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Zhang M, Yin Z, Zhang X, Zhang H, Bao M, Xuan B. Neural mechanisms distinguishing two types of cooperative problem-solving approaches: An fNIRS hyperscanning study. Neuroimage 2024; 291:120587. [PMID: 38548038 DOI: 10.1016/j.neuroimage.2024.120587] [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: 12/04/2023] [Revised: 03/18/2024] [Accepted: 03/25/2024] [Indexed: 04/13/2024] Open
Abstract
Collaborative cooperation (CC) and division of labor cooperation (DLC) are two prevalent forms of cooperative problem-solving approaches in daily life. Despite extensive research on the neural mechanisms underlying cooperative problem-solving approaches, a notable gap exists between the neural processes that support CC and DLC. The present study utilized a functional near-infrared spectroscopy (fNIRS) hyperscanning technique along with a classic cooperative tangram puzzle task to investigate the neural mechanisms engaged by both friends and stranger dyads during CC versus DLC. The key findings of this study were as follows: (1) Dyads exhibited superior behavioral performance in the DLC task than in the CC task. The CC task bolstered intra-brain functional connectivity and inter-brain synchrony (IBS) in regions linked to the mirror neuron system (MNS), spatial perception (SP) and cognitive control. (2) Friend dyads showed stronger IBS in brain regions associated with the MNS than stranger dyads. (3) Perspective-taking predicted not only dyads' behavioral performance in the CC task but also their IBS in brain regions associated with SP during the DLC task. Taken together, these findings elucidate the divergent behavioral performance and neural connection patterns between the two cooperative problem-solving approaches. This study provides novel insights into the various neurocognitive processes underlying flexible coordination strategies in real-world cooperative contexts.
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Affiliation(s)
- Mingming Zhang
- School of Psychology, Shanghai Normal University, 100, Guilin Road, Shanghai 200234, China
| | - Zijun Yin
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China
| | - Xue Zhang
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China
| | - Hui Zhang
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China
| | - Mingjing Bao
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China
| | - Bin Xuan
- School of Educational Science, Anhui Normal University, 2, Beijing Middle Road, Wuhu 241000, China.
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2
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Réveillé C, Vergotte G, Perrey S, Bosselut G. Using interbrain synchrony to study teamwork: A systematic review and meta-analysis. Neurosci Biobehav Rev 2024; 159:105593. [PMID: 38373643 DOI: 10.1016/j.neubiorev.2024.105593] [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: 11/24/2023] [Revised: 01/19/2024] [Accepted: 02/14/2024] [Indexed: 02/21/2024]
Abstract
It has been proposed that interbrain synchrony (IBS) may help to elucidate the neural mechanisms underpinning teamwork. As hyperscanning studies have provided abundant findings on IBS in team environments, the current review aims to synthesize the findings of hyperscanning studies in a way that is relevant to the teamwork research. A systematic review was conducted. Included studies were classified according to the IPO (i.e. input, process, output) model of teamwork. Three multi-level meta-analyses were performed to quantify the associations between IBS and the three IPO variables. The methodology followed PRISMA guidelines and the protocol was pre-registered (https://osf.io/7h8sa/). Of the 229 studies, 41 were included, representing 1326 teams. The three meta-analyses found statistically significant positive effects, indicating a positive association between IBS and the three IPO teamwork variables. This study provides evidence that IBS is a relevant measure of the teamwork process and argues for the continued use of IBS to study teamwork.
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Affiliation(s)
- Coralie Réveillé
- EuroMov Digital Health in Motion (Univ Montpellier, IMT Mines d'Alès), 700 avenue du Pic Saint Loup, Montpellier 34090, France.
| | - Grégoire Vergotte
- EuroMov Digital Health in Motion (Univ Montpellier, IMT Mines d'Alès), 700 avenue du Pic Saint Loup, Montpellier 34090, France
| | - Stéphane Perrey
- EuroMov Digital Health in Motion (Univ Montpellier, IMT Mines d'Alès), 700 avenue du Pic Saint Loup, Montpellier 34090, France
| | - Grégoire Bosselut
- EuroMov Digital Health in Motion (Univ Montpellier, IMT Mines d'Alès), 700 avenue du Pic Saint Loup, Montpellier 34090, France
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3
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Mark JA, Curtin A, Kraft AE, Ziegler MD, Ayaz H. Mental workload assessment by monitoring brain, heart, and eye with six biomedical modalities during six cognitive tasks. FRONTIERS IN NEUROERGONOMICS 2024; 5:1345507. [PMID: 38533517 PMCID: PMC10963413 DOI: 10.3389/fnrgo.2024.1345507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Accepted: 02/15/2024] [Indexed: 03/28/2024]
Abstract
Introduction The efficiency and safety of complex high precision human-machine systems such as in aerospace and robotic surgery are closely related to the cognitive readiness, ability to manage workload, and situational awareness of their operators. Accurate assessment of mental workload could help in preventing operator error and allow for pertinent intervention by predicting performance declines that can arise from either work overload or under stimulation. Neuroergonomic approaches based on measures of human body and brain activity collectively can provide sensitive and reliable assessment of human mental workload in complex training and work environments. Methods In this study, we developed a new six-cognitive-domain task protocol, coupling it with six biomedical monitoring modalities to concurrently capture performance and cognitive workload correlates across a longitudinal multi-day investigation. Utilizing two distinct modalities for each aspect of cardiac activity (ECG and PPG), ocular activity (EOG and eye-tracking), and brain activity (EEG and fNIRS), 23 participants engaged in four sessions over 4 weeks, performing tasks associated with working memory, vigilance, risk assessment, shifting attention, situation awareness, and inhibitory control. Results The results revealed varying levels of sensitivity to workload within each modality. While certain measures exhibited consistency across tasks, neuroimaging modalities, in particular, unveiled meaningful differences between task conditions and cognitive domains. Discussion This is the first comprehensive comparison of these six brain-body measures across multiple days and cognitive domains. The findings underscore the potential of wearable brain and body sensing methods for evaluating mental workload. Such comprehensive neuroergonomic assessment can inform development of next generation neuroadaptive interfaces and training approaches for more efficient human-machine interaction and operator skill acquisition.
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Affiliation(s)
- Jesse A. Mark
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Adrian Curtin
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA, United States
| | - Amanda E. Kraft
- Advanced Technology Laboratories, Lockheed Martin, Arlington, VA, United States
| | - Matthias D. Ziegler
- Advanced Technology Laboratories, Lockheed Martin, Arlington, VA, United States
| | - Hasan Ayaz
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA, United States
- Department of Psychological and Brain Sciences, College of Arts and Sciences, Drexel University, Philadelphia, PA, United States
- Drexel Solutions Institute, Drexel University, Philadelphia, PA, United States
- A. J. Drexel Autism Institute, Drexel University, Philadelphia, PA, United States
- Department of Family and Community Health, University of Pennsylvania, Philadelphia, PA, United States
- Center for Injury Research and Prevention, Children's Hospital of Philadelphia, Philadelphia, PA, United States
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4
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McLinden J, Rahimi N, Kumar C, Krusienski DJ, Shao M, Spencer KM, Shahriari Y. Investigation of electro-vascular phase-amplitude coupling during an auditory task. Comput Biol Med 2024; 169:107902. [PMID: 38159399 DOI: 10.1016/j.compbiomed.2023.107902] [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: 09/06/2023] [Revised: 11/24/2023] [Accepted: 12/23/2023] [Indexed: 01/03/2024]
Abstract
Multimodal neuroimaging using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) provides complementary views of cortical processes, including those related to auditory processing. However, current multimodal approaches often overlook potential insights that can be gained from nonlinear interactions between electrical and hemodynamic signals. Here, we explore electro-vascular phase-amplitude coupling (PAC) between low-frequency hemodynamic and high-frequency electrical oscillations during an auditory task. We further apply a temporally embedded canonical correlation analysis (tCCA)-general linear model (GLM)-based correction approach to reduce the possible effect of systemic physiology on fNIRS recordings. Before correction, we observed significant PAC between fNIRS and broadband EEG in the frontal region (p ≪ 0.05), β (p ≪ 0.05) and γ (p = 0.010) in the left temporal/temporoparietal (left auditory; LA) region, and γ (p = 0.032) in the right temporal/temporoparietal (right auditory; RA) region across the entire dataset. Significant differences in PAC across conditions (task versus silence) were observed in LA (p = 0.023) and RA (p = 0.049) γ sub-bands and in lower frequency (5-20 Hz) frontal activity (p = 0.005). After correction, significant fNIRS-γ-band PAC was observed in the frontal (p = 0.021) and LA (p = 0.025) regions, while fNIRS-α (p = 0.003) and fNIRS-β (p = 0.041) PAC were observed in RA. Decreased frontal γ-band (p = 0.008) and increased β-band (p ≪ 0.05) PAC were observed during the task. These outcomes represent the first characterization of electro-vascular PAC between fNIRS and EEG signals during an auditory task, providing insights into electro-vascular coupling in auditory processing.
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Affiliation(s)
- J McLinden
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA
| | - N Rahimi
- Department of Computer and Information Science, University of Massachusetts Dartmouth, MA, USA
| | - C Kumar
- Department of Computer and Information Science, University of Massachusetts Dartmouth, MA, USA
| | - D J Krusienski
- Department of Biomedical Engineering, Virginia Commonwealth University, Richmond, VA, USA
| | - M Shao
- Department of Computer and Information Science, University of Massachusetts Dartmouth, MA, USA
| | - K M Spencer
- Department of Psychiatry, VA Boston Healthcare System and Harvard Medical School, Boston, MA, USA
| | - Y Shahriari
- Department of Electrical, Computer, and Biomedical Engineering, University of Rhode Island, Kingston, RI, USA.
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Yang D, Ghafoor U, Eggebrecht AT, Hong KS. Effectiveness assessment of repetitive transcranial alternating current stimulation with concurrent EEG and fNIRS measurement. Health Inf Sci Syst 2023; 11:35. [PMID: 37545487 PMCID: PMC10397167 DOI: 10.1007/s13755-023-00233-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Accepted: 07/11/2023] [Indexed: 08/08/2023] Open
Abstract
Transcranial alternating current stimulation (tACS) exhibits the capability to interact with endogenous brain oscillations using an external low-intensity sinusoidal current and influences cerebral function. Despite its potential benefits, the physiological mechanisms and effectiveness of tACS are currently a subject of debate and disagreement. The aims of our study are to (i) evaluate the neurological and behavioral impact of tACS by conducting repetitive sham-controlled experiments and (ii) propose criteria to evaluate effectiveness, which can serve as a benchmark to determine optimal individual-based tACS protocols. In this study, 15 healthy adults participated in the experiment over two visiting: sham and tACS (i.e., 5 Hz, 1 mA). During each visit, we used multimodal recordings of the participants' brain, including simultaneous electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), along with a working memory (WM) score to quantify neurological effects and cognitive changes immediately after each repetitive sham/tACS session. Our results indicate increased WM scores, hemodynamic response strength, and EEG power in theta and delta bands both during and after the tACS period. Additionally, the observed effects do not increase with prolonged stimulation time, as the effects plateau towards the end of the experiment. In conclusion, our proposed closed-loop scheme offers a promising advance for evaluating the effectiveness of tACS during the stimulation session. Specifically, the assessment criteria use participant-specific brain-based signals along with a behavioral output. Moreover, we propose a feedback efficacy score that can aid in determining the optimal stimulation duration based on a participant-specific brain state, thereby preventing the risk of overstimulation.
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Affiliation(s)
- Dalin Yang
- School of Mechanical Engineering, Pusan National University, Busan, 46241 Republic of Korea
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63100 USA
| | - Usman Ghafoor
- School of Mechanical Engineering, Pusan National University, Busan, 46241 Republic of Korea
| | - Adam Thomas Eggebrecht
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO 63100 USA
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63130 USA
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Busan, 46241 Republic of Korea
- Institute for Future, School of Automation, Qingdao University, Qingdao, 266071 Shandong China
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Ali MU, Zafar A, Kallu KD, Yaqub MA, Masood H, Hong KS, Bhutta MR. An Isolated CNN Architecture for Classification of Finger-Tapping Tasks Using Initial Dip Images: A Functional Near-Infrared Spectroscopy Study. Bioengineering (Basel) 2023; 10:810. [PMID: 37508837 PMCID: PMC10376657 DOI: 10.3390/bioengineering10070810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 06/30/2023] [Accepted: 06/30/2023] [Indexed: 07/30/2023] Open
Abstract
This work investigates the classification of finger-tapping task images constructed for the initial dip duration of hemodynamics (HR) associated with the small brain area of the left motor cortex using functional near-infrared spectroscopy (fNIRS). Different layers (i.e., 16-layers, 19-layers, 22-layers, and 25-layers) of isolated convolutional neural network (CNN) designed from scratch are tested to classify the right-hand thumb and little finger-tapping tasks. Functional t-maps of finger-tapping tasks (thumb, little) were constructed for various durations (0.5 to 4 s with a uniform interval of 0.5 s) for the initial dip duration using a three gamma functions-based designed HR function. The results show that the 22-layered isolated CNN model yielded the highest classification accuracy of 89.2% with less complexity in classifying the functional t-maps of thumb and little fingers associated with the same small brain area using the initial dip. The results further demonstrated that the active brain area of the two tapping tasks from the same small brain area are highly different and well classified using functional t-maps of the initial dip (0.5 to 4 s) compared to functional t-maps generated for delayed HR (14 s). This study shows that the images constructed for initial dip duration can be helpful in the future for fNIRS-based diagnosis or cortical analysis of abnormal cerebral oxygen exchange in patients.
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Affiliation(s)
- Muhammad Umair Ali
- Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Republic of Korea
| | - Amad Zafar
- Department of Intelligent Mechatronics Engineering, Sejong University, Seoul 05006, Republic of Korea
| | - Karam Dad Kallu
- Department of Robotics and Intelligent Machine Engineering (RIME), School of Mechanical and Manufacturing Engineering (SMME), National University of Sciences and Technology (NUST), H-12, Islamabad 44000, Pakistan
| | - M Atif Yaqub
- ICFO-Institut de Ciències Fotòniques the Barcelona Institute of Science and Technology, 08860 Castelldefels, Spain
| | - Haris Masood
- Electrical Engineering Department, Wah Engineering College, University of Wah, Wah Cantt 47040, Pakistan
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, 2 Busandaehak-ro, Geumjeong-gu, Busan 46241, Republic of Korea
- Institute for Future, School of Automation, Qingdao University, Qingdao 266071, China
| | - Muhammad Raheel Bhutta
- Department of Electrical and Computer Engineering, University of UTAH Asia Campus, Incheon 21985, Republic of Korea
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Perpetuini D, Günal M, Chiou N, Koyejo S, Mathewson K, Low KA, Fabiani M, Gratton G, Chiarelli AM. Fast Optical Signals for Real-Time Retinotopy and Brain Computer Interface. Bioengineering (Basel) 2023; 10:553. [PMID: 37237623 PMCID: PMC10215195 DOI: 10.3390/bioengineering10050553] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 04/28/2023] [Accepted: 05/03/2023] [Indexed: 05/28/2023] Open
Abstract
A brain-computer interface (BCI) allows users to control external devices through brain activity. Portable neuroimaging techniques, such as near-infrared (NIR) imaging, are suitable for this goal. NIR imaging has been used to measure rapid changes in brain optical properties associated with neuronal activation, namely fast optical signals (FOS) with good spatiotemporal resolution. However, FOS have a low signal-to-noise ratio, limiting their BCI application. Here FOS were acquired with a frequency-domain optical system from the visual cortex during visual stimulation consisting of a rotating checkerboard wedge, flickering at 5 Hz. We used measures of photon count (Direct Current, DC light intensity) and time of flight (phase) at two NIR wavelengths (690 nm and 830 nm) combined with a machine learning approach for fast estimation of visual-field quadrant stimulation. The input features of a cross-validated support vector machine classifier were computed as the average modulus of the wavelet coherence between each channel and the average response among all channels in 512 ms time windows. An above chance performance was obtained when differentiating visual stimulation quadrants (left vs. right or top vs. bottom) with the best classification accuracy of ~63% (information transfer rate of ~6 bits/min) when classifying the superior and inferior stimulation quadrants using DC at 830 nm. The method is the first attempt to provide generalizable retinotopy classification relying on FOS, paving the way for the use of FOS in real-time BCI.
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Affiliation(s)
- David Perpetuini
- Department of Neuroscience, Imaging and Clinical Sciences, G. D’Annunzio University of Chieti-Pescara, 66100 Chieti, Italy
- Institute for Advanced Biomedical Technologies, G. D’Annunzio University of Chieti-Pescara, 66100 Chieti, Italy
| | - Mehmet Günal
- Beckman Institute, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA
| | - Nicole Chiou
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Sanmi Koyejo
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Kyle Mathewson
- Department of Psychology, Faculty of Science, University of Alberta, Edmonton, AB T6G 2R3, Canada
| | - Kathy A. Low
- Beckman Institute, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA
| | - Monica Fabiani
- Beckman Institute, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA
- Psychology Department, University of Illinois at Urbana Champaign, Champaign, IL 61820, USA
| | - Gabriele Gratton
- Beckman Institute, University of Illinois at Urbana Champaign, Urbana, IL 61801, USA
- Psychology Department, University of Illinois at Urbana Champaign, Champaign, IL 61820, USA
| | - Antonio Maria Chiarelli
- Department of Neuroscience, Imaging and Clinical Sciences, G. D’Annunzio University of Chieti-Pescara, 66100 Chieti, Italy
- Institute for Advanced Biomedical Technologies, G. D’Annunzio University of Chieti-Pescara, 66100 Chieti, Italy
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Tierradentro-García LO, Saade-Lemus S, Freeman C, Kirschen M, Huang H, Vossough A, Hwang M. Cerebral Blood Flow of the Neonatal Brain after Hypoxic-Ischemic Injury. Am J Perinatol 2023; 40:475-488. [PMID: 34225373 PMCID: PMC8974293 DOI: 10.1055/s-0041-1731278] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Hypoxic-ischemic encephalopathy (HIE) in infants can have long-term adverse neurodevelopmental effects and markedly reduce quality of life. Both the initial hypoperfusion and the subsequent rapid reperfusion can cause deleterious effects in brain tissue. Cerebral blood flow (CBF) assessment in newborns with HIE can help detect abnormalities in brain perfusion to guide therapy and prognosticate patient outcomes. STUDY DESIGN The review will provide an overview of the pathophysiological implications of CBF derangements in neonatal HIE, current and emerging techniques for CBF quantification, and the potential to utilize CBF as a physiologic target in managing neonates with acute HIE. CONCLUSION The alterations of CBF in infants during hypoxia-ischemia have been studied by using different neuroimaging techniques, including nitrous oxide and xenon clearance, transcranial Doppler ultrasonography, contrast-enhanced ultrasound, arterial spin labeling MRI, 18F-FDG positron emission tomography, near-infrared spectroscopy (NIRS), functional NIRS, and diffuse correlation spectroscopy. Consensus is lacking regarding the clinical significance of CBF estimations detected by these different modalities. Heterogeneity in the imaging modality used, regional versus global estimations of CBF, time for the scan, and variables impacting brain perfusion and cohort clinical characteristics should be considered when translating the findings described in the literature to routine practice and implementation of therapeutic interventions. KEY POINTS · Hypoxic-ischemic injury in infants can result in adverse long-term neurologic sequelae.. · Cerebral blood flow is a useful biomarker in neonatal hypoxic-ischemic injury.. · Imaging modality, variables affecting cerebral blood flow, and patient characteristics affect cerebral blood flow assessment..
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Affiliation(s)
| | - Sandra Saade-Lemus
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Neurology, Brigham and Women’s Hospital & Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts
| | - Colbey Freeman
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Matthew Kirschen
- Department of Anesthesiology and Critical Care Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Hao Huang
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Arastoo Vossough
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Misun Hwang
- Department of Radiology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
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Zhang F, Reid A, Schroeder A, Ding L, Yuan H. Controlling jaw-related motion artifacts in functional near-infrared spectroscopy. J Neurosci Methods 2023; 388:109810. [PMID: 36738847 PMCID: PMC10681683 DOI: 10.1016/j.jneumeth.2023.109810] [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: 08/30/2022] [Revised: 12/29/2022] [Accepted: 01/30/2023] [Indexed: 02/05/2023]
Abstract
BACKGROUND Functional near-infrared spectroscopy (fNIRS) as a non-invasive optical neuroimaging technique has demonstrated great potential in monitoring cerebral activity. Due to its portability and compatibility with medical implants, fNIRS has seen increasing applications in studying the hearing, language and cognitive functions. However, fNIRS is susceptible to artifacts related to jaw movements, such as teeth clenching, swallowing and speaking, which affect recordings over the temporal, parietal and frontal/prefrontal cortices. NEW METHOD We investigated two new approaches to control the jaw-related motion artifacts, an individually customized bite bar apparatus and a denoising algorithm namely PCA-GLM based on multi-channel fNIRS recordings from long-separation and short-separation montage. We first recorded data while subjects performed a clenching task, then an auditory task and a resting-state task with and without the bite bar. RESULTS Our results have shown that jaw clenching can introduce spurious, task-evoked-like responses in fNIRS signals. A bite bar customized for each participant effectively suppressed the movement-related activities in fNIRS, at both task and resting-state conditions. Moreover, the bite bar and the PCA-GLM denoising method are shown to improve auditory responses, by significantly reducing the within-subject standard deviation, increasing the task-related contrast-to-noise ratio, and yielding stronger activations to the auditory stimuli. COMPARISON WITH EXISTING METHOD(S) The current study has demonstrated a novel method to control the jaw-related motion artifacts in fNIRS signals. CONCLUSIONS Our method will benefit the study of the hearing, language and cognitive functions in normal healthy subjects and patients.
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Affiliation(s)
- Fan Zhang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Adaira Reid
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Alissa Schroeder
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA; Institute for Biomedical Engineering, Science and Technology, University of Oklahoma, Norman, OK 73019, USA
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK 73019, USA; Institute for Biomedical Engineering, Science and Technology, University of Oklahoma, Norman, OK 73019, USA.
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10
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Akila V, Johnvictor AC. Functional near infrared spectroscopy for brain functional connectivity analysis: A graph theoretic approach. Heliyon 2023; 9:e15002. [PMID: 37082646 PMCID: PMC10112026 DOI: 10.1016/j.heliyon.2023.e15002] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 03/13/2023] [Accepted: 03/23/2023] [Indexed: 03/31/2023] Open
Abstract
Background Functional Near-Infrared Spectroscopy is an optical brain monitoring technique which uses NIRS to perform functional neuroimaging. It uses near-infrared light for measuring brain activity and to estimate the cortical hemodynamic activity in the brain due to motor activity. Functional NIRS measures the changes in oxygen levels in oxygenated and deoxygenated hemoglobin by optical absorption. One of the main challenges in the analysis of fNIRS signals is the signal degradation due to the interference from noise and artifacts from multiple sources. Methods In this context, this research aims to analyze the connectivity between different regions of the brain using graph theory and hence the geometrical association of brain networks in terms of functional parameters. In this study, the impact of two noise removal processes (CBSI and TDDR), along with two types of correlation fNIRS such as Pearson's Correlation (PC), and Cross Correlation (CC) and various whole-brain network architectures on the reproducibility of graph measurements for individual participants has been carefully examined for different densities ranging from 5% to 50%.The graph measures' repeatability at the individual level was studied using the test-retest variability (TRT). Results The test-retest variability for global measurements in binary networks was substantially large at low densities, regardless of the noise removal method or the kind of correlation. Very low test -reset values are observed for weighted networks and great reproducibility for measures of the entire graph. When comparing the test-retest values for various methods, the kind of correlation, the absolute value of the correlation, and the weight calculation method on the raw correlation value all had significant major effects. Conclusion Based on a weighted network with the absolute cross correlation functioning as the weight, this study revealed that normalized global graph measurements were reliable. The node definition techniques that were utilized to remove noise were not essential for the normalized graph measures to be reproducible.
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11
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Bonilauri A, Sangiuliano Intra F, Baglio F, Baselli G. Impact of Anatomical Variability on Sensitivity Profile in fNIRS-MRI Integration. SENSORS (BASEL, SWITZERLAND) 2023; 23:2089. [PMID: 36850685 PMCID: PMC9962997 DOI: 10.3390/s23042089] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/06/2023] [Accepted: 02/07/2023] [Indexed: 06/18/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is an important non-invasive technique used to monitor cortical activity. However, a varying sensitivity of surface channels vs. cortical structures may suggest integrating the fNIRS with the subject-specific anatomy (SSA) obtained from routine MRI. Actual processing tools permit the computation of the SSA forward problem (i.e., cortex to channel sensitivity) and next, a regularized solution of the inverse problem to map the fNIRS signals onto the cortex. The focus of this study is on the analysis of the forward problem to quantify the effect of inter-subject variability. Thirteen young adults (six males, seven females, age 29.3 ± 4.3) underwent both an MRI scan and a motor grasping task with a continuous wave fNIRS system of 102 measurement channels with optodes placed according to a 10/5 system. The fNIRS sensitivity profile was estimated using Monte Carlo simulations on each SSA and on three major atlases (i.e., Colin27, ICBM152 and FSAverage) for comparison. In each SSA, the average sensitivity curves were obtained by aligning the 102 channels and segmenting them by depth quartiles. The first quartile (depth < 11.8 (0.7) mm, median (IQR)) covered 0.391 (0.087)% of the total sensitivity profile, while the second one (depth < 13.6 (0.7) mm) covered 0.292 (0.009)%, hence indicating that about 70% of the signal was from the gyri. The sensitivity bell-shape was broad in the source-detector direction (20.953 (5.379) mm FWHM, first depth quartile) and steeper in the transversal one (6.082 (2.086) mm). The sensitivity of channels vs. different cortical areas based on SSA were analyzed finding high dispersions among subjects and large differences with atlas-based evaluations. Moreover, the inverse cortical mapping for the grasping task showed differences between SSA and atlas based solutions. In conclusion, integration with MRI SSA can significantly improve fNIRS interpretation.
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Affiliation(s)
- Augusto Bonilauri
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| | | | - Francesca Baglio
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
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12
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Soloukey S, Vincent AJPE, Smits M, De Zeeuw CI, Koekkoek SKE, Dirven CMF, Kruizinga P. Functional imaging of the exposed brain. Front Neurosci 2023; 17:1087912. [PMID: 36845427 PMCID: PMC9947297 DOI: 10.3389/fnins.2023.1087912] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 01/19/2023] [Indexed: 02/11/2023] Open
Abstract
When the brain is exposed, such as after a craniotomy in neurosurgical procedures, we are provided with the unique opportunity for real-time imaging of brain functionality. Real-time functional maps of the exposed brain are vital to ensuring safe and effective navigation during these neurosurgical procedures. However, current neurosurgical practice has yet to fully harness this potential as it pre-dominantly relies on inherently limited techniques such as electrical stimulation to provide functional feedback to guide surgical decision-making. A wealth of especially experimental imaging techniques show unique potential to improve intra-operative decision-making and neurosurgical safety, and as an added bonus, improve our fundamental neuroscientific understanding of human brain function. In this review we compare and contrast close to twenty candidate imaging techniques based on their underlying biological substrate, technical characteristics and ability to meet clinical constraints such as compatibility with surgical workflow. Our review gives insight into the interplay between technical parameters such sampling method, data rate and a technique's real-time imaging potential in the operating room. By the end of the review, the reader will understand why new, real-time volumetric imaging techniques such as functional Ultrasound (fUS) and functional Photoacoustic Computed Tomography (fPACT) hold great clinical potential for procedures in especially highly eloquent areas, despite the higher data rates involved. Finally, we will highlight the neuroscientific perspective on the exposed brain. While different neurosurgical procedures ask for different functional maps to navigate surgical territories, neuroscience potentially benefits from all these maps. In the surgical context we can uniquely combine healthy volunteer studies, lesion studies and even reversible lesion studies in in the same individual. Ultimately, individual cases will build a greater understanding of human brain function in general, which in turn will improve neurosurgeons' future navigational efforts.
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Affiliation(s)
- Sadaf Soloukey
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands,Department of Neurosurgery, Erasmus MC, Rotterdam, Netherlands
| | | | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, Rotterdam, Netherlands
| | - Chris I. De Zeeuw
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands,Netherlands Institute for Neuroscience, Royal Dutch Academy for Arts and Sciences, Amsterdam, Netherlands
| | | | | | - Pieter Kruizinga
- Department of Neuroscience, Erasmus MC, Rotterdam, Netherlands,*Correspondence: Pieter Kruizinga,
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Zhang F, Khan AF, Ding L, Yuan H. Network organization of resting-state cerebral hemodynamics and their aliasing contributions measured by functional near-infrared spectroscopy. J Neural Eng 2023; 20:016012. [PMID: 36535032 PMCID: PMC9855663 DOI: 10.1088/1741-2552/acaccb] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 12/05/2022] [Accepted: 12/19/2022] [Indexed: 12/23/2022]
Abstract
Objective. Spontaneous fluctuations of cerebral hemodynamics measured by functional magnetic resonance imaging (fMRI) are widely used to study the network organization of the brain. The temporal correlations among the ultra-slow, <0.1 Hz fluctuations across the brain regions are interpreted as functional connectivity maps and used for diagnostics of neurological disorders. However, despite the interest narrowed in the ultra-slow fluctuations, hemodynamic activity that exists beyond the ultra-slow frequency range could contribute to the functional connectivity, which remains unclear.Approach. In the present study, we have measured the brain-wide hemodynamics in the human participants with functional near-infrared spectroscopy (fNIRS) in a whole-head, cap-based and high-density montage at a sampling rate of 6.25 Hz. In addition, we have acquired resting state fMRI scans in the same group of participants for cross-modal evaluation of the connectivity maps. Then fNIRS data were deliberately down-sampled to a typical fMRI sampling rate of ∼0.5 Hz and the resulted differential connectivity maps were subject to a k-means clustering.Main results. Our diffuse optical topographical analysis of fNIRS data have revealed a default mode network (DMN) in the spontaneous deoxygenated and oxygenated hemoglobin changes, which remarkably resemble the same fMRI network derived from participants. Moreover, we have shown that the aliased activities in the down-sampled optical signals have altered the connectivity patterns, resulting in a network organization of aliased functional connectivity in the cerebral hemodynamics.Significance.The results have for the first time demonstrated that fNIRS as a broadly accessible modality can image the resting-state functional connectivity in the posterior midline, prefrontal and parietal structures of the DMN in the human brain, in a consistent pattern with fMRI. Further empowered by the fast sampling rate of fNIRS, our findings suggest the presence of aliased connectivity in the current understanding of the human brain organization.
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Affiliation(s)
- Fan Zhang
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Norman, OK 73019, United States of America
| | - Ali F Khan
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Norman, OK 73019, United States of America
| | - Lei Ding
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Norman, OK 73019, United States of America
- Institute for Biomedical Engineering, Science and Technology, The University of Oklahoma, Norman, OK 73019, United States of America
| | - Han Yuan
- Stephenson School of Biomedical Engineering, The University of Oklahoma, Norman, OK 73019, United States of America
- Institute for Biomedical Engineering, Science and Technology, The University of Oklahoma, Norman, OK 73019, United States of America
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Bonilauri A, Sangiuliano Intra F, Rossetto F, Borgnis F, Baselli G, Baglio F. Whole-Head Functional Near-Infrared Spectroscopy as an Ecological Monitoring Tool for Assessing Cortical Activity in Parkinson's Disease Patients at Different Stages. Int J Mol Sci 2022; 23:ijms232314897. [PMID: 36499223 PMCID: PMC9736501 DOI: 10.3390/ijms232314897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 11/18/2022] [Accepted: 11/22/2022] [Indexed: 11/29/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is increasingly employed as an ecological neuroimaging technique in assessing age-related chronic neurological disorders, such as Parkinson's disease (PD), mainly providing a cross-sectional characterization of clinical phenotypes in ecological settings. Current fNIRS studies in PD have investigated the effects of motor and non-motor impairment on cortical activity during gait and postural stability tasks, but no study has employed fNIRS as an ecological neuroimaging tool to assess PD at different stages. Therefore, in this work, we sought to investigate the cortical activity of PD patients during a motor grasping task and its relationship with both the staging of the pathology and its clinical variables. This study considered 39 PD patients (age 69.0 ± 7.64, 38 right-handed), subdivided into two groups at different stages by the Hoehn and Yahr (HY) scale: early PD (ePD; N = 13, HY = [1; 1.5]) and moderate PD (mPD; N = 26, HY = [2; 2.5; 3]). We employed a whole-head fNIRS system with 102 measurement channels to monitor brain activity. Group-level activation maps and region of interest (ROI) analysis were computed for ePD, mPD, and ePD vs. mPD contrasts. A ROI-based correlation analysis was also performed with respect to contrasted subject-level fNIRS data, focusing on age, a Cognitive Reserve Index questionnaire (CRIQ), disease duration, the Unified Parkinson's Disease Rating Scale (UPDRS), and performances in the Stroop Color and Word (SCW) test. We observed group differences in age, disease duration, and the UPDRS, while no significant differences were found for CRIQ or SCW scores. Group-level activation maps revealed that the ePD group presented higher activation in motor and occipital areas than the mPD group, while the inverse trend was found in frontal areas. Significant correlations with CRIQ, disease duration, the UPDRS, and the SCW were mostly found in non-motor areas. The results are in line with current fNIRS and functional and anatomical MRI scientific literature suggesting that non-motor areas-primarily the prefrontal cortex area-provide a compensation mechanism for PD motor impairment. fNIRS may serve as a viable support for the longitudinal assessment of therapeutic and rehabilitation procedures, and define new prodromal, low-cost, and ecological biomarkers of disease progression.
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Affiliation(s)
- Augusto Bonilauri
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| | - Francesca Sangiuliano Intra
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
- Faculty of Education, Free University of Bolzano-Bozen, 39042 Brixen, Italy
- Correspondence:
| | - Federica Rossetto
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
| | - Francesca Borgnis
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
| | - Giuseppe Baselli
- Department of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy
| | - Francesca Baglio
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, CADITER, 20148 Milan, Italy
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Sui Y, Kan C, Zhu S, Zhang T, Wang J, Xu S, Zhuang R, Shen Y, Wang T, Guo C. Resting-state functional connectivity for determining outcomes in upper extremity function after stroke: A functional near-infrared spectroscopy study. Front Neurol 2022; 13:965856. [PMID: 36438935 PMCID: PMC9682186 DOI: 10.3389/fneur.2022.965856] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 10/10/2022] [Indexed: 08/08/2023] Open
Abstract
OBJECTIVE Functional near-infrared spectroscopy (fNIRS) is a non-invasive and promising tool to map the brain functional networks in stroke recovery. Our study mainly aimed to use fNIRS to detect the different patterns of resting-state functional connectivity (RSFC) in subacute stroke patients with different degrees of upper extremity motor impairment defined by Fugl-Meyer motor assessment of upper extremity (FMA-UE). The second aim was to investigate the association between FMA-UE scores and fNIRS-RSFC among different regions of interest (ROIs) in stroke patients. METHODS Forty-nine subacute (2 weeks-6 months) stroke patients with subcortical lesions were enrolled and were classified into three groups based on FMA-UE scores: mild impairment (n = 17), moderate impairment (n = 13), and severe impairment (n = 19). All patients received FMA-UE assessment and 10-min resting-state fNIRS monitoring. The fNIRS signals were recorded over seven ROIs: bilateral dorsolateral prefrontal cortex (DLPFC), middle prefrontal cortex (MPFC), bilateral primary motor cortex (M1), and bilateral primary somatosensory cortex (S1). Functional connectivity (FC) was calculated by correlation coefficients between each channel and each ROI pair. To reveal the comprehensive differences in FC among three groups, we compared FC on the group level and ROI level. In addition, to determine the associations between FMA-UE scores and RSFC among different ROIs, Spearman's correlation analyses were performed with a significance threshold of p < 0.05. For easy comparison, we defined the left hemisphere as the ipsilesional hemisphere and flipped the lesional right hemisphere in MATLAB R2013b. RESULTS For the group-level comparison, the one-way ANOVA and post-hoc t-tests (mild vs. moderate; mild vs. severe; moderate vs. severe) showed that there was a significant difference among three groups (F = 3.42, p = 0.04) and the group-averaged FC in the mild group (0.64 ± 0.14) was significantly higher than that in the severe group (0.53 ± 0.14, p = 0.013). However, there were no significant differences between the mild and moderate group (MD ± SE = 0.05 ± 0.05, p = 0.35) and between the moderate and severe group (MD ± SE = 0.07 ± 0.05, p = 0.16). For the ROI-level comparison, the severe group had significantly lower FC of ipsilesional DLPFC-ipsilesional M1 [p = 0.015, false discovery rate (FDR)-corrected] and ipsilesional DLPFC-contralesional M1 (p = 0.035, FDR-corrected) than those in the mild group. Moreover, the result of Spearman's correlation analyses showed that there were significant correlations between FMA-UE scores and FC of the ipsilesional DLPFC-ipsilesional M1 (r = 0.430, p = 0.002), ipsilesional DLPFC-contralesional M1 (r = 0.388, p = 0.006), ipsilesional DLPFC-MPFC (r = 0.365, p = 0.01), and ipsilesional DLPFC-contralesional DLPFC (r = 0.330, p = 0.021). CONCLUSION Our findings indicate that different degrees of post-stroke upper extremity impairment reflect different RSFC patterns, mainly in the connection between DLPFC and bilateral M1. The association between FMA-UE scores and the FC of ipsilesional DLPFC-associated ROIs suggests that the ipsilesional DLPFC may play an important role in motor-related plasticity. These findings can help us better understand the neurophysiological mechanisms of upper extremity motor impairment and recovery in subacute stroke patients from different perspectives. Furthermore, it sheds light on the ipsilesional DLPFC-bilateral M1 as a possible neuromodulation target.
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Affiliation(s)
- Youxin Sui
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Chaojie Kan
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
- Department of Rehabilitation Medicine, Changzhou Dean Hospital, Changzhou, China
| | - Shizhe Zhu
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Tianjiao Zhang
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Jin Wang
- Department of Rehabilitation Medicine, Changzhou Dean Hospital, Changzhou, China
| | - Sheng Xu
- Department of Rehabilitation Medicine, Changzhou Dean Hospital, Changzhou, China
| | - Ren Zhuang
- Department of Rehabilitation Medicine, Changzhou Dean Hospital, Changzhou, China
| | - Ying Shen
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Tong Wang
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Chuan Guo
- Department of Rehabilitation Medicine, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
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16
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Huang R, Hong KS, Yang D, Huang G. Motion artifacts removal and evaluation techniques for functional near-infrared spectroscopy signals: A review. Front Neurosci 2022; 16:878750. [PMID: 36263362 PMCID: PMC9576156 DOI: 10.3389/fnins.2022.878750] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 07/06/2022] [Indexed: 12/04/2022] Open
Abstract
With the emergence of an increasing number of functional near-infrared spectroscopy (fNIRS) devices, the significant deterioration in measurement caused by motion artifacts has become an essential research topic for fNIRS applications. However, a high requirement for mathematics and programming limits the number of related researches. Therefore, here we provide the first comprehensive review for motion artifact removal in fNIRS aiming to (i) summarize the latest achievements, (ii) present the significant solutions and evaluation metrics from the perspective of application and reproduction, and (iii) predict future topics in the field. The present review synthesizes information from fifty-one journal articles (screened according to three criteria). Three hardware-based solutions and nine algorithmic solutions are summarized, and their application requirements (compatible signal types, the availability for online applications, and limitations) and extensions are discussed. Five metrics for noise suppression and two metrics for signal distortion were synthesized to evaluate the motion artifact removal methods. Moreover, we highlight three deficiencies in the existing research: (i) The balance between the use of auxiliary hardware and that of an algorithmic solution is not clarified; (ii) few studies mention the filtering delay of the solutions, and (iii) the robustness and stability of the solution under extreme application conditions are not discussed.
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Affiliation(s)
- Ruisen Huang
- School of Mechanical Engineering, Pusan National University, Busan, South Korea
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Busan, South Korea
- Department of Cogno-Mechatronics Engineering, Pusan National University, Busan, South Korea
- *Correspondence: Keum-Shik Hong,
| | - Dalin Yang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, MO, United States
| | - Guanghao Huang
- Institute for Future, School of Automation, Qingdao University, Qingdao, China
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Trambaiolli LR, Cassani R, Biazoli CE, Cravo AM, Sato JR, Falk TH. Multimodal resting-state connectivity predicts affective neurofeedback performance. Front Hum Neurosci 2022; 16:977776. [PMID: 36158618 PMCID: PMC9493361 DOI: 10.3389/fnhum.2022.977776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 08/03/2022] [Indexed: 11/13/2022] Open
Abstract
Neurofeedback has been suggested as a potential complementary therapy to different psychiatric disorders. Of interest for this approach is the prediction of individual performance and outcomes. In this study, we applied functional connectivity-based modeling using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) modalities to (i) investigate whether resting-state connectivity predicts performance during an affective neurofeedback task and (ii) evaluate the extent to which predictive connectivity profiles are correlated across EEG and fNIRS techniques. The fNIRS oxyhemoglobin and deoxyhemoglobin concentrations and the EEG beta and gamma bands modulated by the alpha frequency band (beta-m-alpha and gamma-m-alpha, respectively) recorded over the frontal cortex of healthy subjects were used to estimate functional connectivity from each neuroimaging modality. For each connectivity matrix, relevant edges were selected in a leave-one-subject-out procedure, summed into "connectivity summary scores" (CSS), and submitted as inputs to a support vector regressor (SVR). Then, the performance of the left-out-subject was predicted using the trained SVR model. Linear relationships between the CSS across both modalities were evaluated using Pearson's correlation. The predictive model showed a mean absolute error smaller than 20%, and the fNIRS oxyhemoglobin CSS was significantly correlated with the EEG gamma-m-alpha CSS (r = -0.456, p = 0.030). These results support that pre-task electrophysiological and hemodynamic resting-state connectivity are potential predictors of neurofeedback performance and are meaningfully coupled. This investigation motivates the use of joint EEG-fNIRS connectivity as outcome predictors, as well as a tool for functional connectivity coupling investigation.
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Affiliation(s)
- Lucas R. Trambaiolli
- Basic Neuroscience Division, McLean Hospital–Harvard Medical School, Belmont, MA, United States
| | - Raymundo Cassani
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
| | - Claudinei E. Biazoli
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, United Kingdom
| | - André M. Cravo
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
| | - João R. Sato
- Center for Mathematics, Computing and Cognition, Federal University of ABC, São Bernardo do Campo, Brazil
- Big Data, Hospital Israelita Albert Einstein, São Paulo, Brazil
| | - Tiago H. Falk
- Institut National de la Recherche Scientifique, University of Quebec, Montreal, QC, Canada
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Li R, Yang D, Fang F, Hong KS, Reiss AL, Zhang Y. Concurrent fNIRS and EEG for Brain Function Investigation: A Systematic, Methodology-Focused Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22155865. [PMID: 35957421 PMCID: PMC9371171 DOI: 10.3390/s22155865] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/27/2022] [Accepted: 07/30/2022] [Indexed: 05/29/2023]
Abstract
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS-EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS-EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS-EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS-EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS-EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS-EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS-EEG data analyses in future research.
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Affiliation(s)
- Rihui Li
- Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
- Department of Biomedical Engineering, University of Houston, Houston, TX 77004, USA
| | - Dalin Yang
- School of Mechanical Engineering, Pusan National University, Pusan 43241, Korea
- Mallinckrodt Institute of Radiology, Washington University School of Medicine in St. Louis, 4515 McKinley Avenue, St. Louis, MO 63110, USA
| | - Feng Fang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77004, USA
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, Pusan 43241, Korea
| | - Allan L. Reiss
- Center for Interdisciplinary Brain Sciences Research, Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yingchun Zhang
- Department of Biomedical Engineering, University of Houston, Houston, TX 77004, USA
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Le DT, Ogawa H, Tsuyuhara M, Watanabe K, Watanabe T, Ochi R, Nishijo H, Mihara M, Fujita N, Urakawa S. Coupled versus decoupled visuomotor feedback: Differential frontoparietal activity during curved reach planning on simultaneous functional near-infrared spectroscopy and electroencephalography. Brain Behav 2022; 12:e2681. [PMID: 35701382 PMCID: PMC9304848 DOI: 10.1002/brb3.2681] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 04/20/2022] [Accepted: 06/01/2022] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Interacting with the environment requires the planning and execution of reach-to-target movements along given reach trajectory paths. Human neural mechanisms for the motor planning of linear, or point-to-point, reaching movements are relatively well studied. However, the corresponding representations for curved and more complex reaching movements require further investigation. Additionally, the visual and proprioceptive feedback of hand positioning can be spatially and sequentially coupled in alignment (e.g., directly reaching for an object), termed coupled visuomotor feedback, or spatially decoupled (e.g., dragging the computer mouse forward to move the cursor upward), termed decoupled visuomotor feedback. During reach planning, visuomotor processing routes may differ across feedback types. METHODS We investigated the involvement of the frontoparietal regions, including the superior parietal lobule (SPL), dorsal premotor cortex (PMd), and dorsolateral prefrontal cortex (dlPFC), in curved reach planning under different feedback conditions. Participants engaged in two delayed-response reaching tasks with identical starting and target position sets but different reach trajectory paths (linear or curved) under two feedback conditions (coupled or decoupled). Neural responses in frontoparietal regions were analyzed using a combination of functional near-infrared spectroscopy and electroencephalography. RESULTS The results revealed that, regarding the cue period, curved reach planning had a higher hemodynamic response in the left SPL and bilateral PMd and a smaller high-beta power in the left parietal regions than linear reach planning. Regarding the delay period, higher hemodynamic responses during curved reach planning were observed in the right dlPFC for decoupled feedback than those for coupled feedback. CONCLUSION These findings suggest the crucial involvement of both SPL and PMd activities in trajectory-path processing for curved reach planning. Moreover, the dlPFC may be especially involved in the planning of curved reaching movements under decoupled feedback conditions. Thus, this study provides insight into the neural mechanisms underlying reaching function via different feedback conditions.
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Affiliation(s)
- Duc Trung Le
- Department of Musculoskeletal Functional Research and Regeneration, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Hiroki Ogawa
- Department of Musculoskeletal Functional Research and Regeneration, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Masato Tsuyuhara
- Department of Musculoskeletal Functional Research and Regeneration, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Kazuki Watanabe
- Department of Musculoskeletal Functional Research and Regeneration, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Tatsunori Watanabe
- Department of Sensorimotor Neuroscience, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Ryosuke Ochi
- Department of Musculoskeletal Functional Research and Regeneration, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Hisao Nishijo
- Department of System Emotional Science, Graduate School of Medicine and Pharmaceutical Science, University of Toyama, Toyama, Japan.,Research Center for Idling Brain Science (RCIBS), University of Toyama, Toyama, Japan
| | - Masahito Mihara
- Department of Neurology, Kawasaki Medical School, Okayama, Japan
| | - Naoto Fujita
- Department of Musculoskeletal Functional Research and Regeneration, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
| | - Susumu Urakawa
- Department of Musculoskeletal Functional Research and Regeneration, Graduate School of Biomedical and Health Sciences, Hiroshima University, Hiroshima, Japan
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Chen J, Wang D, Hu B, Yi W, Xu M, Chen D, Zhao Q. MCFHNet: Multi-Channel Fusion Hybrid Network for Efficient EEG-fNIRS Multi-modal Motor Imagery Decoding. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:4821-4825. [PMID: 36085621 DOI: 10.1109/embc48229.2022.9871385] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Motor Imagery-based Brain Computer Interface (MI-BCI) is a typical active BCI with a main focus on motor intention identification. Hybrid motor imagery (MI) decoding methods that based on multi-modal fusion of Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), especially deep learning-based methods, become popular in recent MI-BCI studies. However, the fusion strategy and network design in deep learning-based methods are complex. To solve this problem, we proposed the multi-channel fusion method (MCF) to simplify current fusion methods, and we designed a multi-channel fusion hybrid network (MCFHNet) based on MCF. MCFHNet combines depthwise convolutional layers, channel attention mechanism, and Bidirectional Long Short Term Memory (Bi-LSTM) layers, which enables strong capability of feature extraction in spatial and temporal domain. The comparison between MCFHNet and representative deep learning-based methods was performed on an open EEG-fNIRS dataset. We found the proposed method can yield superior performance (mean accuracy of 99.641 % in 5-fold cross validation of an intra-subject experiment). This work provides a new option for multi-modal MI decoding, which can be applied in the rehabilitation field based on hybrid BCI systems.
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21
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Scholkmann F, Tachtsidis I, Wolf M, Wolf U. Systemic physiology augmented functional near-infrared spectroscopy: a powerful approach to study the embodied human brain. NEUROPHOTONICS 2022; 9:030801. [PMID: 35832785 PMCID: PMC9272976 DOI: 10.1117/1.nph.9.3.030801] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 06/07/2022] [Indexed: 05/15/2023]
Abstract
In this Outlook paper, we explain why an accurate physiological interpretation of functional near-infrared spectroscopy (fNIRS) neuroimaging signals is facilitated when systemic physiological activity (e.g., cardiorespiratory and autonomic activity) is measured simultaneously by employing systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS). The rationale for SPA-fNIRS is twofold: (i) SPA-fNIRS enables a more complete interpretation and understanding of the fNIRS signals measured at the head since they contain components originating from neurovascular coupling and from systemic physiological sources. The systemic physiology signals measured with SPA-fNIRS can be used for regressing out physiological confounding components in fNIRS signals. Misinterpretations can thus be minimized. (ii) SPA-fNIRS enables to study the embodied brain by linking the brain with the physiological state of the entire body, allowing novel insights into their complex interplay. We envisage the SPA-fNIRS approach will become increasingly important in the future.
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Affiliation(s)
- Felix Scholkmann
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
- University Hospital Zurich, University of Zurich, Biomedical Optics Research Laboratory, Neonatology Research, Department of Neonatology, Zurich, Switzerland
| | - Ilias Tachtsidis
- University College London, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Martin Wolf
- University Hospital Zurich, University of Zurich, Biomedical Optics Research Laboratory, Neonatology Research, Department of Neonatology, Zurich, Switzerland
| | - Ursula Wolf
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
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22
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de Souza Moura B, Hu XS, DosSantos MF, DaSilva AF. Study Protocol of tDCS Based Pain Modulation in Head and Neck Cancer Patients Under Chemoradiation Therapy Condition: An fNIRS-EEG Study. Front Mol Neurosci 2022; 15:859988. [PMID: 35721312 PMCID: PMC9200064 DOI: 10.3389/fnmol.2022.859988] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundMultiple therapeutic strategies have been adopted to reduce pain, odynophagia, and oral mucositis in head and neck cancer patients. Among them, transcranial direct current stimulation (tDCS) represents a unique analgesic modality. However, the details of tDCS mechanisms in pain treatment are still unclear.Aims(1) to study the analgesic effects of a protocol that encompassed supervised-remote and in-clinic tDCS sessions applied in head and neck patients undergoing chemoradiation therapy; (2) to explore the underlining brain mechanisms of such modulation process, using a novel protocol that combined functional near-infrared spectroscopy (fNIRS), and electroencephalograph (EEG), two distinct neuroimaging methods that bring information regarding changes in the hemodynamic as well as in the electrical activity of the brain, respectively.MethodsThis proof-of-concept study was performed on two subjects. The study protocol included a 7-week-long tDCS stimulation procedure, a pre-tDCS baseline session, and two post-tDCS follow-up sessions. Two types of tDCS devices were used. One was used in the clinical setting and the other remotely. Brain imaging was obtained in weeks 1, 2, 5, 7, 8, and after 1 month.ResultsThe protocol implemented was safe and reliable. Preliminary results of the fNIRS analysis in weeks 2 and 7 showed a decrease in functional connections between the bilateral prefrontal cortex (PFC) and the primary sensory cortex (S1) (p < 0.05, FDR corrected). Changes in EEG power spectra were found in the PFC when comparing the seventh with the first week of tDCS.ConclusionThe protocol combining remote and in-clinic administered tDCS and integrated fNIRS and EEG to evaluate the brain activity is feasible. The preliminary results suggest that the mechanisms of tDCS in reducing the pain of head and neck cancer patients may be related to its effects on the connections between the S1 and the PFC.
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Affiliation(s)
- Brenda de Souza Moura
- Headache & Orofacial Pain Effort (H.O.P.E.), Department of Biologic and Materials Sciences, School of Dentistry, University of Michigan, Ann Arbor, MI, United States
- Laboratório de Propriedades Mecânicas e Biologia Celular (PropBio), Departamento de Prótese e Materiais Dentários, Faculdade de Odontologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil
| | - Xiao-Su Hu
- Headache & Orofacial Pain Effort (H.O.P.E.), Department of Biologic and Materials Sciences, School of Dentistry, University of Michigan, Ann Arbor, MI, United States
| | - Marcos F. DosSantos
- Laboratório de Propriedades Mecânicas e Biologia Celular (PropBio), Departamento de Prótese e Materiais Dentários, Faculdade de Odontologia, Universidade Federal do Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil
- Marcos F. DosSantos ;
| | - Alexandre F. DaSilva
- Headache & Orofacial Pain Effort (H.O.P.E.), Department of Biologic and Materials Sciences, School of Dentistry, University of Michigan, Ann Arbor, MI, United States
- *Correspondence: Alexandre F. DaSilva
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23
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Yeung MK, Chu VW. Viewing neurovascular coupling through the lens of combined EEG-fNIRS: A systematic review of current methods. Psychophysiology 2022; 59:e14054. [PMID: 35357703 DOI: 10.1111/psyp.14054] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 02/01/2022] [Accepted: 03/08/2022] [Indexed: 12/25/2022]
Abstract
Neurovascular coupling is a key physiological mechanism that occurs in the healthy human brain, and understanding this process has implications for understanding the aging and neuropsychiatric populations. Combined electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) has emerged as a promising, noninvasive tool for probing neurovascular interactions in humans. However, the utility of this approach critically depends on the methodological quality used for multimodal integration. Despite a growing number of combined EEG-fNIRS applications reported in recent years, the methodological rigor of past studies remains unclear, limiting the accurate interpretation of reported findings and hindering the translational application of this multimodal approach. To fill this knowledge gap, we critically evaluated various methodological aspects of previous combined EEG-fNIRS studies performed in healthy individuals. A literature search was conducted using PubMed and PsycINFO on June 28, 2021. Studies involving concurrent EEG and fNIRS measurements in awake and healthy individuals were selected. After screening and eligibility assessment, 96 studies were included in the methodological evaluation. Specifically, we critically reviewed various aspects of participant sampling, experimental design, signal acquisition, data preprocessing, outcome selection, data analysis, and results presentation reported in these studies. Altogether, we identified several notable strengths and limitations of the existing EEG-fNIRS literature. In light of these limitations and the features of combined EEG-fNIRS, recommendations are made to improve and standardize research practices to facilitate the use of combined EEG-fNIRS when studying healthy neurovascular coupling processes and alterations in neurovascular coupling among various populations.
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Affiliation(s)
- Michael K Yeung
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
| | - Vivian W Chu
- Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China
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24
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Almulla L, Al-Naib I, Ateeq IS, Althobaiti M. Observation and motor imagery balance tasks evaluation: An fNIRS feasibility study. PLoS One 2022; 17:e0265898. [PMID: 35320324 PMCID: PMC8942212 DOI: 10.1371/journal.pone.0265898] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Accepted: 03/09/2022] [Indexed: 11/25/2022] Open
Abstract
In this study, we aimed at exploring the feasibility of functional near-infrared spectroscopy (fNIRS) for studying the observation and/or motor imagination of various postural tasks. Thirteen healthy adult subjects followed five trials of static and dynamic standing balance tasks, throughout three different experimental setups of action observation (AO), a combination of action observation and motor imagery (AO+MI), and motor imagery (MI). During static and dynamic standing tasks, both the AO+MI and MI experiments revealed that many channels in prefrontal or motor regions are significantly activated while the AO experiment showed almost no significant increase in activations in most of the channels. The contrast between static and dynamic standing tasks showed that with more demanding balance tasks, relative higher activation patterns were observed, particularly during AO and in AO+MI experiments in the frontopolar area. Moreover, the AO+MI experiment revealed a significant difference in premotor and supplementary motor cortices that are related to balance control. Furthermore, it has been observed that the AO+MI experiment induced relatively higher activation patterns in comparison to AO or MI alone. Remarkably, the results of this work match its counterpart from previous functional magnetic resonance imaging studies. Therefore, they may pave the way for using the fNIRS as a diagnostic tool for evaluating the performance of the non-physical balance training during the rehabilitation period of temporally immobilized patients.
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Affiliation(s)
- Latifah Almulla
- Biomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Ibraheem Al-Naib
- Biomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Ijlal Shahrukh Ateeq
- Biomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Murad Althobaiti
- Biomedical Engineering Department, College of Engineering, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
- * E-mail:
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25
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Conti E, Scaffei E, Bosetti C, Marchi V, Costanzo V, Dell’Oste V, Mazziotti R, Dell’Osso L, Carmassi C, Muratori F, Baroncelli L, Calderoni S, Battini R. Looking for “fNIRS Signature” in Autism Spectrum: A Systematic Review Starting From Preschoolers. Front Neurosci 2022; 16:785993. [PMID: 35341016 PMCID: PMC8948464 DOI: 10.3389/fnins.2022.785993] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 02/08/2022] [Indexed: 01/16/2023] Open
Abstract
Accumulating evidence suggests that functional Near-Infrared Spectroscopy (fNIRS) can provide an essential bridge between our current understanding of neural circuit organization and cortical activity in the developing brain. Indeed, fNIRS allows studying brain functions through the measurement of neurovascular coupling that links neural activity to subsequent changes in cerebral blood flow and hemoglobin oxygenation levels. While the literature offers a multitude of fNIRS applications to typical development, only recently this tool has been extended to the study of neurodevelopmental disorders (NDDs). The exponential rise of scientific publications on this topic during the last years reflects the interest to identify a “fNIRS signature” as a biomarker of high translational value to support both early clinical diagnosis and treatment outcome. The purpose of this systematic review is to describe the updating clinical applications of fNIRS in NDDs, with a specific focus on preschool population. Starting from this rationale, a systematic search was conducted for relevant studies in different scientific databases (Pubmed, Scopus, and Web of Science) resulting in 13 published articles. In these studies, fNIRS was applied in individuals with Autism Spectrum Disorder (ASD) or infants at high risk of developing ASD. Both functional connectivity in resting-state conditions and task-evoked brain activation using multiple experimental paradigms were used in the selected investigations, suggesting that fNIRS might be considered a promising method for identifying early quantitative biomarkers in the autism field.
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Affiliation(s)
- Eugenia Conti
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Elena Scaffei
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Neuroscience, Psychology, Drug Research and Child Health NEUROFARBA, University of Florence, Florence, Italy
- *Correspondence: Elena Scaffei,
| | - Chiara Bosetti
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Viviana Marchi
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Valeria Costanzo
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Valerio Dell’Oste
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Raffaele Mazziotti
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
| | - Liliana Dell’Osso
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Claudia Carmassi
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Filippo Muratori
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Laura Baroncelli
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Institute of Neuroscience, National Research Council, Pisa, Italy
| | - Sara Calderoni
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Roberta Battini
- Department of Developmental Neuroscience, IRCCS Stella Maris Foundation, Pisa, Italy
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
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Abstract
In this work, we introduce a deep learning architecture for evaluation on multimodal electroencephalographic (EEG) and functional near-infrared spectroscopy (fNIRS) recordings from 40 epileptic patients. Long short-term memory units and convolutional neural networks are integrated within a multimodal sequence-to-sequence autoencoder. The trained neural network predicts fNIRS signals from EEG, sans a priori, by hierarchically extracting deep features from EEG full spectra and specific EEG frequency bands. Results show that higher frequency EEG ranges are predictive of fNIRS signals with the gamma band inputs dominating fNIRS prediction as compared to other frequency envelopes. Seed based functional connectivity validates similar patterns between experimental fNIRS and our model's fNIRS reconstructions. This is the first study that shows it is possible to predict brain hemodynamics (fNIRS) from encoded neural data (EEG) in the resting human epileptic brain based on power spectrum amplitude modulation of frequency oscillations in the context of specific hypotheses about how EEG frequency bands decode fNIRS signals.
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27
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Abstract
Clinical neuroimaging has largely been limited to examining the neurophysiological outcomes of treatments for psychiatric conditions rather than the neurocognitive mechanisms by which these outcomes are brought about as a function of clinical strategies, and the cognitive neuroscientific research aiming to investigate these mechanisms in nonclinical and clinical populations has been ecologically challenged by the extent to which tasks represent and generalize to intervention strategies. However, recent technological and methodological advancements to neuroimaging techniques such as functional near-infrared spectroscopy and functional near-infrared spectroscopy-based hyperscanning provide novel opportunities to investigate the mechanisms of change in more naturalistic and interactive settings, representing a unique prospect for improving our understanding of the intra- and interbrain systems supporting the recogitation of dysfunctional cognitive operations.
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Affiliation(s)
- James E. Crum II
- Institute of Cognitive Neuroscience, University College
London, London, UK
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28
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Xu D, Shin N, Lee S, Park J. Frequency-Dependent Effects on Coordination and Prefrontal Hemodynamics During Finger Force Production Tasks. Front Hum Neurosci 2021; 15:721679. [PMID: 34733144 PMCID: PMC8558484 DOI: 10.3389/fnhum.2021.721679] [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: 06/07/2021] [Accepted: 09/28/2021] [Indexed: 11/13/2022] Open
Abstract
Behavioral stability partially depends on the variability of net outcomes by means of the co-varied adjustment of individual elements such as multi-finger forces. The properties of cyclic actions affect stability and variability of the performance as well as the activation of the prefrontal cortex that is an origin of subcortical structure for the coordinative actions. Little research has been done on the issue of the relationship between stability and neuronal response. The purpose of the study was to investigate the changes in the neural response, particularly at the prefrontal cortex, to the frequencies of isometric cyclic finger force production. The main experimental task was to produce finger forces while matching the produced force to sine-wave templates as accurately as possible. Also, the hemodynamics responses of the prefrontal cortex, including oxy-hemoglobin concentration (ΔHbO) and the functional connectivity, were measured using functional near-infrared spectroscopy. The frequency conditions comprised 0.1, 1, and 2 Hz. The uncontrolled manifold (UCM) approach was applied to compute synergy indices in time-series. The relative phase (RP), the coefficient of variation (CV) of the peak and trough force values were computed as the indices of performance accuracy. The statistical parametric mapping (SPM) was implemented to compare the synergy indices of three frequency conditions in time-series. A less accurate performance in the high-frequency condition was caused not by the RP, but mainly by the inconsistent peak force values (CV; p < 0.01, η p 2 = 0.90). The SPM analysis revealed that the synergy indices were larger in the low-frequency than in high-frequency conditions. Further, the ΔHbO remained unchanged under all frequency conditions, while the functional connectivity decreased with an increase in the frequency of cyclic force production. The current results suggested that the concurrent activation of the prefrontal region mainly depends on the frequency of cyclic force production, which was associated with the strength of stability indices and performance errors. The current study is the first work to uncover the effect of frequency on the multi-finger synergies as to the hemodynamic response in the prefrontal cortex, which possibly provides a clue of the neural mechanism of synergy formation and its changes.
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Affiliation(s)
- Dayuan Xu
- Department of Physical Education, Seoul National University, Seoul, South Korea.,Institute of Sport Science, Seoul National University, Seoul, South Korea
| | - Narae Shin
- Department of Physical Education, Seoul National University, Seoul, South Korea.,Institute of Sport Science, Seoul National University, Seoul, South Korea
| | - Sungjun Lee
- Department of Physical Education, Seoul National University, Seoul, South Korea
| | - Jaebum Park
- Department of Physical Education, Seoul National University, Seoul, South Korea.,Institute of Sport Science, Seoul National University, Seoul, South Korea.,Advanced Institute of Convergence Technology, Seoul National University, Suwon, South Korea
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29
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Del Angel Arrieta F, Rojas Cisneros M, Rivas JJ, Castrejon LR, Sucar LE, Andreu-Perez J, Orihuela-Espina F. Characterization of a Raspberry Pi as the Core for a Low-cost Multimodal EEG-fNIRS Platform. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:1288-1291. [PMID: 34891521 DOI: 10.1109/embc46164.2021.9629672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Poor understanding of brain recovery after injury, sparsity of evaluations and limited availability of healthcare services hinders the success of neurorehabilitation programs in rural communities. The availability of neuroimaging ca-pacities in remote communities can alleviate this scenario supporting neurorehabilitation programs in remote settings. This research aims at building a multimodal EEG-fNIRS neuroimaging platform deployable to rural communities to support neurorehabilitation efforts. A Raspberry Pi 4 is chosen as the CPU for the platform responsible for presenting the neurorehabilitation stimuli, acquiring, processing and storing concurrent neuroimaging records as well as the proper synchronization between the neuroimaging streams. We present here two experiments to assess the feasibility and characterization of the Raspberry Pi as the core for a multimodal EEG-fNIRS neuroimaging platform; one over controlled conditions using a combination of synthetic and real data, and another from a full test during resting state. CPU usage, RAM usage and operation temperature were measured during the tests with mean operational records below 40% for CPU cores, 13.6% for memory and 58.85 ° C for temperatures. Package loss was inexistent on synthetic data and negligible on experimental data. Current consumption can be satisfied with a 1000 mAh 5V battery. The Raspberry Pi 4 was able to cope with the required workload in conditions of operation similar to those needed to support a neurorehabilitation evaluation.
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30
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Huo C, Xu G, Li W, Xie H, Zhang T, Liu Y, Li Z. A review on functional near-infrared spectroscopy and application in stroke rehabilitation. MEDICINE IN NOVEL TECHNOLOGY AND DEVICES 2021. [DOI: 10.1016/j.medntd.2021.100064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
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31
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Dimitrova M, Wagatsuma H, Krastev A, Vrochidou E, Nunez-Gonzalez JD. A Review of Possible EEG Markers of Abstraction, Attentiveness, and Memorisation in Cyber-Physical Systems for Special Education. Front Robot AI 2021; 8:715962. [PMID: 34532347 PMCID: PMC8439420 DOI: 10.3389/frobt.2021.715962] [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: 05/27/2021] [Accepted: 07/22/2021] [Indexed: 11/21/2022] Open
Abstract
Cyber-physical systems (CPSs) for special education rely on effective mental and brain processing during the lesson, performed with the assistance of humanoid robots. The improved diagnostic ability of the CPS is a prerogative of the system for efficient technological support of the pedagogical process. The article focuses on the available knowledge of possible EEG markers of abstraction, attentiveness, and memorisation (in some cases combined with eye tracking) related to predicting effective mental and brain processing during the lesson. The role of processing abstraction is emphasised as the learning mechanism, which is given priority over the other mechanisms by the cognitive system. The main markers in focus are P1, N170, Novelty P3, RewP, N400, and P600. The description of the effects is accompanied by the analysis of some implications for the design of novel educational scenarios in inclusive classes.
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Affiliation(s)
- Maya Dimitrova
- Department of Interactive Robotics and Control Systems, Institute of Robotics, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Hiroaki Wagatsuma
- Department of Human Intelligence Systems, Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology (KYUTECH), Kitakyushu, Japan
| | - Aleksandar Krastev
- Department of Interactive Robotics and Control Systems, Institute of Robotics, Bulgarian Academy of Sciences, Sofia, Bulgaria
| | - Eleni Vrochidou
- Human-Machines Interaction (HUMAIN) Lab, Department of Computer Science, International Hellenic University (IHU), Kavala, Greece
| | - J. David Nunez-Gonzalez
- Engineering School of Gipuzkoa—Eibar Section, Department of Applied Mathematics, University of Basque Country (UPV/EHU), Bilbao, Spain
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32
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von Lühmann A, Zheng Y, Ortega-Martinez A, Kiran S, Somers DC, Cronin-Golomb A, Awad LN, Ellis TD, Boas DA, Yücel MA. Towards Neuroscience of the Everyday World (NEW) using functional Near-Infrared Spectroscopy. CURRENT OPINION IN BIOMEDICAL ENGINEERING 2021; 18:100272. [PMID: 33709044 PMCID: PMC7943029 DOI: 10.1016/j.cobme.2021.100272] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Functional Near-Infrared Spectroscopy (fNIRS) assesses human brain activity by noninvasively measuring changes of cerebral hemoglobin concentrations caused by modulation of neuronal activity. Recent progress in signal processing and advances in system design, such as miniaturization, wearability and system sensitivity, have strengthened fNIRS as a viable and cost-effective complement to functional Magnetic Resonance Imaging (fMRI), expanding the repertoire of experimental studies that can be performed by the neuroscience community. The availability of fNIRS and Electroencephalography (EEG) for routine, increasingly unconstrained, and mobile brain imaging is leading towards a new domain that we term "Neuroscience of the Everyday World" (NEW). In this light, we review recent advances in hardware, study design and signal processing, and discuss challenges and future directions towards achieving NEW.
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Affiliation(s)
- Alexander von Lühmann
- Neurophotonics Center, Biomedical Engineering, Boston University, Boston, MA 02215, USA
- NIRx Medical Technologies, Berlin 13355, Germany
| | - Yilei Zheng
- Neurophotonics Center, Biomedical Engineering, Boston University, Boston, MA 02215, USA
- State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China
| | | | - Swathi Kiran
- Department of Speech, Language, and Hearing, Boston University, Boston, MA 02215, USA
| | - David C. Somers
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Alice Cronin-Golomb
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Louis N. Awad
- College of Health and Rehabilitation Sciences, Sargent College, Boston University, Boston, MA 02215, USA
| | - Terry D. Ellis
- College of Health and Rehabilitation Sciences, Sargent College, Boston University, Boston, MA 02215, USA
| | - David A. Boas
- Neurophotonics Center, Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Meryem A. Yücel
- Neurophotonics Center, Biomedical Engineering, Boston University, Boston, MA 02215, USA
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33
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AL-Quraishi MS, Elamvazuthi I, Tang TB, Al-Qurishi M, Adil SH, Ebrahim M. Bimodal Data Fusion of Simultaneous Measurements of EEG and fNIRS during Lower Limb Movements. Brain Sci 2021; 11:brainsci11060713. [PMID: 34071982 PMCID: PMC8227788 DOI: 10.3390/brainsci11060713] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 05/19/2021] [Accepted: 05/24/2021] [Indexed: 01/24/2023] Open
Abstract
Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have temporal and spatial characteristics that may complement each other and, therefore, pose an intriguing approach for brain-computer interaction (BCI). In this work, the relationship between the hemodynamic response and brain oscillation activity was investigated using the concurrent recording of fNIRS and EEG during ankle joint movements. Twenty subjects participated in this experiment. The EEG was recorded using 20 electrodes and hemodynamic responses were recorded using 32 optodes positioned over the motor cortex areas. The event-related desynchronization (ERD) feature was extracted from the EEG signal in the alpha band (8-11) Hz, and the concentration change of the oxy-hemoglobin (oxyHb) was evaluated from the hemodynamics response. During the motor execution of the ankle joint movements, a decrease in the alpha (8-11) Hz amplitude (desynchronization) was found to be correlated with an increase of the oxyHb (r = -0.64061, p < 0.00001) observed on the Cz electrode and the average of the fNIRS channels (ch28, ch25, ch32, ch35) close to the foot area representation. Then, the correlated channels in both modalities were used for ankle joint movement classification. The result demonstrates that the integrated modality based on the correlated channels provides a substantial enhancement in ankle joint classification accuracy of 93.01 ± 5.60% (p < 0.01) compared with single modality. These results highlight the potential of the bimodal fNIR-EEG approach for the development of future BCI for lower limb rehabilitation.
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Affiliation(s)
- Maged S. AL-Quraishi
- Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia; (M.S.A.-Q.); (I.E.)
- Faculty of Engineering, Thamar University, Dhamar 87246, Yemen
| | - Irraivan Elamvazuthi
- Department of Electrical and Electronic Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia; (M.S.A.-Q.); (I.E.)
| | - Tong Boon Tang
- Centre for Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Bandar Seri Iskandar 32610, Malaysia
- Correspondence: ; Tel.: +60-5-368-7801
| | - Muhammad Al-Qurishi
- Faculty of information and Computer Science, Thamar University, Dhamar 87246, Yemen;
| | - Syed Hasan Adil
- Faculty of Engineering, Sciences and Technology, Iqra University, Karachi 75500, Pakistan; (S.H.A.); (M.E.)
| | - Mansoor Ebrahim
- Faculty of Engineering, Sciences and Technology, Iqra University, Karachi 75500, Pakistan; (S.H.A.); (M.E.)
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Grässler B, Herold F, Dordevic M, Gujar TA, Darius S, Böckelmann I, Müller NG, Hökelmann A. Multimodal measurement approach to identify individuals with mild cognitive impairment: study protocol for a cross-sectional trial. BMJ Open 2021; 11:e046879. [PMID: 34035103 PMCID: PMC8154928 DOI: 10.1136/bmjopen-2020-046879] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 05/11/2021] [Indexed: 12/26/2022] Open
Abstract
INTRODUCTION The diagnosis of mild cognitive impairment (MCI), that is, the transitory phase between normal age-related cognitive decline and dementia, remains a challenging task. It was observed that a multimodal approach (simultaneous analysis of several complementary modalities) can improve the classification accuracy. We will combine three noninvasive measurement modalities: functional near-infrared spectroscopy (fNIRS), electroencephalography and heart rate variability via ECG. Our aim is to explore neurophysiological correlates of cognitive performance and whether our multimodal approach can aid in early identification of individuals with MCI. METHODS AND ANALYSIS This study will be a cross-sectional with patients with MCI and healthy controls (HC). The neurophysiological signals will be measured during rest and while performing cognitive tasks: (1) Stroop, (2) N-back and (3) verbal fluency test (VFT). Main aims of statistical analysis are to (1) determine the differences in neurophysiological responses of HC and MCI, (2) investigate relationships between measures of cognitive performance and neurophysiological responses and (3) investigate whether the classification accuracy can be improved by using our multimodal approach. To meet these targets, statistical analysis will include machine learning approaches.This is, to the best of our knowledge, the first study that applies simultaneously these three modalities in MCI and HC. We hypothesise that the multimodal approach improves the classification accuracy between HC and MCI as compared with a unimodal approach. If our hypothesis is verified, this study paves the way for additional research on multimodal approaches for dementia research and fosters the exploration of new biomarkers for an early detection of nonphysiological age-related cognitive decline. ETHICS AND DISSEMINATION Ethics approval was obtained from the local Ethics Committee (reference: 83/19). Data will be shared with the scientific community no more than 1 year following completion of study and data assembly. TRIAL REGISTRATION NUMBER ClinicalTrials.gov, NCT04427436, registered on 10 June 2020, https://clinicaltrials.gov/ct2/show/study/NCT04427436.
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Affiliation(s)
- Bernhard Grässler
- Institute of Sport Science, Faculty of Humanities, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Fabian Herold
- Department of Neuroprotection, German Centre for Neurodegenerative Diseases Site Magdeburg, Magdeburg, Germany
| | - Milos Dordevic
- Department of Neuroprotection, German Centre for Neurodegenerative Diseases Site Magdeburg, Magdeburg, Germany
| | - Tariq Ali Gujar
- Institute of Sport Science, Faculty of Humanities, Otto von Guericke University Magdeburg, Magdeburg, Germany
| | - Sabine Darius
- Occupational Medicine, Otto von Guericke University Medical Faculty, Magdeburg, Germany
| | - Irina Böckelmann
- Occupational Medicine, Otto von Guericke University Medical Faculty, Magdeburg, Germany
| | - Notger G Müller
- Department of Neuroprotection, German Centre for Neurodegenerative Diseases Site Magdeburg, Magdeburg, Germany
- Department of Neurology, Otto von Guericke University Medical Faculty, Magdeburg, Germany
| | - Anita Hökelmann
- Institute of Sport Science, Faculty of Humanities, Otto von Guericke University Magdeburg, Magdeburg, Germany
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Chiarelli AM, Perpetuini D, Croce P, Filippini C, Cardone D, Rotunno L, Anzoletti N, Zito M, Zappasodi F, Merla A. Evidence of Neurovascular Un-Coupling in Mild Alzheimer's Disease through Multimodal EEG-fNIRS and Multivariate Analysis of Resting-State Data. Biomedicines 2021; 9:biomedicines9040337. [PMID: 33810484 PMCID: PMC8066873 DOI: 10.3390/biomedicines9040337] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Revised: 03/20/2021] [Accepted: 03/23/2021] [Indexed: 12/18/2022] Open
Abstract
Alzheimer’s disease (AD) is associated with modifications in cerebral blood perfusion and autoregulation. Hence, neurovascular coupling (NC) alteration could become a biomarker of the disease. NC might be assessed in clinical settings through multimodal electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Multimodal EEG-fNIRS was recorded at rest in an ambulatory setting to assess NC and to evaluate the sensitivity and specificity of the methodology to AD. Global NC was evaluated with a general linear model (GLM) framework by regressing whole-head EEG power envelopes in three frequency bands (theta, alpha and beta) with average fNIRS oxy- and deoxy-hemoglobin concentration changes in the frontal and prefrontal cortices. NC was lower in AD compared to healthy controls (HC) with significant differences in the linkage of theta and alpha bands with oxy- and deoxy-hemoglobin, respectively (p = 0.028 and p = 0.020). Importantly, standalone EEG and fNIRS metrics did not highlight differences between AD and HC. Furthermore, a multivariate data-driven analysis of NC between the three frequency bands and the two hemoglobin species delivered a cross-validated classification performance of AD and HC with an Area Under the Curve, AUC = 0.905 (p = 2.17 × 10−5). The findings demonstrate that EEG-fNIRS may indeed represent a powerful ecological tool for clinical evaluation of NC and early identification of AD.
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Affiliation(s)
- Antonio M. Chiarelli
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, Faculty of Medicine, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (C.F.); (D.C.); (F.Z.); (A.M.)
- Correspondence: ; Tel.: +39-087-1355-6954
| | - David Perpetuini
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, Faculty of Medicine, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (C.F.); (D.C.); (F.Z.); (A.M.)
| | - Pierpaolo Croce
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, Faculty of Medicine, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (C.F.); (D.C.); (F.Z.); (A.M.)
| | - Chiara Filippini
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, Faculty of Medicine, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (C.F.); (D.C.); (F.Z.); (A.M.)
| | - Daniela Cardone
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, Faculty of Medicine, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (C.F.); (D.C.); (F.Z.); (A.M.)
| | - Ludovica Rotunno
- Department of Medicine and Science of Ageing, Faculty of Medicine, University G. d’Annunzio of Chieti-Pescara, Via Dei Vestini 31, 66100 Chieti, Italy; (L.R.); (N.A.); (M.Z.)
| | - Nelson Anzoletti
- Department of Medicine and Science of Ageing, Faculty of Medicine, University G. d’Annunzio of Chieti-Pescara, Via Dei Vestini 31, 66100 Chieti, Italy; (L.R.); (N.A.); (M.Z.)
| | - Michele Zito
- Department of Medicine and Science of Ageing, Faculty of Medicine, University G. d’Annunzio of Chieti-Pescara, Via Dei Vestini 31, 66100 Chieti, Italy; (L.R.); (N.A.); (M.Z.)
| | - Filippo Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, Faculty of Medicine, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (C.F.); (D.C.); (F.Z.); (A.M.)
| | - Arcangelo Merla
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, Faculty of Medicine, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (C.F.); (D.C.); (F.Z.); (A.M.)
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Guerrero Moreno J, Biazoli CE, Baptista AF, Trambaiolli LR. Closed-loop neurostimulation for affective symptoms and disorders: An overview. Biol Psychol 2021; 161:108081. [PMID: 33757806 DOI: 10.1016/j.biopsycho.2021.108081] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2020] [Revised: 03/12/2021] [Accepted: 03/15/2021] [Indexed: 12/28/2022]
Abstract
Affective and anxiety disorders are the most prevalent and incident psychiatric disorders worldwide. Therapeutic approaches to these disorders using non-invasive brain stimulation (NIBS) and analogous techniques have been extensively investigated. In this paper, we discuss the combination of NIBS and neurofeedback in closed-loop setups and its application for affective symptoms and disorders. For this, we first provide a rationale for this combination by presenting some of the main original findings of NIBS, with a primary focus on transcranial magnetic stimulation (TMS), and neurofeedback, including protocols based on electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Then, we provide a scope review of studies combining real-time neurofeedback with NIBS protocols in the so-called closed-loop brain state-dependent neuromodulation (BSDS). Finally, we discuss the concomitant use of TMS and real-time functional near-infrared spectroscopy (fNIRS) as a possible solution to the current limitations of BSDS-based protocols for affective and anxiety disorders.
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Affiliation(s)
- Javier Guerrero Moreno
- Center of Mathematics, Computation and Cognition, Universidade Federal do ABC, Santo André, Brazil
| | - Claudinei Eduardo Biazoli
- Center of Mathematics, Computation and Cognition, Universidade Federal do ABC, Santo André, Brazil; Department of Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, UK
| | - Abrahão Fontes Baptista
- Center of Mathematics, Computation and Cognition, Universidade Federal do ABC, Santo André, Brazil; Laboratory of Medical Investigations 54 (LIM-54), Universidade de São Paulo, São Paulo, Brazil; NAPeN Network (Rede de Núcleos de Assistência e Pesquisa em Neuromodulação), Brazil; Brazilian Institute of Neuroscience and Neurotechnology (BRAINN/CEPID-FAPESP), University of Campinas, Campinas, São Paulo, Brazil
| | - Lucas Remoaldo Trambaiolli
- McLean Hospital, Harvard Medical School, Boston, USA; School of Medicine and Dentistry, University of Rochester, Rochester, USA.
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Brauns K, Friedl-Werner A, Maggioni MA, Gunga HC, Stahn AC. Head-Down Tilt Position, but Not the Duration of Bed Rest Affects Resting State Electrocortical Activity. Front Physiol 2021; 12:638669. [PMID: 33716785 PMCID: PMC7951060 DOI: 10.3389/fphys.2021.638669] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/28/2021] [Indexed: 11/13/2022] Open
Abstract
Adverse cognitive and behavioral conditions and psychiatric disorders are considered a critical and unmitigated risk during future long-duration space missions (LDSM). Monitoring and mitigating crew health and performance risks during these missions will require tools and technologies that allow to reliably assess cognitive performance and mental well-being. Electroencephalography (EEG) has the potential to meet the technical requirements for the non-invasive and objective monitoring of neurobehavioral conditions during LDSM. Weightlessness is associated with fluid and brain shifts, and these effects could potentially challenge the interpretation of resting state EEG recordings. Head-down tilt bed rest (HDBR) provides a unique spaceflight analog to study these effects on Earth. Here, we present data from two long-duration HDBR experiments, which were used to systematically investigate the time course of resting state electrocortical activity during prolonged HDBR. EEG spectral power significantly reduced within the delta, theta, alpha, and beta frequency bands. Likewise, EEG source localization revealed significantly lower activity in a broad range of centroparietal and occipital areas within the alpha and beta frequency domains. These changes were observed shortly after the onset of HDBR, did not change throughout HDBR, and returned to baseline after the cessation of bed rest. EEG resting state functional connectivity was not affected by HDBR. The results provide evidence for a postural effect on resting state brain activity that persists throughout long-duration HDBR, indicating that immobilization and inactivity per se do not affect resting state electrocortical activity during HDBR. Our findings raise an important issue on the validity of EEG to identify the time course of changes in brain function during prolonged HBDR, and highlight the importance to maintain a consistent body posture during all testing sessions, including data collections at baseline and recovery.
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Affiliation(s)
- Katharina Brauns
- Charité - Universitätsmedizin Berlin, a corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Physiology, Berlin, Germany
| | - Anika Friedl-Werner
- Charité - Universitätsmedizin Berlin, a corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Physiology, Berlin, Germany.,INSERM U 1075 COMETE, Université de Normandie, Caen, France
| | - Martina A Maggioni
- Charité - Universitätsmedizin Berlin, a corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Physiology, Berlin, Germany.,Department of Biomedical Sciences for Health, Università degli Studi di Milano, Milan, Italy
| | - Hanns-Christian Gunga
- Charité - Universitätsmedizin Berlin, a corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Physiology, Berlin, Germany
| | - Alexander C Stahn
- Charité - Universitätsmedizin Berlin, a corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Physiology, Berlin, Germany.,Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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38
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Pinti P, Siddiqui MF, Levy AD, Jones EJH, Tachtsidis I. An analysis framework for the integration of broadband NIRS and EEG to assess neurovascular and neurometabolic coupling. Sci Rep 2021; 11:3977. [PMID: 33597576 PMCID: PMC7889942 DOI: 10.1038/s41598-021-83420-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Accepted: 01/28/2021] [Indexed: 01/31/2023] Open
Abstract
With the rapid growth of optical-based neuroimaging to explore human brain functioning, our research group has been developing broadband Near Infrared Spectroscopy (bNIRS) instruments, a technological extension to functional Near Infrared Spectroscopy (fNIRS). bNIRS has the unique capacity of monitoring brain haemodynamics/oxygenation (measuring oxygenated and deoxygenated haemoglobin), and metabolism (measuring the changes in the redox state of cytochrome-c-oxidase). When combined with electroencephalography (EEG), bNIRS provides a unique neuromonitoring platform to explore neurovascular coupling mechanisms. In this paper, we present a novel pipeline for the integrated analysis of bNIRS and EEG signals, and demonstrate its use on multi-channel bNIRS data recorded with concurrent EEG on healthy adults during a visual stimulation task. We introduce the use of the Finite Impulse Response functions within the General Linear Model for bNIRS and show its feasibility to statistically localize the haemodynamic and metabolic activity in the occipital cortex. Moreover, our results suggest that the fusion of haemodynamic and metabolic measures unveils additional information on brain functioning over haemodynamic imaging alone. The cross-correlation-based analysis of interrelationships between electrical (EEG) and haemodynamic/metabolic (bNIRS) activity revealed that the bNIRS metabolic signal offers a unique marker of brain activity, being more closely coupled to the neuronal EEG response.
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Affiliation(s)
- P. Pinti
- grid.83440.3b0000000121901201Department of Medical Physics and Biomedical Engineering, University College London, London, UK ,grid.4464.20000 0001 2161 2573Centre for Brain and Cognitive Development, Birkbeck College, University of London, London, UK
| | - M. F. Siddiqui
- grid.4464.20000 0001 2161 2573Centre for Brain and Cognitive Development, Birkbeck College, University of London, London, UK
| | - A. D. Levy
- grid.83440.3b0000000121901201Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, UK ,grid.83440.3b0000000121901201Headache and Facial Pain, Brain Repair and Rehabilitation, Institute of Neurology, University College London, London, UK
| | - E. J. H. Jones
- grid.4464.20000 0001 2161 2573Centre for Brain and Cognitive Development, Birkbeck College, University of London, London, UK
| | - Ilias Tachtsidis
- grid.83440.3b0000000121901201Department of Medical Physics and Biomedical Engineering, University College London, London, UK
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Yücel MA, Lühmann AV, Scholkmann F, Gervain J, Dan I, Ayaz H, Boas D, Cooper RJ, Culver J, Elwell CE, Eggebrecht A, Franceschini MA, Grova C, Homae F, Lesage F, Obrig H, Tachtsidis I, Tak S, Tong Y, Torricelli A, Wabnitz H, Wolf M. Best practices for fNIRS publications. NEUROPHOTONICS 2021; 8:012101. [PMID: 33442557 PMCID: PMC7793571 DOI: 10.1117/1.nph.8.1.012101] [Citation(s) in RCA: 123] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 12/02/2020] [Indexed: 05/09/2023]
Abstract
The application of functional near-infrared spectroscopy (fNIRS) in the neurosciences has been expanding over the last 40 years. Today, it is addressing a wide range of applications within different populations and utilizes a great variety of experimental paradigms. With the rapid growth and the diversification of research methods, some inconsistencies are appearing in the way in which methods are presented, which can make the interpretation and replication of studies unnecessarily challenging. The Society for Functional Near-Infrared Spectroscopy has thus been motivated to organize a representative (but not exhaustive) group of leaders in the field to build a consensus on the best practices for describing the methods utilized in fNIRS studies. Our paper has been designed to provide guidelines to help enhance the reliability, repeatability, and traceability of reported fNIRS studies and encourage best practices throughout the community. A checklist is provided to guide authors in the preparation of their manuscripts and to assist reviewers when evaluating fNIRS papers.
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Affiliation(s)
- Meryem A. Yücel
- Boston University, Neurophotonics Center, Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
- Address all correspondence to Meryem A. Yücel,
| | - Alexander v. Lühmann
- Boston University, Neurophotonics Center, Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Felix Scholkmann
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Neonatology Research, Zurich, Switzerland
- University of Bern, Institute for Complementary and Integrative Medicine, Bern, Switzerland
| | - Judit Gervain
- Université de Paris, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
- Università di Padova, Department of Social and Developmental Psychology, Padua, Italy
| | - Ippeita Dan
- Chuo University, Faculty of Science and Engineering, Applied Cognitive Neuroscience Laboratory, Tokyo, Japan
| | - Hasan Ayaz
- Drexel University, School of Biomedical Engineering, Science and Health Systems, Philadelphia, Pennsylvania, United States
- Drexel University, College of Arts and Sciences, Department of Psychology, Philadelphia, Pennsylvania, United States
- Drexel University, Drexel Solutions Institute, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, Department of Family and Community Health, Philadelphia, Pennsylvania, United States
- Children’s Hospital of Philadelphia, Center for Injury Research and Prevention, Philadelphia, Pennsylvania, United States
| | - David Boas
- Boston University, Neurophotonics Center, Biomedical Engineering, Boston, Massachusetts, United States
| | - Robert J. Cooper
- University College London, DOT-HUB, Department of Medical Physics and Biomedical Engineering, Biomedical Optics Research Laboratory, London, United Kingdom
| | - Joseph Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Clare E. Elwell
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Adam Eggebrecht
- Washington University School of Medicine, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Maria A. Franceschini
- Massachusetts General Hospital, Harvard Medical School, MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Charlestown, Massachusetts, United States
| | - Christophe Grova
- Concordia University, Department of Physics and PERFORM Centre, Multimodal Functional Imaging Lab, Montreal, Québec, Canada
- McGill University, Biomedical Engineering Department, Multimodal Functional Imaging Lab, Montreal, Québec, Canada
| | - Fumitaka Homae
- Tokyo Metropolitan University, Department of Language Sciences, Tokyo, Japan
| | - Frédéric Lesage
- Polytechnique Montréal, Department Electrical Engineering, Montreal, Canada
| | - Hellmuth Obrig
- University Hospital Leipzig, Max-Planck-Institute for Human Cognitive and Brain Sciences and Clinic for Cognitive Neurology, Leipzig, Germany
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Sungho Tak
- Korea Basic Science Institute, Research Center for Bioconvergence Analysis, Ochang, Cheongju, Republic of Korea
| | - Yunjie Tong
- Weldon School of Biomedical Engineering Purdue University, West Lafayette, Indiana, United States
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Milan, Italy
- Consiglio Nazionale delle Ricerche, Istituto di Fotonica e Nanotecnologie, Milan, Italy
| | | | - Martin Wolf
- University Hospital Zurich, University of Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Neonatology Research, Zurich, Switzerland
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Sukal-Moulton T, de Campos AC, Alter KE, Damiano DL. Functional near-infrared spectroscopy to assess sensorimotor cortical activity during hand squeezing and ankle dorsiflexion in individuals with and without bilateral and unilateral cerebral palsy. NEUROPHOTONICS 2020; 7:045001. [PMID: 33062800 PMCID: PMC7536541 DOI: 10.1117/1.nph.7.4.045001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 09/04/2020] [Indexed: 05/10/2023]
Abstract
Significance: Our study is the first comparison of brain activation patterns during motor tasks across unilateral cerebral palsy (UCP), bilateral cerebral palsy (BCP), and typical development (TD) to elucidate neural mechanisms and inform rehabilitation strategies. Aim: Cortical activation patterns were compared for distal upper and lower extremity tasks in UCP, BCP, and TD using functional near-infrared spectroscopy (fNIRS) and related to functional severity. Approach: Individuals with UCP ( n = 10 , 18.8 ± 6.8 years ), BCP ( n = 14 , 17.5 ± 9.6 years ), and TD ( n = 16 , 17.3 ± 9.1 years ) participated in this cross-sectional cohort study. The fNIRS was used to noninvasively monitor the hemodynamic response to task-related cortical activation. The block design involved repetitive nondominant hand squeezing and ankle dorsiflexion. Results: Individuals with UCP demonstrated the highest levels of activation for the squeeze task ( UCP > BCP q = 0.049 ; BCP > TD q < 0.001 ; and UCP > TD q = 0.001 ) and more activity in the ipsilateral versus contralateral hemisphere. Individuals with BCP showed the highest levels of cortical activation in the dorsiflexion task ( BCP > UCP q < 0.001 ; BCP > TD ). Conclusions: Grouping by CP subtype and manual function or mobility level demonstrated significant differences from TD, even for individuals with the mildest forms of CP. Hemispheric activation patterns showed hypothesized but nonsignificant trends.
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Affiliation(s)
- Theresa Sukal-Moulton
- Northwestern University Feinberg School of Medicine, Department of Physical Therapy and Human Movement Sciences, Department of Pediatrics, Chicago, Illinois, United States
| | - Ana C. de Campos
- Federal University of São Carlos, Department of Physical Therapy, São Carlos, Brazil
| | - Katharine E. Alter
- National Institutes of Health, Clinical Center, Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, Bethesda, Maryland, United States
| | - Diane L. Damiano
- National Institutes of Health, Clinical Center, Functional and Applied Biomechanics Section, Rehabilitation Medicine Department, Bethesda, Maryland, United States
- Address all correspondence to Diane L Damiano,
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Hori D, Sasahara S, Doki S, Oi Y, Matsuzaki I. Prefrontal activation while listening to a letter of gratitude read aloud by a coworker face-to-face: A NIRS study. PLoS One 2020; 15:e0238715. [PMID: 32898150 PMCID: PMC7478838 DOI: 10.1371/journal.pone.0238715] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Accepted: 08/21/2020] [Indexed: 11/30/2022] Open
Abstract
Near-infrared spectroscopy (NIRS) is a non-invasive functional brain imaging technique. NIRS is suitable for monitoring brain activation during social interactions. One of the omnipresent social interactions for employees is saying thank you and being thanked. It has been demonstrated that expressing and receiving gratitude leads to employees’ well-being and performance. To date, there have been no neuroimaging studies that monitor brain activity when receiving gratitude. Thus, we designed an experiment using NIRS to monitor brain function while listening to a letter of gratitude read by a coworker. We hypothesized that listening to a letter of gratitude read aloud by a co-worker in a face-to-face setting would have different effects on PFC activity than listening to a conversation about a neutral topic. We recruited 10 pairs of healthy right-handed employees. They were asked to write a letter of gratitude to their partner 1 week before the experiment. In the experiment, each pair sat face-to-face and read their letters aloud to each other. We evaluated changes in mood state before and after the experiment. NIRS was measured in each participant while they listened to their peers in the experimental condition (gratitude letter) and control condition (talking about the weather and date). The results suggested that negative mood state decreased after the experiment. Moreover, there were interaction effects between conditions and periods. Although further studies are needed to confirm the interpretation, our findings suggested that experience of being thanked was accompanied by prefrontal cortex activation.
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Affiliation(s)
- Daisuke Hori
- Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan
- * E-mail:
| | | | - Shotaro Doki
- Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Yuichi Oi
- Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan
| | - Ichiyo Matsuzaki
- Faculty of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan
- International Institute for Integrative Sleep Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan
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Yang B, Gu X, Gu C, Xu D, Fan C. Review of pathological index detection and new rehabilitation technique of drug addicts. BRAIN SCIENCE ADVANCES 2020. [DOI: 10.26599/bsa.2020.9050010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022] Open
Abstract
There are two major research issues with regard to detoxification; one is pathological testing of drug users and the other is rehabilitation methods and techniques. Over the years, domestic and foreign researchers have done a lot of work on pathological changes in the brain and rehabilitation techniques for drug users. This article discusses the research status of these two aspects. At present, the evaluation of brain function in drug addicts is still dominated by a single electroencephalography (EEG), near-infrared spectroscopy (NIRS), or magnetic resonance imaging scan. The multimodal physiological data acquisition method based on EEG–NIRS technique is relatively advantageous for actual physiological data acquisition. The traditional drug rehabilitation method is based on medication and psychological counseling. In recent years, psychological correction (e.g., emotional ventilation, intelligent physical and mental decompression, virtual reality technique and drug addiction suppression system, sports training, and rehabilitation) and physical therapy (transcranial magnetic stimulation) have gradually spread. These rehabilitations focus on comprehensive treatment from the psychological and physical aspects. In recent years, new intervention ideas such as brain–computer interface technique have been continuously proposed. In this review, we have introduced multimodal brain function detection and rehabilitation intervention, which have theoretical and practical significance in drug rehabilitation research.
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Affiliation(s)
- Banghua Yang
- School of Mechanical and Electrical Engineering and Automation, Shanghai University, Shanghai 200444, China
| | - Xuelin Gu
- School of Mechanical and Electrical Engineering and Automation, Shanghai University, Shanghai 200444, China
| | - Chao Gu
- Shanghai Qingdong Drug Rehabilitation Center, Shanghai 201701, China
| | - Ding Xu
- Shanghai Drug Rehabilitation Administration, Shanghai 200080, China
| | - Chengcheng Fan
- School of Mechanical and Electrical Engineering and Automation, Shanghai University, Shanghai 200444, China
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Orcioli-Silva D, Vitório R, Beretta VS, da Conceição NR, Nóbrega-Sousa P, Oliveira AS, Gobbi LTB. Is Cortical Activation During Walking Different Between Parkinson’s Disease Motor Subtypes? J Gerontol A Biol Sci Med Sci 2020; 76:561-567. [DOI: 10.1093/gerona/glaa174] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Indexed: 11/12/2022] Open
Abstract
Abstract
Parkinson’s disease (PD) is often classified into tremor dominant (TD) and postural instability gait disorder (PIGD) subtypes. Degeneration of subcortical/cortical pathways is different between PD subtypes, which leads to differences in motor behavior. However, the influence of PD subtype on cortical activity during walking remains poorly understood. Therefore, we aimed to investigate the influence of PD motor subtypes on cortical activity during unobstructed walking and obstacle avoidance. Seventeen PIGD and 19 TD patients performed unobstructed walking and obstacle avoidance conditions. Brain activity was measured using a mobile functional near-infrared spectroscopy–electroencephalography (EEG) systems, and gait parameters were analyzed using an electronic carpet. Concentrations of oxygenated hemoglobin (HbO2) of the prefrontal cortex (PFC) and EEG absolute power from alpha, beta, and gamma bands in FCz, Cz, CPz, and Oz channels were calculated. These EEG channels correspond to supplementary motor area, primary motor cortex, posterior parietal cortex, and visual cortex, respectively. Postural instability gait disorder patients presented higher PFC activity than TD patients, regardless of the walking condition. Tremor dominant patients presented reduced beta power in the Cz channel during obstacle avoidance compared to unobstructed walking. Both TD and PIGD patients decreased alpha and beta power in the FCz and CPz channels. In conclusion, PIGD patients need to recruit additional cognitive resources from the PFC for walking. Both TD and PIGD patients presented changes in the activation of brain areas related to motor/sensorimotor areas in order to maintain balance control during obstacle avoidance, being that TD patients presented further changes in the motor area (Cz channel) to avoid obstacles.
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Affiliation(s)
- Diego Orcioli-Silva
- São Paulo State University (UNESP), Institute of Biosciences, Posture and Gait Studies Laboratory (LEPLO), Rio Claro, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro, Brazil
| | - Rodrigo Vitório
- São Paulo State University (UNESP), Institute of Biosciences, Posture and Gait Studies Laboratory (LEPLO), Rio Claro, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro, Brazil
- Department of Neurology, Oregon Health and Science University, Portland
| | - Victor Spiandor Beretta
- São Paulo State University (UNESP), Institute of Biosciences, Posture and Gait Studies Laboratory (LEPLO), Rio Claro, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro, Brazil
| | - Núbia Ribeiro da Conceição
- São Paulo State University (UNESP), Institute of Biosciences, Posture and Gait Studies Laboratory (LEPLO), Rio Claro, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro, Brazil
| | - Priscila Nóbrega-Sousa
- São Paulo State University (UNESP), Institute of Biosciences, Posture and Gait Studies Laboratory (LEPLO), Rio Claro, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro, Brazil
| | | | - Lilian Teresa Bucken Gobbi
- São Paulo State University (UNESP), Institute of Biosciences, Posture and Gait Studies Laboratory (LEPLO), Rio Claro, Brazil
- Graduate Program in Movement Sciences, São Paulo State University (UNESP), Rio Claro, Brazil
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Cheong D, Zhang F, Kim K, Reid A, Hanan C, Ding L, Yuan H. Task-Related Systemic Artifacts 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 2020; 2020:948-951. [PMID: 33018141 DOI: 10.1109/embc44109.2020.9176366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) has the potential to become the next common noninvasive neuroimaging technique for routine clinical use. Compared to the current standard for neuroimaging, functional magnetic resonance imaging (fMRI), fNIRS boasts several advantages which increase its likelihood for clinical adoption. However, fNIRS suffers from an intrinsic interference from the superficial tissues, which the near-infrared light must penetrate before reaching the deeper cerebral cortex. Therefore, the removal of signals captured by SS channels has been proposed to attenuate the systematic interference. This study aimed to investigate the task-related systemic artefacts, in a high-density montage covering the sensorimotor cortex. We compared the association between LS and SS channels over the contralateral motor cortex which was activated by a hand clenching task, with that over the ipsilateral cortex where no task-related activation was expected. Our findings provide important guidelines regarding how to removal SS signals in a high-density whole-head montage.
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Trambaiolli LR, Cassani R, Falk TH. EEG spectro-temporal amplitude modulation as a measurement of cortical hemodynamics: an EEG-fNIRS study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2020:3481-3484. [PMID: 33018753 DOI: 10.1109/embc44109.2020.9175409] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Neurovascular coupling provides valuable descriptive information about neural function and communication. In this work, we propose to objectively characterize EEG sub-band modulation in an attempt to compare with local variations of fNIRS hemoglobin concentration. First, full-band EEG signals are decomposed into five well-known frequency sub-bands: delta, theta, alpha, beta, and gamma. The temporal amplitude envelope of each sub-band is then computed via Hilbert transformation. The proposed EEG 'spectro-temporal amplitude modulation' (EEG-AM) feature measures the rate at which each sub-band is modulated. Similarities between EEG-AM features and fNIRS hemoglobin concentration are computed for four neighboring channels over the occipital area during resting-state. Experiments with a database of 29 participants show statistically significant similarities between the total hemoglobin concentration and the alpha band modulating the alpha, beta, and gamma frequencies. These results support the idea that the EEG-AM can carry hemodynamic properties.Clinical relevance- This shows that the EEG spectro-temporal amplitude modulation present similarities with the hemoglobin concentration in co-placed channels.
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Chiarelli AM, Perpetuini D, Croce P, Greco G, Mistretta L, Rizzo R, Vinciguerra V, Romeo MF, Zappasodi F, Merla A, Fallica PG, Edlinger G, Ortner R, Giaconia GC. Fiberless, Multi-Channel fNIRS-EEG System Based on Silicon Photomultipliers: Towards Sensitive and Ecological Mapping of Brain Activity and Neurovascular Coupling. SENSORS (BASEL, SWITZERLAND) 2020; 20:E2831. [PMID: 32429372 PMCID: PMC7285196 DOI: 10.3390/s20102831] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 05/08/2020] [Accepted: 05/13/2020] [Indexed: 11/17/2022]
Abstract
Portable neuroimaging technologies can be employed for long-term monitoring of neurophysiological and neuropathological states. Functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalography (EEG) are highly suited for such a purpose. Their multimodal integration allows the evaluation of hemodynamic and electrical brain activity together with neurovascular coupling. An innovative fNIRS-EEG system is here presented. The system integrated a novel continuous-wave fNIRS component and a modified commercial EEG device. fNIRS probing relied on fiberless technology based on light emitting diodes and silicon photomultipliers (SiPMs). SiPMs are sensitive semiconductor detectors, whose large detection area maximizes photon harvesting from the scalp and overcomes limitations of fiberless technology. To optimize the signal-to-noise ratio and avoid fNIRS-EEG interference, a digital lock-in was implemented for fNIRS signal acquisition. A benchtop characterization of the fNIRS component showed its high performances with a noise equivalent power below 1 pW. Moreover, the fNIRS-EEG device was tested in vivo during tasks stimulating visual, motor and pre-frontal cortices. Finally, the capabilities to perform ecological recordings were assessed in clinical settings on one Alzheimer's Disease patient during long-lasting cognitive tests. The system can pave the way to portable technologies for accurate evaluation of multimodal brain activity, allowing their extensive employment in ecological environments and clinical practice.
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Affiliation(s)
- Antonio Maria Chiarelli
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (F.Z.); (A.M.)
| | - David Perpetuini
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (F.Z.); (A.M.)
| | - Pierpaolo Croce
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (F.Z.); (A.M.)
| | - Giuseppe Greco
- Department of Energy, Engineering and Mathematical Models, University of Palermo, Viale delle Scienze 9, 90128 Palermo, Italy; (G.G.); (L.M.); (R.R.); (G.C.G.)
| | - Leonardo Mistretta
- Department of Energy, Engineering and Mathematical Models, University of Palermo, Viale delle Scienze 9, 90128 Palermo, Italy; (G.G.); (L.M.); (R.R.); (G.C.G.)
| | - Raimondo Rizzo
- Department of Energy, Engineering and Mathematical Models, University of Palermo, Viale delle Scienze 9, 90128 Palermo, Italy; (G.G.); (L.M.); (R.R.); (G.C.G.)
| | - Vincenzo Vinciguerra
- ADG R&D, STMicroelectronics s.r.l., Stradale Primosole 50, 95121 Catania, Italy; (V.V.); (M.F.R.); (P.G.F.)
| | - Mario Francesco Romeo
- ADG R&D, STMicroelectronics s.r.l., Stradale Primosole 50, 95121 Catania, Italy; (V.V.); (M.F.R.); (P.G.F.)
| | - Filippo Zappasodi
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (F.Z.); (A.M.)
| | - Arcangelo Merla
- Department of Neuroscience, Imaging and Clinical Sciences, Institute for Advanced Biomedical Technologies, University G. D’Annunzio of Chieti-Pescara, Via Luigi Polacchi 13, 66100 Chieti, Italy; (D.P.); (P.C.); (F.Z.); (A.M.)
| | - Pier Giorgio Fallica
- ADG R&D, STMicroelectronics s.r.l., Stradale Primosole 50, 95121 Catania, Italy; (V.V.); (M.F.R.); (P.G.F.)
| | - Günter Edlinger
- Guger Technologies OG, Herbersteinstrasse 60, 8020 Graz, Austria;
| | - Rupert Ortner
- g.tec Medical Engineering Spain S.L., Calle Plom 5-7, 08038 Barcelona, Spain;
| | - Giuseppe Costantino Giaconia
- Department of Energy, Engineering and Mathematical Models, University of Palermo, Viale delle Scienze 9, 90128 Palermo, Italy; (G.G.); (L.M.); (R.R.); (G.C.G.)
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Dutta A, Das A, Kondziella D, Stachowiak MK. Bioenergy Crisis in Coronavirus Diseases? Brain Sci 2020; 10:E277. [PMID: 32370257 PMCID: PMC7287678 DOI: 10.3390/brainsci10050277] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 04/12/2020] [Accepted: 04/16/2020] [Indexed: 12/22/2022] Open
Abstract
Coronavirus disease (COVID-19) has been declared as a pandemic by the World Health Organization (WHO).[...].
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Affiliation(s)
- Anirban Dutta
- Department of Biomedical Engineering, University at Buffalo, Buffalo, NY 14260, USA
| | - Abhijit Das
- Department of Neurology, The Walton Centre NHS Foundation Trust, Liverpool L9 7LJ, UK;
| | - Daniel Kondziella
- Department of Neurology, Rigshospitalet, Copenhagen University Hospital, 2100 Copenhagen, Denmark;
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Michal K. Stachowiak
- Department of Pathology and Anatomical Sciences, University at Buffalo, Buffalo, NY 14203, USA;
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48
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Chiarelli AM, Giaconia GC, Perpetuini D, Greco G, Mistretta L, Rizzo R, Vinciguerra V, Romeo MF, Merla A, Fallica PG. Wearable, Fiber-less, Multi-Channel System for Continuous Wave Functional Near Infrared Spectroscopy Based on Silicon Photomultipliers Detectors and Lock-In Amplification. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2020; 2019:60-66. [PMID: 31945845 DOI: 10.1109/embc.2019.8857206] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
Development and in-vivo validation of a Continuous Wave (CW) functional Near Infrared Spectroscopy (fNIRS) system is presented. The system is wearable, fiber-less, multi-channel (16×16, 256 channels) and expandable and it relies on silicon photomultipliers (SiPMs) for light detection. SiPMs are inexpensive, low voltage and resilient semiconductor light detectors, whose performances are analogous to photomultiplier tubes (PMTs). The advantage of SiPMs with respect to PMTs is that they allow direct contact with the scalp and avoidance of optical fibers. In fact, the coupling of SiPMs and light emitting diodes (LEDs) allows the transfer of the analog signals to and from the scalp through thin electric cables that greatly increase the system flexibility. Moreover, the optical probes, mechanically resembling electroencephalographic electrodes, are robust against motion artifacts. In order to increase the signal-to-noise-ratio (SNR) of the fNIRS acquisition and to decrease ambient noise contamination, a digital lock-in technique was implemented through LEDs modulation and SiPMs signal processing chain. In-vivo validation proved the system capabilities of detecting functional brain activity in the sensorimotor cortices. When compared to other state-of-the-art wearable fNIRS systems, the single photon sensitivity and dynamic range of SiPMs can exploit the long and variable interoptode distances needed for estimation of brain functional hemodynamics using CW-fNIRS.
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Relationship Between Cerebral Blood Oxygenation and Electrical Activity During Mental Stress Tasks: Simultaneous Measurements of NIRS and EEG. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2020; 1232:99-104. [PMID: 31893400 DOI: 10.1007/978-3-030-34461-0_14] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The incidence of stress-induced psychological and somatic diseases has been increasing rapidly, and it is important to clarify the neurophysiological mechanisms of stress response in order to establish effective stress management methods. We previously reported that the prefrontal cortex (PFC) plays an important role in stress response. In the present study, we employed near-infrared spectroscopy (NIRS) and electroencephalography (EEG) to investigate the characteristics of PFC activity during mental arithmetic tasks. A two-channel NIRS device was used to measure hemoglobin (Hb) concentration changes in the bilateral PFC during a mental arithmetic task (2 min) in normal adults. Simultaneously, EEG was used to also measure bilateral PFC activity during the same task. We evaluated concentration changes of oxy-Hb induced by the task while analyzing α wave changes using power spectrum analysis. It was observed that oxy-Hb in the bilateral PFC increased significantly during the task (p < 0.05), while α wave power in the PFC decreased significantly (p < 0.01). The present results indicate that mental stress tasks caused the activation of the bilateral PFC. Simultaneous measurements of NIRS and EEG are useful for evaluating the neurophysiological mechanism of stress responses in the brain.
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50
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Epileptic seizures identification with autoregressive model and firefly optimization based classification. EVOLVING SYSTEMS 2019. [DOI: 10.1007/s12530-019-09319-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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