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Kang KYL, Rosenkranz R, Altinsoy ME, Li SC. Cortical processes of multisensory plausibility modulation of vibrotactile perception in virtual environments in middled-aged and older adults. Sci Rep 2024; 14:13366. [PMID: 38862559 PMCID: PMC11166973 DOI: 10.1038/s41598-024-64054-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 06/04/2024] [Indexed: 06/13/2024] Open
Abstract
Digital technologies, such as virtual or augmented reality, can potentially support neurocognitive functions of the aging populations worldwide and complement existing intervention methods. However, aging-related declines in the frontal-parietal network and dopaminergic modulation which progress gradually across the later periods of the adult lifespan may affect the processing of multisensory congruence and expectancy based contextual plausibility. We assessed hemodynamic brain responses while middle-aged and old adults experienced car-riding virtual-reality scenarios where the plausibility of vibrotactile stimulations was manipulated by delivering stimulus intensities that were either congruent or incongruent with the digitalized audio-visual contexts of the respective scenarios. Relative to previous findings observed in young adults, although highly plausible vibrotactile stimulations confirming with contextual expectations also elicited higher brain hemodynamic responses in middle-aged and old adults, this effect was limited to virtual scenarios with extreme expectancy violations. Moreover, individual differences in plausibility-related frontal activity did not correlate with plausibility violation costs in the sensorimotor cortex, indicating less systematic frontal context-based sensory filtering in older ages. These findings have practical implications for advancing digital technologies to support aging societies.
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Affiliation(s)
- Kathleen Y L Kang
- Centre for Tactile Internet with Human-in-the-Loop (CeTI), Technische Universität Dresden, Dresden, Germany.
- Faculty of Psychology, Technische Universität Dresden, Zellerscher Weg 17 Room A232/233, 01069, Dresden, Germany.
- School of Psychology and Vision Sciences, University of Leicester, Leicester, UK.
| | - Robert Rosenkranz
- Centre for Tactile Internet with Human-in-the-Loop (CeTI), Technische Universität Dresden, Dresden, Germany
- Faculty of Electrical and Computer Engineering, Technische Universität Dresden, Dresden, Germany
| | - Mehmet Ercan Altinsoy
- Centre for Tactile Internet with Human-in-the-Loop (CeTI), Technische Universität Dresden, Dresden, Germany
- Faculty of Electrical and Computer Engineering, Technische Universität Dresden, Dresden, Germany
| | - Shu-Chen Li
- Centre for Tactile Internet with Human-in-the-Loop (CeTI), Technische Universität Dresden, Dresden, Germany.
- Faculty of Psychology, Technische Universität Dresden, Zellerscher Weg 17 Room A232/233, 01069, Dresden, Germany.
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2
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Zadeh AK, Sadeghbeigi N, Safakheil H, Setarehdan SK, Alibiglou L. Connecting the dots: Sensory cueing enhances functional connectivity between pre-motor and supplementary motor areas in Parkinson's disease. Eur J Neurosci 2024. [PMID: 38858176 DOI: 10.1111/ejn.16437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 05/10/2024] [Accepted: 05/26/2024] [Indexed: 06/12/2024]
Abstract
People with Parkinson's disease often exhibit improvements in motor tasks when exposed to external sensory cues. While the effects of different types of sensory cues on motor functions in Parkinson's disease have been widely studied, the underlying neural mechanism of these effects and the potential of sensory cues to alter the motor cortical activity patterns and functional connectivity of cortical motor areas are still unclear. This study aims to compare changes in oxygenated haemoglobin, deoxygenated haemoglobin and correlations among different cortical regions of interest during wrist movement under different external stimulus conditions between people with Parkinson's disease and controls. Ten Parkinson's disease patients and 10 age- and sex-matched neurologically healthy individuals participated, performing repetitive wrist flexion and extension tasks under auditory and visual cues. Changes in oxygenated and deoxygenated haemoglobin in motor areas were measured using functional near-infrared spectroscopy, along with electromyograms from wrist muscles and wrist movement kinematics. The functional near-infrared spectroscopy data revealed significantly higher neural activity changes in the Parkinson's disease group's pre-motor area compared to controls (p = 0.006), and functional connectivity between the supplementary motor area and pre-motor area was also significantly higher in the Parkinson's disease group when external sensory cues were present (p = 0.016). These results indicate that external sensory cues' beneficial effects on motor tasks are linked to changes in the functional connectivity between motor areas responsible for planning and preparation of movements.
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Affiliation(s)
- Ali K Zadeh
- Department of Clinical Neurosciences, Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
- School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | | | - Hosein Safakheil
- Department of Neuroscience, School of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Seyed Kamaledin Setarehdan
- School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Laila Alibiglou
- Department of Physical Therapy, School of Health and Human Sciences, Indiana University, Indianapolis, Indiana, USA
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3
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Caulier-Cisterna R, Appelgren-Gonzáles JP, Oyarzún JE, Valenzuela F, Sitaram R, Eblen-Zajjur A, Uribe S. Comparison of LED- and LASER-based fNIRS technologies to record the human peri‑spinal cord neurovascular response. Med Eng Phys 2024; 127:104170. [PMID: 38692767 DOI: 10.1016/j.medengphy.2024.104170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 03/13/2024] [Accepted: 04/11/2024] [Indexed: 05/03/2024]
Abstract
Recently, functional Near-Infrared Spectroscopy (fNIRS) was applied to obtain, non-invasively, the human peri‑spinal Neuro-Vascular Response (NVR) under a non-noxious electrical stimulation of a peripheral nerve. This method allowed the measurements of changes in the concentration of oxyhemoglobin (O2Hb) and deoxyhemoglobin (HHb) from the peri‑spinal vascular network. However, there is a lack of clarity about the potential differences in perispinal NVR recorded by the different fNIRS technologies currently available. In this work, the two main noninvasive fNIRS technologies were compared, i.e., LED and LASER-based. The recording of the human peri‑spinal NVR induced by non-noxious electrical stimulation of a peripheral nerve was recorded simultaneously at C7 and T10 vertebral levels. The amplitude, rise time, and full width at half maximum duration of the perispinal NVRs were characterized in healthy volunteers and compared between both systems. The main difference was that the LED-based system shows about one order of magnitude higher values of amplitude than the LASER-based system. No statistical differences were found for rise time and for duration parameters (at thoracic level). The comparison of point-to-point wave patterns did not show significant differences between both systems. In conclusion, the peri‑spinal NRV response obtained by different fNIRS technologies was reproducible, and only the amplitude showed differences, probably due to the power of the system which should be considered when assessing the human peri‑spinal vascular network.
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Affiliation(s)
- Raúl Caulier-Cisterna
- Department of Informatics and Computing, Faculty of Engineering, Universidad Tecnológica Metropolitana, Santiago, Chile.
| | - Juan-Pablo Appelgren-Gonzáles
- Center for Biomedical Imaging, the Radiology Department, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Juan-Esteban Oyarzún
- Center for Biomedical Imaging, the Radiology Department, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, iHEALTH, Santiago, Chile
| | - Felipe Valenzuela
- Center for Biomedical Imaging, the Radiology Department, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Ranganatha Sitaram
- Diagnostic Imaging Department, Multimodal Functional Brain Imaging and Neurorehabilitation Hub, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Antonio Eblen-Zajjur
- Translational Neuroscience Laboratory, Facultad de Medicina, Universidad Diego Portales, Santiago, Chile
| | - Sergio Uribe
- Department of Medical Imaging and Radiation Sciences, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University, Australia.
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Lu J, Zhang X, Shu Z, Han J, Yu N. A dynamic brain network decomposition method discovers effective brain hemodynamic sub-networks for Parkinson's disease. J Neural Eng 2024; 21:026047. [PMID: 38621377 DOI: 10.1088/1741-2552/ad3eb6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2024] [Accepted: 04/15/2024] [Indexed: 04/17/2024]
Abstract
Objective.Dopaminergic treatment is effective for Parkinson's disease (PD). Nevertheless, the conventional treatment assessment mainly focuses on human-administered behavior examination while the underlying functional improvements have not been well explored. This paper aims to investigate brain functional variations of PD patients after dopaminergic therapy.Approach.This paper proposed a dynamic brain network decomposition method and discovered brain hemodynamic sub-networks that well characterized the efficacy of dopaminergic treatment in PD. Firstly, a clinical walking procedure with functional near-infrared spectroscopy was developed, and brain activations during the procedure from fifty PD patients under the OFF and ON states (without and with dopaminergic medication) were captured. Then, dynamic brain networks were constructed with sliding-window analysis of phase lag index and integrated time-varying functional networks across all patients. Afterwards, an aggregated network decomposition algorithm was formulated based on aggregated effectiveness optimization of functional networks in spanning network topology and cross-validation network variations, and utilized to unveil effective brain hemodynamic sub-networks for PD patients. Further, dynamic sub-network features were constructed to characterize the brain flexibility and dynamics according to the temporal switching and activation variations of discovered sub-networks, and their correlations with differential treatment-induced gait alterations were analyzed.Results.The results demonstrated that PD patients exhibited significantly enhanced flexibility after dopaminergic therapy within a sub-network related to the improvement of motor functions. Other sub-networks were significantly correlated with trunk-related axial symptoms and exhibited no significant treatment-induced dynamic interactions.Significance.The proposed method promises a quantified and objective approach for dopaminergic treatment evaluation. Moreover, the findings suggest that the gait of PD patients comprises distinct motor domains, and the corresponding neural controls are selectively responsive to dopaminergic treatment.
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Affiliation(s)
- Jiewei Lu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Xinyuan Zhang
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Zhilin Shu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
| | - Jianda Han
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
- Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin, People's Republic of China
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen, People's Republic of China
| | - Ningbo Yu
- College of Artificial Intelligence, Nankai University, Tianjin, People's Republic of China
- Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin, People's Republic of China
- Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen, People's Republic of China
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Vera DA, García HA, Carbone NA, Waks-Serra MV, Iriarte DI, Pomarico JA. Retrieval of chromophore concentration changes in a digital human head model using analytical mean partial pathlengths of photons. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:025004. [PMID: 38419755 PMCID: PMC10901244 DOI: 10.1117/1.jbo.29.2.025004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 01/25/2024] [Accepted: 01/26/2024] [Indexed: 03/02/2024]
Abstract
Significance Continuous-wave functional near-infrared spectroscopy has proved to be a valuable tool for assessing hemodynamic activity in the human brain in a non-invasively and inexpensive way. However, most of the current processing/analysis methods assume the head is a homogeneous medium, and hence do not appropriately correct for the signal coming from the scalp. This effect can be reduced by considering light propagation in a layered model of the human head, being the Monte Carlo (MC) simulations the gold standard to this end. However, this implies large computation times and demanding hardware capabilities. Aim In this work, we study the feasibility of replacing the homogeneous model and the MC simulations by means of analytical multilayered models, combining in this way, the speed and simplicity of implementation of the former with the robustness and accuracy of the latter. Approach Oxy- and deoxyhemoglobin (HbO and HbR, respectively) concentration changes were proposed in two different layers of a magnetic resonance imaging (MRI)-based meshed model of the human head, and then these changes were retrieved by means of (i) a typical homogeneous reconstruction and (ii) a theoretical layered reconstruction. Results Results suggest that the use of analytical models of light propagation in layered models outperforms the results obtained using traditional homogeneous reconstruction algorithms, providing much more accurate results for both, the extra- and the cerebral tissues. We also compare the analytical layered reconstruction with MC-based reconstructions, achieving similar degrees of accuracy, especially in the gray matter layer, but much faster (between 4 and 5 orders of magnitude). Conclusions We have successfully developed, implemented, and validated a method for retrieving chromophore concentration changes in the human brain, combining the simplicity and speed of the traditional homogeneous reconstruction algorithms with robustness and accuracy much more similar to those provided by MC simulations.
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Reddy P, Izzetoglu K, Shewokis PA, Sangobowale M, Diaz-Arrastia R. Differences in time-frequency characteristics between healthy controls and TBI patients during hypercapnia assessed via fNIRS. Neuroimage Clin 2023; 40:103504. [PMID: 37734166 PMCID: PMC10518610 DOI: 10.1016/j.nicl.2023.103504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 07/24/2023] [Accepted: 09/01/2023] [Indexed: 09/23/2023]
Abstract
Damage to the cerebrovascular network is a universal feature of traumatic brain injury (TBI). This damage is present during different phases of the injury and can be non-invasively assessed using functional near infrared spectroscopy (fNIRS). fNIRS signals are influenced by partial arterial carbon dioxide (PaCO2), neurogenic, Mayer waves, respiratory and cardiac oscillations, whose characteristics vary in time and frequency and may differ in the presence of TBI. Therefore, this study aims to investigate differences in time-frequency characteristics of these fNIRS signal components between healthy controls and TBI patients and characterize the changes in their characteristics across phases of the injury. Data from 11 healthy controls and 21 TBI patients were collected during the hypercapnic protocol. Results demonstrated significant differences in low-frequency oscillations between healthy controls and TBI patients, with the largest differences observed in Mayer wave band (0.06 to 0.15 Hz), followed by the PaCO2 band (0.012 to 0.02 Hz). The effects within these bands were opposite, with (i) Mayer wave activity being lower in TBI patients during acute phase of the injury (d = 0.37 [0.16, 0.57]) and decreasing further during subacute (d = 0.66 [0.44, 0.87]) and postacute (d = 0.75 [0.50, 0.99]) phases; (ii) PaCO2 activity being lower in TBI patients only during acute phase of the injury (d = 0.36 [0.15, 0.56]) and stabilizing to healthy levels by the subacute phase. These findings demonstrate that TBI patients have impairments in low frequency oscillations related to different mechanisms and that these impairments evolve differently over the course of injury.
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Affiliation(s)
- Pratusha Reddy
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA.
| | - Kurtulus Izzetoglu
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA.
| | - Patricia A Shewokis
- School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA; Nutrition Sciences Department, Health Sciences Division of College of Nursing and Health Professions, Drexel University, Philadelphia, PA 19104, USA
| | - Michael Sangobowale
- Clinical TBI Research Center and Department of Neurology at University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Ramon Diaz-Arrastia
- Clinical TBI Research Center and Department of Neurology at University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
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Vera DA, García HA, Waks-Serra MV, Carbone NA, Iriarte DI, Pomarico JA. Reconstruction of light absorption changes in the human head using analytically computed photon partial pathlengths in layered media. JOURNAL OF THE OPTICAL SOCIETY OF AMERICA. A, OPTICS, IMAGE SCIENCE, AND VISION 2023; 40:C126-C137. [PMID: 37132982 DOI: 10.1364/josaa.482288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Functional near infrared spectroscopy has been used in recent decades to sense and quantify changes in hemoglobin concentrations in the human brain. This noninvasive technique can deliver useful information concerning brain cortex activation associated with different motor/cognitive tasks or external stimuli. This is usually accomplished by considering the human head as a homogeneous medium; however, this approach does not explicitly take into account the detailed layered structure of the head, and thus, extracerebral signals can mask those arising at the cortex level. This work improves this situation by considering layered models of the human head during reconstruction of the absorption changes in layered media. To this end, analytically calculated mean partial pathlengths of photons are used, which guarantees fast and simple implementation in real-time applications. Results obtained from synthetic data generated by Monte Carlo simulations in two- and four-layered turbid media suggest that a layered description of the human head greatly outperforms typical homogeneous reconstructions, with errors, in the first case, bounded up to ∼20% maximum, while in the second case, the error is usually larger than 75%. Experimental measurements on dynamic phantoms support this conclusion.
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8
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Huo C, Xu G, Sun A, Xie H, Hu X, Li W, Li Z, Fan Y. Cortical response induced by task-oriented training of the upper limb in subacute stroke patients as assessed by functional near-infrared spectroscopy. JOURNAL OF BIOPHOTONICS 2023; 16:e202200228. [PMID: 36222197 DOI: 10.1002/jbio.202200228] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 08/28/2022] [Accepted: 09/27/2022] [Indexed: 06/16/2023]
Abstract
Despite the popularity of task-oriented training for stroke, the cortical reorganization associated with this type of therapy remains to be fully elucidated due to the lack of dynamic assessment tools. A good tolerance for motion artifacts makes functional near-infrared spectroscopy (fNIRS) suitable for investigating task-induced cortical responses in stroke patients. Here, patients were randomly assigned to receive task oriented (n = 25) or cyclic rotary training (n = 25) with simultaneous cortical activation and effective connectivity network analysis between prefrontal and motor cortices (PFC/MC). Compared with cyclic rotary training, task-oriented training induced significantly increased activation in both hemispheres and enhanced influence of PFC on MC. In addition, significantly decreased activation lateralization and increased betweenness centrality of the contralesional MC suggested widespread involvement of the contralesional hemisphere during task-oriented training. This study verifies the feasibility of fNIRS combined with motor paradigms for assessing neural responses associated with stroke rehabilitation in real time.
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Affiliation(s)
- Congcong Huo
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Gongcheng Xu
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Aiping Sun
- Department of Neurological Rehabilitation, National Rehabilitation Hospital of National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Hui Xie
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Xiaoling Hu
- Department of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong, China
| | - Wenhao Li
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Zengyong Li
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
- Key Laboratory of Neuro-Functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Beijing, China
| | - Yubo Fan
- Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
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Congruence-based contextual plausibility modulates cortical activity during vibrotactile perception in virtual multisensory environments. Commun Biol 2022; 5:1360. [PMID: 36509971 PMCID: PMC9744907 DOI: 10.1038/s42003-022-04318-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 11/29/2022] [Indexed: 12/14/2022] Open
Abstract
How congruence cues and congruence-based expectations may together shape perception in virtual reality (VR) still need to be unravelled. We linked the concept of plausibility used in VR research with congruence-based modulation by assessing brain responses while participants experienced vehicle riding experiences in VR scenarios. Perceptual plausibility was manipulated by sensory congruence, with multisensory stimulations confirming with common expectations of road scenes being plausible. We hypothesized that plausible scenarios would elicit greater cortical responses. The results showed that: (i) vibrotactile stimulations at expected intensities, given embedded audio-visual information, engaged greater cortical activities in frontal and sensorimotor regions; (ii) weaker plausible stimulations resulted in greater responses in the sensorimotor cortex than stronger but implausible stimulations; (iii) frontal activities under plausible scenarios negatively correlated with plausibility violation costs in the sensorimotor cortex. These results potentially indicate frontal regulation of sensory processing and extend previous evidence of contextual modulation to the tactile sense.
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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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Chiovetto E, Salatiello A, d'Avella A, Giese MA. Toward a unifying framework for the modeling and identification of motor primitives. Front Comput Neurosci 2022; 16:926345. [PMID: 36172054 PMCID: PMC9510628 DOI: 10.3389/fncom.2022.926345] [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: 04/22/2022] [Accepted: 08/08/2022] [Indexed: 11/13/2022] Open
Abstract
A large body of evidence suggests that human and animal movements, despite their apparent complexity and flexibility, are remarkably structured. Quantitative analyses of various classes of motor behaviors consistently identify spatial and temporal features that are invariant across movements. Such invariant features have been observed at different levels of organization in the motor system, including the electromyographic, kinematic, and kinetic levels, and are thought to reflect fixed modules-named motor primitives-that the brain uses to simplify the construction of movement. However, motor primitives across space, time, and organization levels are often described with ad-hoc mathematical models that tend to be domain-specific. This, in turn, generates the need to use model-specific algorithms for the identification of both the motor primitives and additional model parameters. The lack of a comprehensive framework complicates the comparison and interpretation of the results obtained across different domains and studies. In this work, we take the first steps toward addressing these issues, by introducing a unifying framework for the modeling and identification of qualitatively different classes of motor primitives. Specifically, we show that a single model, the anechoic mixture model, subsumes many popular classes of motor primitive models. Moreover, we exploit the flexibility of the anechoic mixture model to develop a new class of identification algorithms based on the Fourier-based Anechoic Demixing Algorithm (FADA). We validate our framework by identifying eight qualitatively different classes of motor primitives from both simulated and experimental data. We show that, compared to established model-specific algorithms for the identification of motor primitives, our flexible framework reaches overall comparable and sometimes superior reconstruction performance. The identification framework is publicly released as a MATLAB toolbox (FADA-T, https://tinyurl.com/compsens) to facilitate the identification and comparison of different motor primitive models.
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Affiliation(s)
- Enrico Chiovetto
- Section for Computational Sensomotorics, Centre for Integrative Neuroscience, Hertie Institute for Clinical Brain Research, University Clinic Tübingen, Tübingen, Germany
| | - Alessandro Salatiello
- Section for Computational Sensomotorics, Centre for Integrative Neuroscience, Hertie Institute for Clinical Brain Research, University Clinic Tübingen, Tübingen, Germany
| | - Andrea d'Avella
- Laboratory of Neuromotor Physiology, IRCCS Fondazione Santa Lucia, Rome, Italy
- Department of Biomedical and Dental Sciences and Morphofunctional Imaging, University of Messina, Messina, Italy
| | - Martin A. Giese
- Section for Computational Sensomotorics, Centre for Integrative Neuroscience, Hertie Institute for Clinical Brain Research, University Clinic Tübingen, Tübingen, Germany
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12
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Somech N, Mizrahi T, Caspi Y, Axelrod V. Functional near-infrared spectroscopy imaging of the prefrontal cortex during a naturalistic comedy movie. Front Neurosci 2022; 16:913540. [PMID: 36161175 PMCID: PMC9493198 DOI: 10.3389/fnins.2022.913540] [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: 04/05/2022] [Accepted: 08/12/2022] [Indexed: 11/16/2022] Open
Abstract
Naturalistic stimulation (i.e., movies and auditory narratives of some minutes' length) has been a powerful approach to bringing more real-life experiences into laboratory experiments. Data-driven, intersubject correlation (ISC) analysis permits examining to what extent activity in a specific brain region correlates across participants during exposure to a naturalistic stimulus, as well as testing whether neural activity correlates with behavioral measures. Notably, most of the previous research with naturalistic stimuli was conducted using functional fMRI (fMRI). Here, we tested whether a naturalistic approach and the ISC are feasible using functional near-infrared spectroscopy (fNIRS) - the imaging method particularly suited for populations of patients and children. Fifty-three healthy adult participants watched twice a 3-min segment of a Charlie Chaplin movie while we recorded the brain activity on the surface of their prefrontal cortex using fNIRS. In addition, an independent group of 18 participants used a continuous scoring procedure to rate the extent to which they felt that different parts of the movie fragment were funny. Our two findings were as follows. First, we found higher-than-zero ISC in fNIRS signals in the prefrontal cortex lobes, a result that was particularly high in the oxygenated channels during the first repetition of the movie. Second, we found a significant negative correlation between oxygenated brain signals and ratings of the movie's humorousness. In a series of control analyses we demonstrated that this latter correlation could not be explained by various non-humor-related movie sensory properties (e.g., auditory volume and image brightness). The key overall outcome of the present study is that fNIRS in combination with the naturalistic paradigms and the ISC might be a sensitive and powerful research method to explore cognitive processing. Our results also suggest a potential role of the prefrontal cortex in humor appreciation.
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Affiliation(s)
- Noam Somech
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
| | - Tamar Mizrahi
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
- Head Injuries Rehabilitation Department, Sheba Medical Center, Ramat Gan, Israel
| | - Yael Caspi
- Department of Psychology, Bar-Ilan University, Ramat Gan, Israel
| | - Vadim Axelrod
- The Gonda Multidisciplinary Brain Research Center, Bar-Ilan University, Ramat Gan, Israel
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Liu D, Zhang Y, Zhang P, Li T, Li Z, Zhang L, Gao F. Deep-learning informed Kalman filtering for priori-free and real-time hemodynamics extraction in functional near-infrared spectroscopy. BIOMEDICAL OPTICS EXPRESS 2022; 13:4787-4801. [PMID: 36187239 PMCID: PMC9484432 DOI: 10.1364/boe.467943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/04/2022] [Accepted: 08/05/2022] [Indexed: 06/16/2023]
Abstract
Separation of the physiological interferences and the neural hemodynamics has been a vitally important task in the realistic implementation of functional near-infrared spectroscopy (fNIRS). Although many efforts have been devoted, the established solutions to this issue additionally rely on priori information on the interferences and activation responses, such as time-frequency characteristics and spatial patterns, etc., also hindering the realization of real-time. To tackle the adversity, we herein propose a novel priori-free scheme for real-time physiological interference suppression. This method combines the robustness of deep-leaning-based interference characterization and adaptivity of Kalman filtering: a long short-term memory (LSTM) network is trained with the time-courses of the absorption perturbation baseline for interferences profiling, and successively, a Kalman filtering process is applied with reference to the noise prediction for real-time activation extraction. The proposed method is validated using both simulated dynamic data and in-vivo experiments, showing the comprehensively improved performance and promisingly appended superiority achieved in the purely data-driven way.
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Affiliation(s)
- Dongyuan Liu
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Yao Zhang
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Pengrui Zhang
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Tieni Li
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Zhiyong Li
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
| | - Limin Zhang
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Tianjin Key laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
| | - Feng Gao
- College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin 300072, China
- Tianjin Key laboratory of Biomedical Detecting Techniques and Instruments, Tianjin 300072, China
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14
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Adaptation of stimulation duration to enhance auditory response in fNIRS block design. Hear Res 2022; 424:108593. [DOI: 10.1016/j.heares.2022.108593] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Revised: 07/19/2022] [Accepted: 07/26/2022] [Indexed: 11/04/2022]
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15
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Paranawithana I, Mao D, Wong YT, McKay CM. Reducing false discoveries in resting-state functional connectivity using short channel correction: an fNIRS study. NEUROPHOTONICS 2022; 9:015001. [PMID: 35071689 PMCID: PMC8765292 DOI: 10.1117/1.nph.9.1.015001] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 12/23/2021] [Indexed: 06/14/2023]
Abstract
Significance: Functional near-infrared spectroscopy (fNIRS) is a neuroimaging tool that can measure resting-state functional connectivity; however, non-neuronal components present in fNIRS signals introduce false discoveries in connectivity, which can impact interpretation of functional networks. Aim: We investigated the effect of short channel correction on resting-state connectivity by removing non-neuronal signals from fNIRS long channel data. We hypothesized that false discoveries in connectivity can be reduced, hence improving the discriminability of functional networks of known, different connectivity strengths. Approach: A principal component analysis-based short channel correction technique was applied to resting-state data of 10 healthy adult subjects. Connectivity was analyzed using magnitude-squared coherence of channel pairs in connectivity groups of homologous and control brain regions, which are known to differ in connectivity. Results: By removing non-neuronal components using short channel correction, significant reduction of coherence was observed for oxy-hemoglobin concentration changes in frequency bands associated with resting-state connectivity that overlap with the Mayer wave frequencies. The results showed that short channel correction reduced spurious correlations in connectivity measures and improved the discriminability between homologous and control groups. Conclusions: Resting-state functional connectivity analysis with short channel correction performs better than without correction in its ability to distinguish functional networks with distinct connectivity characteristics.
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Affiliation(s)
- Ishara Paranawithana
- Monash University, Department of Electrical and Computer Systems Engineering, Clayton, Victoria, Australia
- The Bionics Institute, East Melbourne, Victoria, Australia
| | - Darren Mao
- The Bionics Institute, East Melbourne, Victoria, Australia
- The University of Melbourne, Department of Medical Bionics, Parkville, Victoria, Australia
| | - Yan T. Wong
- Monash University, Department of Electrical and Computer Systems Engineering, Clayton, Victoria, Australia
- Monash University, Monash Biomedicine Discovery Institute, Department of Physiology, Clayton, Victoria, Australia
| | - Colette M. McKay
- The Bionics Institute, East Melbourne, Victoria, Australia
- The University of Melbourne, Department of Medical Bionics, Parkville, Victoria, Australia
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16
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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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17
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Kassab A, Hinnoutondji Toffa D, Robert M, Lesage F, Peng K, Khoa Nguyen D. Hemodynamic changes associated with common EEG patterns in critically ill patients: Pilot results from continuous EEG-fNIRS study. Neuroimage Clin 2021; 32:102880. [PMID: 34773798 PMCID: PMC8594770 DOI: 10.1016/j.nicl.2021.102880] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2021] [Revised: 11/04/2021] [Accepted: 11/05/2021] [Indexed: 11/21/2022]
Abstract
Functional near-infrared spectroscopy (fNIRS) is currently the only non-invasive method allowing for continuous long-term assessment of cerebral hemodynamic. We evaluate the feasibility of using continueous electroencephalgraphy (cEEG)-fNIRS to study the cortical hemodynamic associated with status epilepticus (SE), burst suppression (BS) and periodic discharges (PDs). Eleven adult comatose patients admitted to the neuroICU for SE were recruited, and cEEG-fNIRS monitoring was performed to measure concentration changes in oxygenated (HbO) and deoxygenated hemoglobin (HbR). Seizures were associated with a large increase HbO and a decrease in HbR whose durations were positively correlated with the seizures' length. Similar observations were made for hemodynamic changes associated with bursts, showing overall increases in HbO and decreases in HbR relative to the suppression periods. PDs were seen to induce widespread HbO increases and HbR decreases. These results suggest that normal neurovascular coupling is partially retained with the hemodynamic response to the detected EEG patterns in these patients. However, the shape and distribution of the response were highly variable. This work highlighted the feasibility of conducting long-term cEEG-fNIRS to monitor hemodynamic changes over a large cortical area in critically ill patients, opening new routes for better understanding and management of abnormal EEG patterns in neuroICU.
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Affiliation(s)
- Ali Kassab
- Department of Neurological Sciences, Université de Montréal, C.P. 6128, succ. Centre-ville, Montreal, Quebec H3C 3J7, Canada; Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Université de Montréal, 900 Saint Denis St., Montreal, Quebec H2X 0A9, Canada.
| | - Dènahin Hinnoutondji Toffa
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Université de Montréal, 900 Saint Denis St., Montreal, Quebec H2X 0A9, Canada.
| | - Manon Robert
- Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Université de Montréal, 900 Saint Denis St., Montreal, Quebec H2X 0A9, Canada.
| | - Frédéric Lesage
- Biomedical Engineering Institute, École Polytechnique de Montréal, 2500 Chemin de Polytechnique, Montréal, Quebec H3T 1J4, Canada; Research Center, Montreal Heart Institute, 5000 Rue Bélanger, Montreal, Quebec H1T 1C8, Canada.
| | - Ke Peng
- Department of Neurological Sciences, Université de Montréal, C.P. 6128, succ. Centre-ville, Montreal, Quebec H3C 3J7, Canada; Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Université de Montréal, 900 Saint Denis St., Montreal, Quebec H2X 0A9, Canada.
| | - Dang Khoa Nguyen
- Department of Neurological Sciences, Université de Montréal, C.P. 6128, succ. Centre-ville, Montreal, Quebec H3C 3J7, Canada; Centre de Recherche du Centre Hospitalier de l'Université de Montréal, Université de Montréal, 900 Saint Denis St., Montreal, Quebec H2X 0A9, Canada; Division of Neurology, Centre Hospitalier de l'Université de Montréal, Université de Montréal, 1000 Saint Denis St, Montreal, Quebec (H2X OC1), Canada.
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18
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Liu D, Zhang P, Zhang Y, Bai L, Gao F. Suppressing physiological interferences and physical noises in functional diffuse optical tomography via tandem inversion filtering and LSTM classification. OPTICS EXPRESS 2021; 29:29275-29291. [PMID: 34615040 DOI: 10.1364/oe.433917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 08/13/2021] [Indexed: 06/13/2023]
Abstract
For performance enhancement of functional diffuse optical tomography (fDOT), we propose a tandem method that takes advantage of the inversion filtering and the long short term memory (LSTM) classification to simultaneously suppress the physiological interferences and physical noises in fDOT. In the former phase, the absorption perturbation maps over the scalp-skull (SS) and cerebral-cortex (CC) layers are firstly pre-reconstructed using a two-layer topography scheme. Then, the recovered SS-map is inversed into measurement space by the forward calculation to estimate the intensity changes associated with the physiological interferences. Finally, the raw measurements are adaptively filtered with reference to the estimated intensity changes for accomplishing the model-based full three-dimension (3D) reconstruction. In the later phase, for further removing the randomly distributed physical noises, mainly instrumental noise, a LSTM network based fusion strategy is applied, where a pixel-wise binary mask of "activated" or "inactive" state is generated by performing LSTM classification and then fused with the 3D reconstruction. The results of the simulative investigation and in-vivo experiment show the proposed tandem scheme achieves improved performance in fDOT using a cost-effective and physically explicable way. Thus, the proposed method can be promisingly applied in real-time neuroimaging to acquire cortical neural activation information with improved reliability, quantification and resolution.
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19
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Zhang F, Cheong D, Khan AF, Chen Y, Ding L, Yuan H. Correcting physiological noise in whole-head functional near-infrared spectroscopy. J Neurosci Methods 2021; 360:109262. [PMID: 34146592 DOI: 10.1016/j.jneumeth.2021.109262] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 05/20/2021] [Accepted: 06/14/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Functional near-infrared spectroscopy (fNIRS) has been increasingly employed to monitor cerebral hemodynamics in normal and diseased conditions. However, fNIRS suffers from its susceptibility to superficial activity and systemic physiological noise. The objective of the study was to establish a noise reduction method for fNIRS in a whole-head montage. NEW METHOD We have developed an automated denoising method for whole-head fNIRS. A high-density montage consisting of 109 long-separation channels and 8 short-separation channels was used for recording. Auxiliary sensors were also used to measure motion, respiration and pulse simultaneously. The method incorporates principal component analysis and general linear model to identify and remove a globally uniform superficial component. Our denoising method was evaluated in experimental data acquired from a group of healthy human subjects during a visually cued motor task and further compared with a minimal preprocessing method and three established denoising methods in the literature. Quantitative metrics including contrast-to-noise ratio, within-subject standard deviation and adjusted coefficient of determination were evaluated. RESULTS After denoising, whole-head topography of fNIRS revealed focal activations concurrently in the primary motor and visual areas. COMPARISON WITH EXISTING METHODS Analysis showed that our method improves upon the four established preprocessing methods in the literature. CONCLUSIONS An automatic, effective and robust preprocessing pipeline was established for removing physiological noise in whole-head fNIRS recordings. Our method can enable fNIRS as a reliable tool in monitoring large-scale, network-level brain activities for clinical uses.
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Affiliation(s)
- Fan Zhang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA
| | - Daniel Cheong
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA
| | - Ali F Khan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA
| | - Yuxuan Chen
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA; Institute for Biomedical Engineering, Science and Technology, University of Oklahoma, Norman, OK, USA
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA; Institute for Biomedical Engineering, Science and Technology, University of Oklahoma, Norman, OK, USA.
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20
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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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21
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Perpetuini D, Chiarelli AM, Filippini C, Cardone D, Croce P, Rotunno L, Anzoletti N, Zito M, Zappasodi F, Merla A. Working Memory Decline in Alzheimer's Disease Is Detected by Complexity Analysis of Multimodal EEG-fNIRS. ENTROPY (BASEL, SWITZERLAND) 2020; 22:E1380. [PMID: 33279924 PMCID: PMC7762102 DOI: 10.3390/e22121380] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Revised: 11/30/2020] [Accepted: 12/03/2020] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) is characterized by working memory (WM) failures that can be assessed at early stages through administering clinical tests. Ecological neuroimaging, such as Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS), may be employed during these tests to support AD early diagnosis within clinical settings. Multimodal EEG-fNIRS could measure brain activity along with neurovascular coupling (NC) and detect their modifications associated with AD. Data analysis procedures based on signal complexity are suitable to estimate electrical and hemodynamic brain activity or their mutual information (NC) during non-structured experimental paradigms. In this study, sample entropy of whole-head EEG and frontal/prefrontal cortex fNIRS was evaluated to assess brain activity in early AD and healthy controls (HC) during WM tasks (i.e., Rey-Osterrieth complex figure and Raven's progressive matrices). Moreover, conditional entropy between EEG and fNIRS was evaluated as indicative of NC. The findings demonstrated the capability of complexity analysis of multimodal EEG-fNIRS to detect WM decline in AD. Furthermore, a multivariate data-driven analysis, performed on these entropy metrics and based on the General Linear Model, allowed classifying AD and HC with an AUC up to 0.88. EEG-fNIRS may represent a powerful tool for the clinical evaluation of WM decline in early AD.
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Affiliation(s)
- David Perpetuini
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (A.M.C.); (C.F.); (D.C.); (P.C.); (F.Z.); (A.M.)
| | - Antonio Maria Chiarelli
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (A.M.C.); (C.F.); (D.C.); (P.C.); (F.Z.); (A.M.)
| | - Chiara Filippini
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (A.M.C.); (C.F.); (D.C.); (P.C.); (F.Z.); (A.M.)
| | - Daniela Cardone
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (A.M.C.); (C.F.); (D.C.); (P.C.); (F.Z.); (A.M.)
| | - Pierpaolo Croce
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (A.M.C.); (C.F.); (D.C.); (P.C.); (F.Z.); (A.M.)
| | - Ludovica Rotunno
- Department of Medicine and Science of Ageing, University G. D’Annunzio, Via Dei Vestini 31, 66100 Chieti, Italy; (L.R.); (N.A.); (M.Z.)
| | - Nelson Anzoletti
- Department of Medicine and Science of Ageing, University G. D’Annunzio, Via Dei Vestini 31, 66100 Chieti, Italy; (L.R.); (N.A.); (M.Z.)
| | - Michele Zito
- Department of Medicine and Science of Ageing, University G. D’Annunzio, Via Dei Vestini 31, 66100 Chieti, Italy; (L.R.); (N.A.); (M.Z.)
| | - Filippo Zappasodi
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (A.M.C.); (C.F.); (D.C.); (P.C.); (F.Z.); (A.M.)
| | - Arcangelo Merla
- Institute for Advanced Biomedical Technologies, Department of Neuroscience and Imaging, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (A.M.C.); (C.F.); (D.C.); (P.C.); (F.Z.); (A.M.)
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22
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Yang HCS, Liang Z, Vike NL, Lee T, Rispoli JV, Nauman EA, Talavage TM, Tong Y. Characterizing near-infrared spectroscopy signal under hypercapnia. JOURNAL OF BIOPHOTONICS 2020; 13:e202000173. [PMID: 32706517 DOI: 10.1002/jbio.202000173] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2020] [Revised: 07/11/2020] [Accepted: 07/20/2020] [Indexed: 06/11/2023]
Abstract
Vasoactive stress tests (i.e. hypercapnia, elevated partial pressure of arterial CO2 [PaCO2 ]) are commonly used in functional MRI (fMRI), to induce cerebral blood flow changes and expose hidden perfusion deficits in the brain. Compared with fMRI, near-infrared spectroscopy (NIRS) is an alternative low-cost, real-time, and non-invasive tool, which can be applied in out-of-hospital settings. To develop and optimize vasoactive stress tests for NIRS, several hypercapnia-induced tasks were tested using concurrent-NIRS/fMRI on healthy subjects. The results indicated that the cerebral and extracerebral reactivity to elevated PaCO2 depended on the rate of the CO2 increase. A steep increase resulted in different cerebral and extracerebral reactivities, leading to unpredictable NIRS measurements compared with fMRI. However, a ramped increase, induced by ramped-CO2 inhalation or breath-holding tasks, induced synchronized cerebral, and extracerebral reactivities, resulting in consistent NIRS and fMRI measurements. These results demonstrate that only tasks that increase PaCO2 gradually can produce reliable NIRS results.
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Affiliation(s)
- Ho-Ching Shawn Yang
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Zhenhu Liang
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
- Institute of Electrical Engineering, Yanshan University, Qinhuangdao, China
| | - Nicole L Vike
- Department of Basic Medical Sciences, Purdue University, West Lafayette, Indiana, USA
| | - Taylor Lee
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Joseph V Rispoli
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Eric A Nauman
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
- School of Mechanical Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Thomas M Talavage
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
- School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana, USA
| | - Yunjie Tong
- Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA
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23
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Milej D, Abdalmalak A, Rajaram A, St. Lawrence K. Direct assessment of extracerebral signal contamination on optical measurements of cerebral blood flow, oxygenation, and metabolism. NEUROPHOTONICS 2020; 7:045002. [PMID: 33062801 PMCID: PMC7540337 DOI: 10.1117/1.nph.7.4.045002] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 09/04/2020] [Indexed: 05/08/2023]
Abstract
Significance: Near-infrared spectroscopy (NIRS) combined with diffuse correlation spectroscopy (DCS) provides a noninvasive approach for monitoring cerebral blood flow (CBF), oxygenation, and oxygen metabolism. However, these methods are vulnerable to signal contamination from the scalp. Our work evaluated methods of reducing the impact of this contamination using time-resolved (TR) NIRS and multidistance (MD) DCS. Aim: The magnitude of scalp contamination was evaluated by measuring the flow, oxygenation, and metabolic responses to a global hemodynamic challenge. Contamination was assessed by collecting data with and without impeding scalp blood flow. Approach: Experiments involved healthy participants. A pneumatic tourniquet was used to cause scalp ischemia, as confirmed by contrast-enhanced NIRS, and a computerized gas system to generate a hypercapnic challenge. Results: Comparing responses acquired with and without the tourniquet demonstrated that the TR-NIRS technique could reduce scalp contributions in hemodynamic signals up to 4 times (r SD = 3 cm ) and 6 times (r SD = 4 cm ). Similarly, blood flow responses from the scalp and brain could be separated by analyzing MD DCS data with a multilayer model. Using these techniques, there was no change in metabolism during hypercapnia, as expected, despite large increases in CBF and oxygenation. Conclusion: NIRS/DCS can accurately monitor CBF and metabolism with the appropriate enhancement to depth sensitivity, highlighting the potential of these techniques for neuromonitoring.
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Affiliation(s)
- Daniel Milej
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Androu Abdalmalak
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Ajay Rajaram
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Keith St. Lawrence
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
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24
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Milej D, Shahid M, Abdalmalak A, Rajaram A, Diop M, St. Lawrence K. Characterizing dynamic cerebral vascular reactivity using a hybrid system combining time-resolved near-infrared and diffuse correlation spectroscopy. BIOMEDICAL OPTICS EXPRESS 2020; 11:4571-4585. [PMID: 32923065 PMCID: PMC7449704 DOI: 10.1364/boe.392113] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Revised: 04/28/2020] [Accepted: 05/12/2020] [Indexed: 05/09/2023]
Abstract
This study presents the characterization of dynamic cerebrovascular reactivity (CVR) in healthy adults by a hybrid optical system combining time-resolved (TR) near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS). Blood flow and oxygenation (oxy- and deoxy-hemoglobin) responses to a step hypercapnic challenge were recorded to characterize dynamic and static components of CVR. Data were acquired at short and long source-detector separations (r SD) to assess the impact of scalp hemodynamics, and moment analysis applied to the TR-NIRS to further enhance the sensitivity to the brain. Comparing blood flow and oxygenation responses acquired at short and long r SD demonstrated that scalp contamination distorted the CVR time courses, particularly for oxyhemoglobin. This effect was significantly diminished by the greater depth sensitivity of TR NIRS and less evident in the DCS data due to the higher blood flow in the brain compared to the scalp. The reactivity speed was similar for blood flow and oxygenation in the healthy brain. Given the ease-of-use, portability, and non-invasiveness of this hybrid approach, it is well suited to investigate if the temporal relationship between CBF and oxygenation is altered by factors such as age and cerebrovascular disease.
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Affiliation(s)
- Daniel Milej
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada
- Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1, Canada
| | - Marwan Shahid
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada
- Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1, Canada
| | - Androu Abdalmalak
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada
- Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1, Canada
| | - Ajay Rajaram
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada
- Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1, Canada
| | - Mamadou Diop
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada
- Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1, Canada
| | - Keith St. Lawrence
- Imaging Program, Lawson Health Research Institute, London, Ontario, N6A 4V2, Canada
- Department of Medical Biophysics, Western University, London, Ontario, N6A 5C1, Canada
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Fantini S, Sassaroli A. Frequency-Domain Techniques for Cerebral and Functional Near-Infrared Spectroscopy. Front Neurosci 2020; 14:300. [PMID: 32317921 PMCID: PMC7154496 DOI: 10.3389/fnins.2020.00300] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 03/16/2020] [Indexed: 12/31/2022] Open
Abstract
This article reviews the basic principles of frequency-domain near-infrared spectroscopy (FD-NIRS), which relies on intensity-modulated light sources and phase-sensitive optical detection, and its non-invasive applications to the brain. The simpler instrumentation and more straightforward data analysis of continuous-wave NIRS (CW-NIRS) accounts for the fact that almost all the current commercial instruments for cerebral NIRS have embraced the CW technique. However, FD-NIRS provides data with richer information content, which complements or exceeds the capabilities of CW-NIRS. One example is the ability of FD-NIRS to measure the absolute optical properties (absorption and reduced scattering coefficients) of tissue, and thus the absolute concentrations of oxyhemoglobin and deoxyhemoglobin in brain tissue. This article reviews the measured values of such optical properties and hemoglobin concentrations reported in the literature for animal models and for the human brain in newborns, infants, children, and adults. We also review the application of FD-NIRS to functional brain studies that focused on slower hemodynamic responses to brain activity (time scale of seconds) and faster optical signals that have been linked to neuronal activation (time scale of 100 ms). Another example of the power of FD-NIRS data is related to the different regions of sensitivity featured by intensity and phase data. We report recent developments that take advantage of this feature to maximize the sensitivity of non-invasive optical signals to brain tissue relative to more superficial extracerebral tissue (scalp, skull, etc.). We contend that this latter capability is a highly appealing quality of FD-NIRS, which complements absolute optical measurements and may result in significant advances in the field of non-invasive optical sensing of the brain.
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Affiliation(s)
- Sergio Fantini
- Department of Biomedical Engineering, Tufts University, Medford, MA, United States
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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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Amyot F, Kenney K, Spessert E, Moore C, Haber M, Silverman E, Gandjbakhche A, Diaz-Arrastia R. Assessment of cerebrovascular dysfunction after traumatic brain injury with fMRI and fNIRS. NEUROIMAGE-CLINICAL 2019; 25:102086. [PMID: 31790877 PMCID: PMC6909332 DOI: 10.1016/j.nicl.2019.102086] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 11/07/2019] [Accepted: 11/09/2019] [Indexed: 11/26/2022]
Abstract
Traumatic cerebral vascular injury (TCVI) is a frequent, but under-recognized, endophenotype of traumatic brain injury (TBI). It likely contributes to functional deficits after TBI and TBI-related chronic disability, and represents an attractive target for targeted therapeutic interventions. The aim of this prospective study is to assess microvascular injury/dysfunction in chronic TBI by measuring cerebral vascular reactivity (CVR) by 2 methods, functional magnetic resonance imaging (fMRI) and functional Near InfraRed Spectroscopy (fNIRS) imaging, as each has attractive features relevant to clinical utility. 42 subjects (27 chronic TBI, 15 age- and gender-matched non-TBI volunteers) were enrolled and underwent outpatient CVR testing by 2 methods, MRI-BOLD and fNIRS, each with hypercapnia challenge, a neuropsychological testing battery, and symptom survey questionnaires. Chronic TBI subjects showed a significant reduction in global CVR compared to HC (p < 0.0001). Mean CVR measures by fMRI were 0.225 ± 0.014 and 0.183 ± 0.026 %BOLD/mmHg for non-TBI and TBI subjects respectively and 12.3 ± 1.8 and 9.2 ± 1.7 mM/mmHg by fNIRS for non-TBI versus TBI subjects respectively. Global CVR measured by fNIRS imaging correlates with results by MRI-BOLD (R = 0.5). Focal CVR deficits seen on CVR maps by fMRI are also observed in the same areas by fNIRS in the frontal regions. Global CVR is significantly lower in chronic TBI patients and is reliably measured by both fMRI and fNIRS, the former with better spatial and the latter with better temporal resolution. Both methods show promise as non-invasive measures of CVR function and microvascular integrity after TBI.
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Affiliation(s)
- Franck Amyot
- Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA; Center for Neuroscience and Regenerative Medicine, Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA.
| | - Kimbra Kenney
- Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA; Center for Neuroscience and Regenerative Medicine, Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA
| | - Emily Spessert
- Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA; Center for Neuroscience and Regenerative Medicine, Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA
| | - Carol Moore
- Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA; Center for Neuroscience and Regenerative Medicine, Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA
| | - Margalit Haber
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Erika Silverman
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Amir Gandjbakhche
- Section on Analytical and Functional Biophotonics, Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health (NIH), Bethesda, Maryland, USA
| | - Ramon Diaz-Arrastia
- Center for Neuroscience and Regenerative Medicine, Department of Neurology, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA; Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia
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von Lühmann A, Boukouvalas Z, Müller KR, Adalı T. A new blind source separation framework for signal analysis and artifact rejection in functional Near-Infrared Spectroscopy. Neuroimage 2019; 200:72-88. [DOI: 10.1016/j.neuroimage.2019.06.021] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Revised: 05/29/2019] [Accepted: 06/07/2019] [Indexed: 10/26/2022] Open
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Zhang F, Cheong D, Chen Y, Khan A, Ding L, Yuan H. Superficial Fluctuations in Functional Near-Infrared Spectroscopy. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2019; 2019:4779-4782. [PMID: 31946930 DOI: 10.1109/embc.2019.8856349] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a non-invasive optical functional neuroimaging that has seen rapid development and increasing use in studying human brain under normal and diseased conditions. Compared with blood-oxygenation-level dependent functional magnetic resonance imaging (BOLD fMRI), fNIRS offers advantages including its low cost, portability and compatibility with implanted medical devices. Thus, fNIRS can be used to monitor brain activity particularly in infants, elders and patients who are unable to undergo routine fMRI scans. However, fNIRS suffers from its susceptibility to scalp and to systemic physiological noises. Fluctuations originated from heartbeat, respiration and low-frequency oscillations lead to contamination of cerebral activity. In order to tap the full potential of fNIRS, it is essential to eliminate these confounding noises from fNIRS measurements. Therefore, the present study aims to understand the underlying relationship between superficial signals and the compound signals respectively measured by short channels and long channels of fNIRS optodes in a whole head configuration. Our results reveal that: 1) 49.56% of total variances in long-channel data are contributed by a global component shared across all long channels; 2) this global component is significantly correlated with the superficial fluctuations extracted from short-channel data. Finally, our findings indicate that compound signals measured by long channels of fNIRS are contaminated by superficial fluctuations and that careful removal of these fluctuations from long-channel data is critical in obtaining accurate images of cerebral activity with fNIRS.
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Paik SH, Erdogan S, Phillips V Z, Kim YK, Song KI, Park SE, Choi Y, Youn I, Kim BM. Hemodynamic correlation imaging of the mouse brain for application in unilateral neurodegenerative diseases. BIOMEDICAL OPTICS EXPRESS 2019; 10:1736-1749. [PMID: 31086700 PMCID: PMC6485007 DOI: 10.1364/boe.10.001736] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Revised: 02/25/2019] [Accepted: 02/27/2019] [Indexed: 06/09/2023]
Abstract
We developed a single-camera two-channel hemodynamic imaging system that uses near-infrared light to monitor the mouse brain in vivo with an exposed, un-thinned, and intact skull to explore the effect of Parkinson's disease on the resting state functional connectivity of the brain. To demonstrate our system's ability to monitor cerebral hemodynamics, we first performed direct electrical stimulation of an anesthetized healthy mouse brain and detected hemodynamic changes localized to the stimulated area. Subsequently, we developed a unilaterally lesioned 6-hydroxydopamine (hemi-parkinsonian) mouse model and detected the differences in functional connectivity between the normal and hemi-parkinsonian mouse brains by comparing the hemispheric hemodynamic correlations during the resting state. Seed-based correlation for the oxy-hemoglobin channel from the left and right hemispheres of healthy mice was much higher and more symmetric than in hemi-parkinsonian mice. Through a k-means clustering of the hemodynamic signals, the healthy mouse brains were segmented according to brain region, but the hemi-parkinsonian mice did not show a similar segmentation. Overall, this study highlights the development of a spatial multiplexing hemodynamic imaging system that reveals the resting state hemodynamic connectivity in healthy and hemi-parkinsonian mice.
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Affiliation(s)
- Seung-Ho Paik
- Korea University, Department of Bio-convergence Engineering, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea
- Co-first authors
| | - Sedef Erdogan
- Korea University, Department of Bio-convergence Engineering, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea
- Co-first authors
| | - Zephaniah Phillips V
- Korea University, Department of Bio-convergence Engineering, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea
| | - Young-Kyu Kim
- Korea University, Department of Bio-convergence Engineering, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea
| | - Kang-Il Song
- Korea Institute of Science and Technology, Biomedical Research Institute, Hwarangno14-gil5, Seongbuk-gu, Seoul, 02792, South Korea
| | - Sunghee Estelle Park
- Korea Institute of Science and Technology, Biomedical Research Institute, Hwarangno14-gil5, Seongbuk-gu, Seoul, 02792, South Korea
| | - Youngwoon Choi
- Korea University, Department of Bio-convergence Engineering, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea
| | - Inchan Youn
- Korea Institute of Science and Technology, Biomedical Research Institute, Hwarangno14-gil5, Seongbuk-gu, Seoul, 02792, South Korea
- Co-corresponding authors
| | - Beop-Min Kim
- Korea University, Department of Bio-convergence Engineering, 145, Anam-ro, Seongbuk-gu, Seoul, 02841, South Korea
- Co-corresponding authors
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Scheunemann J, Unni A, Ihme K, Jipp M, Rieger JW. Demonstrating Brain-Level Interactions Between Visuospatial Attentional Demands and Working Memory Load While Driving Using Functional Near-Infrared Spectroscopy. Front Hum Neurosci 2019; 12:542. [PMID: 30728773 PMCID: PMC6351455 DOI: 10.3389/fnhum.2018.00542] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2018] [Accepted: 12/31/2018] [Indexed: 11/13/2022] Open
Abstract
Driving is a complex task concurrently drawing on multiple cognitive resources. Yet, there is a lack of studies investigating interactions at the brain-level among different driving subtasks in dual-tasking. This study investigates how visuospatial attentional demands related to increased driving difficulty interacts with different working memory load (WML) levels at the brain level. Using multichannel whole-head high density functional near-infrared spectroscopy (fNIRS) brain activation measurements, we aimed to predict driving difficulty level, both separate for each WML level and with a combined model. Participants drove for approximately 60 min on a highway with concurrent traffic in a virtual reality driving simulator. In half of the time, the course led through a construction site with reduced lane width, increasing visuospatial attentional demands. Concurrently, participants performed a modified version of the n-back task with five different WML levels (from 0-back up to 4-back), forcing them to continuously update, memorize, and recall the sequence of the previous 'n' speed signs and adjust their speed accordingly. Using multivariate logistic ridge regression, we were able to correctly predict driving difficulty in 75.0% of the signal samples (1.955 Hz sampling rate) across 15 participants in an out-of-sample cross-validation of classifiers trained on fNIRS data separately for each WML level. There was a significant effect of the WML level on the driving difficulty prediction accuracies [range 62.2-87.1%; χ2(4) = 19.9, p < 0.001, Kruskal-Wallis H test] with highest prediction rates at intermediate WML levels. On the contrary, training one classifier on fNIRS data across all WML levels severely degraded prediction performance (mean accuracy of 46.8%). Activation changes in the bilateral dorsal frontal (putative BA46), bilateral inferior parietal (putative BA39), and left superior parietal (putative BA7) areas were most predictive to increased driving difficulty. These discriminative patterns diminished at higher WML levels indicating that visuospatial attentional demands and WML involve interacting underlying brain processes. The changing pattern of driving difficulty related brain areas across WML levels could indicate potential changes in the multitasking strategy with level of WML demand, in line with the multiple resource theory.
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Affiliation(s)
- Jakob Scheunemann
- Department of Psychology, University of Oldenburg, Oldenburg, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Anirudh Unni
- Department of Psychology, University of Oldenburg, Oldenburg, Germany
| | - Klas Ihme
- Institute of Transportation Systems, German Aerospace Center (DLR), Braunschweig, Germany
| | - Meike Jipp
- Institute of Transportation Systems, German Aerospace Center (DLR), Braunschweig, Germany
| | - Jochem W. Rieger
- Department of Psychology, University of Oldenburg, Oldenburg, Germany
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Sutoko S, Chan YL, Obata A, Sato H, Maki A, Numata T, Funane T, Atsumori H, Kiguchi M, Tang TB, Li Y, Frederick BD, Tong Y. Denoising of neuronal signal from mixed systemic low-frequency oscillation using peripheral measurement as noise regressor in near-infrared imaging. NEUROPHOTONICS 2019; 6:015001. [PMID: 30662924 PMCID: PMC6326259 DOI: 10.1117/1.nph.6.1.015001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 12/10/2018] [Indexed: 05/07/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a noninvasive functional imaging technique measuring hemodynamic changes including oxygenated ( O 2 Hb ) and deoxygenated (HHb) hemoglobin. Low frequency (LF; 0.01 to 0.15 Hz) band is commonly analyzed in fNIRS to represent neuronal activation. However, systemic physiological artifacts (i.e., nonneuronal) likely occur also in overlapping frequency bands. We measured peripheral photoplethysmogram (PPG) signal concurrently with fNIRS (at prefrontal region) to extract the low-frequency oscillations (LFOs) as systemic noise regressors. We investigated three main points in this study: (1) the relationship between prefrontal fNIRS and peripheral PPG signals; (2) the denoising potential using these peripheral LFOs, and (3) the innovative ways to avoid the false-positive result in fNIRS studies. We employed spatial working memory (WM) and control tasks (e.g., resting state) to illustrate these points. Our results showed: (1) correlation between signals from prefrontal fNIRS and peripheral PPG is region-dependent. The high correlation with peripheral ear signal (i.e., O 2 Hb ) occurred mainly in frontopolar regions in both spatial WM and control tasks. This may indicate the finding of task-dependent effect even in peripheral signals. We also found that the PPG recording at the ear has a high correlation with prefrontal fNIRS signal than the finger signals. (2) The systemic noise was reduced by 25% to 34% on average across regions, with a maximum of 39% to 58% in the highly correlated frontopolar region, by using these peripheral LFOs as noise regressors. (3) By performing the control tasks, we confirmed that the statistically significant activation was observed in the spatial WM task, not in the controls. This suggested that systemic (and any other) noises unlikely violated the major statistical inference. (4) Lastly, by denoising using the task-related signals, the significant activation of region-of-interest was still observed suggesting the manifest task-evoked response in the spatial WM task.
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Affiliation(s)
- Stephanie Sutoko
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
- Address all correspondence to Stephanie Sutoko, E-mail:
| | - Yee Ling Chan
- Universiti Teknologi PETRONAS, Electrical and Electronic Engineering Department, Bandar Seri Iskandar, Tronoh Perak, Malaysia
| | - Akiko Obata
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
| | - Hiroki Sato
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
| | - Atsushi Maki
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
| | - Takashi Numata
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
| | - Tsukasa Funane
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
| | - Hirokazu Atsumori
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
| | - Masashi Kiguchi
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
| | - Tong Boon Tang
- Universiti Teknologi PETRONAS, Electrical and Electronic Engineering Department, Bandar Seri Iskandar, Tronoh Perak, Malaysia
| | - Yingwei Li
- McLean Hospital, Brain Imaging Center, Belmont, Massachusetts, United States
- Yanshan University, School of Information Science and Engineering, Qinhuangdao, China
| | - Blaise deB Frederick
- McLean Hospital, Brain Imaging Center, Belmont, Massachusetts, United States
- Harvard Medical School, Department of Psychiatry, Boston, Massachusetts, United States
| | - Yunjie Tong
- Hitachi, Ltd., Center for Exploratory Research, Research & Development Group, Akanuma, Hatoyama, Saitama, Japan
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
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Nguyen HD, Yoo SH, Bhutta MR, Hong KS. Adaptive filtering of physiological noises in fNIRS data. Biomed Eng Online 2018; 17:180. [PMID: 30514303 PMCID: PMC6278088 DOI: 10.1186/s12938-018-0613-2] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 11/27/2018] [Indexed: 11/10/2022] Open
Abstract
The study presents a recursive least-squares estimation method with an exponential forgetting factor for noise removal in functional near-infrared spectroscopy data and extraction of hemodynamic responses (HRs) from the measured data. The HR is modeled as a linear regression form in which the expected HR, the first and second derivatives of the expected HR, a short-separation measurement data, three physiological noises, and the baseline drift are included as components in the regression vector. The proposed method is applied to left-motor-cortex experiments on the right thumb and little finger movements in five healthy male participants. The algorithm is evaluated with respect to its performance improvement in terms of contrast-to-noise ratio in comparison with Kalman filter, low-pass filtering, and independent component method. The experimental results show that the proposed model achieves reductions of 77% and 99% in terms of the number of channels exhibiting higher contrast-to-noise ratios in oxy-hemoglobin and deoxy-hemoglobin, respectively. The approach is robust in obtaining consistent HR data. The proposed method is applied for both offline and online noise removal.
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Affiliation(s)
- Hoang-Dung Nguyen
- Department of Automation Technology, Can Tho University, Can Tho, 900000, Vietnam
| | - So-Hyeon Yoo
- School of Mechanical Engineering, Pusan National University, Busan, 46241, Republic of Korea
| | - M Raheel Bhutta
- Department of Computer Science and Engineering, Sejong University, Seoul, 05006, Republic of Korea
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Busan, 46241, Republic of Korea. .,Department of Cogno-Mechatronics Engineering, Pusan National University, Busan, 46241, Republic of Korea.
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Exploring brain functional connectivity in rest and sleep states: a fNIRS study. Sci Rep 2018; 8:16144. [PMID: 30385843 PMCID: PMC6212555 DOI: 10.1038/s41598-018-33439-2] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 09/19/2018] [Indexed: 11/16/2022] Open
Abstract
This study investigates the brain functional connectivity in the rest and sleep states. We collected EEG, EOG, and fNIRS signals simultaneously during rest and sleep phases. The rest phase was defined as a quiet wake-eyes open (w_o) state, while the sleep phase was separated into three states; quiet wake-eyes closed (w_c), non-rapid eye movement sleep stage 1 (N1), and non-rapid eye movement sleep stage 2 (N2) using the EEG and EOG signals. The fNIRS signals were used to calculate the cerebral hemodynamic responses (oxy-, deoxy-, and total hemoglobin). We grouped 133 fNIRS channels into five brain regions (frontal, motor, temporal, somatosensory, and visual areas). These five regions were then used to form fifteen brain networks. A network connectivity was computed by calculating the Pearson correlation coefficients of the hemodynamic responses between fNIRS channels belonging to the network. The fifteen networks were compared across the states using the connection ratio and connection strength calculated from the normalized correlation coefficients. Across all fifteen networks and three hemoglobin types, the connection ratio was high in the w_c and N1 states and low in the w_o and N2 states. In addition, the connection strength was similar between the w_c and N1 states and lower in the w_o and N2 states. Based on our experimental results, we believe that fNIRS has a high potential to be a main tool to study the brain connectivity in the rest and sleep states.
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Sutoko S, Monden Y, Funane T, Tokuda T, Katura T, Sato H, Nagashima M, Kiguchi M, Maki A, Yamagata T, Dan I. Adaptive algorithm utilizing acceptance rate for eliminating noisy epochs in block-design functional near-infrared spectroscopy data: application to study in attention deficit/hyperactivity disorder children. NEUROPHOTONICS 2018; 5:045001. [PMID: 30345324 PMCID: PMC6181242 DOI: 10.1117/1.nph.5.4.045001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/16/2018] [Accepted: 09/14/2018] [Indexed: 06/08/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) signals are prone to problems caused by motion artifacts and physiological noises. These noises unfortunately reduce the fNIRS sensitivity in detecting the evoked brain activation while increasing the risk of statistical error. In fNIRS measurements, the repetitive resting-stimulus cycle (so-called block-design analysis) is commonly adapted to increase the sample number. However, these blocks are often affected by noises. Therefore, we developed an adaptive algorithm to identify, reject, and select the noise-free and/or least noisy blocks in accordance with the preset acceptance rate. The main features of this algorithm are personalized evaluation for individual data and controlled rejection to maintain the sample number. Three typical noise criteria (sudden amplitude change, shifted baseline, and minimum intertrial correlation) were adopted. Depending on the quality of the dataset used, the algorithm may require some or all noise criteria with distinct parameters. Aiming for real applications in a pediatric study, we applied this algorithm to fNIRS datasets obtained from attention deficit/hyperactivity disorder (ADHD) children as had been studied previously. These datasets were divided for training and validation purposes. A validation process was done to examine the feasibility of the algorithm regardless of the types of datasets, including those obtained under sample population (ADHD or typical developing children), intervention (nonmedication and drug/placebo administration), and measurement (task paradigm) conditions. The algorithm was optimized so as to enhance reproducibility of previous inferences. The optimum algorithm design involved all criteria ordered sequentially (0.047 mM mm of amplitude change, 0.029 mM mm / s of baseline slope, and 0.6 × interquartile range of outlier threshold for each criterion, respectively) and presented complete reproducibility in both training and validation datasets. Compared to the visual-based rejection as done in the previous studies, the algorithm achieved 71.8% rejection accuracy. This suggests that the algorithm has robustness and potential to substitute for visual artifact-detection.
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Affiliation(s)
- Stephanie Sutoko
- Hitachi Ltd., Research and Development Group, Center for Exploratory Research, Saitama, Japan
| | - Yukifumi Monden
- Jichi Medical University, Department of Pediatrics, Shimotsuke, Japan
- International University of Health and Welfare, Department of Pediatrics, Shiobara, Japan
| | - Tsukasa Funane
- Hitachi Ltd., Research and Development Group, Center for Exploratory Research, Saitama, Japan
- Jichi Medical University, Department of Pediatrics, Shimotsuke, Japan
| | - Tatsuya Tokuda
- Chuo University, Research and Development Initiatives, Applied Cognitive Neuroscience Laboratory, Tokyo, Japan
| | - Takusige Katura
- Hitachi Ltd., Research and Development Group, Center for Exploratory Research, Saitama, Japan
| | - Hiroki Sato
- Hitachi Ltd., Research and Development Group, Center for Exploratory Research, Saitama, Japan
| | - Masako Nagashima
- Jichi Medical University, Department of Pediatrics, Shimotsuke, Japan
| | - Masashi Kiguchi
- Hitachi Ltd., Research and Development Group, Center for Exploratory Research, Saitama, Japan
| | - Atsushi Maki
- Hitachi Ltd., Research and Development Group, Center for Exploratory Research, Saitama, Japan
| | - Takanori Yamagata
- Jichi Medical University, Department of Pediatrics, Shimotsuke, Japan
| | - Ippeita Dan
- Chuo University, Research and Development Initiatives, Applied Cognitive Neuroscience Laboratory, Tokyo, Japan
- Jichi Medical University, Center for Development of Advanced Medical Technology, Shimotsuke, Japan
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Duan L, Zhao Z, Lin Y, Wu X, Luo Y, Xu P. Wavelet-based method for removing global physiological noise in functional near-infrared spectroscopy. BIOMEDICAL OPTICS EXPRESS 2018; 9:3805-3820. [PMID: 30338157 PMCID: PMC6191612 DOI: 10.1364/boe.9.003805] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 06/26/2018] [Accepted: 07/02/2018] [Indexed: 05/20/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a fast-developing non-invasive functional brain imaging technology widely used in cognitive neuroscience, clinical research and neural engineering. However, it is a challenge to effectively remove the global physiological noise in the fNIRS signal. The global physiological noise in fNIRS arises from multiple physiological origins in both superficial tissues and the brain. It has complex temporal, spatial and frequency characteristics, casting significant influence on the results. In the present study, we developed a novel wavelet-based method for fNIRS global physiological noise removal. The method is data-driven and does not rely on any additional hardware or subjective noise component selection procedure. It consists of two steps. Firstly, we use wavelet transform coherence to automatically detect the time-frequency points contaminated by the global physiological noise. Secondly, we decompose the fNIRS signal by using the wavelet transform, and then suppress the wavelet energy of the contaminated time-frequency points. Finally, we transform the signal back to a time series. We validated the method by using simulation and real data at both task- and resting-state. The results showed that our method can effectively remove the global physiological noise from the fNIRS signal and improve the spatial specificity of the task activation and the resting-state functional connectivity pattern.
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Affiliation(s)
- Lian Duan
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
- These authors have contributed equally to this work
| | - Ziping Zhao
- College of Computer and Information Engineering, Tianjin Normal University, Tianjin, China
- These authors have contributed equally to this work
| | - Yongling Lin
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
| | - Xiaoyan Wu
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
| | - Yuejia Luo
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Pengfei Xu
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
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37
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Gerega A, Milej D, Weigl W, Kacprzak M, Liebert A. Multiwavelength time-resolved near-infrared spectroscopy of the adult head: assessment of intracerebral and extracerebral absorption changes. BIOMEDICAL OPTICS EXPRESS 2018; 9:2974-2993. [PMID: 29984079 PMCID: PMC6033559 DOI: 10.1364/boe.9.002974] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2018] [Revised: 04/27/2018] [Accepted: 05/17/2018] [Indexed: 05/23/2023]
Abstract
An optical technique based on diffuse reflectance measurement combined with indocyanine green (ICG) bolus tracking is extensively tested as a method for the clinical assessment of brain perfusion at the bedside. We report on multiwavelength time-resolved diffuse reflectance spectroscopy measurements carried out on the head of a healthy adult during the intravenous administration of a bolus of ICG. Intracerebral and extracerebral changes in absorption were estimated from an analysis of changes in statistical moments (total number of photons, mean time of flight and variance) of the distributions of times of flight (DTOF) of photons recorded simultaneously at 16 wavelengths from the range of 650-850 nm using sensitivity factors estimated by diffusion approximation based on a layered model of the studied medium. We validated the proposed method in a series of phantom experiments and in-vivo measurements. The results obtained show that changes in the concentration of the ICG can be assessed as a function of time of the experiment and depth in the tissue. Thus, the separation of changes in ICG concentration appearing in intra- and extracerebral tissues can be estimated from optical data acquired at a single source-detector pair of fibers/fiber bundles positioned on the surface of the head.
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Affiliation(s)
- Anna Gerega
- Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences Trojdena 4, 02-109 Warsaw, Poland
| | - Daniel Milej
- Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences Trojdena 4, 02-109 Warsaw, Poland
- Department of Medical Biophysics, Western University, London, Ontario N6A 5C1, Canada
- Imaging Division, Lawson Health Research Institute, London, Ontario N6A 4V2, Canada
| | - Wojciech Weigl
- Anesthesiology and Intensive Care, Department of Surgical Sciences, Uppsala University, Akademiska Hospital, 751 85 Uppsala, Sweden
| | - Michal Kacprzak
- Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences Trojdena 4, 02-109 Warsaw, Poland
| | - Adam Liebert
- Nalecz Institute of Biocybernetics and Biomedical Engineering Polish Academy of Sciences Trojdena 4, 02-109 Warsaw, Poland
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Rupawala M, Dehghani H, Lucas SJE, Tino P, Cruse D. Shining a Light on Awareness: A Review of Functional Near-Infrared Spectroscopy for Prolonged Disorders of Consciousness. Front Neurol 2018; 9:350. [PMID: 29872420 PMCID: PMC5972220 DOI: 10.3389/fneur.2018.00350] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 04/30/2018] [Indexed: 12/19/2022] Open
Abstract
Qualitative clinical assessments of the recovery of awareness after severe brain injury require an assessor to differentiate purposeful behavior from spontaneous behavior. As many such behaviors are minimal and inconsistent, behavioral assessments are susceptible to diagnostic errors. Advanced neuroimaging tools can bypass behavioral responsiveness and reveal evidence of covert awareness and cognition within the brains of some patients, thus providing a means for more accurate diagnoses, more accurate prognoses, and, in some instances, facilitated communication. The majority of reports to date have employed the neuroimaging methods of functional magnetic resonance imaging, positron emission tomography, and electroencephalography (EEG). However, each neuroimaging method has its own advantages and disadvantages (e.g., signal resolution, accessibility, etc.). Here, we describe a burgeoning technique of non-invasive optical neuroimaging—functional near-infrared spectroscopy (fNIRS)—and review its potential to address the clinical challenges of prolonged disorders of consciousness. We also outline the potential for simultaneous EEG to complement the fNIRS signal and suggest the future directions of research that are required in order to realize its clinical potential.
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Affiliation(s)
- Mohammed Rupawala
- Centre for Doctoral Training in Physical Sciences for Health, University of Birmingham, Birmingham, United Kingdom
| | - Hamid Dehghani
- Centre for Doctoral Training in Physical Sciences for Health, University of Birmingham, Birmingham, United Kingdom.,School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Samuel J E Lucas
- School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Peter Tino
- School of Computer Science, University of Birmingham, Birmingham, United Kingdom
| | - Damian Cruse
- School of Psychology, University of Birmingham, Birmingham, United Kingdom
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39
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Herold F, Wiegel P, Scholkmann F, Thiers A, Hamacher D, Schega L. Functional near-infrared spectroscopy in movement science: a systematic review on cortical activity in postural and walking tasks. NEUROPHOTONICS 2017; 4:041403. [PMID: 28924563 PMCID: PMC5538329 DOI: 10.1117/1.nph.4.4.041403] [Citation(s) in RCA: 169] [Impact Index Per Article: 24.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2017] [Accepted: 06/23/2017] [Indexed: 05/07/2023]
Abstract
Safe locomotion is a crucial aspect of human daily living that requires well-functioning motor control processes. The human neuromotor control of daily activities such as walking relies on the complex interaction of subcortical and cortical areas. Technical developments in neuroimaging systems allow the quantification of cortical activation during the execution of motor tasks. Functional near-infrared spectroscopy (fNIRS) seems to be a promising tool to monitor motor control processes in cortical areas in freely moving subjects. However, so far, there is no established standardized protocol regarding the application and data processing of fNIRS signals that limits the comparability among studies. Hence, this systematic review aimed to summarize the current knowledge about application and data processing in fNIRS studies dealing with walking or postural tasks. Fifty-six articles of an initial yield of 1420 publications were reviewed and information about methodology, data processing, and findings were extracted. Based on our results, we outline the recommendations with respect to the design and data processing of fNIRS studies. Future perspectives of measuring fNIRS signals in movement science are discussed.
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Affiliation(s)
- Fabian Herold
- Otto von Guericke University Magdeburg, Institute III, Department of Sport Science, Magdeburg, Germany
- Address all correspondence to: Fabian Herold, E-mail:
| | - Patrick Wiegel
- University of Freiburg, Department of Sport Science, Freiburg, Germany
| | - Felix Scholkmann
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zurich, Switzerland
| | - Angelina Thiers
- Otto von Guericke University Magdeburg, Institute III, Department of Sport Science, Magdeburg, Germany
| | - Dennis Hamacher
- Otto von Guericke University Magdeburg, Institute III, Department of Sport Science, Magdeburg, Germany
| | - Lutz Schega
- Otto von Guericke University Magdeburg, Institute III, Department of Sport Science, Magdeburg, Germany
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40
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Schecklmann M, Mann A, Langguth B, Ehlis AC, Fallgatter AJ, Haeussinger FB. The Temporal Muscle of the Head Can Cause Artifacts in Optical Imaging Studies with Functional Near-Infrared Spectroscopy. Front Hum Neurosci 2017; 11:456. [PMID: 28966580 PMCID: PMC5605559 DOI: 10.3389/fnhum.2017.00456] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2017] [Accepted: 08/28/2017] [Indexed: 11/24/2022] Open
Abstract
Background: Extracranial signals are the main source of noise in functional near-infrared spectroscopy (fNIRS) as light is penetrating the cortex but also skin and muscles of the head. Aim: Here we performed three experiments to investigate the contamination of fNIRS measurements by temporal muscle activity. Material and methods: For experiment 1, we provoked temporal muscle activity by instructing 31 healthy subjects to clench their teeth three times. We measured fNIRS signals over left temporal and frontal channels with an interoptode distance of 3 cm, in one short optode distance (SOD) channel (1 cm) and electromyography (EMG) over the edge of the temporal muscle. In experiment 2, we screened resting state fNIRS-fMRI (functional magnetic resonance imaging) data of one healthy subject for temporal muscle artifacts. In experiment 3, we screened a dataset of sound-evoked activity (n = 33) using bi-temporal probe-sets and systematically contrasted subjects presenting vs. not presenting artifacts and blocks/events contaminated or not contaminated with artifacts. Results: In experiment 1, we could demonstrate a hemodynamic-response-like increase in oxygenated (O2Hb) and decrease in deoxygenated (HHb) hemoglobin with a large amplitude and large spatial extent highly exceeding normal cortical activity. Correlations between EMG, SOD, and fNIRS artifact activity showed only limited evidence for associations on a group level with rather clear associations in a sub-group of subjects. The fNIRS-fMRI experiment showed that during the temporal muscle artifact, fNIRS is completely saturated by muscle oxygenation. Experiment 3 showed hints for contamination of sound-evoked oxygenation by the temporal muscle artifact. This was of low relevance in analyzing the whole sample. Discussion: Temporal muscle activity e.g., by clenching the teeth induces a large hemodynamic-like artifact in fNIRS measurements which should be avoided by specific subject instructions. Data should be screened for this artifact might be corrected by exclusion of contaminated blocks/events. The usefulness of established artifact correction methods should be evaluated in future studies. Conclusion: Temporal muscle activity, e.g., by clenching the teeth is one major source of noise in fNIRS measurements.
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Affiliation(s)
- Martin Schecklmann
- Department of Psychiatry and Psychotherapy, University of RegensburgRegensburg, Germany
| | - Alexander Mann
- Department of Psychiatry and Psychotherapy, Psychophysiology and Optical Imaging, University Hospital of TübingenTübingen, Germany
| | - Berthold Langguth
- Department of Psychiatry and Psychotherapy, University of RegensburgRegensburg, Germany
| | - Ann-Christine Ehlis
- Department of Psychiatry and Psychotherapy, Psychophysiology and Optical Imaging, University Hospital of TübingenTübingen, Germany
| | - Andreas J. Fallgatter
- Department of Psychiatry and Psychotherapy, Psychophysiology and Optical Imaging, University Hospital of TübingenTübingen, Germany
| | - Florian B. Haeussinger
- Department of Psychiatry and Psychotherapy, Psychophysiology and Optical Imaging, University Hospital of TübingenTübingen, Germany
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41
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Lee CW, Cooper RJ, Austin T. Diffuse optical tomography to investigate the newborn brain. Pediatr Res 2017; 82:376-386. [PMID: 28419082 DOI: 10.1038/pr.2017.107] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2016] [Accepted: 02/06/2017] [Indexed: 11/09/2022]
Abstract
Over the past 15 years, functional near-infrared spectroscopy (fNIRS) has emerged as a powerful technology for studying the developing brain. Diffuse optical tomography (DOT) is an extension of fNIRS that combines hemodynamic information from dense optical sensor arrays over a wide field of view. Using image reconstruction techniques, DOT can provide images of the hemodynamic correlates to neural function that are comparable to those produced by functional magnetic resonance imaging. This review article explains the principles of DOT, and highlights the growing literature on the use of DOT in the study of healthy development of the infant brain, and the study of novel pathophysiology in infants with brain injury. Current challenges, particularly around instrumentation and image reconstruction, will be discussed, as will the future of this growing field, with particular focus on whole-brain, time-resolved DOT.
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Affiliation(s)
- Chuen Wai Lee
- neoLAB, The Evelyn Perinatal Imaging Centre, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.,Department of Neonatology, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Robert J Cooper
- neoLAB, The Evelyn Perinatal Imaging Centre, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.,Department of Medical Physics and Biomedical Engineering, University College London, London, UK
| | - Topun Austin
- neoLAB, The Evelyn Perinatal Imaging Centre, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.,Department of Neonatology, The Rosie Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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42
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Cortical activation during balancing on a balance board. Hum Mov Sci 2017; 51:51-58. [DOI: 10.1016/j.humov.2016.11.002] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2016] [Revised: 07/26/2016] [Accepted: 11/07/2016] [Indexed: 01/28/2023]
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Abstract
Near-infrared spectroscopy (NIRS) was originally designed for clinical monitoring of tissue oxygenation, and it has also been developed into a useful tool in neuroimaging studies, with the so-called functional NIRS (fNIRS). With NIRS, cerebral activation is detected by measuring the cerebral hemoglobin (Hb), where however, the precise correlation between NIRS signal and neural activity remains to be fully understood. This can in part be attributed to the situation that NIRS signals are inherently subject to contamination by signals arising from extracerebral tissue. In recent years, several approaches have been investigated to distinguish between NIRS signals originating in cerebral tissue and signals originating in extracerebral tissue. Selective measurements of cerebral Hb will enable a further evolution of fNIRS. This chapter is divided into six sections: first a summary of the basic theory of NIRS, NIRS signals arising in the activated areas, correlations between NIRS signals and fMRI signals, correlations between NIRS signals and neural activities, and the influence of a variety of extracerebral tissue on NIRS signals and approaches to this issue are reviewed. Finally, future prospects of fNIRS are described.
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Affiliation(s)
- Y Hoshi
- Institute for Medical Photonics Research, Preeminent Medical Photonics Education & Research Center, Hamamatsu University School of Medicine, Hamamatsu, Japan.
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44
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Near-infrared spectroscopy determined cerebral oxygenation with eliminated skin blood flow in young males. J Clin Monit Comput 2015; 30:243-50. [DOI: 10.1007/s10877-015-9709-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2014] [Accepted: 05/22/2015] [Indexed: 01/01/2023]
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45
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Bonomini V, Zucchelli L, Re R, Ieva F, Spinelli L, Contini D, Paganoni A, Torricelli A. Linear regression models and k-means clustering for statistical analysis of fNIRS data. BIOMEDICAL OPTICS EXPRESS 2015; 6:615-30. [PMID: 25780751 PMCID: PMC4354588 DOI: 10.1364/boe.6.000615] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Revised: 01/17/2015] [Accepted: 01/22/2015] [Indexed: 05/10/2023]
Abstract
We propose a new algorithm, based on a linear regression model, to statistically estimate the hemodynamic activations in fNIRS data sets. The main concern guiding the algorithm development was the minimization of assumptions and approximations made on the data set for the application of statistical tests. Further, we propose a K-means method to cluster fNIRS data (i.e. channels) as activated or not activated. The methods were validated both on simulated and in vivo fNIRS data. A time domain (TD) fNIRS technique was preferred because of its high performances in discriminating cortical activation and superficial physiological changes. However, the proposed method is also applicable to continuous wave or frequency domain fNIRS data sets.
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Affiliation(s)
- Viola Bonomini
- MOX - Department of Mathematics, Politecnico di Milano, Milan,
Italy
- first two authors contributed equally to this work
| | - Lucia Zucchelli
- Dipartimento di Fisica, Politecnico di Milano, Milan,
Italy
- first two authors contributed equally to this work
| | - Rebecca Re
- Dipartimento di Fisica, Politecnico di Milano, Milan,
Italy
| | - Francesca Ieva
- Department of Mathematics “Federigo Enriques”, Università degli Studi di Milano, Milan,
Italy
| | | | - Davide Contini
- Dipartimento di Fisica, Politecnico di Milano, Milan,
Italy
| | - Anna Paganoni
- MOX - Department of Mathematics, Politecnico di Milano, Milan,
Italy
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46
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Tanaka Y, Ebihara A, Ikota M, Yamaguro T, Kamochi H, Kusaka G, Ishikawa M, Konno T, Mashiko T, Watanabe E. Early diagnosis of cerebral ischemia in cerebral vasospasm by oxygen-pulse near-infrared optical topography. ACTA NEUROCHIRURGICA. SUPPLEMENT 2015; 120:269-74. [PMID: 25366635 DOI: 10.1007/978-3-319-04981-6_45] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
PURPOSE Early diagnosis of vasospasm is a key factor in the choice of treatment after subarachnoid hemorrhage (SAH). However, a noninvasive method of diagnosing delayed ischemic neurological deficit (DIND) has not been established. We therefore propose a new method of diagnosing cerebral ischemia using near-infrared optical topography (OT) with oxygen inhalation. MATERIALS AND METHODS We used a 44-channel OT system that covers the bilateral front otemporoparietal areas to assess 29 patients who underwent surgery within 72 h of the onset of SAH. The patients inhaled room air followed by oxygen for 2 min, and then peripheral oxygen saturation (SpO₂) was continuously monitored at the index fingertip. The patients were assessed by N-isopropyl-p-[¹²³I]iodoamphetamine (IMP)-SPECT and OT on the same day. Ischemic findings were confirmed using principal component analysis with reference to the systemic SpO₂value. RESULTS Seven of 29 patients developed DIND. Evidence of ischemia was identified by OT in all seven of these patients before the onset of DIND. The OT and SPECT findings agreed in 27 (93 %) of the 29 patients. DISCUSSION AND CONCLUSIONS Our method might detect cerebral ischemia before the onset of DIND and thus be clinically useful for assessing cerebral ischemia with vasospasm.
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Affiliation(s)
- Yuichi Tanaka
- Department of Neurosurgery, Jichi Medical University Saitama Medical Center, Saitama-Ken, Japan,
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47
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Bauernfeind G, Wriessnegger SC, Daly I, Müller-Putz GR. Separating heart and brain: on the reduction of physiological noise from multichannel functional near-infrared spectroscopy (fNIRS) signals. J Neural Eng 2014; 11:056010. [PMID: 25111822 DOI: 10.1088/1741-2560/11/5/056010] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVE Functional near-infrared spectroscopy (fNIRS) is an emerging technique for the in vivo assessment of functional activity of the cerebral cortex as well as in the field of brain-computer interface (BCI) research. A common challenge for the utilization of fNIRS in these areas is a stable and reliable investigation of the spatio-temporal hemodynamic patterns. However, the recorded patterns may be influenced and superimposed by signals generated from physiological processes, resulting in an inaccurate estimation of the cortical activity. Up to now only a few studies have investigated these influences, and still less has been attempted to remove/reduce these influences. The present study aims to gain insights into the reduction of physiological rhythms in hemodynamic signals (oxygenated hemoglobin (oxy-Hb), deoxygenated hemoglobin (deoxy-Hb)). APPROACH We introduce the use of three different signal processing approaches (spatial filtering, a common average reference (CAR) method; independent component analysis (ICA); and transfer function (TF) models) to reduce the influence of respiratory and blood pressure (BP) rhythms on the hemodynamic responses. MAIN RESULTS All approaches produce large reductions in BP and respiration influences on the oxy-Hb signals and, therefore, improve the contrast-to-noise ratio (CNR). In contrast, for deoxy-Hb signals CAR and ICA did not improve the CNR. However, for the TF approach, a CNR-improvement in deoxy-Hb can also be found. SIGNIFICANCE The present study investigates the application of different signal processing approaches to reduce the influences of physiological rhythms on the hemodynamic responses. In addition to the identification of the best signal processing method, we also show the importance of noise reduction in fNIRS data.
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Affiliation(s)
- G Bauernfeind
- Institute for Knowledge Discovery, Graz University of Technology, A-8010 Graz, Austria
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48
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Selb J, Boas DA, Chan ST, Evans KC, Buckley EM, Carp SA. Sensitivity of near-infrared spectroscopy and diffuse correlation spectroscopy to brain hemodynamics: simulations and experimental findings during hypercapnia. NEUROPHOTONICS 2014; 1:015005. [PMID: 25453036 PMCID: PMC4247161 DOI: 10.1117/1.nph.1.1.015005] [Citation(s) in RCA: 104] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/10/2014] [Revised: 06/12/2014] [Accepted: 06/25/2014] [Indexed: 05/18/2023]
Abstract
Near-infrared spectroscopy (NIRS) and diffuse correlation spectroscopy (DCS) are two diffuse optical technologies for brain imaging that are sensitive to changes in hemoglobin concentrations and blood flow, respectively. Measurements for both modalities are acquired on the scalp, and therefore hemodynamic processes in the extracerebral vasculature confound the interpretation of cortical hemodynamic signals. The sensitivity of NIRS to the brain versus the extracerebral tissue and the contrast-to-noise ratio (CNR) of NIRS to cerebral hemodynamic responses have been well characterized, but the same has not been evaluated for DCS. This is important to assess in order to understand their relative capabilities in measuring cerebral physiological changes. We present Monte Carlo simulations on a head model that demonstrate that the relative brain-to-scalp sensitivity is about three times higher for DCS (0.3 at 3 cm) than for NIRS (0.1 at 3 cm). However, because DCS has higher levels of noise due to photon-counting detection, the CNR is similar for both modalities in response to a physiologically realistic simulation of brain activation. Even so, we also observed higher CNR of the hemodynamic response during graded hypercapnia in adult subjects with DCS than with NIRS.
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Affiliation(s)
- Juliette Selb
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Optics Division, 149 13th Street, Charlestown, Massachusetts 02129, United States
- Address all correspondence to: Juliette Selb, E-mail:
| | - David A. Boas
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Optics Division, 149 13th Street, Charlestown, Massachusetts 02129, United States
| | - Suk-Tak Chan
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Optics Division, 149 13th Street, Charlestown, Massachusetts 02129, United States
| | - Karleyton C. Evans
- Massachusetts General Hospital, Harvard Medical School, Department of Psychiatry, 149 13th Street, Charlestown, Massachusetts 02129, United States
| | - Erin M. Buckley
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Optics Division, 149 13th Street, Charlestown, Massachusetts 02129, United States
| | - Stefan A. Carp
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Department of Radiology, Optics Division, 149 13th Street, Charlestown, Massachusetts 02129, United States
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49
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Jelzow A, Wabnitz H, Tachtsidis I, Kirilina E, Brühl R, Macdonald R. Separation of superficial and cerebral hemodynamics using a single distance time-domain NIRS measurement. BIOMEDICAL OPTICS EXPRESS 2014; 5:1465-82. [PMID: 24877009 PMCID: PMC4026903 DOI: 10.1364/boe.5.001465] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/23/2014] [Revised: 03/13/2014] [Accepted: 03/24/2014] [Indexed: 05/09/2023]
Abstract
In functional near-infrared spectroscopy (fNIRS) superficial hemodynamics can mask optical signals related to brain activity. We present a method to separate superficial and cerebral absorption changes based on the analysis of changes in moments of time-of-flight distributions and a two-layered model. The related sensitivity factors were calculated from individual optical properties. The method was validated on a two-layer liquid phantom. Absorption changes in the lower layer were retrieved with an accuracy better than 20%. The method was successfully applied to in vivo data and compared to the reconstruction of homogeneous absorption changes.
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Affiliation(s)
- Alexander Jelzow
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2-12, 10587, Berlin, Germany
| | - Heidrun Wabnitz
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2-12, 10587, Berlin, Germany
| | - Ilias Tachtsidis
- University College London, Dept. Med. Physics and Bioengineering, Gower Street, London WC1E 6BT, UK
| | | | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2-12, 10587, Berlin, Germany
| | - Rainer Macdonald
- Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2-12, 10587, Berlin, Germany
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50
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Statistical analysis of fNIRS data: A comprehensive review. Neuroimage 2014; 85 Pt 1:72-91. [DOI: 10.1016/j.neuroimage.2013.06.016] [Citation(s) in RCA: 248] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2013] [Revised: 04/20/2013] [Accepted: 06/07/2013] [Indexed: 11/16/2022] Open
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