1
|
Schnakers C. Assessing consciousness and cognition in disorders of consciousness. NeuroRehabilitation 2024; 54:11-21. [PMID: 38251070 DOI: 10.3233/nre-230140] [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] [Indexed: 01/23/2024]
Abstract
Detecting willful cognition in these patients is known to be challenging due to the patients' motor disabilities and high vigilance fluctuations but also due to the lack of expertise and use of adequate tools to assess these patients in specific settings. This review will discuss the main disorders of consciousness after severe brain injury, how to assess consciousness and cognition in these patients, as well as the challenges and tools available to overcome these challenges and reach an accurate diagnosis.
Collapse
Affiliation(s)
- Caroline Schnakers
- Research Institute, Casa Colina Hospital and Centers for Healthcare, 255 E. Bonita Avenue, Pomona, CA 91769, USA. Tel.: +1 909 596 7733 (ext. 3038); E-mail:
| |
Collapse
|
2
|
Wu H, Xie Q, Pan J, Liang Q, Lan Y, Guo Y, Han J, Xie M, Liu Y, Jiang L, Wu X, Li Y, Qin P. Identifying Patients with Cognitive Motor Dissociation Using Resting-state Temporal Stability. Neuroimage 2023; 272:120050. [PMID: 36963740 DOI: 10.1016/j.neuroimage.2023.120050] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 02/04/2023] [Accepted: 03/21/2023] [Indexed: 03/26/2023] Open
Abstract
Using task-dependent neuroimaging techniques, recent studies discovered a fraction of patients with disorders of consciousness (DOC) who had no command-following behaviors but showed a clear sign of awareness as healthy controls, which was defined as cognitive motor dissociation (CMD). However, existing task-dependent approaches might fail when CMD patients have cognitive function (e.g., attention, memory) impairments, in which patients with covert awareness cannot perform a specific task accurately and are thus wrongly considered unconscious, which leads to false-negative findings. Recent studies have suggested that sustaining a stable functional organization over time, i.e., high temporal stability, is crucial for supporting consciousness. Thus, temporal stability could be a powerful tool to detect the patient's cognitive functions (e.g., consciousness), while its alteration in the DOC and its capacity for identifying CMD were unclear. The resting-state fMRI (rs-fMRI) study included 119 participants from three independent research sites. A sliding-window approach was used to investigate global and regional temporal stability, which measured how stable the brain's functional architecture was across time. The temporal stability was compared in the first dataset (36/16 DOC/controls), and then a Support Vector Machine (SVM) classifier was built to discriminate DOC from controls. Furthermore, the generalizability of the SVM classifier was tested in the second independent dataset (35/21 DOC/controls). Finally, the SVM classifier was applied to the third independent dataset, where patients underwent rs-fMRI and brain-computer interface assessment (4/7 CMD/potential non-CMD), to test its performance in identifying CMD. Our results showed that global and regional temporal stability was impaired in DOC patients, especially in regions of the cingulo-opercular task control network, default-mode network, fronto-parietal task control network, and salience network. Using temporal stability as the feature, the SVM model not only showed good performance in the first dataset (accuracy = 90%), but also good generalizability in the second dataset (accuracy = 84%). Most importantly, the SVM model generalized well in identifying CMD in the third dataset (accuracy = 91%). Our preliminary findings suggested that temporal stability could be a potential tool to assist in diagnosing CMD. Furthermore, the temporal stability investigated in this study also contributed to a deeper understanding of the neural mechanism of consciousness.
Collapse
Affiliation(s)
- Hang Wu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China
| | - Qiuyou Xie
- Joint Center for disorders of consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, 510220, China; Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, 510010, China
| | - Jiahui Pan
- School of Software, South China Normal University, Foshan, 528225, China; Pazhou Lab, Guangzhou, 510330, China
| | - Qimei Liang
- Joint Center for disorders of consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, 510220, China
| | - Yue Lan
- Joint Center for disorders of consciousness, Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, 510220, China
| | - Yequn Guo
- Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, 510010, China
| | - Junrong Han
- Key Laboratory of Brain, Cognition and Education Science, Ministry of Education, China; Institute for Brain Research and Rehabilitation, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, 510631 Guangzhou, China
| | - Musi Xie
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China
| | - Yueyao Liu
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China
| | - Liubei Jiang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China
| | - Xuehai Wu
- Pazhou Lab, Guangzhou, 510330, China; Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200433, China; Neurosurgical Institute of Fudan University, Shanghai Clinical Medical Center of Neurosurgery, Shanghai Key laboratory of Brain Function Restoration and Neural Regeneration, Shanghai, 200433, China; State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, School of Basic Medical Sciences and Institutes of Brain Science, Fudan University, Shanghai, 200433, China.
| | - Yuanqing Li
- Pazhou Lab, Guangzhou, 510330, China; School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, China.
| | - Pengmin Qin
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou, Guangdong, 510631, China; Pazhou Lab, Guangzhou, 510330, China.
| |
Collapse
|
3
|
He Q, He J, Yang Y, Zhao J. Brain-Computer Interfaces in Disorders of Consciousness. Neurosci Bull 2023; 39:348-352. [PMID: 35941403 PMCID: PMC9905465 DOI: 10.1007/s12264-022-00920-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 06/03/2022] [Indexed: 11/25/2022] Open
Affiliation(s)
- Qiheng He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| | - Jianghong He
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
| | - Yi Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China.
- Chinese Institute for Brain Research, Beijing, 100010, China.
- Beijing Institute of Brain Disorders, Beijing, 100069, China.
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China.
| | - Jizong Zhao
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, 100070, China
- China National Clinical Research Center for Neurological Diseases, Beijing, 100070, China
| |
Collapse
|
4
|
Zheng RZ, Qi ZX, Wang Z, Xu ZY, Wu XH, Mao Y. Clinical Decision on Disorders of Consciousness After Acquired Brain Injury: Stepping Forward. Neurosci Bull 2023; 39:138-162. [PMID: 35804219 PMCID: PMC9849546 DOI: 10.1007/s12264-022-00909-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 04/10/2022] [Indexed: 01/22/2023] Open
Abstract
Major advances have been made over the past few decades in identifying and managing disorders of consciousness (DOC) in patients with acquired brain injury (ABI), bringing the transformation from a conceptualized definition to a complex clinical scenario worthy of scientific exploration. Given the continuously-evolving framework of precision medicine that integrates valuable behavioral assessment tools, sophisticated neuroimaging, and electrophysiological techniques, a considerably higher diagnostic accuracy rate of DOC may now be reached. During the treatment of patients with DOC, a variety of intervention methods are available, including amantadine and transcranial direct current stimulation, which have both provided class II evidence, zolpidem, which is also of high quality, and non-invasive stimulation, which appears to be more encouraging than pharmacological therapy. However, heterogeneity is profoundly ingrained in study designs, and only rare schemes have been recommended by authoritative institutions. There is still a lack of an effective clinical protocol for managing patients with DOC following ABI. To advance future clinical studies on DOC, we present a comprehensive review of the progress in clinical identification and management as well as some challenges in the pathophysiology of DOC. We propose a preliminary clinical decision protocol, which could serve as an ideal reference tool for many medical institutions.
Collapse
Affiliation(s)
- Rui-Zhe Zheng
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- National Center for Neurological Disorders, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, 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
| | - Zeng-Xin Qi
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- National Center for Neurological Disorders, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, 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
| | - Zhe Wang
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- National Center for Neurological Disorders, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, 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
| | - Ze-Yu Xu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
- National Center for Neurological Disorders, Shanghai, 200040, China
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China
- Shanghai Clinical Medical Center of Neurosurgery, 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
| | - Xue-Hai Wu
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
- National Center for Neurological Disorders, Shanghai, 200040, China.
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China.
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China.
- Shanghai Clinical Medical Center of Neurosurgery, 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.
| | - Ying Mao
- Department of Neurosurgery, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
- National Center for Neurological Disorders, Shanghai, 200040, China.
- Shanghai Key Laboratory of Brain Function and Restoration and Neural Regeneration, Shanghai, 200040, China.
- Neurosurgical Institute of Fudan University, Shanghai, 200040, China.
- Shanghai Clinical Medical Center of Neurosurgery, 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.
| |
Collapse
|
5
|
Ten-Year Change in Disorders of Consciousness: A Bibliometric Analysis. MEDICINA (KAUNAS, LITHUANIA) 2022; 59:medicina59010078. [PMID: 36676702 PMCID: PMC9867218 DOI: 10.3390/medicina59010078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 12/21/2022] [Accepted: 12/26/2022] [Indexed: 12/31/2022]
Abstract
Objectives: Disorders of consciousness (DoC) is a dynamic and challenging discipline, presenting intriguing challenges to clinicians and neurorehabilitation specialists for the lack of reliable assessment methods and interventions. Understanding DoC keeps pace with scientific research is urgent to need. We quantitively analyzed publications on DoC over the recent 10 years via bibliometrics analysis, to summarize the intellectual structure, current research hotspots, and future research trends in the field of DoC. Methods: Literature was obtained from the Science Citation Index Expanded of Web of Science Core Collection (WoSCC). To illustrate the knowledge structure of DoC, CiteSpace 5.8.R3 was used to conduct a co-occurrence analysis of countries, institutions, and keywords, and a co-citation analysis of references and journals. Also, Gephi 0.9.2 contributed to the author and co-cited author analysis. We found the most influential journals, authors, and countries and the most talked about keywords in the last decade of research. Results: A total of 1919 publications were collected. Over the past 10 years, the total number of annual publications has continued to increase, with the largest circulation in 2018. We found most DoC research and close cooperation originated from developed countries, e.g., the USA, Canada, and Italy. Academics from Belgium appear to have a strong presence in the field of DoC. The most influential journals were also mainly distributed in the USA and some European countries. Conclusions: This bibliometric study sheds light on the knowledge architecture of DoC research over the past decade, reflecting current hotspots and emerging trends, and providing new insights for clinicians and academics interested in DoC. The hot issues in DoC were diagnosing and differentiating the level of consciousness, and detecting covert awareness in early severe brain-injured patients. New trends focus on exploring the recovery mechanism of DoC and neuromodulation techniques.
Collapse
|
6
|
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.
Collapse
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
| |
Collapse
|
7
|
Understanding, detecting, and stimulating consciousness recovery in the ICU. Acta Neurochir (Wien) 2022; 165:809-828. [PMID: 36242637 DOI: 10.1007/s00701-022-05378-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 08/07/2022] [Indexed: 11/01/2022]
Abstract
Coma is a medical and socioeconomic emergency. Although underfunded, research on coma and disorders of consciousness has made impressive progress. Lesion-network-mapping studies have delineated the precise brainstem regions that consistently produce coma when damaged. Functional neuroimaging has revealed how mechanisms like "communication through coherence" and "inhibition by gating" work in synergy to enable cortico-cortical processing and how this information transfer is disrupted in brain injury. On the cellular level, break-down of intracellular communication between the layer 5 pyramidal cell soma and the apical dendritic part impairs dendritic information integration, with up-stream effects on microcircuits in local neuronal populations and on large-scale fronto-parietal networks, which correlates with loss of consciousness. A breakthrough in clinical concepts occurred when fMRI, and later EEG, studies revealed that 15% of clinically unresponsive patients in acute and chronic settings are in fact awake and aware, as shown by their command following abilities revealed by brain activation during motor and locomotion imagery tasks. This condition is now termed "cognitive motor dissociation." Furthermore, epidemiological data on coma were literally non-existent until recently because of difficulties related to case ascertainment with traditional methods, but crowdsourcing of family observations enabled the first estimates of how frequent coma is in the general population (pooled annual incidence of 201 coma cases per 100,000 population in the UK and the USA). Diagnostic guidelines on coma and disorders of consciousness by the American Academy of Neurology and the European Academy of Neurology provide ambitious clinical frameworks to accommodate these achievements. As for therapy, a broad range of medical and non-medical treatment options is now being tested in increasingly larger trials; in particular, amantadine and transcranial direct current stimulation appear promising in this regard. Major international initiatives like the Curing Coma Campaign aim to raise awareness for coma and disorders of consciousness in the public, with the ultimate goal to make more brain-injured patients recover consciousness after a coma. To highlight all these accomplishments, this paper provides a comprehensive overview of recent progress and future challenges related to understanding, detecting, and stimulating consciousness recovery in the ICU.
Collapse
|
8
|
Pan J, Xiao J, Wang J, Wang F, Li J, Qiu L, Di H, Li Y. Brain-Computer Interfaces for Awareness Detection, Auxiliary Diagnosis, Prognosis and Rehabilitation in Patients with Disorders of Consciousness. Semin Neurol 2022; 42:363-374. [PMID: 35835448 DOI: 10.1055/a-1900-7261] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Affiliation(s)
- Jiahui Pan
- Pazhou Lab, Guangzhou, China.,South China Normal University, Guangzhou, China
| | - Jun Xiao
- Pazhou Lab, Guangzhou, China.,South China University of Technology, Guangzhou, China
| | - Jing Wang
- Hangzhou Normal University, Hangzhou, China
| | - Fei Wang
- Pazhou Lab, Guangzhou, China.,South China Normal University, Guangzhou, China
| | - Jingcong Li
- Pazhou Lab, Guangzhou, China.,South China Normal University, Guangzhou, China
| | - Lina Qiu
- South China Normal University, Guangzhou, China
| | - Haibo Di
- Hangzhou Normal University, Hangzhou, China
| | - Yuanqing Li
- Pazhou Lab, Guangzhou, China.,South China University of Technology, Guangzhou, China
| |
Collapse
|
9
|
Kondziella D, Stevens RD. Classifying Disorders of Consciousness: Past, Present, and Future. Semin Neurol 2022; 42:239-248. [PMID: 35738291 DOI: 10.1055/a-1883-1021] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
|
10
|
Monti MM, Schnakers C. Flowchart for Implementing Advanced Imaging and Electrophysiology in Patients With Disorders of Consciousness: To fMRI or Not to fMRI? Neurology 2022; 98:452-459. [PMID: 35058337 DOI: 10.1212/wnl.0000000000200038] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
The American Academy of Neurology and the European Academy of Neurology have recognized, for the first time, the value of advanced neuroimaging and electrophysiology techniques (AIEs) in the context of diagnosing patients with a disorder of consciousness (DOC). This recognition is part of an important agenda of promoting evidence-based competency in the management of patients with DOC. Nonetheless, considering that these techniques (and the required knowledge) are seldom available outside of advanced medical centers, it is important to provide physicians with a framework for balancing risks and benefits and deciding, on a single patient basis, whether AIEs are suitable. This issue is all the more urgent considering that family members are increasingly aware of the use of AIEs in patients with DOC, pressure for these assessments is likely to increase in the context of ethical and clinical imperatives to meet standards of care, and pathways for reimbursement for such assessments in DOC are yet to be established. The new guidelines, however, provide no guiding principle for physicians to decide when such assessments are appropriate, a limitation that impedes their wide adoption. We address this important gap by proposing an easy to use algorithmic flowchart that is based on the new guidelines and can be used to determine the appropriateness of AIEs for any given patient with DOC and ensure that evidence-based best practices are being followed. We also provide a brief context for understanding the main categories of AIEs available to clinicians, their advantages, and their limitations.
Collapse
Affiliation(s)
- Martin Max Monti
- From the Department of Psychology (M.M.M.) and Department of Neurosurgery, Brain Injury Research Center (C.S.), University of California Los Angeles; and Research Institute (C.S.), Casa Colina Hospitals and Centers for Healthcare, Pomona, CA.
| | - Caroline Schnakers
- From the Department of Psychology (M.M.M.) and Department of Neurosurgery, Brain Injury Research Center (C.S.), University of California Los Angeles; and Research Institute (C.S.), Casa Colina Hospitals and Centers for Healthcare, Pomona, CA
| |
Collapse
|
11
|
Antonietti A, Balachandran P, Hossaini A, Hu Y, Valeriani D. The BCI Glossary: a first proposal for a community review. BRAIN-COMPUTER INTERFACES 2021. [DOI: 10.1080/2326263x.2021.1969789] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Alberto Antonietti
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy
| | | | - Ali Hossaini
- Department of Engineering, King’s College London, London, UK
| | - Yaoping Hu
- Department of Electrical and Software Engineering,University of Calgary, Calgary, AB, Canada
| | - Davide Valeriani
- Department of Otolaryngology Head and Neck Surgery, Massachusetts Eye and Ear, Boston, MA, USA
- Department of Otolaryngology Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
12
|
Pan J, Xie Q, Qin P, Chen Y, He Y, Huang H, Wang F, Ni X, Cichocki A, Yu R, Li Y. Prognosis for patients with cognitive motor dissociation identified by brain-computer interface. Brain 2020; 143:1177-1189. [PMID: 32101603 PMCID: PMC7174053 DOI: 10.1093/brain/awaa026] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 12/08/2019] [Accepted: 12/17/2019] [Indexed: 01/15/2023] Open
Abstract
Cognitive motor dissociation describes a subset of patients with disorders of consciousness who show neuroimaging evidence of consciousness but no detectable command-following behaviours. Although essential for family counselling, decision-making, and the design of rehabilitation programmes, the prognosis for patients with cognitive motor dissociation remains under-investigated. The current study included 78 patients with disorders of consciousness who showed no detectable command-following behaviours. These patients included 45 patients with unresponsive wakefulness syndrome and 33 patients in a minimally conscious state, as diagnosed using the Coma Recovery Scale-Revised. Each patient underwent an EEG-based brain-computer interface experiment, in which he or she was instructed to perform an item-selection task (i.e. select a photograph or a number from two candidates). Patients who achieved statistically significant brain-computer interface accuracies were identified as cognitive motor dissociation. Two evaluations using the Coma Recovery Scale-Revised, one before the experiment and the other 3 months later, were carried out to measure the patients’ behavioural improvements. Among the 78 patients with disorders of consciousness, our results showed that within the unresponsive wakefulness syndrome patient group, 15 of 18 patients with cognitive motor dissociation (83.33%) regained consciousness, while only five of the other 27 unresponsive wakefulness syndrome patients without significant brain-computer interface accuracies (18.52%) regained consciousness. Furthermore, within the minimally conscious state patient group, 14 of 16 patients with cognitive motor dissociation (87.5%) showed improvements in their Coma Recovery Scale-Revised scores, whereas only four of the other 17 minimally conscious state patients without significant brain-computer interface accuracies (23.53%) had improved Coma Recovery Scale-Revised scores. Our results suggest that patients with cognitive motor dissociation have a better outcome than other patients. Our findings extend current knowledge of the prognosis for patients with cognitive motor dissociation and have important implications for brain-computer interface-based clinical diagnosis and prognosis for patients with disorders of consciousness.
Collapse
Affiliation(s)
- Jiahui Pan
- Center for Brain-Computer Interfaces and Brain Information Processing, South China University of Technology, Guangzhou, China.,School of Software, South China Normal University, Guangzhou, China
| | - Qiuyou Xie
- Department of Rehabilitation Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, China.,Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China
| | - Pengmin Qin
- Centre for Studies of Psychological Applications, Guangdong Key Laboratory of Mental Health and Cognitive Science, School of Psychology, South China Normal University, Guangzhou, China
| | - Yan Chen
- Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China
| | - Yanbin He
- Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China.,Department of Traumatic Brain Injury Rehabilitation and Severe Rehabilitation, Guangdong Work Injury Rehabilitation Hospital, Guangzhou, China
| | - Haiyun Huang
- Center for Brain-Computer Interfaces and Brain Information Processing, South China University of Technology, Guangzhou, China
| | - Fei Wang
- Center for Brain-Computer Interfaces and Brain Information Processing, South China University of Technology, Guangzhou, China.,School of Software, South China Normal University, Guangzhou, China
| | - Xiaoxiao Ni
- Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China
| | - Andrzej Cichocki
- Skolkovo Institute of Science and Technology (Skoltech), Moscow 143026, Russia.,Nicolaus Copernicus University (UMK), Torun 87-100, Poland
| | - Ronghao Yu
- Centre for Hyperbaric Oxygen and Neurorehabilitation, Guangzhou General Hospital of Guangzhou Military Command, Guangzhou, China
| | - Yuanqing Li
- Center for Brain-Computer Interfaces and Brain Information Processing, South China University of Technology, Guangzhou, China
| |
Collapse
|
13
|
Abstract
INTRODUCTION New guidelines regarding the diagnosis of disorders of consciousness (DOC) (such as vegetative state and minimally conscious state) have recently been published by the American Academy of Neurology and the European Academy of Neurology. This follows an impressive number of prospective studies performed on DOC and recent multi-centric studies with larger sample size, which have gathered precious information on the recovery of cohort of patients through years and which now call for a better management of patients with DOC. AREAS COVERED This review will discuss recent updates on the clinical entities of DOC, the challenges for an accurate diagnosis and the last developments in diagnostic tools. EXPERT OPINION The authors will also discuss the impact of the new guidelines on their way of diagnosing patients and how diagnosis will most likely change in a near future.
Collapse
Affiliation(s)
- Caroline Schnakers
- Research Institute, Casa Colina Hospital and Centers for Healthcare , Pomona, CA, USA
| |
Collapse
|
14
|
Virtual Reality Based Cognitive Rehabilitation in Minimally Conscious State: A Case Report with EEG Findings and Systematic Literature Review. Brain Sci 2020; 10:brainsci10070414. [PMID: 32630179 PMCID: PMC7407378 DOI: 10.3390/brainsci10070414] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Revised: 06/22/2020] [Accepted: 06/23/2020] [Indexed: 12/14/2022] Open
Abstract
Chronic disorders of consciousness cause a total or partial and fluctuating unawareness of the surrounding environment. Virtual reality (VR) can be useful as a diagnostic and/or a neurorehabilitation tool, and its effects can be monitored by means of both clinical and electroencephalography (EEG) data recording of brain activity. We reported on the case of a 17-year-old patient with a disorder of consciousness (DoC) who was provided with VR training to improve her cognitive-behavioral outcomes, which were assessed using clinical scales (the Coma Recovery Scale-Revised, the Disability Rating Scale, and the Rancho Los Amigos Levels of Cognitive Functioning), as well as EEG recording, during VR training sessions. At the end of the training, significant improvements in both clinical and neurophysiological outcomes were achieved. Then, we carried out a systematic review of the literature to investigate the role of EEG and VR in the management of patients with DoC. A search on PubMed, Web of Science, Scopus, and Google Scholar databases was performed, using the keywords: “disorders of consciousness” and “virtual reality”, or “EEG”. The results of the literature review suggest that neurophysiological data in combination with VR could be useful in evaluating the reactions induced by different paradigms in DoC patients, helping in the differential diagnosis. In conclusion, the EEG plus VR approach used with our patient could be promising to define the most appropriate stimulation protocol, so as to promote a better personalization of the rehabilitation program. However, further clinical trials, as well as meta-analysis of the literature, are needed to be affirmative on the role of VR in patients with DoC.
Collapse
|
15
|
Aubinet C, Larroque SK, Heine L, Martial C, Majerus S, Laureys S, Di Perri C. Clinical subcategorization of minimally conscious state according to resting functional connectivity. Hum Brain Mapp 2018; 39:4519-4532. [PMID: 29972267 PMCID: PMC6866360 DOI: 10.1002/hbm.24303] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2016] [Revised: 05/15/2018] [Accepted: 06/20/2018] [Indexed: 11/11/2022] Open
Abstract
Patients in minimally conscious state (MCS) have been subcategorized in MCS plus and MCS minus, based on command-following, intelligible verbalization or intentional communication. We here aimed to better characterize the functional neuroanatomy of MCS based on this clinical subcategorization by means of resting state functional magnetic resonance imaging (fMRI). Resting state fMRI was acquired in 292 MCS patients and a seed-based analysis was conducted on a convenience sample of 10 MCS plus patients, 9 MCS minus patients and 35 healthy subjects. We investigated the left and right frontoparietal networks (FPN), auditory network, default mode network (DMN), thalamocortical connectivity and DMN between-network anticorrelations. We also employed an analysis based on regions of interest (ROI) to examine interhemispheric connectivity and investigated intergroup differences in gray/white matter volume by means of voxel-based morphometry. We found a higher connectivity in MCS plus as compared to MCS minus in the left FPN, specifically between the left dorso-lateral prefrontal cortex and left temporo-occipital fusiform cortex. No differences between patient groups were observed in the auditory network, right FPN, DMN, thalamocortical and interhemispheric connectivity, between-network anticorrelations and gray/white matter volume. Our preliminary group-level results suggest that the clinical subcategorization of MCS may involve functional connectivity differences in a language-related executive control network. MCS plus and minus patients are seemingly not differentiated by networks associated to auditory processing, perception of surroundings and internal awareness/self-mentation, nor by interhemispheric integration and structural brain damage.
Collapse
Affiliation(s)
- Charlène Aubinet
- Coma Science Group, GIGA Research Center and Neurology DepartmentUniversity and University Hospital of LiègeLiègeBelgium
| | - Stephen Karl Larroque
- Coma Science Group, GIGA Research Center and Neurology DepartmentUniversity and University Hospital of LiègeLiègeBelgium
| | - Lizette Heine
- Auditory Cognition and Psychoacoustics Team – Lyon Neuroscience Research Center (UCBL, CNRS UMR5292, Inserm U1028)LyonFrance
| | - Charlotte Martial
- Coma Science Group, GIGA Research Center and Neurology DepartmentUniversity and University Hospital of LiègeLiègeBelgium
| | - Steve Majerus
- Psychology and Neuroscience of Cognition Research UnitUniversity of LiegeBelgium
| | - Steven Laureys
- Coma Science Group, GIGA Research Center and Neurology DepartmentUniversity and University Hospital of LiègeLiègeBelgium
| | - Carol Di Perri
- Coma Science Group, GIGA Research Center and Neurology DepartmentUniversity and University Hospital of LiègeLiègeBelgium
- Centre for Clinical Brain Sciences UK Dementia Research Institute, Centre for Dementia PreventionUniversity of EdinburghEdinburghUnited Kingdom
| |
Collapse
|
16
|
Brain-Computer Interface for Clinical Purposes: Cognitive Assessment and Rehabilitation. BIOMED RESEARCH INTERNATIONAL 2017; 2017:1695290. [PMID: 28913349 PMCID: PMC5587953 DOI: 10.1155/2017/1695290] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 03/30/2017] [Revised: 06/13/2017] [Accepted: 07/03/2017] [Indexed: 12/11/2022]
Abstract
Alongside the best-known applications of brain-computer interface (BCI) technology for restoring communication abilities and controlling external devices, we present the state of the art of BCI use for cognitive assessment and training purposes. We first describe some preliminary attempts to develop verbal-motor free BCI-based tests for evaluating specific or multiple cognitive domains in patients with Amyotrophic Lateral Sclerosis, disorders of consciousness, and other neurological diseases. Then we present the more heterogeneous and advanced field of BCI-based cognitive training, which has its roots in the context of neurofeedback therapy and addresses patients with neurological developmental disorders (autism spectrum disorder and attention-deficit/hyperactivity disorder), stroke patients, and elderly subjects. We discuss some advantages of BCI for both assessment and training purposes, the former concerning the possibility of longitudinally and reliably evaluating cognitive functions in patients with severe motor disabilities, the latter regarding the possibility of enhancing patients' motivation and engagement for improving neural plasticity. Finally, we discuss some present and future challenges in the BCI use for the described purposes.
Collapse
|