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Zhang J, Wang J, Wang Y, Zhang D, Li H, Lei Y. Sleep deprivation increases the generalization of perceptual and concept-based fear: An fNIRS study. J Anxiety Disord 2024; 105:102892. [PMID: 38889495 DOI: 10.1016/j.janxdis.2024.102892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 05/20/2024] [Accepted: 06/10/2024] [Indexed: 06/20/2024]
Abstract
Insufficient sleep can initiate or exacerbate anxiety by triggering excessive fear generalization. In this study, a de novo paradigm was developed and used to examine the neural mechanisms governing the effects of sleep deprivation on processing perceptual and concept-based fear generalizations. A between-subject design was adopted, wherein a control group (who had a typical night's sleep) and a one-night sleep deprivation group completed a fear acquisition task at 9:00 PM on the first day and underwent a generalization test the following morning at 7:00 AM. In the fear acquisition task, navy blue and olive green were used as perceptual cues (P+ and P-, respectively), while animals and furniture items were used as conceptual cues (C+ and C-, respectively). Generalization was tested for four novel generalized categories (C+P+, C+P-, C-P+, and C-P-). Shock expectancy ratings, skin conductance responses, and functional near-infrared spectroscopy were recorded during the fear acquisition and generalization processes. Compared with the group who had a typical night's sleep, the sleep deprived group showed higher shock expectancy ratings (especially for P+ and C-), increased oxygenated hemoglobin in the dorsolateral prefrontal cortex, and increased activation in the triangular inferior frontal gyrus during the generalization test. These findings suggest that sleep deprivation increases the generalization of threat memories, thus providing insights into the overgeneralization characteristics of anxiety and fear-related disorders.
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Affiliation(s)
- Jie Zhang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China; School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Jinxia Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China; Faculty of Education and Psychology, University of Jyvaskyla, Finland
| | - Yuanyuan Wang
- School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Dandan Zhang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China
| | - Hong Li
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China; School of Psychology, South China Normal University, Guangzhou 510631, China
| | - Yi Lei
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu 610066, China.
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Takahashi S, Takahashi D, Kuroiwa Y, Sakurai N, Kodama N. Construction and evaluation of a neurofeedback system using finger tapping and near-infrared spectroscopy. FRONTIERS IN NEUROIMAGING 2024; 3:1361513. [PMID: 38726042 PMCID: PMC11079114 DOI: 10.3389/fnimg.2024.1361513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Accepted: 04/09/2024] [Indexed: 05/12/2024]
Abstract
Introduction Neurofeedback using near-infrared spectroscopy (NIRS) has been used in patients with stroke and other patients, but few studies have included older people or patients with cognitive impairment. Methods We constructed a NIRS-based neurofeedback system and used finger tapping to investigate whether neurofeedback can be implemented in older adults while finger tapping and whether brain activity improves in older adults and healthy participants. Our simple neurofeedback system was constructed using a portable wearable optical topography (WOT-HS) device. Brain activity was evaluated in 10 older and 31 healthy young individuals by measuring oxygenated hemoglobin concentration during finger tapping and neurofeedback implementation. Results During neurofeedback, the concentration of oxygenated hemoglobin increased in the prefrontal regions in both the young and older participants. Discussion The results of this study demonstrate the usefulness of neurofeedback using simple NIRS devices for older adults and its potential to mitigate cognitive decline.
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Affiliation(s)
- Shingo Takahashi
- Department of Healthcare Informatics, Faculty of Health and Welfare, Takasaki University of Health and Welfare, Takasaki, Japan
| | - Daishi Takahashi
- Department of Healthcare Informatics, Faculty of Health and Welfare, Takasaki University of Health and Welfare, Takasaki, Japan
| | - Yuki Kuroiwa
- Department of Healthcare Informatics, Faculty of Health and Welfare, Takasaki University of Health and Welfare, Takasaki, Japan
| | - Noriko Sakurai
- Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Japan
| | - Naoki Kodama
- Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Japan
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Li H, Han Y, Niu H. Greater up-modulation of intra-individual brain signal variability makes a high-load cognitive task more arduous for older adults. Neuroimage 2024; 290:120577. [PMID: 38490585 DOI: 10.1016/j.neuroimage.2024.120577] [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: 12/01/2023] [Revised: 02/27/2024] [Accepted: 03/12/2024] [Indexed: 03/17/2024] Open
Abstract
The extent to which brain responses are less distinctive across varying cognitive loads in older adults is referred to as neural dedifferentiation. Moment-to-moment brain signal variability, an emerging indicator, reveals not only the adaptability of an individual's brain as an inter-individual trait, but also the allocation of neural resources within an individual due to ever-changing task demands, thus shedding novel insight into the process of neural dedifferentiation. However, how the modulation of intra-individual brain signal variability reflects behavioral differences related to cognitively demanding tasks remains unclear. In this study, we employed functional near-infrared spectroscopy (fNIRS) imaging to capture the variability of brain signals, which was quantified by the standard deviation, during both the resting state and an n-back task (n = 1, 2, 3) in 57 healthy older adults. Using multivariate Partial Least Squares (PLS) analysis, we found that fNIRS signal variability increased from the resting state to the task and increased with working memory load in older adults. We further confirmed that greater fNIRS signal variability generally supported faster and more stable response time in the 2- and 3-back conditions. However, the intra-individual level analysis showed that the greater the up-modulation in fNIRS signal variability with cognitive loads, the more its accuracy decreases and mean response time increases, suggesting that a greater intra-individual brain signal variability up-modulation may reflect decreased efficiency in neural information processing. Taken together, our findings offer new insights into the nature of brain signal variability, suggesting that inter- and intra-individual brain signal variability may index distinct theoretical constructs.
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Affiliation(s)
- Hong Li
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875 China
| | - Ying Han
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, 100053, China; School of Biomedical Engineering, Hainan University, Haikou, 570228, China; Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China; National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China; Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875 China.
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Friedman LM, Eckrich SJ, Rapport MD, Bohil CJ, Calub C. Working and short-term memory in children with ADHD: an examination of prefrontal cortical functioning using functional Near-Infrared Spectroscopy (fNIRS). Child Neuropsychol 2024; 30:462-485. [PMID: 37199502 DOI: 10.1080/09297049.2023.2213463] [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: 11/08/2022] [Accepted: 05/05/2023] [Indexed: 05/19/2023]
Abstract
Working memory impairments are an oft-reported deficit among children with ADHD, and complementary neuroimaging studies implicate reductions in prefrontal cortex (PFC) structure and function as a neurobiological explanation. Most imaging studies, however, rely on costly, movement-intolerant, and/or invasive methods to examine cortical differences. This is the first study to use a newer neuroimaging tool that overcomes these limitations, functional Near Infrared Spectroscopy (fNIRS), to investigate hypothesized prefrontal differences. Children (aged 8-12) with ADHD (N = 22) and typically developing (N = 18) children completed phonological working memory (PHWM) and short-term memory (PHSTM) tasks. Children with ADHD evinced poorer performance on both tasks, with greater differences observed in PHWM (Hedges' g = 0.67) relative to PHSTM (g = 0.39). fNIRS revealed reduced hemodynamic response among children with ADHD in the dorsolateral PFC while completing the PHWM task, but not within the anterior or posterior PFC. No between-group fNIRS differences were observed during the PHSTM task. Findings suggest that children with ADHD exhibit an inadequate hemodynamic response in a region of the brain that underlies PHWM abilities. The study also highlights the use of fNIRS as a cost-effective, noninvasive neuroimaging technique to localize/quantify neural activation patterns associated with executive functions.
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Affiliation(s)
| | - Samuel J Eckrich
- Department of Psychology, University of Central Florida, Orlando, FL, USA
- Department of Neuropsychology, Kennedy Krieger/Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Mark D Rapport
- Department of Psychology, University of Central Florida, Orlando, FL, USA
| | - Corey J Bohil
- Department of Psychology, University of Central Florida, Orlando, FL, USA
| | - Catrina Calub
- Department of Psychiatry, University of California, Sacramento, CA, USA
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Shin JH, Kang MJ, Lee SA. Wearable functional near-infrared spectroscopy for measuring dissociable activation dynamics of prefrontal cortex subregions during working memory. Hum Brain Mapp 2024; 45:e26619. [PMID: 38339822 PMCID: PMC10858338 DOI: 10.1002/hbm.26619] [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: 07/27/2023] [Revised: 01/18/2024] [Accepted: 01/22/2024] [Indexed: 02/12/2024] Open
Abstract
The prefrontal cortex (PFC) has been extensively studied in relation to various cognitive abilities, including executive function, attention, and memory. Nevertheless, there is a gap in our scientific knowledge regarding the functionally dissociable neural dynamics across the PFC during a cognitive task and their individual differences in performance. Here, we explored this possibility using a delayed match-to-sample (DMTS) working memory (WM) task using NIRSIT, a high-density, wireless, wearable functional near-infrared spectroscopy (fNIRS) system. First, upon presentation of the sample stimulus, we observed an immediate signal increase in the ventral (orbitofrontal) region of the anterior PFC, followed by activity in the dorsolateral PFC. After the DMTS test stimulus appeared, the orbitofrontal cortex activated once again, while the rest of the PFC showed overall disengagement. Individuals with higher accuracy showed earlier and sustained activation of the PFC across the trial. Furthermore, higher network efficiency and functional connectivity in the PFC were correlated with individual WM performance. Our study sheds new light on the dynamics of PFC subregional activity during a cognitive task and its potential applicability in explaining individual differences in experimental, educational, or clinical populations. PRACTITIONER POINTS: Wearable functional near-infrared spectroscopy (fNIRS) captured dissociable temporal dynamics across prefrontal subregions during a delayed match-to-sample task. Anterior regions of the orbitofrontal cortex (OFC) activated first during the delay period, followed by the dorsolateral prefrontal cortex (PFC). PFC disengaged overall after the delay, but the OFC reactivated to the test stimulus. Earlier and sustained activation of PFC was associated with better accuracy. Functional connectivity and network efficiency also varied with task performance.
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Affiliation(s)
- Jung Han Shin
- Program of Brain and Cognitive EngineeringKorea Advanced Institute of Science and Technology (KAIST)DaejeonSouth Korea
- Department of Brain and Cognitive SciencesSeoul National UniversitySeoulSouth Korea
| | - Min Jun Kang
- Department of Bio and Brain EngineeringKorea Advanced Institute of Science and Technology (KAIST)DaejeonSouth Korea
| | - Sang Ah Lee
- Department of Brain and Cognitive SciencesSeoul National UniversitySeoulSouth Korea
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Qi L, Wang GL, Tian ZH, Guan S, Yang SY, Yang YL, Liu LQ, Lin YZ. Prefrontal cortical hemodynamics and functional network organization during Tai Chi standing meditation: an fNIRS study. Front Hum Neurosci 2023; 17:1294312. [PMID: 37954940 PMCID: PMC10634523 DOI: 10.3389/fnhum.2023.1294312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 10/11/2023] [Indexed: 11/14/2023] Open
Abstract
Introduction Tai Chi standing meditation (Zhan Zhuang, also called pile standing) is characterized by meditation, deep breathing, and mental focus based on theories of traditional Chinese medicine. The purpose of the present study was to explore prefrontal cortical hemodynamics and the functional network organization associated with Tai Chi standing meditation by using functional near-infrared spectroscopy (fNIRS). Methods Twenty-four channel fNIRS signals were recorded from 24 male Tai Chi Quan practitioners (54.71 ± 8.04 years) while standing at rest and standing during Tai Chi meditation. The general linear model and the SPM method were used to analyze the fNIRS signals. Pearson correlation was calculated to determine the functional connectivity between the prefrontal cortical sub-regions. The small world properties of the FC networks were then further analyzed based on graph theory. Results During Tai Chi standing meditation, significantly higher concentrations of oxygenated hemoglobin were observed in bilateral dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), frontal eye field (FEF), and pre-motor cortex (PMC) compared with the values measured during standing rest (p < 0.05). Simultaneously, significant decreases in deoxygenated hemoglobin concentration were observed in left VLPFC, right PMC and DLPFC during Tai Chi standing meditation than during standing rest (p < 0.05). Functional connectivity between the left and right PFC was also significantly stronger during the Tai Chi standing meditation (p < 0.05). The functional brain networks exhibited small-world architecture, and more network hubs located in DLPFC and VLPFC were identified during Tai Chi standing meditation than during standing rest. Discussion These findings suggest that Tai Chi standing meditation introduces significant changes in the cortical blood flow and the brain functional network organization.
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Affiliation(s)
- Liping Qi
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Guo-Liang Wang
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Zhi-Hao Tian
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Shuo Guan
- Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian, China
| | - Shu-Ye Yang
- School of Physical Education and Health, Dalian University of Technology, Dalian, China
| | - Yu-Long Yang
- School of Physical Education and Health, Dalian University of Technology, Dalian, China
| | - Li-Qing Liu
- School of Physical Education and Health, Dalian University of Technology, Dalian, China
| | - Yong-Zhong Lin
- The Second Affiliated Hospital of Dalian Medical University, Dalian, China
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Han Y, Huang J, Yin Y, Chen H. From brain to worksite: the role of fNIRS in cognitive studies and worker safety. Front Public Health 2023; 11:1256895. [PMID: 37954053 PMCID: PMC10634210 DOI: 10.3389/fpubh.2023.1256895] [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: 07/11/2023] [Accepted: 10/11/2023] [Indexed: 11/14/2023] Open
Abstract
Effective hazard recognition and decision-making are crucial factors in ensuring workplace safety in the construction industry. Workers' cognition closely relates to that hazard-handling behavior. Functional near-infrared spectroscopy (fNIRS) is a neurotechique tool that can evaluate the concentration vibration of oxygenated hemoglobin [ H b O 2 ] and deoxygenated hemoglobin [H b R ] to reflect the cognition process. It is essential to monitor workers' brain activity by fNIRS to analyze their cognitive status and reveal the mechanism in hazard recognition and decision-making process, providing guidance for capability evaluation and management enhancement. This review offers a systematic assessment of fNIRS, encompassing the basic theory, experiment analysis, data analysis, and discussion. A literature search and content analysis are conducted to identify the application of fNIRS in construction safety research, the limitations of selected studies, and the prospects of fNIRS in future research. This article serves as a guide for researchers keen on harnessing fNIRS to bolster construction safety standards and forwards insightful recommendations for subsequent studies.
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Affiliation(s)
| | | | | | - Huihua Chen
- School of Civil Engineering, Central South University, Changsha, China
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Kong Y, Peng W, Li J, Zhu C, Zhang C, Fan Y. Alteration in brain functional connectivity in patients with post-stroke cognitive impairment during memory task: A fNIRS study. J Stroke Cerebrovasc Dis 2023; 32:107280. [PMID: 37517137 DOI: 10.1016/j.jstrokecerebrovasdis.2023.107280] [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: 03/25/2023] [Revised: 07/11/2023] [Accepted: 07/24/2023] [Indexed: 08/01/2023] Open
Abstract
OBJECTIVE This study attempted to evaluate the functional connectivity (FC) in relevant cortex areas during three memory tasks using the functional near-infrared spectroscopy (fNIRS) method to expound the neural mechanisms in individuals with post-stroke cognitive impairment (PSCI). METHODS Short-term memory and visuospatial abilities were assessed using the clock drawing test, digit span test, and Corsi Block-tapping tests with simultaneous fNIRS. The oxygenated hemoglobin concentration signals were recorded from the bilateral motor sense cortex (LMS/RMS) and prefrontal lobe (LPFT/PFT/RPFT) of 19 subjects with cognitive impairment (PSCI group), 27 stroke subjects (STR group) and 26 healthy subjects (HC group). RESULTS MMSE scores were positively correlated with the clock drawing test and digit span test scores but not with Corsi Block-tapping scores. During each test, functional connectivity between the bilateral MS (LMS/RMS) was highest within each group, but the functional connectivity between motor sense cortex and frontal lobe was lowest. PSCI group showed decreased FC between bilateral motor sense cortex (P < 0.05) and between motor sense cortex and frontal lobe (P > 0.05) during clock drawing test and Corsi Block-tapping test while decreased FC between each region of interest during digit span test with no significant difference. Functional connectivity levels were closely related to MMSE scores. CONCLUSIONS Decreased functional connectivity level may be a marker of impaired cognitive function in post-stroke cognitive impairment. The fNIRS-based functional connectivity provides a non-invasive method to recognize cognitive impairment post-stroke. Functional connectivity changes may help to further understand the neural mechanisms of cognitive impairment post stroke.
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Affiliation(s)
- Ying Kong
- Department of Rehabilitation, the Second Xiangya Hospital, Central South University, No. 139, Renmin Rd. Furong District, Changsha 410011, Hunan China
| | - Wenna Peng
- Department of Rehabilitation, the Second Xiangya Hospital, Central South University, No. 139, Renmin Rd. Furong District, Changsha 410011, Hunan China
| | - Jing Li
- Department of Rehabilitation, the Second Xiangya Hospital, Central South University, No. 139, Renmin Rd. Furong District, Changsha 410011, Hunan China
| | - Chunjiao Zhu
- Department of Rehabilitation, the Second Xiangya Hospital, Central South University, No. 139, Renmin Rd. Furong District, Changsha 410011, Hunan China
| | - Changjie Zhang
- Department of Rehabilitation, the Second Xiangya Hospital, Central South University, No. 139, Renmin Rd. Furong District, Changsha 410011, Hunan China
| | - Yongmei Fan
- Department of Rehabilitation, the Second Xiangya Hospital, Central South University, No. 139, Renmin Rd. Furong District, Changsha 410011, Hunan China.
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Shi S, Qie S, Wang H, Wang J, Liu T. Recombination of the right cerebral cortex in patients with left side USN after stroke: fNIRS evidence from resting state. Front Neurol 2023; 14:1178087. [PMID: 37545727 PMCID: PMC10400010 DOI: 10.3389/fneur.2023.1178087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 06/29/2023] [Indexed: 08/08/2023] Open
Abstract
Objective Unilateral spatial neglect (USN) is an impaired contralesional stimulus detection, response, or action, causing functional disability. After a stroke, the right hemisphere experiences USN more noticeably, severely, and persistently than the left. However, few studies using fNIRS have been reported in cases of USN. This study aimed to confirm weaker RSFC in USN and investigate the potential inherent features in hemodynamic fluctuations that may be associated with USN. Furthermore, these features were combined into a mathematical model for more accurate classification. Methods A total of 33 stroke patients with right-sided brain damage were chosen, of whom 12 had non-USN after stroke, and 21 had USN after stroke (the USN group). Graph theory was used to evaluate the hemodynamic signals of the brain's right cerebral cortex during rest. Furthermore, a support vector machine model was built to categorize the subjects into two groups based on the chosen network properties. Results First, mean functional connectivity was lower in the USN group (0.745 ± 0.239) than in the non-USN group (0.843 ± 0.254) (t = -4.300, p < 0.001). Second, compared with the non-USN group, USN patients had a larger clustering coefficient (C) (t = 3.145, p < 0.001), local efficiency (LE) (t = 3.189, p < 0.001), and smaller global efficiency (GE) (t = 3.047, p < 0.001). Notably, there were differences in characteristic path length (L) and small worldness (σ) values between the two groups at certain thresholds, mainly as higher L (t = 3.074, p < 0.001) and lower small worldness (σ) values (t = 2.998, p < 0.001) in USN patients compared with non-USN patients. Finally, the classification accuracy of the SVM model based on AUC aC (t = -2.259, p = 0.031) and AUC aLE (t = -2.063, p = 0.048) was 85%, the sensitivity was 75%, and the specificity was 89%. Conclusion The functional network architecture of the right cerebral cortex exhibits significant topological alterations in individuals with USN following stroke, and the sensitivity index based on the small-world property AUC may be utilized to identify these patients accurately.
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Affiliation(s)
- Shanshan Shi
- Rehabilitation Clinic, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Shuyan Qie
- Rehabilitation Clinic, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Hujun Wang
- Rehabilitation Clinic, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Jie Wang
- Rehabilitation Clinic, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
| | - Tiejun Liu
- Department of General Surgery, Beijing Rehabilitation Hospital, Capital Medical University, Beijing, China
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Liao W, Cao L, Leng L, Wang S, He X, Dong Y, Yang R, Bai G. Lack of functional brain connectivity was associated with poor inhibition in children with attention-deficit/hyperactivity disorder using near-infrared spectroscopy. Front Psychiatry 2023; 14:1221242. [PMID: 37502819 PMCID: PMC10368997 DOI: 10.3389/fpsyt.2023.1221242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 06/26/2023] [Indexed: 07/29/2023] Open
Abstract
Objectives The present study aimed to evaluate the characteristics of functional brain connectivity in the resting state in children with attention deficit hyperactivity disorder (ADHD) and to assess the association between the connectivity and inhibition function using near-infrared spectroscopy (NIRS). Methods In total, 34 children aged 6-13 diagnosed with ADHD were recruited from Hangzhou Seventh People's Hospital. In comparison, 37 healthy children were recruited from a local primary school as controls matched by age and sex. We used NIRS to collect information on brain images. The Stroop test assessed inhibition function. We compared the differences in functional brain connectivity in two groups by analyzing the resting-state brain network. Pearson partial correlation analysis was applied to evaluate the correlation between functional brain connectivity and inhibition in all the children. Results Compared with the control group, results of NIRS images analysis showed that children with ADHD had significantly low functional brain connectivity in regions of the orbitofrontal cortex, left dorsolateral prefrontal cortex, left pre-motor and supplementary motor cortex, inferior prefrontal gyrus, and right middle temporal gyrus (p = 0.006). Inhibition function of children with ADHD was negatively correlated with functional brain connectivity (p = 0.009), while such correlation was not found in the control group. Conclusion The present study demonstrated that children with ADHD had relatively low connectivity in several brain regions measured at the resting state. Our results supported the evidence that lack of functional brain connectivity was associated with impaired inhibition function in children with ADHD.
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Affiliation(s)
- Wenjing Liao
- Department of Psychology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Longfei Cao
- Centre for Cognition and Brain Disorders, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Lingli Leng
- Department of Sociology, Zhejiang University, Hangzhou, China
| | - Shaohua Wang
- Affiliated Mental Health Center, Zhejiang University School of Medicine (Hangzhou Seventh People’s Hospital), Hangzhou, China
| | - Xinyu He
- Department of Child Health Care, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Yusang Dong
- Department of Child Health Care, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Rongwang Yang
- Department of Psychology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
| | - Guannan Bai
- Department of Child Health Care, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health, Hangzhou, China
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Zhang F, Liu W, Zheng Y, Liu C, Hu Y, Chen H, Tang X, Wei Y, Zhang T, Wang J, Guo Q, Li G, Liu X. Decreased hemodynamic response to fearful faces relative to neutral faces in the medial frontal cortex of first-episode drug-naïve major depressive disorder. J Affect Disord 2023; 326:57-65. [PMID: 36682699 DOI: 10.1016/j.jad.2023.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 12/19/2022] [Accepted: 01/03/2023] [Indexed: 01/22/2023]
Abstract
BACKGROUND Major depressive disorder (MDD) is a disabling disease with impaired recognition of emotional facial expressions. However, the evidence is heterogeneous, regarding the mechanism of emotional processing in MDD. Focusing on patients with first-episode drug-naïve MDD, we used functional near-infrared spectroscopy (fNIRS) to investigate whether MDD have characteristic patterns in cerebral activation under facial emotion recognition task (FERT). METHODS Thirty-five patients with first-episode drug-naïve MDD and 39 healthy controls (HCs) underwent fNIRS measure to evaluate cerebral hemodynamic response in the frontal and temporal cortex during FERT. The 17-item Hamilton Depression Rating Scale, Hamilton Anxiety Rating Scale and Inventory of Depressive Symptomatology-Self Report were applied to assess the symptoms of the patients. Cognitive functions were assessed using THINC-integrated tool. RESULTS Hypoactivation in the medial frontal was observed in patients with MDD during recognition of fearful faces relative to neutral faces (F-N faces). Specifically, we found more right lateralized activation in the medial frontal cortex among patients with MDD compared to HCs. Further, the medial frontal activation under the condition of F-N faces was positively correlated to scores of digit symbol substitution test, and negatively relative to severity of depressive symptoms in MDD group. LIMITATIONS Our study is cross-sectional designed, and has a relatively small sample size. CONCLUSIONS We found abnormal patterns in the medial frontal activation of patients with first-episode drug-naïve MDD in recognition of F-N faces, which correlates with performance in cognitive function and depressive symptoms.
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Affiliation(s)
- Fuxu Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Wanying Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yanqun Zheng
- Huashan Hospital, Affiliated with Fudan University, Shanghai 200030, China
| | - Caiping Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yao Hu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Haiying Chen
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Xiaochen Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yanyan Wei
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Tianhong Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Jijun Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Qian Guo
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
| | - Guanjun Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
| | - Xiaohua Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China.
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Neuroplasticity Following Stroke from a Functional Laterality Perspective: A fNIRS Study. Brain Topogr 2023; 36:283-293. [PMID: 36856917 DOI: 10.1007/s10548-023-00946-z] [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: 12/09/2022] [Accepted: 02/14/2023] [Indexed: 03/02/2023]
Abstract
To explore alterations of resting-state functional connectivity (rsFC) in sensorimotor cortex following strokes with left or right hemiplegia considering the lateralization and neuroplasticity. Seventy-three resting-state functional near-infrared spectroscopy (fNIRS) files were selected, including 26 from left hemiplegia (LH), 21 from right hemiplegia (RH) and 26 from normal controls (NC) group. Whole-brain analyses matching the Pearson correlation were used for rsFC calculations. For right-handed normal controls, rsFC of motor components (M1 and M2) in the left hemisphere displayed a prominent intensity in comparison with the right hemisphere (p < 0.05), while for stroke groups, this asymmetry has disappeared. Additionally, RH rather than LH showed stronger rsFC between left S1 and left M1 in contrast to normal controls (p < 0.05), which correlated inversely with motor function (r = - 0.53, p < 0.05). Regarding M1, rsFC within ipsi-lesioned M1 has a negative correlation with motor function of the affected limb (r = - 0.60 for the RH group and - 0.43 for the LH group, p < 0.05). The rsFC within contra-lesioned M1 that innervates the normal side was weakened compared with that of normal controls (p < 0.05). Stronger rsFC of motor components in left hemisphere was confirmed by rs-fNIRS as the "secret of dominance" for the first time, while post-stroke hemiplegia broke this cortical asymmetry. Meanwhile, a statistically strengthened rsFC between left S1 and M1 only in right-hemiplegia group may act as a compensation for the impairment of the dominant side. This research has implications for brain-computer interfaces synchronizing sensory feedback with motor performance and transcranial magnetic regulation for cortical excitability to induce cortical plasticity.
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13
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Gong H, Sun H, Ma Y, Tan Y, Cui M, Luo M, Chen Y. Prefrontal brain function in patients with chronic insomnia disorder: A pilot functional near-infrared spectroscopy study. Front Neurol 2022; 13:985988. [PMID: 36588900 PMCID: PMC9798108 DOI: 10.3389/fneur.2022.985988] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 11/24/2022] [Indexed: 12/23/2022] Open
Abstract
Purpose Insomnia is one of the most common diseases in elderly patients, which seriously affect the quality of life and psychological state of patients. The purpose of this study was to investigate the changes in the functional network pattern of the prefrontal cortex in patients with chronic insomnia disorder (CID) after taking drugs, using non-invasive and low-cost functional neuroimaging with multi-channel near-infrared spectroscopy (fNIRS). Methods All subjects were assessed using the Pittsburgh Sleep Quality Index (PSQI), Hamilton Depression Scale (HAMD), Hamilton Anxiety Scale (HAMA), and fNIRS. The fNIRS assessment consists of two parts: the verbal fluency test (VFT) task state and the resting state, which assessed the differences in prefrontal activation and functional connectivity, respectively. Results A total of 30 patients with chronic insomnia disorder (CID) and 15 healthy peers completed the study. During the VFT task, a significantly lower PFC activation was observed in patients with insomnia compared to the control group (P < 0.05). However, the PFC activation in patients taking medication was higher than in patients who did not receive medication. Functional connectivity analysis showed a weaker mean PFC channel connectivity strength in patients with CID who did not receive drug treatment. Drug treatment resulted in enhanced functional connectivity of the prefrontal lobe, especially the DLPFC and frontal poles. Conclusion A weak prefrontal cortex response was detected in patients with CID when performing the VFT task, which could be enhanced by taking hypnotics. The weakened right prefrontal lobe network may play a role in the development of CID. fNIRS may serve as a potential tool to assess sleep status and guide drug therapy.
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Affiliation(s)
- Haiyan Gong
- Department of Internal Neurology, Tongji Hospital, Tongji University, Shanghai, China
| | - Hui Sun
- Department of Internal Neurology, Tongji Hospital, Tongji University, Shanghai, China
| | - Yeyang Ma
- Department of Internal Neurology, Tongji Hospital, Tongji University, Shanghai, China
| | - Yaling Tan
- Department of Internal Neurology, Tongji Hospital, Tongji University, Shanghai, China
| | - Minglong Cui
- Department of Internal Neurology, Tongji Hospital, Tongji University, Shanghai, China
| | - Ming Luo
- Department of Geriatrics, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yuhui Chen
- Department of Internal Neurology, Tongji Hospital, Tongji University, Shanghai, China,*Correspondence: Yuhui Chen ✉
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14
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Frequency-specific electrogastrography as a non-invasive tool to measure gastrointestinal maturity in preterm infants. Sci Rep 2022; 12:20728. [PMID: 36456633 PMCID: PMC9715709 DOI: 10.1038/s41598-022-24110-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 11/10/2022] [Indexed: 12/05/2022] Open
Abstract
Enteral feeding is challenging in preterm infants because of gastrointestinal (GI) immaturity. Electrogastrography (EGG) is a non-invasive technology that measures gastric myoelectrical activity and can be utilized to measure changes that occur with maturation at different gestational ages (GA). Three gastric rhythms (GR) exist between 0.5-9 cycles per minute (cpm), namely, bradygastria (0.5 ≤ GR < 2 cpm), normogastria (2 ≤ GR < 4 cpm), and tachygastria (4 ≤ GR < 9 cpm). We aimed to characterize EGG-derived parameters for different GA by quantifying (1) power spectral density (PSD) and its spectral means at three GR bands (i.e., mPSDGR) and (2) the percent (%) time spent in each band. Data analyzed was from a longitudinal cohort of preterm infants (n = 51) born at early, mid, and term GA of < 29, 29-33, and ≥ 37 weeks, respectively. Weekly EGG monitoring was performed until 40 weeks' postmenstrual age or discharge. Pre-, during, and post-feed data were analyzed for mPSDGR at each GR band. Also, % bradygastria, % normogastria, and % tachygastria were calculated by continuous wavelet transform analysis. Results showed (1) mPSD values in normogastria and tachygastria during feeding increased with advancing GA, and (2) % normogastria increased with advancing GA regardless of GR ranges, suggesting EGG may measure GI maturity in preterm infants.
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15
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Zhang F, Moerman F, Niu H, Warreyn P, Roeyers H. Atypical brain network development of infants at elevated likelihood for autism spectrum disorder during the first year of life. Autism Res 2022; 15:2223-2237. [PMID: 36193817 DOI: 10.1002/aur.2827] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/20/2022] [Indexed: 12/15/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by behavioral features that appear early in life. Although studies have shown that atypical brain functional and structural connectivity are associated with these behavioral traits, the occurrence and initial alterations of brain networks have not been fully investigated. The current study aimed to map early brain network efficiency and information transferring in infants at elevated likelihood (EL) compared to infants at typical likelihood (TL) for ASD in the first year of life. This study used a resting-state functional near-infrared spectroscopy (fNIRS) approach to obtain the length and strength of functional connections in the frontal and temporal areas in 45 5-month-old and 38 10-month-old infants. Modular organization and small-world properties were detected in both EL and TL infants at 5 and 10 months. In 5-month-old EL infants, local and nodal efficiency were significantly greater than age-matched TL infants, indicating overgrown local connections. Furthermore, we used a support vector machine (SVM) model to classify infants with or without EL based on the obtained global properties of the network, achieving an accuracy of 77.6%. These results suggest that infants with EL for ASD exhibit inefficiencies in the organization of brain networks during the first year of life.
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Affiliation(s)
- Fen Zhang
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
- ICFO-Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Floor Moerman
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Haijing Niu
- State Key Lab. of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Petra Warreyn
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
| | - Herbert Roeyers
- Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium
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16
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Wang Y, Wu M, Wu K, Liu H, Wu S, Zhang Z, Liu M, Wei C, Zhang YX, Liu Y. Differential auditory cortical development in left and right cochlear implanted children. Cereb Cortex 2022; 32:5438-5454. [PMID: 35165693 DOI: 10.1093/cercor/bhac025] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Revised: 01/12/2022] [Accepted: 01/14/2022] [Indexed: 12/27/2022] Open
Abstract
Unilateral aural stimulation has been shown to cause massive cortical reorganization in brain with congenital deafness, particularly during the sensitive period of brain development. However, it is unclear which side of stimulation provides most advantages for auditory development. The left hemisphere dominance of speech and linguistic processing in normal hearing adult brain has led to the assumption of functional and developmental advantages of right over left implantation, but existing evidence is controversial. To test this assumption and provide evidence for clinical choice, we examined 34 prelingually deaf children with unilateral cochlear implants using near-infrared spectroscopy. While controlling for age of implantation, residual hearing, and dominant hand, cortical processing of speech showed neither developmental progress nor influence of implantation side weeks to months after implant activation. In sharp contrast, for nonspeech (music signal vs. noise) processing, left implantation showed functional advantages over right implantation that were not yet discernable using clinical, questionnaire-based outcome measures. These findings support the notion that the right hemisphere develops earlier and is better preserved from adverse environmental influences than its left counterpart. This study thus provides, to our knowledge, the first evidence for differential influences of left and right auditory peripheral stimulation on early cortical development of the human brain.
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Affiliation(s)
- Yuyang Wang
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China.,Department of Otolaryngology Head and Neck Surgery, Hunan Provincial People's Hospital (First Affiliated Hospital of Hunan Normal University), Changsha 610041, China
| | - Meiyun Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Kun Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Haotian Liu
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China.,Department of Otolaryngology Head and Neck Surgery, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Shinan Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Zhikai Zhang
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China.,Department of Otolaryngology Head and Neck Surgery, Beijing Chao-Yang Hospital, Capital Medical University, Beijing 100043, China
| | - Min Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Chaogang Wei
- Department of Otolaryngology Head and Neck Surgery, Peking University First Hospital, Beijing 100034, China
| | - Yu-Xuan Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Yuhe Liu
- Department of Otolaryngology Head and Neck Surgery, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
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17
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Liu Y, Kang XG, Chen BB, Song CG, Liu Y, Hao JM, Yuan F, Jiang W. Detecting residual brain networks in disorders of consciousness: a resting-state fNIRS study. Brain Res 2022; 1798:148162. [DOI: 10.1016/j.brainres.2022.148162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 10/22/2022] [Accepted: 11/08/2022] [Indexed: 11/12/2022]
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18
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Zhang S, Zhu T, Tian Y, Jiang W, Li D, Wang D. Early screening model for mild cognitive impairment based on resting-state functional connectivity: a functional near-infrared spectroscopy study. NEUROPHOTONICS 2022; 9:045010. [PMID: 36483024 PMCID: PMC9722394 DOI: 10.1117/1.nph.9.4.045010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 11/15/2022] [Indexed: 05/19/2023]
Abstract
SIGNIFICANCE As an early stage of Alzheimer's disease (AD), the diagnosis of amnestic mild cognitive impairment (aMCI) has important clinical value for timely intervention of AD. Functional near-infrared spectroscopy (fNIRS)-based resting-state brain connectivity analysis, which could provide an economic and quick screening strategy for aMCI, remains to be extensively investigated. AIM This study aimed to verify the feasibility of fNIRS-based resting-state brain connectivity for evaluating brain function in patients with aMCI, and to determine an early screening model for auxiliary diagnosis. APPROACH The resting-state fNIRS was utilized for exploring the changes in functional connectivity of 64 patients with aMCI. The region of interest (ROI)-based and channel-based connections with significant inter-group differences have been extracted through the two-sample t -tests and the receiver operating characteristic (ROC). These connections with specificity and sensitivity were then taken as features for classification. RESULTS Compared with healthy controls, connections of the MCI group were significantly reduced between the bilateral prefrontal, parietal, occipital, and right temporal lobes. Specifically, the long-range connections from prefrontal to occipital lobe, and from prefrontal to parietal lobe, exhibited stronger identifiability (area under the ROC curve > 0.65 , ** p < 0.01 ). Subsequently, the optimal classification accuracy of ROI-based connections was 71.59%. Furthermore, the most responsive connections were located between the right dorsolateral prefrontal lobe and the left occipital lobe, concomitant with the highest classification accuracy of 73.86%. CONCLUSION Our findings indicate that fNIRS-based resting-state functional connectivity analysis could support MCI diagnosis. Notably, long-range connections involving the prefrontal and occipital lobes have the potential to be efficient biomarkers.
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Affiliation(s)
- Shen Zhang
- Beihang University, School of Biological Science and Medical Engineering, Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing, China
| | - Ting Zhu
- Beihang University, School of Biological Science and Medical Engineering, Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing, China
| | - Yizhu Tian
- Beihang University, School of Biological Science and Medical Engineering, Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing, China
| | - Wenyu Jiang
- Guangxi Jiangbin Hospital, Department of Neurological Rehabilitation, Nanning, China
- Address all correspondence to Daifa Wang, ; Deyu Li, ; Wenyu Jiang,
| | - Deyu Li
- Beihang University, School of Biological Science and Medical Engineering, Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing, China
- Beihang University, State Key Laboratory of Software Development Environment, Beijing, China
- Beihang University, State Key Laboratory of Virtual Reality Technology and System, Beijing, China
- Address all correspondence to Daifa Wang, ; Deyu Li, ; Wenyu Jiang,
| | - Daifa Wang
- Beihang University, School of Biological Science and Medical Engineering, Beijing Advanced Innovation Centre for Biomedical Engineering, Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing, China
- Address all correspondence to Daifa Wang, ; Deyu Li, ; Wenyu Jiang,
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19
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Canario E, Chen D, Han Y, Niu H, Biswal B. Global Network Analysis of Alzheimer’s Disease with Minimum Spanning Trees. J Alzheimers Dis 2022; 89:571-581. [DOI: 10.3233/jad-215573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: A minimum spanning tree (MST) is a unique efficient network comprising the necessary connections needed to connect all regions in a network while retaining the lowest possible cost of connection weight. Objective: This study aimed to utilize functional near-infrared spectroscopy (fNIRS) to analyze brain activity in different regions and then construct MST-based regions to characterize the brain topologies of participants with Alzheimer’s disease (AD), mild cognitive impairment (MCI), and normal controls (NC). Methods: A 46 channel fNIRS setup was used on all participants, with correlation being calculated for each channel pair. An MST was constructed from the resulting correlation matrix, from which graph theory measures were calculated. The average number of connections within a lobe in the left versus right hemisphere was calculated to identify which lobes displayed and abnormal amount of connectivity. Results: Compared to those in the MCI group, the AD group showed a less integrated network structure, with a higher characteristic path length, but lower leaf fraction, maximum degree, and degree divergence. The AD group also showed a higher number of connections in the frontal lobe within the left hemisphere and a lower number between hemispheric frontal lobes as compared to MCI. Conclusion: These results indicate a deviation in network structure and connectivity within patient groups that is consistent with the theory of dysconnectivity for AD. Additionally, the AD group showed strong correlations between the Hamilton depression rating scale and different graph metrics, suggesting a link between network organization and the recurrence of depression in AD.
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Affiliation(s)
- Edgar Canario
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Donna Chen
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Ying Han
- Hainan University, Haikou, China
| | | | - Bharat Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
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20
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Ayaz H, Baker WB, Blaney G, Boas DA, Bortfeld H, Brady K, Brake J, Brigadoi S, Buckley EM, Carp SA, Cooper RJ, Cowdrick KR, Culver JP, Dan I, Dehghani H, Devor A, Durduran T, Eggebrecht AT, Emberson LL, Fang Q, Fantini S, Franceschini MA, Fischer JB, Gervain J, Hirsch J, Hong KS, Horstmeyer R, Kainerstorfer JM, Ko TS, Licht DJ, Liebert A, Luke R, Lynch JM, Mesquida J, Mesquita RC, Naseer N, Novi SL, Orihuela-Espina F, O’Sullivan TD, Peterka DS, Pifferi A, Pollonini L, Sassaroli A, Sato JR, Scholkmann F, Spinelli L, Srinivasan VJ, St. Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report. NEUROPHOTONICS 2022; 9:S24001. [PMID: 36052058 PMCID: PMC9424749 DOI: 10.1117/1.nph.9.s2.s24001] [Citation(s) in RCA: 42] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- 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 Psychological and Brain Sciences, Philadelphia, Pennsylvania, United States
| | - Wesley B. Baker
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Giles Blaney
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - David A. Boas
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Heather Bortfeld
- University of California, Merced, Departments of Psychological Sciences and Cognitive and Information Sciences, Merced, California, United States
| | - Kenneth Brady
- Lurie Children’s Hospital, Northwestern University Feinberg School of Medicine, Department of Anesthesiology, Chicago, Illinois, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - Sabrina Brigadoi
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
| | - Erin M. Buckley
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Robert J. Cooper
- University College London, Department of Medical Physics and Bioengineering, DOT-HUB, London, United Kingdom
| | - Kyle R. Cowdrick
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Ippeita Dan
- Chuo University, Faculty of Science and Engineering, Tokyo, Japan
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Anna Devor
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Turgut Durduran
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
- Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Spain
| | - Adam T. Eggebrecht
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Lauren L. Emberson
- University of British Columbia, Department of Psychology, Vancouver, British Columbia, Canada
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Sergio Fantini
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Maria Angela Franceschini
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Jonas B. Fischer
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
| | - Judit Gervain
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Joy Hirsch
- Yale School of Medicine, Department of Psychiatry, Neuroscience, and Comparative Medicine, New Haven, Connecticut, United States
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Keum-Shik Hong
- Pusan National University, School of Mechanical Engineering, Busan, Republic of Korea
- Qingdao University, School of Automation, Institute for Future, Qingdao, China
| | - Roarke Horstmeyer
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
- Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
- Duke University, Department of Physics, Durham, North Carolina, United States
| | - Jana M. Kainerstorfer
- Carnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States
- Carnegie Mellon University, Neuroscience Institute, Pittsburgh, Pennsylvania, United States
| | - Tiffany S. Ko
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Daniel J. Licht
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
| | - Adam Liebert
- Polish Academy of Sciences, Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Robert Luke
- Macquarie University, Department of Linguistics, Sydney, New South Wales, Australia
- Macquarie University Hearing, Australia Hearing Hub, Sydney, New South Wales, Australia
| | - Jennifer M. Lynch
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Jaume Mesquida
- Parc Taulí Hospital Universitari, Critical Care Department, Sabadell, Spain
| | - Rickson C. Mesquita
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Noman Naseer
- Air University, Department of Mechatronics and Biomedical Engineering, Islamabad, Pakistan
| | - Sergio L. Novi
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Western University, Department of Physiology and Pharmacology, London, Ontario, Canada
| | | | - Thomas D. O’Sullivan
- University of Notre Dame, Department of Electrical Engineering, Notre Dame, Indiana, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behaviour Institute, New York, United States
| | | | - Luca Pollonini
- University of Houston, Department of Engineering Technology, Houston, Texas, United States
| | - Angelo Sassaroli
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - João Ricardo Sato
- Federal University of ABC, Center of Mathematics, Computing and Cognition, São Bernardo do Campo, São Paulo, Brazil
| | - Felix Scholkmann
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Lorenzo Spinelli
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Vivek J. Srinivasan
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- NYU Langone Health, Department of Ophthalmology, New York, New York, United States
- NYU Langone Health, Department of Radiology, New York, New York, United States
| | - Keith St. Lawrence
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Yunjie Tong
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Milan, Italy
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Tara Urner
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Heidrun Wabnitz
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Martin Wolf
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Ursula Wolf
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Shiqi Xu
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Changhuei Yang
- California Institute of Technology, Department of Electrical Engineering, Pasadena, California, United States
| | - Arjun G. Yodh
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
| | - Meryem A. Yücel
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Wenjun Zhou
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- China Jiliang University, College of Optical and Electronic Technology, Hangzhou, Zhejiang, China
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21
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Huang B, Wang X, Wei F, Sun Q, Sun J, Liang Y, Chen H, Zhuang H, Xiong G. Notched Sound Alleviates Tinnitus by Reorganization Emotional Center. Front Hum Neurosci 2022; 15:762492. [PMID: 35153700 PMCID: PMC8832119 DOI: 10.3389/fnhum.2021.762492] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2021] [Accepted: 12/22/2021] [Indexed: 11/13/2022] Open
Abstract
BackgroundTinnitus is a common disease, and sound therapy is an effective method to alleviate it. Previous studies have shown that notched sound not only changes levels of cortical blood oxygen, but affects blood oxygen in specific cerebral cortical areas, such as Brodmann area 46 (BA46), which is associated with emotion. Extensive evidence has confirmed that tinnitus is closely related to emotion. Whether notched sound plays a role in regulating the emotional center is still unclear.MethodsThis study included 29 patients with newly diagnosed chronic tinnitus who were treated with notched sound. Functional near-infrared spectroscopy (fNIRS) was conducted before and after treatment to observe bilateral changes in cortical blood oxygen in the cerebral hemispheres. We compared the changes in connectivity between the two regions of interest (the superior temporal gyrus and BA46), as wells as other cortical regions before and after treatment.ResultsThe results showed (1) That global connectivity between the bilateral auditory cortex of the superior temporal sulcus and the ipsilateral cortex did not change significantly between baseline and the completion of treatment, and (2) That the connectivity between channel 14 and the right superior temporal sulcus decreased after treatment. The overall connectivity between the right BA46 region and the right cortex decreased after treatment, and decreases in connectivity after treatment were specifically found for channels 10 and 14 in the right parietal lobe and channels 16, 20, 21, and 22 in the frontal lobe, while there was no significant change on the left side. There were no significant changes in the questionnaire measures of tinnitus, anxiety, or depression before and after treatment.ConclusionThe results of the study indicate that cerebral cortex reorganization occurs in tinnitus patients after submitted to treatment with notched sound for 1 month, and that notched sound decreases the connectivity between the auditory cortex and specific brain regions.SignificanceNotched sound not only regulates the auditory center through lateral inhibition, but also alleviates tinnitus by reorganizing the emotional control center.
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Affiliation(s)
- Bixue Huang
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Xianren Wang
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
- *Correspondence: Xianren Wang,
| | - Fanqing Wei
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Qiyang Sun
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Jincangjian Sun
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Yue Liang
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Huiting Chen
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Huiwen Zhuang
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Guanxia Xiong
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
- Guanxia Xiong,
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22
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LIONirs: flexible Matlab toolbox for fNIRS data analysis. J Neurosci Methods 2022; 370:109487. [DOI: 10.1016/j.jneumeth.2022.109487] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 01/19/2022] [Accepted: 01/21/2022] [Indexed: 11/21/2022]
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Yaqub MA, Hong KS, Zafar A, Kim CS. Control of Transcranial Direct Current Stimulation Duration by Assessing Functional Connectivity of Near-Infrared Spectroscopy Signals. Int J Neural Syst 2021; 32:2150050. [PMID: 34609264 DOI: 10.1142/s0129065721500507] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Transcranial direct current stimulation (tDCS) has been shown to create neuroplasticity in healthy and diseased populations. The control of stimulation duration by providing real-time brain state feedback using neuroimaging is a topic of great interest. This study presents the feasibility of a closed-loop modulation for the targeted functional network in the prefrontal cortex. We hypothesize that we cannot improve the brain state further after reaching a specific state during a stimulation therapy session. A high-definition tDCS of 1[Formula: see text]mA arranged in a ring configuration was applied at the targeted right prefrontal cortex of 15 healthy male subjects for 10[Formula: see text]min. Functional near-infrared spectroscopy was used to monitor hemoglobin chromophores during the stimulation period continuously. The correlation matrices obtained from filtered oxyhemoglobin were binarized to form subnetworks of short- and long-range connections. The connectivity in all subnetworks was analyzed individually using a new quantification measure of connectivity percentage based on the correlation matrix. The short-range network in the stimulated hemisphere showed increased connectivity in the initial stimulation phase. However, the increase in connection density reduced significantly after 6[Formula: see text]min of stimulation. The short-range network of the left hemisphere and the long-range network gradually increased throughout the stimulation period. The connectivity percentage measure showed a similar response with network theory parameters. The connectivity percentage and network theory metrics represent the brain state during the stimulation therapy. The results from the network theory metrics, including degree centrality, efficiency, and connection density, support our hypothesis and provide a guideline for feedback on the brain state. The proposed neuro-feedback scheme is feasible to control the stimulation duration to avoid overdosage.
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Affiliation(s)
- M Atif Yaqub
- ICFO-Institut de Ciències Fotòniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels (Barcelona), Spain
| | - Keum-Shik Hong
- School of Mechanical Engineering, Pusan National University, 2 Busandaehak-ro, Geumjeong-gu, Busan 46241, Korea
| | - Amad Zafar
- Department of Electrical Engineering, University of Lahore, Sihala Zone V, Islamabad, Pakistan
| | - Chang-Seok Kim
- Department of Cogno-Mechatronics Engineering, Pusan National University, 2 Busandaehak-ro, Geumjeong-gu, Busan 46241, Korea
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24
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Kelsey CM, Farris K, Grossmann T. Variability in Infants' Functional Brain Network Connectivity Is Associated With Differences in Affect and Behavior. Front Psychiatry 2021; 12:685754. [PMID: 34177669 PMCID: PMC8220897 DOI: 10.3389/fpsyt.2021.685754] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 05/14/2021] [Indexed: 11/13/2022] Open
Abstract
Variability in functional brain network connectivity has been linked to individual differences in cognitive, affective, and behavioral traits in adults. However, little is known about the developmental origins of such brain-behavior correlations. The current study examined functional brain network connectivity and its link to behavioral temperament in typically developing newborn and 1-month-old infants (M [age] = 25 days; N = 75) using functional near-infrared spectroscopy (fNIRS). Specifically, we measured long-range connectivity between cortical regions approximating fronto-parietal, default mode, and homologous-interhemispheric networks. Our results show that connectivity in these functional brain networks varies across infants and maps onto individual differences in behavioral temperament. Specifically, connectivity in the fronto-parietal network was positively associated with regulation and orienting behaviors, whereas connectivity in the default mode network showed the opposite effect on these behaviors. Our analysis also revealed a significant positive association between the homologous-interhemispheric network and infants' negative affect. The current results suggest that variability in long-range intra-hemispheric and cross-hemispheric functional connectivity between frontal, parietal, and temporal cortex is associated with individual differences in affect and behavior. These findings shed new light on the brain origins of individual differences in early-emerging behavioral traits and thus represent a viable novel approach for investigating developmental trajectories in typical and atypical neurodevelopment.
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Affiliation(s)
- Caroline M. Kelsey
- Division of Developmental Medicine, Department of Pediatrics, Boston Children's Hospital, Boston, MA, United States
- Department of Psychology, University of Virginia, Charlottesville, VA, United States
| | - Katrina Farris
- Department of Psychology, University of Virginia, Charlottesville, VA, United States
- Department of Psychology, Georgia State University, Atlanta, GA, United States
| | - Tobias Grossmann
- Department of Psychology, University of Virginia, Charlottesville, VA, United States
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
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25
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Qi L, Yin Y, Bu L, Tang Z, Tang L, Dong G. Acute VR competitive cycling exercise enhanced cortical activations and brain functional network efficiency in MA-dependent individuals. Neurosci Lett 2021; 757:135969. [PMID: 34023411 DOI: 10.1016/j.neulet.2021.135969] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Revised: 05/14/2021] [Accepted: 05/17/2021] [Indexed: 12/23/2022]
Abstract
BACKGROUND Methamphetamine (MA) dependence is associated with elevated rates cognitive impairment in MA users. The objective of the present study was to investigate the effects of virtual reality (VR) competitive cycling excise on the neurocognitive functions and on negative affectivity of MA-dependent individuals. METHODS Thirty MA-dependent individuals performed a colour-word Stroop task and underwent a profile of mood states (POMS) scale assessment both before and after a 10 min VR competitive cycling exercise. Functional near-infrared spectroscopy (fNIRS) were recorded during the pre-and post-exercise Stroop tasks and during rest. RESULTS After acute exercise, neural activity, along with improved Stroop performance, was enhanced significantly in the dorsolateral prefrontal cortex. Also observed during post-exercise Stroop tasks was a more efficient network architecture in the topological organization of brain networks than during the pre-exercise Stroop tasks. As for resting states before versus after exercisethe, we detected an increased functional connectivity between the prefrontal cortex and the motor cortex after exercise. CONCLUSIONS These results suggest that an acute bout of VR competitive cycling exercise facilitates executive information processing by enhancing task-related cortical activations and brain functional network efficiency in MA-dependent individuals.
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Affiliation(s)
- Liping Qi
- School of Biomedical Engineering, Dalian University of Technology, Dalian, 116024, China.
| | - Yue Yin
- School of Biomedical Engineering, Dalian University of Technology, Dalian, 116024, China
| | - Lingguo Bu
- Joint SDU-NTU Centre for Artificial Intelligence Research (C-FAIR), Shandong University, Jinan, 250101, China
| | - Zekun Tang
- Shandong Sport University, Jinan, 250102, China
| | - Lei Tang
- Compulsory Isolation Drug Rehabilitation Center of Shandong Province, Zibo, 255311, China
| | - Guijun Dong
- Shandong Sport University, Jinan, 250102, China.
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26
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Hu Z, Liu L, Wang M, Jia G, Li H, Si F, Dong M, Qian Q, Niu H. Disrupted signal variability of spontaneous neural activity in children with attention-deficit/hyperactivity disorder. BIOMEDICAL OPTICS EXPRESS 2021; 12:3037-3049. [PMID: 34168913 PMCID: PMC8194629 DOI: 10.1364/boe.418921] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 04/16/2021] [Accepted: 04/22/2021] [Indexed: 05/08/2023]
Abstract
Brain signal variability (BSV) has shown to be powerful in characterizing human brain development and neuropsychiatric disorders. Multiscale entropy (MSE) is a novel method for quantifying the variability of brain signal, and helps elucidate complex dynamic pathological mechanisms in children with attention-deficit/hyperactivity disorder (ADHD). Here, multiple-channel resting-state functional near-infrared spectroscopy (fNIRS) imaging data were acquired from 42 children with ADHD and 41 healthy controls (HCs) and then BSV was calculated for each participant based on the MSE analysis. Compared with HCs, ADHD group exhibited reduced BSV in both high-order and primary brain functional networks, e.g., the default mode, frontoparietal, attention and visual networks. Intriguingly, the BSV aberrations negatively correlated with ADHD symptoms in the frontoparietal network and negatively correlated with reaction time variability in the frontoparietal, default mode, somatomotor and attention networks. This study demonstrates a wide alternation in the moment-to-moment variability of spontaneous brain signal in children with ADHD, and highlights the potential for using MSE metric as a disease biomarker.
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Affiliation(s)
- Zhenyan Hu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Zhenyan Hu and Lu Liu contributed equally to this research
| | - Lu Liu
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
- Zhenyan Hu and Lu Liu contributed equally to this research
| | - Mengjing Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Gaoding Jia
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Haimei Li
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Feifei Si
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Min Dong
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Qiujin Qian
- Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
- NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - HaiJing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
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27
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Zhang S, Peng C, Yang Y, Wang D, Hou X, Li D. Resting-state brain networks in neonatal hypoxic-ischemic brain damage: a functional near-infrared spectroscopy study. NEUROPHOTONICS 2021; 8:025007. [PMID: 33997105 PMCID: PMC8119736 DOI: 10.1117/1.nph.8.2.025007] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 04/28/2021] [Indexed: 06/12/2023]
Abstract
Significance: There is an emerging need for convenient and continuous bedside monitoring of full-term newborns with hypoxic-ischemic brain damage (HIBD) to determine whether early intervention is required. Functional near-infrared spectroscopy (fNIRS)-based resting-state brain network analysis, which could provide an effective evaluation method, remains to be extensively studied. Aim: Our study aims to verify the feasibility of fNIRS-based resting-state brain networks for evaluating brain function in infants with HIBD to provide a new and effective means for clinical research in neonatal HIBD. Approach: Thirteen neonates with HIBD were scanned using fNIRS in the resting state. The brain network properties were explored to attempt to extract effective features as recognition indicators. Results: Compared with healthy controls, newborns with HIBD showed decreased brain functional connectivity. Specifically, there were severe losses of long-range functional connectivity of the contralateral parietal-temporal lobe, contralateral parietal-frontal lobe, and contralateral parietal lobe. The node degree showed a widespread decrease in the left frontal middle gyrus, left superior frontal gyrus dorsal, and right central posterior gyrus. However, newborns with HIBD showed a significantly higher local network efficiency (* p < 0.05 ). Subsequently, network indicators based on small-worldness, local efficiency, modularity, and normalized clustering coefficient were extracted for HIBD identification with the accuracy observed as 79.17%. Conclusions: Our findings indicate that fNIRS-based resting-state brain network analysis could support early HIBD diagnosis.
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Affiliation(s)
- Shen Zhang
- Beihang University, School of Biological Science and Medical Engineering, Beijing, China
| | - Cheng Peng
- Peking University First Hospital, Department of Neonatal Ward, Beijing, China
| | - Yang Yang
- Beihang University, School of Biological Science and Medical Engineering, Beijing, China
| | - Daifa Wang
- Beihang University, School of Biological Science and Medical Engineering, Beijing, China
- Beihang University, Advanced Innovation Center for Biomedical Engineering, Beijing, China
| | - Xinlin Hou
- Peking University First Hospital, Department of Neonatal Ward, Beijing, China
| | - Deyu Li
- Beihang University, School of Biological Science and Medical Engineering, Beijing, China
- Beihang University, Advanced Innovation Center for Biomedical Engineering, Beijing, China
- Beihang University, State Key Laboratory of Software Development Environment, Beijing, China
- Beihang University, State Key Laboratory of Virtual Reality Technology and System, Beijing, China
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28
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Hou X, Zhang Z, Zhao C, Duan L, Gong Y, Li Z, Zhu C. NIRS-KIT: a MATLAB toolbox for both resting-state and task fNIRS data analysis. NEUROPHOTONICS 2021; 8:010802. [PMID: 33506071 PMCID: PMC7829673 DOI: 10.1117/1.nph.8.1.010802] [Citation(s) in RCA: 78] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Accepted: 01/05/2021] [Indexed: 05/27/2023]
Abstract
Significance: Functional near-infrared spectroscopy (fNIRS) has been widely used to probe human brain function during task state and resting state. However, the existing analysis toolboxes mainly focus on task activation analysis, few software packages can assist resting-state fNIRS studies. Aim: We aimed to provide a versatile and easy-to-use toolbox to perform analysis for both resting state and task fNIRS. Approach: We developed a MATLAB toolbox called NIRS-KIT that works for both resting-state analysis and task activation detection. Results: NIRS-KIT implements common and necessary processing steps for performing fNIRS data analysis, including data preparation, quality control, preprocessing, individual-level analysis, group-level statistics with several popular statistical models, and multiple comparison correction methods, and finally results visualization. For resting-state fNIRS analysis, functional connectivity analysis, graph theory-based network analysis, and amplitude of low-frequency fluctuations analysis are provided. Additionally, NIRS-KIT also supports activation analysis for task fNIRS. Conclusions: NIRS-KIT offers an open source tool for researchers to analyze resting-state and/or task fNIRS data in one suite. It contains several key features: (1) good compatibility, supporting multiple fNIRS recording systems, data formats of NIRS-SPM and Homer2, and the shared near-infrared spectroscopy format data format recommended by the fNIRS society; (2) flexibility, supporting customized preprocessing scripts; (3) ease-to-use, allowing processing fNIRS signals in batch manner with user-friendly graphical user interfaces; and (4) feature-packed data viewing and result visualization. We anticipate that this NIRS-KIT will facilitate the development of the fNIRS field.
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Affiliation(s)
- Xin Hou
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Zong Zhang
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Chen Zhao
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Lian Duan
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Yilong Gong
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Zheng Li
- Beijing Normal University at Zhuhai, Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Zhuhai, China
- Beijing Normal University, Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing, China
| | - Chaozhe Zhu
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
- Beijing Normal University, Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing, China
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29
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Gut microbiota composition is associated with newborn functional brain connectivity and behavioral temperament. Brain Behav Immun 2021; 91:472-486. [PMID: 33157257 DOI: 10.1016/j.bbi.2020.11.003] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/27/2020] [Accepted: 11/01/2020] [Indexed: 12/12/2022] Open
Abstract
The gut microbiome appears to play an important role in human health and disease. However, only little is known about how variability in the gut microbiome contributes to individual differences during early and sensitive stages of brain and behavioral development. The current study examined the link between gut microbiome, brain, and behavior in newborn infants (N = 63; M [age] = 25 days). Infant gut microbiome diversity was measured from stool samples using metagenomic sequencing, infant functional brain network connectivity was assessed using a resting state functional near infrared spectroscopy (rs-fNIRS) procedure, and infant behavioral temperament was assessed using parental report. Our results show that gut microbiota composition is linked to individual variability in brain network connectivity, which in turn mediated individual differences in behavioral temperament, specifically negative emotionality, among infants. Furthermore, virulence factors, possibly indexing pathogenic activity, were associated with differences in brain network connectivity linked to negative emotionality. These findings provide novel insights into the early developmental origins of the gut microbiome-brain axis and its association with variability in important behavioral traits. This suggests that the gut microbiome is an important biological factor to consider when studying human development and health.
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30
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Urquhart EL, Wanniarachchi H, Wang X, Gonzalez-Lima F, Alexandrakis G, Liu H. Transcranial photobiomodulation-induced changes in human brain functional connectivity and network metrics mapped by whole-head functional near-infrared spectroscopy in vivo. BIOMEDICAL OPTICS EXPRESS 2020; 11:5783-5799. [PMID: 33149986 PMCID: PMC7587286 DOI: 10.1364/boe.402047] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 09/10/2020] [Accepted: 09/13/2020] [Indexed: 06/11/2023]
Abstract
Transcranial photobiomodulation (tPBM) with near-infrared light on the human head has been shown to enhance human cognition. In this study, tPBM-induced effects on resting state brain networks were investigated using 111-channel functional near-infrared spectroscopy over the whole head. Measurements were collected with and without 8-minute tPBM in 19 adults. Functional connectivity (FC) and brain network metrics were quantified using Pearson's correlation coefficients and graph theory analysis (GTA), respectively, for the periods of pre-, during, and post-tPBM. Our results revealed that tPBM (1) enhanced information processing speed and efficiency of the brain network, and (2) increased FC significantly in the frontal-parietal network, shedding light on a better understanding of tPBM effects on brain networks.
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Affiliation(s)
- Elizabeth L. Urquhart
- University of Texas at Arlington, Department of Bioengineering, Arlington, TX 76010, USA
| | - Hashini Wanniarachchi
- University of Texas at Arlington, Department of Bioengineering, Arlington, TX 76010, USA
| | - Xinlong Wang
- University of Texas at Arlington, Department of Bioengineering, Arlington, TX 76010, USA
| | - Francisco Gonzalez-Lima
- University of Texas at Austin, Department of Psychology and Institute for Neuroscience, Austin, TX 78712, USA
| | - George Alexandrakis
- University of Texas at Arlington, Department of Bioengineering, Arlington, TX 76010, USA
| | - Hanli Liu
- University of Texas at Arlington, Department of Bioengineering, Arlington, TX 76010, USA
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31
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Identifying Resting-State Functional Connectivity Changes in the Motor Cortex Using fNIRS During Recovery from Stroke. Brain Topogr 2020; 33:710-719. [PMID: 32685998 DOI: 10.1007/s10548-020-00785-2] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2020] [Accepted: 07/11/2020] [Indexed: 12/23/2022]
Abstract
Resting-state functional imaging has been used to study the functional reorganization of the brain. The application of functional near-infrared spectroscopy (fNIRS) to assess resting-state functional connectivity (rsFC) has already been demonstrated in recent years. The present study aimed to identify the difference in rsFC patterns during the recovery from the upper-limb deficit due to stroke. Twenty patients with mild stroke having an onset of four to eight weeks were recruited from the stroke clinic of our institute and an equal number of healthy volunteers were included in the study after ethical committee approval. The fNIRS signals were recorded bilaterally over the premotor area and supplementary motor area and over the primary motor cortex. Pearson Correlation is the method used to compute rsFC for the healthy group and patient group. For the healthy group, both intra-hemispheric and inter-hemispheric connections were stronger. RSFC analysis demonstrated changes from the healthy pattern for the patient group with an upper-limb deficit. The left hemisphere affected group showed disrupted ipsilesional and an increased contra-lesional connectivity. The longitudinal data analysis of rsFC showed improvement in the connections in the ipsilesional hemisphere between the primary motor area, somatosensory area, and premotor areas. In the future, the rsFC changes during the recovery could be used to predict the extent of recovery from stroke motor deficits.
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32
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Hu Z, Liu G, Dong Q, Niu H. Applications of Resting-State fNIRS in the Developing Brain: A Review From the Connectome Perspective. Front Neurosci 2020; 14:476. [PMID: 32581671 PMCID: PMC7284109 DOI: 10.3389/fnins.2020.00476] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 04/16/2020] [Indexed: 12/21/2022] Open
Abstract
Early brain development from infancy through childhood is closely related to the development of cognition and behavior in later life. Human brain connectome is a novel framework for describing topological organization of the developing brain. Resting-state functional near-infrared spectroscopy (fNIRS), with a natural scanning environment, low cost, and high portability, is considered as an emerging imaging technique and has shown valuable potential in exploring brain network architecture and its changes during the development. Here, we review the recent advances involving typical and atypical development of the brain connectome from neonates to children using resting-state fNIRS imaging. This review highlights that the combination of brain connectome and resting-state fNIRS imaging offers a promising framework for understanding human brain development.
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Affiliation(s)
- Zhishan Hu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Guangfang Liu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
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33
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Sun Q, Wang X, Huang B, Sun J, Li J, Zhuang H, Xiong G. Cortical Activation Patterns of Different Masking Noises and Correlation With Their Masking Efficacy, Determined by Functional Near-Infrared Spectroscopy. Front Hum Neurosci 2020; 14:149. [PMID: 32410973 PMCID: PMC7198837 DOI: 10.3389/fnhum.2020.00149] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 04/06/2020] [Indexed: 01/21/2023] Open
Abstract
Acoustic therapy in tinnitus treatment is poorly characterized, and efficacy assessment depends on subjective descriptions. Narrow-band noise, notched sound, and white noise have positive therapeutic effects on monotonous tinnitus. Considering the tonotopic characteristics of the auditory system and the spectral characteristics of these three masking sounds, the activation pattern of the auditory cortex and the mechanism of inhibiting tinnitus may be different. This study aimed to compare the activation patterns of three spectrally different masking noises and study the correlation between the masking effects and variational amplitude of oxygenated hemoglobin (HbO) in the corresponding cortical regions. We also assessed near-infrared spectroscopy brain function imaging (NIRS) as an objective assessment tool in acoustic therapy. Patients with persistent non-pulsatile tinnitus and control volunteers without tinnitus were enrolled in this study. The subjects were seated in a sound-proof room, with two optode arrays covering the bilateral temporal lobe. Auditory stimuli were presented; stimulation sequences followed the block design: different noises appeared randomly and repeated in five cycles. Tinnitus match and residual inhibition were performed in the tinnitus group. The data analyses were conducted using the NIRS_SPM toolbox. The group analysis results showed that the narrow-band noise caused a marginally significant decrease in HbO signal in the Brodmann 21 region (BA21), while white noise caused a significant increase in HbO signal in BA21. Notched sound did not cause significant changes in the HbO signal in the temporal cortex. And none of the three masking noises caused significant changes in the HbR signal in the temporal cortex. The depth of residual inhibition induced by the narrow-band noise and white noise significantly correlated with ΔHbO in the region of interest (ROI). However, neither the depth nor duration of the residual inhibition induced by notched sound correlated with the ΔHbO. Thus, NIRS showed three cortical activation patterns induced by three different masking noises, and correlations between residual inhibition effects and change of HbO amplitude were found. NIRS could therefore be applied in objective assessment of acoustic therapy.
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Affiliation(s)
- Qiyang Sun
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Xianren Wang
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Bixue Huang
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - JinCangjian Sun
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Jiahui Li
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Huiwen Zhuang
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
| | - Guanxia Xiong
- Department of Otorhinolaryngology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Institute of Otorhinolaryngology, Sun Yat-sen University, Guangzhou, China
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Urquhart EL, Wang X, Liu H, Fadel PJ, Alexandrakis G. Differences in Net Information Flow and Dynamic Connectivity Metrics Between Physically Active and Inactive Subjects Measured by Functional Near-Infrared Spectroscopy (fNIRS) During a Fatiguing Handgrip Task. Front Neurosci 2020; 14:167. [PMID: 32210748 PMCID: PMC7076120 DOI: 10.3389/fnins.2020.00167] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Accepted: 02/14/2020] [Indexed: 12/11/2022] Open
Abstract
Twenty-three young adults (4 Females, 25.13 ± 3.72 years) performed an intermittent maximal handgrip force task using their dominant hand for 20 min (3.5 s squeeze/6.5 s release, 120 blocks) with concurrent cortical activity imaging by functional Near-Infrared Spectroscopy (fNRIS; OMM-3000, Shimadzu Corp., 111 channels). Subjects were grouped as physically active (n = 10) or inactive (n = 12) based on a questionnaire (active-exercise at least four times a week, inactive- exercise less than two times a week). We explored how motor task fatigue affected the vasomotion-induced oscillations in ΔHbO as measured by fNIRS at each hemodynamic frequency band: endothelial component (0.003–0.02 Hz) associated to microvascular activity, neurogenic component (0.02–0.04 Hz) related to intrinsic neuronal activity, and myogenic component (0.04–0.15 Hz) linked to activity of smooth muscles of arterioles. To help understand how these three neurovascular regulatory mechanisms relate to handgrip task performance we quantified several dynamic fNIRS metrics, including directional phase transfer entropy (dPTE), a computationally efficient and data-driven method used as a marker of information flow between cortical regions, and directional connectivity (DC), a means to compute directionality of information flow between two cortical regions. The relationship between static functional connectivity (SFC) and functional connectivity variability (FCV) was also explored to understand their mutual dependence for each frequency band in the context of handgrip performance as fatigued increased. Our findings ultimately showed differences between subject groups across all fNIRS metrics and hemodynamic frequency bands. These findings imply that physical activity modulates neurovascular control mechanisms at the endogenic, neurogenic, and myogenic frequency bands resulting in delayed fatigue onset and enhanced performance. The dynamic cortical network metrics quantified in this work for young, healthy subjects provides baseline measurements to guide future work on older individuals and persons with impaired cardiovascular health.
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Affiliation(s)
- Elizabeth L Urquhart
- Bioengineering Department, University of Texas at Arlington, Arlington, TX, United States
| | - Xinlong Wang
- Bioengineering Department, University of Texas at Arlington, Arlington, TX, United States
| | - Hanli Liu
- Bioengineering Department, University of Texas at Arlington, Arlington, TX, United States
| | - Paul J Fadel
- Department of Kinesiology, University of Texas at Arlington, Arlington, TX, United States
| | - George Alexandrakis
- Bioengineering Department, University of Texas at Arlington, Arlington, TX, United States
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Wang M, Hu Z, Liu L, Li H, Qian Q, Niu H. Disrupted functional brain connectivity networks in children with attention-deficit/hyperactivity disorder: evidence from resting-state functional near-infrared spectroscopy. NEUROPHOTONICS 2020; 7:015012. [PMID: 32206679 PMCID: PMC7064804 DOI: 10.1117/1.nph.7.1.015012] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Accepted: 02/20/2020] [Indexed: 05/19/2023]
Abstract
Significance: Attention-deficit/hyperactivity disorder (ADHD) is the most common psychological disease in childhood. Currently, widely used neuroimaging techniques require complete body confinement and motionlessness and thus are extremely hard for brain scanning of ADHD children. Aim: We present resting-state functional near-infrared spectroscopy (fNIRS) as an imaging technique to record spontaneous brain activity in children with ADHD. Approach: The brain functional connectivity was calculated, and the graph theoretical analysis was further applied to investigate alterations in the global and regional properties of the brain network in the patients. In addition, the relationship between brain network features and core symptoms was examined. Results: ADHD patients exhibited significant decreases in both functional connectivity and global network efficiency. Meanwhile, the nodal efficiency in children with ADHD was also found to be altered, e.g., increase in the visual and dorsal attention networks and decrease in somatomotor and default mode networks, compared to the healthy controls. More importantly, the disrupted functional connectivity and nodal efficiency significantly correlated with dimensional ADHD scores. Conclusions: We clearly demonstrate the feasibility and potential of fNIRS-based connectome technique in ADHD or other neurological diseases in the future.
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Affiliation(s)
- Mengjing Wang
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Zhishan Hu
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Lu Liu
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, China
- Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders, Beijing, China
- Peking University, National Health Commission Key Laboratory of Mental Health, Beijing, China
| | - Haimei Li
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, China
- Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders, Beijing, China
- Peking University, National Health Commission Key Laboratory of Mental Health, Beijing, China
| | - Qiujin Qian
- Peking University Sixth Hospital, Institute of Mental Health, Beijing, China
- Peking University Sixth Hospital, National Clinical Research Center for Mental Disorders, Beijing, China
- Peking University, National Health Commission Key Laboratory of Mental Health, Beijing, China
- Address all correspondence to Qiujin Qian, E-mail: ; Haijing Niu, E-mail:
| | - Haijing Niu
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
- Beijing Normal University, Center of Social Welfare Studies, Beijing, China
- Address all correspondence to Qiujin Qian, E-mail: ; Haijing Niu, E-mail:
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Almajidy RK, Mankodiya K, Abtahi M, Hofmann UG. A Newcomer's Guide to Functional Near Infrared Spectroscopy Experiments. IEEE Rev Biomed Eng 2019; 13:292-308. [PMID: 31634142 DOI: 10.1109/rbme.2019.2944351] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
This review presents a practical primer for functional near-infrared spectroscopy (fNIRS) with respect to technology, experimentation, and analysis software. Its purpose is to jump-start interested practitioners considering utilizing a non-invasive, versatile, nevertheless challenging window into the brain using optical methods. We briefly recapitulate relevant anatomical and optical foundations and give a short historical overview. We describe competing types of illumination (trans-illumination, reflectance, and differential reflectance) and data collection methods (continuous wave, time domain and frequency domain). Basic components (light sources, detection, and recording components) of fNIRS systems are presented. Advantages and limitations of fNIRS techniques are offered, followed by a list of very practical recommendations for its use. A variety of experimental and clinical studies with fNIRS are sampled, shedding light on many brain-related ailments. Finally, we describe and discuss a number of freely available analysis and presentation packages suited for data analysis. In conclusion, we recommend fNIRS due to its ever-growing body of clinical applications, state-of-the-art neuroimaging technique and manageable hardware requirements. It can be safely concluded that fNIRS adds a new arrow to the quiver of neuro-medical examinations due to both its great versatility and limited costs.
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Urquhart EL, Wanniarachchi HI, Wang X, Liu H, Fadel PJ, Alexandrakis G. Mapping cortical network effects of fatigue during a handgrip task by functional near-infrared spectroscopy in physically active and inactive subjects. NEUROPHOTONICS 2019; 6:045011. [PMID: 31853458 PMCID: PMC6904890 DOI: 10.1117/1.nph.6.4.045011] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 11/19/2019] [Indexed: 05/29/2023]
Abstract
The temporal evolution of cortical activation and connectivity patterns during a fatiguing handgrip task were studied by functional near-infrared spectroscopy (fNIRS). Twenty-three young adults (18 to 35 years old) were recruited to use a handheld force sensor to perform intermittent handgrip contractions with their dominant hand at their personal maximum voluntary contraction force level for 3.5 s followed by 6.5 s of rest for 120 blocks. Subjects were divided into self-reported physically active and inactive groups, and their hemodynamic activity over the prefrontal and sensory-motor cortices (111 channels) was mapped while they performed this task. Using this fNIRS setup, a more detailed time sequence of cortical activation and connectivity patterns was observed compared to prior studies. A temporal evolution sequence of hemodynamic activation patterns was noted, which was different between the active and the inactive groups. Physically active subjects demonstrated delayed fatigue onset and significantly longer-lasting and more spatially extended functional connectivity (FC) patterns, compared to inactive subjects. The observed differences in activation and FC suggested differences in cortical network adaptation patterns as fatigue set in, which were dependent on subjects' physical activity. The findings of this study suggest that physical activity increases FC with regions involved in motor task control and correlates to extended fatigue onset and enhanced performance.
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Affiliation(s)
- Elizabeth L. Urquhart
- University of Texas at Arlington, Bioengineering Department, Arlington, Texas, United States
| | | | - Xinlong Wang
- University of Texas at Arlington, Bioengineering Department, Arlington, Texas, United States
| | - Hanli Liu
- University of Texas at Arlington, Bioengineering Department, Arlington, Texas, United States
| | - Paul J. Fadel
- University of Texas at Arlington, Department of Kinesiology, Arlington, Texas, United States
| | - George Alexandrakis
- University of Texas at Arlington, Bioengineering Department, Arlington, Texas, United States
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Klempir O, Krupicka R, Mehnert J, Cejka V, Polakova K, Brozova H, Szabo Z, Ruzicka E, Jech R. Reshaping cortical activity with subthalamic stimulation in Parkinson's disease during finger tapping and gait mapped by near infrared spectroscopy. J Appl Biomed 2019; 17:157-166. [PMID: 34907697 DOI: 10.32725/jab.2019.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Accepted: 08/19/2019] [Indexed: 11/05/2022] Open
Abstract
Exploration of motor cortex activity is essential to understanding the pathophysiology in Parkinson's Disease (PD), but only simple motor tasks can be investigated using a fMRI or PET. We aim to investigate the cortical activity of PD patients during a complex motor task (gait) to verify the impact of deep brain stimulation in the subthalamic nucleus (DBS-STN) by using Near-Infrared-Spectroscopy (NIRS). NIRS is a neuroimaging method of brain cortical activity using low-energy optical radiation to detect local changes in (de)oxyhemoglobin concentration. We used a multichannel portable NIRS during finger tapping (FT) and gait. To determine the signal activity, our methodology consisted of a pre-processing phase for the raw signal, followed by statistical analysis based on a general linear model. Processed recordings from 9 patients were statistically compared between the on and off states of DBS-STN. DBS-STN led to an increased activity in the contralateral motor cortex areas during FT. During gait, we observed a concentration of activity towards the cortex central area in the "stimulation-on" state. Our study shows how NIRS can be used to detect functional changes in the cortex of patients with PD with DBS-STN and indicates its future use for applications unsuited for PET and a fMRI.
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Affiliation(s)
- Ondrej Klempir
- Czech Technical University in Prague, Faculty of Biomedical Engineering, Department of Biomedical Informatics, Kladno, Czech Republic
| | - Radim Krupicka
- Czech Technical University in Prague, Faculty of Biomedical Engineering, Department of Biomedical Informatics, Kladno, Czech Republic
| | - Jan Mehnert
- University Medical Center Eppendorf, Department of Systems Neuroscience, Hamburg, Germany.,Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Vaclav Cejka
- Czech Technical University in Prague, Faculty of Biomedical Engineering, Department of Biomedical Informatics, Kladno, Czech Republic.,Charles University, First Faculty of Medicine and General University Hospital, Department of Neurology, Prague, Czech Republic
| | - Kamila Polakova
- Charles University, First Faculty of Medicine and General University Hospital, Department of Neurology, Prague, Czech Republic
| | - Hana Brozova
- Charles University, First Faculty of Medicine and General University Hospital, Department of Neurology, Prague, Czech Republic
| | - Zoltan Szabo
- Czech Technical University in Prague, Faculty of Biomedical Engineering, Department of Biomedical Informatics, Kladno, Czech Republic
| | - Evzen Ruzicka
- Charles University, First Faculty of Medicine and General University Hospital, Department of Neurology, Prague, Czech Republic
| | - Robert Jech
- Charles University, First Faculty of Medicine and General University Hospital, Department of Neurology, Prague, Czech Republic
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Hu Z, Zhang J, Zhang L, Xiang YT, Yuan Z. Linking brain activation to topological organization in the frontal lobe as a synergistic indicator to characterize the difference between various cognitive processes of executive functions. NEUROPHOTONICS 2019; 6:025008. [PMID: 31172018 PMCID: PMC6537479 DOI: 10.1117/1.nph.6.2.025008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 03/28/2019] [Indexed: 05/17/2023]
Abstract
Executive functions (EFs) associated with the frontal lobe are vital for goal-orientated behavior. To date, limited efforts have been made to examine the relationships among the behavior, brain activation, and topological organization of functional networks in the frontal lobe underlying various EF tasks, including inhibition, working memory, and cognitive flexibility. In this study, functional near-infrared spectroscopy neuroimaging technique was used to systematically inspect the differences in the brain activation and the topological organization of brain networks between various EF tasks in the frontal lobe. In addition, the relationships between brain activation/network properties and task performances and the relationships between brain activation and network properties were, respectively, examined for different EF tasks. Consequently, we have discovered that the nodal and global properties of the resting-state and task-evoked networks, respectively, exhibited significant correlations with the activation of various brain regions during various EF tasks. In particular, the measure that links the neural activation to the topological organization of the brain networks in the frontal lobe can serve as a synergistic indicator to examine the difference between various EF tasks, which paves a way toward a comprehensive understanding of the neural mechanism underlying EFs.
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Affiliation(s)
- Zhishan Hu
- University of Macau, Faculty of Health Sciences, Macao Special Administrative Region, China
| | - Juan Zhang
- University of Macau, Faculty of Education, Macao Special Administrative Region, China
| | - Lingyan Zhang
- The Third Affiliated Hospital of China Southern Medical University, Department of Radiology, Guangzhou, China
| | - Yu-Tao Xiang
- University of Macau, Faculty of Health Sciences, Macao Special Administrative Region, China
| | - Zhen Yuan
- University of Macau, Faculty of Health Sciences, Macao Special Administrative Region, China
- Address all correspondence to Zhen Yuan, E-mail:
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40
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Cai L, Dong Q, Wang M, Niu H. Functional near-infrared spectroscopy evidence for the development of topological asymmetry between hemispheric brain networks from childhood to adulthood. NEUROPHOTONICS 2019; 6:025005. [PMID: 31172017 PMCID: PMC6537120 DOI: 10.1117/1.nph.6.2.025005] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2018] [Accepted: 04/08/2019] [Indexed: 05/14/2023]
Abstract
Cerebral asymmetry is considered an important marker of the successful development of the human brain. Recent studies have demonstrated topological asymmetries between structurally hemispheric networks in the human brain. However, it remains largely unknown whether and how the functionally topological asymmetries evolve from childhood to adulthood, a critical period that constitutes the primary peak of human brain and cognitive development. Here, we adopted resting-state functional near-infrared spectroscopy imaging data to construct hemispheric functional networks and then applied graph theory analysis to quantify the topological characteristics of the hemispheric networks. We found that the adult group exhibited consistent leftward hemispheric asymmetries in both global and local network efficiency, and the degree of leftward asymmetry in local network efficiency was significantly increased with development from childhood to adulthood. At the nodal level, the degree of leftward asymmetry in nodal efficiency, mainly involving the frontal, parietal-occipital junction, and occipital regions, increased with development. These developmental patterns of topological asymmetries suggest that the protracted maturation of functional segregation in the left hemisphere could underlie language development from childhood to adulthood and provide insight into the development of human brain functional networks.
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Affiliation(s)
- Lin Cai
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing, China
- Beijing Normal University, Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing, China
- Keio University, Department of Electronics and Electrical Engineering, Yokohama, Japan
| | - Qi Dong
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing, China
| | - Mengjing Wang
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing, China
- Beijing Normal University, Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing, China
| | - Haijing Niu
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing, China
- Beijing Normal University, Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing, China
- Address all correspondence to Haijing Niu, E-mail:
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41
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Koren Y, Parmet Y, Bar-Haim S. Treading on the unknown increases prefrontal activity: A pilot fNIRS study. Gait Posture 2019; 69:96-100. [PMID: 30690327 DOI: 10.1016/j.gaitpost.2019.01.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2018] [Revised: 12/16/2018] [Accepted: 01/17/2019] [Indexed: 02/02/2023]
Abstract
BACKGROUND Complex walking conditions (e.g. dual tasking) have been associated with increased prefrontal (PFC) activity. However, most paradigms include a predictable environment, specifically, a predictable walking terrain. In the present study we investigate PFC activity under an unusual walking condition where each foot placement was on unexpected terrain, thus causing a mismatch between visuospatial perception and lower-extremity proprioception. RESEARCH OBJECTIVE To assess whether PFC activity increases under unstable unpredictable conditions compared to unstable but predictable conditions. METHODS This was a prospective study involving twenty healthy adults. Participants walked in two conditions: unstable but predictable, and unstable and unpredictable. To assess walking stability, both stride-time (ST) and stride-time variability (CV) were measured. To assess PFC activity, two wireless near-infrared spectroscopy devices were used. The group hemodynamic response (GHR) was calculated for each condition. For statistical analysis, a linear-mixed-effects model was used. RESULTS Walking with unpredictable perturbations did not change the ST (t = 0.51, p = 0.61) but significantly increased the parameter CV (t = 11.74, p < 0.001). The GHR of both conditions indicated brief per-initiation PFC activity that was similar across conditions. However, when GHRs were calculated relative to normal walking (i.e., the participants' own shoes), continuous activity was evident. Compared to the predictable condition, the unpredictable condition significantly increased this activity during steady-state walking (t = 2.13, p = 0.033). SIGNIFICANCE Observations from the present study suggest that at least two neural components are present in the measured signal-a brief one, occurring per-initiation, and a continuous one, sensitive to the predictability of the terrain. The second component was accompanied by a decrease in walking stability. These results may contribute to our understanding of the control mechanism underlying gait and future planning of rehabilitation protocols.
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Affiliation(s)
- Yogev Koren
- The Laboratory for Rehabilitation and Motor Control of Walking, Department of Physical Therapy, Recanati School for Community Health Professions, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel.
| | - Yisrael Parmet
- Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel.
| | - Simona Bar-Haim
- The Laboratory for Rehabilitation and Motor Control of Walking, Department of Physical Therapy, Recanati School for Community Health Professions, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer Sheva, Israel.
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Herold F, Wiegel P, Scholkmann F, Müller NG. Applications of Functional Near-Infrared Spectroscopy (fNIRS) Neuroimaging in Exercise⁻Cognition Science: A Systematic, Methodology-Focused Review. J Clin Med 2018; 7:E466. [PMID: 30469482 PMCID: PMC6306799 DOI: 10.3390/jcm7120466] [Citation(s) in RCA: 210] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2018] [Revised: 11/09/2018] [Accepted: 11/15/2018] [Indexed: 12/18/2022] Open
Abstract
For cognitive processes to function well, it is essential that the brain is optimally supplied with oxygen and blood. In recent years, evidence has emerged suggesting that cerebral oxygenation and hemodynamics can be modified with physical activity. To better understand the relationship between cerebral oxygenation/hemodynamics, physical activity, and cognition, the application of state-of-the art neuroimaging tools is essential. Functional near-infrared spectroscopy (fNIRS) is such a neuroimaging tool especially suitable to investigate the effects of physical activity/exercises on cerebral oxygenation and hemodynamics due to its capability to quantify changes in the concentration of oxygenated hemoglobin (oxyHb) and deoxygenated hemoglobin (deoxyHb) non-invasively in the human brain. However, currently there is no clear standardized procedure regarding the application, data processing, and data analysis of fNIRS, and there is a large heterogeneity regarding how fNIRS is applied in the field of exercise⁻cognition science. Therefore, this review aims to summarize the current methodological knowledge about fNIRS application in studies measuring the cortical hemodynamic responses during cognitive testing (i) prior and after different physical activities interventions, and (ii) in cross-sectional studies accounting for the physical fitness level of their participants. Based on the review of the methodology of 35 as relevant considered publications, we outline recommendations for future fNIRS studies in the field of exercise⁻cognition science.
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Affiliation(s)
- Fabian Herold
- Research Group Neuroprotection, German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany.
| | - Patrick Wiegel
- Department of Sport Science, University of Freiburg, Freiburg 79117, Germany.
- Bernstein Center Freiburg, University of Freiburg, Freiburg 79104, Germany.
| | - Felix Scholkmann
- Biomedical Optics Research Laboratory, Department of Neonatology, University Hospital Zurich, University of Zürich, Zürich 8091, Switzerland.
| | - Notger G Müller
- Research Group Neuroprotection, German Center for Neurodegenerative Diseases (DZNE), Magdeburg 39120, Germany.
- Center for Behavioral Brain Sciences (CBBS), Magdeburg 39118, Germany.
- Department of Neurology, Medical Faculty, Otto von Guericke University, Magdeburg 39120, Germany.
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Wang MY, Zhang J, Lu FM, Xiang YT, Yuan Z. Neuroticism and conscientiousness respectively positively and negatively correlated with the network characteristic path length in dorsal lateral prefrontal cortex: A resting-state fNIRS study. Brain Behav 2018; 8:e01074. [PMID: 30054989 PMCID: PMC6160652 DOI: 10.1002/brb3.1074] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 06/23/2018] [Accepted: 06/26/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Accumulating evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is implicated in personality traits. In this study, resting-state functional near infrared spectroscopy (fNIRS) combined with small-world analysis was utilized to examine the relationship between the network properties of dlPFC and personality traits. METHODS Thirty college students (aged between 20 and 29) were recruited from the University of Macau campus, whose personality scores were accessed with the NEO-FFT questionnaire. Graph theory combined with resting-state fNIRS data was used to quantify the network properties of dlPFC, whereas Pearson correlation analysis was performed to generate the relationship between the small-world indicators and personality scores. RESULTS Compared to matched random networks, the resting-state brain networks exhibited a larger clustering coefficient (Cp , 0.1-0.66), shorter characteristic path length (Lp , 0.1-0.66), and higher global (Eg , 0.1-0.66) and local efficiency (Eloc , 0.1-0.65). In particular, conscientiousness (r = -0.63) and neuroticism (r = 0.40) respectively showed negative and positive correlation with the Lp . CONCLUSIONS The resting-state functional brain networks in dlPFC exhibited the small-world properties. In addition, participants with higher conscientiousness scores showed a shorter Lp .
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Affiliation(s)
- Meng-Yun Wang
- Faculty of Health Sciences, University of Macau, Taipa, China
| | - Juan Zhang
- Faculty of Education, University of Macau, Taipa, China
| | - Feng-Mei Lu
- Chengdu Mental Health Center, Chengdu, China.,MOE Key Lab for Neuroinformation, The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - Yu-Tao Xiang
- Faculty of Health Sciences, University of Macau, Taipa, China
| | - Zhen Yuan
- Faculty of Health Sciences, University of Macau, Taipa, China
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Li X, Zhu Z, Zhao W, Sun Y, Wen D, Xie Y, Liu X, Niu H, Han Y. Decreased resting-state brain signal complexity in patients with mild cognitive impairment and Alzheimer's disease: a multiscale entropy analysis. BIOMEDICAL OPTICS EXPRESS 2018; 9:1916-1929. [PMID: 29675329 PMCID: PMC5905934 DOI: 10.1364/boe.9.001916] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 03/20/2018] [Accepted: 03/20/2018] [Indexed: 05/17/2023]
Abstract
Multiscale entropy (MSE) analysis is a novel entropy-based analysis method for quantifying the complexity of dynamic neural signals and physiological systems across multiple temporal scales. This approach may assist in elucidating the pathophysiologic mechanisms of amnestic mild cognitive impairment (aMCI) and Alzheimer's disease (AD). Using resting-state fNIRS imaging, we recorded spontaneous brain activity from 31 healthy controls (HC), 27 patients with aMCI, and 24 patients with AD. The quantitative analysis of MSE revealed that reduced brain signal complexity in AD patients in several networks, namely, the default, frontoparietal, ventral and dorsal attention networks. For the default and ventral attention networks, the MSE values also showed significant positive correlations with cognitive performances. These findings demonstrated that the MSE-based analysis method could serve as a novel tool for fNIRS study in characterizing and understanding the complexity of abnormal cortical signals in AD cohorts.
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Affiliation(s)
- Xuanyu Li
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, 100053, China
- Xuanyu Li, Zhaojun Zhu, and Weina Zhao contributed equally to this research
| | - Zhaojun Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China
- Xuanyu Li, Zhaojun Zhu, and Weina Zhao contributed equally to this research
| | - Weina Zhao
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, 100053, China
- Department of Neurology, Mudanjiang Medical University Affiliated HongQi Hospital, Mudanjiang, 157000, China
- Xuanyu Li, Zhaojun Zhu, and Weina Zhao contributed equally to this research
| | - Yu Sun
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, 100053, China
| | - Dong Wen
- School of Information Science and Engineering, Yanshan University, 438 Hebei Avenue, Qinhuangdao, 066004, China
- The Key Laboratory of Software Engineering of Hebei Province, Yanshan University, 438 Hebei Avenue, Qinhuangdao, 066004, China
| | - Yunyan Xie
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, 100053, China
| | - Xiangyu Liu
- Shenzhen Longhua District Central Hospital, Shenzhen, 518110, China
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China
| | - Ying Han
- Department of Neurology, XuanWu Hospital of Capital Medical University, Beijing, 100053, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China
- Beijing Institute of Geriatrics, Beijing, 100053, China
- National Clinical Research Center for Geriatric Disorders, Beijing, 100053, China
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45
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The development of functional network organization in early childhood and early adolescence: A resting-state fNIRS study. Dev Cogn Neurosci 2018; 30:223-235. [PMID: 29631206 PMCID: PMC6969083 DOI: 10.1016/j.dcn.2018.03.003] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Revised: 03/02/2018] [Accepted: 03/06/2018] [Indexed: 12/16/2022] Open
Abstract
Early childhood (7–8 years old) and early adolescence (11–12 years old) constitute two landmark developmental stages that comprise considerable changes in neural cognition. However, very limited information from functional neuroimaging studies exists on the functional topological configuration of the human brain during specific developmental periods. In the present study, we utilized continuous resting-state functional near-infrared spectroscopy (rs-fNIRS) imaging data to examine topological changes in network organization during development from early childhood and early adolescence to adulthood. Our results showed that the properties of small-worldness and modularity were not significantly different across development, demonstrating the developmental maturity of important functional brain organization in early childhood. Intriguingly, young children had a significantly lower global efficiency than early adolescents and adults, which revealed that the integration of the distributed networks strengthens across the developmental stages underlying cognitive development. Moreover, local efficiency of young children and adolescents was significantly lower than that of adults, while there was no difference between these two younger groups. This finding demonstrated that functional segregation remained relatively steady from early childhood to early adolescence, and the brain in these developmental periods possesses no optimal network configuration. Furthermore, we found heterogeneous developmental patterns in the regional nodal properties in various brain regions, such as linear increased nodal properties in the frontal cortex, indicating increasing cognitive capacity over development. Collectively, our results demonstrated that significant topological changes in functional network organization occurred during these two critical developmental stages, and provided a novel insight into elucidating subtle changes in brain functional networks across development.
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46
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Orihuela-Espina F, Leff DR, James DRC, Darzi AW, Yang GZ. Imperial College near infrared spectroscopy neuroimaging analysis framework. NEUROPHOTONICS 2018; 5:011011. [PMID: 28948193 PMCID: PMC5603769 DOI: 10.1117/1.nph.5.1.011011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2017] [Accepted: 08/23/2017] [Indexed: 05/03/2023]
Abstract
This paper describes the Imperial College near infrared spectroscopy neuroimaging analysis (ICNNA) software tool for functional near infrared spectroscopy neuroimaging data. ICNNA is a MATLAB-based object-oriented framework encompassing an application programming interface and a graphical user interface. ICNNA incorporates reconstruction based on the modified Beer-Lambert law and basic processing and data validation capabilities. Emphasis is placed on the full experiment rather than individual neuroimages as the central element of analysis. The software offers three types of analyses including classical statistical methods based on comparison of changes in relative concentrations of hemoglobin between the task and baseline periods, graph theory-based metrics of connectivity and, distinctively, an analysis approach based on manifold embedding. This paper presents the different capabilities of ICNNA in its current version.
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Affiliation(s)
- Felipe Orihuela-Espina
- Imperial College London, Hamlyn Center for Robotic Surgery, United Kingdom
- Instituto Nacional de Astrofísica, Óptica y Electrónica (INAOE), Puebla, Mexico
- Address all correspondence to: Felipe Orihuela-Espina, E-mail:
| | - Daniel R. Leff
- Imperial College London, Hamlyn Center for Robotic Surgery, United Kingdom
| | - David R. C. James
- Imperial College London, Hamlyn Center for Robotic Surgery, United Kingdom
| | - Ara W. Darzi
- Imperial College London, Hamlyn Center for Robotic Surgery, United Kingdom
| | - Guang-Zhong Yang
- Imperial College London, Hamlyn Center for Robotic Surgery, United Kingdom
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47
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Racz FS, Mukli P, Nagy Z, Eke A. Increased prefrontal cortex connectivity during cognitive challenge assessed by fNIRS imaging. BIOMEDICAL OPTICS EXPRESS 2017; 8:3842-3855. [PMID: 28856054 PMCID: PMC5560845 DOI: 10.1364/boe.8.003842] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Revised: 05/05/2017] [Accepted: 05/30/2017] [Indexed: 05/24/2023]
Abstract
In this study, functional near-infrared spectroscopy (fNIRS) and the graph theory approach were used to access the functional connectivity (FC) of the prefrontal cortex (PFC) in a resting state and during increased mental workload. For this very purpose, a pattern recognition-based test was developed, which elicited a strong response throughout the PFC during the test condition. FC parameters obtained during stimulation were found increased compared to those in a resting state after correlation based signal improvement (CBSI), which can attenuate those components of fNIRS signals which are unrelated to neural activity. These results indicate that the cognitive challenge increased the FC in the PFC and suggests a great potential in investigating FC in various cognitive states.
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Affiliation(s)
- Frigyes Samuel Racz
- Institute of Clinical Experimental Research, Semmelweis University, 37-43 Tűzoltó Street, Budapest 1094, Hungary
- Department of Physiology, 37-43 Tűzoltó Street, Budapest 1094, Hungary
| | - Peter Mukli
- Institute of Clinical Experimental Research, Semmelweis University, 37-43 Tűzoltó Street, Budapest 1094, Hungary
- Department of Physiology, 37-43 Tűzoltó Street, Budapest 1094, Hungary
| | - Zoltan Nagy
- Institute of Clinical Experimental Research, Semmelweis University, 37-43 Tűzoltó Street, Budapest 1094, Hungary
| | - Andras Eke
- Institute of Clinical Experimental Research, Semmelweis University, 37-43 Tűzoltó Street, Budapest 1094, Hungary
- Department of Physiology, 37-43 Tűzoltó Street, Budapest 1094, Hungary
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48
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Wang J, Dong Q, Niu H. The minimum resting-state fNIRS imaging duration for accurate and stable mapping of brain connectivity network in children. Sci Rep 2017; 7:6461. [PMID: 28743886 PMCID: PMC5527110 DOI: 10.1038/s41598-017-06340-7] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2016] [Accepted: 06/12/2017] [Indexed: 01/01/2023] Open
Abstract
Resting-state functional near-infrared spectroscopy (fNIRS) is a potential technique for the study of brain functional connectivity (FC) and networks in children. However, the necessary fNIRS scanning duration required to map accurate and stable functional brain connectivity and graph theory metrics in the resting-state brain activity remains largely unknown. Here, we acquired resting-state fNIRS imaging data from 53 healthy children to provide the first empirical evidence for the minimum imaging time required to obtain accurate and stable FC and graph theory metrics of brain network activity (e.g., nodal efficiency and network global and local efficiency). Our results showed that FC was accurately and stably achieved after 7.0-min fNIRS imaging duration, whereas the necessary scanning time for accurate and stable network measures was a minimum of 2.5 min at low network thresholds. These quantitative results provide direct evidence for the choice of the resting-state fNIRS imaging time in children in brain FC and network topology study. The current study also demonstrates that these methods are feasible and cost-effective in the application of time-constrained infants and critically ill children.
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Affiliation(s)
- Jingyu Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875, China. .,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China.
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49
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Geng S, Liu X, Biswal BB, Niu H. Effect of Resting-State fNIRS Scanning Duration on Functional Brain Connectivity and Graph Theory Metrics of Brain Network. Front Neurosci 2017; 11:392. [PMID: 28775676 PMCID: PMC5517460 DOI: 10.3389/fnins.2017.00392] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2016] [Accepted: 06/22/2017] [Indexed: 12/18/2022] Open
Abstract
As an emerging brain imaging technique, functional near infrared spectroscopy (fNIRS) has attracted widespread attention for advancing resting-state functional connectivity (FC) and graph theoretical analyses of brain networks. However, it remains largely unknown how the duration of the fNIRS signal scanning is related to stable and reproducible functional brain network features. To answer this question, we collected resting-state fNIRS signals (10-min duration, two runs) from 18 participants and then truncated the hemodynamic time series into 30-s time bins that ranged from 1 to 10 min. Measures of nodal efficiency, nodal betweenness, network local efficiency, global efficiency, and clustering coefficient were computed for each subject at each fNIRS signal acquisition duration. Analyses of the stability and between-run reproducibility were performed to identify optimal time length for each measure. We found that the FC, nodal efficiency and nodal betweenness stabilized and were reproducible after 1 min of fNIRS signal acquisition, whereas network clustering coefficient, local and global efficiencies stabilized after 1 min and were reproducible after 5 min of fNIRS signal acquisition for only local and global efficiencies. These quantitative results provide direct evidence regarding the choice of the resting-state fNIRS scanning duration for functional brain connectivity and topological metric stability of brain network connectivity.
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Affiliation(s)
- Shujie Geng
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijing, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal UniversityBeijing, China
| | - Xiangyu Liu
- Department of Neurology, Shenzhen Longhua District Central HospitalGuang dong, China
| | - Bharat B Biswal
- Department of Biomedical Engineering, New Jersey Institute of Technology, University HeightNewark, NJ, United States
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal UniversityBeijing, China.,Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal UniversityBeijing, China.,Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal UniversityBeijing, China
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50
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Santosa H, Aarabi A, Perlman SB, Huppert TJ. Characterization and correction of the false-discovery rates in resting state connectivity using functional near-infrared spectroscopy. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:55002. [PMID: 28492852 PMCID: PMC5424771 DOI: 10.1117/1.jbo.22.5.055002] [Citation(s) in RCA: 54] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 04/11/2017] [Indexed: 05/18/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a noninvasive neuroimaging technique that uses low levels of red to near-infrared light to measure changes in cerebral blood oxygenation. Spontaneous (resting state) functional connectivity (sFC) has become a critical tool for cognitive neuroscience for understanding task-independent neural networks, revealing pertinent details differentiating healthy from disordered brain function, and discovering fluctuations in the synchronization of interacting individuals during hyperscanning paradigms. Two of the main challenges to sFC-NIRS analysis are (i) the slow temporal structure of both systemic physiology and the response of blood vessels, which introduces false spurious correlations, and (ii) motion-related artifacts that result from movement of the fNIRS sensors on the participants’ head and can introduce non-normal and heavy-tailed noise structures. In this work, we systematically examine the false-discovery rates of several time- and frequency-domain metrics of functional connectivity for characterizing sFC-NIRS. Specifically, we detail the modifications to the statistical models of these methods needed to avoid high levels of false-discovery related to these two sources of noise in fNIRS. We compare these analysis procedures using both simulated and experimental resting-state fNIRS data. Our proposed robust correlation method has better performance in terms of being more reliable to the noise outliers due to the motion artifacts.
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Affiliation(s)
- Hendrik Santosa
- University of Pittsburgh, Department of Radiology, Pittsburgh, Pennsylvania, United States
| | - Ardalan Aarabi
- Universite de Picardie Jules Verne, Department of Medicine, Amiens, France
| | - Susan B. Perlman
- University of Pittsburgh, Department of Psychiatry, Pittsburgh, Pennsylvania, United States
| | - Theodore J. Huppert
- University of Pittsburgh, Departments of Radiology and Bioengineering, Clinical Science Translational Institute, and Center for the Neural Basis of Cognition, Pittsburgh, Pennsylvania, United States
- Address all correspondence to: Theodore J. Huppert, E-mail:
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