injury: a narrative review. J Intensive Care 2024; 12:37. [PMID: 39327599 PMCID: PMC11425956 DOI: 10.1186/s40560-024-00749-9] [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: 05/15/2024] [Accepted: 09/01/2024] [Indexed: 09/28/2024] Open
Abstract
BACKGROUND Disorders of consciousness (DoC) are frequently encountered in both, acute and chronic brain injuries. In many countries, early withdrawal of life-sustaining treatments is common practice for these patients even though the accuracy of predicting recovery is debated and delayed recovery can be seen. In this review, we will discuss theoretical concepts of consciousness and pathophysiology, explore effective strategies for management, and discuss the accurate prediction of long-term clinical outcomes. We will also address research challenges. MAIN TEXT DoC are characterized by alterations in arousal and/or content, being classified as coma, unresponsive wakefulness syndrome/vegetative state, minimally conscious state, and confusional state. Patients with willful modulation of brain activity detectable by functional MRI or EEG but not by behavioral examination is a state also known as covert consciousness or cognitive motor dissociation. This state may be as common as every 4th or 5th patient without behavioral evidence of verbal command following and has been identified as an independent predictor of long-term functional recovery. Underlying mechanisms are uncertain but intact arousal and thalamocortical projections maybe be essential. Insights into the mechanisms underlying DoC will be of major importance as these will provide a framework to conceptualize treatment approaches, including medical, mechanical, or electoral brain stimulation. CONCLUSIONS We are beginning to gain insights into the underlying mechanisms of DoC, identifying novel advanced prognostication tools to improve the accuracy of recovery predictions, and are starting to conceptualize targeted treatments to support the recovery of DoC patients. It is essential to determine how these advancements can be implemented and benefit DoC patients across a range of clinical settings and global societal systems. The Curing Coma Campaign has highlighted major gaps knowledge and provides a roadmap to advance the field of coma science with the goal to support the recovery of patients with DoC.
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Affiliation(s)
- Satoshi Egawa
- Department of Neurology, Neurological Institute, Columbia University Medical Center, NewYork-Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA
- NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jeremy Ader
- Department of Neurology, Neurological Institute, Columbia University Medical Center, NewYork-Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA
- NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Neurological Institute, Columbia University Medical Center, NewYork-Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York, NY, 10032, USA.
- NewYork-Presbyterian Hospital, New York, NY, USA.
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Zhao S, Cao Y, Yang W, Yu J, Xu C, Dai W, Li S, Pan G, Luo B. DOCTer: a novel EEG-based diagnosis framework for disorders of consciousness. J Neural Eng 2024; 21:056021. [PMID: 39255823 DOI: 10.1088/1741-2552/ad7904] [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: 06/01/2024] [Accepted: 09/10/2024] [Indexed: 09/12/2024]
Abstract
Objective. Accurately diagnosing patients with disorders of consciousness (DOC) is challenging and prone to errors. Recent studies have demonstrated that EEG (electroencephalography), a non-invasive technique of recording the spontaneous electrical activity of brains, offers valuable insights for DOC diagnosis. However, some challenges remain: (1) the EEG signals have not been fully used; and (2) the data scale in most existing studies is limited. In this study, our goal is to differentiate between minimally conscious state (MCS) and unresponsive wakefulness syndrome (UWS) using resting-state EEG signals, by proposing a new deep learning framework.Approach. We propose DOCTer, an end-to-end framework for DOC diagnosis based on EEG. It extracts multiple pertinent features from the raw EEG signals, including time-frequency features and microstates. Meanwhile, it takes clinical characteristics of patients into account, and then combines all the features together for the diagnosis. To evaluate its effectiveness, we collect a large-scale dataset containing 409 resting-state EEG recordings from 128 UWS and 187 MCS cases.Main results. Evaluated on our dataset, DOCTer achieves the state-of-the-art performance, compared to other methods. The temporal/spectral features contributes the most to the diagnosis task. The cerebral integrity is important for detecting the consciousness level. Meanwhile, we investigate the influence of different EEG collection duration and number of channels, in order to help make the appropriate choices for clinics.Significance. The DOCTer framework significantly improves the accuracy of DOC diagnosis, helpful for developing appropriate treatment programs. Findings derived from the large-scale dataset provide valuable insights for clinics.
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Affiliation(s)
- Sha Zhao
- College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
- The State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Yue Cao
- School of Software Technology, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
- The State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Wei Yang
- College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
- The State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Jie Yu
- Department of Neurology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China
| | - Chuan Xu
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China
| | - Wei Dai
- Stanford University, 450 Jane Stanford Way, Stanford, CA 94305, United States of America
| | - Shijian Li
- College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
- The State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Gang Pan
- College of Computer Science and Technology, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
- The State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
- MOE Frontier Science Center for Brain Science and Brain-Machine Integration, Zhejiang University, Hangzhou, People's Republic of China
| | - Benyan Luo
- The State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
- Department of Neurology, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China
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Dong L, Yang R, Xie A, Wang X, Feng Z, Li F, Ren J, Li J, Yao D. Transforming of scalp EEGs with different channel locations by REST for comparative study. Brain Res Bull 2024; 217:111064. [PMID: 39232993 DOI: 10.1016/j.brainresbull.2024.111064] [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: 05/20/2024] [Revised: 08/11/2024] [Accepted: 08/30/2024] [Indexed: 09/06/2024]
Abstract
OBJECTIVE The diversity of electrode placement systems brought the problem of channel location harmonization in large-scale electroencephalography (EEG) applications to the forefront. Therefore, our goal was to resolve this problem by introducing and assessing the reference electrode standardization technique (REST) to transform EEGs into a common electrode distribution with computational zero reference at infinity offline. METHODS Simulation and eye-closed resting-state EEG datasets were used to investigate the performance of REST for EEG signals and power configurations. RESULTS REST produced small errors (the root mean square error (RMSE): 0.2936-0.4583; absolute errors: 0.2343-0.3657) and high correlations (>0.9) between the estimated signals and true ones. The comparison of configuration similarities in power among various electrode distributions revealed that REST induced infinity reference could maintain a perfect performance similar (>0.9) to that of true one. CONCLUSION These results demonstrated that REST transformation could be adopted to resolve the channel location harmonization problem in large-scale EEG applications.
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Affiliation(s)
- Li Dong
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, China; Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu, China
| | - Runchen Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Ao Xie
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Xinrui Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Zongwen Feng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Fali Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Junru Ren
- Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu, China
| | - Jianfu Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, Chengdu 2019RU035, China; Sichuan Institute for Brain Science and Brain-Inspired Intelligence, Chengdu, China; School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China.
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Zhou LY, Peng LJ, Liu YF, Wang SW, Qiu Y, Chen SJ, Feng MM, Liu J, Wu SS, Luo T, Liu ZY, Wu HJ, Ge JP, Reinhardt JD, Lu X. Transcutaneous auricular vagal nerve stimulation for consciousness recovery in patients with prolonged disorders of consciousness (TAVREC): study protocol for a multicenter, triple-blind, randomized controlled trial in China. BMJ Open 2024; 14:e083888. [PMID: 38821572 PMCID: PMC11149147 DOI: 10.1136/bmjopen-2024-083888] [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] [Received: 01/02/2024] [Accepted: 03/22/2024] [Indexed: 06/02/2024] Open
Abstract
INTRODUCTION Prolonged disorders of consciousness (pDoC) are a catastrophic condition following brain injury with few therapeutic options. Transcutaneous auricular vagal nerve stimulation (taVNS), a safe, non-invasive intervention modulating thalamo-cortical connectivity and brain function, is a possible treatment option of pDoC. We developed a protocol for a randomised controlled study to evaluate the effectiveness of taVNS on consciousness recovery in patients with pDoC (TAVREC). METHODS AND ANALYSIS The TAVREC programme is a multicentre, triple-blind, randomised controlled trial with 4 weeks intervention followed by 4 weeks follow-up period. A minimum number of 116 eligible pDoC patients will be recruited and randomly receive either: (1) conventional therapy plus taVNS (30 s monophasic square current of pulse width 300 μs, frequency of 25 Hz and intensity of 1 mA followed by 30 s rest, 60 min, two times per day, for 4 weeks); or (2) conventional therapy plus taVNS placebo. Primary outcome of TAVREC is the rate of improved consciousness level based on the Coma Recovery Scale-Revised (CRS-R) at week 4. Secondary outcomes are CRS-R total and subscale scores, Glasgow Coma Scale score, Full Outline of UnResponsiveness score, ECG parameters, brainstem auditory evoked potential, upper somatosensory evoked potential, neuroimaging parameters from positron emission tomography/functional MRI, serum biomarkers associated with consciousness level and adverse events. ETHICS AND DISSEMINATION This study was reviewed and approved by the Research Ethics Committee of the First Affiliated Hospital of Nanjing Medical University (Reference number: 2023-SR-392). Findings will be disseminated in a peer-reviewed journal and presented at relevant conferences. TRIAL REGISTRATION NUMBER ChiCTR2300073950.
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Affiliation(s)
- Long-Yun Zhou
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Li-Jun Peng
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Ya-Feng Liu
- Department of Critical Care Medicine, Nanjing Zijin Hospital, Nanjing, People's Republic of China
| | - Shu-Wei Wang
- Department of Critical Care Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People's Republic of China
| | - Yue Qiu
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, People's Republic of China
| | - Si-Jing Chen
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Ming-Ming Feng
- Department of Critical Care Medicine, Nanjing Zijin Hospital, Nanjing, People's Republic of China
| | - Jin Liu
- Institute of Clinical Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Shan-Shan Wu
- Department of Critical Care Medicine, Nanjing Zijin Hospital, Nanjing, People's Republic of China
| | - Ting Luo
- Department of Critical Care Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People's Republic of China
| | - Zhen-Yu Liu
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Hui-Juan Wu
- Department of Critical Care Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People's Republic of China
| | - Jiang-Ping Ge
- Nanjing Zijin Hospital, Nanjing, People's Republic of China
| | - Jan D Reinhardt
- Institute for Disaster Management and Reconstruction, Sichuan University, Chengdu, People's Republic of China
- Department of Health Sciences and Medicine, University of Lucerne, Lucerne, Switzerland
- Rehabilitation Research Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
| | - Xiao Lu
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, People's Republic of China
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Wan X, Zhang Y, Li Y, Song W. Effects of parietal repetitive transcranial magnetic stimulation in prolonged disorders of consciousness: A pilot study. Heliyon 2024; 10:e30192. [PMID: 38707352 PMCID: PMC11066627 DOI: 10.1016/j.heliyon.2024.e30192] [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: 09/22/2023] [Revised: 04/21/2024] [Accepted: 04/22/2024] [Indexed: 05/07/2024] Open
Abstract
Objective Although the parietal cortex is related to consciousness, the dorsolateral prefrontal and primary motor cortices are the usual targets for repetitive transcranial magnetic stimulation (rTMS) for prolonged disorders of consciousness (pDoC). Herein, we applied parietal rTMS to patients with pDoC, to verify its neurobehavioral effects and explore a new potential rTMS target. Materials and methods Twenty-six patients with pDoC were assigned to a rTMS or sham group. The rTMS group received 10 sessions of parietal rTMS; the sham group received 10 sessions of sham stimulation. The Coma Recovery Scale-Revised (CRS-R) and event-related potential (ERP) were collected before and after the 10 sessions or sham sessions. Results After the 10 sessions, the rTMS group showed: a significant CRS-R score increase; ERP appearance of a P300 waveform and significantly increased Fz amplitudes; increased potentials on topographic mapping, especially in the left prefrontal cortex; and an increase in delta and theta band powers at Fz, Cz, and Pz. The sham group did not show such changes in CRS-R score or ERP results statistically. Conclusion Parietal rTMS shows promise as a novel intervention in the recovery of consciousness in pDoC. It showed neurobehavioral enhancement of residual brain function and may promote frontal activity by enhancing frontal-parietal connections. The parietal cortex may thus be an alternative for rTMS therapy protocols.
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Affiliation(s)
- Xiaoping Wan
- Department of Rehabilitation Medicine, Xuan Wu Hospital, Capital Medical University, No. 45 Chang Chun Street, Beijing, 100053, China
| | - Ye Zhang
- Department of Rehabilitation Medicine, Xuan Wu Hospital, Capital Medical University, No. 45 Chang Chun Street, Beijing, 100053, China
| | - Yanhua Li
- Department of Rehabilitation Medicine, Xuan Wu Hospital, Capital Medical University, No. 45 Chang Chun Street, Beijing, 100053, China
| | - Weiqun Song
- Department of Rehabilitation Medicine, Xuan Wu Hospital, Capital Medical University, No. 45 Chang Chun Street, Beijing, 100053, China
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Toplutaş E, Aydın F, Hanoğlu L. EEG Microstate Analysis in Patients with Disorders of Consciousness and Its Clinical Significance. Brain Topogr 2024; 37:377-387. [PMID: 36735192 DOI: 10.1007/s10548-023-00939-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 01/19/2023] [Indexed: 02/04/2023]
Abstract
Disorders of Consciousness are divided into two major categories such as vegetative and minimally conscious states. Objective measures that allow correct identification of patients with vegetative and minimally conscious state are needed. EEG microstate analysis is a promising approach that we believe has the potential to be effective in examining the resting state activities of the brain in different stages of consciousness by allowing the proper identification of vegetative and minimally conscious patients. As a result, we try to identify clinical evaluation scales and microstate characteristics with resting state EEGs from individuals with disorders of consciousness. Our prospective observational study included 28 individuals with a disorder of consciousness. Control group included 18 healthy subjects with proper EEG data. We made clinical evaluations using patient behavior scales. We also analyzed the EEGs using microstate analysis. In our study, microstate D coverage differed substantially between vegetative and minimally conscious state patients. Also, there was a strong connection between microstate D characteristics and clinical scale scores. Consequently, we have demonstrated that the most accurate parameter for representing consciousness level is microstate D. Microstate analysis appears to be a strong option for future use in the diagnosis, follow-up, and treatment response of patients with Disorders of Consciousness.
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Affiliation(s)
- Eren Toplutaş
- Department of Neurology, Istanbul Eyupsultan Public Hospital, Istanbul, Turkey.
- Program of Neuroscience Ph.D., Graduate School of Health Sciences,, Istanbul Medipol University, Istanbul, Turkey.
| | - Fatma Aydın
- Program of Neuroscience Ph.D., Graduate School of Health Sciences,, Istanbul Medipol University, Istanbul, Turkey
| | - Lütfü Hanoğlu
- Department of Neurology, School of Medicine, Istanbul Medipol University, Istanbul, Turkey
- Neuroimaging and Neuromodulation Lab, Clinical Electrophysiology, REMER, Istanbul Medipol University, Istanbul, Turkey
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Herbert C. Brain-computer interfaces and human factors: the role of language and cultural differences-Still a missing gap? Front Hum Neurosci 2024; 18:1305445. [PMID: 38665897 PMCID: PMC11043545 DOI: 10.3389/fnhum.2024.1305445] [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: 10/01/2023] [Accepted: 02/02/2024] [Indexed: 04/28/2024] Open
Abstract
Brain-computer interfaces (BCIs) aim at the non-invasive investigation of brain activity for supporting communication and interaction of the users with their environment by means of brain-machine assisted technologies. Despite technological progress and promising research aimed at understanding the influence of human factors on BCI effectiveness, some topics still remain unexplored. The aim of this article is to discuss why it is important to consider the language of the user, its embodied grounding in perception, action and emotions, and its interaction with cultural differences in information processing in future BCI research. Based on evidence from recent studies, it is proposed that detection of language abilities and language training are two main topics of enquiry of future BCI studies to extend communication among vulnerable and healthy BCI users from bench to bedside and real world applications. In addition, cultural differences shape perception, actions, cognition, language and emotions subjectively, behaviorally as well as neuronally. Therefore, BCI applications should consider cultural differences in information processing to develop culture- and language-sensitive BCI applications for different user groups and BCIs, and investigate the linguistic and cultural contexts in which the BCI will be used.
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Affiliation(s)
- Cornelia Herbert
- Applied Emotion and Motivation Psychology, Institute of Psychology and Education, Ulm University, Ulm, Germany
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Mathur R, Meyfroidt G, Robba C, Stevens RD. Neuromonitoring in the ICU - what, how and why? Curr Opin Crit Care 2024; 30:99-105. [PMID: 38441121 DOI: 10.1097/mcc.0000000000001138] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
PURPOSE OF REVIEW We selectively review emerging noninvasive neuromonitoring techniques and the evidence that supports their use in the ICU setting. The focus is on neuromonitoring research in patients with acute brain injury. RECENT FINDINGS Noninvasive intracranial pressure evaluation with optic nerve sheath diameter measurements, transcranial Doppler waveform analysis, or skull mechanical extensometer waveform recordings have potential safety and resource-intensity advantages when compared to standard invasive monitors, however each of these techniques has limitations. Quantitative electroencephalography can be applied for detection of cerebral ischemia and states of covert consciousness. Near-infrared spectroscopy may be leveraged for cerebral oxygenation and autoregulation computation. Automated quantitative pupillometry and heart rate variability analysis have been shown to have diagnostic and/or prognostic significance in selected subtypes of acute brain injury. Finally, artificial intelligence is likely to transform interpretation and deployment of neuromonitoring paradigms individually and when integrated in multimodal paradigms. SUMMARY The ability to detect brain dysfunction and injury in critically ill patients is being enriched thanks to remarkable advances in neuromonitoring data acquisition and analysis. Studies are needed to validate the accuracy and reliability of these new approaches, and their feasibility and implementation within existing intensive care workflows.
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Affiliation(s)
- Rohan Mathur
- Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Geert Meyfroidt
- Department of Intensive Care Medicine, University Hospitals Leuven, Belgium and Laboratory of Intensive Care Medicine, Department of Cellular and Molecular Medicine, KU Leuven, Belgium
| | - Chiara Robba
- IRCCS Ospedale Policlinico San Martino, Genova, Italy
- Dipartimento di Scienze Chirurgiche e Diagnostiche Integrate, Università degli Studi di Genova, Genova, Italy
| | - Robert D Stevens
- Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore MD, USA
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Casarotto S, Hassan G, Rosanova M, Sarasso S, Derchi CC, Trimarchi PD, Viganò A, Russo S, Fecchio M, Devalle G, Navarro J, Massimini M, Comanducci A. Dissociations between spontaneous electroencephalographic features and the perturbational complexity index in the minimally conscious state. Eur J Neurosci 2024; 59:934-947. [PMID: 38440949 DOI: 10.1111/ejn.16299] [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: 03/22/2023] [Revised: 12/21/2023] [Accepted: 02/13/2024] [Indexed: 03/06/2024]
Abstract
The analysis of spontaneous electroencephalogram (EEG) is a cornerstone in the assessment of patients with disorders of consciousness (DoC). Although preserved EEG patterns are highly suggestive of consciousness even in unresponsive patients, moderately or severely abnormal patterns are difficult to interpret. Indeed, growing evidence shows that consciousness can be present despite either large delta or reduced alpha activity in spontaneous EEG. Quantifying the complexity of EEG responses to direct cortical perturbations (perturbational complexity index [PCI]) may complement the observational approach and provide a reliable assessment of consciousness even when spontaneous EEG features are inconclusive. To seek empirical evidence of this hypothesis, we compared PCI with EEG spectral measures in the same population of minimally conscious state (MCS) patients (n = 40) hospitalized in rehabilitation facilities. We found a remarkable variability in spontaneous EEG features across MCS patients as compared with healthy controls: in particular, a pattern of predominant delta and highly reduced alpha power-more often observed in vegetative state/unresponsive wakefulness syndrome (VS/UWS) patients-was found in a non-negligible number of MCS patients. Conversely, PCI values invariably fell above an externally validated empirical cutoff for consciousness in all MCS patients, consistent with the presence of clearly discernible, albeit fleeting, behavioural signs of awareness. These results confirm that, in some MCS patients, spontaneous EEG rhythms may be inconclusive about the actual capacity for consciousness and suggest that a perturbational approach can effectively compensate for this pitfall with practical implications for the individual patient's stratification and tailored rehabilitation.
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Affiliation(s)
- Silvia Casarotto
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Gabriel Hassan
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | | | | | | | - Simone Russo
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Matteo Fecchio
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Guya Devalle
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Jorge Navarro
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Marcello Massimini
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Angela Comanducci
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
- Università Campus Bio-Medico di Roma, Rome, Italy
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Comanducci A, Casarotto S, Rosanova M, Derchi CC, Viganò A, Pirastru A, Blasi V, Cazzoli M, Navarro J, Edlow BL, Baglio F, Massimini M. Unconsciousness or unresponsiveness in akinetic mutism? Insights from a multimodal longitudinal exploration. Eur J Neurosci 2024; 59:860-873. [PMID: 37077023 DOI: 10.1111/ejn.15994] [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: 12/30/2022] [Revised: 04/02/2023] [Accepted: 04/17/2023] [Indexed: 04/21/2023]
Abstract
The clinical assessment of patients with disorders of consciousness (DoC) relies on the observation of behavioural responses to standardised sensory stimulation. However, several medical comorbidities may directly impair the production of reproducible and appropriate responses, thus reducing the sensitivity of behaviour-based diagnoses. One such comorbidity is akinetic mutism (AM), a rare neurological syndrome characterised by the inability to initiate volitional motor responses, sometimes associated with clinical presentations that overlap with those of DoC. In this paper, we describe the case of a patient with large bilateral mesial frontal lesions, showing prolonged behavioural unresponsiveness and severe disorganisation of electroencephalographic (EEG) background, compatible with a vegetative state/unresponsive wakefulness syndrome (VS/UWS). By applying an unprecedented multimodal battery of advanced imaging and electrophysiology-based techniques (AIE) encompassing spontaneous EEG, evoked potentials, event-related potentials, transcranial magnetic stimulation combined with EEG and structural and functional MRI, we provide the following: (i) a demonstration of the preservation of consciousness despite unresponsiveness in the context of AM, (ii) a plausible neurophysiological explanation for behavioural unresponsiveness and its subsequent recovery during rehabilitation stay and (iii) novel insights into the relationships between DoC, AM and parkinsonism. The present case offers proof-of-principle evidence supporting the clinical utility of a multimodal hierarchical workflow that combines AIEs to detect covert signs of consciousness in unresponsive patients.
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Affiliation(s)
| | - Silvia Casarotto
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
- Department Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Mario Rosanova
- Department Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | | | | | | | - Valeria Blasi
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Marta Cazzoli
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Jorge Navarro
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | | | - Marcello Massimini
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
- Department Biomedical and Clinical Sciences, University of Milan, Milan, Italy
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12
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Kikuchi-Hayakawa H, Ishikawa H, Suda K, Gondo Y, Hirasawa G, Nakamura H, Takada M, Kawai M, Matsuda K. Effects of Lacticaseibacillus paracasei Strain Shirota on Daytime Performance in Healthy Office Workers: A Double-Blind, Randomized, Crossover, Placebo-Controlled Trial. Nutrients 2023; 15:5119. [PMID: 38140378 PMCID: PMC10745872 DOI: 10.3390/nu15245119] [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: 10/31/2023] [Revised: 12/12/2023] [Accepted: 12/14/2023] [Indexed: 12/24/2023] Open
Abstract
Lacticaseibacillus paracasei strain Shirota (LcS) modulates psychological homeostasis via the gut-brain axis. To explore the possible efficacy of LcS for improving daytime performance, we conducted a double-blind, randomized, crossover, placebo-controlled study of 12 healthy office workers with sleep complaints. The participants received fermented milk containing viable LcS (daily intake of 1 × 1011 colony-forming units) and non-fermented placebo milk, each for a 4-week period. In the last week of each period, the participants underwent assessments of their subjective mood and measurements of physiological state indicators via an electroencephalogram (EEG) and heart rate variability in the morning and afternoon. The attention score in the afternoon as assessed by the visual analog scale was higher in the LcS intake period than in the placebo intake period (p = 0.041). Theta power on EEG measured at rest or during an auditory oddball task in the afternoon was significantly lower in the LcS period than in the placebo period (p = 0.025 and 0.009, respectively). The change rate of theta power was associated with the change in attention score. Treatment-associated changes were also observed in heart rate and the sympathetic nerve activity index. These results indicate that LcS has possible efficacy for improving daytime performance, supported by observations of the related physiological state indicators.
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Affiliation(s)
| | - Hiroshi Ishikawa
- Yakult Central Institute, 5-11 Izumi, Kunitachi-shi, Tokyo 186-8650, Japan
| | - Kazunori Suda
- Yakult Central Institute, 5-11 Izumi, Kunitachi-shi, Tokyo 186-8650, Japan
- Yakult Honsha European Research Center for Microbiology VOF, Technologiepark 94 bus 3, 9052 Ghent, Belgium
| | - Yusuke Gondo
- Yakult Central Institute, 5-11 Izumi, Kunitachi-shi, Tokyo 186-8650, Japan
| | - Genki Hirasawa
- Yakult Central Institute, 5-11 Izumi, Kunitachi-shi, Tokyo 186-8650, Japan
| | - Hayato Nakamura
- Yakult Central Institute, 5-11 Izumi, Kunitachi-shi, Tokyo 186-8650, Japan
| | - Mai Takada
- Yakult Central Institute, 5-11 Izumi, Kunitachi-shi, Tokyo 186-8650, Japan
| | - Mitsuhisa Kawai
- Yakult Central Institute, 5-11 Izumi, Kunitachi-shi, Tokyo 186-8650, Japan
| | - Kazunori Matsuda
- Yakult Central Institute, 5-11 Izumi, Kunitachi-shi, Tokyo 186-8650, Japan
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13
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Chowdhury A, van Lutterveld R, Laukkonen RE, Slagter HA, Ingram DM, Sacchet MD. Investigation of advanced mindfulness meditation "cessation" experiences using EEG spectral analysis in an intensively sampled case study. Neuropsychologia 2023; 190:108694. [PMID: 37777153 PMCID: PMC10843092 DOI: 10.1016/j.neuropsychologia.2023.108694] [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: 03/25/2023] [Revised: 09/20/2023] [Accepted: 09/22/2023] [Indexed: 10/02/2023]
Abstract
Mindfulness meditation is a contemplative practice informed by Buddhism that targets the development of present-focused awareness and non-judgment of experience. Interest in mindfulness is burgeoning, and it has been shown to be effective in improving mental and physical health in clinical and non-clinical contexts. In this report, for the first time, we used electroencephalography (EEG) combined with a neurophenomenological approach to examine the neural signature of "cessation" events, which are dramatic experiences of complete discontinuation in awareness similar to the loss of consciousness, which are reported to be experienced by very experienced meditators, and are proposed to be evidence of mastery of mindfulness meditation. We intensively sampled these cessations as experienced by a single advanced meditator (with over 23,000 h of meditation training) and analyzed 37 cessation events collected in 29 EEG sessions between November 12, 2019, and March 11, 2020. Spectral analyses of the EEG data surrounding cessations showed that these events were marked by a large-scale alpha-power decrease starting around 40 s before their onset, and that this alpha-power was lowest immediately following a cessation. Region-of-interest (ROI) based examination of this finding revealed that this alpha-suppression showed a linear decrease in the occipital and parietal regions of the brain during the pre-cessation time period. Additionally, there were modest increases in theta power for the central, parietal, and right temporal ROIs during the pre-cessation timeframe, whereas power in the Delta and Beta frequency bands were not significantly different surrounding cessations. By relating cessations to objective and intrinsic measures of brain activity (i.e., EEG power) that are related to consciousness and high-level psychological functioning, these results provide evidence for the ability of experienced meditators to voluntarily modulate their state of consciousness and lay the foundation for studying these unique states using a neuroscientific approach.
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Affiliation(s)
- Avijit Chowdhury
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
| | - Remko van Lutterveld
- Brain Research and Innovation Centre, Dutch Ministry of Defence and Department of Psychiatry, University Medical Center, Utrecht, the Netherlands.
| | - Ruben E Laukkonen
- Faculty of Health, Southern Cross University, Gold Coast, QLD, Australia.
| | - Heleen A Slagter
- Department of Experimental and Applied Psychology, Vrije Universiteit Amsterdam, the Netherlands; Institute for Brain and Behavior, Vrije Universiteit Amsterdam, the Netherlands.
| | | | - Matthew D Sacchet
- Meditation Research Program, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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Ling Y, Xu C, Wen X, Li J, Gao J, Luo B. Cortical responses to auditory stimulation predict the prognosis of patients with disorders of consciousness. Clin Neurophysiol 2023; 153:11-20. [PMID: 37385110 DOI: 10.1016/j.clinph.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 05/15/2023] [Accepted: 06/03/2023] [Indexed: 07/01/2023]
Abstract
OBJECTIVE This study aimed to assess the prognosis of patients with disorders of consciousness (DoC) using auditory stimulation with electroencephalogram (EEG) recordings. METHODS We enrolled 72 patients with DoC in the study, which involved subjecting patients to auditory stimulation while EEG responses were recorded. Coma Recovery Scale-Revised (CRS-R) scores and Glasgow Outcome Scale (GOS) were determined for each patient and followed up for three months. A frequency spectrum analysis was performed on the EEG recordings. Finally, the power spectral density (PSD) index was used to predict the prognosis of patients with DoC based on a support vector machine (SVM) model. RESULTS Power spectral analyses revealed that the cortical response to auditory stimulation showed a decreasing trend with decreasing consciousness levels. Auditory stimulation-induced changes in absolute PSD at the delta and theta bands were positively correlated with the CRS-R and GOS scores. Furthermore, these cortical responses to auditory stimulation had a good ability to discriminate between good and poor prognoses of patients with DoC. CONCLUSIONS Auditory stimulation-induced changes in the PSD were highly predictive of DoC outcomes. SIGNIFICANCE Our findings showed that cortical responses to auditory stimulation may be an important electrophysiological indicator of prognosis in patients with DoC.
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Affiliation(s)
- Yi Ling
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310000, China
| | - Chuan Xu
- Department of Neurology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310016, China
| | - Xinrui Wen
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310000, China
| | - Jingqi Li
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou 311215, China
| | - Jian Gao
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou 311215, China
| | - Benyan Luo
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310000, China.
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15
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Wu Y, Li Z, Qu R, Wang Y, Li Z, Wang L, Zhao G, Feng K, Cheng Y, Yin S. Electroencephalogram-Based Brain Connectivity Analysis in Prolonged Disorders of Consciousness. Neural Plast 2023; 2023:4142053. [PMID: 37113750 PMCID: PMC10129427 DOI: 10.1155/2023/4142053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2023] [Revised: 03/03/2023] [Accepted: 04/02/2023] [Indexed: 04/29/2023] Open
Abstract
Background Prolonged disorders of consciousness (pDOC) are common in neurology and place a heavy burden on families and society. This study is aimed at investigating the characteristics of brain connectivity in patients with pDOC based on quantitative EEG (qEEG) and extending a new direction for the evaluation of pDOC. Methods Participants were divided into a control group (CG) and a DOC group by the presence or absence of pDOC. Participants underwent magnetic resonance imaging (MRI) T1 three-dimensional magnetization with a prepared rapid acquisition gradient echo (3D-T1-MPRAGE) sequence, and video EEG data were collected. After calculating the power spectrum by EEG data analysis tool, DTABR ((δ + θ)/(α + β) ratio), Pearson's correlation coefficient (Pearson r), Granger's causality, and phase transfer entropy (PTE), we performed statistical analysis between two groups. Finally, receiver operating characteristic (ROC) curves of connectivity metrics were made. Results The proportion of power in frontal, central, parietal, and temporal regions in the DOC group was lower than that in the CG. The percentage of delta power in the DOC group was significantly higher than that in the CG, the DTABR in the DOC group was higher than that in the CG, and the value was inverted. The Pearson r of the DOC group was higher than that of CG. The Pearson r of the delta band (Z = -6.71, P < 0.01), theta band (Z = -15.06, P < 0.01), and alpha band (Z = -28.45, P < 0.01) were statistically significant. Granger causality showed that the intensity of directed connections between the two hemispheres in the DOC group at the same threshold was significantly reduced (Z = -82.43, P < 0.01). The PTE of each frequency band in the DOC group was lower than that in the CG. The PTE of the delta band (Z = -42.68, P < 0.01), theta band (Z = -56.79, P < 0.01), the alpha band (Z = -35.11, P < 0.01), and beta band (Z = -63.74, P < 0.01) had statistical significance. Conclusion Brain connectivity analysis based on EEG has the advantages of being noninvasive, convenient, and bedside. The Pearson r of DTABR, delta, theta, and alpha bands, Granger's causality, and PTE of the delta, theta, alpha, and beta bands can be used as biological markers to distinguish between pDOC and healthy people, especially when behavior evaluation is difficult or ambiguous; it can supplement clinical diagnosis.
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Affiliation(s)
- Yuzhang Wu
- Clinical College of Neurology, Neurosurgery, and Neurorehabilitation, Tianjin Medical University, Tianjin 300000, China
| | - Zhitao Li
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300000, China
| | - Ruowei Qu
- State Key Laboratory of Reliability and Intelligence of Electrical Equipment, Hebei University of Technology, Tianjin 300000, China
| | - Yangang Wang
- Clinical College of Neurology, Neurosurgery, and Neurorehabilitation, Tianjin Medical University, Tianjin 300000, China
| | - Zhongzhen Li
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300000, China
| | - Le Wang
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300000, China
| | - Guangrui Zhao
- Clinical College of Neurology, Neurosurgery, and Neurorehabilitation, Tianjin Medical University, Tianjin 300000, China
| | - Keke Feng
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300000, China
| | - Yifeng Cheng
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300000, China
| | - Shaoya Yin
- Department of Neurosurgery, Tianjin Huanhu Hospital, Tianjin 300000, China
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16
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Buccellato A, Zang D, Zilio F, Gomez-Pilar J, Wang Z, Qi Z, Zheng R, Xu Z, Wu X, Bisiacchi P, Felice AD, Mao Y, Northoff G. Disrupted relationship between intrinsic neural timescales and alpha peak frequency during unconscious states - A high-density EEG study. Neuroimage 2023; 265:119802. [PMID: 36503159 DOI: 10.1016/j.neuroimage.2022.119802] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 11/22/2022] [Accepted: 12/07/2022] [Indexed: 12/13/2022] Open
Abstract
Our brain processes the different timescales of our environment's temporal input stochastics. Is such a temporal input processing mechanism key for consciousness? To address this research question, we calculated measures of input processing on shorter (alpha peak frequency, APF) and longer (autocorrelation window, ACW) timescales on resting-state high-density EEG (256 channels) recordings and compared them across different consciousness levels (awake/conscious, ketamine and sevoflurane anaesthesia, unresponsive wakefulness, minimally conscious state). We replicate and extend previous findings of: (i) significantly longer ACW values, consistently over all states of unconsciousness, as measured with ACW-0 (an unprecedented longer version of the well-know ACW-50); (ii) significantly slower APF values, as measured with frequency sliding, in all four unconscious states. Most importantly, we report a highly significant correlation of ACW-0 and APF in the conscious state, while their relationship is disrupted in the unconscious states. In sum, we demonstrate the relevance of the brain's capacity for input processing on shorter (APF) and longer (ACW) timescales - including their relationship - for consciousness. Albeit indirectly, e.g., through the analysis of electrophysiological activity at rest, this supports the mechanism of temporo-spatial alignment to the environment's temporal input stochastics, through relating different neural timescales, as one key predisposing factor of consciousness.
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Affiliation(s)
- Andrea Buccellato
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy.
| | - Di Zang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Federico Zilio
- Department of Philosophy, Sociology, Education and Applied Psychology, University of Padova, Padua, Italy
| | - Javier Gomez-Pilar
- Biomedical Engineering Group, University of Valladolid, Paseo de Belén, 15, Valladolid 47011, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Valladolid, Spain
| | - Zhe Wang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Ruizhe Zheng
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Zeyu Xu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Xuehai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China
| | - Patrizia Bisiacchi
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of General Psychology, University of Padova, Padova, Italy
| | - Alessandra Del Felice
- Padova Neuroscience Center, University of Padova, Padova, Italy; Department of Neuroscience, Section of Rehabilitation, University of Padova, Padova, Italy
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University,Shanghai, 200040, China; Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China; State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200032, China; National Center for Neurological Disorders, Shanghai, 200040, China; Neurosurgical Institute of Fudan University, Shanghai, 200040, China; Shanghai Clinical Medical Center of Neurosurgery, Shanghai, 200040, China.
| | - Georg Northoff
- Mind, Brain Imaging and Neuroethics Research Unit, Institute of Mental Health, Royal Ottawa Mental Health Centre and University of Ottawa, Ottawa, Ontario K1Z7K4, Canada; Mental Health Center, Zhejiang University School of Medicine, Hangzhou 310013, Zhejiang Province, China; Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310013, Zhejiang Province, China.
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17
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Ferré F, Heine L, Naboulsi E, Gobert F, Beaudoin-Gobert M, Dailler F, Buffières W, Corneyllie A, Sarton B, Riu B, Luauté J, Silva S, Perrin F. Self-processing in coma, unresponsive wakefulness syndrome and minimally conscious state. Front Hum Neurosci 2023; 17:1145253. [PMID: 37125347 PMCID: PMC10132704 DOI: 10.3389/fnhum.2023.1145253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 03/23/2023] [Indexed: 05/02/2023] Open
Abstract
Introduction Behavioral and cerebral dissociation has been now clearly established in some patients with acquired disorders of consciousness (DoC). Altogether, these studies mainly focused on the preservation of high-level cognitive markers in prolonged DoC, but did not specifically investigate lower but key-cognitive functions to consciousness emergence, such as the ability to take a first-person perspective, notably at the acute stage of coma. We made the hypothesis that the preservation of self-recognition (i) is independent of the behavioral impairment of consciousness, and (ii) can reflect the ability to recover consciousness. Methods Hence, using bedside Electroencephalography (EEG) recordings, we acquired, in a large cohort of 129 severely brain damaged patients, the brain response to the passive listening of the subject's own name (SON) and unfamiliar other first names (OFN). One hundred and twelve of them (mean age ± SD = 46 ± 18.3 years, sex ratio M/F: 71/41) could be analyzed for the detection of an individual and significant discriminative P3 event-related brain response to the SON as compared to OFN ('SON effect', primary endpoint assessed by temporal clustering permutation tests). Results Patients were either coma (n = 38), unresponsive wakefulness syndrome (UWS, n = 30) or minimally conscious state (MCS, n = 44), according to the revised version of the Coma Recovery Scale (CRS-R). Overall, 33 DoC patients (29%) evoked a 'SON effect'. This electrophysiological index was similar between coma (29%), MCS (23%) and UWS (34%) patients (p = 0.61). MCS patients at the time of enrolment were more likely to emerged from MCS (EMCS) at 6 months than coma and UWS patients (p = 0.013 for comparison between groups). Among the 72 survivors' patients with event-related responses recorded within 3 months after brain injury, 75% of the 16 patients with a SON effect were EMCS at 6 months, while 59% of the 56 patients without a SON effect evolved to this favorable behavioral outcome. Discussion About 30% of severely brain-damaged patients suffering from DoC are capable to process salient self-referential auditory stimuli, even in case of absence of behavioral detection of self-conscious processing. We suggest that self-recognition covert brain ability could be an index of consciousness recovery, and thus could help to predict good outcome.
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Affiliation(s)
- Fabrice Ferré
- CAP Team (Cognition Auditive et Psychoacoustique), Lyon Neuroscience Research Centre (Université Claude Bernard Lyon 1, INSERM U1028, CNRS UMR5292), Bron Cedex, France
- Intensive Care Unit, Purpan University Teaching Hospital, Place du Dr Joseph Baylac, Toulouse CEDEX 9, France
- Toulouse NeuroImaging Centre (ToNIC), UPS—INSERM UMR, Place du Dr Joseph Baylac, Purpan University Teaching Hospital, Toulouse CEDEX 3, France
- *Correspondence: Fabrice Ferré,
| | - Lizette Heine
- CAP Team (Cognition Auditive et Psychoacoustique), Lyon Neuroscience Research Centre (Université Claude Bernard Lyon 1, INSERM U1028, CNRS UMR5292), Bron Cedex, France
| | - Edouard Naboulsi
- Intensive Care Unit, Purpan University Teaching Hospital, Place du Dr Joseph Baylac, Toulouse CEDEX 9, France
| | - Florent Gobert
- CAP Team (Cognition Auditive et Psychoacoustique), Lyon Neuroscience Research Centre (Université Claude Bernard Lyon 1, INSERM U1028, CNRS UMR5292), Bron Cedex, France
- Neuro-Intensive Care Unit, Hospices Civils de Lyon, Neurological Hospital Pierre-Wertheimer, Bron, France
- Trajectoires Team, Lyon Neuroscience Research Centre (Université Claude Bernard Lyon 1, INSERM U1028, CNRS UMR5292), Bron, France
| | - Maude Beaudoin-Gobert
- Physical Medicine and Rehabilitation Department, Henry-Gabrielle Hospital, Hospices Civils de Lyon, Saint Genis Laval, France
| | - Frédéric Dailler
- Neuro-Intensive Care Unit, Hospices Civils de Lyon, Neurological Hospital Pierre-Wertheimer, Bron, France
| | - William Buffières
- Intensive Care Unit, Purpan University Teaching Hospital, Place du Dr Joseph Baylac, Toulouse CEDEX 9, France
- Toulouse NeuroImaging Centre (ToNIC), UPS—INSERM UMR, Place du Dr Joseph Baylac, Purpan University Teaching Hospital, Toulouse CEDEX 3, France
| | - Alexandra Corneyllie
- CAP Team (Cognition Auditive et Psychoacoustique), Lyon Neuroscience Research Centre (Université Claude Bernard Lyon 1, INSERM U1028, CNRS UMR5292), Bron Cedex, France
| | - Benjamine Sarton
- Intensive Care Unit, Purpan University Teaching Hospital, Place du Dr Joseph Baylac, Toulouse CEDEX 9, France
- Toulouse NeuroImaging Centre (ToNIC), UPS—INSERM UMR, Place du Dr Joseph Baylac, Purpan University Teaching Hospital, Toulouse CEDEX 3, France
| | - Béatrice Riu
- Intensive Care Unit, Purpan University Teaching Hospital, Place du Dr Joseph Baylac, Toulouse CEDEX 9, France
| | - Jacques Luauté
- Physical Medicine and Rehabilitation Department, Henry-Gabrielle Hospital, Hospices Civils de Lyon, Saint Genis Laval, France
| | - Stein Silva
- Intensive Care Unit, Purpan University Teaching Hospital, Place du Dr Joseph Baylac, Toulouse CEDEX 9, France
- Toulouse NeuroImaging Centre (ToNIC), UPS—INSERM UMR, Place du Dr Joseph Baylac, Purpan University Teaching Hospital, Toulouse CEDEX 3, France
| | - Fabien Perrin
- CAP Team (Cognition Auditive et Psychoacoustique), Lyon Neuroscience Research Centre (Université Claude Bernard Lyon 1, INSERM U1028, CNRS UMR5292), Bron Cedex, France
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18
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Livinț Popa L, Chira D, Dăbală V, Hapca E, Popescu BO, Dina C, Cherecheș R, Strilciuc Ș, Mureșanu DF. Quantitative EEG as a Biomarker in Evaluating Post-Stroke Depression. Diagnostics (Basel) 2022; 13:diagnostics13010049. [PMID: 36611341 PMCID: PMC9818970 DOI: 10.3390/diagnostics13010049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 12/14/2022] [Accepted: 12/22/2022] [Indexed: 12/28/2022] Open
Abstract
Introduction: Post-stroke depression (PSD) has complex pathophysiology determined by various biological and psychological factors. Although it is a long-term complication of stroke, PSD is often underdiagnosed. Given the diagnostic role of quantitative electroencephalography (qEEG) in depression, it was investigated whether a possible marker of PSD could be identified by observing the evolution of the (Delta + Theta)/(Alpha + Beta) Ratio (DTABR), respectively the Delta/Alpha Ratio (DAR) values in post-stroke depressed patients (evaluated through the HADS-D subscale). Methods: The current paper analyzed the data of 57 patients initially selected from a randomized control trial (RCT) that assessed the role of N-Pep 12 in stroke rehabilitation. EEG recordings from the original trial database were analyzed using signal processing techniques, respecting the conditions (eyes open, eyes closed), and several cognitive tasks. Results: We observed two significant associations between the DTABR values and the HADS-D scores of post-stroke depressed patients for each of the two visits (V1 and V2) of the N-Pep 12 trial. We recorded the relationships in the Global (V1 = 30 to 120 days after stroke) and Frontal Extended (V2 = 90 days after stroke) regions during cognitive tasks that trained attention and working memory. For the second visit, the association between the analyzed variables was negative. Conclusions: As both our relationships were described during the cognitive condition, we can state that the neural networks involved in processing attention and working memory might go through a reorganization process one to four months after the stroke onset. After a period longer than six months, the process could localize itself at the level of frontal regions, highlighting a possible divergence between the local frontal dynamics and the subjective well-being of stroke survivors. QEEG parameters linked to stroke progression evolution (like DAR or DTABR) can facilitate the identification of the most common neuropsychiatric complication in stroke survivors.
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Affiliation(s)
- Livia Livinț Popa
- RoNeuro Institute for Neurological Research and Diagnostic, 400364 Cluj-Napoca, Romania
- Department of Neuroscience, Iuliu Hatieganu University of Medicine and Pharmacy, 400083 Cluj-Napoca, Romania
| | - Diana Chira
- RoNeuro Institute for Neurological Research and Diagnostic, 400364 Cluj-Napoca, Romania
- Correspondence:
| | - Victor Dăbală
- RoNeuro Institute for Neurological Research and Diagnostic, 400364 Cluj-Napoca, Romania
- Department of Neuroscience, Iuliu Hatieganu University of Medicine and Pharmacy, 400083 Cluj-Napoca, Romania
| | - Elian Hapca
- RoNeuro Institute for Neurological Research and Diagnostic, 400364 Cluj-Napoca, Romania
- Department of Neuroscience, Iuliu Hatieganu University of Medicine and Pharmacy, 400083 Cluj-Napoca, Romania
| | - Bogdan Ovidiu Popescu
- Department of Neuroscience, Carol Davila University of Medicine and Pharmacy, 050474 Bucharest, Romania
| | - Constantin Dina
- Faculty of Medicine, Ovidius University, 900527 Constanta, Romania
| | - Răzvan Cherecheș
- Department of Public Health, Babes-Bolyai University, 400294 Cluj-Napoca, Romania
| | - Ștefan Strilciuc
- RoNeuro Institute for Neurological Research and Diagnostic, 400364 Cluj-Napoca, Romania
- Department of Neuroscience, Iuliu Hatieganu University of Medicine and Pharmacy, 400083 Cluj-Napoca, Romania
| | - Dafin F. Mureșanu
- RoNeuro Institute for Neurological Research and Diagnostic, 400364 Cluj-Napoca, Romania
- Department of Neuroscience, Iuliu Hatieganu University of Medicine and Pharmacy, 400083 Cluj-Napoca, Romania
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Chen C, Han J, Zheng S, Zhang X, Sun H, Zhou T, Hu S, Yan X, Wang C, Wang K, Hu Y. Dynamic Changes of Brain Activity in Different Responsive Groups of Patients with Prolonged Disorders of Consciousness. Brain Sci 2022; 13:brainsci13010005. [PMID: 36671987 PMCID: PMC9856292 DOI: 10.3390/brainsci13010005] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 12/07/2022] [Accepted: 12/12/2022] [Indexed: 12/24/2022] Open
Abstract
As medical technology continues to improve, many patients diagnosed with brain injury survive after treatments but are still in a coma. Further, multiple clinical studies have demonstrated recovery of consciousness after transcranial direct current stimulation. To identify possible neurophysiological mechanisms underlying disorders of consciousness (DOCs) improvement, we examined the changes in multiple resting-state EEG microstate parameters after high-definition transcranial direct current stimulation (HD-tDCS). Because the left dorsolateral prefrontal cortex is closely related to consciousness, it is often chosen as a stimulation target for tDCS treatment of DOCs. A total of 21 patients diagnosed with prolonged DOCs were included in this study, and EEG microstate analysis of resting state EEG datasets was performed on all patients before and after interventions. Each of them underwent 10 anodal tDCS sessions of the left dorsolateral prefrontal cortex over 5 consecutive working days. According to whether the clinical manifestations improved, DOCs patients were divided into the responsive (RE) group and the non-responsive (N-RE) group. The dynamic changes of resting state EEG microstate parameters were also analyzed. After multiple HD-tDCS interventions, the duration and coverage of class C microstates in the RE group were significantly increased. This study also found that the transition between microstates A and C increased, while the transition between microstates B and D decreased in the responsive group. However, these changes in EEG microstate parameters in the N-RE group have not been reported. Our findings suggest that EEG neural signatures have the potential to assess consciousness states and that improvement in the dynamics of brain activity was associated with the recovery of DOCs. This study extends our understanding of the neural mechanism of DOCs patients in consciousness recovery.
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Affiliation(s)
- Chen Chen
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Jinying Han
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Shuang Zheng
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Xintong Zhang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
| | - Haibo Sun
- The First Clinical College of Anhui Medical University, Hefei 230032, China
| | - Ting Zhou
- Department of Neurology, The Second Affiliated Hospital of Anhui University of Chinese Medicine, Hefei 230001, China
| | - Shunyin Hu
- Department of Neurorehabilitation, Hefei Anhua Trauma Rehabilitation Hospital, Hefei 230011, China
| | - Xiaoxiang Yan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
| | - Changqing Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
| | - Kai Wang
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
- Hefei Comprehensive National Science Center, Institute of Artificial Intelligence, Hefei 230032, China
| | - Yajuan Hu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei 230032, China
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental Health, Hefei 230032, China
- Anhui Province Key Laboratory of Cognition and Neuropsychiatric Disorders, Hefei 230032, China
- The School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230032, China
- Correspondence: ; Tel.: +139-5691-2105
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20
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Galiotta V, Quattrociocchi I, D'Ippolito M, Schettini F, Aricò P, Sdoia S, Formisano R, Cincotti F, Mattia D, Riccio A. EEG-based Brain-Computer Interfaces for people with Disorders of Consciousness: Features and applications. A systematic review. Front Hum Neurosci 2022; 16:1040816. [PMID: 36545350 PMCID: PMC9760911 DOI: 10.3389/fnhum.2022.1040816] [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: 09/09/2022] [Accepted: 11/17/2022] [Indexed: 12/11/2022] Open
Abstract
Background Disorders of Consciousness (DoC) are clinical conditions following a severe acquired brain injury (ABI) characterized by absent or reduced awareness, known as coma, Vegetative State (VS)/Unresponsive Wakefulness Syndrome (VS/UWS), and Minimally Conscious State (MCS). Misdiagnosis rate between VS/UWS and MCS is attested around 40% due to the clinical and behavioral fluctuations of the patients during bedside consciousness assessments. Given the large body of evidence that some patients with DoC possess "covert" awareness, revealed by neuroimaging and neurophysiological techniques, they are candidates for intervention with brain-computer interfaces (BCIs). Objectives The aims of the present work are (i) to describe the characteristics of BCI systems based on electroencephalography (EEG) performed on DoC patients, in terms of control signals adopted to control the system, characteristics of the paradigm implemented, classification algorithms and applications (ii) to evaluate the performance of DoC patients with BCI. Methods The search was conducted on Pubmed, Web of Science, Scopus and Google Scholar. The PRISMA guidelines were followed in order to collect papers published in english, testing a BCI and including at least one DoC patient. Results Among the 527 papers identified with the first run of the search, 27 papers were included in the systematic review. Characteristics of the sample of participants, behavioral assessment, control signals employed to control the BCI, the classification algorithms, the characteristics of the paradigm, the applications and performance of BCI were the data extracted from the study. Control signals employed to operate the BCI were: P300 (N = 19), P300 and Steady-State Visual Evoked Potentials (SSVEP; hybrid system, N = 4), sensorimotor rhythms (SMRs; N = 5) and brain rhythms elicited by an emotional task (N = 1), while assessment, communication, prognosis, and rehabilitation were the possible applications of BCI in DoC patients. Conclusion Despite the BCI is a promising tool in the management of DoC patients, supporting diagnosis and prognosis evaluation, results are still preliminary, and no definitive conclusions may be drawn; even though neurophysiological methods, such as BCI, are more sensitive to covert cognition, it is suggested to adopt a multimodal approach and a repeated assessment strategy.
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Affiliation(s)
- Valentina Galiotta
- Neuroelectric Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia (IRCCS), Rome, Italy,Department of Psychology, Sapienza University of Rome, Rome, Italy
| | - Ilaria Quattrociocchi
- Neuroelectric Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia (IRCCS), Rome, Italy,Department of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, Rome, Italy
| | - Mariagrazia D'Ippolito
- Neuroelectric Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia (IRCCS), Rome, Italy,*Correspondence: Mariagrazia D'Ippolito
| | - Francesca Schettini
- Neuroelectric Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia (IRCCS), Rome, Italy,Servizio di Ausilioteca per la Riabilitazione Assistita con Tecnologia, Fondazione Santa Lucia (IRCCS), Rome, Italy
| | - Pietro Aricò
- Department of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, Rome, Italy,Department of Molecular Medicine, Sapienza University of Rome, Rome, Italy,BrainSigns srl, Rome, Italy
| | - Stefano Sdoia
- Department of Psychology, Sapienza University of Rome, Rome, Italy
| | - Rita Formisano
- Neurorehabilitation 2 and Post-Coma Unit, Fondazione Santa Lucia (IRCCS), Rome, Italy
| | - Febo Cincotti
- Department of Computer, Control, and Management Engineering “Antonio Ruberti”, Sapienza University of Rome, Rome, Italy
| | - Donatella Mattia
- Neuroelectric Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia (IRCCS), Rome, Italy,Servizio di Ausilioteca per la Riabilitazione Assistita con Tecnologia, Fondazione Santa Lucia (IRCCS), Rome, Italy
| | - Angela Riccio
- Neuroelectric Imaging and Brain-Computer Interface Laboratory, Fondazione Santa Lucia (IRCCS), Rome, Italy,Servizio di Ausilioteca per la Riabilitazione Assistita con Tecnologia, Fondazione Santa Lucia (IRCCS), Rome, Italy
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21
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Ballanti S, Campagnini S, Liuzzi P, Hakiki B, Scarpino M, Macchi C, Oddo CM, Carrozza MC, Grippo A, Mannini A. EEG-based methods for recovery prognosis of patients with disorders of consciousness: A systematic review. Clin Neurophysiol 2022; 144:98-114. [PMID: 36335795 DOI: 10.1016/j.clinph.2022.09.017] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 09/15/2022] [Accepted: 09/19/2022] [Indexed: 11/19/2022]
Abstract
OBJECTIVE Disorders of consciousness (DoC) are acquired conditions of severely altered consciousness. Electroencephalography (EEG)-derived biomarkers have been studied as clinical predictors of consciousness recovery. Therefore, this study aimed to systematically review the methods, features, and models used to derive prognostic EEG markers in patients with DoC in a rehabilitation setting. METHODS We conducted a systematic literature search of EEG-based strategies for consciousness recovery prognosis in five electronic databases. RESULTS The search resulted in 2964 papers. After screening, 15 studies were included in the review. Our analyses revealed that simpler experimental settings and similar filtering cut-off frequencies are preferred. The results of studies were categorised by extracting qualitative and quantitative features. The quantitative features were further classified into evoked/event-related potentials, spectral measures, entropy measures, and graph-theory measures. Despite the variety of methods, features from all categories, including qualitative ones, exhibited significant correlations with DoC prognosis. Moreover, no agreement was found on the optimal set of EEG-based features for the multivariate prognosis of patients with DoC, which limits the computational methods applied for outcome prediction and correlation analysis to classical ones. Nevertheless, alpha power, reactivity, and higher complexity metrics were often found to be predictive of consciousness recovery. CONCLUSIONS This study's findings confirm the essential role of qualitative EEG and suggest an important role for quantitative EEG. Their joint use could compensate for their reciprocal limitations. SIGNIFICANCE This study emphasises the need for further efforts toward guidelines on standardised EEG analysis pipeline, given the already proven role of EEG markers in the recovery prognosis of patients with DoC.
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Affiliation(s)
- Sara Ballanti
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy; The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | - Silvia Campagnini
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy; The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | - Piergiuseppe Liuzzi
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy; The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | - Bahia Hakiki
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy.
| | | | - Claudio Macchi
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy; Department of Experimental and Clinical Medicine, University of Florence, Firenze 50143, Italy.
| | - Calogero Maria Oddo
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | - Maria Chiara Carrozza
- The Biorobotics Institute, Scuola Superiore Sant'Anna, Pontedera 56025, Pisa, Italy; Department of Excellence in Robotics & AI, Scuola Superiore Sant'Anna, Pisa 56127, Italy.
| | | | - Andrea Mannini
- IRCCS Fondazione Don Carlo Gnocchi, Firenze 50143, Italy.
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22
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Zhuang Y, Yang Y, Xu L, Chen X, Geng X, Zhao J, He J. Effects of short-term spinal cord stimulation on patients with prolonged disorder of consciousness: A pilot study. Front Neurol 2022; 13:1026221. [PMID: 36313512 PMCID: PMC9614028 DOI: 10.3389/fneur.2022.1026221] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 09/26/2022] [Indexed: 11/13/2022] Open
Abstract
Background Spinal cord stimulation (SCS) can improve the level of awareness of prolonged disorder of consciousness (pDOC), but its application is restricted due to damage of invasive operation. Short-term spinal cord stimulation (st-SCS) in a minimally invasive manner will better balance the benefits and risks. Objectives This study focuses on the safety and efficacy of st-SCS for pDOC and reveals the modulation characteristics of different frequencies of SCS. Methods 31 patients received 2-week st-SCS treatment and 3-months follow-up. All patients were divided into two types of frequency treatment groups of 5 Hz and 70 Hz according to the postoperative electroencephalography (EEG) test. The efficacy was assessed based on the revised coma recovery scale (CRS-R). Results The results showed a significant increase in CRS-R scores after treatment (Z = −3.668, p < 0.001) without significant adverse effects. Univariate analysis showed that the minimally conscious state minus (MCS–) benefits most from treatment. Furthermore, two frequency have a difference in the time-point of the CRS-R score increase. 5 Hz mainly showed a significant increase in CRS-R score at 2 weeks of treatment (p = 0.027), and 70 Hz additionally showed a delayed effect of a continued significant increase at 1 week after treatment (p = 0.004). Conclusion st-SCS was safe and effective in improving patients with pDOC levels of consciousness, and was most effective for MCS–. Both 5 Hz and 70 Hz st-SCS can promote consciousness recovery, with 70 Hz showing a delayed effect in particular.
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Affiliation(s)
- Yutong Zhuang
- Department of Neurosurgery, The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Yi Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Long Xu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xueling Chen
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Xiaoli Geng
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - Jizong Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
- *Correspondence: Jizong Zhao
| | - Jianghong He
- Department of Neurosurgery, The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Jianghong He
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23
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Arvin S, Yonehara K, Glud AN. Therapeutic Neuromodulation toward a Critical State May Serve as a General Treatment Strategy. Biomedicines 2022; 10:biomedicines10092317. [PMID: 36140418 PMCID: PMC9496064 DOI: 10.3390/biomedicines10092317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 09/11/2022] [Accepted: 09/14/2022] [Indexed: 11/18/2022] Open
Abstract
Brain disease has become one of this century’s biggest health challenges, urging the development of novel, more effective treatments. To this end, neuromodulation represents an excellent method to modulate the activity of distinct neuronal regions to alleviate disease. Recently, the medical indications for neuromodulation therapy have expanded through the adoption of the idea that neurological disorders emerge from deficits in systems-level structures, such as brain waves and neural topology. Connections between neuronal regions are thought to fluidly form and dissolve again based on the patterns by which neuronal populations synchronize. Akin to a fire that may spread or die out, the brain’s activity may similarly hyper-synchronize and ignite, such as seizures, or dwindle out and go stale, as in a state of coma. Remarkably, however, the healthy brain remains hedged in between these extremes in a critical state around which neuronal activity maneuvers local and global operational modes. While it has been suggested that perturbations of this criticality could underlie neuropathologies, such as vegetative states, epilepsy, and schizophrenia, a major translational impact is yet to be made. In this hypothesis article, we dissect recent computational findings demonstrating that a neural network’s short- and long-range connections have distinct and tractable roles in sustaining the critical regime. While short-range connections shape the dynamics of neuronal activity, long-range connections determine the scope of the neuronal processes. Thus, to facilitate translational progress, we introduce topological and dynamical system concepts within the framework of criticality and discuss the implications and possibilities for therapeutic neuromodulation guided by topological decompositions.
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Affiliation(s)
- Simon Arvin
- Center for Experimental Neuroscience—CENSE, Department of Neurosurgery, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, 8200 Aarhus N, Denmark
- Danish Research Institute of Translational Neuroscience—DANDRITE, Nordic-EMBL Partnership for Molecular Medicine, Department of Biomedicine, Aarhus University, Ole Worms Allé 8, 8000 Aarhus C, Denmark
- Department of Neurosurgery, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11 Building A, 8200 Aarhus N, Denmark
- Correspondence: ; Tel.: +45 6083-1275
| | - Keisuke Yonehara
- Danish Research Institute of Translational Neuroscience—DANDRITE, Nordic-EMBL Partnership for Molecular Medicine, Department of Biomedicine, Aarhus University, Ole Worms Allé 8, 8000 Aarhus C, Denmark
- Multiscale Sensory Structure Laboratory, National Institute of Genetics, Mishima, Shizuoka 411-8540, Japan
- Department of Genetics, The Graduate University for Advanced Studies (SOKENDAI), Mishima, Shizuoka 411-8540, Japan
| | - Andreas Nørgaard Glud
- Center for Experimental Neuroscience—CENSE, Department of Neurosurgery, Aarhus University Hospital, Palle Juul-Jensens Boulevard 165, 8200 Aarhus N, Denmark
- Department of Neurosurgery, Department of Clinical Medicine, Aarhus University, Palle Juul-Jensens Boulevard 11 Building A, 8200 Aarhus N, Denmark
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24
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Liuzzi P, Grippo A, Campagnini S, Scarpino M, Draghi F, Romoli A, Bahia H, Sterpu R, Maiorelli A, Macchi C, Cecchi F, Carrozza MC, Mannini A. Merging Clinical and EEG Biomarkers in an Elastic-Net Regression for Disorder of Consciousness Prognosis Prediction. IEEE Trans Neural Syst Rehabil Eng 2022; 30:1504-1513. [PMID: 35635833 DOI: 10.1109/tnsre.2022.3178801] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Patients with Disorder of Consciousness (DoC) entering Intensive Rehabilitation Units after a severe Acquired Brain Injury have a highly variable evolution of the state of consciousness which is a complex aspect to predict. Besides clinical factors, electroencephalography has clearly shown its potential into the identification of prognostic biomarkers of consciousness recovery. In this retrospective study, with a dataset of 271 patients with DoC, we proposed three different Elastic-Net regressors trained on different datasets to predict the Coma Recovery Scale-Revised value at discharge based on data collected at admission. One dataset was completely EEG-based, one solely clinical data-based and the last was composed by the union of the two. Each model was optimized, validated and tested with a robust nested cross-validation pipeline. The best models resulted in a median absolute test error of 4.54 [IQR = 4.56], 3.39 [IQR = 4.36], 3.16 [IQR = 4.13] for respectively the EEG, clinical and hybrid model. Furthermore, the hybrid model for what concerns overcoming an unresponsive wakefulness state and exiting a DoC results in an AUC of 0.91 and 0.88 respectively. Small but useful improvements are added by the EEG dataset to the clinical model for what concerns overcoming an unresponsive wakefulness state. Data-driven techniques and namely, machine learning models are hereby shown to be capable of supporting the complex decision-making process the practitioners must face.
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25
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Curley WH, Comanducci A, Fecchio M. Conventional and Investigational Approaches Leveraging Clinical EEG for Prognosis in Acute Disorders of Consciousness. Semin Neurol 2022; 42:309-324. [PMID: 36100227 DOI: 10.1055/s-0042-1755220] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
Prediction of recovery of consciousness after severe brain injury is difficult and limited by a lack of reliable, standardized biomarkers. Multiple approaches for analysis of clinical electroencephalography (EEG) that shed light on prognosis in acute severe brain injury have emerged in recent years. These approaches fall into two major categories: conventional characterization of EEG background and quantitative measurement of resting state or stimulus-induced EEG activity. Additionally, a small number of studies have associated the presence of electrophysiologic sleep features with prognosis in the acute phase of severe brain injury. In this review, we focus on approaches for the analysis of clinical EEG that have prognostic significance and that could be readily implemented with minimal additional equipment in clinical settings, such as intensive care and intensive rehabilitation units, for patients with acute disorders of consciousness.
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Affiliation(s)
- William H Curley
- Harvard Medical School, Boston, Massachusetts.,Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts
| | - Angela Comanducci
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.,Università Campus Bio-Medico di Roma, Rome, Italy
| | - Matteo Fecchio
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, Massachusetts
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26
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Duszyk-Bogorodzka A, Zieleniewska M, Jankowiak-Siuda K. Brain Activity Characteristics of Patients With Disorders of Consciousness in the EEG Resting State Paradigm: A Review. Front Syst Neurosci 2022; 16:654541. [PMID: 35720438 PMCID: PMC9198636 DOI: 10.3389/fnsys.2022.654541] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 04/25/2022] [Indexed: 11/13/2022] Open
Abstract
The assessment of the level of consciousness in disorders of consciousness (DoC) is still one of the most challenging problems in contemporary medicine. Nevertheless, based on the multitude of studies conducted over the last 20 years on resting states based on electroencephalography (EEG) in DoC, it is possible to outline the brain activity profiles related to both patients without preserved consciousness and minimally conscious ones. In the case of patients without preserved consciousness, the dominance of low, mostly delta, frequency, and the marginalization of the higher frequencies were observed, both in terms of the global power of brain activity and in functional connectivity patterns. In turn, the minimally conscious patients revealed the opposite brain activity pattern—the characteristics of higher frequency bands were preserved both in global power and in functional long-distance connections. In this short review, we summarize the state of the art of EEG-based research in the resting state paradigm, in the context of providing potential support to the traditional clinical assessment of the level of consciousness.
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Affiliation(s)
- Anna Duszyk-Bogorodzka
- Behavioural Neuroscience Lab, Institute of Psychology, SWPS University of Social Sciences and Humanities, Warsaw, Poland
- *Correspondence: Anna Duszyk-Bogorodzka
| | | | - Kamila Jankowiak-Siuda
- Behavioural Neuroscience Lab, Institute of Psychology, SWPS University of Social Sciences and Humanities, Warsaw, Poland
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Arechavala RJ, Rochart R, Kloner RA, Liu A, Wu DA, Hung SM, Shimojo S, Fonteh AN, Kleinman MT, Harrington MG, Arakaki X. Task switching reveals abnormal brain-heart electrophysiological signatures in cognitively healthy individuals with abnormal CSF amyloid/tau, a pilot study. Int J Psychophysiol 2021; 170:102-111. [PMID: 34666107 PMCID: PMC8865562 DOI: 10.1016/j.ijpsycho.2021.10.007] [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: 04/29/2021] [Revised: 10/03/2021] [Accepted: 10/12/2021] [Indexed: 11/07/2022]
Abstract
Electroencephalographic (EEG) alpha oscillations have been related to heart rate variability (HRV) and both change in Alzheimer’s disease (AD). We explored if task switching reveals altered alpha power and HRV in cognitively healthy individuals with AD pathology in cerebrospinal fluid (CSF) and whether HRV improves the AD pathology classification by alpha power alone. We compared low and high alpha event-related desynchronization (ERD) and HRV parameters during task switch testing between two groups of cognitively healthy participants classified by CSF amyloid/tau ratio: normal (CH-NAT, n = 19) or pathological (CH-PAT, n = 27). For the task switching paradigm, participants were required to name the color or word for each colored word stimulus, with two sequential stimuli per trial. Trials include color (cC) or word (wW) repeats with low load repeating, and word (cW) or color switch (wC) for high load switching. HRV was assessed for RR interval, standard deviation of RR-intervals (SDNN) and root mean squared successive differences (RMSSD) in time domain, and low frequency (LF), high frequency (HF), and LF/HF ratio in frequency domain. Results showed that CH-PATs compared to CH-NATs presented: 1) increased (less negative) low alpha ERD during low load repeat trials and lower word switch cost (low alpha: p = 0.008, Cohen’s d = −0.83, 95% confidence interval −1.44 to −0.22, and high alpha: p = 0.019, Cohen’s d = −0.73, 95% confidence interval −1.34 to −0.13); 2) decreasing HRV from rest to task, suggesting hyper-activated sympatho-vagal responses. 3) CH-PATs classification by alpha ERD was improved by supplementing HRV signatures, supporting a potentially compromised brain-heart interoceptive regulation in CH-PATs. Further experiments are needed to validate these findings for clinical significance.
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Affiliation(s)
| | - Roger Rochart
- Neurosciences, Huntington Medical Research Institutes, Pasadena, CA 91105, USA
| | - Robert A Kloner
- Cardiovascular Research, Huntington Medical Research Institutes, Pasadena, CA 91105, USA; Division of Cardiovascular Medicine, Dept of Medicine, Keck School of Medicine at University of Southern California, Los Angeles, CA 90033, USA
| | - Anqi Liu
- Department of Computing and Mathematical Sciences (CMS), California Institute of Technology, Pasadena, CA 91125, USA; Department of Computer Science, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Daw-An Wu
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Shao-Min Hung
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Shinsuke Shimojo
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Alfred N Fonteh
- Neurosciences, Huntington Medical Research Institutes, Pasadena, CA 91105, USA
| | | | - Michael G Harrington
- Neurology, Keck School of Medicine at University of Southern California, Los Angeles, CA 90033, USA
| | - Xianghong Arakaki
- Neurosciences, Huntington Medical Research Institutes, Pasadena, CA 91105, USA.
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