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Marques Paulo AJ, Sato JR, de Faria DD, Balardin J, Borges V, de Azevedo Silva SM, Ballalai Ferraz H, de Carvalho Aguiar P. Task-related brain activity in upper limb dystonia revealed by simultaneous fNIRS and EEG. Clin Neurophysiol 2024; 159:1-12. [PMID: 38232654 DOI: 10.1016/j.clinph.2023.12.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 11/21/2023] [Accepted: 12/12/2023] [Indexed: 01/19/2024]
Abstract
OBJECTIVE The aim of this study was to explore differences in brain activity and connectivity using simultaneous electroencephalography and near-infrared spectroscopy in patients with focal dystonia during handwriting and finger-tapping tasks. METHODS Patients with idiopathic right upper limb focal dystonia and controls were assessed by simultaneous near-infrared spectroscopy and electroencephalography during the writing and finger-tapping tasks in terms of the mu-alpha, mu-beta, beta and low gamma power and effective connectivity, as well as relative changes in oxyhemoglobin (oxy-Hb) and deoxyhemoglobin using a channel-wise approach with a mixed-effect model. RESULTS Patients exhibited higher oxy-Hb levels in the right and left motor cortex and supplementary motor area during writing, but lower oxy-Hb levels in the left sensorimotor and bilateral somatosensory area during finger-tapping compared to controls. During writing, patients showed increased low gamma power in the bilateral sensorimotor cortex and less mu-beta and beta attenuation compared to controls. Additionally, patients had reduced connectivity between the supplementary motor area and the left sensorimotor cortex during writing. No differences were observed in terms of effective connectivity in either task. Finally, patients failed to attenuate the mu-alpha, mu-beta, and beta rhythms during the finger-tapping task. CONCLUSIONS Cortical blood flow and EEG spectral power differ between controls and dystonia patients, depending on the task. Writing increased blood flow and altered connectivity in dystonia patients, and it also decreased slow-band attenuation. Finger-tapping decreased blood flow and slow-band attenuation. SIGNIFICANCE Simultaneous fNIRS and EEG may show relevant information regarding brain dynamics in movement disorders patients in unconstrained environments.
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Affiliation(s)
- Artur José Marques Paulo
- Hospital Israelita Albert Einstein, Instituto de Ensino e Pesquisa, Av. Albert Einstein, 627, São Paulo-SP 05652-900, Brazil
| | - João Ricardo Sato
- Hospital Israelita Albert Einstein, Instituto de Ensino e Pesquisa, Av. Albert Einstein, 627, São Paulo-SP 05652-900, Brazil; Universidade Federal do ABC, Centro de Matemática Computação e Cognição , São Bernardo do Campo-SP , 09606-045, Brazil
| | - Danilo Donizete de Faria
- Universidade Federal de São Paulo, Department of Neurology and Neurosurgery, R. Pedro de Toledo, 650, São Paulo - SP 04039-002, Brazil; Hospital do Servidor Público Estadual, Av. Ibirapuera, 981 - Vila Clementino, São Paulo - SP 04038-034, Brazil
| | - Joana Balardin
- Hospital Israelita Albert Einstein, Instituto de Ensino e Pesquisa, Av. Albert Einstein, 627, São Paulo-SP 05652-900, Brazil
| | - Vanderci Borges
- Universidade Federal de São Paulo, Department of Neurology and Neurosurgery, R. Pedro de Toledo, 650, São Paulo - SP 04039-002, Brazil
| | - Sonia Maria de Azevedo Silva
- Universidade Federal de São Paulo, Department of Neurology and Neurosurgery, R. Pedro de Toledo, 650, São Paulo - SP 04039-002, Brazil; Hospital do Servidor Público Estadual, Av. Ibirapuera, 981 - Vila Clementino, São Paulo - SP 04038-034, Brazil
| | - Henrique Ballalai Ferraz
- Universidade Federal de São Paulo, Department of Neurology and Neurosurgery, R. Pedro de Toledo, 650, São Paulo - SP 04039-002, Brazil
| | - Patrícia de Carvalho Aguiar
- Hospital Israelita Albert Einstein, Instituto de Ensino e Pesquisa, Av. Albert Einstein, 627, São Paulo-SP 05652-900, Brazil; Universidade Federal de São Paulo, Department of Neurology and Neurosurgery, R. Pedro de Toledo, 650, São Paulo - SP 04039-002, Brazil.
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2
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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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3
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Lin J, Lu J, Shu Z, Yu N, Han J. An EEG-fNIRS neurovascular coupling analysis method to investigate cognitive-motor interference. Comput Biol Med 2023; 160:106968. [PMID: 37196454 DOI: 10.1016/j.compbiomed.2023.106968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/27/2023] [Accepted: 04/19/2023] [Indexed: 05/19/2023]
Abstract
BACKGROUND AND OBJECTIVE The simultaneous execution of a motor and cognitive dual task may lead to the deterioration of task performance in one or both tasks due to cognitive-motor interference (CMI). Neuroimaging techniques are promising ways to reveal the underlying neural mechanism of CMI. However, existing studies have only explored CMI from a single neuroimaging modality, which lack built-in validation and comparison of analysis results. This work is aimed to establish an effective analysis framework to comprehensively investigate the CMI by exploring the electrophysiological and hemodynamic activities as well as their neurovascular coupling. METHODS Experiments including an upper limb single motor task, single cognitive task, and cognitive-motor dual task were designed and performed with 16 healthy young participants. Bimodal signals of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) were recorded simultaneously during the experiments. A novel bimodal signal analysis framework was proposed to extract the task-related components for EEG and fNIRS signals respectively and analyze their correlation. Indicators including within-class similarity and between-class distance were utilized to validate the effectiveness of the proposed analysis framework compared to the canonical channel-averaged method. Statistical analysis was performed to investigate the difference in the behavior and neural correlates between the single and dual tasks. RESULTS Our results revealed that the extra cognitive interference caused divided attention in the dual task, which led to the decreased neurovascular coupling between fNIRS and EEG in all theta, alpha, and beta rhythms. The proposed framework was demonstrated to have a better ability in characterizing the neural patterns than the canonical channel-averaged method with significantly higher within-class similarity and between-class distance indicators. CONCLUSIONS This study proposed a method to investigate CMI by exploring the task-related electrophysiological and hemodynamic activities as well as their neurovascular coupling. Our concurrent EEG-fNIRS study provides new insight into the EEG-fNIRS correlation analysis and novel evidence for the mechanism of neurovascular coupling in the CMI.
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Affiliation(s)
- Jianeng Lin
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China
| | - Jiewei Lu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China
| | - Zhilin Shu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China
| | - Ningbo Yu
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China; Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China.
| | - Jianda Han
- College of Artificial Intelligence, Nankai University, Tianjin 300350, China; Engineering Research Center of Trusted Behavior Intelligence, Ministry of Education, Nankai University, Tianjin 300350, China; Tianjin Key Laboratory of Intelligent Robotics, Nankai University, Tianjin 300350, China; Institute of Intelligence Technology and Robotic Systems, Shenzhen Research Institute of Nankai University, Shenzhen 518083, China.
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Christensen J, Slavik L, Nicol JJ, Loehr JD. Alpha oscillations related to self-other integration and distinction during live orchestral performance: A naturalistic case study. PSYCHOLOGY OF MUSIC 2023; 51:295-315. [PMID: 36532616 PMCID: PMC9751440 DOI: 10.1177/03057356221091313] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Ensemble music performance requires musicians to achieve precise interpersonal coordination while maintaining autonomous control over their own actions. To do so, musicians dynamically shift between integrating other performers' actions into their own action plans and maintaining a distinction between their own and others' actions. Research in laboratory settings has shown that this dynamic process of self-other integration and distinction is indexed by sensorimotor alpha oscillations. The purpose of the current descriptive case study was to examine oscillations related to self-other integration and distinction in a naturalistic performance context. We measured alpha activity from four violinists during a concert hall performance of a 60-musician orchestra. We selected a musical piece from the orchestra's repertoire and, before analyzing alpha activity, performed a score analysis to divide the piece into sections that were expected to strongly promote self-other integration and distinction. In line with previous laboratory findings, performers showed suppressed and enhanced alpha activity during musical sections that promoted self-other integration and distinction, respectively. The current study thus provides preliminary evidence that findings from carefully controlled laboratory experiments generalize to complex real-world performance. Its findings also suggest directions for future research and potential applications of interest to musicians, music educators, and music therapists.
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Affiliation(s)
| | - Lauren Slavik
- Department of Psychology, University of Saskatchewan, Saskatoon, Canada
| | - Jennifer J Nicol
- Department of Educational Psychology and Special Education, University of Saskatchewan, Saskatoon, Canada
| | - Janeen D Loehr
- Department of Psychology, University of Saskatchewan, Saskatoon, Canada
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5
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Wang Y, Yang Z, Ji H, Li J, Liu L, Zhuang J. Cross-Modal Transfer Learning From EEG to Functional Near-Infrared Spectroscopy for Classification Task in Brain-Computer Interface System. Front Psychol 2022; 13:833007. [PMID: 35465540 PMCID: PMC9021696 DOI: 10.3389/fpsyg.2022.833007] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 03/07/2022] [Indexed: 11/13/2022] Open
Abstract
The brain-computer interface (BCI) based on functional near-infrared spectroscopy (fNIRS) has received more and more attention due to its vast application potential in emotion recognition. However, the relatively insufficient investigation of the feature extraction algorithms limits its use in practice. In this article, to improve the performance of fNIRS-based BCI, we proposed a method named R-CSP-E, which introduces EEG signals when computing fNIRS signals' features based on transfer learning and ensemble learning theory. In detail, we used the Independent Component Analysis (ICA) algorithm for the correspondence between the sources of the two signals. We then introduced the EEG signals when computing the spatial filter based on a modified Common Spatial Pattern (CSP) algorithm. Experimental results on public datasets show that the proposed method in this paper outperforms traditional methods without transfer. In general, the mean classification accuracy can be increased by up to 5%. To our knowledge, it is an innovation that we tried to apply transfer learning between EEG and fNIRS. Our study's findings not only prove the potential of the transfer learning algorithm in cross-model brain-computer interface, but also offer a new and innovative perspective to research the hybrid brain-computer interface.
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Affiliation(s)
- Yuqing Wang
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Collage of Electronic and Information Engineering, Tongji University, Shanghai, China
| | - Zhiqiang Yang
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Collage of Electronic and Information Engineering, Tongji University, Shanghai, China
| | - Hongfei Ji
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Collage of Electronic and Information Engineering, Tongji University, Shanghai, China
| | - Jie Li
- Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), Collage of Electronic and Information Engineering, Tongji University, Shanghai, China
| | - Lingyu Liu
- Department of Neurorehabilitation, Shanghai Yangzhi Rehabilitation Hospital (Shanghai Sunshine Rehabilitation Center), School of Medicine, Tongji University, Shanghai, China
| | - Jie Zhuang
- School of Psychology, Shanghai University of Sport, Shanghai, China
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6
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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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7
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Kwak Y, Song WJ, Kim SE. FGANet: fNIRS-guided Attention Network for Hybrid EEG-fNIRS Brain-Computer Interfaces. IEEE Trans Neural Syst Rehabil Eng 2022; 30:329-339. [PMID: 35130163 DOI: 10.1109/tnsre.2022.3149899] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Non-invasive brain-computer interfaces (BCIs) have been widely used for neural decoding, linking neural signals to control devices. Hybrid BCI systems using electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have received significant attention for overcoming the limitations of EEG- and fNIRS-standalone BCI systems. However, most hybrid EEG-fNIRS BCI studies have focused on late fusion because of discrepancies in their temporal resolutions and recording locations. Despite the enhanced performance of hybrid BCIs, late fusion methods have difficulty in extracting correlated features in both EEG and fNIRS signals. Therefore, in this study, we proposed a deep learning-based early fusion structure, which combines two signals before the fully-connected layer, called the fNIRS-guided attention network (FGANet). First, 1D EEG and fNIRS signals were converted into 3D EEG and fNIRS tensors to spatially align EEG and fNIRS signals at the same time point. The proposed fNIRS-guided attention layer extracted a joint representation of EEG and fNIRS tensors based on neurovascular coupling, in which the spatially important regions were identified from fNIRS signals, and detailed neural patterns were extracted from EEG signals. Finally, the final prediction was obtained by weighting the sum of the prediction scores of the EEG and fNIRS-guided attention features to alleviate performance degradation owing to delayed fNIRS response. In the experimental results, the FGANet significantly outperformed the EEG-standalone network. Furthermore, the FGANet has 4.0% and 2.7% higher accuracy than the state-of-the-art algorithms in mental arithmetic and motor imagery tasks, respectively.
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8
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de With LA, Thammasan N, Poel M. Detecting Fear of Heights Response to a Virtual Reality Environment Using Functional Near-Infrared Spectroscopy. FRONTIERS IN COMPUTER SCIENCE 2022. [DOI: 10.3389/fcomp.2021.652550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
To enable virtual reality exposure therapy (VRET) that treats anxiety disorders by gradually exposing the patient to fear using virtual reality (VR), it is important to monitor the patient's fear levels during the exposure. Despite the evidence of a fear circuit in the brain as reflected by functional near-infrared spectroscopy (fNIRS), the measurement of fear response in highly immersive VR using fNIRS is limited, especially in combination with a head-mounted display (HMD). In particular, it is unclear to what extent fNIRS can differentiate users with and without anxiety disorders and detect fear response in a highly ecological setting using an HMD. In this study, we investigated fNIRS signals captured from participants with and without a fear of height response. To examine the extent to which fNIRS signals of both groups differ, we conducted an experiment during which participants with moderate fear of heights and participants without it were exposed to VR scenarios involving heights and no heights. The between-group statistical analysis shows that the fNIRS data of the control group and the experimental group are significantly different only in the channel located close to right frontotemporal lobe, where the grand average oxygenated hemoglobin Δ[HbO] contrast signal of the experimental group exceeds that of the control group. The within-group statistical analysis shows significant differences between the grand average Δ[HbO] contrast values during fear responses and those during no-fear responses, where the Δ[HbO] contrast values of the fear responses were significantly higher than those of the no-fear responses in the channels located towards the frontal part of the prefrontal cortex. Also, the channel located close to frontocentral lobe was found to show significant difference for the grand average deoxygenated hemoglobin contrast signals. Support vector machine-based classifier could detect fear responses at an accuracy up to 70% and 74% in subject-dependent and subject-independent classifications, respectively. The results demonstrate that cortical hemodynamic responses of a control group and an experimental group are different to a considerable extent, exhibiting the feasibility and ecological validity of the combination of VR-HMD and fNIRS to elicit and detect fear responses. This research thus paves a way toward the a brain-computer interface to effectively manipulate and control VRET.
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9
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Processing of fMRI-related anxiety and bi-directional information flow between prefrontal cortex and brain stem. Sci Rep 2021; 11:22348. [PMID: 34785719 PMCID: PMC8595881 DOI: 10.1038/s41598-021-01710-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 10/19/2021] [Indexed: 12/30/2022] Open
Abstract
Brain-heart synchronization is fundamental for emotional-well-being and brain-heart desynchronization is characteristic for anxiety disorders including specific phobias. Recording BOLD signals with functional magnetic resonance imaging (fMRI) is an important noninvasive diagnostic tool; however, 1-2% of fMRI examinations have to be aborted due to claustrophobia. In the present study, we investigated the information flow between regions of interest (ROI's) in the cortex and brain stem by using a frequency band close to 0.1 Hz. Causal coupling between signals important in brain-heart interaction (cardiac intervals, respiration, and BOLD signals) was studied by means of Directed Transfer Function based on the Granger causality principle. Compared were initial resting states with elevated anxiety and final resting states with low or no anxiety in a group of fMRI-naïve young subjects. During initial high anxiety the results showed an increased information flow from the middle frontal gyrus (MFG) to the pre-central gyrus (PCG) and to the brainstem. There also was an increased flow from the brainstem to the PCG. While the top-down flow during increased anxiety was predominant, the weaker ascending flow from brainstem structures may characterize a rhythmic pacemaker-like activity that (at least in part) drives respiration. We assume that these changes in information flow reflect successful anxiety processing.
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10
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Lu HY, Lorenc ES, Zhu H, Kilmarx J, Sulzer J, Xie C, Tobler PN, Watrous AJ, Orsborn AL, Lewis-Peacock J, Santacruz SR. Multi-scale neural decoding and analysis. J Neural Eng 2021; 18. [PMID: 34284369 PMCID: PMC8840800 DOI: 10.1088/1741-2552/ac160f] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 07/20/2021] [Indexed: 12/15/2022]
Abstract
Objective. Complex spatiotemporal neural activity encodes rich information related to behavior and cognition. Conventional research has focused on neural activity acquired using one of many different measurement modalities, each of which provides useful but incomplete assessment of the neural code. Multi-modal techniques can overcome tradeoffs in the spatial and temporal resolution of a single modality to reveal deeper and more comprehensive understanding of system-level neural mechanisms. Uncovering multi-scale dynamics is essential for a mechanistic understanding of brain function and for harnessing neuroscientific insights to develop more effective clinical treatment. Approach. We discuss conventional methodologies used for characterizing neural activity at different scales and review contemporary examples of how these approaches have been combined. Then we present our case for integrating activity across multiple scales to benefit from the combined strengths of each approach and elucidate a more holistic understanding of neural processes. Main results. We examine various combinations of neural activity at different scales and analytical techniques that can be used to integrate or illuminate information across scales, as well the technologies that enable such exciting studies. We conclude with challenges facing future multi-scale studies, and a discussion of the power and potential of these approaches. Significance. This roadmap will lead the readers toward a broad range of multi-scale neural decoding techniques and their benefits over single-modality analyses. This Review article highlights the importance of multi-scale analyses for systematically interrogating complex spatiotemporal mechanisms underlying cognition and behavior.
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Affiliation(s)
- Hung-Yun Lu
- The University of Texas at Austin, Biomedical Engineering, Austin, TX, United States of America
| | - Elizabeth S Lorenc
- The University of Texas at Austin, Psychology, Austin, TX, United States of America.,The University of Texas at Austin, Institute for Neuroscience, Austin, TX, United States of America
| | - Hanlin Zhu
- Rice University, Electrical and Computer Engineering, Houston, TX, United States of America
| | - Justin Kilmarx
- The University of Texas at Austin, Mechanical Engineering, Austin, TX, United States of America
| | - James Sulzer
- The University of Texas at Austin, Mechanical Engineering, Austin, TX, United States of America.,The University of Texas at Austin, Institute for Neuroscience, Austin, TX, United States of America
| | - Chong Xie
- Rice University, Electrical and Computer Engineering, Houston, TX, United States of America
| | - Philippe N Tobler
- University of Zurich, Neuroeconomics and Social Neuroscience, Zurich, Switzerland
| | - Andrew J Watrous
- The University of Texas at Austin, Neurology, Austin, TX, United States of America
| | - Amy L Orsborn
- University of Washington, Electrical and Computer Engineering, Seattle, WA, United States of America.,University of Washington, Bioengineering, Seattle, WA, United States of America.,Washington National Primate Research Center, Seattle, WA, United States of America
| | - Jarrod Lewis-Peacock
- The University of Texas at Austin, Psychology, Austin, TX, United States of America.,The University of Texas at Austin, Institute for Neuroscience, Austin, TX, United States of America
| | - Samantha R Santacruz
- The University of Texas at Austin, Biomedical Engineering, Austin, TX, United States of America.,The University of Texas at Austin, Institute for Neuroscience, Austin, TX, United States of America
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11
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Abdalmalak A, Milej D, Norton L, Debicki DB, Owen AM, Lawrence KS. The Potential Role of fNIRS in Evaluating Levels of Consciousness. Front Hum Neurosci 2021; 15:703405. [PMID: 34305558 PMCID: PMC8296905 DOI: 10.3389/fnhum.2021.703405] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 05/31/2021] [Indexed: 12/13/2022] Open
Abstract
Over the last few decades, neuroimaging techniques have transformed our understanding of the brain and the effect of neurological conditions on brain function. More recently, light-based modalities such as functional near-infrared spectroscopy have gained popularity as tools to study brain function at the bedside. A recent application is to assess residual awareness in patients with disorders of consciousness, as some patients retain awareness albeit lacking all behavioural response to commands. Functional near-infrared spectroscopy can play a vital role in identifying these patients by assessing command-driven brain activity. The goal of this review is to summarise the studies reported on this topic, to discuss the technical and ethical challenges of working with patients with disorders of consciousness, and to outline promising future directions in this field.
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Affiliation(s)
- Androu Abdalmalak
- Department of Physiology and Pharmacology, Western University, London, ON, Canada.,Brain and Mind Institute, Western University, London, ON, Canada
| | - Daniel Milej
- Imaging Program, Lawson Health Research Institute, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada
| | - Loretta Norton
- Department of Psychology, King's College, Western University, London, ON, Canada
| | - Derek B Debicki
- Brain and Mind Institute, Western University, London, ON, Canada.,Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Adrian M Owen
- Department of Physiology and Pharmacology, Western University, London, ON, Canada.,Brain and Mind Institute, Western University, London, ON, Canada.,Department of Psychology, Western University, London, ON, Canada
| | - Keith St Lawrence
- Imaging Program, Lawson Health Research Institute, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada
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12
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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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13
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de Echegaray J, Moratti S. Threat imminence modulates neural gain in attention and motor relevant brain circuits in humans. Psychophysiology 2021; 58:e13849. [PMID: 34031900 DOI: 10.1111/psyp.13849] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 04/15/2021] [Accepted: 04/28/2021] [Indexed: 11/25/2022]
Abstract
Different levels of threat imminence elicit distinct computational strategies reflecting how the organism interacts with its environment in order to guarantee survival. Thereby, parasympathetically driven orienting and inhibition of on-going behavior in post-encounter situations and defense reactions in circa-strike conditions associated with sympathetically driven action preparation are typically observed across species. Here, we show that healthy humans are characterized by markedly variable individual orienting or defense response tendencies as indexed by differential heart rate (HR) changes during the passive viewing of unpleasant pictures. Critically, these HR response tendencies predict neural gain modulations in cortical attention and preparatory motor circuits as measured by neuromagnetic steady-state visual evoked fields (ssVEFs) and induced beta-band (19-30 Hz) desynchronization, respectively. Decelerative HR orienting responses were associated with increased ssVEF power in the parietal cortex and reduced beta-band desynchronization in pre-motor and motor areas. However, accelerative HR defense response tendencies covaried with reduced ssVEF power in the parietal cortex and lower beta-band desynchronization in cortical motor circuits. These results show that neural gain in attention- and motor-relevant brain areas is modulated by HR indexed threat imminence during the passive viewing of unpleasant pictures. The observed mutual ssVEF and beta-band power modulations in attention and motor brain circuits support the idea of two prevalent response tendencies characterized by orienting and motor inhibition or reduced stimulus processing and action initiation tendencies at different perceived threat imminence levels.
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Affiliation(s)
- Javier de Echegaray
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain.,Laboratory of Cognitive Neuroscience, Center for Biomedical Technology, Polytechnic University of Madrid, Madrid, Spain
| | - Stephan Moratti
- Department of Experimental Psychology, Complutense University of Madrid, Madrid, Spain.,Laboratory of Cognitive Neuroscience, Center for Biomedical Technology, Polytechnic University of Madrid, Madrid, Spain.,Laboratory of Clinical Neuroscience, Center for Biomedical Technology, Polytechnic University of Madrid, Madrid, Spain
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14
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Dans PW, Foglia SD, Nelson AJ. Data Processing in Functional Near-Infrared Spectroscopy (fNIRS) Motor Control Research. Brain Sci 2021; 11:606. [PMID: 34065136 PMCID: PMC8151801 DOI: 10.3390/brainsci11050606] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Revised: 05/05/2021] [Accepted: 05/07/2021] [Indexed: 12/26/2022] Open
Abstract
FNIRS pre-processing and processing methodologies are very important-how a researcher chooses to process their data can change the outcome of an experiment. The purpose of this review is to provide a guide on fNIRS pre-processing and processing techniques pertinent to the field of human motor control research. One hundred and twenty-three articles were selected from the motor control field and were examined on the basis of their fNIRS pre-processing and processing methodologies. Information was gathered about the most frequently used techniques in the field, which included frequency cutoff filters, wavelet filters, smoothing filters, and the general linear model (GLM). We discuss the methodologies of and considerations for these frequently used techniques, as well as those for some alternative techniques. Additionally, general considerations for processing are discussed.
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Affiliation(s)
- Patrick W. Dans
- Department of Kinesiology, McMaster University, Hamilton, ON L8S 4K1, Canada;
| | - Stevie D. Foglia
- School of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada;
| | - Aimee J. Nelson
- Department of Kinesiology, McMaster University, Hamilton, ON L8S 4K1, Canada;
- School of Biomedical Engineering, McMaster University, Hamilton, ON L8S 4K1, Canada;
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15
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Galati A, Schoppa R, Lu A. Exploring the SenseMaking Process through Interactions and fNIRS in Immersive Visualization. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2021; 27:2714-2724. [PMID: 33750695 DOI: 10.1109/tvcg.2021.3067693] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Theories of cognition inform our decisions when designing human-computer interfaces, and immersive systems enable us to examine these theories. This work explores the sensemaking process in an immersive environment through studying both internal and external user behaviors with a classical visualization problem: a visual comparison and clustering task. We developed an immersive system to perform a user study, collecting user behavior data from different channels: AR HMD for capturing external user interactions, functional near-infrared spectroscopy (fNIRS) for capturing internal neural sequences, and video for references. To examine sensemaking, we assessed how the layout of the interface (planar 2D vs. cylindrical 3D layout) and the challenge level of the task (low vs. high cognitive load) influenced the users' interactions, how these interactions changed over time, and how they influenced task performance. We also developed a visualization system to explore joint patterns among all the data channels. We found that increased interactions and cerebral hemodynamic responses were associated with more accurate performance, especially on cognitively demanding trials. The layout types did not reliably influence interactions or task performance. We discuss how these findings inform the design and evaluation of immersive systems, predict user performance and interaction, and offer theoretical insights about sensemaking from the perspective of embodied and distributed cognition.
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16
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Tablet Use Affects Preschoolers' Executive Function: fNIRS Evidence from the Dimensional Change Card Sort Task. Brain Sci 2021; 11:brainsci11050567. [PMID: 33946675 PMCID: PMC8146550 DOI: 10.3390/brainsci11050567] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 12/14/2022] Open
Abstract
This study aims to examine the impact of heavy use of tablets on preschoolers’ executive function during the Dimensional Change Card Sort (DCCS) task using the functional near-infrared spectroscopy (fNIRS). Altogether, 38 Chinese preschoolers (Mage = 5.0 years, SD = 0.69 years, 17 girls) completed the tasks before the COVID-19 lockdown. Eight children never used tablets, while 16 children were diagnosed as the ‘heavy-user’. The results indicated that: (1) the ‘non-user’ outperformed the ‘heavy-user’ with a significantly higher correct rate in the DCCS task; (2) the two groups differed significantly in the activation of the prefrontal cortex (BA 9): the ‘non-user’ pattern is normal and healthy, whereas the ‘heavy-user’ pattern is not normal and needs further exploration.
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17
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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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18
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Peng K, Karunakaran KD, Labadie R, Veliu M, Cheung C, Lee A, Yu PB, Upadhyay J. Suppressed prefrontal cortex oscillations associate with clinical pain in fibrodysplasia ossificans progressiva. Orphanet J Rare Dis 2021; 16:54. [PMID: 33516233 PMCID: PMC7847608 DOI: 10.1186/s13023-021-01709-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Accepted: 01/21/2021] [Indexed: 11/10/2022] Open
Abstract
Background Pain is a highly prevalent symptom experienced by patients across numerous rare musculoskeletal conditions. Much remains unknown regarding the central, neurobiological processes associated with clinical pain in musculoskeletal disease states. Fibrodysplasia ossificans progressiva (FOP) is an inherited condition characterized by substantial physical disability and pain. FOP arises from mutations of the bone morphogenetic protein (BMP) receptor Activin A receptor type 1 (ACVR1) causing patients to undergo painful flare-ups as well as heterotopic ossification (HO) of skeletal muscles, tendons, ligaments, and fascia. To date, the neurobiological processes that underlie pain in FOP have rarely been investigated. We examined pain and central pain mechanism in FOP as a model primary musculoskeletal condition. Central nervous system (CNS) functional properties were investigated in FOP patients (N = 17) stratified into low (0–3; 0–10 Scale) and high (≥ 4) pain cohorts using functional near-infrared spectroscopy (fNIRS). Associations among clinical pain, mental health, and physical health were also quantified using responses derived from a battery of clinical questionnaires. Results Resting-state fNIRS revealed suppressed power of hemodynamic activity within the slow-5 frequency sub-band (0.01–0.027 Hz) in the prefrontal cortex in high pain FOP patients, where reduced power of slow-5, prefrontal cortex oscillations exhibited robust negative correlations with pain levels. Higher clinical pain intensities were also associated with higher magnitudes of depressive symptoms. Conclusions Our findings not only demonstrate a robust coupling among prefrontal cortex functionality and clinical pain in FOP but lays the groundwork for utilizing fNIRS to objectively monitor and central pain mechanisms in FOP and other musculoskeletal disorders.
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Affiliation(s)
- Ke Peng
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.,Département en Neuroscience, Centre de Recherche du CHUM, l'Université de Montréal, Montreal, QC, Canada
| | - Keerthana Deepti Karunakaran
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Robert Labadie
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Miranda Veliu
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Chandler Cheung
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Arielle Lee
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Paul B Yu
- Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jaymin Upadhyay
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA. .,Department of Psychiatry, McLean Hospital, Harvard Medical School, Belmont, MA, USA.
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19
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Khan H, Naseer N, Yazidi A, Eide PK, Hassan HW, Mirtaheri P. Analysis of Human Gait Using Hybrid EEG-fNIRS-Based BCI System: A Review. Front Hum Neurosci 2021; 14:613254. [PMID: 33568979 PMCID: PMC7868344 DOI: 10.3389/fnhum.2020.613254] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 12/15/2020] [Indexed: 11/21/2022] Open
Abstract
Human gait is a complex activity that requires high coordination between the central nervous system, the limb, and the musculoskeletal system. More research is needed to understand the latter coordination's complexity in designing better and more effective rehabilitation strategies for gait disorders. Electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) are among the most used technologies for monitoring brain activities due to portability, non-invasiveness, and relatively low cost compared to others. Fusing EEG and fNIRS is a well-known and established methodology proven to enhance brain–computer interface (BCI) performance in terms of classification accuracy, number of control commands, and response time. Although there has been significant research exploring hybrid BCI (hBCI) involving both EEG and fNIRS for different types of tasks and human activities, human gait remains still underinvestigated. In this article, we aim to shed light on the recent development in the analysis of human gait using a hybrid EEG-fNIRS-based BCI system. The current review has followed guidelines of preferred reporting items for systematic reviews and meta-Analyses (PRISMA) during the data collection and selection phase. In this review, we put a particular focus on the commonly used signal processing and machine learning algorithms, as well as survey the potential applications of gait analysis. We distill some of the critical findings of this survey as follows. First, hardware specifications and experimental paradigms should be carefully considered because of their direct impact on the quality of gait assessment. Second, since both modalities, EEG and fNIRS, are sensitive to motion artifacts, instrumental, and physiological noises, there is a quest for more robust and sophisticated signal processing algorithms. Third, hybrid temporal and spatial features, obtained by virtue of fusing EEG and fNIRS and associated with cortical activation, can help better identify the correlation between brain activation and gait. In conclusion, hBCI (EEG + fNIRS) system is not yet much explored for the lower limb due to its complexity compared to the higher limb. Existing BCI systems for gait monitoring tend to only focus on one modality. We foresee a vast potential in adopting hBCI in gait analysis. Imminent technical breakthroughs are expected using hybrid EEG-fNIRS-based BCI for gait to control assistive devices and Monitor neuro-plasticity in neuro-rehabilitation. However, although those hybrid systems perform well in a controlled experimental environment when it comes to adopting them as a certified medical device in real-life clinical applications, there is still a long way to go.
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Affiliation(s)
- Haroon Khan
- Department of Mechanical, Electronics and Chemical Engineering, OsloMet-Oslo Metropolitan University, Oslo, Norway
| | - Noman Naseer
- Department of Mechatronics and Biomedical Engineering, Air University, Islamabad, Pakistan
| | - Anis Yazidi
- Department of Computer Science, OsloMet-Oslo Metropolitan University, Oslo, Norway.,Department of Plastic and Reconstructive Surgery, Oslo University Hospital, Oslo, Norway.,Department of Computer Science, Norwegian University of Science and Technology, Trondheim, Norway
| | | | - Hafiz Wajahat Hassan
- Department of Mechanical, Electronics and Chemical Engineering, OsloMet-Oslo Metropolitan University, Oslo, Norway
| | - Peyman Mirtaheri
- Department of Mechanical, Electronics and Chemical Engineering, OsloMet-Oslo Metropolitan University, Oslo, Norway.,Department of Biomedical Engineering, Michigan Technological University, Michigan, MI, United States
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20
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Berger A, Steinberg F, Thomas F, Doppelmayr M. Neural Correlates of Age-Related Changes in Precise Grip Force Regulation: A Combined EEG-fNIRS Study. Front Aging Neurosci 2020; 12:594810. [PMID: 33362531 PMCID: PMC7759198 DOI: 10.3389/fnagi.2020.594810] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 11/11/2020] [Indexed: 01/16/2023] Open
Abstract
Motor control is associated with suppression of oscillatory activity in alpha (8–12 Hz) and beta (12–30 Hz) ranges and elevation of oxygenated hemoglobin levels in motor-cortical areas. Aging leads to changes in oscillatory and hemodynamic brain activity and impairments in motor control. However, the relationship between age-related changes in motor control and brain activity is not yet fully understood. Therefore, this study aimed to investigate age-related and task-complexity-related changes in grip force control and the underlying oscillatory and hemodynamic activity. Sixteen younger [age (mean ± SD) = 25.4 ± 1.9, 20–30 years] and 16 older (age = 56.7 ± 4.7, 50–70 years) healthy men were asked to use a power grip to perform six trials each of easy and complex force tracking tasks (FTTs) with their right dominant hand in a randomized within-subject design. Grip force control was assessed using a sensor-based device. Brain activity in premotor and primary motor areas of both hemispheres was assessed by electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). Older adults showed significantly higher inaccuracies and higher hemodynamic activity in both FTTs than did young adults. Correlations between grip force control owing to task complexity and beta activity were different in the contralateral premotor cortex (PMC) between younger and older adults. Collectively, these findings suggest that aging leads to impairment of grip force control and an increase in hemodynamic activity independent of task complexity. EEG beta oscillations may represent a task-specific neurophysiological marker for age-related decline in complex grip force control and its underlying compensation strategies. Further EEG-fNIRS studies are necessary to determine neurophysiological markers of dysfunctions underlying age-related motor disabilities for the improvement of individual diagnosis and therapeutic approaches.
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Affiliation(s)
- Alisa Berger
- Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Fabian Steinberg
- Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, Germany.,School of Kinesiology, Louisiana State University, Baton Rouge, LA, United States
| | - Fabian Thomas
- Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Michael Doppelmayr
- Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University Mainz, Mainz, Germany.,Centre for Cognitive Neuroscience, Paris Lodron University of Salzburg, Salzburg, Austria
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21
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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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22
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Li R, Zhao C, Wang C, Wang J, Zhang Y. Enhancing fNIRS Analysis Using EEG Rhythmic Signatures: An EEG-Informed fNIRS Analysis Study. IEEE Trans Biomed Eng 2020; 67:2789-2797. [PMID: 32031925 DOI: 10.1109/tbme.2020.2971679] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Neurovascular coupling represents the relationship between changes in neuronal activity and cerebral hemodynamics. Concurrent Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) recording and integration analysis has emerged as a promising multi-modal neuroimaging approach to study the neurovascular coupling as it provides complementary properties with regard to high temporal and moderate spatial resolution of brain activity. In this study we developed an EEG-informed-fNIRS analysis framework to investigate the neuro-correlate between neuronal activity and cerebral hemodynamics by identifying specific EEG rhythmic modulations which contribute to the improvement of the fNIRS-based general linear model (GLM) analysis. Specifically, frequency-specific regressors derived from EEG were used to construct design matrices to guide the GLM analysis of the fNIRS signals collected during a hand grasp task. Our results showed that the EEG-informed fNIRS GLM analysis, especially the alpha and beta band, revealed significantly higher sensitivity and specificity in localizing the task-evoked regions compared to the canonical boxcar model, demonstrating the strong correlations between hemodynamic response and EEG rhythmic modulations. Results also indicated that analysis based on the deoxygenated hemoglobin (HbR) signal slightly outperformed the oxygenated hemoglobin (HbO)-based analysis. The findings in our study not only validate the feasibility of enhancing fNIRS GLM analysis using simultaneously recorded EEG signals, but also provide a new perspective to study the neurovascular coupling of brain activity.
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23
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Berger A, Horst F, Müller S, Steinberg F, Doppelmayr M. Current State and Future Prospects of EEG and fNIRS in Robot-Assisted Gait Rehabilitation: A Brief Review. Front Hum Neurosci 2019; 13:172. [PMID: 31231200 PMCID: PMC6561323 DOI: 10.3389/fnhum.2019.00172] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 05/13/2019] [Indexed: 01/22/2023] Open
Abstract
Gait and balance impairments are frequently considered as the most significant concerns among individuals suffering from neurological diseases. Robot-assisted gait training (RAGT) has shown to be a promising neurorehabilitation intervention to improve gait recovery in patients following stroke or brain injury by potentially initiating neuroplastic changes. However, the neurophysiological processes underlying gait recovery through RAGT remain poorly understood. As non-invasive, portable neuroimaging techniques, electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) provide new insights regarding the neurophysiological processes occurring during RAGT by measuring different perspectives of brain activity. Due to spatial information about changes in cortical activation patterns and the rapid temporal resolution of bioelectrical changes, more features correlated with brain activation and connectivity can be identified when using fused EEG-fNIRS, thus leading to a detailed understanding of neurophysiological mechanisms underlying motor behavior and impairments due to neurological diseases. Therefore, multi-modal integrations of EEG-fNIRS appear promising for the characterization of neurovascular coupling in brain network dynamics induced by RAGT. In this brief review, we surveyed neuroimaging studies focusing specifically on robotic gait rehabilitation. While previous studies have examined either EEG or fNIRS with respect to RAGT, a multi-modal integration of both approaches is lacking. Based on comparable studies using fused EEG-fNIRS integrations either for guiding non-invasive brain stimulation or as part of brain-machine interface paradigms, the potential of this methodologically combined approach in RAGT is discussed. Future research directions and perspectives for targeted, individualized gait recovery that optimize the outcome and efficiency of RAGT in neurorehabilitation were further derived.
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Affiliation(s)
- Alisa Berger
- Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University, Mainz, Germany
| | - Fabian Horst
- Department of Training and Movement Science, Institute of Sport Science, Johannes Gutenberg-University, Mainz, Germany
| | - Sophia Müller
- Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University, Mainz, Germany
| | - Fabian Steinberg
- Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University, Mainz, Germany
| | - Michael Doppelmayr
- Department of Sport Psychology, Institute of Sport Science, Johannes Gutenberg-University, Mainz, Germany.,Centre for Cognitive Neuroscience, University of Salzburg, Salzburg, Austria
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Lachert P, Zygierewicz J, Janusek D, Pulawski P, Sawosz P, Kacprzak M, Liebert A, Blinowska KJ. Causal Coupling Between Electrophysiological Signals, Cerebral Hemodynamics and Systemic Blood Supply Oscillations in Mayer Wave Frequency Range. Int J Neural Syst 2018; 29:1850033. [PMID: 30175672 DOI: 10.1142/s0129065718500338] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The aim of the study was to assess causal coupling between neuronal activity, microvascular hemodynamics and blood supply oscillations in the Mayer wave frequency range. An electroencephalogram, cerebral blood oxygenation changes, an electrocardiogram and blood pressure were recorded during rest and during a movement task. Causal coupling between them was evaluated using directed transfer function, a measure based on the Granger causality principle. The multivariate autoregressive model was fitted to all the signals simultaneously, which made it possible to construct a complete scheme of interactions between the considered signals. The obtained pattern of interactions in the resting state estimated in the 0.05-0.15 Hz band revealed a predominant influence of blood pressure oscillations on all the other variables. Reciprocal connections between blood pressure and heart rate variability time series indicated the presence of feedback loops between these signals. During movement, the pattern of connections did not change dramatically. The number of connections decreased, but the couplings between blood pressure and heart rate variability signal were not significantly changed, and the strong influence of the decreased blood hemoglobin concentration on the oxygenated hemoglobin concentration persisted. For the first time our results provided a comprehensive scheme of interactions between electrical and hemodynamic brain signals, heart rate and blood pressure oscillations. Persistent reciprocal connections between blood pressure and heart rate variability time series suggest possible feedforward and feedback coupling of cardiovascular variables which may lead to the observed oscillations in Mayer wave range.
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Affiliation(s)
- P Lachert
- * Department of Methods of Brain Imaging, and Functional Research of Nervous System, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland
| | - J Zygierewicz
- † Department of Biomedical Physics, Faculty of Physics, University of Warsaw, Pasteura 5, 02-093 Warsaw, Poland
| | - D Janusek
- * Department of Methods of Brain Imaging, and Functional Research of Nervous System, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland
| | - P Pulawski
- * Department of Methods of Brain Imaging, and Functional Research of Nervous System, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland
| | - P Sawosz
- * Department of Methods of Brain Imaging, and Functional Research of Nervous System, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland
| | - M Kacprzak
- * Department of Methods of Brain Imaging, and Functional Research of Nervous System, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland
| | - A Liebert
- * Department of Methods of Brain Imaging, and Functional Research of Nervous System, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland
| | - K J Blinowska
- * Department of Methods of Brain Imaging, and Functional Research of Nervous System, Nalecz Institute of Biocybernetics and Biomedical Engineering, Polish Academy of Sciences, Ks. Trojdena 4, 02-109 Warsaw, Poland.,† Department of Biomedical Physics, Faculty of Physics, University of Warsaw, Pasteura 5, 02-093 Warsaw, Poland
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