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Evaluation of fNIRS signal components elicited by cognitive and hypercapnic stimuli. Sci Rep 2021; 11:23457. [PMID: 34873185 PMCID: PMC8648757 DOI: 10.1038/s41598-021-02076-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 10/18/2021] [Indexed: 11/08/2022] Open
Abstract
Functional near infrared spectroscopy (fNIRS) measurements are confounded by signal components originating from multiple physiological causes, whose activities may vary temporally and spatially (across tissue layers, and regions of the cortex). Furthermore, the stimuli can induce evoked effects, which may lead to over or underestimation of the actual effect of interest. Here, we conducted a temporal, spectral, and spatial analysis of fNIRS signals collected during cognitive and hypercapnic stimuli to characterize effects of functional versus systemic responses. We utilized wavelet analysis to discriminate physiological causes and employed long and short source-detector separation (SDS) channels to differentiate tissue layers. Multi-channel measures were analyzed further to distinguish hemispheric differences. The results highlight cardiac, respiratory, myogenic, and very low frequency (VLF) activities within fNIRS signals. Regardless of stimuli, activity within the VLF band had the largest contribution to the overall signal. The systemic activities dominated the measurements from the short SDS channels during cognitive stimulus, but not hypercapnic stimulus. Importantly, results indicate that characteristics of fNIRS signals vary with type of the stimuli administered as cognitive stimulus elicited variable responses between hemispheres in VLF band and task-evoked temporal effect in VLF, myogenic and respiratory bands, while hypercapnic stimulus induced a global response across both hemispheres.
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2
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Wyser D, Mattille M, Wolf M, Lambercy O, Scholkmann F, Gassert R. Short-channel regression in functional near-infrared spectroscopy is more effective when considering heterogeneous scalp hemodynamics. NEUROPHOTONICS 2020; 7:035011. [PMID: 33029548 PMCID: PMC7523733 DOI: 10.1117/1.nph.7.3.035011] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 09/04/2020] [Indexed: 05/20/2023]
Abstract
Significance: The reliability of functional near-infrared spectroscopy (fNIRS) measurements is reduced by systemic physiology. Short-channel regression algorithms aim at removing systemic "noise" by subtracting the signal measured at a short source-detector separation (mainly scalp hemodynamics) from the one of a long separation (brain and scalp hemodynamics). In literature, incongruent approaches on the selection of the optimal regressor signal are reported based on different assumptions on scalp hemodynamics properties. Aim: We investigated the spatial and temporal distribution of scalp hemodynamics over the sensorimotor cortex and evaluated its influence on the effectiveness of short-channel regressions. Approach: We performed hand-grasping and resting-state experiments with five subjects, measuring with 16 optodes over sensorimotor areas, including eight 8-mm channels. We performed detailed correlation analyses of scalp hemodynamics and evaluated 180 hand-grasping and 270 simulated (overlaid on resting-state measurements) trials. Five short-channel regressor combinations were implemented with general linear models. Three were chosen according to literature, and two were proposed based on additional physiological assumptions [considering multiple short channels and their Mayer wave (MW) oscillations]. Results: We found heterogeneous hemodynamics in the scalp, coming on top of a global close-to-homogeneous behavior (correlation 0.69 to 0.92). The results further demonstrate that short-channel regression always improves brain activity estimates but that better results are obtained when heterogeneity is assumed. In particular, we highlight that short-channel regression is more effective when combining multiple scalp regressors and when MWs are additionally included. Conclusion: We shed light on the selection of optimal regressor signals for improving the removal of systemic physiological artifacts in fNIRS. We conclude that short-channel regression is most effective when assuming heterogeneous hemodynamics, in particular when combining spatial- and frequency-specific information. A better understanding of scalp hemodynamics and more effective short-channel regression will promote more accurate assessments of functional brain activity in clinical and research settings.
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Affiliation(s)
- Dominik Wyser
- ETH Zurich, Department of Health Sciences and Technology, Rehabilitation Engineering Laboratory, Zurich, Switzerland
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
- Address all correspondence to Dominik Wyser, E-mail:
| | - Michelle Mattille
- ETH Zurich, Department of Health Sciences and Technology, Rehabilitation Engineering Laboratory, Zurich, Switzerland
| | - Martin Wolf
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
| | - Olivier Lambercy
- ETH Zurich, Department of Health Sciences and Technology, Rehabilitation Engineering Laboratory, Zurich, Switzerland
| | - Felix Scholkmann
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Roger Gassert
- ETH Zurich, Department of Health Sciences and Technology, Rehabilitation Engineering Laboratory, Zurich, Switzerland
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3
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Izzetoglu M, Holtzer R. Effects of Processing Methods on fNIRS Signals Assessed During Active Walking Tasks in Older Adults. IEEE Trans Neural Syst Rehabil Eng 2020; 28:699-709. [PMID: 32070987 DOI: 10.1109/tnsre.2020.2970407] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Functional near infrared spectroscopy (fNIRS) is a noninvasive optics-based neuroimaging modality successfully applied to real-life settings. The technology uses light in the near infrared range (650-950nm) to track changes in oxygenated (HbO2) and deoxygenated hemoglobin (Hb) obtained from measured light intensity using light-tissue interaction principles. fNIRS data processing involves artifact removal and hemodynamic signal conversion using modified Beer-Lambert law (MBLL) to obtain Hb and HbO2, reliably. fNIRS signals can get contaminated by various noise sources of physiological and non-physiological origins. Various algorithms have been proposed for the elimination of artifacts from frequency selective filters to blind source separation methods. Hemodynamic signal extraction using raw intensity measurements at multiple wavelengths based on MBLL usually involves apriori knowledge of certain conversion parameters such as molar extinction coefficients ( ε ) and differential path length factor (DPF). Different sets of conversion parameters dependent upon wavelength, chromophores, and age have been reported. Variation in processing algorithms and parameters can cause differences in Hb and HbO2 extraction which can in turn change study outcomes. Using fNIRS, we have previously shown significant increases in oxygenation in the prefrontal cortex from Single-Task-Walking (STW) to Dual-task-Walking (DTW) conditions in older adults due to greater cognitive demands inherent in the latter condition. In the current study, we re-analyzed our data and determined that although using different conversion parameters i.e. ε and age dependent DPF and filter cut-off frequencies at 0.14 and 0.08Hz including those designed to remove confounding effects of Mayer waves had caused some linear increases or decreases on the extracted Hb and HbO2 signals, those effects were minimal in task related comparisons and hence, the overall study outcomes.
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4
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Dong S, Jeong J. Improvement in Recovery of Hemodynamic Responses by Extended Kalman Filter With Non-Linear State-Space Model and Short Separation Measurement. IEEE Trans Biomed Eng 2019; 66:2152-2162. [DOI: 10.1109/tbme.2018.2884169] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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5
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Rupawala M, Dehghani H, Lucas SJE, Tino P, Cruse D. Shining a Light on Awareness: A Review of Functional Near-Infrared Spectroscopy for Prolonged Disorders of Consciousness. Front Neurol 2018; 9:350. [PMID: 29872420 PMCID: PMC5972220 DOI: 10.3389/fneur.2018.00350] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 04/30/2018] [Indexed: 12/19/2022] Open
Abstract
Qualitative clinical assessments of the recovery of awareness after severe brain injury require an assessor to differentiate purposeful behavior from spontaneous behavior. As many such behaviors are minimal and inconsistent, behavioral assessments are susceptible to diagnostic errors. Advanced neuroimaging tools can bypass behavioral responsiveness and reveal evidence of covert awareness and cognition within the brains of some patients, thus providing a means for more accurate diagnoses, more accurate prognoses, and, in some instances, facilitated communication. The majority of reports to date have employed the neuroimaging methods of functional magnetic resonance imaging, positron emission tomography, and electroencephalography (EEG). However, each neuroimaging method has its own advantages and disadvantages (e.g., signal resolution, accessibility, etc.). Here, we describe a burgeoning technique of non-invasive optical neuroimaging—functional near-infrared spectroscopy (fNIRS)—and review its potential to address the clinical challenges of prolonged disorders of consciousness. We also outline the potential for simultaneous EEG to complement the fNIRS signal and suggest the future directions of research that are required in order to realize its clinical potential.
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Affiliation(s)
- Mohammed Rupawala
- Centre for Doctoral Training in Physical Sciences for Health, University of Birmingham, Birmingham, United Kingdom
| | - Hamid Dehghani
- Centre for Doctoral Training in Physical Sciences for Health, University of Birmingham, Birmingham, United Kingdom.,School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Samuel J E Lucas
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Peter Tino
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Damian Cruse
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
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6
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Beausoleil TP, Janaillac M, Barrington KJ, Lapointe A, Dehaes M. Cerebral oxygen saturation and peripheral perfusion in the extremely premature infant with intraventricular and/or pulmonary haemorrhage early in life. Sci Rep 2018; 8:6511. [PMID: 29695729 PMCID: PMC5916916 DOI: 10.1038/s41598-018-24836-8] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Accepted: 04/09/2018] [Indexed: 12/29/2022] Open
Abstract
Extremely preterm infants are at higher risk of pulmonary (PH) and intraventricular (IVH) haemorrhage during the transitioning physiology due to immature cardiovascular system. Monitoring of haemodynamics can detect early abnormal circulation that may lead to these complications. We described time-frequency relationships between near infrared spectroscopy (NIRS) cerebral regional haemoglobin oxygen saturation (CrSO2) and preductal peripheral perfusion index (PI), capillary oxygen saturation (SpO2) and heart rate (HR) in extremely preterm infants in the first 72 h of life. Patients were sub-grouped in infants with PH and/or IVH (N H = 8) and healthy controls (N C = 11). Data were decomposed in wavelets allowing the analysis of localized variations of power. This approach allowed to quantify the percentage of time of significant cross-correlation, semblance, gain (transfer function) and coherence between signals. Ultra-low frequencies (<0.28 mHz) were analyzed as slow and prolonged periods of impaired circulation are considered more detrimental than transient fluctuations. Cross-correlation between CrSO2 and oximetry (PI, SpO2 and HR) as well as in-phase semblance and gain between CrSO2 and HR were significantly lower while anti-phase semblance between CrSO2 and HR was significantly higher in PH-IVH infants compared to controls. These differences may reflect haemodynamic instability associated with cerebrovascular autoregulation and hemorrhagic complications observed during the transitioning physiology.
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Affiliation(s)
- Thierry P Beausoleil
- Institute of Biomedical Engineering, University of Montréal, Montréal, Canada.,Research Centre, CHU Sainte-Justine, Montréal, Canada
| | - Marie Janaillac
- Department of Pediatrics, Division of Neonatology, CHU Sainte-Justine and University of Montréal, Montréal, Canada
| | - Keith J Barrington
- Research Centre, CHU Sainte-Justine, Montréal, Canada.,Department of Pediatrics, Division of Neonatology, CHU Sainte-Justine and University of Montréal, Montréal, Canada
| | - Anie Lapointe
- Department of Pediatrics, Division of Neonatology, CHU Sainte-Justine and University of Montréal, Montréal, Canada
| | - Mathieu Dehaes
- Research Centre, CHU Sainte-Justine, Montréal, Canada. .,Department of Radiology, Radio-oncology and Nuclear Medicine, University of Montréal, Montréal, Canada.
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7
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Yücel MA, Selb J, Aasted CM, Lin PY, Borsook D, Becerra L, Boas DA. Mayer waves reduce the accuracy of estimated hemodynamic response functions in functional near-infrared spectroscopy. BIOMEDICAL OPTICS EXPRESS 2016; 7:3078-88. [PMID: 27570699 PMCID: PMC4986815 DOI: 10.1364/boe.7.003078] [Citation(s) in RCA: 98] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2016] [Revised: 06/30/2016] [Accepted: 07/05/2016] [Indexed: 05/07/2023]
Abstract
Analysis of cerebral hemodynamics reveals a wide spectrum of oscillations ranging from 0.0095 to 2 Hz. While most of these oscillations can be filtered out during analysis of functional near-infrared spectroscopy (fNIRS) signals when estimating stimulus evoked hemodynamic responses, oscillations around 0.1 Hz are an exception. This is due to the fact that they share a common spectral range with typical stimulus evoked hemodynamic responses from the brain. Here we investigate the effect of hemodynamic oscillations around 0.1 Hz on the estimation of hemodynamic response functions from fNIRS data. Our results show that for an expected response of ~1 µM in oxygenated hemoglobin concentration (HbO), Mayer wave oscillations with an amplitude > ~1 µM at 0.1 Hz reduce the accuracy of the estimated response as quantified by a 3 fold increase in the mean squared error and decrease in correlation (R(2) below 0.78) when compared to the true HRF. These results indicate that the amplitude of oscillations at 0.1 Hz can serve as an objective metric of the expected HRF estimation accuracy. In addition, we investigated the effect of short separation regression on the recovered HRF, and found that this improves the recovered HRF when large amplitude 0.1 Hz oscillations are present in fNIRS data. We suspect that the development of other filtering strategies may provide even further improvement.
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Affiliation(s)
- Meryem A. Yücel
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - Juliette Selb
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - Christopher M. Aasted
- Center for Pain and the Brain, Departments of Anaesthesia and Radiology, Boston Children’s Hospital, Boston, MA, USA
| | - Pei-Yi Lin
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
| | - David Borsook
- Center for Pain and the Brain, Departments of Anaesthesia and Radiology, Boston Children’s Hospital, Boston, MA, USA
| | - Lino Becerra
- Center for Pain and the Brain, Departments of Anaesthesia and Radiology, Boston Children’s Hospital, Boston, MA, USA
| | - David A. Boas
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital (MGH), Harvard Medical School, Charlestown, MA, USA
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8
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Yücel MA, Selb J, Aasted CM, Petkov MP, Becerra L, Borsook D, Boas DA. Short separation regression improves statistical significance and better localizes the hemodynamic response obtained by near-infrared spectroscopy for tasks with differing autonomic responses. NEUROPHOTONICS 2015; 2:035005. [PMID: 26835480 PMCID: PMC4717232 DOI: 10.1117/1.nph.2.3.035005] [Citation(s) in RCA: 81] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Accepted: 08/10/2015] [Indexed: 05/07/2023]
Abstract
Autonomic nervous system response is known to be highly task-dependent. The sensitivity of near-infrared spectroscopy (NIRS) measurements to superficial layers, particularly to the scalp, makes it highly susceptible to systemic physiological changes. Thus, one critical step in NIRS data processing is to remove the contribution of superficial layers to the NIRS signal and to obtain the actual brain response. This can be achieved using short separation channels that are sensitive only to the hemodynamics in the scalp. We investigated the contribution of hemodynamic fluctuations due to autonomous nervous system activation during various tasks. Our results provide clear demonstrations of the critical role of using short separation channels in NIRS measurements to disentangle differing autonomic responses from the brain activation signal of interest.
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Affiliation(s)
- Meryem A. Yücel
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, 149 13th Street, Charlestown, Massachusetts 02129, United States
- Address all correspondence to: Meryem A. Yücel, E-mail:
| | - Juliette Selb
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, 149 13th Street, Charlestown, Massachusetts 02129, United States
| | - Christopher M. Aasted
- Boston Children’s Hospital, Center for Pain and the Brain, Departments of Anaesthesia and Radiology, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Mike P. Petkov
- Boston Children’s Hospital, Center for Pain and the Brain, Departments of Anaesthesia and Radiology, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - Lino Becerra
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, 149 13th Street, Charlestown, Massachusetts 02129, United States
- Boston Children’s Hospital, Center for Pain and the Brain, Departments of Anaesthesia and Radiology, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
- Harvard Medical School, Department of Anesthesiology, Perioperative, and Pain Medicine, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - David Borsook
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, 149 13th Street, Charlestown, Massachusetts 02129, United States
- Boston Children’s Hospital, Center for Pain and the Brain, Departments of Anaesthesia and Radiology, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
- Harvard Medical School, Department of Anesthesiology, Perioperative, and Pain Medicine, 300 Longwood Avenue, Boston, Massachusetts 02115, United States
| | - David A. Boas
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, 149 13th Street, Charlestown, Massachusetts 02129, United States
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9
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Analysis of task-evoked systemic interference in fNIRS measurements: Insights from fMRI. Neuroimage 2014; 87:490-504. [DOI: 10.1016/j.neuroimage.2013.10.024] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2013] [Revised: 10/09/2013] [Accepted: 10/12/2013] [Indexed: 11/21/2022] Open
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10
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Scholkmann F, Kleiser S, Metz AJ, Zimmermann R, Mata Pavia J, Wolf U, Wolf M. A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. Neuroimage 2014; 85 Pt 1:6-27. [PMID: 23684868 DOI: 10.1016/j.neuroimage.2013.05.004] [Citation(s) in RCA: 986] [Impact Index Per Article: 98.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2013] [Revised: 04/12/2013] [Accepted: 05/03/2013] [Indexed: 01/09/2023] Open
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11
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Hemmati Berivanlou N, Setarehdan SK, Ahmadi Noubari H. Evoked hemodynamic response estimation using ensemble empirical mode decomposition based adaptive algorithm applied to dual channel functional near infrared spectroscopy (fNIRS). J Neurosci Methods 2013; 224:13-25. [PMID: 24365048 DOI: 10.1016/j.jneumeth.2013.12.007] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2013] [Revised: 12/09/2013] [Accepted: 12/12/2013] [Indexed: 11/19/2022]
Abstract
BACKGROUND The quality of the functional near infrared spectroscopy (fNIRS) recordings is highly degraded by the presence of physiological interferences. It is crucial to efficiently separate the evoked hemodynamic responses (EHRs) from other background hemodynamic activities prior to any further processing. NEW METHOD This paper presents a novel algorithm for physiological interferences reduction from the dual channel fNIRS measurements using ensemble empirical mode decomposition (EEMD) technique. The proposed algorithm is comprised of two main steps: (1) decomposing reference signal into its constituents called intrinsic mode functions (IMFs) and (2) adaptively defining appropriate weights of the corresponding IMFs to estimate the proportion of physiological interference in standard channel measurement. RESULTS Performance of the proposed algorithm was evaluated using both synthetic and semi-real brain hemodynamic data based on four parameters of relative mean squared error (rMSE), Pearson's correlation coefficient (R(2)), percentage estimation error of peak amplitude (EPA) and peak latency (EL). COMPARISON WITH EXISTING METHODS Results obtained from synthetic data revealed that both the EEMD based normalized least mean squares (EEMD-NLMS) and EEMD based recursive least squares (EEMD-RLS) methods could reduce the average rMSE by at least 34% and 49%, respectively, when compared with widely used methods: block averaging, band-pass filtering and principal and/or independent component analysis. Furthermore, the two proposed methods outperform the regression method in reducing rMSE by at least 21% and 35% respectively when applied to semi-real data. CONCLUSIONS An effective algorithm for estimating the EHRs from raw fNIRS data was proposed in which no assumption about the amplitude, shape and duration of the responses is considered.
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Affiliation(s)
- Nima Hemmati Berivanlou
- Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Seyed Kamaledin Setarehdan
- Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
| | - Hossein Ahmadi Noubari
- Control and Intelligent Processing Center of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran; Electrical and Computer Engineering Department, University of British Columbia, Vancouver, Canada
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12
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Gagnon L, Cooper RJ, Yücel MA, Perdue KL, Greve DN, Boas DA. Short separation channel location impacts the performance of short channel regression in NIRS. Neuroimage 2012; 59:2518-28. [PMID: 21945793 PMCID: PMC3254723 DOI: 10.1016/j.neuroimage.2011.08.095] [Citation(s) in RCA: 208] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2011] [Revised: 08/19/2011] [Accepted: 08/30/2011] [Indexed: 11/16/2022] Open
Abstract
Near-Infrared Spectroscopy (NIRS) allows the recovery of cortical oxy- and deoxyhemoglobin changes associated with evoked brain activity. NIRS is a back-reflection measurement making it very sensitive to the superficial layers of the head, i.e. the skin and the skull, where systemic interference occurs. As a result, the NIRS signal is strongly contaminated with systemic interference of superficial origin. A recent approach to overcome this problem has been the use of additional short source-detector separation optodes as regressors. Since these additional measurements are mainly sensitive to superficial layers in adult humans, they can be used to remove the systemic interference present in longer separation measurements, improving the recovery of the cortical hemodynamic response function (HRF). One question that remains to answer is whether or not a short separation measurement is required in close proximity to each long separation NIRS channel. Here, we show that the systemic interference occurring in the superficial layers of the human head is inhomogeneous across the surface of the scalp. As a result, the improvement obtained by using a short separation optode decreases as the relative distance between the short and the long measurement is increased. NIRS data was acquired on 6 human subjects both at rest and during a motor task consisting of finger tapping. The effect of distance between the short and the long channel was first quantified by recovering a synthetic hemodynamic response added over the resting-state data. The effect was also observed in the functional data collected during the finger tapping task. Together, these results suggest that the short separation measurement must be located as close as 1.5 cm from the standard NIRS channel in order to provide an improvement which is of practical use. In this case, the improvement in Contrast-to-Noise Ratio (CNR) compared to a standard General Linear Model (GLM) procedure without using any small separation optode reached 50% for HbO and 100% for HbR. Using small separations located farther than 2 cm away resulted in mild or negligible improvements only.
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Affiliation(s)
- Louis Gagnon
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
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13
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Cooper RJ, Gagnon L, Goldenholz DM, Boas DA, Greve DN. The utility of near-infrared spectroscopy in the regression of low-frequency physiological noise from functional magnetic resonance imaging data. Neuroimage 2011; 59:3128-38. [PMID: 22119653 DOI: 10.1016/j.neuroimage.2011.11.028] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2011] [Revised: 10/06/2011] [Accepted: 11/09/2011] [Indexed: 10/15/2022] Open
Abstract
Near-infrared spectroscopy (NIRS) signals have been shown to correlate with resting-state BOLD-fMRI data across the whole brain volume, particularly at frequencies below 0.1Hz. While the physiological origins of this correlation remain unclear, its existence may have a practical application in minimizing the background physiological noise present in BOLD-fMRI recordings. We performed simultaneous, resting-state fMRI and 28-channel NIRS in seven adult subjects in order to assess the utility of NIRS signals in the regression of physiological noise from fMRI data. We calculated the variance of the residual error in a general linear model of the baseline fMRI signal, and the reduction of this variance achieved by including NIRS signals in the model. In addition, we introduced a sequence of simulated hemodynamic response functions (HRFs) into the resting-state fMRI data of each subject in order to quantify the effectiveness of NIRS signals in optimizing the recovery of that HRF. For comparison, these calculations were also performed using a pulse and respiration RETROICOR model. Our results show that the use of 10 or more NIRS channels can reduce variance in the residual error by as much as 36% on average across the whole cortex. However the same number of low-pass filtered white noise regressors is shown to produce a reduction of 19%. The RETROICOR model obtained a variance reduction of 6.4%. Our HRF simulation showed that the mean-squared error (MSE) between the recovered and true HRFs is reduced by 21% on average when 10 NIRS channels are applied and by introducing an optimized time lag between the NIRS and fMRI time series, a single NIRS channel can provide an average MSE reduction of 14%. The RETROICOR model did not provide a significant change in MSE. By each of the metrics calculated, NIRS recording is shown to be of significant benefit to the regression of low-frequency physiological noise from fMRI data.
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Affiliation(s)
- R J Cooper
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
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14
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Gagnon L, Perdue K, Greve DN, Goldenholz D, Kaskhedikar G, Boas DA. Improved recovery of the hemodynamic response in diffuse optical imaging using short optode separations and state-space modeling. Neuroimage 2011; 56:1362-71. [PMID: 21385616 DOI: 10.1016/j.neuroimage.2011.03.001] [Citation(s) in RCA: 179] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2010] [Revised: 02/19/2011] [Accepted: 03/01/2011] [Indexed: 11/28/2022] Open
Abstract
Diffuse optical imaging (DOI) allows the recovery of the hemodynamic response associated with evoked brain activity. The signal is contaminated with systemic physiological interference which occurs in the superficial layers of the head as well as in the brain tissue. The back-reflection geometry of the measurement makes the DOI signal strongly contaminated by systemic interference occurring in the superficial layers. A recent development has been the use of signals from small source-detector separation (1cm) optodes as regressors. Since those additional measurements are mainly sensitive to superficial layers in adult humans, they help in removing the systemic interference present in longer separation measurements (3 cm). Encouraged by those findings, we developed a dynamic estimation procedure to remove global interference using small optode separations and to estimate simultaneously the hemodynamic response. The algorithm was tested by recovering a simulated synthetic hemodynamic response added over baseline DOI data acquired from 6 human subjects at rest. The performance of the algorithm was quantified by the Pearson R(2) coefficient and the mean square error (MSE) between the recovered and the simulated hemodynamic responses. Our dynamic estimator was also compared with a static estimator and the traditional adaptive filtering method. We observed a significant improvement (two-tailed paired t-test, p<0.05) in both HbO and HbR recovery using our Kalman filter dynamic estimator compared to the traditional adaptive filter, the static estimator and the standard GLM technique.
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Affiliation(s)
- Louis Gagnon
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
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Dehaes M, Gagnon L, Lesage F, Pélégrini-Issac M, Vignaud A, Valabrègue R, Grebe R, Wallois F, Benali H. Quantitative investigation of the effect of the extra-cerebral vasculature in diffuse optical imaging: a simulation study. BIOMEDICAL OPTICS EXPRESS 2011; 2:680-95. [PMID: 21412472 PMCID: PMC3047372 DOI: 10.1364/boe.2.000680] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2010] [Revised: 02/10/2011] [Accepted: 02/10/2011] [Indexed: 05/25/2023]
Abstract
Diffuse optical imaging (DOI) is a non invasive technique allowing the recovery of hemodynamic changes in the brain. Due to the diffusive nature of photon propagation in turbid media and the fact that cerebral tissues are located around 1.5 cm under the adult human scalp, DOI measurements are subject to partial volume errors. DOI measurements are also sensitive to large pial vessels because oxygenated and deoxygenated hemoglobin are the dominant chromophores in the near infrared window. In this study, the effect of the extra-cerebral vasculature in proximity of the sagittal sinus was investigated for its impact on DOI measurements simulated over the human adult visual cortex. Numerical Monte Carlo simulations were performed on two specific models of the human head derived from magnetic resonance imaging (MRI) scans. The first model included the extra-cerebral vasculature in which constant hemoglobin concentrations were assumed while the second did not. The screening effect of the vasculature was quantified by comparing recovered hemoglobin changes from each model for different optical arrays and regions of activation. A correction factor accounting for the difference between the recovered and the simulated hemoglobin changes was computed in each case. The results show that changes in hemoglobin concentration are better estimated when the extra-cerebral vasculature is modeled and the correction factors obtained in this case were at least 1.4-fold lower. The effect of the vasculature was also examined in a high-density diffuse optical tomography configuration. In this case, the difference between changes in hemoglobin concentration recovered with each model was reduced down to 10%.
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Affiliation(s)
- Mathieu Dehaes
- Inserm, UPMC Univ Paris 06, UMR-S 678, LIF & LINeM, Paris, France
- Université de Picardie Jules Verne, GRAMFC, EA 4293, Amiens, France
- Present address: Division of Newborn Medicine, Department of Medicine, Children's Hospital Boston and Harvard Medical School, 300 Longwood Avenue, Boston, Massachusetts 02115, phone: +1-857-218-5142, fax: +1-617-730-4671, USA
| | - Louis Gagnon
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts 02129, USA
- Harvard-MIT Division of Health Sciences and Technology, Cambridge, Massachusetts USA
| | - Frédéric Lesage
- École Polytechnique de Montréal, Département de génie électrique, Montréal, Canada
| | | | | | | | - Reinhard Grebe
- Université de Picardie Jules Verne, GRAMFC, EA 4293, Amiens, France
| | - Fabrice Wallois
- Université de Picardie Jules Verne, GRAMFC, EA 4293, Amiens, France
| | - Habib Benali
- Inserm, UPMC Univ Paris 06, UMR-S 678, LIF & LINeM, Paris, France
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Matteau-Pelletier C, Dehaes M, Lesage F, Lina JM. 1/f noise in diffuse optical imaging and wavelet-based response estimation. IEEE TRANSACTIONS ON MEDICAL IMAGING 2009; 28:415-22. [PMID: 19244013 DOI: 10.1109/tmi.2008.2006524] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
In diffuse optical imaging (DOI) data analysis, the functional response is contaminated with physiological noise as in functional magnetic resonance imaging (fMRI). In this work we extend a previously proposed method for fMRI to estimate the parameters of a linear model of DOI time series. The regression is performed in the wavelet domain to infer drift coefficients at different scales and to estimate the strength of the hemodynamic response function (HRF). This multiresolution approach benefits from the whitening property of the discrete wavelet transform (DWT), which approximately decorrelates long-memory noise processes. We also show that a more accurate estimation is obtained by removing some regressors correlating with the protocol. Moreover, we observe that this improvement is related to a quantitative measure of 1/f noise. The performances of the method are first evaluated against a standard spline-cosine drift approach with simulated HRF and real background physiology. Lastly, the technique is applied to experimental event-related data acquired by near-infrared spectroscopy (NIRS).
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Affiliation(s)
- Carl Matteau-Pelletier
- Département de Génie Electrique and Institut de Génie Biomédical, Ecole Polytechnique de Montréal, Montréal, QC, H3C 3A7 Canada.
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