Resting-State NIRS–EEG in Unresponsive Patients with Acute Brain Injury: A Proof-of-Concept Study

Othman, Marwan H.; Bhattacharya, Malay; Møller, Kirsten; Kjeldsen, Søren; Grand, Johannes; Kjærgaard, Jesper; Dutta, Anirban; Kondziella, Daniel

doi:10.1007/s12028-020-00971-x

Cited by 34 publications

(40 citation statements)

References 85 publications

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“…Multimodal EEG–fNIRS is highly advantageous in that it allows for the concurrent assessment of electric and hemodynamic brain activity. EEG–fNIRS has been increasingly applied in multiple sectors, such as BCI [ 10 , 11 , 12 , 13 , 14 ], clinical neurology [ 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 ], and neurorehabilitation [ 70 , 71 ]. In the evolution of this field, the development of wearable, integrated EEG–fNIRS technology is a critical next step.…”

Section: Discussionmentioning

confidence: 99%

“…Studies of brain-computer interfaces (BCI) frequently employ combined EEG-fNIRS systems to increase the amount of available information from the brain and improve classification accuracy [5,[10][11][12][13][14]. Clinically, EEG-fNIRS has demonstrated applicability to patients with stroke [15][16][17], Parkinson's disease [18], and epilepsy [19,20], among other conditions [21,22]. EEG-fNIRS systems are of particular interest in neonatal brain research since both methods are minimally invasive, silent, and can be employed cot-side [23].…”

Section: Introductionmentioning

confidence: 99%

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Wearable, Integrated EEG–fNIRS Technologies: A Review

Uchitel

Vidal-Rosas

Cooper

et al. 2021

Sensors

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There has been considerable interest in applying electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) simultaneously for multimodal assessment of brain function. EEG–fNIRS can provide a comprehensive picture of brain electrical and hemodynamic function and has been applied across various fields of brain science. The development of wearable, mechanically and electrically integrated EEG–fNIRS technology is a critical next step in the evolution of this field. A suitable system design could significantly increase the data/image quality, the wearability, patient/subject comfort, and capability for long-term monitoring. Here, we present a concise, yet comprehensive, review of the progress that has been made toward achieving a wearable, integrated EEG–fNIRS system. Significant marks of progress include the development of both discrete component-based and microchip-based EEG–fNIRS technologies; modular systems; miniaturized, lightweight form factors; wireless capabilities; and shared analogue-to-digital converter (ADC) architecture between fNIRS and EEG data acquisitions. In describing the attributes, advantages, and disadvantages of current technologies, this review aims to provide a roadmap toward the next generation of wearable, integrated EEG–fNIRS systems.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Wearable, Integrated EEG–fNIRS Technologies: A Review

Uchitel

Vidal-Rosas

Cooper

et al. 2021

Sensors

View full text Add to dashboard Cite

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“…Notably, while they did combine EEG and fNIRS features in a multivariate data-driven analysis, they did not evaluate cross-modality metrics related to NC. In fact, although EEG-fNIRS systems have been employed to extract cross-modality metrics of NC in different clinical populations, such as stroke patients [53], neonates [54], patients with acute brain injury [55] and in the assessment of physiological aging [56], to our knowledge, such multimodal methodology was not applied for the evaluation of NC and its modification in AD.…”

Section: Introductionmentioning

confidence: 99%

Evidence of Neurovascular Un-Coupling in Mild Alzheimer’s Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data

et al. 2021

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Alzheimer’s disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed in clinical settings through multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest in an ambulatory setting to assess NC and to evaluate the sensitivity and specificity of the methodology to AD. Global NC was evaluated with a general linear model (GLM) framework by regressing whole-head EEG power envelopes in three frequency bands (theta, alpha and beta) with average fNIRS oxy- and deoxy-hemoglobin concentration changes in the frontal and prefrontal cortices. NC was lower in AD compared to healthy controls (HC) with significant differences in the linkage of theta and alpha bands with oxy- and deoxy-hemoglobin, respectively (p = 0.028 and p = 0.020). Importantly, standalone EEG and fNIRS metrics did not highlight differences between AD and HC. Furthermore, a multivariate data-driven analysis of NC between the three frequency bands and the two hemoglobin species delivered a cross-validated classification performance of AD and HC with an Area Under the Curve, AUC = 0.905 (p = 2.17 × 10−5). The findings demonstrate that EEG-fNIRS may indeed represent a powerful ecological tool for clinical evaluation of NC and early identification of AD.

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“…This method is a non-invasive optical technique that maps local changes in neural blood oxygenation in response to stimuli and at rest. Near infrared spectroscopy is a feasible tool for detecting neural activity following acute brain injury ( 23 ) and has been used as a communication modality with non-responsive patients in the ICU ( 24 ).…”

Section: Introductionmentioning

confidence: 99%

Improving Diagnosis and Prognosis in Acute Severe Brain Injury: A Multimodal Imaging Protocol

et al. 2021

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Multi-modal neuroimaging techniques have the potential to dramatically improve the diagnosis of the level consciousness and prognostication of neurological outcome for patients with severe brain injury in the intensive care unit (ICU). This protocol describes a study that will utilize functional Magnetic Resonance Imaging (fMRI), electroencephalography (EEG), and functional Near Infrared Spectroscopy (fNIRS) to measure and map the brain activity of acute critically ill patients. Our goal is to investigate whether these modalities can provide objective and quantifiable indicators of good neurological outcome and reliably detect conscious awareness. To this end, we will conduct a prospective longitudinal cohort study to validate the prognostic and diagnostic utility of neuroimaging techniques in the ICU. We will recruit 350 individuals from two ICUs over the course of 7 years. Participants will undergo fMRI, EEG, and fNIRS testing several times over the first 10 days of care to assess for residual cognitive function and evidence of covert awareness. Patients who regain behavioral awareness will be asked to complete web-based neurocognitive tests for 1 year, as well as return for follow up neuroimaging to determine which acute imaging features are most predictive of cognitive and functional recovery. Ultimately, multi-modal neuroimaging techniques may improve the clinical assessments of patients' level of consciousness, aid in the prediction of outcome, and facilitate efforts to find interventional methods that improve recovery and quality of life.

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Resting-State NIRS–EEG in Unresponsive Patients with Acute Brain Injury: A Proof-of-Concept Study

Cited by 34 publications

References 85 publications

Wearable, Integrated EEG–fNIRS Technologies: A Review

Wearable, Integrated EEG–fNIRS Technologies: A Review

Evidence of Neurovascular Un-Coupling in Mild Alzheimer’s Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data

Improving Diagnosis and Prognosis in Acute Severe Brain Injury: A Multimodal Imaging Protocol

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