1
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Issa MF, Khan I, Ruzzoli M, Molinaro N, Lizarazu M. On the speech envelope in the cortical tracking of speech. Neuroimage 2024; 297:120675. [PMID: 38885886 DOI: 10.1016/j.neuroimage.2024.120675] [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: 02/26/2024] [Revised: 06/05/2024] [Accepted: 06/06/2024] [Indexed: 06/20/2024] Open
Abstract
The synchronization between the speech envelope and neural activity in auditory regions, referred to as cortical tracking of speech (CTS), plays a key role in speech processing. The method selected for extracting the envelope is a crucial step in CTS measurement, and the absence of a consensus on best practices among the various methods can influence analysis outcomes and interpretation. Here, we systematically compare five standard envelope extraction methods the absolute value of Hilbert transform (absHilbert), gammatone filterbanks, heuristic approach, Bark scale, and vocalic energy), analyzing their impact on the CTS. We present performance metrics for each method based on the recording of brain activity from participants listening to speech in clear and noisy conditions, utilizing intracranial EEG, MEG and EEG data. As expected, we observed significant CTS in temporal brain regions below 10 Hz across all datasets, regardless of the extraction methods. In general, the gammatone filterbanks approach consistently demonstrated superior performance compared to other methods. Results from our study can guide scientists in the field to make informed decisions about the optimal analysis to extract the CTS, contributing to advancing the understanding of the neuronal mechanisms implicated in CTS.
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Affiliation(s)
- Mohamed F Issa
- BCBL, Basque Center on Cognition, Brain and Language, San Sebastian, Spain; Department of Scientific Computing, Faculty of Computers and Artificial Intelligence, Benha University, Benha, Egypt.
| | - Izhar Khan
- BCBL, Basque Center on Cognition, Brain and Language, San Sebastian, Spain
| | - Manuela Ruzzoli
- BCBL, Basque Center on Cognition, Brain and Language, San Sebastian, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Nicola Molinaro
- BCBL, Basque Center on Cognition, Brain and Language, San Sebastian, Spain; Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Mikel Lizarazu
- BCBL, Basque Center on Cognition, Brain and Language, San Sebastian, Spain
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2
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Young MJ, Kazazian K, Fischer D, Lissak IA, Bodien YG, Edlow BL. Disclosing Results of Tests for Covert Consciousness: A Framework for Ethical Translation. Neurocrit Care 2024; 40:865-878. [PMID: 38243150 PMCID: PMC11147696 DOI: 10.1007/s12028-023-01899-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 11/22/2023] [Indexed: 01/21/2024]
Abstract
The advent of neurotechnologies including advanced functional magnetic resonance imaging and electroencephalography to detect states of awareness not detectable by traditional bedside neurobehavioral techniques (i.e., covert consciousness) promises to transform neuroscience research and clinical practice for patients with brain injury. As these interventions progress from research tools into actionable, guideline-endorsed clinical tests, ethical guidance for clinicians on how to responsibly communicate the sensitive results they yield is crucial yet remains underdeveloped. Drawing on insights from empirical and theoretical neuroethics research and our clinical experience with advanced neurotechnologies to detect consciousness in behaviorally unresponsive patients, we critically evaluate ethical promises and perils associated with disclosing the results of clinical covert consciousness assessments and describe a semistructured approach to responsible data sharing to mitigate potential risks.
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Affiliation(s)
- Michael J Young
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA.
| | - Karnig Kazazian
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA
- Western Institute of Neuroscience, Western University, London, ON, Canada
| | - David Fischer
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - India A Lissak
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA, 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
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3
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Fischer D, Edlow BL. Coma Prognostication After Acute Brain Injury: A Review. JAMA Neurol 2024:2815829. [PMID: 38436946 DOI: 10.1001/jamaneurol.2023.5634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Abstract
Importance Among the most impactful neurologic assessments is that of neuroprognostication, defined here as the prediction of neurologic recovery from disorders of consciousness caused by severe, acute brain injury. Across a range of brain injury etiologies, these determinations often dictate whether life-sustaining treatment is continued or withdrawn; thus, they have major implications for morbidity, mortality, and health care costs. Neuroprognostication relies on a diverse array of tests, including behavioral, radiologic, physiological, and serologic markers, that evaluate the brain's functional and structural integrity. Observations Prognostic markers, such as the neurologic examination, electroencephalography, and conventional computed tomography and magnetic resonance imaging (MRI), have been foundational in assessing a patient's current level of consciousness and capacity for recovery. Emerging techniques, such as functional MRI, diffusion MRI, and advanced forms of electroencephalography, provide new ways of evaluating the brain, leading to evolving schemes for characterizing neurologic function and novel methods for predicting recovery. Conclusions and Relevance Neuroprognostic markers are rapidly evolving as new ways of assessing the brain's structural and functional integrity after brain injury are discovered. Many of these techniques remain in development, and further research is needed to optimize their prognostic utility. However, even as such efforts are underway, a series of promising findings coupled with the imperfect predictive value of conventional prognostic markers and the high stakes of these assessments have prompted clinical guidelines to endorse emerging techniques for neuroprognostication. Thus, clinicians have been thrust into an uncertain predicament in which emerging techniques are not yet perfected but too promising to ignore. This review illustrates the current, and likely future, landscapes of prognostic markers. No matter how much prognostic markers evolve and improve, these assessments must be approached with humility and individualized to reflect each patient's values.
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Affiliation(s)
- David Fischer
- Division of Neurocritical Care, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown
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4
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Gallucci A, Varoli E, Del Mauro L, Hassan G, Rovida M, Comanducci A, Casarotto S, Lo Re V, Romero Lauro LJ. Multimodal approaches supporting the diagnosis, prognosis and investigation of neural correlates of disorders of consciousness: A systematic review. Eur J Neurosci 2024; 59:874-933. [PMID: 38140883 DOI: 10.1111/ejn.16149] [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: 12/12/2022] [Revised: 08/30/2023] [Accepted: 09/11/2023] [Indexed: 12/24/2023]
Abstract
The limits of the standard, behaviour-based clinical assessment of patients with disorders of consciousness (DoC) prompted the employment of functional neuroimaging, neurometabolic, neurophysiological and neurostimulation techniques, to detect brain-based covert markers of awareness. However, uni-modal approaches, consisting in employing just one of those techniques, are usually not sufficient to provide an exhaustive exploration of the neural underpinnings of residual awareness. This systematic review aimed at collecting the evidence from studies employing a multimodal approach, that is, combining more instruments to complement DoC diagnosis, prognosis and better investigating their neural correlates. Following the PRISMA guidelines, records from PubMed, EMBASE and Scopus were screened to select peer-review original articles in which a multi-modal approach was used for the assessment of adult patients with a diagnosis of DoC. Ninety-two observational studies and 32 case reports or case series met the inclusion criteria. Results highlighted a diagnostic and prognostic advantage of multi-modal approaches that involve electroencephalography-based (EEG-based) measurements together with neuroimaging or neurometabolic data or with neurostimulation. Multimodal assessment deepened the knowledge on the neural networks underlying consciousness, by showing correlations between the integrity of the default mode network and the different clinical diagnosis of DoC. However, except for studies using transcranial magnetic stimulation combined with electroencephalography, the integration of more than one technique in most of the cases occurs without an a priori-designed multi-modal diagnostic approach. Our review supports the feasibility and underlines the advantages of a multimodal approach for the diagnosis, prognosis and for the investigation of neural correlates of DoCs.
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Affiliation(s)
- Alessia Gallucci
- Ph.D. Program in Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy
- NeuroMi (Neuroscience Center), University of Milano-Bicocca, Milan, Italy
| | - Erica Varoli
- Neurology Service, Department of Diagnostic and Therapeutic Services, Istituto di Ricovero e Cura a Carattere Scientifico-Istituto Mediterraneo per i Trapianti e Terapie ad Alta Specializzazione (IRCCS ISMETT), Palermo, Italy
| | - Lilia Del Mauro
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
| | - Gabriel Hassan
- Department of Biomedical and Clinical Sciences, University of Milan, Italy
| | - Margherita Rovida
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
| | - Angela Comanducci
- IRCSS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
- Università Campus Bio-Medico di Roma, Rome, Italy
| | - Silvia Casarotto
- Department of Biomedical and Clinical Sciences, University of Milan, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Milan, Italy
| | - Vincenzina Lo Re
- Neurology Service, Department of Diagnostic and Therapeutic Services, Istituto di Ricovero e Cura a Carattere Scientifico-Istituto Mediterraneo per i Trapianti e Terapie ad Alta Specializzazione (IRCCS ISMETT), Palermo, Italy
| | - Leonor J Romero Lauro
- NeuroMi (Neuroscience Center), University of Milano-Bicocca, Milan, Italy
- Department of Psychology, University of Milano-Bicocca, Milan, Italy
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5
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Young MJ, Fecchio M, Bodien YG, Edlow BL. Covert cortical processing: a diagnosis in search of a definition. Neurosci Conscious 2024; 2024:niad026. [PMID: 38327828 PMCID: PMC10849751 DOI: 10.1093/nc/niad026] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 10/22/2023] [Accepted: 12/10/2023] [Indexed: 02/09/2024] Open
Abstract
Historically, clinical evaluation of unresponsive patients following brain injury has relied principally on serial behavioral examination to search for emerging signs of consciousness and track recovery. Advances in neuroimaging and electrophysiologic techniques now enable clinicians to peer into residual brain functions even in the absence of overt behavioral signs. These advances have expanded clinicians' ability to sub-stratify behaviorally unresponsive and seemingly unaware patients following brain injury by querying and classifying covert brain activity made evident through active or passive neuroimaging or electrophysiologic techniques, including functional MRI, electroencephalography (EEG), transcranial magnetic stimulation-EEG, and positron emission tomography. Clinical research has thus reciprocally influenced clinical practice, giving rise to new diagnostic categories including cognitive-motor dissociation (i.e. 'covert consciousness') and covert cortical processing (CCP). While covert consciousness has received extensive attention and study, CCP is relatively less understood. We describe that CCP is an emerging and clinically relevant state of consciousness marked by the presence of intact association cortex responses to environmental stimuli in the absence of behavioral evidence of stimulus processing. CCP is not a monotonic state but rather encapsulates a spectrum of possible association cortex responses from rudimentary to complex and to a range of possible stimuli. In constructing a roadmap for this evolving field, we emphasize that efforts to inform clinicians, philosophers, and researchers of this condition are crucial. Along with strategies to sensitize diagnostic criteria and disorders of consciousness nosology to these vital discoveries, democratizing access to the resources necessary for clinical identification of CCP is an emerging clinical and ethical imperative.
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Affiliation(s)
- Michael J Young
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA 02114, USA
| | - Matteo Fecchio
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA 02114, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA 02114, USA
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, 300 1st Ave, Charlestown, Boston, MA 02129, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, 101 Merrimac Street, Suite 310, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, 149 13th St, Charlestown, Charlestown, MA 02129, USA
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6
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Liu G, Chi B. Technological Modalities in the Assessment and Treatment of Disorders of Consciousness. Phys Med Rehabil Clin N Am 2024; 35:109-126. [PMID: 37993182 DOI: 10.1016/j.pmr.2023.07.005] [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: 11/24/2023]
Abstract
Over the last 10 years, there have been rapid advances made in technologies that can be utilized in the diagnosis and treatment of patients with a disorder of consciousness (DoC). This article provides a comprehensive review of these modalities including the evidence supporting their potential use in DoC. This review specifically addresses diagnostic, non-invasive therapeutic, and invasive therapeutic technological modalities except for neuroimaging, which is discussed in another article. While technologic advances appear promising for both assessment and treatment of patients with a DoC, high-quality evidence supporting widespread clinical adoption remains limited.
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Affiliation(s)
- Gang Liu
- Department of Rehabilitation Medicine, Huashan Hospital, Fudan University, No 12 Wulumuqi Middle Road, Shanghai 200040, China
| | - Bradley Chi
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, 7200 Cambridge Street, Houston, TX 77030, USA.
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7
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Jia Z, Xu C, Li J, Gao J, Ding N, Luo B, Zou J. Phase Property of Envelope-Tracking EEG Response Is Preserved in Patients with Disorders of Consciousness. eNeuro 2023; 10:ENEURO.0130-23.2023. [PMID: 37500493 PMCID: PMC10420405 DOI: 10.1523/eneuro.0130-23.2023] [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: 04/20/2023] [Revised: 07/16/2023] [Accepted: 07/20/2023] [Indexed: 07/29/2023] Open
Abstract
When listening to speech, the low-frequency cortical response below 10 Hz can track the speech envelope. Previous studies have demonstrated that the phase lag between speech envelope and cortical response can reflect the mechanism by which the envelope-tracking response is generated. Here, we analyze whether the mechanism to generate the envelope-tracking response is modulated by the level of consciousness, by studying how the stimulus-response phase lag is modulated by the disorder of consciousness (DoC). It is observed that DoC patients in general show less reliable neural tracking of speech. Nevertheless, the stimulus-response phase lag changes linearly with frequency between 3.5 and 8 Hz, for DoC patients who show reliable cortical tracking to speech, regardless of the consciousness state. The mean phase lag is also consistent across these DoC patients. These results suggest that the envelope-tracking response to speech can be generated by an automatic process that is barely modulated by the consciousness state.
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Affiliation(s)
- Ziting Jia
- The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250033, China
| | - Chuan Xu
- Department of Neurology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310019, 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
| | - Nai Ding
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
| | - Benyan Luo
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China
| | - Jiajie Zou
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou 310027, China
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8
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Curley WH, Bodien YG, Zhou DW, Conte MM, Foulkes AS, Giacino JT, Victor JD, Schiff ND, Edlow BL. Electrophysiological correlates of thalamocortical function in acute severe traumatic brain injury. Cortex 2022; 152:136-152. [PMID: 35569326 PMCID: PMC9759728 DOI: 10.1016/j.cortex.2022.04.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 01/26/2022] [Accepted: 04/04/2022] [Indexed: 12/26/2022]
Abstract
Tools assaying the neural networks that modulate consciousness may facilitate tracking of recovery after acute severe brain injury. The ABCD framework classifies resting-state EEG into categories reflecting levels of thalamocortical network function that correlate with outcome in post-cardiac arrest coma. In this longitudinal cohort study, we applied the ABCD framework to 20 patients with acute severe traumatic brain injury requiring intensive care (12 of whom were also studied at ≥6-months post-injury) and 16 healthy controls. We tested four hypotheses: 1) EEG ABCD classifications are spatially heterogeneous and temporally variable; 2) ABCD classifications improve longitudinally, commensurate with the degree of behavioral recovery; 3) ABCD classifications correlate with behavioral level of consciousness; and 4) the Coma Recovery Scale-Revised arousal facilitation protocol yields improved ABCD classifications. Channel-level EEG power spectra were classified based on spectral peaks within pre-defined frequency bands: 'A' = no peaks above delta (<4 Hz) range (complete thalamocortical disruption); 'B' = theta (4-8 Hz) peak (severe thalamocortical disruption); 'C' = theta and beta (13-24 Hz) peaks (moderate thalamocortical disruption); or 'D' = alpha (8-13 Hz) and beta peaks (normal thalamocortical function). Acutely, 95% of patients demonstrated 'D' signals in at least one channel but exhibited within-session temporal variability and spatial heterogeneity in the proportion of different channel-level ABCD classifications. By contrast, healthy participants and patients at follow-up consistently demonstrated signals corresponding to intact thalamocortical network function. Patients demonstrated longitudinal improvement in ABCD classifications (p < .05) and ABCD classification distinguished patients with and without command-following in the subacute-to-chronic phase of recovery (p < .01). In patients studied acutely, ABCD classifications improved after the Coma Recovery Scale-Revised arousal facilitation protocol (p < .05) but did not correspond with behavioral level of consciousness. These findings support the use of the ABCD framework to characterize channel-level EEG dynamics and track fluctuations in functional thalamocortical network integrity in spatial detail.
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Affiliation(s)
- William H Curley
- Harvard Medical School, Boston, MA, USA; Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA, USA
| | - David W Zhou
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Mary M Conte
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA
| | - Andrea S Foulkes
- Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital and Harvard Medical School, Charlestown, MA, USA; Department of Physical Medicine and Rehabilitation, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jonathan D Victor
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA; Department of Neurology, New York Presbyterian Hospital, New York, NY, USA
| | - Nicholas D Schiff
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, New York, NY, USA; Department of Neurology, New York Presbyterian Hospital, New York, NY, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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9
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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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10
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Aubinet C, Schnakers C, Majerus S. Language Assessment in Patients with Disorders of Consciousness. Semin Neurol 2022; 42:273-282. [PMID: 36100226 DOI: 10.1055/s-0042-1755561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Abstract
The assessment of residual language abilities in patients with disorders of consciousness (DoC) after severe brain injury is particularly challenging due to their limited behavioral repertoire. Moreover, associated language impairment such as receptive aphasia may lead to an underestimation of actual consciousness levels. In this review, we examine past research on the assessment of residual language processing in DoC patients, and we discuss currently available tools for identifying language-specific abilities and their prognostic value. We first highlight the need for validated and sensitive bedside behavioral assessment tools for residual language abilities in DoC patients. As regards neuroimaging and electrophysiological methods, the tasks involving higher level linguistic commands appear to be the most informative about level of consciousness and have the best prognostic value. Neuroimaging methods should be combined with the most appropriate behavioral tools in multimodal assessment protocols to assess receptive language abilities in DoC patients in the most complete and sensitive manner.
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Affiliation(s)
- Charlène Aubinet
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium.,Centre du Cerveau, University Hospital of Liège, Liège, Belgium.,Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège, Belgium
| | - Caroline Schnakers
- Research Institute, Casa Colina Hospital and Centers for Healthcare, Pomona, California
| | - Steve Majerus
- Psychology and Neuroscience of Cognition Research Unit, University of Liège, Liège, Belgium
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11
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MacIntyre AD, Cai CQ, Scott SK. Pushing the envelope: Evaluating speech rhythm with different envelope extraction techniques. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2022; 151:2002. [PMID: 35364952 DOI: 10.1121/10.0009844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 03/05/2022] [Indexed: 06/14/2023]
Abstract
The amplitude of the speech signal varies over time, and the speech envelope is an attempt to characterise this variation in the form of an acoustic feature. Although tacitly assumed, the similarity between the speech envelope-derived time series and that of phonetic objects (e.g., vowels) remains empirically unestablished. The current paper, therefore, evaluates several speech envelope extraction techniques, such as the Hilbert transform, by comparing different acoustic landmarks (e.g., peaks in the speech envelope) with manual phonetic annotation in a naturalistic and diverse dataset. Joint speech tasks are also introduced to determine which acoustic landmarks are most closely coordinated when voices are aligned. Finally, the acoustic landmarks are evaluated as predictors for the temporal characterisation of speaking style using classification tasks. The landmark that performed most closely to annotated vowel onsets was peaks in the first derivative of a human audition-informed envelope, consistent with converging evidence from neural and behavioural data. However, differences also emerged based on language and speaking style. Overall, the results show that both the choice of speech envelope extraction technique and the form of speech under study affect how sensitive an engineered feature is at capturing aspects of speech rhythm, such as the timing of vowels.
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Affiliation(s)
| | - Ceci Qing Cai
- Institute of Cognitive Neuroscience, University College London, London, WC1N 3AZ, United Kingdom
| | - Sophie K Scott
- Institute of Cognitive Neuroscience, University College London, London, WC1N 3AZ, United Kingdom
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12
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Schmitt R, Meyer M, Giroud N. Better speech-in-noise comprehension is associated with enhanced neural speech tracking in older adults with hearing impairment. Cortex 2022; 151:133-146. [DOI: 10.1016/j.cortex.2022.02.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 12/19/2021] [Accepted: 02/03/2022] [Indexed: 11/27/2022]
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13
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Porcaro C, Nemirovsky IE, Riganello F, Mansour Z, Cerasa A, Tonin P, Stojanoski B, Soddu A. Diagnostic Developments in Differentiating Unresponsive Wakefulness Syndrome and the Minimally Conscious State. Front Neurol 2022; 12:778951. [PMID: 35095725 PMCID: PMC8793804 DOI: 10.3389/fneur.2021.778951] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Accepted: 12/08/2021] [Indexed: 12/12/2022] Open
Abstract
When treating patients with a disorder of consciousness (DOC), it is essential to obtain an accurate diagnosis as soon as possible to generate individualized treatment programs. However, accurately diagnosing patients with DOCs is challenging and prone to errors when differentiating patients in a Vegetative State/Unresponsive Wakefulness Syndrome (VS/UWS) from those in a Minimally Conscious State (MCS). Upwards of ~40% of patients with a DOC can be misdiagnosed when specifically designed behavioral scales are not employed or improperly administered. To improve diagnostic accuracy for these patients, several important neuroimaging and electrophysiological technologies have been proposed. These include Positron Emission Tomography (PET), functional Magnetic Resonance Imaging (fMRI), Electroencephalography (EEG), and Transcranial Magnetic Stimulation (TMS). Here, we review the different ways in which these techniques can improve diagnostic differentiation between VS/UWS and MCS patients. We do so by referring to studies that were conducted within the last 10 years, which were extracted from the PubMed database. In total, 55 studies met our criteria (clinical diagnoses of VS/UWS from MCS as made by PET, fMRI, EEG and TMS- EEG tools) and were included in this review. By summarizing the promising results achieved in understanding and diagnosing these conditions, we aim to emphasize the need for more such tools to be incorporated in standard clinical practice, as well as the importance of data sharing to incentivize the community to meet these goals.
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Affiliation(s)
- Camillo Porcaro
- Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy
- Institute of Cognitive Sciences and Technologies (ISTC)–National Research Council (CNR), Rome, Italy
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
- Centre for Human Brain Health, School of Psychology, University of Birmingham, Birmingham, United Kingdom
- *Correspondence: Camillo Porcaro ; orcid.org/0000-0003-4847-163X
| | - Idan Efim Nemirovsky
- Department of Physics and Astronomy, Brain and Mind Institute, University of Western Ontario, London, ON, Canada
| | - Francesco Riganello
- Sant'Anna Institute and Research in Advanced Neurorehabilitation (RAN), Crotone, Italy
| | - Zahra Mansour
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| | - Antonio Cerasa
- Sant'Anna Institute and Research in Advanced Neurorehabilitation (RAN), Crotone, Italy
- Institute for Biomedical Research and Innovation (IRIB), National Research Council, Messina, Italy
- Pharmacotechnology Documentation and Transfer Unit, Preclinical and Translational Pharmacology, Department of Pharmacy, Health Science and Nutrition, University of Calabria, Rende, Italy
| | - Paolo Tonin
- Sant'Anna Institute and Research in Advanced Neurorehabilitation (RAN), Crotone, Italy
| | - Bobby Stojanoski
- Faculty of Social Science and Humanities, University of Ontario Institute of Technology, Oshawa, ON, Canada
- Department of Psychology, Brain and Mind Institute, University of Western Ontario, London, ON, Canada
| | - Andrea Soddu
- Department of Physics and Astronomy, Brain and Mind Institute, University of Western Ontario, London, ON, Canada
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14
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Gnanateja GN, Devaraju DS, Heyne M, Quique YM, Sitek KR, Tardif MC, Tessmer R, Dial HR. On the Role of Neural Oscillations Across Timescales in Speech and Music Processing. Front Comput Neurosci 2022; 16:872093. [PMID: 35814348 PMCID: PMC9260496 DOI: 10.3389/fncom.2022.872093] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 05/24/2022] [Indexed: 11/25/2022] Open
Abstract
This mini review is aimed at a clinician-scientist seeking to understand the role of oscillations in neural processing and their functional relevance in speech and music perception. We present an overview of neural oscillations, methods used to study them, and their functional relevance with respect to music processing, aging, hearing loss, and disorders affecting speech and language. We first review the oscillatory frequency bands and their associations with speech and music processing. Next we describe commonly used metrics for quantifying neural oscillations, briefly touching upon the still-debated mechanisms underpinning oscillatory alignment. Following this, we highlight key findings from research on neural oscillations in speech and music perception, as well as contributions of this work to our understanding of disordered perception in clinical populations. Finally, we conclude with a look toward the future of oscillatory research in speech and music perception, including promising methods and potential avenues for future work. We note that the intention of this mini review is not to systematically review all literature on cortical tracking of speech and music. Rather, we seek to provide the clinician-scientist with foundational information that can be used to evaluate and design research studies targeting the functional role of oscillations in speech and music processing in typical and clinical populations.
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Affiliation(s)
- G Nike Gnanateja
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, United States
| | - Dhatri S Devaraju
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, United States
| | - Matthias Heyne
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, United States
| | - Yina M Quique
- Center for Education in Health Sciences, Northwestern University, Chicago, IL, United States
| | - Kevin R Sitek
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, United States
| | - Monique C Tardif
- Department of Communication Science and Disorders, University of Pittsburgh, Pittsburgh, PA, United States
| | - Rachel Tessmer
- Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin, Austin, TX, United States
| | - Heather R Dial
- Department of Speech, Language, and Hearing Sciences, The University of Texas at Austin, Austin, TX, United States.,Department of Communication Sciences and Disorders, University of Houston, Houston, TX, United States
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15
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Palana J, Schwartz S, Tager-Flusberg H. Evaluating the Use of Cortical Entrainment to Measure Atypical Speech Processing: A Systematic Review. Neurosci Biobehav Rev 2021; 133:104506. [PMID: 34942267 DOI: 10.1016/j.neubiorev.2021.12.029] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 12/12/2021] [Accepted: 12/18/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Cortical entrainment has emerged as promising means for measuring continuous speech processing in young, neurotypical adults. However, its utility for capturing atypical speech processing has not been systematically reviewed. OBJECTIVES Synthesize evidence regarding the merit of measuring cortical entrainment to capture atypical speech processing and recommend avenues for future research. METHOD We systematically reviewed publications investigating entrainment to continuous speech in populations with auditory processing differences. RESULTS In the 25 publications reviewed, most studies were conducted on older and/or hearing-impaired adults, for whom slow-wave entrainment to speech was often heightened compared to controls. Research conducted on populations with neurodevelopmental disorders, in whom slow-wave entrainment was often reduced, was less common. Across publications, findings highlighted associations between cortical entrainment and speech processing performance differences. CONCLUSIONS Measures of cortical entrainment offer useful means of capturing speech processing differences and future research should leverage them more extensively when studying populations with neurodevelopmental disorders.
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Affiliation(s)
- Joseph Palana
- Department of Psychological and Brain Sciences, Boston University, 64 Cummington Mall, Boston, MA, 02215, USA; Laboratories of Cognitive Neuroscience, Division of Developmental Medicine, Harvard Medical School, Boston Children's Hospital, 1 Autumn Street, Boston, MA, 02215, USA
| | - Sophie Schwartz
- Department of Psychological and Brain Sciences, Boston University, 64 Cummington Mall, Boston, MA, 02215, USA
| | - Helen Tager-Flusberg
- Department of Psychological and Brain Sciences, Boston University, 64 Cummington Mall, Boston, MA, 02215, USA.
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16
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Aubinet C, Chatelle C, Gosseries O, Carrière M, Laureys S, Majerus S. Residual implicit and explicit language abilities in patients with disorders of consciousness: A systematic review. Neurosci Biobehav Rev 2021; 132:391-409. [PMID: 34864003 DOI: 10.1016/j.neubiorev.2021.12.001] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 11/13/2021] [Accepted: 12/01/2021] [Indexed: 01/14/2023]
Abstract
Language assessment in post-comatose patients is difficult due to their limited behavioral repertoire; yet associated language deficits might lead to an underestimation of consciousness levels in unresponsive wakefulness syndrome (UWS) or minimally conscious state (MCS; -/+) diagnoses. We present a systematic review of studies from 2002 assessing residual language abilities with neuroimaging, electrophysiological or behavioral measures in patients with severe brain injury. Eighty-five articles including a total of 2278 patients were assessed for quality. The median percentages of patients showing residual implicit language abilities (i.e., cortical responses to specific words/sentences) were 33 % for UWS, 50 % for MCS- and 78 % for MCS + patients, whereas explicit language abilities (i.e., command-following using brain-computer interfaces) were reported in 20 % of UWS, 33 % of MCS- and 50 % of MCS + patients. Cortical responses to verbal stimuli increased along with consciousness levels and the progressive recovery of consciousness after a coma was paralleled by the reappearance of both implicit and explicit language processing. This review highlights the importance of language assessment in patients with disorders of consciousness.
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Affiliation(s)
- Charlène Aubinet
- Coma Science Group, GIGA Consciousness, University of Liège, Belgium; Centre du Cerveau, University Hospital of Liège, Belgium.
| | - Camille Chatelle
- Coma Science Group, GIGA Consciousness, University of Liège, Belgium; Centre du Cerveau, University Hospital of Liège, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Belgium; Centre du Cerveau, University Hospital of Liège, Belgium; Fund for Scientific Research, FNRS, Belgium
| | - Manon Carrière
- Coma Science Group, GIGA Consciousness, University of Liège, Belgium; Centre du Cerveau, University Hospital of Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Belgium; Centre du Cerveau, University Hospital of Liège, Belgium; Fund for Scientific Research, FNRS, Belgium
| | - Steve Majerus
- Fund for Scientific Research, FNRS, Belgium; Psychology and Neuroscience of Cognition Research Unit, University of Liège, Belgium.
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17
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Complementary roles of neural synchrony and complexity for indexing consciousness and chances of surviving in acute coma. Neuroimage 2021; 245:118638. [PMID: 34624502 DOI: 10.1016/j.neuroimage.2021.118638] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 09/28/2021] [Accepted: 10/05/2021] [Indexed: 11/23/2022] Open
Abstract
An open challenge in consciousness research is understanding how neural functions are altered by pathological loss of consciousness. To maintain consciousness, the brain needs synchronized communication of information across brain regions, and sufficient complexity in neural activity. Coordination of brain activity, typically indexed through measures of neural synchrony, has been shown to decrease when consciousness is lost and to reflect the clinical state of patients with disorders of consciousness. Moreover, when consciousness is lost, neural activity loses complexity, while the levels of neural noise, indexed by the slope of the electroencephalography (EEG) spectral exponent decrease. Although these properties have been well investigated in resting state activity, it remains unknown whether the sensory processing network, which has been shown to be preserved in coma, suffers from a loss of synchronization or information content. Here, we focused on acute coma and hypothesized that neural synchrony in response to auditory stimuli would reflect coma severity, while complexity, or neural noise, would reflect the presence or loss of consciousness. Results showed that neural synchrony of EEG signals was stronger for survivors than non-survivors and predictive of patients' outcome, but indistinguishable between survivors and healthy controls. Measures of neural complexity and neural noise were not informative of patients' outcome and had high or low values for patients compared to controls. Our results suggest different roles for neural synchrony and complexity in acute coma. Synchrony represents a precondition for consciousness, while complexity needs an equilibrium between high or low values to support conscious cognition.
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18
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Sokoliuk R, Degano G, Melloni L, Noppeney U, Cruse D. The Influence of Auditory Attention on Rhythmic Speech Tracking: Implications for Studies of Unresponsive Patients. Front Hum Neurosci 2021; 15:702768. [PMID: 34456697 PMCID: PMC8385206 DOI: 10.3389/fnhum.2021.702768] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Accepted: 07/21/2021] [Indexed: 11/13/2022] Open
Abstract
Language comprehension relies on integrating words into progressively more complex structures, like phrases and sentences. This hierarchical structure-building is reflected in rhythmic neural activity across multiple timescales in E/MEG in healthy, awake participants. However, recent studies have shown evidence for this “cortical tracking” of higher-level linguistic structures also in a proportion of unresponsive patients. What does this tell us about these patients’ residual levels of cognition and consciousness? Must the listener direct their attention toward higher level speech structures to exhibit cortical tracking, and would selective attention across levels of the hierarchy influence the expression of these rhythms? We investigated these questions in an EEG study of 72 healthy human volunteers listening to streams of monosyllabic isochronous English words that were either unrelated (scrambled condition) or composed of four-word-sequences building meaningful sentences (sentential condition). Importantly, there were no physical cues between four-word-sentences. Rather, boundaries were marked by syntactic structure and thematic role assignment. Participants were divided into three attention groups: from passive listening (passive group) to attending to individual words (word group) or sentences (sentence group). The passive and word groups were initially naïve to the sentential stimulus structure, while the sentence group was not. We found significant tracking at word- and sentence rate across all three groups, with sentence tracking linked to left middle temporal gyrus and right superior temporal gyrus. Goal-directed attention to words did not enhance word-rate-tracking, suggesting that word tracking here reflects largely automatic mechanisms, as was shown for tracking at the syllable-rate before. Importantly, goal-directed attention to sentences relative to words significantly increased sentence-rate-tracking over left inferior frontal gyrus. This attentional modulation of rhythmic EEG activity at the sentential rate highlights the role of attention in integrating individual words into complex linguistic structures. Nevertheless, given the presence of high-level cortical tracking under conditions of lower attentional effort, our findings underline the suitability of the paradigm in its clinical application in patients after brain injury. The neural dissociation between passive tracking of sentences and directed attention to sentences provides a potential means to further characterise the cognitive state of each unresponsive patient.
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Affiliation(s)
- Rodika Sokoliuk
- School of Psychology, University of Birmingham, Birmingham, United Kingdom.,Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
| | - Giulio Degano
- School of Psychology, University of Birmingham, Birmingham, United Kingdom.,Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom.,Brain and Language Lab, Department of Psychology, Faculty of Psychology and Educational Sciences, University of Geneva, Geneva, Switzerland
| | - Lucia Melloni
- Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany.,Department of Neurology, New York University, New York City, NY, United States
| | - Uta Noppeney
- Donders Centre for Cognitive Neuroimaging, Nijmegen, Netherlands.,Department of Biophysics, Radboud University, Nijmegen, Netherlands
| | - Damian Cruse
- School of Psychology, University of Birmingham, Birmingham, United Kingdom.,Centre for Human Brain Health, University of Birmingham, Birmingham, United Kingdom
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19
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Sanz LRD, Thibaut A, Edlow BL, Laureys S, Gosseries O. Update on neuroimaging in disorders of consciousness. Curr Opin Neurol 2021; 34:488-496. [PMID: 34054109 PMCID: PMC8938964 DOI: 10.1097/wco.0000000000000951] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
PURPOSE OF REVIEW Neuroimaging has acquired a prominent place in the assessment of disorders of consciousness (DoC). Rapidly evolving technologies combined with state-of-the-art data analyses open new horizons to probe brain activity, but selecting appropriate imaging modalities from the plethora of available techniques can be challenging for clinicians. This update reviews selected advances in neuroimaging that demonstrate clinical relevance and translational potential in the assessment of severely brain-injured patients with DoC. RECENT FINDINGS Magnetic resonance imaging and high-density electroencephalography provide measurements of brain connectivity between functional networks, assessments of language function, detection of covert consciousness, and prognostic markers of recovery. Positron emission tomography can identify patients with preserved brain metabolism despite clinical unresponsiveness and can measure glucose consumption rates in targeted brain regions. Transcranial magnetic stimulation and near-infrared spectroscopy are noninvasive and practical tools with promising clinical applications. SUMMARY Each neuroimaging technique conveys advantages and pitfalls to assess consciousness. We recommend a multimodal approach in which complementary techniques provide diagnostic and prognostic information about brain function. Patients demonstrating neuroimaging evidence of covert consciousness may benefit from early adapted rehabilitation. Translating methodological advances to clinical care will require the implementation of recently published international guidelines and the integration of neuroimaging techniques into patient-centered decision-making algorithms.
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Affiliation(s)
- Leandro R. D. Sanz
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Aurore Thibaut
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Brian L. Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du Cerveau, University Hospital of Liège, Liège, Belgium
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20
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Claassen J, Akbari Y, Alexander S, Bader MK, Bell K, Bleck TP, Boly M, Brown J, Chou SHY, Diringer MN, Edlow BL, Foreman B, Giacino JT, Gosseries O, Green T, Greer DM, Hanley DF, Hartings JA, Helbok R, Hemphill JC, Hinson HE, Hirsch K, Human T, James ML, Ko N, Kondziella D, Livesay S, Madden LK, Mainali S, Mayer SA, McCredie V, McNett MM, Meyfroidt G, Monti MM, Muehlschlegel S, Murthy S, Nyquist P, Olson DM, Provencio JJ, Rosenthal E, Sampaio Silva G, Sarasso S, Schiff ND, Sharshar T, Shutter L, Stevens RD, Vespa P, Videtta W, Wagner A, Ziai W, Whyte J, Zink E, Suarez JI. Proceedings of the First Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness. Neurocrit Care 2021; 35:4-23. [PMID: 34236619 PMCID: PMC8264966 DOI: 10.1007/s12028-021-01260-x] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Accepted: 04/15/2021] [Indexed: 01/04/2023]
Abstract
Coma and disorders of consciousness (DoC) are highly prevalent and constitute a burden for patients, families, and society worldwide. As part of the Curing Coma Campaign, the Neurocritical Care Society partnered with the National Institutes of Health to organize a symposium bringing together experts from all over the world to develop research targets for DoC. The conference was structured along six domains: (1) defining endotype/phenotypes, (2) biomarkers, (3) proof-of-concept clinical trials, (4) neuroprognostication, (5) long-term recovery, and (6) large datasets. This proceedings paper presents actionable research targets based on the presentations and discussions that occurred at the conference. We summarize the background, main research gaps, overall goals, the panel discussion of the approach, limitations and challenges, and deliverables that were identified.
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Affiliation(s)
- Jan Claassen
- Department of Neurology, Columbia University and New York-Presbyterian Hospital, 177 Fort Washington Avenue, MHB 8 Center, Room 300, New York City, NY, 10032, USA.
| | - Yama Akbari
- Departments of Neurology, Neurological Surgery, and Anatomy & Neurobiology and Beckman Laser Institute and Medical Clinic, University of California, Irvine, Irvine, CA, USA
| | - Sheila Alexander
- Acute and Tertiary Care, School of Nursing and Critical Care Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | | | - Kathleen Bell
- Department of Physical Medicine and Rehabilitation, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Thomas P Bleck
- Davee Department of Neurology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Melanie Boly
- Department of Neurology, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Jeremy Brown
- Office of Emergency Care Research, Division of Clinical Research, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Sherry H-Y Chou
- Departments of Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael N Diringer
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Brian L Edlow
- Department of Neurology, Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital and Harvard Medical School, Harvard University, Boston, MA, USA
| | - Brandon Foreman
- Departments of Neurology and Rehabilitation Medicine, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Olivia Gosseries
- GIGA Consciousness After Coma Science Group, University of Liege, Liege, Belgium
| | - Theresa Green
- School of Nursing, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - David M Greer
- Department of Neurology, School of Medicine, Boston University, Boston, MA, USA
| | - Daniel F Hanley
- Division of Brain Injury Outcomes, Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jed A Hartings
- Department of Neurosurgery, College of Medicine, University of Cincinnati, Cincinnati, OH, USA
| | - Raimund Helbok
- Neurocritical Care Unit, Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - J Claude Hemphill
- Department of Neurology, Weill Institute for Neurosciences, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - H E Hinson
- Department of Neurology, School of Medicine, Oregon Health & Science University, Portland, OR, USA
| | - Karen Hirsch
- Department of Neurology, Stanford University, Palo Alto, CA, USA
| | - Theresa Human
- Department of Pharmacy, Barnes Jewish Hospital, St. Louis, MO, USA
| | - Michael L James
- Departments of Anesthesiology and Neurology, Duke University, Durham, NC, USA
| | - Nerissa Ko
- Department of Neurology, Weill Institute for Neurosciences, School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Daniel Kondziella
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - Sarah Livesay
- College of Nursing, Rush University, Chicago, IL, USA
| | - Lori K Madden
- Center for Nursing Science, University of California, Davis, Sacramento, CA, USA
| | - Shraddha Mainali
- Department of Neurology, The Ohio State University, Columbus, OH, USA
| | - Stephan A Mayer
- Department of Neurology, New York Medical College, Valhalla, NY, USA
| | - Victoria McCredie
- Interdepartmental Division of Critical Care, Department of Respirology, University of Toronto, Toronto, ON, Canada
| | - Molly M McNett
- College of Nursing, The Ohio State University, Columbus, OH, USA
| | - Geert Meyfroidt
- Department of Intensive Care Medicine, University Hospitals Leuven and University of Leuven, Leuven, Belgium
| | - Martin M Monti
- Departments of Neurosurgery and Psychology, Brain Injury Research Center, University of California, Los Angeles, Los Angeles, CA, USA
| | - Susanne Muehlschlegel
- Departments of Neurology, Anesthesiology/Critical Care, and Surgery, Medical School, University of Massachusetts, Worcester, MA, USA
| | - Santosh Murthy
- Department of Neurology, Weill Cornell Medical College, New York City, NY, USA
| | - Paul Nyquist
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - DaiWai M Olson
- Departments of Neurology and Neurosurgery, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - J Javier Provencio
- Departments of Neurology and Neuroscience, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Eric Rosenthal
- Department of Neurology, Harvard Medical School, Harvard University, Boston, MA, USA
| | - Gisele Sampaio Silva
- Department of Neurology, Albert Einstein Israelite Hospital and Universidade Federal de São Paulo, São Paulo, Brazil
| | - Simone Sarasso
- Department of Biomedical and Clinical Sciences "L. Sacco", Università degli Studi di Milano, Milan, Italy
| | - Nicholas D Schiff
- Department of Neurology and Brain Mind Research Institute, Weill Cornell Medicine, Cornell University, New York City, NY, USA
| | - Tarek Sharshar
- Department of Intensive Care, Paris Descartes University, Paris, France
| | - Lori Shutter
- Departments of Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Robert D Stevens
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Paul Vespa
- Departments of Neurosurgery and Neurology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Walter Videtta
- National Hospital Alejandro Posadas, Buenos Aires, Argentina
| | - Amy Wagner
- Department of Physical Medicine and Rehabilitation, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wendy Ziai
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - John Whyte
- Moss Rehabilitation Research Institute, Elkins Park, PA, USA
| | - Elizabeth Zink
- Division of Neurosciences Critical Care, Department of Neurology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jose I Suarez
- Division of Neurosciences Critical Care, Departments of Anesthesiology and Critical Care Medicine, Neurology, and Neurosurgery, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
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21
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Abstract
PURPOSE OF REVIEW Recovery after severe brain injury is variable and challenging to accurately predict at the individual patient level. This review highlights new developments in clinical prognostication with a special focus on the prediction of consciousness and increasing reliance on methods from data science. RECENT FINDINGS Recent research has leveraged serum biomarkers, quantitative electroencephalography, MRI, and physiological time-series to build models for recovery prediction. The analysis of high-resolution data and the integration of features from different modalities can be approached with efficient computational techniques. SUMMARY Advances in neurophysiology and neuroimaging, in combination with computational methods, represent a novel paradigm for prediction of consciousness and functional recovery after severe brain injury. Research is needed to produce reliable, patient-level predictions that could meaningfully impact clinical decision making.
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22
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Xu C, Zou J, He F, Wen X, Li J, Gao J, Ding N, Luo B. Neural Tracking of Sound Rhythms Correlates With Diagnosis, Severity, and Prognosis of Disorders of Consciousness. Front Neurosci 2021; 15:646543. [PMID: 33994924 PMCID: PMC8113690 DOI: 10.3389/fnins.2021.646543] [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: 12/27/2020] [Accepted: 03/19/2021] [Indexed: 12/03/2022] Open
Abstract
Effective diagnosis and prognosis of patients with disorders of consciousness (DOC) provides a basis for family counseling, decision-making, and the design of rehabilitation programs. However, effective and objective bedside evaluation is a challenging problem. In this study, we explored electroencephalography (EEG) response tracking sound rhythms as potential neural markers for DOC evaluation. We analyzed the responses to natural speech and tones modulated at 2 and 41 Hz. At the population level, patients with positive outcomes (DOC-P) showed higher cortical synchronization to modulated tones at 41 Hz compared with patients with negative outcomes (DOC-N). At the individual level, phase coherence to modulated tones at 41 Hz was significantly correlated with Coma Recovery Scale-Revised (CRS-R) and Glasgow Outcome Scale-Extended (GOS-E) scores. Furthermore, SVM classifiers, trained using phase coherences in higher frequency bands or combination of the low frequency aSSR and speech tracking responses, performed very well in diagnosis and prognosis of DOC. These findings show that EEG response to auditory rhythms is a potential tool for diagnosis, severity, and prognosis of DOC.
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Affiliation(s)
- Chuan Xu
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jiajie Zou
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China.,Research Center for Advanced Artificial Intelligence Theory Zhejiang Lab, Hangzhou, China
| | - Fangping He
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xinrui Wen
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jingqi Li
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou, China
| | - Jian Gao
- Department of Rehabilitation, Hangzhou Mingzhou Brain Rehabilitation Hospital, Hangzhou, China
| | - Nai Ding
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Sciences, Zhejiang University, Hangzhou, China.,Research Center for Advanced Artificial Intelligence Theory Zhejiang Lab, Hangzhou, China
| | - Benyan Luo
- Department of Neurology, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
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23
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Olsen A, Babikian T, Bigler ED, Caeyenberghs K, Conde V, Dams-O'Connor K, Dobryakova E, Genova H, Grafman J, Håberg AK, Heggland I, Hellstrøm T, Hodges CB, Irimia A, Jha RM, Johnson PK, Koliatsos VE, Levin H, Li LM, Lindsey HM, Livny A, Løvstad M, Medaglia J, Menon DK, Mondello S, Monti MM, Newcombe VFJ, Petroni A, Ponsford J, Sharp D, Spitz G, Westlye LT, Thompson PM, Dennis EL, Tate DF, Wilde EA, Hillary FG. Toward a global and reproducible science for brain imaging in neurotrauma: the ENIGMA adult moderate/severe traumatic brain injury working group. Brain Imaging Behav 2021; 15:526-554. [PMID: 32797398 PMCID: PMC8032647 DOI: 10.1007/s11682-020-00313-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
The global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group's short-term, intermediate, and long-term goals.
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Affiliation(s)
- Alexander Olsen
- Department of Psychology, Norwegian University of Science and Technology, 7491, Trondheim, Norway.
- Department of Physical Medicine and Rehabilitation, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
| | - Talin Babikian
- Department of Psychiatry and Biobehavioral Sciences, Semel Institute for Neuroscience and Human Behavior, UCLA, Los Angeles, CA, USA
- UCLA Steve Tisch BrainSPORT Program, Los Angeles, CA, USA
| | - Erin D Bigler
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Psychology and Neuroscience Center, Brigham Young University, Provo, UT, USA
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Australia
| | - Virginia Conde
- Department of Psychology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Kristen Dams-O'Connor
- Department of Rehabilitation Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ekaterina Dobryakova
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ, USA
- Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Helen Genova
- Center for Traumatic Brain Injury, Kessler Foundation, East Hanover, NJ, USA
| | - Jordan Grafman
- Cognitive Neuroscience Laboratory, Shirley Ryan AbilityLab, Chicago, IL, USA
- Department of Physical Medicine & Rehabilitation, Neurology, Department of Psychiatry & Department of Psychology, Cognitive Neurology and Alzheimer's, Center, Feinberg School of Medicine, Weinberg, Chicago, IL, USA
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs Hopsital, Trondheim University Hospital, Trondheim, Norway
| | - Ingrid Heggland
- Section for Collections and Digital Services, NTNU University Library, Norwegian University of Science and Technology, Trondheim, Norway
| | - Torgeir Hellstrøm
- Department of Physical Medicine and Rehabilitation, Oslo University Hospital, Oslo, Norway
| | - Cooper B Hodges
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Psychology, Brigham Young University, Provo, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Andrei Irimia
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
| | - Ruchira M Jha
- Departments of Critical Care Medicine, Neurology, Neurological Surgery, University of Pittsburgh, Pittsburgh, PA, USA
- Safar Center for Resuscitation Research, Pittsburgh, PA, USA
- Clinical and Translational Science Institute, Pittsburgh, PA, USA
| | - Paula K Johnson
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- Neuroscience Center, Brigham Young University, Provo, UT, USA
| | - Vassilis E Koliatsos
- Departments of Pathology(Neuropathology), Neurology, and Psychiatry and Behavioral Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Neuropsychiatry Program, Sheppard and Enoch Pratt Hospital, Baltimore, MD, USA
| | - Harvey Levin
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
- Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX, USA
| | - Lucia M Li
- C3NL, Imperial College London, London, UK
- UK DRI Centre for Health Care and Technology, Imperial College London, London, UK
| | - Hannah M Lindsey
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Psychology, Brigham Young University, Provo, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Abigail Livny
- Department of Diagnostic Imaging, Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel
- Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel
| | - Marianne Løvstad
- Sunnaas Rehabilitation Hospital, Nesodden, Norway
- Department of Psychology, University of Oslo, Oslo, Norway
| | - John Medaglia
- Department of Psychology, Drexel University, Philadelphia, PA, USA
- Department of Neurology, Drexel University, Philadelphia, PA, USA
| | - David K Menon
- Division of Anaesthesia, University of Cambridge, Cambridge, UK
| | - Stefania Mondello
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Martin M Monti
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
- Department of Neurosurgery, Brain Injury Research Center (BIRC), UCLA, Los Angeles, CA, USA
| | | | - Agustin Petroni
- Department of Psychology, Norwegian University of Science and Technology, 7491, Trondheim, Norway
- Department of Computer Science, Faculty of Exact & Natural Sciences, University of Buenos Aires, Buenos Aires, Argentina
- National Scientific & Technical Research Council, Institute of Research in Computer Science, Buenos Aires, Argentina
| | - Jennie Ponsford
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia
- Monash Epworth Rehabilitation Research Centre, Epworth Healthcare, Melbourne, Australia
| | - David Sharp
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research & Technology Centre, UK Dementia Research Institute, London, UK
| | - Gershon Spitz
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Melbourne, Australia
| | - Lars T Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
- Departments of Neurology, Pediatrics, Psychiatry, Radiology, Engineering, and Ophthalmology, USC, Los Angeles, CA, USA
| | - Emily L Dennis
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- Imaging Genetics Center, Stevens Neuroimaging & Informatics Institute, Keck School of Medicine of USC, Marina del Rey, CA, USA
| | - David F Tate
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Elisabeth A Wilde
- Department of Neurology, University of Utah School of Medicine, Salt Lake City, UT, USA
- George E. Wahlen Veterans Affairs Medical Center, Salt Lake City, UT, USA
- H. Ben Taub Department of Physical Medicine and Rehabilitation, Baylor College of Medicine, Houston, TX, USA
| | - Frank G Hillary
- Department of Neurology, Hershey Medical Center, State College, PA, USA.
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24
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Edlow BL, Claassen J, Schiff ND, Greer DM. Recovery from disorders of consciousness: mechanisms, prognosis and emerging therapies. Nat Rev Neurol 2021; 17:135-156. [PMID: 33318675 PMCID: PMC7734616 DOI: 10.1038/s41582-020-00428-x] [Citation(s) in RCA: 238] [Impact Index Per Article: 79.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/23/2020] [Indexed: 12/16/2022]
Abstract
Substantial progress has been made over the past two decades in detecting, predicting and promoting recovery of consciousness in patients with disorders of consciousness (DoC) caused by severe brain injuries. Advanced neuroimaging and electrophysiological techniques have revealed new insights into the biological mechanisms underlying recovery of consciousness and have enabled the identification of preserved brain networks in patients who seem unresponsive, thus raising hope for more accurate diagnosis and prognosis. Emerging evidence suggests that covert consciousness, or cognitive motor dissociation (CMD), is present in up to 15-20% of patients with DoC and that detection of CMD in the intensive care unit can predict functional recovery at 1 year post injury. Although fundamental questions remain about which patients with DoC have the potential for recovery, novel pharmacological and electrophysiological therapies have shown the potential to reactivate injured neural networks and promote re-emergence of consciousness. In this Review, we focus on mechanisms of recovery from DoC in the acute and subacute-to-chronic stages, and we discuss recent progress in detecting and predicting recovery of consciousness. We also describe the developments in pharmacological and electrophysiological therapies that are creating new opportunities to improve the lives of patients with DoC.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, New York Presbyterian Hospital, New York, NY, USA
| | - Nicholas D Schiff
- Feil Family Brain Mind Research Institute, Weill Cornell Medical College, New York, NY, USA
| | - David M Greer
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA.
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25
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Edlow BL, Naccache L. Unmasking Covert Language Processing in the Intensive Care Unit with Electroencephalography. Ann Neurol 2021; 89:643-645. [PMID: 33491250 PMCID: PMC8048541 DOI: 10.1002/ana.26030] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 01/20/2021] [Accepted: 01/21/2021] [Indexed: 01/16/2023]
Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA.,Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA
| | - Lionel Naccache
- PICNIC Lab Team, INSERM, U 1127, CNRS UMR 7225, Faculté de Médecine de Sorbonne Université, UMR S 1127, Institut du Cerveau et de la Moelle épinière, ICM, Hôpital Pitié-Salpêtrière, Paris, France.,APHP, Departments of Neurology and of Clinical Neurophysiology, Hôpital de la Salpêtriere, Paris, France
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26
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Effect of number and placement of EEG electrodes on measurement of neural tracking of speech. PLoS One 2021; 16:e0246769. [PMID: 33571299 PMCID: PMC7877609 DOI: 10.1371/journal.pone.0246769] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 01/25/2021] [Indexed: 11/19/2022] Open
Abstract
Measurement of neural tracking of natural running speech from the electroencephalogram (EEG) is an increasingly popular method in auditory neuroscience and has applications in audiology. The method involves decoding the envelope of the speech signal from the EEG signal, and calculating the correlation with the envelope of the audio stream that was presented to the subject. Typically EEG systems with 64 or more electrodes are used. However, in practical applications, set-ups with fewer electrodes are required. Here, we determine the optimal number of electrodes, and the best position to place a limited number of electrodes on the scalp. We propose a channel selection strategy based on an utility metric, which allows a quick quantitative assessment of the influence of a channel (or a group of channels) on the reconstruction error. We consider two use cases: a subject-specific case, where the optimal number and position of the electrodes is determined for each subject individually, and a subject-independent case, where the electrodes are placed at the same positions (in the 10-20 system) for all the subjects. We evaluated our approach using 64-channel EEG data from 90 subjects. In the subject-specific case we found that the correlation between actual and reconstructed envelope first increased with decreasing number of electrodes, with an optimum at around 20 electrodes, yielding 29% higher correlations using the optimal number of electrodes compared to all electrodes. This means that our strategy of removing electrodes can be used to improve the correlation metric in high-density EEG recordings. In the subject-independent case, we obtained a stable decoding performance when decreasing from 64 to 22 channels. When the number of channels was further decreased, the correlation decreased. For a maximal decrease in correlation of 10%, 32 well-placed electrodes were sufficient in 91% of the subjects.
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27
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Sokoliuk R, Degano G, Banellis L, Melloni L, Hayton T, Sturman S, Veenith T, Yakoub KM, Belli A, Noppeney U, Cruse D. Covert Speech Comprehension Predicts Recovery From Acute Unresponsive States. Ann Neurol 2021; 89:646-656. [PMID: 33368496 DOI: 10.1002/ana.25995] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 12/07/2020] [Accepted: 12/07/2020] [Indexed: 11/08/2022]
Abstract
OBJECTIVE Patients with traumatic brain injury who fail to obey commands after sedation-washout pose one of the most significant challenges for neurological prognostication. Reducing prognostic uncertainty will lead to more appropriate care decisions and ensure provision of limited rehabilitation resources to those most likely to benefit. Bedside markers of covert residual cognition, including speech comprehension, may reduce this uncertainty. METHODS We recruited 28 patients with acute traumatic brain injury who were 2 to 7 days sedation-free and failed to obey commands. Patients heard streams of isochronous monosyllabic words that built meaningful phrases and sentences while their brain activity via electroencephalography (EEG) was recorded. In healthy individuals, EEG activity only synchronizes with the rhythm of phrases and sentences when listeners consciously comprehend the speech. This approach therefore provides a measure of residual speech comprehension in unresponsive patients. RESULTS Seventeen and 16 patients were available for assessment with the Glasgow Outcome Scale Extended (GOSE) at 3 months and 6 months, respectively. Outcome significantly correlated with the strength of patients' acute cortical tracking of phrases and sentences (r > 0.6, p < 0.007), quantified by inter-trial phase coherence. Linear regressions revealed that the strength of this comprehension response (beta = 0.603, p = 0.006) significantly improved the accuracy of prognoses relative to clinical characteristics alone (eg, Glasgow Coma Scale [GCS], computed tomography [CT] grade). INTERPRETATION A simple, passive, auditory EEG protocol improves prognostic accuracy in a critical period of clinical decision making. Unlike other approaches to probing covert cognition for prognostication, this approach is entirely passive and therefore less susceptible to cognitive deficits, increasing the number of patients who may benefit. ANN NEUROL 2021;89:646-656.
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Affiliation(s)
- Rodika Sokoliuk
- School of Psychology, University of Birmingham, Birmingham, UK.,Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Giulio Degano
- School of Psychology, University of Birmingham, Birmingham, UK.,Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Leah Banellis
- School of Psychology, University of Birmingham, Birmingham, UK.,Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Lucia Melloni
- Department of Neuroscience, Max Planck Institute for Empirical Aesthetics, Frankfurt, Germany.,Department of Neurology, New York University School of Medicine, New York, NY, USA
| | - Tom Hayton
- Surgical Reconstruction and Microbiology Research Centre, National Institute for Health Research, Birmingham, UK
| | - Steve Sturman
- Surgical Reconstruction and Microbiology Research Centre, National Institute for Health Research, Birmingham, UK
| | - Tonny Veenith
- Surgical Reconstruction and Microbiology Research Centre, National Institute for Health Research, Birmingham, UK.,Birmingham Acute Care Research Group, Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
| | - Kamal M Yakoub
- Surgical Reconstruction and Microbiology Research Centre, National Institute for Health Research, Birmingham, UK
| | - Antonio Belli
- Centre for Human Brain Health, University of Birmingham, Birmingham, UK.,Surgical Reconstruction and Microbiology Research Centre, National Institute for Health Research, Birmingham, UK
| | - Uta Noppeney
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Damian Cruse
- School of Psychology, University of Birmingham, Birmingham, UK.,Centre for Human Brain Health, University of Birmingham, Birmingham, UK
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28
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Friston KJ, Sajid N, Quiroga-Martinez DR, Parr T, Price CJ, Holmes E. Active listening. Hear Res 2021; 399:107998. [PMID: 32732017 PMCID: PMC7812378 DOI: 10.1016/j.heares.2020.107998] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2019] [Revised: 05/11/2020] [Accepted: 05/13/2020] [Indexed: 11/27/2022]
Abstract
This paper introduces active listening, as a unified framework for synthesising and recognising speech. The notion of active listening inherits from active inference, which considers perception and action under one universal imperative: to maximise the evidence for our (generative) models of the world. First, we describe a generative model of spoken words that simulates (i) how discrete lexical, prosodic, and speaker attributes give rise to continuous acoustic signals; and conversely (ii) how continuous acoustic signals are recognised as words. The 'active' aspect involves (covertly) segmenting spoken sentences and borrows ideas from active vision. It casts speech segmentation as the selection of internal actions, corresponding to the placement of word boundaries. Practically, word boundaries are selected that maximise the evidence for an internal model of how individual words are generated. We establish face validity by simulating speech recognition and showing how the inferred content of a sentence depends on prior beliefs and background noise. Finally, we consider predictive validity by associating neuronal or physiological responses, such as the mismatch negativity and P300, with belief updating under active listening, which is greatest in the absence of accurate prior beliefs about what will be heard next.
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Affiliation(s)
- Karl J Friston
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, WC1N 3AR, UK.
| | - Noor Sajid
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, WC1N 3AR, UK.
| | | | - Thomas Parr
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, WC1N 3AR, UK.
| | - Cathy J Price
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, WC1N 3AR, UK.
| | - Emma Holmes
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, London, WC1N 3AR, UK.
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29
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Friston KJ, Parr T, Yufik Y, Sajid N, Price CJ, Holmes E. Generative models, linguistic communication and active inference. Neurosci Biobehav Rev 2020; 118:42-64. [PMID: 32687883 PMCID: PMC7758713 DOI: 10.1016/j.neubiorev.2020.07.005] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Revised: 06/26/2020] [Accepted: 07/08/2020] [Indexed: 11/24/2022]
Abstract
This paper presents a biologically plausible generative model and inference scheme that is capable of simulating communication between synthetic subjects who talk to each other. Building on active inference formulations of dyadic interactions, we simulate linguistic exchange to explore generative models that support dialogues. These models employ high-order interactions among abstract (discrete) states in deep (hierarchical) models. The sequential nature of language processing mandates generative models with a particular factorial structure-necessary to accommodate the rich combinatorics of language. We illustrate linguistic communication by simulating a synthetic subject who can play the 'Twenty Questions' game. In this game, synthetic subjects take the role of the questioner or answerer, using the same generative model. This simulation setup is used to illustrate some key architectural points and demonstrate that many behavioural and neurophysiological correlates of linguistic communication emerge under variational (marginal) message passing, given the right kind of generative model. For example, we show that theta-gamma coupling is an emergent property of belief updating, when listening to another.
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Affiliation(s)
- Karl J Friston
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, 12 Queen Square, London, WC1N 3AR, UK.
| | - Thomas Parr
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, 12 Queen Square, London, WC1N 3AR, UK.
| | - Yan Yufik
- Virtual Structures Research, Inc., 12204 Saint James Rd, Potomac, MD 20854, USA.
| | - Noor Sajid
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, 12 Queen Square, London, WC1N 3AR, UK.
| | - Catherine J Price
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, 12 Queen Square, London, WC1N 3AR, UK.
| | - Emma Holmes
- The Wellcome Centre for Human Neuroimaging, UCL Queen Square Institute of Neurology, 12 Queen Square, London, WC1N 3AR, UK.
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30
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Chatelle C, Rosenthal ES, Bodien YG, Spencer-Salmon CA, Giacino JT, Edlow BL. EEG Correlates of Language Function in Traumatic Disorders of Consciousness. Neurocrit Care 2020; 33:449-457. [PMID: 31900883 PMCID: PMC7373666 DOI: 10.1007/s12028-019-00904-3] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
BACKGROUND/OBJECTIVE Behavioral examinations may fail to detect language function in patients with severe traumatic brain injury (TBI) due to confounds such as having an endotracheal tube. We investigated whether resting and stimulus-evoked electroencephalography (EEG) methods detect the presence of language function in patients with severe TBI. METHODS Four EEG measures were assessed: (1) resting background (applying Forgacs' criteria), (2) reactivity to speech, (3) background and reactivity (applying Synek's criteria); and (4) an automated support vector machine (classifier for speech versus rest). Cohen's kappa measured agreement between the four EEG measures and evidence of language function on a behavioral coma recovery scale-revised (CRS-R) and composite (CRS-R or functional MRI) reference standard. Sensitivity and specificity of each EEG measure were calculated against the reference standards. RESULTS We enrolled 17 adult patients with severe TBI (mean ± SD age 27.0 ± 7.0 years; median [range] 11.5 [2-1173] days post-injury) and 16 healthy subjects (age 28.5 ± 7.8 years). The classifier, followed by Forgacs' criteria for resting background, demonstrated the highest agreement with the behavioral reference standard. Only Synek's criteria for background and reactivity showed significant agreement with the composite reference standard. The classifier and resting background showed balanced sensitivity and specificity for behavioral (sensitivity = 84.6% and 80.8%; specificity = 57.1% for both) and composite reference standards (sensitivity = 79.3% and 75.9%, specificity = 50% for both). CONCLUSIONS Methods applying an automated classifier, resting background, or resting background with reactivity may identify severe TBI patients with preserved language function. Automated classifier methods may enable unbiased and efficient assessment of larger populations or serial timepoints, while qualitative visual methods may be practical in community settings.
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Affiliation(s)
- Camille Chatelle
- GIGA Consciousness, Coma Science Group, University of Liège, Avenue de l'Hôpital, 11, 4000, Liège, Belgium.
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA.
| | - Eric S Rosenthal
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Clinical Data Animation Center, Massachusetts General Hospital, Boston, MA, USA
| | - Yelena G Bodien
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Joseph T Giacino
- Department of Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Harvard Medical School, Boston, MA, USA
| | - Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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31
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Tóth B, Honbolygó F, Szalárdy O, Orosz G, Farkas D, Winkler I. The effects of speech processing units on auditory stream segregation and selective attention in a multi-talker (cocktail party) situation. Cortex 2020; 130:387-400. [DOI: 10.1016/j.cortex.2020.06.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Revised: 03/24/2020] [Accepted: 06/08/2020] [Indexed: 10/23/2022]
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32
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Gui P, Jiang Y, Zang D, Qi Z, Tan J, Tanigawa H, Jiang J, Wen Y, Xu L, Zhao J, Mao Y, Poo MM, Ding N, Dehaene S, Wu X, Wang L. Assessing the depth of language processing in patients with disorders of consciousness. Nat Neurosci 2020; 23:761-770. [DOI: 10.1038/s41593-020-0639-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Accepted: 04/08/2020] [Indexed: 12/18/2022]
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33
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Binder M, Górska U, Pipinis E, Voicikas A, Griskova-Bulanova I. Auditory steady-state response to chirp-modulated tones: A pilot study in patients with disorders of consciousness. NEUROIMAGE-CLINICAL 2020; 27:102261. [PMID: 32388346 PMCID: PMC7215243 DOI: 10.1016/j.nicl.2020.102261] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Revised: 03/23/2020] [Accepted: 03/29/2020] [Indexed: 12/17/2022]
Abstract
Chirp-evoked responses were evaluated in patients with disorders of consciousness. PLI estimates in 38–42 Hz window positively correlated with the CRS-R total score. Gamma-range evoked activity may indicate the integrity of thalamocortical networks.
Objective Due to the problems with behavioral diagnosis of patients with prolonged DOC (disorders of consciousness), complementary approaches based on objective measurement of neural function are necessary. In this pilot study, we assessed the sensitivity of auditory chirp-evoked responses to the state of patients with severe brain injury as measured with CRS-R (Coma Recovery Scale - Revised). Methods A convenience sample of fifteen DOC patients was included in the study. Auditory stimuli, chirp-modulated at 1–120 Hz were used to evoke auditory steady-state response (ASSR). Phase-locking index (PLI) estimates within low gamma and high gamma windows were evaluated. Results The PLI estimates within a narrow low gamma 38–42 Hz window positively correlated with the CRS-R total score and with the scores of the Auditory and Visual Function subscales. In the same low gamma window, significant difference in the PLIs was found between minimally conscious (MCS) and vegetative state (VS) patients. We did not observe any between-group differences nor any significant correlations with CRS-R scores in the high gamma window (80–110 Hz). Conclusions Our results support the notion that the activity around 40 Hz may serve as a possible marker of the integrity of thalamocortical networks in prolonged DOC patients. Significance Auditory steady-state responses at gamma-band frequencies highlight the role of upper parts of auditory system in evaluation of the level of consciousness in DOC patients.
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Affiliation(s)
- Marek Binder
- Institute of Psychology, Jagiellonian University, ul. Ingardena 6, 30-060 Krakow, Poland.
| | - Urszula Górska
- Institute of Psychology, Jagiellonian University, ul. Ingardena 6, 30-060 Krakow, Poland
| | - Evaldas Pipinis
- Department of Neurobiology and Biophysics, Vilnius University, Sauletekio ave 7, LT-10257 Vilnius, Lithuania
| | - Aleksandras Voicikas
- Department of Neurobiology and Biophysics, Vilnius University, Sauletekio ave 7, LT-10257 Vilnius, Lithuania
| | - Inga Griskova-Bulanova
- Department of Neurobiology and Biophysics, Vilnius University, Sauletekio ave 7, LT-10257 Vilnius, Lithuania
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Kondziella D, Bender A, Diserens K, van Erp W, Estraneo A, Formisano R, Laureys S, Naccache L, Ozturk S, Rohaut B, Sitt JD, Stender J, Tiainen M, Rossetti AO, Gosseries O, Chatelle C. European Academy of Neurology guideline on the diagnosis of coma and other disorders of consciousness. Eur J Neurol 2020; 27:741-756. [PMID: 32090418 DOI: 10.1111/ene.14151] [Citation(s) in RCA: 291] [Impact Index Per Article: 72.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2019] [Accepted: 01/09/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND AND PURPOSE Patients with acquired brain injury and acute or prolonged disorders of consciousness (DoC) are challenging. Evidence to support diagnostic decisions on coma and other DoC is limited but accumulating. This guideline provides the state-of-the-art evidence regarding the diagnosis of DoC, summarizing data from bedside examination techniques, functional neuroimaging and electroencephalography (EEG). METHODS Sixteen members of the European Academy of Neurology (EAN) Scientific Panel on Coma and Chronic Disorders of Consciousness, representing 10 European countries, reviewed the scientific evidence for the evaluation of coma and other DoC using standard bibliographic measures. Recommendations followed the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. The guideline was endorsed by the EAN. RESULTS Besides a comprehensive neurological examination, the following suggestions are made: probe for voluntary eye movements using a mirror; repeat clinical assessments in the subacute and chronic setting, using the Coma Recovery Scale - Revised; use the Full Outline of Unresponsiveness score instead of the Glasgow Coma Scale in the acute setting; obtain clinical standard EEG; search for sleep patterns on EEG, particularly rapid eye movement sleep and slow-wave sleep; and, whenever feasible, consider positron emission tomography, resting state functional magnetic resonance imaging (fMRI), active fMRI or EEG paradigms and quantitative analysis of high-density EEG to complement behavioral assessment in patients without command following at the bedside. CONCLUSIONS Standardized clinical evaluation, EEG-based techniques and functional neuroimaging should be integrated for multimodal evaluation of patients with DoC. The state of consciousness should be classified according to the highest level revealed by any of these three approaches.
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Affiliation(s)
- D Kondziella
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.,Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark.,Department of Neurosciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - A Bender
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany.,Therapiezentrum Burgau, Burgau, Germany
| | - K Diserens
- Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - W van Erp
- Coma Science Group, GIGA Consciousness, University and University Hospital of Liège, Liège, Belgium.,Department of Primary Care, Radboud University Medical Center, Nijmegen, The Netherlands
| | - A Estraneo
- Neurology Unit, Santa Maria della Pietà General Hospital, Nola, Italy.,IRCCS Fondazione don Carlo Gnocchi ONLUS, Florence, Italy
| | - R Formisano
- Post-Coma Unit, Neurorehabilitation Hospital and Research Institution, Santa Lucia Foundation, Rome, Italy
| | - S Laureys
- Coma Science Group, GIGA Consciousness, University and University Hospital of Liège, Liège, Belgium
| | - L Naccache
- Department of Neurology, AP-HP, Groupe hospitalier Pitié-Salpêtrière, Paris, France.,Sorbonne Université, UPMC Univ Paris 06, Faculté de Médecine Pitié-Salpêtrière, Paris, France
| | - S Ozturk
- Department of Neurology, Faculty of Medicine, Selcuk University, Konya, Turkey
| | - B Rohaut
- Department of Neurology, AP-HP, Groupe hospitalier Pitié-Salpêtrière, Paris, France.,Sorbonne Université, UPMC Univ Paris 06, Faculté de Médecine Pitié-Salpêtrière, Paris, France.,Neuro-ICU, Department of Neurology, Columbia University, New York, NY, USA
| | - J D Sitt
- Sorbonne Université, UPMC Univ Paris 06, Faculté de Médecine Pitié-Salpêtrière, Paris, France
| | - J Stender
- Department of Neurosurgery, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
| | - M Tiainen
- Department of Neurology, Helsinki University Hospital, Helsinki, Finland
| | - A O Rossetti
- Department of Clinical Neurosciences, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland
| | - O Gosseries
- Coma Science Group, GIGA Consciousness, University and University Hospital of Liège, Liège, Belgium
| | - C Chatelle
- Coma Science Group, GIGA Consciousness, University and University Hospital of Liège, Liège, Belgium.,Laboratory for NeuroImaging of Coma and Consciousness - Department of Neurology, Harvard Medical School, Massachusetts General Hospital, Boston, MA, USA
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35
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Das N, Vanthornhout J, Francart T, Bertrand A. Stimulus-aware spatial filtering for single-trial neural response and temporal response function estimation in high-density EEG with applications in auditory research. Neuroimage 2020; 204:116211. [PMID: 31546052 PMCID: PMC7355237 DOI: 10.1016/j.neuroimage.2019.116211] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 08/30/2019] [Accepted: 09/17/2019] [Indexed: 12/21/2022] Open
Abstract
A common problem in neural recordings is the low signal-to-noise ratio (SNR), particularly when using non-invasive techniques like magneto- or electroencephalography (M/EEG). To address this problem, experimental designs often include repeated trials, which are then averaged to improve the SNR or to infer statistics that can be used in the design of a denoising spatial filter. However, collecting enough repeated trials is often impractical and even impossible in some paradigms, while analyses on existing data sets may be hampered when these do not contain such repeated trials. Therefore, we present a data-driven method that takes advantage of the knowledge of the presented stimulus, to achieve a joint noise reduction and dimensionality reduction without the need for repeated trials. The method first estimates the stimulus-driven neural response using the given stimulus, which is then used to find a set of spatial filters that maximize the SNR based on a generalized eigenvalue decomposition. As the method is fully data-driven, the dimensionality reduction enables researchers to perform their analyses without having to rely on their knowledge of brain regions of interest, which increases accuracy and reduces the human factor in the results. In the context of neural tracking of a speech stimulus using EEG, our method resulted in more accurate short-term temporal response function (TRF) estimates, higher correlations between predicted and actual neural responses, and higher attention decoding accuracies compared to existing TRF-based decoding methods. We also provide an extensive discussion on the central role played by the generalized eigenvalue decomposition in various denoising methods in the literature, and address the conceptual similarities and differences with our proposed method.
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Affiliation(s)
- Neetha Das
- Dept. Electrical Engineering (ESAT), Stadius Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Kasteelpark Arenberg 10, B-3001, Leuven, Belgium; Dept. Neurosciences, ExpORL, KU Leuven, Herestraat 49 Bus 721, B-3000, Leuven, Belgium.
| | - Jonas Vanthornhout
- Dept. Neurosciences, ExpORL, KU Leuven, Herestraat 49 Bus 721, B-3000, Leuven, Belgium
| | - Tom Francart
- Dept. Neurosciences, ExpORL, KU Leuven, Herestraat 49 Bus 721, B-3000, Leuven, Belgium
| | - Alexander Bertrand
- Dept. Electrical Engineering (ESAT), Stadius Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Kasteelpark Arenberg 10, B-3001, Leuven, Belgium.
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36
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Edlow BL. Covert Consciousness: Searching for Volitional Brain Activity in the Unresponsive. Curr Biol 2019; 28:R1345-R1348. [PMID: 30513331 DOI: 10.1016/j.cub.2018.10.022] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Consciousness may evade detection by bedside behavioral examination. New research suggests that an electrophysiologic screening tool can identify people with severe brain injuries who are likely to be covertly conscious.
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Affiliation(s)
- Brian L Edlow
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, 175 Cambridge Street - Suite 300, Boston, MA 02114, USA.
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37
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Vanthornhout J, Decruy L, Francart T. Effect of Task and Attention on Neural Tracking of Speech. Front Neurosci 2019; 13:977. [PMID: 31607841 PMCID: PMC6756133 DOI: 10.3389/fnins.2019.00977] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 08/30/2019] [Indexed: 12/02/2022] Open
Abstract
EEG-based measures of neural tracking of natural running speech are becoming increasingly popular to investigate neural processing of speech and have applications in audiology. When the stimulus is a single speaker, it is usually assumed that the listener actively attends to and understands the stimulus. However, as the level of attention of the listener is inherently variable, we investigated how this affected neural envelope tracking. Using a movie as a distractor, we varied the level of attention while we estimated neural envelope tracking. We varied the intelligibility level by adding stationary noise. We found a significant difference in neural envelope tracking between the condition with maximal attention and the movie condition. This difference was most pronounced in the right-frontal region of the brain. The degree of neural envelope tracking was highly correlated with the stimulus signal-to-noise ratio, even in the movie condition. This could be due to residual neural resources to passively attend to the stimulus. When envelope tracking is used to measure speech understanding objectively, this means that the procedure can be made more enjoyable and feasible by letting participants watch a movie during stimulus presentation.
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Affiliation(s)
| | - Lien Decruy
- Department of Neurosciences, ExpORL, KU Leuven, Leuven, Belgium
| | - Tom Francart
- Department of Neurosciences, ExpORL, KU Leuven, Leuven, Belgium
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38
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Noel JP, Chatelle C, Perdikis S, Jöhr J, Lopes Da Silva M, Ryvlin P, De Lucia M, Millán JDR, Diserens K, Serino A. Peri-personal space encoding in patients with disorders of consciousness and cognitive-motor dissociation. NEUROIMAGE-CLINICAL 2019; 24:101940. [PMID: 31357147 PMCID: PMC6664240 DOI: 10.1016/j.nicl.2019.101940] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Revised: 07/13/2019] [Accepted: 07/17/2019] [Indexed: 01/06/2023]
Abstract
Behavioral assessments of consciousness based on overt command following cannot differentiate patients with disorders of consciousness (DOC) from those who demonstrate a dissociation between intent/awareness and motor capacity: cognitive motor dissociation (CMD). We argue that delineation of peri-personal space (PPS) – the multisensory-motor space immediately surrounding the body – may differentiate these patients due to its central role in mediating human-environment interactions, and putatively in scaffolding a minimal form of selfhood. In Experiment 1, we determined a normative physiological index of PPS by recording electrophysiological (EEG) responses to tactile, auditory, or audio-tactile stimulation at different distances (5 vs. 75 cm) in healthy volunteers (N = 19). Contrasts between paired (AT) and summed (A + T) responses demonstrated multisensory supra-additivity when AT stimuli were presented near, i.e., within the PPS, and highlighted somatosensory-motor sensors as electrodes of interest. In Experiment 2, we recorded EEG in patients behaviorally diagnosed as DOC or putative CMD (N = 17, 30 sessions). The PPS-measure developed in Experiment 1 was analyzed in relation with both standard clinical diagnosis (i.e., Coma Recovery Scale; CRS-R) and a measure of neural complexity associated with consciousness. Results demonstrated a significant correlation between the PPS measure and neural complexity, but not with the CRS-R, highlighting the added value of the physiological recordings. Further, multisensory processing in PPS was preserved in putative CMD but not in DOC patients. Together, the findings suggest that indexing PPS allows differentiating between groups of patients whom both show overt motor impairments (DOC and CMD) but putatively distinct levels of awareness or motor intent. Behavioral assessments confound consciousness and motor output. We suggest that multisensory coding of actionable space may dissociate these two. We develop an electrophysiological marker of peri-personal space. Then use this marker to distinguish impairments in consciousness and motor output.
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Affiliation(s)
- Jean-Paul Noel
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Camille Chatelle
- Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Boston, MA, USA; Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA; Coma Science Group, GIGA Consciousness, University and University Hospital of Liège, Liège, Belgium
| | - Serafeim Perdikis
- Center for Neuroprosthetics, School of Engineering, Ecole Polytechnique Federale de Lausanne (EPFL), Geneva, Switzerland; Brain-Computer Interfaces and Neural Engineering Laboratory, School of Computer Science and Electronic Engineering, University of Essex, UK
| | - Jane Jöhr
- Acute Neurorehabilitation Unit, Neurology, Department of and Clinical Neurosciences, University Hospital of Lausanne, Lausanne, Switzerland
| | - Marina Lopes Da Silva
- Acute Neurorehabilitation Unit, Neurology, Department of and Clinical Neurosciences, University Hospital of Lausanne, Lausanne, Switzerland
| | - Philippe Ryvlin
- Acute Neurorehabilitation Unit, Neurology, Department of and Clinical Neurosciences, University Hospital of Lausanne, Lausanne, Switzerland
| | - Marzia De Lucia
- Laboratoire de Recherche en Neuroimagerie, Department of Clinical Neurosciences, University Hospital of Lausanne, University of Lausanne, Lausanne, Switzerland
| | - José Del R Millán
- Center for Neuroprosthetics, School of Engineering, Ecole Polytechnique Federale de Lausanne (EPFL), Geneva, Switzerland
| | - Karin Diserens
- Acute Neurorehabilitation Unit, Neurology, Department of and Clinical Neurosciences, University Hospital of Lausanne, Lausanne, Switzerland.
| | - Andrea Serino
- MySpace Lab, Department of Clinical Neurosciences, University Hospital of Lausanne, University of Lausanne, Lausanne, Switzerland.
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