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Pang R, Sang H, Yi L, Gao C, Xu H, Wei Y, Zhang L, Sun J. Working memory load recognition with deep learning time series classification. BIOMEDICAL OPTICS EXPRESS 2024; 15:2780-2797. [PMID: 38855665 PMCID: PMC11161351 DOI: 10.1364/boe.516063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 01/19/2024] [Accepted: 01/31/2024] [Indexed: 06/11/2024]
Abstract
Working memory load (WML) is one of the widely applied signals in the areas of human-machine interaction. The precise evaluation of the WML is crucial for this kind of application. This study aims to propose a deep learning (DL) time series classification (TSC) model for inter-subject WML decoding. We used fNIRS to record the hemodynamic signals of 27 participants during visual working memory tasks. Traditional machine learning and deep time series classification algorithms were respectively used for intra-subject and inter-subject WML decoding from the collected blood oxygen signals. The intra-subject classification accuracy of LDA and SVM were 94.6% and 79.1%. Our proposed TAResnet-BiLSTM model had the highest inter-subject WML decoding accuracy, reaching 92.4%. This study provides a new idea and method for the brain-computer interface application of fNIRS in real-time WML detection.
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Affiliation(s)
- Richong Pang
- Barco Technology Limited, Zhuhai 519031, China
- Joint Laboratory of Brain-Verse Digital Convergence, Guangdong Institute of Intelligence Science and Technology, Zhuhai 519031, China
| | - Haojun Sang
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Li Yi
- School of Mechatronic Engineering and Automation, Foshan University, Foshan 528000, China
| | - Chenyang Gao
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences and Peking Union Medical College, Tianjin 300110, China
| | - Hongkai Xu
- Barco Technology Limited, Zhuhai 519031, China
- Joint Laboratory of Brain-Verse Digital Convergence, Guangdong Institute of Intelligence Science and Technology, Zhuhai 519031, China
| | - Yanzhao Wei
- Barco Technology Limited, Zhuhai 519031, China
- Joint Laboratory of Brain-Verse Digital Convergence, Guangdong Institute of Intelligence Science and Technology, Zhuhai 519031, China
| | - Lei Zhang
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Jinyan Sun
- School of Medicine, Foshan University, Foshan 528000, China
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Ercan R, Xia Y, Zhao Y, Loureiro R, Yang S, Zhao H. An Ultralow-Power Real-Time Machine Learning Based fNIRS Motion Artifacts Detection. IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS 2024; 32:763-773. [PMID: 38765316 PMCID: PMC11100859 DOI: 10.1109/tvlsi.2024.3356161] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 11/02/2023] [Accepted: 01/13/2024] [Indexed: 05/22/2024]
Abstract
Due to iterative matrix multiplications or gradient computations, machine learning modules often require a large amount of processing power and memory. As a result, they are often not feasible for use in wearable devices, which have limited processing power and memory. In this study, we propose an ultralow-power and real-time machine learning-based motion artifact detection module for functional near-infrared spectroscopy (fNIRS) systems. We achieved a high classification accuracy of 97.42%, low field-programmable gate array (FPGA) resource utilization of 38354 lookup tables and 6024 flip-flops, as well as low power consumption of 0.021 W in dynamic power. These results outperform conventional CPU support vector machine (SVM) methods and other state-of-the-art SVM implementations. This study has demonstrated that an FPGA-based fNIRS motion artifact classifier can be exploited while meeting low power and resource constraints, which are crucial in embedded hardware systems while keeping high classification accuracy.
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Affiliation(s)
- Renas Ercan
- UCLUCLWC1E 6BTLondonU.K.
- Department of PhysicsUniversity of CambridgeCB2 1TNCambridgeU.K.
| | - Yunjia Xia
- HUB of Intelligent Neuro-Engineering (HUBIN)Division of Surgery and Interventional ScienceUCLWC1E 6BTLondonU.K.
| | - Yunyi Zhao
- HUB of Intelligent Neuro-Engineering (HUBIN)Division of Surgery and Interventional ScienceUCLWC1E 6BTLondonU.K.
| | - Rui Loureiro
- IOMS, Division of Surgery and Interventional Science, UCLWC1E 6BTLondonU.K.
| | - Shufan Yang
- UCLUCLWC1E 6BTLondonU.K.
- Institute of Medical and Biological Engineering, School of Mechanical Engineering, University of LeedsLS2 9JTLeedsU.K.
| | - Hubin Zhao
- HUB of Intelligent Neuro-Engineering (HUBIN)Division of Surgery and Interventional ScienceUCLWC1E 6BTLondonU.K.
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Gao C, Xiu J, Huang C, Ma K, Li T. Reliability Evaluation for Continuous-Wave Functional Near-Infrared Spectroscopy Systems: Comprehensive Testing from Bench Characterization to Human Test. SENSORS (BASEL, SWITZERLAND) 2024; 24:2045. [PMID: 38610255 PMCID: PMC11014010 DOI: 10.3390/s24072045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Revised: 03/18/2024] [Accepted: 03/18/2024] [Indexed: 04/14/2024]
Abstract
In recent years, biomedical optics technology has developed rapidly. The current widespread use of biomedical optics was made possible by the invention of optical instruments. The advantages of being non-invasive, portable, effective, low cost, and less susceptible to system noise have led to the rapid development of functional near-infrared spectroscopy (fNIRS) technology for hemodynamics detection, especially in the field of functional brain imaging. At the same time, laboratories and companies have developed various fNIRS-based systems. The safety, stability, and efficacy of fNIRS systems are key performance indicators. However, there is still a lack of comprehensive and systematic evaluation methods for fNIRS instruments. This study uses the fNIRS system developed in our laboratory as the test object. The test method established in this study includes system validation and performance testing to comprehensively assess fNIRS systems' reliability. These methods feature low cost and high practicality. Based on this study, existing or newly developed systems can be comprehensively and easily evaluated in the laboratory or workspace.
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Affiliation(s)
- Chenyang Gao
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, China; (C.G.); (J.X.)
| | - Jia Xiu
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, China; (C.G.); (J.X.)
| | - Chong Huang
- Philips North America, Carlsbad, CA 92011, USA;
| | - Kaixue Ma
- School of Microelectronics, Tianjin University, Tianjin 300072, China;
| | - Ting Li
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300192, China; (C.G.); (J.X.)
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Ning M, Duwadi S, Yücel MA, von Lühmann A, Boas DA, Sen K. fNIRS dataset during complex scene analysis. Front Hum Neurosci 2024; 18:1329086. [PMID: 38576451 PMCID: PMC10991699 DOI: 10.3389/fnhum.2024.1329086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 03/06/2024] [Indexed: 04/06/2024] Open
Affiliation(s)
- Matthew Ning
- Department of Biomedical Engineering, Neurophotonics Center, Boston University, Boston, MA, United States
| | - Sudan Duwadi
- Department of Biomedical Engineering, Neurophotonics Center, Boston University, Boston, MA, United States
| | - Meryem A. Yücel
- Department of Biomedical Engineering, Neurophotonics Center, Boston University, Boston, MA, United States
| | - Alexander von Lühmann
- Department of Biomedical Engineering, Neurophotonics Center, Boston University, Boston, MA, United States
- BIFOLD – Berlin Institute for the Foundations of Learning and Data, Berlin, Germany
- Intelligent Biomedical Sensing (IBS) Lab, Technical University Berlin, Berlin, Germany
| | - David A. Boas
- Department of Biomedical Engineering, Neurophotonics Center, Boston University, Boston, MA, United States
| | - Kamal Sen
- Department of Biomedical Engineering, Neurophotonics Center, Boston University, Boston, MA, United States
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Ning M, Duwadi S, Yücel MA, Von Lühmann A, Boas DA, Sen K. fNIRS Dataset During Complex Scene Analysis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576715. [PMID: 38328139 PMCID: PMC10849700 DOI: 10.1101/2024.01.23.576715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
When analyzing complex scenes, humans often focus their attention on an object at a particular spatial location. The ability to decode the attended spatial location would facilitate brain computer interfaces for complex scene analysis (CSA). Here, we investigated capability of functional near-infrared spectroscopy (fNIRS) to decode audio-visual spatial attention in the presence of competing stimuli from multiple locations. We targeted dorsal frontoparietal network including frontal eye field (FEF) and intra-parietal sulcus (IPS) as well as superior temporal gyrus/planum temporal (STG/PT). They all were shown in previous functional magnetic resonance imaging (fMRI) studies to be activated by auditory, visual, or audio-visual spatial tasks. To date, fNIRS has not been applied to decode auditory and visual-spatial attention during CSA, and thus, no such dataset exists yet. This report provides an open-access fNIRS dataset that can be used to develop, test, and compare machine learning algorithms for classifying attended locations based on the fNIRS signals on a single trial basis.
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Affiliation(s)
- Matthew Ning
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Sudan Duwadi
- Neurophotonics Center, Department of Biomedical Engineering, Boston University
| | - Meryem A. Yücel
- Neurophotonics Center, Department of Biomedical Engineering, Boston University
| | - Alexander Von Lühmann
- Neurophotonics Center, Department of Biomedical Engineering, Boston University
- BIFOLD – Berlin Institute for the Foundations of Learning and Data, 10587 Berlin, Germany
- Intelligent Biomedical Sensing (IBS) Lab, Technische Universität Berlin, 10587 Berlin, Germany
| | - David A. Boas
- Neurophotonics Center, Department of Biomedical Engineering, Boston University
| | - Kamal Sen
- Neurophotonics Center, Department of Biomedical Engineering, Boston University
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Fazliazar E, Sudakou A, Sawosz P, Gerega A, Kacprzak M, Liebert A. Depth-selective method for time-domain diffuse reflectance measurements: validation study of the dual subtraction technique. BIOMEDICAL OPTICS EXPRESS 2023; 14:6233-6249. [PMID: 38420319 PMCID: PMC10898577 DOI: 10.1364/boe.497671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 08/18/2023] [Accepted: 08/28/2023] [Indexed: 03/02/2024]
Abstract
Research on the spatial distribution of sensitivity of time-domain near infrared diffuse reflectance measurement is reported in this paper. The main objective of the investigation is to validate theoretically calculated sensitivity profiles for a measurement geometry with two detectors and two sources in which sensitivity profiles of statistical moments of distributions of time of flight of photons (DTOFs) are spatially restricted to a region underneath the detectors. For this dual subtraction method, smaller sensitivities to changes appearing in the superficial layer of the medium were observed compared to the single distance and single subtraction methods. Experimental validation of this approach is based on evaluation of changes in the statistical moments of DTOFs measured on a liquid phantom with local absorption perturbations. The spatial distributions of sensitivities, depth-related sensitivity and depth selectivities were obtained from the dual subtraction method and compared with those from single distance and single subtraction approaches. Also, the contrast to noise ratio (CNR) was calculated for the dual subtraction technique and combined with depth selectivity in order to assess the overall performance (product of CNR and depth selectivity) of the method. Spatial sensitivity profiles from phantom experiments are in a good agreement with the results of theoretical studies and feature more locally restricted sensitivity volume with the point of maximal sensitivity located deeper. The highest value of overall performance was obtained experimentally for the second statistical moment in the dual subtraction method (∼10.8) surpassing that of the single distance method (∼8.7). This confirms the advantage of dual subtraction measurement geometries in the suppression of optical signals originated in the superficial layer of the medium.
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Affiliation(s)
- Elham Fazliazar
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Aleh Sudakou
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Piotr Sawosz
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Anna Gerega
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Michal Kacprzak
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
| | - Adam Liebert
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Warsaw, Poland
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Cowdrick KR, Urner T, Sathialingam E, Fang Z, Quadri A, Turrentine K, Yup Lee S, Buckley EM. Agreement in cerebrovascular reactivity assessed with diffuse correlation spectroscopy across experimental paradigms improves with short separation regression. NEUROPHOTONICS 2023; 10:025002. [PMID: 37034012 PMCID: PMC10079775 DOI: 10.1117/1.nph.10.2.025002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 03/07/2023] [Indexed: 06/19/2023]
Abstract
Significance Cerebrovascular reactivity (CVR), i.e., the ability of cerebral vasculature to dilate or constrict in response to vasoactive stimuli, is a biomarker of vascular health. Exogenous administration of inhaled carbon dioxide, i.e., hypercapnia (HC), remains the "gold-standard" intervention to assess CVR. More tolerable paradigms that enable CVR quantification when HC is difficult/contraindicated have been proposed. However, because these paradigms feature mechanistic differences in action, an assessment of agreement of these more tolerable paradigms to HC is needed. Aim We aim to determine the agreement of CVR assessed during HC, breath-hold (BH), and resting state (RS) paradigms. Approach Healthy adults were subject to HC, BH, and RS paradigms. End tidal carbon dioxide (EtCO2) and cerebral blood flow (CBF, assessed with diffuse correlation spectroscopy) were monitored continuously. CVR (%/mmHg) was quantified via linear regression of CBF versus EtCO2 or via a general linear model (GLM) that was used to minimize the influence of systemic and extracerebral signal contributions. Results Strong agreement ( CCC ≥ 0.69 ; R ≥ 0.76 ) among CVR paradigms was demonstrated when utilizing a GLM to regress out systemic/extracerebral signal contributions. Linear regression alone showed poor agreement across paradigms ( CCC ≤ 0.35 ; R ≤ 0.45 ). Conclusions More tolerable experimental paradigms coupled with regression of systemic/extracerebral signal contributions may offer a viable alternative to HC for assessing CVR.
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Affiliation(s)
- Kyle R. Cowdrick
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Tara Urner
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Eashani Sathialingam
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Zhou Fang
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Ayesha Quadri
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
- Morehouse School of Medicine, Atlanta, Georgia, United States
| | - Katherine Turrentine
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Seung Yup Lee
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Kennesaw State University, Department of Electrical and Computer Engineering, Marietta, Georgia, United States
| | - Erin M. Buckley
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Children’s Healthcare of Atlanta and Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
- Children’s Healthcare of Atlanta, Children’s Research Scholar, Atlanta, Georgia, United States
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Stress estimation by the prefrontal cortex asymmetry: Study on fNIRS signals. J Affect Disord 2023; 325:151-157. [PMID: 36627057 DOI: 10.1016/j.jad.2023.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 12/21/2022] [Accepted: 01/04/2023] [Indexed: 01/09/2023]
Abstract
BACKGROUND Functional near-infrared spectroscopy (fNIRS) is a non-invasive technique frequently used to measure the brain hemodynamic activity in applications to evaluate affective disorders and stress. Using two wavelengths of light, it is possible to monitor relative changes in the concentrations of oxyhemoglobin and deoxyhemoglobin. Besides, the spatial asymmetry in the prefrontal cortex activity has been correlated with the brain response to stressful situations. METHODS We measured prefrontal cortex activity with a NIRS multi-distance device during a baseline period, under stressful conditions (e.g., social stress), and after a recovery phase. We calculated a laterality index for the contaminated brain signal and for the brain signal where we removed the influence of extracerebral hemodynamic activity by using a short channel. RESULTS There was a significant right lateralization during stress when using the contaminated signals, consistent with previous investigations, but this significant difference disappeared using the corrected signals. Indeed, exploration of the susceptibility to contamination of the different channels showed non-homogeneous spatial patterns, which would hint at detection of stress from extracerebral activity from the forehead. LIMITATIONS There was no recovery phase between the social and the arithmetic stressor, a cumulative effect was not considered. CONCLUSIONS Extracerebral hemodynamic activity provided insights into the pertinence of short channel corrections in fNIRS studies dealing with emotions. It is important to consider this issue in clinical applications including modern monitoring systems based on fNIRS technique to assess emotional states in affective disorders.
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Rezaei E, Shalbaf A. Classification of Right/Left Hand Motor Imagery by Effective Connectivity Based on Transfer Entropy in Electroencephalogram Signal. Basic Clin Neurosci 2023; 14:213-224. [PMID: 38107527 PMCID: PMC10719976 DOI: 10.32598/bcn.2021.2034.3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 07/18/2021] [Accepted: 09/18/2021] [Indexed: 12/19/2023] Open
Abstract
Introduction The right and left-hand motor imagery (MI) analysis based on the electroencephalogram (EEG) signal can directly link the central nervous system to a computer or a device. This study aims to identify a set of robust and nonlinear effective brain connectivity features quantified by transfer entropy (TE) to characterize the relationship between brain regions from EEG signals and create a hierarchical feature selection and classification for discrimination of right and lefthand MI tasks. Methods TE is calculated among EEG channels as the distinctive, effective connectivity features. TE is a model-free method that can measure nonlinear effective connectivity and analyze multivariate dependent directed information flow among neural EEG channels. Then four feature subset selection methods namely relief-F, Fisher, Laplacian, and local learningbased clustering (LLCFS) algorithms are used to choose the most significant effective connectivity features and reduce redundant information. Finally, support vector machine (SVM) and linear discriminant analysis (LDA) methods are used for classification. Results Results show that the best performance in 29 healthy subjects and 60 trials is achieved using the TE method via the Relief-F algorithm as feature selection and support vector machine (SVM) classification with 91.02% accuracy. Conclusion The TE index and a hierarchical feature selection and classification can be useful for the discrimination of right- and left-hand MI tasks from multichannel EEG signals. Highlights Effective connectivity features were extracted from electroencephalogram (EEG) to analyze relationships between regions.Four feature selection methods used to select most significant effective features.Support vector machine (SVM) used for discrimination of right and left hand motor imagery (MI) task. Plain Language Summary In this study, we investigated brain activity using effective connectivity during MI task based on EEG signals. The motor imagery task can accomplish the same goal as motor execution, since they are both activated by the same brain area. Transfer entropy, coherence, and Granger casualty were employed to extract the features. Differential patterns of activity between the left vs. right MI task showed activity around the motor area rather than other areas. In order to reduce redundant information and select the most significant effective connectivity features, four feature subset selection algorithms are used: Relief-F, Fisher, Laplacian, and learning-based clustering feature selection (LLCFS). Then, support vector machine (SVM) and linear discriminant analysis (LDA) are used to classify left and right hand MI task. Comparison of three different connectivity methods showed that TE index had the highest classification accuracy, and could be useful for the discrimination of right and left hand MI tasks from multichannel EEG signals.
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Affiliation(s)
- Erfan Rezaei
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Ahmad Shalbaf
- Department of Medical Physics and Biomedical Engineering, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Blaney G, Fernandez C, Sassaroli A, Fantini S. Dual-slope imaging of cerebral hemodynamics with frequency-domain near-infrared spectroscopy. NEUROPHOTONICS 2023; 10:013508. [PMID: 36601543 PMCID: PMC9807277 DOI: 10.1117/1.nph.10.1.013508] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
Significance This work targets the contamination of optical signals by superficial hemodynamics, which is one of the chief hurdles in non-invasive optical measurements of the human brain. Aim To identify optimal source-detector distances for dual-slope (DS) measurements in frequency-domain (FD) near-infrared spectroscopy (NIRS) and demonstrate preferential sensitivity of DS imaging to deeper tissue (brain) versus superficial tissue (scalp). Approach Theoretical studies (in-silico) based on diffusion theory in two-layered and in homogeneous scattering media. In-vivo demonstrations of DS imaging of the human brain during visual stimulation and during systemic blood pressure oscillations. Results The mean distance (between the two source-detector distances needed for DS) is the key factor for depth sensitivity. In-vivo imaging of the human occipital lobe with FD NIRS and a mean distance of 31 mm indicated: (1) greater hemodynamic response to visual stimulation from FD phase versus intensity, and from DS versus single-distance (SD); (2) hemodynamics from FD phase and DS mainly driven by blood flow, and hemodynamics from SD intensity mainly driven by blood volume. Conclusions DS imaging with FD NIRS may suppress confounding contributions from superficial hemodynamics without relying on data at short source-detector distances. This capability can have significant implications for non-invasive optical measurements of the human brain.
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Affiliation(s)
- Giles Blaney
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Cristianne Fernandez
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Angelo Sassaroli
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Sergio Fantini
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
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Klein F, Lührs M, Benitez-Andonegui A, Roehn P, Kranczioch C. Performance comparison of systemic activity correction in functional near-infrared spectroscopy for methods with and without short distance channels. NEUROPHOTONICS 2023; 10:013503. [PMID: 36248616 PMCID: PMC9555616 DOI: 10.1117/1.nph.10.1.013503] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 07/25/2022] [Indexed: 05/20/2023]
Abstract
Significance: Functional near-infrared spectroscopy (fNIRS) is a promising tool for neurofeedback (NFB) or brain-computer interfaces (BCIs). However, fNIRS signals are typically highly contaminated by systemic activity (SA) artifacts, and, if not properly corrected, NFB or BCIs run the risk of being based on noise instead of brain activity. This risk can likely be reduced by correcting for SA, in particular when short-distance channels (SDCs) are available. Literature comparing correction methods with and without SDCs is still sparse, specifically comparisons considering single trials are lacking. Aim: This study aimed at comparing the performance of SA correction methods with and without SDCs. Approach: Semisimulated and real motor task data of healthy older adults were used. Correction methods without SDCs included a simple and a more advanced spatial filter. Correction methods with SDCs included a regression approach considering only the closest SDC and two GLM-based methods, one including all eight SDCs and one using only two a priori selected SDCs as regressors. All methods were compared with data uncorrected for SA and correction performance was assessed with quality measures quantifying signal improvement and spatial specificity at single trial level. Results: All correction methods were found to improve signal quality and enhance spatial specificity as compared with the uncorrected data. Methods with SDCs usually outperformed methods without SDCs. Correction methods without SDCs tended to overcorrect the data. However, the exact pattern of results and the degree of differences observable between correction methods varied between semisimulated and real data, and also between quality measures. Conclusions: Overall, results confirmed that both Δ [ HbO ] and Δ [ HbR ] are affected by SA and that correction methods with SDCs outperform methods without SDCs. Nonetheless, improvements in signal quality can also be achieved without SDCs and should therefore be given priority over not correcting for SA.
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Affiliation(s)
- Franziska Klein
- Carl von Ossietzky University of Oldenburg, Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Oldenburg, Germany
- Address all correspondence to Franziska Klein,
| | - Michael Lührs
- Maastricht University, Faculty of Psychology and Neuroscience, Maastricht, The Netherlands
- Brain Innovation B.V., Maastricht, The Netherlands
| | | | - Pauline Roehn
- Carl von Ossietzky University of Oldenburg, Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Oldenburg, Germany
| | - Cornelia Kranczioch
- Carl von Ossietzky University of Oldenburg, Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Oldenburg, Germany
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Becker S, Klein F, König K, Mathys C, Liman T, Witt K. Assessment of dynamic cerebral autoregulation in near-infrared spectroscopy using short channels: A feasibility study in acute ischemic stroke patients. Front Neurol 2022; 13:1028864. [PMID: 36479048 PMCID: PMC9719939 DOI: 10.3389/fneur.2022.1028864] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 11/04/2022] [Indexed: 10/07/2023] Open
Abstract
Introduction In acute ischemic stroke, progressive impairment of cerebral autoregulation (CA) is frequent and associated with unfavorable outcomes. Easy assessment of cerebral blood flow and CA in stroke units bedside tools like near-infrared spectroscopy (NIRS) might improve early detection of CA deterioration. This study aimed to assess dynamic CA with multichannel CW-NIRS in acute ischemic stroke (AIS) patients compared to agematched healthy controls. Methods CA reaction was amplified by changes in head of bed position. Long- and short channels were used to monitor systemic artery pressure- and intracranial oscillations simultaneously. Gain and phase shift in spontaneous low- and very low-frequency oscillations (LFO, VLFO) of blood pressure were assessed. Results A total of 54 participants, 27 with AIS and 27 age-matched controls were included. Gain was significantly lower in the AIS group in the LFO range (i) when the upper body was steadily elevated to 30. and (ii) after its abrupt elevation to 30°. No other differences were found between groups. Discussion This study demonstrates the feasibility of NIRS short channels to measure CA in AIS patients in one single instrument. A lower gain in AIS might indicate decreased CA activity in this pilot study, but further studies investigating the role of NIRS short channels in AIS are needed.
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Affiliation(s)
- Sabeth Becker
- Department of Neurology, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
| | - Franziska Klein
- Neurocognition and Functional Neurorehabilitation Group, Neuropsychology Lab, Department of Psychology, Faculty of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
| | - Katja König
- Department of Neurology, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
- University Clinic for Neurology, Evangelical Hospital, Oldenburg, Germany
| | - Christian Mathys
- Institute of Radiology and Neuroradiology, Evangelical Hospital, Oldenburg, Germany
- Research Centre Neurosensory Science, Department of Human Medicine, Faculty of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
| | - Thomas Liman
- Department of Neurology, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
- University Clinic for Neurology, Evangelical Hospital, Oldenburg, Germany
| | - Karsten Witt
- Department of Neurology, School of Medicine and Health Sciences, Carl von Ossietzky University of Oldenburg, Oldenburg, Germany
- University Clinic for Neurology, Evangelical Hospital, Oldenburg, Germany
- Institute of Radiology and Neuroradiology, Evangelical Hospital, Oldenburg, Germany
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13
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Paul R, Murali K, Varma HM. High-density diffuse correlation tomography with enhanced depth localization and minimal surface artefacts. BIOMEDICAL OPTICS EXPRESS 2022; 13:6081-6099. [PMID: 36733746 PMCID: PMC9872877 DOI: 10.1364/boe.469405] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 09/14/2022] [Accepted: 09/21/2022] [Indexed: 05/08/2023]
Abstract
A spatially weighted filter applied to both the measurement and the Jacobian is proposed for high-density diffuse correlation tomography (DCT) to remove unwanted extracerebral interferences and artefacts along with better depth localization in the reconstructed blood flow images. High-density DCT is implemented by appropriate modification of recently introduced Multi-speckle Diffuse Correlation Spectroscopy (M-DCS) system. Additionally, we have used autocorrelation measurements at multiple delay-times in an iterative manner to improve the reconstruction results. The proposed scheme has been validated by simulations, phantom experiments and in-vivo human experiments.
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14
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Trambaiolli LR, Cassani R, Biazoli CE, Cravo AM, Sato JR, Falk TH. Multimodal resting-state connectivity predicts affective neurofeedback performance. Front Hum Neurosci 2022; 16:977776. [PMID: 36158618 PMCID: PMC9493361 DOI: 10.3389/fnhum.2022.977776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/03/2022] [Indexed: 11/13/2022] Open
Abstract
Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The fNIRS oxyhemoglobin and deoxyhemoglobin concentrations and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into "connectivity summary scores" (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson's correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = -0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation.
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Affiliation(s)
- Lucas R. Trambaiolli
- Basic Neuroscience Division, McLean Hospital–Harvard Medical School, Belmont, MA, United States
| | - Raymundo Cassani
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Claudinei E. Biazoli
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom
| | - André M. Cravo
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
| | - João R. Sato
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
- Big Data, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Tiago H. Falk
- Institut National de la Recherche Scientifique, University of Quebec, Montreal, QC, Canada
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15
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Molina-Rodríguez S, Mirete-Fructuoso M, Martínez LM, Ibañez-Ballesteros J. Frequency-domain analysis of fNIRS fluctuations induced by rhythmic mental arithmetic. Psychophysiology 2022; 59:e14063. [PMID: 35394075 PMCID: PMC9540762 DOI: 10.1111/psyp.14063] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 01/19/2022] [Accepted: 03/08/2022] [Indexed: 12/25/2022]
Abstract
Functional near‐infrared spectroscopy (fNIRS) is an increasingly used technology for imaging neural correlates of cognitive processes. However, fNIRS signals are commonly impaired by task‐evoked and spontaneous hemodynamic oscillations of non‐cerebral origin, a major challenge in fNIRS research. In an attempt to isolate the task‐evoked cortical response, we investigated the coupling between hemodynamic changes arising from superficial and deep layers during mental effort. For this aim, we applied a rhythmic mental arithmetic task to induce cyclic hemodynamic fluctuations suitable for effective frequency‐resolved measurements. Twenty university students aged 18–25 years (eight males) underwent the task while hemodynamic changes were monitored in the forehead using a newly developed NIRS device, capable of multi‐channel and multi‐distance recordings. We found significant task‐related fluctuations for oxy‐ and deoxy‐hemoglobin, highly coherent across shallow and deep tissue layers, corroborating the strong influence of surface hemodynamics on deep fNIRS signals. Importantly, after removing such surface contamination by linear regression, we show that the frontopolar cortex response to a mental math task follows an unusual inverse oxygenation pattern. We confirm this finding by applying for the first time an alternative method to estimate the neural signal, based on transfer function analysis and phasor algebra. Altogether, our results demonstrate the feasibility of using a rhythmic mental task to impose an oscillatory state useful to separate true brain functional responses from those of non‐cerebral origin. This separation appears to be essential for a better understanding of fNIRS data and to assess more precisely the dynamics of the neuro‐visceral link. We proposed the use of rhythmic mental arithmetic tasks to induce cyclic oscillations in multi‐distance fNIRS signals measured on the forehead, suitable for effective frequency‐domain analysis to better identify the actual neural functional response. We confirm the impairment of deep signals by task‐evoked non‐cerebral confounds, while providing evidence for an inverse oxygenation response in the frontopolar cortex.
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Affiliation(s)
- Sergio Molina-Rodríguez
- Cellular and Systems Neurobiology, Institute of Neurosciences, Spanish National Research Council-Miguel Hernandez University, Alicante, Spain
| | - Marcos Mirete-Fructuoso
- Cellular and Systems Neurobiology, Institute of Neurosciences, Spanish National Research Council-Miguel Hernandez University, Alicante, Spain
| | - Luis M Martínez
- Cellular and Systems Neurobiology, Institute of Neurosciences, Spanish National Research Council-Miguel Hernandez University, Alicante, Spain
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16
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Poon CS, Langri DS, Rinehart B, Rambo TM, Miller AJ, Foreman B, Sunar U. First-in-clinical application of a time-gated diffuse correlation spectroscopy system at 1064 nm using superconducting nanowire single photon detectors in a neuro intensive care unit. BIOMEDICAL OPTICS EXPRESS 2022; 13:1344-1356. [PMID: 35414986 PMCID: PMC8973196 DOI: 10.1364/boe.448135] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 01/20/2022] [Accepted: 01/24/2022] [Indexed: 06/02/2023]
Abstract
Recently proposed time-gated diffuse correlation spectroscopy (TG-DCS) has significant advantages compared to conventional continuous wave (CW)-DCS, but it is still in an early stage and clinical capability has yet to be established. The main challenge for TG-DCS is the lower signal-to-noise ratio (SNR) when gating for the deeper traveling late photons. Longer wavelengths, such as 1064 nm have a smaller effective attenuation coefficient and a higher power threshold in humans, which significantly increases the SNR. Here, we demonstrate the clinical utility of TG-DCS at 1064 nm in a case study on a patient with severe traumatic brain injury admitted to the neuro-intensive care unit (neuroICU). We showed a significant correlation between TG-DCS early (ρ = 0.67) and late (ρ = 0.76) gated against invasive thermal diffusion flowmetry. We also analyzed TG-DCS at high temporal resolution (50 Hz) to elucidate pulsatile flow data. Overall, this study demonstrates the first clinical translation capability of the TG-DCS system at 1064 nm using a superconducting nanowire single-photon detector.
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Affiliation(s)
- Chien-Sing Poon
- Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, OH 45435, USA
| | - Dharminder S. Langri
- Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, OH 45435, USA
| | - Benjamin Rinehart
- Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, OH 45435, USA
| | | | | | - Brandon Foreman
- Dept of Neurology & Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH 45219, USA
| | - Ulas Sunar
- Department of Biomedical, Industrial and Human Factors Engineering, Wright State University, Dayton, OH 45435, USA
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17
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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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18
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De Wachter J, Proost M, Habay J, Verstraelen M, Díaz-García J, Hurst P, Meeusen R, Van Cutsem J, Roelands B. Prefrontal Cortex Oxygenation During Endurance Performance: A Systematic Review of Functional Near-Infrared Spectroscopy Studies. Front Physiol 2021; 12:761232. [PMID: 34764885 PMCID: PMC8576380 DOI: 10.3389/fphys.2021.761232] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 09/27/2021] [Indexed: 01/17/2023] Open
Abstract
Introduction: A myriad of factors underlie pacing-/exhaustion-decisions that are made during whole-body endurance performance. The prefrontal cortex (PFC) is a brain region that is crucial for decision-making, planning, and attention. PFC oxygenation seems to be a mediating factor of performance decisions during endurance performance. Nowadays, there is no general overview summarizing the current knowledge on how PFC oxygenation evolves during whole-body endurance performance and whether this is a determining factor. Methods: Three electronic databases were searched for studies related to the assessment of PFC oxygenation, through near-IR spectroscopy (NIRS), during endurance exercise. To express PFC oxygenation, oxygenated (HbO2) and deoxygenated hemoglobin (HHb) concentrations were the primary outcome measures. Results: Twenty-eight articles were included. Ten articles focused on assessing prefrontal oxygenation through a maximal incremental test (MIT) and 18 focused on using endurance tasks at workloads ranging from low intensity to supramaximal intensity. In four MIT studies measuring HbO2, an increase of HbO2 was noticed at the respiratory compensation point (RCP), after which it decreased. HbO2 reached a steady state in the four studies and increased in one study until exhaustion. All studies found a decrease or steady state in HHb from the start until RCP and an increase to exhaustion. In regard to (non-incremental) endurance tasks, a general increase in PFC oxygenation was found while achieving a steady state at vigorous intensities. PCF deoxygenation was evident for near-to-maximal intensities at which an increase in oxygenation and the maintenance of a steady state could not be retained. Discussion/Conclusion: MIT studies show the presence of a cerebral oxygenation threshold (ThCox) at RCP. PFC oxygenation increases until the RCP threshold, thereafter, a steady state is reached and HbO2 declines. This study shows that the results obtained from MIT are transferable to non-incremental endurance exercise. HbO2 increases during low-intensity and moderate-intensity until vigorous-intensity exercise, and it reaches a steady state in vigorous-intensity exercise. Furthermore, ThCox can be found between vigorous and near-maximal intensities. During endurance exercise at near-maximal intensities, PFC oxygenation increases until the value exceeding this threshold, resulting in a decrease in PFC oxygenation. Future research should aim at maintaining and improving PFC oxygenation to help in improving endurance performance and to examine whether PFC oxygenation has a role in other performance-limiting factors.
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Affiliation(s)
- Jonas De Wachter
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium
| | - Matthias Proost
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium
| | - Jelle Habay
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium
| | - Matthias Verstraelen
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium
| | - Jesús Díaz-García
- Faculty of Sport Sciences, University of Extremadura, Caceres, Spain
| | - Philip Hurst
- The School of Psychology & Life Sciences, Canterbury Christ Church University, Canterbury, United Kingdom
| | - Romain Meeusen
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium
| | - Jeroen Van Cutsem
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium.,VIPER Research Unit, Royal Military Academy, Brussels, Belgium
| | - Bart Roelands
- Human Physiology and Sports Physiotherapy Research Group, Vrije Universiteit Brussel, Brussels, Belgium
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19
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Huo C, Xu G, Li W, Xie H, Zhang T, Liu Y, Li Z. A review on functional near-infrared spectroscopy and application in stroke rehabilitation. MEDICINE IN NOVEL TECHNOLOGY AND DEVICES 2021. [DOI: 10.1016/j.medntd.2021.100064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
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20
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A Motion Artifact Correction Procedure for fNIRS Signals Based on Wavelet Transform and Infrared Thermography Video Tracking. SENSORS 2021; 21:s21155117. [PMID: 34372353 PMCID: PMC8346954 DOI: 10.3390/s21155117] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Revised: 07/13/2021] [Accepted: 07/26/2021] [Indexed: 12/13/2022]
Abstract
Functional near infrared spectroscopy (fNIRS) is a neuroimaging technique that allows to monitor the functional hemoglobin oscillations related to cortical activity. One of the main issues related to fNIRS applications is the motion artefact removal, since a corrupted physiological signal is not correctly indicative of the underlying biological process. A novel procedure for motion artifact correction for fNIRS signals based on wavelet transform and video tracking developed for infrared thermography (IRT) is presented. In detail, fNIRS and IRT were concurrently recorded and the optodes' movement was estimated employing a video tracking procedure developed for IRT recordings. The wavelet transform of the fNIRS signal and of the optodes' movement, together with their wavelet coherence, were computed. Then, the inverse wavelet transform was evaluated for the fNIRS signal excluding the frequency content corresponding to the optdes' movement and to the coherence in the epochs where they were higher with respect to an established threshold. The method was tested using simulated functional hemodynamic responses added to real resting-state fNIRS recordings corrupted by movement artifacts. The results demonstrated the effectiveness of the procedure in eliminating noise, producing results with higher signal to noise ratio with respect to another validated method.
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21
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Pinti P, Devoto A, Greenhalgh I, Tachtsidis I, Burgess PW, de C Hamilton AF. The role of anterior prefrontal cortex (area 10) in face-to-face deception measured with fNIRS. Soc Cogn Affect Neurosci 2021; 16:129-142. [PMID: 32577765 PMCID: PMC7812627 DOI: 10.1093/scan/nsaa086] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 05/19/2020] [Accepted: 06/15/2020] [Indexed: 12/12/2022] Open
Abstract
Anterior prefrontal cortex (PFC, Brodmann area 10) activations are often, but not always, found in neuroimaging studies investigating deception, and the precise role of this area remains unclear. To explore the role of the PFC in face-to-face deception, we invited pairs of participants to play a card game involving lying and lie detection while we used functional near infrared spectroscopy (fNIRS) to record brain activity in the PFC. Participants could win points for successfully lying about the value of their cards or for detecting lies. We contrasted patterns of brain activation when the participants either told the truth or lied, when they were either forced into this or did so voluntarily and when they either succeeded or failed to detect a lie. Activation in the anterior PFC was found in both lie production and detection, unrelated to reward. Analysis of cross-brain activation patterns between participants identified areas of the PFC where the lead player’s brain activity synchronized their partner’s later brain activity. These results suggest that during situations that involve close interpersonal interaction, the anterior PFC supports processing widely involved in deception, possibly relating to the demands of monitoring one’s own and other people’s behaviour.
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Affiliation(s)
- Paola Pinti
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK.,Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
| | - Andrea Devoto
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
| | - Isobel Greenhalgh
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
| | - Ilias Tachtsidis
- Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK
| | - Paul W Burgess
- Institute of Cognitive Neuroscience, University College London, London WC1N 3AZ, UK
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22
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Zhou W, Kholiqov O, Zhu J, Zhao M, Zimmermann LL, Martin RM, Lyeth BG, Srinivasan VJ. Functional interferometric diffusing wave spectroscopy of the human brain. SCIENCE ADVANCES 2021; 7:eabe0150. [PMID: 33980479 PMCID: PMC8115931 DOI: 10.1126/sciadv.abe0150] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2020] [Accepted: 03/23/2021] [Indexed: 05/18/2023]
Abstract
Cerebral blood flow (CBF) is essential for brain function, and CBF-related signals can inform us about brain activity. Yet currently, high-end medical instrumentation is needed to perform a CBF measurement in adult humans. Here, we describe functional interferometric diffusing wave spectroscopy (fiDWS), which introduces and collects near-infrared light via the scalp, using inexpensive detector arrays to rapidly monitor coherent light fluctuations that encode brain blood flow index (BFI), a surrogate for CBF. Compared to other functional optical approaches, fiDWS measures BFI faster and deeper while also providing continuous wave absorption signals. Achieving clear pulsatile BFI waveforms at source-collector separations of 3.5 cm, we confirm that optical BFI, not absorption, shows a graded hypercapnic response consistent with human cerebrovascular physiology, and that BFI has a better contrast-to-noise ratio than absorption during brain activation. By providing high-throughput measurements of optical BFI at low cost, fiDWS will expand access to CBF.
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Affiliation(s)
- Wenjun Zhou
- Department of Biomedical Engineering, University of California, Davis, Davis, CA, USA
| | - Oybek Kholiqov
- Department of Biomedical Engineering, University of California, Davis, Davis, CA, USA
| | - Jun Zhu
- Department of Biomedical Engineering, University of California, Davis, Davis, CA, USA
| | - Mingjun Zhao
- Department of Biomedical Engineering, University of California, Davis, Davis, CA, USA
| | - Lara L Zimmermann
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA, USA
| | - Ryan M Martin
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA, USA
| | - Bruce G Lyeth
- Department of Neurological Surgery, University of California, Davis, Sacramento, CA, USA
| | - Vivek J Srinivasan
- Department of Biomedical Engineering, University of California, Davis, Davis, CA, USA.
- Department of Ophthalmology and Vision Science, University of California, Davis, Sacramento, CA, USA
- Department of Ophthalmology, NYU Langone Health, New York, NY, USA
- Department of Radiology, NYU Langone Health, New York, NY, USA
- Tech4Health Institute, NYU Langone Health, New York, NY, USA
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23
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Deconvolution of hemodynamic responses along the cortical surface using personalized functional near infrared spectroscopy. Sci Rep 2021; 11:5964. [PMID: 33727581 PMCID: PMC7966407 DOI: 10.1038/s41598-021-85386-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Accepted: 02/26/2021] [Indexed: 11/28/2022] Open
Abstract
In functional near infrared spectroscopy (fNIRS), deconvolution analysis of oxy and deoxy-hemoglobin concentration changes allows estimating specific hemodynamic response functions (HRF) elicited by neuronal activity, taking advantage of the fNIRS excellent temporal resolution. Diffuse optical tomography (DOT) is also becoming the new standard reconstruction procedure as it is more accurate than the modified Beer Lambert law approach at the sensor level. The objective of this study was to assess the relevance of HRF deconvolution after DOT constrained along the cortical surface. We used local personalized fNIRS montages which consists in optimizing the position of fNIRS optodes to ensure maximal sensitivity to subject specific target brain regions. We carefully evaluated the accuracy of deconvolution when applied after DOT, using realistic simulations involving several HRF models at different signal to noise ratio (SNR) levels and on real data related to motor and visual tasks in healthy subjects and from spontaneous pathological activity in one patient with epilepsy. We demonstrated that DOT followed by deconvolution was able to accurately recover a large variability of HRFs over a large range of SNRs. We found good performances of deconvolution analysis for SNR levels usually encountered in our applications and we were able to reconstruct accurately the temporal dynamics of HRFs in real conditions.
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24
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Trambaiolli LR, Tossato J, Cravo AM, Biazoli CE, Sato JR. Subject-independent decoding of affective states using functional near-infrared spectroscopy. PLoS One 2021; 16:e0244840. [PMID: 33411817 PMCID: PMC7790273 DOI: 10.1371/journal.pone.0244840] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 12/01/2020] [Indexed: 11/25/2022] Open
Abstract
Affective decoding is the inference of human emotional states using brain signal measurements. This approach is crucial to develop new therapeutic approaches for psychiatric rehabilitation, such as affective neurofeedback protocols. To reduce the training duration and optimize the clinical outputs, an ideal clinical neurofeedback could be trained using data from an independent group of volunteers before being used by new patients. Here, we investigated if this subject-independent design of affective decoding can be achieved using functional near-infrared spectroscopy (fNIRS) signals from frontal and occipital areas. For this purpose, a linear discriminant analysis classifier was first trained in a dataset (49 participants, 24.65±3.23 years) and then tested in a completely independent one (20 participants, 24.00±3.92 years). Significant balanced accuracies between classes were found for positive vs. negative (64.50 ± 12.03%, p<0.01) and negative vs. neutral (68.25 ± 12.97%, p<0.01) affective states discrimination during a reactive block consisting in viewing affective-loaded images. For an active block, in which volunteers were instructed to recollect personal affective experiences, significant accuracy was found for positive vs. neutral affect classification (71.25 ± 18.02%, p<0.01). In this last case, only three fNIRS channels were enough to discriminate between neutral and positive affective states. Although more research is needed, for example focusing on better combinations of features and classifiers, our results highlight fNIRS as a possible technique for subject-independent affective decoding, reaching significant classification accuracies of emotional states using only a few but biologically relevant features.
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Affiliation(s)
- Lucas R. Trambaiolli
- Division of Basic Neuroscience, McLean Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- * E-mail:
| | - Juliana Tossato
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, São Paulo, Brazil
| | - André M. Cravo
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, São Paulo, Brazil
| | - Claudinei E. Biazoli
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, São Paulo, Brazil
| | - João R. Sato
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, São Paulo, Brazil
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25
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Nemani A, Kamat A, Gao Y, Yucel M, Gee D, Cooper C, Schwaitzberg S, Intes X, Dutta A, De S. Functional brain connectivity related to surgical skill dexterity in physical and virtual simulation environments. NEUROPHOTONICS 2021; 8:015008. [PMID: 33681406 PMCID: PMC7927423 DOI: 10.1117/1.nph.8.1.015008] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 02/11/2021] [Indexed: 05/15/2023]
Abstract
Significance: Surgical simulators, both virtual and physical, are increasingly used as training tools for teaching and assessing surgical technical skills. However, the metrics used for assessment in these simulation environments are often subjective and inconsistent. Aim: We propose functional activation metrics, derived from brain imaging measurements, to objectively assess the correspondence between brain activation with surgical motor skills for subjects with varying degrees of surgical skill. Approach: Cortical activation based on changes in the oxygenated hemoglobin (HbO) of 36 subjects was measured using functional near-infrared spectroscopy at the prefrontal cortex (PFC), primary motor cortex, and supplementary motor area (SMA) due to their association with motor skill learning. Inter-regional functional connectivity metrics, namely, wavelet coherence (WCO) and wavelet phase coherence were derived from HbO changes to correlate brain activity to surgical motor skill levels objectively. Results: One-way multivariate analysis of variance found a statistically significant difference in the inter-regional WCO metrics for physical simulator based on Wilk's Λ for expert versus novice, F ( 10,1 ) = 7495.5 , p < 0.01 . Partial eta squared effect size for the inter-regional WCO metrics was found to be highest between the central prefrontal cortex (CPFC) and SMA, CPFC-SMA ( η 2 = 0.257 ). Two-tailed Mann-Whitney U tests with a 95% confidence interval showed baseline equivalence and a statistically significant ( p < 0.001 ) difference in the CPFC-SMA WPCO metrics for the physical simulator training group ( 0.960 ± 0.045 ) versus the untrained control group ( 0.735 ± 0.177 ) following training for 10 consecutive days in addition to the pretest and posttest days. Conclusion: We show that brain functional connectivity WCO metric corresponds to surgical motor skills in the laparoscopic physical simulators. Functional connectivity between the CPFC and the SMA is lower for subjects that exhibit expert surgical motor skills than untrained subjects in laparoscopic physical simulators.
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Affiliation(s)
- Arun Nemani
- Rensselaer Polytechnic Institute, Center for Modeling, Simulation, and Imaging in Medicine, Troy, New York, United States
| | - Anil Kamat
- Rensselaer Polytechnic Institute, Center for Modeling, Simulation, and Imaging in Medicine, Troy, New York, United States
| | - Yuanyuan Gao
- Rensselaer Polytechnic Institute, Center for Modeling, Simulation, and Imaging in Medicine, Troy, New York, United States
| | - Meryem Yucel
- Massachusetts General Hospital, Department of Surgery, Boston, Massachusetts, United States
| | - Denise Gee
- Massachusetts General Hospital, Department of Surgery, Boston, Massachusetts, United States
| | - Clairice Cooper
- University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, United States
| | - Steven Schwaitzberg
- University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, United States
| | - Xavier Intes
- Rensselaer Polytechnic Institute, Center for Modeling, Simulation, and Imaging in Medicine, Troy, New York, United States
| | - Anirban Dutta
- University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, New York, United States
| | - Suvranu De
- Rensselaer Polytechnic Institute, Center for Modeling, Simulation, and Imaging in Medicine, Troy, New York, United States
- Address all correspondence to Suvranu De,
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26
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Veesa JD, Dehghani H. Signal regression in frequency-domain diffuse optical tomography to remove superficial signal contamination. NEUROPHOTONICS 2021; 8:015013. [PMID: 33816650 PMCID: PMC8011719 DOI: 10.1117/1.nph.8.1.015013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 03/17/2021] [Indexed: 05/28/2023]
Abstract
Significance: Signal contamination is a major hurdle in functional near-infrared spectroscopy (fNIRS) of the human head as the NIR signal is contaminated with the changes corresponding to superficial tissue, therefore occluding the functional information originating from the cerebral region. For continuous wave, this is generally handled through linear regression of the shortest source-detector (SD) distance intensity measurement from all of the signals. Although phase measurements utilizing frequency domain (FD) provide deeper tissue sampling, the use of the shortest SD distance phase measurement for regression of superficial signal contamination can lead to misleading results, therefore suppressing cortical signals. Aim: An approach for FD fNIRS that utilizes a short-separation intensity signal directly to regress both intensity and phase measurements, providing a better regression of superficial signal contamination from both data-types, is proposed. Approach: Simulated data from realistic models of the human head are used, and signal regression using both intensity and phase-based components of the FD fNIRS is evaluated. Results: Intensity-based phase regression achieves a suppression of superficial signal contamination by 68% whereas phase-based phase regression is only by 13%. Phase-based phase regression is also shown to generate false-positive signals from the cortex, which are not desirable. Conclusions: Intensity-based phase regression provides a better methodology for minimizing superficial signal contamination in FD fNIRS.
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Affiliation(s)
- Joshua D. Veesa
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
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27
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Zhou X, Sobczak G, McKay CM, Litovsky RY. Comparing fNIRS signal qualities between approaches with and without short channels. PLoS One 2020; 15:e0244186. [PMID: 33362260 PMCID: PMC7757903 DOI: 10.1371/journal.pone.0244186] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 12/04/2020] [Indexed: 11/18/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is a non-invasive technique used to measure changes in oxygenated (HbO) and deoxygenated (HbR) hemoglobin, related to neuronal activity. fNIRS signals are contaminated by the systemic responses in the extracerebral tissue (superficial layer) of the head, as fNIRS uses a back-reflection measurement. Using shorter channels that are only sensitive to responses in the extracerebral tissue but not in the deeper layers where target neuronal activity occurs has been a ‘gold standard’ to reduce the systemic responses in the fNIRS data from adults. When shorter channels are not available or feasible for implementation, an alternative, i.e., anti-correlation (Anti-Corr) method has been adopted. To date, there has not been a study that directly assesses the outcomes from the two approaches. In this study, we compared the Anti-Corr method with the ‘gold standard’ in reducing systemic responses to improve fNIRS neural signal qualities. We used eight short channels (8-mm) in a group of adults, and conducted a principal component analysis (PCA) to extract two components that contributed the most to responses in the 8 short channels, which were assumed to contain the global components in the extracerebral tissue. We then used a general linear model (GLM), with and without including event-related regressors, to regress out the 2 principal components from regular fNIRS channels (30 mm), i.e., two GLM-PCA methods. Our results found that, the two GLM-PCA methods showed similar performance, both GLM-PCA methods and the Anti-Corr method improved fNIRS signal qualities, and the two GLM-PCA methods had better performance than the Anti-Corr method.
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Affiliation(s)
- Xin Zhou
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- * E-mail:
| | - Gabriel Sobczak
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Colette M. McKay
- Bionics Institute of Australia, Melbourne, Australia
- Department of Medical Bionics, University of Melbourne, Melbourne, Australia
| | - Ruth Y. Litovsky
- Waisman Center, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Department of Communication Science and Disorders, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Department of Surgery, Division of Otolaryngology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
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28
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Chen X, Song X, Chen L, An X, Ming D. Performance Improvement for Detecting Brain Function Using fNIRS: A Multi-Distance Probe Configuration With PPL Method. Front Hum Neurosci 2020; 14:569508. [PMID: 33240063 PMCID: PMC7677412 DOI: 10.3389/fnhum.2020.569508] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 09/25/2020] [Indexed: 11/25/2022] Open
Abstract
To improve the spatial resolution of imaging and get more effective brain function information, a multi-distance probe configuration with three distances (28.2, 40, and 44.7 mm) and 52 channels is designed. At the same time, a data conversion method of modified Beer–Lambert law (MBLL) with partial pathlength (PPL) is proposed. In the experiment, three kinds of tasks, grip of left hand, grip of right hand, and rest, are performed with eight healthy subjects. First, with a typical single-distance probe configuration (30 mm, 24 channels), the feasibility of the proposed MBLL with PPL is preliminarily validated. Further, the characteristic of the proposed method is evaluated with the multi-distance probe configuration. Compared with MBLL with differential pathlength factor (DPF), the proposed MBLL with PPL is able to acquire more obvious concentration change and can achieve higher classification accuracy of the three tasks. Then, with the proposed method, the performance of the multi-distance probe configuration is discussed. Results show that, compared with a single distance, the combination of the three distances has better spatial resolution and could explore more accurate brain activation information. Besides, the classification accuracy of the three tasks obtained with the combination of three distances is higher than that of any combination of two distances. Also, with the combination of the three distances, the two-class classification between different tasks is carried out. Both theory and experimental results demonstrate that, using multi-distance probe configuration and the MBLL with PPL method, the performance of brain function detected by NIRS can be improved.
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Affiliation(s)
- Xinrui Chen
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
| | - Xizi Song
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
| | - Long Chen
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
| | - Xingwei An
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translation Medicine, Tianjin University, Tianjin, China
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China
- *Correspondence: Dong Ming,
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29
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Hernandez-Martin E, Marcano F, Modroño C, Janssen N, González-Mora JL. Diffuse optical tomography to measure functional changes during motor tasks: a motor imagery study. BIOMEDICAL OPTICS EXPRESS 2020; 11:6049-6067. [PMID: 33282474 PMCID: PMC7687968 DOI: 10.1364/boe.399907] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 09/12/2020] [Accepted: 09/16/2020] [Indexed: 05/03/2023]
Abstract
The present work shows the spatial reliability of the diffuse optical tomography (DOT) system in a group of healthy subjects during a motor imagery task. Prior to imagery task performance, the subjects executed a motor task based on the finger to thumb opposition for motor training, and to corroborate the DOT spatial localization during the motor execution. DOT technology and data treatment allows us to distinguish oxy- and deoxyhemoglobin at the cerebral gyri level unlike the cerebral activations provided by fMRI series that were processed using different approaches. Here we show the DOT reliability showing functional activations at the cerebral gyri level during motor execution and motor imagery, which provide subtler cerebral activations than the motor execution. These results will allow the use of the DOT system as a monitoring device in a brain computer interface.
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Affiliation(s)
- Estefania Hernandez-Martin
- Department of Basic Medical Science (Physiology), Faculty of Health Sciences, Medicine Section, Universidad de La Laguna 38071, Spain
| | - Francisco Marcano
- Department of Basic Medical Science (Physiology), Faculty of Health Sciences, Medicine Section, Universidad de La Laguna 38071, Spain
- Instituto de Tecnologías Biomédicas, Universidad de la Laguna, Spain
- Instituto de Neurociencias, Universidad de la Laguna, Spain
| | - Cristian Modroño
- Department of Basic Medical Science (Physiology), Faculty of Health Sciences, Medicine Section, Universidad de La Laguna 38071, Spain
- Instituto de Tecnologías Biomédicas, Universidad de la Laguna, Spain
- Instituto de Neurociencias, Universidad de la Laguna, Spain
| | - Niels Janssen
- Instituto de Tecnologías Biomédicas, Universidad de la Laguna, Spain
- Instituto de Neurociencias, Universidad de la Laguna, Spain
- Psychology Department, Universidad de La Laguna 38071, Spain
| | - Jose Luis González-Mora
- Department of Basic Medical Science (Physiology), Faculty of Health Sciences, Medicine Section, Universidad de La Laguna 38071, Spain
- Instituto de Tecnologías Biomédicas, Universidad de la Laguna, Spain
- Instituto de Neurociencias, Universidad de la Laguna, Spain
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30
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Butler LK, Kiran S, Tager-Flusberg H. Functional Near-Infrared Spectroscopy in the Study of Speech and Language Impairment Across the Life Span: A Systematic Review. AMERICAN JOURNAL OF SPEECH-LANGUAGE PATHOLOGY 2020; 29:1674-1701. [PMID: 32640168 PMCID: PMC7893520 DOI: 10.1044/2020_ajslp-19-00050] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Purpose Functional brain imaging is playing an increasingly important role in the diagnosis and treatment of communication disorders, yet many populations and settings are incompatible with functional magnetic resonance imaging and other commonly used techniques. We conducted a systematic review of neuroimaging studies using functional near-infrared spectroscopy (fNIRS) with individuals with speech or language impairment across the life span. We aimed to answer the following question: To what extent has fNIRS been used to investigate the neural correlates of speech-language impairment? Method This systematic review was preregistered with PROSPERO, the international prospective register of systematic reviews (CRD42019136464). We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol for preferred reporting items for systematic reviews. The database searches were conducted between February and March of 2019 with the following search terms: (a) fNIRS or functional near-infrared spectroscopy or NIRS or near-infrared spectroscopy, (b) speech or language, and (c) disorder or impairment or delay. Results We found 34 fNIRS studies that involved individuals with speech or language impairment across nine categories: (a) autism spectrum disorders; (b) developmental speech and language disorders; (c) cochlear implantation and deafness; (d) dementia, dementia of the Alzheimer's type, and mild cognitive impairment; (e) locked-in syndrome; (f) neurologic speech disorders/dysarthria; (g) stroke/aphasia; (h) stuttering; and (i) traumatic brain injury. Conclusions Though it is not without inherent challenges, fNIRS may have advantages over other neuroimaging techniques in the areas of speech and language impairment. fNIRS has clinical applications that may lead to improved early and differential diagnosis, increase our understanding of response to treatment, improve neuroprosthetic functioning, and advance neurofeedback.
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Affiliation(s)
- Lindsay K. Butler
- Sargent College of Health and Rehabilitation Sciences, Boston University, MA
| | - Swathi Kiran
- Sargent College of Health and Rehabilitation Sciences, Boston University, MA
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31
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Chen WL, Wagner J, Heugel N, Sugar J, Lee YW, Conant L, Malloy M, Heffernan J, Quirk B, Zinos A, Beardsley SA, Prost R, Whelan HT. Functional Near-Infrared Spectroscopy and Its Clinical Application in the Field of Neuroscience: Advances and Future Directions. Front Neurosci 2020; 14:724. [PMID: 32742257 PMCID: PMC7364176 DOI: 10.3389/fnins.2020.00724] [Citation(s) in RCA: 132] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Accepted: 06/17/2020] [Indexed: 01/20/2023] Open
Abstract
Similar to functional magnetic resonance imaging (fMRI), functional near-infrared spectroscopy (fNIRS) detects the changes of hemoglobin species inside the brain, but via differences in optical absorption. Within the near-infrared spectrum, light can penetrate biological tissues and be absorbed by chromophores, such as oxyhemoglobin and deoxyhemoglobin. What makes fNIRS more advantageous is its portability and potential for long-term monitoring. This paper reviews the basic mechanisms of fNIRS and its current clinical applications, the limitations toward more widespread clinical usage of fNIRS, and current efforts to improve the temporal and spatial resolution of fNIRS toward robust clinical usage within subjects. Oligochannel fNIRS is adequate for estimating global cerebral function and it has become an important tool in the critical care setting for evaluating cerebral oxygenation and autoregulation in patients with stroke and traumatic brain injury. When it comes to a more sophisticated utilization, spatial and temporal resolution becomes critical. Multichannel NIRS has improved the spatial resolution of fNIRS for brain mapping in certain task modalities, such as language mapping. However, averaging and group analysis are currently required, limiting its clinical use for monitoring and real-time event detection in individual subjects. Advances in signal processing have moved fNIRS toward individual clinical use for detecting certain types of seizures, assessing autonomic function and cortical spreading depression. However, its lack of accuracy and precision has been the major obstacle toward more sophisticated clinical use of fNIRS. The use of high-density whole head optode arrays, precise sensor locations relative to the head, anatomical co-registration, short-distance channels, and multi-dimensional signal processing can be combined to improve the sensitivity of fNIRS and increase its use as a wide-spread clinical tool for the robust assessment of brain function.
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Affiliation(s)
- Wei-Liang Chen
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States.,Department of Neurology, Children's Hospital of Wisconsin, Milwaukee, WI, United States.,School of Medicine, University of Washington, Seattle, WA, United States
| | - Julie Wagner
- Department of Biochemical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, United States
| | - Nicholas Heugel
- Department of Biochemical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, United States
| | - Jeffrey Sugar
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Yu-Wen Lee
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States.,Department of Neurology, Children's Hospital of Wisconsin, Milwaukee, WI, United States
| | - Lisa Conant
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Marsha Malloy
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States.,Department of Neurology, Children's Hospital of Wisconsin, Milwaukee, WI, United States
| | - Joseph Heffernan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Brendan Quirk
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Anthony Zinos
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States.,Department of Biochemical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, United States
| | - Scott A Beardsley
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States.,Department of Biochemical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, United States
| | - Robert Prost
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Harry T Whelan
- Department of Neurology, Medical College of Wisconsin, Milwaukee, WI, United States.,Department of Neurology, Children's Hospital of Wisconsin, Milwaukee, WI, United States
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32
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Yang CL, Lim SB, Peters S, Eng JJ. Cortical Activation During Shoulder and Finger Movements in Healthy Adults: A Functional Near-Infrared Spectroscopy (fNIRS) Study. Front Hum Neurosci 2020; 14:260. [PMID: 32733221 PMCID: PMC7362764 DOI: 10.3389/fnhum.2020.00260] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Accepted: 06/12/2020] [Indexed: 02/03/2023] Open
Abstract
Characterization of cortical activation patterns during movement of the upper extremity in healthy adults is helpful in understanding recovery mechanisms following neurological disorders. This study explores cortical activation patterns associated with movements of the shoulder and fingers in healthy adults using functional near-infrared spectroscopy (fNIRS). Twelve healthy right-handed participants were recruited. Two motor tasks (shoulder abduction and finger extension) with two different trial lengths (10 s and 20 s) were performed in a sitting position at a rate of 0.5 Hz. The hemodynamic response, as indicated by oxy-hemoglobin (HbO) and deoxy-hemoglobin (HbR), over both hemispheres was acquired using a 54-channel fNIRS system. We found a generalized bilateral cortical activation during both motor tasks with greater activation in the contralateral compared to the ipsilateral primary motor cortex. Particularly in the more medial part of the contralateral hemisphere, significant higher activation was found during the shoulder compared to finger movements. Furthermore, cortical activation patterns are affected not only by motor tasks but also by trial lengths. HbO is more sensitive to detect cortical activation during finger movements in longer trials, while HbR is a better surrogate to capture active areas during shoulder movement in shorter trials. Based on these findings, reporting both HbO and HbR is strongly recommended for future fNIRS studies, and trial lengths should be taken into account when designing experiments and explaining results. Our findings demonstrating distinct cortical activation patterns associated with shoulder and finger movements in healthy adults provide a foundation for future research to study recovery mechanisms following neurological disorders.
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Affiliation(s)
- Chieh-Ling Yang
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,Rehabilitation Research Program, GF Strong Rehabilitation Centre, Vancouver, BC, Canada
| | - Shannon B Lim
- Rehabilitation Research Program, GF Strong Rehabilitation Centre, Vancouver, BC, Canada.,Graduate Programs in Rehabilitation Sciences, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Sue Peters
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,Rehabilitation Research Program, GF Strong Rehabilitation Centre, Vancouver, BC, Canada
| | - Janice J Eng
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.,Rehabilitation Research Program, GF Strong Rehabilitation Centre, Vancouver, BC, Canada
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33
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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: 41] [Impact Index Per Article: 10.3] [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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34
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Zarei M, Ansari MA, Zare K. The Temporal Confounding Effects of Extra-cerebral Contamination Factors on the Hemodynamic Signal Measured by Functional Near-Infrared Spectroscopy. J Lasers Med Sci 2020; 10:S73-S81. [PMID: 32021678 DOI: 10.15171/jlms.2019.s14] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Introduction: Functional near-infrared spectroscopy (fNIRS) has been broadly applied for optical brain imaging. This method is hemodynamic-based functional brain imaging relying on the measurement of the neurovascular coupling to detect changes in cerebral neuronal activities. The extra-cerebral hemodynamic changes are important contaminating factors in fNIRS measurements. This error signal can be misinterpreted as cerebral activities during fNIRS studies. Recently, it was assumed that temporal changes in deoxygenated hemoglobin concentration [HHb] was hardly affected by superficial blood flow, and it was proposed that the activation maps could be determined from [HHb] at large source-detector separation. Methods: In the current study, we measured the temporal changes in [HHb] using a continueswave fNIRS device at large source-detector separation, while superficial blood flow was stimulated by infrared lasers. A mesh-based Monte Carlo code was applied to estimate fNIRS sensitivity to superficial hemodynamic changes in a realistic 3D MRI-based brain phantom. Results: First, we simulated photon migration in a four-layered human-head slab model to calculate PPLs and fNIRS sensitivity. Then, the localization of the infrared laser inside a realistic brain model was studied using the Monte Carlo method. Finally, the changes in [HHb] over the prefrontal cortex of six adult males were measured by fNIRS at a source-detector separation of 3 cm. The results demonstrated that the relation between fNIRS sensitivity and an increase in S-D separation was nonlinear and a correlation between shallow and deep signals was observed. Conclusion: The presented results demonstrated that the temporal changes in the superficial blood flow could strongly affect HHb measurement at large source-detector separation. Hence, the cerebral activity map extracted from the [HHb] signal was mainly contaminated by superficial blood flow.
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Affiliation(s)
- Mehrdad Zarei
- Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, Iran
| | - Mohammad Ali Ansari
- Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, Iran
| | - Kourosh Zare
- Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, Iran
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35
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Li R, Zhao C, Wang C, Wang J, Zhang Y. Enhancing fNIRS Analysis Using EEG Rhythmic Signatures: An EEG-Informed fNIRS Analysis Study. IEEE Trans Biomed Eng 2020; 67:2789-2797. [PMID: 32031925 DOI: 10.1109/tbme.2020.2971679] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Neurovascular coupling represents the relationship between changes in neuronal activity and cerebral hemodynamics. Concurrent Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) recording and integration analysis has emerged as a promising multi-modal neuroimaging approach to study the neurovascular coupling as it provides complementary properties with regard to high temporal and moderate spatial resolution of brain activity. In this study we developed an EEG-informed-fNIRS analysis framework to investigate the neuro-correlate between neuronal activity and cerebral hemodynamics by identifying specific EEG rhythmic modulations which contribute to the improvement of the fNIRS-based general linear model (GLM) analysis. Specifically, frequency-specific regressors derived from EEG were used to construct design matrices to guide the GLM analysis of the fNIRS signals collected during a hand grasp task. Our results showed that the EEG-informed fNIRS GLM analysis, especially the alpha and beta band, revealed significantly higher sensitivity and specificity in localizing the task-evoked regions compared to the canonical boxcar model, demonstrating the strong correlations between hemodynamic response and EEG rhythmic modulations. Results also indicated that analysis based on the deoxygenated hemoglobin (HbR) signal slightly outperformed the oxygenated hemoglobin (HbO)-based analysis. The findings in our study not only validate the feasibility of enhancing fNIRS GLM analysis using simultaneously recorded EEG signals, but also provide a new perspective to study the neurovascular coupling of brain activity.
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36
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Noah JA, Zhang X, Dravida S, Ono Y, Naples A, McPartland JC, Hirsch J. Real-Time Eye-to-Eye Contact Is Associated With Cross-Brain Neural Coupling in Angular Gyrus. Front Hum Neurosci 2020; 14:19. [PMID: 32116606 PMCID: PMC7016046 DOI: 10.3389/fnhum.2020.00019] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2019] [Accepted: 01/17/2020] [Indexed: 11/25/2022] Open
Abstract
Direct eye contact between two individuals is a salient social behavior known to initiate and promote interpersonal interaction. However, the neural processes that underlie these live interactive behaviors and eye-to-eye contact are not well understood. The Dynamic Neural Coupling Hypothesis presents a general theoretical framework proposing that shared interactive behaviors are represented by cross-brain signal coherence. Using functional near-infrared spectroscopy (fNIRS) adapted for hyper scanning, we tested this hypothesis specifically for neural mechanisms associated with eye-to-eye gaze between human participants compared to similar direct eye-gaze at a dynamic video of a face and predicted that the coherence of neural signals between the two participants during reciprocal eye-to-eye contact would be greater than coherence observed during direct eye-gaze at a dynamic video for those signals originating in social and face processing systems. Consistent with this prediction cross-brain coherence was increased for signals within the angular gyrus (AG) during eye-to-eye contact relative to direct eye-gaze at a dynamic face video (p < 0.01). Further, activity in the right temporal-parietal junction (TPJ) was increased in the real eye-to-eye condition (p < 0.05, FDR corrected). Together, these findings advance a functional and mechanistic understanding of the AG and cross-brain neural coupling associated with real-time eye-to-eye contact.
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Affiliation(s)
- J Adam Noah
- Brain Function Laboratory, Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Xian Zhang
- Brain Function Laboratory, Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States
| | - Swethasri Dravida
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT, United States
| | - Yumie Ono
- Department of Electronics and Bioinformatics, School of Science and Technology, Meiji University, Kawasaki, Japan
| | - Adam Naples
- Yale Child Study Center, Yale School of Medicine, New Haven, CT, United States
| | - James C McPartland
- Yale Child Study Center, Yale School of Medicine, New Haven, CT, United States
| | - Joy Hirsch
- Brain Function Laboratory, Department of Psychiatry, Yale School of Medicine, New Haven, CT, United States.,Department of Neuroscience, Yale School of Medicine, New Haven, CT, United States.,Department of Comparative Medicine, Yale School of Medicine, New Haven, CT, United States.,Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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Aihara T, Shimokawa T, Ogawa T, Okada Y, Ishikawa A, Inoue Y, Yamashita O. Resting-State Functional Connectivity Estimated With Hierarchical Bayesian Diffuse Optical Tomography. Front Neurosci 2020; 14:32. [PMID: 32082110 PMCID: PMC7005139 DOI: 10.3389/fnins.2020.00032] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Accepted: 01/13/2020] [Indexed: 12/15/2022] Open
Abstract
Resting-state functional connectivity (RSFC) has been generally assessed with functional magnetic resonance imaging (fMRI) thanks to its high spatial resolution. However, fMRI has several disadvantages such as high cost and low portability. In addition, fMRI may not be appropriate for people with metal or electronic implants in their bodies, with claustrophobia and who are pregnant. Diffuse optical tomography (DOT), a method of neuroimaging using functional near-infrared spectroscopy (fNIRS) to reconstruct three-dimensional brain activity images, offers a non-invasive alternative, because fNIRS as well as fMRI measures changes in deoxygenated hemoglobin concentrations and, in addition, fNIRS is free of above disadvantages. We recently proposed a hierarchical Bayesian (HB) DOT algorithm and verified its performance in terms of task-related brain responses. In this study, we attempted to evaluate the HB DOT in terms of estimating RSFC. In 20 healthy males (21-38 years old), 10 min of resting-state data was acquired with 3T MRI scanner or high-density NIRS on different days. The NIRS channels consisted of 96 long (29-mm) source-detector (SD) channels and 56 short (13-mm) SD channels, which covered bilateral frontal and parietal areas. There were one and two resting-state runs in the fMRI and fNIRS experiments, respectively. The reconstruction performances of our algorithm and the two currently prevailing algorithms for DOT were evaluated using fMRI signals as a reference. Compared with the currently prevailing algorithms, our HB algorithm showed better performances in both the similarity to fMRI data and inter-run reproducibility, in terms of estimating the RSFC.
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Affiliation(s)
- Takatsugu Aihara
- Graduate School of Human and Environmental Studies, Kyoto University, Kyoto, Japan
- Neural Information Analysis Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Takeaki Shimokawa
- Neural Information Analysis Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Takeshi Ogawa
- Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Yuto Okada
- Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan
| | - Akihiro Ishikawa
- Medical Systems Division, Research and Development Department, Shimadzu Corporation, Kyoto, Japan
| | - Yoshihiro Inoue
- Medical Systems Division, Research and Development Department, Shimadzu Corporation, Kyoto, Japan
| | - Okito Yamashita
- Neural Information Analysis Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
- RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
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Song X, Chen X, Wang Z, An X, Ming D. MBLL with weighted partial path length for multi-distance probe configuration of fNIRS. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:4766-4769. [PMID: 31946927 DOI: 10.1109/embc.2019.8857684] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Functional near-infrared spectroscopy (fNIRS) has broad prospects in both clinical application and brain-computer interface. To improve the spatial resolution, modified Beer-Lambert law with weighted partial optical path length (wMBLL) is proposed for multi-distance probe configuration. Taking both surface tissue layers and deep tissue layers into consideration, the partial optical path length is estimated as a function of the distance between source and detector. Besides, a multi-distance, 15mm and 30mm, probe configuration is designed, which approximates a rectangle. Constructed with 9 sources and 14 detectors, 40 channels are produced, including 20 short short-separation channel and 20 long-separation channel. Also, experiment is implemented with left hand grip-stretch movement and involves five healthy subjects. The concentration of HbO is used to image the brain activation map. Results demonstrate that, compared with the conventional method, the proposed wMBLL method is effective to detect brain activity with higher spatial resolution.
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Helmich I, Coenen J, Henckert S, Pardalis E, Schupp S, Lausberg H. Reduced frontopolar brain activation characterizes concussed athletes with balance deficits. NEUROIMAGE-CLINICAL 2020; 25:102164. [PMID: 31954336 PMCID: PMC6965737 DOI: 10.1016/j.nicl.2020.102164] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Revised: 01/07/2020] [Accepted: 01/08/2020] [Indexed: 11/25/2022]
Abstract
Symptomatic athletes with balance deficits present reduced frontopolar oxygenation during postural control with closed eyes. Decreased brain oxygenation in the FPC of symptomatic individuals may characterize the deficit of shifting the focus from visual inputs towards proprioception.
Objectives Athletes with sport-related concussions (SRC) often demonstrate deficits in postural stability. Lower cerebral blood flow in frontal cortices has been documented in athletes with symptoms after SRC, however, it is unclear if functional brain oxygenation during postural control tasks is reduced in symptomatic athletes after SRC in the same manner. We therefore compared brain oxygenation patterns in frontal cortices of symptomatic and asymptomatic athletes with SRC during postural control tasks with the hypothesis that symptomatic athletes are characterized by reduced functional brain oxygenation during postural control. Methods 62 concussed athletes (n = 31 symptomatic, n = 31 asymptomatic) were investigated during four postural control tasks with eyes closed versus eyes opened conditions and stable vs. unstable surface conditions. Brain oxygenation was assessed using functional NearInfraRed Spectroscopy (fNIRS) on frontopolar cortices of each hemisphere. Postural sway was measured by the analysis of ground reaction forces. Results Symptomatic athletes showed greater postural sway when compared to asymptomatic athletes during postural control, particularly during closed eyes and/or unstable surface conditions. Changes of oxygenated hemoglobin (∆HbO2) within the left hemispheric frontopolar cortex were significantly reduced in symptomatic athletes when compared to asymptomatic athletes during the eyes closed condition. A stepwise linear regression analysis revealed that self-reported post-concussion symptoms such as headaches and sadness predict decreased brain oxygenation during postural control with closed eyes. Conclusion Symptomatic athletes with increased postural sway are characterized by decreased frontopolar brain oxygenation during postural control tasks, particularly during conditions with closed eyes. Because the frontopolar cortex showed to be involved in redistributing executive functions to novel task situations, we conclude that athletes with post-concussion symptoms suffer from a deficit in coordinating postural adjustments to balance control tasks with reduced sensory input.
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Affiliation(s)
- I Helmich
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany.
| | - J Coenen
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany; Department of Sport and Health, Institute of Sport Medicine, Paderborn University, Warburger Str. 100, 33098 Paderborn, Germany
| | - S Henckert
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany
| | - E Pardalis
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany
| | - S Schupp
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany
| | - H Lausberg
- Department of Neurology, Psychosomatic Medicine and Psychiatry, Institute of Health Promotion and Clinical Movement Science, German Sport University (GSU) Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany
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Blaney G, Sassaroli A, Pham T, Fernandez C, Fantini S. Phase dual-slopes in frequency-domain near-infrared spectroscopy for enhanced sensitivity to brain tissue: First applications to human subjects. JOURNAL OF BIOPHOTONICS 2020; 13:e201960018. [PMID: 31479582 PMCID: PMC9219023 DOI: 10.1002/jbio.201960018] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 08/14/2019] [Accepted: 08/29/2019] [Indexed: 05/05/2023]
Abstract
We present a first in vivo application of phase dual-slopes (DSϕ), measured with frequency-domain near-infrared spectroscopy on four healthy human subjects, to demonstrate their enhanced sensitivity to cerebral hemodynamics. During arterial blood pressure oscillations elicited at a frequency of 0.1 Hz, we compare three different ways to analyze either intensity (I) or phase (ϕ) data collected on the subject's forehead at multiple source-detector distances: Single-distance, single-slope and DS. Theoretical calculations based on diffusion theory show that the method with the deepest maximal sensitivity (at about 11 mm) is DSϕ. The in vivo results indicate a qualitative difference of phase data (especially DSϕ) and intensity data (especially single-distance intensity [SDI]), which we assign to stronger contributions from scalp hemodynamics to SDI and from cortical hemodynamics to DSϕ. Our findings suggest that scalp hemodynamic oscillations may be dominated by blood volume dynamics, whereas cortical hemodynamics may be dominated by blood flow velocity dynamics.
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Affiliation(s)
- Giles Blaney
- Correspondence: 4 Colby Street, Medford, MA USA 02155,
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Fantini S, Blaney G, Sassaroli A. Transformational change in the field of diffuse optics: From going bananas to going nuts. JOURNAL OF INNOVATIVE OPTICAL HEALTH SCIENCES 2020; 13:1930013. [PMID: 36340430 PMCID: PMC9632641 DOI: 10.1142/s1793545819300131] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
The concept of region of sensitivity is central to the field of diffuse optics and is closely related to the Jacobian matrix used to solve the inverse problem in imaging. It is well-known that, in diffuse reflectance, the region of sensitivity associated with a given source-detector pair is shaped as a banana, and features maximal sensitivity to the portions of the sample that are closest to the source and the detector. We have recently introduced a dual-slope method based on a special arrangement of two sources and two detectors, which results in deeper and more localized regions of sensitivity, resembling the shapes of different kinds of nuts. Here, we report the regions of sensitivity associated with a variety of source-detector arrangements for dual-slope measurements of intensity and phase with frequency-domain spectroscopy (modulation frequency: 140 MHz) in a medium with absorption and reduced scattering coefficients of 0.1 cm-1 and 12 cm-1, respectively. The main result is that the depth of maximum sensitivity, considering only cases that use source-detector separations of 25 and 35 mm, progressively increases as we consider single-distance intensity (2.0 mm), dual-slope intensity (4.6 mm), single-distance phase (7.5 mm), and dual-slope phase (10.9 mm). These results indicate the importance of dual-slope measurements, and even more so of phase measurements, when it is desirable to selectively probe deeper portions of a sample with diffuse optics. This is certainly the case in non-invasive optical studies of brain, muscle, and breast tissue, which are located underneath superficial tissue at variable depths.
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Affiliation(s)
- Sergio Fantini
- Department of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA
| | - Giles Blaney
- Department of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA
| | - Angelo Sassaroli
- Department of Biomedical Engineering, Tufts University, 4 Colby Street, Medford, MA 02155, USA
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Open-Access fNIRS Dataset for Classification of Unilateral Finger- and Foot-Tapping. ELECTRONICS 2019. [DOI: 10.3390/electronics8121486] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Numerous open-access electroencephalography (EEG) datasets have been released and widely employed by EEG researchers. However, not many functional near-infrared spectroscopy (fNIRS) datasets are publicly available. More fNIRS datasets need to be freely accessible in order to facilitate fNIRS studies. Toward this end, we introduce an open-access fNIRS dataset for three-class classification. The concentration changes of oxygenated and reduced hemoglobin were measured, while 30 volunteers repeated each of the three types of overt movements (i.e., left- and right-hand unilateral complex finger-tapping, foot-tapping) for 25 times. The ternary support vector machine (SVM) classification accuracy obtained using leave-one-out cross-validation was estimated at 70.4% ± 18.4% on average. A total of 21 out of 30 volunteers scored a superior binary SVM classification accuracy (left-hand vs. right-hand finger-tapping) of over 80.0%. We believe that the introduced fNIRS dataset can facilitate future fNIRS studies.
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Almajidy RK, Mankodiya K, Abtahi M, Hofmann UG. A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments. IEEE Rev Biomed Eng 2019; 13:292-308. [PMID: 31634142 DOI: 10.1109/rbme.2019.2944351] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs.
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Sawosz P, Liebert A. Method to improve the depth sensitivity of diffuse reflectance measurements to absorption changes in optically turbid medium. BIOMEDICAL OPTICS EXPRESS 2019; 10:5031-5041. [PMID: 31646028 PMCID: PMC6788621 DOI: 10.1364/boe.10.005031] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Revised: 08/30/2019] [Accepted: 08/30/2019] [Indexed: 05/24/2023]
Abstract
We have studied the spatial distributions of the sensitivity of time-resolved near-infrared diffuse reflectance measurement. Sensitivity factors representing a change of parameters of a measured optical signal induced by absorption perturbation in a certain voxel of the medium were simulated using the diffusion equation solution. The parameters were statistical moments of measured distributions of time of flight of photons (DTOFs) i.e., the total number of photons, mean time of flight and variance. The distributions of the sensitivity of statistical moments of DTOFs to a change in absorption were generated for various source-detector separations and various optical properties of the medium. Furthermore, differential sensitivity distributions for two different source-detector separations were calculated. A measurement geometry, in which two detection spots, separated by 5 mm, in combination with two sources was proposed. For this setup differences between the signals obtained for both detectors were calculated independently for both sources and afterward summed up for both source positions. Obtained differences in moments of DTOFs assessed at two source-detector separations and summed up for different positioning of the sources allowed to shape up the sensitivity profiles. Calculated sensitivity profiles show that positive sensitivities of the mean time of flight of photons and variance of the DTOF can be obtained. These positive sensitivity areas are located just between both detection spots and cover the compartment located deeply in the medium. The sensitivity in superficial compartments of the medium is negative and much smaller in amplitude. The proposed technique can be used for improved discrimination of optical signals related to the intracerebral change in absorption which remains a serious obstacle in the application of the NIRS technique in the assessment of brain oxygenation or perfusion.
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Affiliation(s)
- Piotr Sawosz
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Trojdena 4, 02-109 Warsaw, Poland
| | - Adam Liebert
- Nalecz Institute of Biocybernetics and Biomedical Engineering, Trojdena 4, 02-109 Warsaw, Poland
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Veesa JD, Dehghani H. Functional near infrared spectroscopy using spatially resolved data to account for tissue scattering: A numerical study and arm-cuff experiment. JOURNAL OF BIOPHOTONICS 2019; 12:e201900064. [PMID: 31169976 PMCID: PMC7065609 DOI: 10.1002/jbio.201900064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 06/03/2019] [Accepted: 06/04/2019] [Indexed: 05/12/2023]
Abstract
Functional Near-Infrared Spectroscopy (fNIRS) aims to recover changes in tissue optical parameters relating to tissue hemodynamics, to infer functional information in biological tissue. A widely-used application of fNIRS relies on continuous wave (CW) methodology that utilizes multiple distance measurements on human head for study of brain health. The typical method used is spatially resolved spectroscopy (SRS), which is shown to recover tissue oxygenation index (TOI) based on gradient of light intensity measured between two detectors. However, this methodology does not account for tissue scattering which is often assumed. A new parameter recovery algorithm is developed, which directly recovers both the scattering parameter and scaled chromophore concentrations and hence TOI from the measured gradient of light-attenuation at multiple wavelengths. It is shown through simulations that in comparison to conventional SRS which estimates cerebral TOI values with an error of ±12.3%, the proposed method provides more accurate estimate of TOI exhibiting an error of ±5.7% without any prior assumptions of tissue scatter, and can be easily implemented within CW fNIRS systems. Using an arm-cuff experiment, the obtained TOI using the proposed method is shown to provide a higher and more realistic value as compared to utilizing any prior assumptions of tissue scatter.
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Affiliation(s)
- Joshua D. Veesa
- School of Computer ScienceUniversity of BirminghamBirminghamUK
| | - Hamid Dehghani
- School of Computer ScienceUniversity of BirminghamBirminghamUK
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Schumacher FK, Steinborn C, Weiller C, Schelter BO, Reinhard M, Kaller CP. The impact of physiological noise on hemodynamic-derived estimates of directed functional connectivity. Brain Struct Funct 2019; 224:3145-3157. [DOI: 10.1007/s00429-019-01954-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2019] [Accepted: 08/31/2019] [Indexed: 11/29/2022]
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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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48
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Nemani A, Kruger U, Cooper CA, Schwaitzberg SD, Intes X, De S. Objective assessment of surgical skill transfer using non-invasive brain imaging. Surg Endosc 2019; 33:2485-2494. [PMID: 30334166 PMCID: PMC10756643 DOI: 10.1007/s00464-018-6535-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2018] [Accepted: 10/12/2018] [Indexed: 12/16/2022]
Abstract
BACKGROUND Physical and virtual surgical simulators are increasingly being used in training technical surgical skills. However, metrics such as completion time or subjective performance checklists often show poor correlation to transfer of skills into clinical settings. We hypothesize that non-invasive brain imaging can objectively differentiate and classify surgical skill transfer, with higher accuracy than established metrics, for subjects based on motor skill levels. STUDY DESIGN 18 medical students at University at Buffalo were randomly assigned into control, physical surgical trainer, or virtual trainer groups. Training groups practiced a surgical technical task on respective simulators for 12 consecutive days. To measure skill transfer post-training, all subjects performed the technical task in an ex-vivo environment. Cortical activation was measured using functional near-infrared spectroscopy (fNIRS) in the prefrontal cortex, primary motor cortex, and supplementary motor area, due to their direct impact on motor skill learning. RESULTS Classification between simulator trained and untrained subjects based on traditional metrics is poor, where misclassification errors range from 20 to 41%. Conversely, fNIRS metrics can successfully classify physical or virtual trained subjects from untrained subjects with misclassification errors of 2.2% and 8.9%, respectively. More importantly, untrained subjects are successfully classified from physical or virtual simulator trained subjects with misclassification errors of 2.7% and 9.1%, respectively. CONCLUSION fNIRS metrics are significantly more accurate than current established metrics in classifying different levels of surgical motor skill transfer. Our approach brings robustness, objectivity, and accuracy in validating the effectiveness of future surgical trainers in translating surgical skills to clinically relevant environments.
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Affiliation(s)
- Arun Nemani
- Rensselaer Polytechnic Institute, 110, 8th Street, Troy, NY, 12180, USA
| | - Uwe Kruger
- Rensselaer Polytechnic Institute, 110, 8th Street, Troy, NY, 12180, USA
| | - Clairice A Cooper
- University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY, 14228, USA
| | - Steven D Schwaitzberg
- University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY, 14228, USA
| | - Xavier Intes
- Rensselaer Polytechnic Institute, 110, 8th Street, Troy, NY, 12180, USA
| | - Suvranu De
- Rensselaer Polytechnic Institute, 110, 8th Street, Troy, NY, 12180, USA.
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Downey D, Brigadoi S, Trevithick L, Elliott R, Elwell C, McAllister-Williams RH, Anderson IM. Frontal haemodynamic responses in depression and the effect of electroconvulsive therapy. J Psychopharmacol 2019; 33:1003-1014. [PMID: 31237182 PMCID: PMC6628632 DOI: 10.1177/0269881119858313] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Reduced frontal cortex metabolism and blood flow in depression may be associated with low mood and cognitive impairment. Further reduction has been reported during a course of electroconvulsive therapy but it is not known if this relates to mood and cognitive changes caused by electroconvulsive therapy. AIMS The purpose of this study was to investigate frontal function while undertaking cognitive tasks in depressed patients compared with healthy controls, and following electroconvulsive therapy in patients. METHODS We measured frontal haemodynamic responses to a category verbal fluency task and a working memory N-back task using portable functional near infra-red spectroscopy (fNIRS) in 51 healthy controls and 18 severely depressed patients, 12 of whom were retested after the fourth treatment of a course of electroconvulsive therapy. Mood was assessed using the Montgomery Åsberg Depression Rating Scale and cognitive function using category Verbal Fluency from the Controlled Oral Word Association Test and Digit Span backwards. RESULTS Compared to healthy controls, depressed patients had bilaterally lower frontal oxyhaemoglobin responses to the cognitive tasks, although this was only significant for the N-Back task where performance correlated inversely with depression severity in patients. After four electroconvulsive therapy treatments oxyhaemoglobin responses were further reduced during the Verbal Fluency task but the changes did not correlate with mood or cognitive changes. DISCUSSION Our results confirmed a now extensive literature showing impaired frontal fNIRS oxyhaemoglobin responses to cognitive tasks in depression, and showed for the first time that these are further reduced during a course of electroconvulsive therapy. Further research is needed to investigate the biology and clinical utility of frontal fNIRS in psychiatric patients.
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Affiliation(s)
- Darragh Downey
- Faculty of Biology, Medicine and Health,
The University of Manchester, Manchester, UK
| | - Sabrina Brigadoi
- Biomedical Optics Research Laboratory,
University College London, London, UK,Department of Developmental and Social
Psychology, University of Padova, Padova, Italy
| | - Liam Trevithick
- School of Psychology, Newcastle
University, Newcastle upon Tyne, UK,Northumberland Tyne and Wear NHS
Foundation Trust, Newcastle upon Tyne, UK
| | - Rebecca Elliott
- Neuroscience and Psychiatry Unit, The
University of Manchester, Manchester, UK
| | - Clare Elwell
- Biomedical Optics Research Laboratory,
University College London, London, UK
| | - R Hamish McAllister-Williams
- School of Psychology, Newcastle
University, Newcastle upon Tyne, UK,Neuroscience and Psychiatry Unit, The
University of Manchester, Manchester, UK
| | - Ian M Anderson
- Institute of Neuroscience, Newcastle
University, Newcastle upon Tyne, UK,Ian M Anderson, Neuroscience and Psychiatry
Unit, The University of Manchester and Manchester Academic Health Science
Centre, Room G809, Stopford Building, Oxford Road, Manchester, M13 9PT, UK.
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50
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Blaney G, Sassaroli A, Pham T, Krishnamurthy N, Fantini S. Multi-distance frequency-domain optical measurements of coherent cerebral hemodynamics. PHOTONICS 2019; 6:83. [PMID: 34079837 PMCID: PMC8168742 DOI: 10.3390/photonics6030083] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
We report non-invasive, bilateral optical measurements on the forehead of five healthy human subjects, of 0.1 Hz oscillatory hemodynamics elicited either by cyclic inflation of pneumatic thigh cuffs, or by paced breathing. Optical intensity and the phase of photon-density waves were collected with frequency-domain near-infrared spectroscopy at seven source-detector distances (11-40 mm). Coherent hemodynamic oscillations are represented by phasors of oxyhemoglobin (O) and deoxyhemoglobin (D) concentrations, and by the vector D/O that represents the amplitude ratio and phase difference of D and O. We found that, on average, the amplitude ratio (|D/O|) and the phase difference (∠(D/O)) obtained with single-distance intensity at 11-40 mm increase from 0.1 and -330°, to 0.2 and -200°, respectively. Single-distance phase and the intensity slope featured a weaker dependence on source-detector separation, and yielded |D/O| and ∠(D/O) values of about 0.5 and -200°, respectively, at distances greater than 20 mm. The key findings are: (1) single-distance phase and intensity slope are sensitive to deeper tissue compared to single-distance intensity; (2) deeper tissue hemodynamic oscillations, which more closely represent the brain, feature D and O phasors that are consistent with a greater relative flow-to-volume contributions in brain tissue compared to extracerebral, superficial tissue.
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Affiliation(s)
- Giles Blaney
- Tufts University, Department of Biomedical Engineering
| | | | - Thao Pham
- Tufts University, Department of Biomedical Engineering
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