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Dubois J, Field RM, Jawhar S, Koch EM, Aghajan ZM, Miller N, Perdue KL, Taylor M. Reliability of brain metrics derived from a Time-Domain Functional Near-Infrared Spectroscopy System. Sci Rep 2024; 14:17500. [PMID: 39080458 PMCID: PMC11289386 DOI: 10.1038/s41598-024-68555-9] [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: 03/20/2024] [Accepted: 07/24/2024] [Indexed: 08/02/2024] Open
Abstract
With the growing interest in establishing brain-based biomarkers for precision medicine, there is a need for noninvasive, scalable neuroimaging devices that yield valid and reliable metrics. Kernel's second-generation Flow2 Time-Domain Functional Near-Infrared Spectroscopy (TD-fNIRS) system meets the requirements of noninvasive and scalable neuroimaging, and uses a validated modality to measure brain function. In this work, we investigate the test-retest reliability (TRR) of a set of metrics derived from the Flow2 recordings. We adopted a repeated-measures design with 49 healthy participants, and quantified TRR over multiple time points and different headsets-in different experimental conditions including a resting state, a sensory, and a cognitive task. Results demonstrated high reliability in resting state features including hemoglobin concentrations, head tissue light attenuation, amplitude of low frequency fluctuations, and functional connectivity. Additionally, passive auditory and Go/No-Go inhibitory control tasks each exhibited similar activation patterns across days. Notably, areas with the highest reliability were in auditory regions during the auditory task, and right prefrontal regions during the Go/No-Go task, consistent with prior literature. This study underscores the reliability of Flow2-derived metrics, supporting its potential to actualize the vision of using brain-based biomarkers for diagnosis, treatment selection and treatment monitoring of neuropsychiatric and neurocognitive disorders.
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Affiliation(s)
- Julien Dubois
- Kernel, 10361 Jefferson Blvd, Culver City, CA, 90232, USA
| | - Ryan M Field
- Kernel, 10361 Jefferson Blvd, Culver City, CA, 90232, USA
| | - Sami Jawhar
- Kernel, 10361 Jefferson Blvd, Culver City, CA, 90232, USA
| | - Erin M Koch
- Kernel, 10361 Jefferson Blvd, Culver City, CA, 90232, USA
| | | | - Naomi Miller
- Kernel, 10361 Jefferson Blvd, Culver City, CA, 90232, USA
| | | | - Moriah Taylor
- Kernel, 10361 Jefferson Blvd, Culver City, CA, 90232, USA
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2
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Shen F, Zhou H. Advances in the etiology and neuroimaging of children with attention deficit hyperactivity disorder. Front Pediatr 2024; 12:1400468. [PMID: 38915870 PMCID: PMC11194347 DOI: 10.3389/fped.2024.1400468] [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: 03/13/2024] [Accepted: 05/20/2024] [Indexed: 06/26/2024] Open
Abstract
Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in children, characterized by age-inappropriate inattention, hyperactivity, and impulsivity, which can cause extensive damage to children's academic, occupational, and social skills. This review will present current advancements in the field of attention deficit hyperactivity disorder, including genetics, environmental factors, epigenetics, and neuroimaging features. Simultaneously, we will discuss the highlights of promising directions for further study.
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Affiliation(s)
| | - Hui Zhou
- Department of Pediatrics, West China Second University Hospital, Sichuan University, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, Chengdu, China
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3
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Dong Y, Mao M, Wu Y, Che C, Song Q, Sun W, Zhang C. Frontal and parietal cortices activation during walking is repeatable in older adults based on fNIRS. Heliyon 2024; 10:e30197. [PMID: 38756562 PMCID: PMC11096826 DOI: 10.1016/j.heliyon.2024.e30197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 04/19/2024] [Accepted: 04/22/2024] [Indexed: 05/18/2024] Open
Abstract
Purpose This study aimed to explore the test-retest reliability of fNIRS in measuring frontal and parietal cortices activation during straight walking and turning walking in older adults, in order to provide a theoretical foundation for selecting assessment tools for clinical research on motor control and some diseases such as Parkinson's disease in older adults. Methods 18 healthy older participants (69.1 ± 0.7 years) were included in this study. The participants completed straight walking and figure-of-eight turning walking tasks at self-selected speeds. Intra-class correlation coefficients (ICCs) and Bland-Altman scatter plots were used to assess the test-retest reliability of oxyhemoglobin (HbO2) changes derived from fNIRS. p < 0.05 was considered statistically significant. Results The test-retest reliability of HbO2 in prefrontal cortex (ICC, 0.67-0.78) was good and excellent, in frontal motor cortex (ICC, 0.51-0.61) and parietal sensory cortex (ICC, 0.53-0.62) is fair and good when the older adults performed straight and turning walking tasks. Bland-Altman diagram shows that the data consistency is fair and good. Conclusion fNIRS can be used as a clinical measurement method to evaluate the brain activation of the older adults when walking in a straight line and turning, and the results are acceptable repeatability and consistency. However, it is necessary to strictly control the testing process and consider the possible changes in the repeated measurements.
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Affiliation(s)
- Yuqi Dong
- Graduate School, Shandong Sport University, Jinan, China
| | - Min Mao
- Graduate School, Shandong Sport University, Jinan, China
- School of Nursing and Rehabilitation, Shandong University, Jinan, China
| | - Yunzhi Wu
- Graduate School, Shandong Sport University, Jinan, China
| | - Chengzhang Che
- Graduate School, Shandong Sport University, Jinan, China
| | - Qipeng Song
- Graduate School, Shandong Sport University, Jinan, China
| | - Wei Sun
- Graduate School, Shandong Sport University, Jinan, China
| | - Cui Zhang
- Graduate School, Shandong Sport University, Jinan, China
- Sports Biomechanics Lab, Shandong Institute of Sport Science, Jinan, China
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4
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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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Bröhl T, Rings T, Pukropski J, von Wrede R, Lehnertz K. The time-evolving epileptic brain network: concepts, definitions, accomplishments, perspectives. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 3:1338864. [PMID: 38293249 PMCID: PMC10825060 DOI: 10.3389/fnetp.2023.1338864] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 12/19/2023] [Indexed: 02/01/2024]
Abstract
Epilepsy is now considered a network disease that affects the brain across multiple levels of spatial and temporal scales. The paradigm shift from an epileptic focus-a discrete cortical area from which seizures originate-to a widespread epileptic network-spanning lobes and hemispheres-considerably advanced our understanding of epilepsy and continues to influence both research and clinical treatment of this multi-faceted high-impact neurological disorder. The epileptic network, however, is not static but evolves in time which requires novel approaches for an in-depth characterization. In this review, we discuss conceptual basics of network theory and critically examine state-of-the-art recording techniques and analysis tools used to assess and characterize a time-evolving human epileptic brain network. We give an account on current shortcomings and highlight potential developments towards an improved clinical management of epilepsy.
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Affiliation(s)
- Timo Bröhl
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Thorsten Rings
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
| | - Jan Pukropski
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Randi von Wrede
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
| | - Klaus Lehnertz
- Department of Epileptology, University of Bonn Medical Centre, Bonn, Germany
- Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Bonn, Germany
- Interdisciplinary Center for Complex Systems, University of Bonn, Bonn, Germany
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Xu G, Huo C, Yin J, Zhong Y, Sun G, Fan Y, Wang D, Li Z. Test-retest reliability of fNIRS in resting-state cortical activity and brain network assessment in stroke patients. BIOMEDICAL OPTICS EXPRESS 2023; 14:4217-4236. [PMID: 37799694 PMCID: PMC10549743 DOI: 10.1364/boe.491610] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 06/24/2023] [Accepted: 07/05/2023] [Indexed: 10/07/2023]
Abstract
Resting-state functional near infrared spectroscopy (fNIRS) scanning has attracted considerable attention in stroke rehabilitation research in recent years. The aim of this study was to quantify the reliability of fNIRS in cortical activity intensity and brain network metrics among resting-state stroke patients, and to comprehensively evaluate the effects of frequency selection, scanning duration, analysis and preprocessing strategies on test-retest reliability. Nineteen patients with stroke underwent two resting fNIRS scanning sessions with an interval of 24 hours. The haemoglobin signals were preprocessed by principal component analysis, common average reference and haemodynamic modality separation (HMS) algorithm respectively. The cortical activity, functional connectivity level, local network metrics (degree, betweenness and local efficiency) and global network metrics were calculated at 25 frequency scales × 16 time windows. The test-retest reliability of each fNIRS metric was quantified by the intraclass correlation coefficient. The results show that (1) the high-frequency band has higher ICC values than the low-frequency band, and the fNIRS metric is more reliable than at the individual channel level when averaged within the brain region channel, (2) the ICC values of the low-frequency band above the 4-minute scan time are generally higher than 0.5, the local efficiency and global network metrics reach high and excellent reliability levels after 4 min (0.5 < ICC < 0.9), with moderate or even poor reliability for degree and betweenness (ICC < 0.5), (3) HMS algorithm performs best in improving the low-frequency band ICC values. The results indicate that a scanning duration of more than 4 minutes can lead to high reliability of most fNIRS metrics when assessing low-frequency resting brain function in stroke patients. It is recommended to use the global correction method of HMS, and the reporting of degree, betweenness and single channel level should be performed with caution. This paper provides the first comprehensive reference for resting-state experimental design and analysis strategies for fNIRS in stroke rehabilitation.
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Affiliation(s)
- Gongcheng Xu
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
| | - Congcong Huo
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Jiahui Yin
- School of Athletic Performance, Shanghai University of Sport, Shanghai, China
| | - Yanbiao Zhong
- Department of Rehabilitation Medicine, First Affiliated Hospital of Gannan Medical University, Ganzhou, China
| | - Guoyu Sun
- Changsha Medical University, Changsha, China
| | - Yubo Fan
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
- School of Engineering Medicine, Beihang University, Beijing, China
| | - Daifa Wang
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Zengyong Li
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids, Beijing, China
- Key Laboratory of Neuro-functional Information and Rehabilitation Engineering of the Ministry of Civil Affairs, Beijing, China
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Jia G, Hubbard CS, Hu Z, Xu J, Dong Q, Niu H, Liu H. Intrinsic brain activity is increasingly complex and develops asymmetrically during childhood and early adolescence. Neuroimage 2023:120225. [PMID: 37336421 DOI: 10.1016/j.neuroimage.2023.120225] [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: 04/11/2023] [Revised: 05/18/2023] [Accepted: 06/11/2023] [Indexed: 06/21/2023] Open
Abstract
A large body of evidence suggests that brain signal complexity (BSC) may be an important indicator of healthy brain functioning or alternately, a harbinger of disease and dysfunction. However, despite recent progress our current understanding of how BSC emerges and evolves in large-scale networks, and the factors that shape these dynamics, remains limited. Here, we utilized resting-state functional near-infrared spectroscopy (rs-fNIRS) to capture and characterize the nature and time course of BSC dynamics within large-scale functional networks in 107 healthy participants ranging from 6-13 years of age. Age-dependent increases in spontaneous BSC were observed predominantly in higher-order association areas including the default mode (DMN) and attentional (ATN) networks. Our results also revealed asymmetrical developmental patterns in BSC that were specific to the dorsal and ventral ATN networks, with the former showing a left-lateralized and the latter demonstrating a right-lateralized increase in BSC. These age-dependent laterality shifts appeared to be more pronounced in females compared to males. Lastly, using a machine-learning model, we showed that BSC is a reliable predictor of chronological age. Higher-order association networks such as the DMN and dorsal ATN demonstrated the most robust prognostic power for predicting ages of previously unseen individuals. Taken together, our findings offer new insights into the spatiotemporal patterns of BSC dynamics in large-scale intrinsic networks that evolve over the course of childhood and adolescence, suggesting that a network-based measure of BSC represents a promising approach for tracking normative brain development and may potentially aid in the early detection of atypical developmental trajectories.
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Affiliation(s)
- Gaoding Jia
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
| | - Catherine S Hubbard
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Zhenyan Hu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China
| | - Jingping Xu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, 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
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, 100875 China.
| | - Hesheng Liu
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
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Iester C, Biggio M, Cutini S, Brigadoi S, Papaxanthis C, Brichetto G, Bove M, Bonzano L. Time-of-day influences resting-state functional cortical connectivity. Front Neurosci 2023; 17:1192674. [PMID: 37325041 PMCID: PMC10264597 DOI: 10.3389/fnins.2023.1192674] [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: 03/23/2023] [Accepted: 05/12/2023] [Indexed: 06/17/2023] Open
Abstract
Time-of-day is rarely considered during experimental protocols investigating motor behavior and neural activity. The goal of this work was to investigate differences in functional cortical connectivity at rest linked to the time of the day using functional Near-Infrared Spectroscopy (fNIRS). Since resting-state brain is shown to be a succession of cognitive, emotional, perceptual, and motor processes that can be both conscious and nonconscious, we studied self-generated thought with the goal to help in understanding brain dynamics. We used the New-York Cognition Questionnaire (NYC-Q) for retrospective introspection to explore a possible relationship between the ongoing experience and the brain at resting-state to gather information about the overall ongoing experience of subjects. We found differences in resting-state functional connectivity in the inter-hemispheric parietal cortices, which was significantly greater in the morning than in the afternoon, whilst the intra-hemispheric fronto-parietal functional connectivity was significantly greater in the afternoon than in the morning. When we administered the NYC-Q we found that the score of the question 27 ("during RS acquisition my thoughts were like a television program or film") was significantly greater in the afternoon with respect to the morning. High scores in question 27 point to a form of thought based on imagery. It is conceivable to think that the unique relationship found between NYC-Q question 27 and the fronto-parietal functional connectivity might be related to a mental imagery process during resting-state in the afternoon.
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Affiliation(s)
- Costanza Iester
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Monica Biggio
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Genoa, Italy
| | - Simone Cutini
- Department of Developmental and Social Psychology, University of Padova, Padua, Italy
| | - Sabrina Brigadoi
- Department of Developmental and Social Psychology, University of Padova, Padua, Italy
| | - Charalambos Papaxanthis
- INSERM UMR1093-CAPS, Université Bourgogne Franche-Comté, UFR des Sciences du Sport, Dijon, France
| | - Giampaolo Brichetto
- Italian Multiple Sclerosis Foundation, Scientific Research Area, Genoa, Italy
| | - Marco Bove
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Laura Bonzano
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
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Novi SL, Carvalho AC, Forti RM, Cendes F, Yasuda CL, Mesquita RC. Revealing the spatiotemporal requirements for accurate subject identification with resting-state functional connectivity: a simultaneous fNIRS-fMRI study. NEUROPHOTONICS 2023; 10:013510. [PMID: 36756003 PMCID: PMC9896013 DOI: 10.1117/1.nph.10.1.013510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 01/10/2023] [Indexed: 06/18/2023]
Abstract
SIGNIFICANCE Brain fingerprinting refers to identifying participants based on their functional patterns. Despite its success with functional magnetic resonance imaging (fMRI), brain fingerprinting with functional near-infrared spectroscopy (fNIRS) still lacks adequate validation. AIM We investigated how fNIRS-specific acquisition features (limited spatial information and nonneural contributions) influence resting-state functional connectivity (rsFC) patterns at the intra-subject level and, therefore, brain fingerprinting. APPROACH We performed multiple simultaneous fNIRS and fMRI measurements in 29 healthy participants at rest. Data were preprocessed following the best practices, including the removal of motion artifacts and global physiology. The rsFC maps were extracted with the Pearson correlation coefficient. Brain fingerprinting was tested with pairwise metrics and a simple linear classifier. RESULTS Our results show that average classification accuracy with fNIRS ranges from 75% to 98%, depending on the number of runs and brain regions used for classification. Under the right conditions, brain fingerprinting with fNIRS is close to the 99.9% accuracy found with fMRI. Overall, the classification accuracy is more impacted by the number of runs and the spatial coverage than the choice of the classification algorithm. CONCLUSIONS This work provides evidence that brain fingerprinting with fNIRS is robust and reliable for extracting unique individual features at the intra-subject level once relevant spatiotemporal constraints are correctly employed.
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Affiliation(s)
- Sergio L. Novi
- University of Campinas, “Gleb Wataghin” Institute of Physics, Campinas, Brazil
- Western University, Department of Physiology and Pharmacology, London, Ontario, Canada
| | - Alex C. Carvalho
- University of Campinas, “Gleb Wataghin” Institute of Physics, Campinas, Brazil
- University of Campinas, Laboratory of Neuroimaging, Campinas, Brazil
| | - R. M. Forti
- University of Campinas, “Gleb Wataghin” Institute of Physics, Campinas, Brazil
- The Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
| | - Fernado Cendes
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
- University of Campinas, School of Medical Sciences, Department of Neurology, Campinas, Brazil
| | - Clarissa L. Yasuda
- University of Campinas, Laboratory of Neuroimaging, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
- University of Campinas, School of Medical Sciences, Department of Neurology, Campinas, Brazil
| | - Rickson C. Mesquita
- University of Campinas, “Gleb Wataghin” Institute of Physics, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
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Talesh Jafadideh A, Mohammadzadeh Asl B. Structural filtering of functional data offered discriminative features for autism spectrum disorder. PLoS One 2022; 17:e0277989. [PMID: 36472989 PMCID: PMC9725140 DOI: 10.1371/journal.pone.0277989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 11/07/2022] [Indexed: 12/12/2022] Open
Abstract
This study attempted to answer the question, "Can filtering the functional data through the frequency bands of the structural graph provide data with valuable features which are not valuable in unfiltered data"?. The valuable features discriminate between autism spectrum disorder (ASD) and typically control (TC) groups. The resting-state fMRI data was passed through the structural graph's low, middle, and high-frequency band (LFB, MFB, and HFB) filters to answer the posed question. The structural graph was computed using the diffusion tensor imaging data. Then, the global metrics of functional graphs and metrics of functional triadic interactions were computed for filtered and unfiltered rfMRI data. Compared to TCs, ASDs had significantly higher clustering coefficients in the MFB, higher efficiencies and strengths in the MFB and HFB, and lower small-world propensity in the HFB. These results show over-connectivity, more global integration, and decreased local specialization in ASDs compared to TCs. Triadic analysis showed that the numbers of unbalanced triads were significantly lower for ASDs in the MFB. This finding may indicate the reason for restricted and repetitive behavior in ASDs. Also, in the MFB and HFB, the numbers of balanced triads and the energies of triadic interactions were significantly higher and lower for ASDs, respectively. These findings may reflect the disruption of the optimum balance between functional integration and specialization. There was no significant difference between ASDs and TCs when using the unfiltered data. All of these results demonstrated that significant differences between ASDs and TCs existed in the MFB and HFB of the structural graph when analyzing the global metrics of the functional graph and triadic interaction metrics. Also, these results demonstrated that frequency bands of the structural graph could offer significant findings which were not found in the unfiltered data. In conclusion, the results demonstrated the promising perspective of using structural graph frequency bands for attaining discriminative features and new knowledge, especially in the case of ASD.
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Xu Y, Wang Y, Hu N, Yang L, Yu Z, Han L, Xu Q, Zhou J, Chen J, Mao H, Pan Y. Intrinsic Organization of Occipital Hubs Predicts Depression: A Resting-State fNIRS Study. Brain Sci 2022; 12:brainsci12111562. [PMID: 36421888 PMCID: PMC9688420 DOI: 10.3390/brainsci12111562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 11/11/2022] [Accepted: 11/15/2022] [Indexed: 11/19/2022] Open
Abstract
Dysfunctional brain networks have been found in patients with major depressive disorder (MDD). In this study, to verify this in a more straightforward way, we investigated the intrinsic organization of brain networks in MDD by leveraging the resting-state functional near-infrared spectroscopy (rs-fNIRS). Thirty-four MDD patients (24 females, 38.41 ± 13.14 years old) and thirty healthy controls (22 females, 34.43 ± 5.03 years old) underwent a 10 min rest while their brain activity was recorded via fNIRS. The results showed that MDD patients and healthy controls exhibited similar resting-state functional connectivity. Moreover, the depression group showed lower small-world Lambda (1.12 ± 0.04 vs. 1.16 ± 0.10, p = 0.04) but higher global efficiency (0.51 ± 0.03 vs. 0.48 ± 0.05, p = 0.03) than the control group. Importantly, MDD patients, as opposed to healthy controls, showed a significantly lower nodal local efficiency at the left middle occipital gyrus (0.56 ± 0.36 vs. 0.81 ± 0.20, pFDR < 0.05), which predicted the level of depression in MDD (r = 0.45, p = 0.01, R2 = 0.15). In sum, we found a more integrated brain network in MDD patients with a lower nodal local efficiency at the occipital hub, which could predict depressive symptoms.
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Affiliation(s)
- You Xu
- Department of Sleep Medicine, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Tianmushan Road 305, Hangzhou 310013, China
| | - Yajie Wang
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
| | - Nannan Hu
- Department of Psychiatry, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China
| | - Lili Yang
- Department of Sleep Medicine, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Tianmushan Road 305, Hangzhou 310013, China
| | - Zhenghe Yu
- Department of Sleep Medicine, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Tianmushan Road 305, Hangzhou 310013, China
| | - Li Han
- Department of Sleep Medicine, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Tianmushan Road 305, Hangzhou 310013, China
| | - Qianqian Xu
- Department of Sleep Medicine, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Tianmushan Road 305, Hangzhou 310013, China
| | - Jingjing Zhou
- Department of Sleep Medicine, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Tianmushan Road 305, Hangzhou 310013, China
| | - Ji Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
| | - Hongjing Mao
- Department of Sleep Medicine, Affiliated Mental Health Center & Hangzhou Seventh People’s Hospital, Zhejiang University School of Medicine, Tianmushan Road 305, Hangzhou 310013, China
- Correspondence: (H.M.); (Y.P.)
| | - Yafeng Pan
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310058, China
- Correspondence: (H.M.); (Y.P.)
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12
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Eng CM, Pocsai M, Fulton VE, Moron SP, Thiessen ED, Fisher AV. Longitudinal investigation of executive function development employing task-based, teacher reports, and fNIRS multimethodology in 4- to 5-year-old children. Dev Sci 2022; 25:e13328. [PMID: 36221252 PMCID: PMC10408588 DOI: 10.1111/desc.13328] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 09/07/2022] [Accepted: 09/12/2022] [Indexed: 01/13/2023]
Abstract
Increased focus on resting-state functional connectivity (rsFC) and the use and accessibility of functional near-infrared spectroscopy (fNIRS) have advanced knowledge on the interconnected nature of neural substrates underlying executive function (EF) development in adults and clinical populations. Less is known about the relationship between rsFC and developmental changes in EF during preschool years in typically developing children, a gap the present study addresses employing task-based assessment, teacher reports, and fNIRS multimethodology. This preregistered study contributes to our understanding of the neural basis of EF development longitudinally with 41 children ages 4-5. Changes in prefrontal cortex (PFC) rsFC utilizing fNIRS, EF measured with a common task-based assessment (Day-Night task), and teacher reports of behavior (BRIEF-P) were monitored over multiple timepoints: Initial Assessment, 72 h follow-up, 1 Month Follow-up, and 4 Month Follow-up. Measures of rsFC were strongly correlated 72 h apart, providing evidence of high rsFC measurement reliability using fNIRS with preschool-aged children. PFC rsFC was positively correlated with performance on task-based and report-based EF assessments. Children's PFC functional connectivity at rest uniquely predicted later EF, controlling for verbal IQ, age, and sex. Functional connectivity at rest using fNIRS may potentially show the rapid changes in EF development in young children, not only neurophysiologically, but also as a correlate of task-based EF performance and ecologically-relevant teacher reports of EF in a classroom context.
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Affiliation(s)
- Cassondra M Eng
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, California, USA
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Melissa Pocsai
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
- Department of Psychology, City University of New York, New York, New York, USA
| | - Virginia E Fulton
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Suanna P Moron
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
- Graduate School of Education, Stanford University, Stanford, California, USA
| | - Erik D Thiessen
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
| | - Anna V Fisher
- Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
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Uchitel J, Blanco B, Vidal-Rosas E, Collins-Jones L, Cooper RJ. Reliability and similarity of resting state functional connectivity networks imaged using wearable, high-density diffuse optical tomography in the home setting. Neuroimage 2022; 263:119663. [PMID: 36202159 DOI: 10.1016/j.neuroimage.2022.119663] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 09/28/2022] [Accepted: 10/02/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND When characterizing the brain's resting state functional connectivity (RSFC) networks, demonstrating networks' similarity across sessions and reliability across different scan durations is essential for validating results and possibly minimizing the scanning time needed to obtain stable measures of RSFC. Recent advances in optical functional neuroimaging technologies have resulted in fully wearable devices that may serve as a complimentary tool to functional magnetic resonance imaging (fMRI) and allow for investigations of RSFC networks repeatedly and easily in non-traditional scanning environments. METHODS Resting-state cortical hemodynamic activity was repeatedly measured in a single individual in the home environment during COVID-19 lockdown conditions using the first ever application of a 24-module (72 sources, 96 detectors) wearable high-density diffuse optical tomography (HD-DOT) system. Twelve-minute recordings of resting-state data were acquired over the pre-frontal and occipital regions in fourteen experimental sessions over three weeks. As an initial validation of the data, spatial independent component analysis was used to identify RSFC networks. Reliability and similarity scores were computed using metrics adapted from the fMRI literature. RESULTS We observed RSFC networks over visual regions (visual peripheral, visual central networks) and higher-order association regions (control, salience and default mode network), consistent with previous fMRI literature. High similarity was observed across testing sessions and across chromophores (oxygenated and deoxygenated haemoglobin, HbO and HbR) for all functional networks, and for each network considered separately. Stable reliability values (described here as a <10% change between time windows) were obtained for HbO and HbR with differences in required scanning time observed on a network-by-network basis. DISCUSSION Using RSFC data from a highly sampled individual, the present work demonstrates that wearable HD-DOT can be used to obtain RSFC measurements with high similarity across imaging sessions and reliability across recording durations in the home environment. Wearable HD-DOT may serve as a complimentary tool to fMRI for studying RSFC networks outside of the traditional scanning environment and in vulnerable populations for whom fMRI is not feasible.
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Affiliation(s)
- Julie Uchitel
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom
| | - Borja Blanco
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom; Department of Psychology, University of Cambridge, Cambridge, United Kingdom.
| | - Ernesto Vidal-Rosas
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom
| | - Liam Collins-Jones
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom
| | - Robert J Cooper
- DOT-HUB, Department of Medical Physics and Biomedical Engineering, UCL, London, United Kingdom
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14
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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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15
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Systematic Bibliometric and Visualized Analysis of Research Hotspots and Trends on Autism Spectrum Disorder Neuroimaging. DISEASE MARKERS 2022; 2022:3372217. [PMID: 35899177 PMCID: PMC9313970 DOI: 10.1155/2022/3372217] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 06/26/2022] [Accepted: 06/30/2022] [Indexed: 11/17/2022]
Abstract
Background Autism spectrum disorder (ASD) is a chronic developmental disability caused by differences in the brain. The gold standard for the diagnosis of this condition is based on behavioral science, but research on the application of neurological detection to diagnose the atypical nervous system of ASD is ongoing. ASD neuroimaging research involves the examination of the brain's structure, functional connections, and neurometabolic. However, limited medical resource and the unique heterogeneity of ASD have resulted in many challenges when neuroimaging is utilized. Objective This bibliometric study is aimed at summarizing themes and trends in research on autism spectrum disorder neuroimaging and at proposing potential directions for future inquiry. Methods Citations were downloaded from the Web of Science Core Collection database on neuroimaging published from January 1, 2012, to December 31, 2021. The retrieved information was analyzed using Bibliometric.com, CiteSpace.5.8. R3, and VOS viewer. Results A total of 1,363 papers were published across 58 regions. The United States was the leading source of publications. The League of European Research Universities published the largest number of articles (171). Burst keywords from 2018 to 2021 include identification and network. The clusters of references that continued into 2020 included graph theory, functional connectivity, and classification, which represent key research topics. Conclusions Imaging data is being used to identify neuro-network models with higher accuracy for ASD discrimination. Functional near-infrared imaging is advantageous compared to other neuroimaging. In the future, research on systematic and accurate computer-aided diagnosis technology should be encouraged. Moreover, the study of neuroimaging of ASD in different psychological and behavioral states can inspire new ideas about the diagnosis and intervention training of ASD and should be explored.
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Liu G, Huo E, Liu H, Jia G, Zhi Y, Dong Q, Niu H. Development and emergence of functional network asymmetry in 3- to 9-month-old infants. Cortex 2022; 154:390-404. [DOI: 10.1016/j.cortex.2022.06.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 05/09/2022] [Accepted: 06/30/2022] [Indexed: 11/03/2022]
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17
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Lanka P, Bortfeld H, Huppert TJ. Correction of global physiology in resting-state functional near-infrared spectroscopy. NEUROPHOTONICS 2022; 9:035003. [PMID: 35990173 PMCID: PMC9386281 DOI: 10.1117/1.nph.9.3.035003] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 07/08/2022] [Indexed: 05/30/2023]
Abstract
Significance: Resting-state functional connectivity (RSFC) analyses of functional near-infrared spectroscopy (fNIRS) data reveal cortical connections and networks across the brain. Motion artifacts and systemic physiology in evoked fNIRS signals present unique analytical challenges, and methods that control for systemic physiological noise have been explored. Whether these same methods require modification when applied to resting-state fNIRS (RS-fNIRS) data remains unclear. Aim: We systematically examined the sensitivity and specificity of several RSFC analysis pipelines to identify the best methods for correcting global systemic physiological signals in RS-fNIRS data. Approach: Using numerically simulated RS-fNIRS data, we compared the rates of true and false positives for several connectivity analysis pipelines. Their performance was scored using receiver operating characteristic analysis. Pipelines included partial correlation and multivariate Granger causality, with and without short-separation measurements, and a modified multivariate causality model that included a non-traditional zeroth-lag cross term. We also examined the effects of pre-whitening and robust statistical estimators on performance. Results: Consistent with previous work on bivariate correlation models, our results demonstrate that robust statistics and pre-whitening are effective methods to correct for motion artifacts and autocorrelation in the fNIRS time series. Moreover, we found that pre-filtering using principal components extracted from short-separation fNIRS channels as part of a partial correlation model was most effective in reducing spurious correlations due to shared systemic physiology when the two signals of interest fluctuated synchronously. However, when there was a temporal lag between the signals, a multivariate Granger causality test incorporating the short-separation channels was better. Since it is unknown if such a lag exists in experimental data, we propose a modified version of Granger causality that includes the non-traditional zeroth-lag term as a compromising solution. Conclusions: A combination of pre-whitening, robust statistical methods, and partial correlation in the processing pipeline to reduce autocorrelation, motion artifacts, and global physiology are suggested for obtaining statistically valid connectivity metrics with RS-fNIRS. Further studies should validate the effectiveness of these methods using human data.
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Affiliation(s)
- Pradyumna Lanka
- University of California, Merced, Department of Psychological Sciences, Merced, California, United States
| | - Heather Bortfeld
- University of California, Merced, Department of Psychological Sciences, Merced, California, United States
- University of California, Merced, Department of Cognitive and Information Sciences, Merced, California, United States
| | - Theodore J. Huppert
- University of Pittsburgh, Department of Electrical and Computer Engineering, Pittsburgh, Pennsylvania, United States
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18
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Truong NCD, Wang X, Wanniarachchi H, Liu H. Enhancement of Frequency-Specific Hemodynamic Power and Functional Connectivity by Transcranial Photobiomodulation in Healthy Humans. Front Neurosci 2022; 16:896502. [PMID: 35757526 PMCID: PMC9226485 DOI: 10.3389/fnins.2022.896502] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/09/2022] [Indexed: 12/03/2022] Open
Abstract
Transcranial photobiomodulation (tPBM) has been considered a safe and effective brain stimulation modality being able to enhance cerebral oxygenation and neurocognitive function. To better understand the underlying neurophysiological effects of tPBM in the human brain, we utilized a 111-channel functional near infrared spectroscopy (fNIRS) system to map cerebral hemodynamic responses over the whole head to 8-min tPBM with 1,064-nm laser given on the forehead of 19 healthy participants. Instead of analyzing broad-frequency hemodynamic signals (0–0.2 Hz), we investigated frequency-specific effects of tPBM on three infra-slow oscillation (ISO) components consisting of endogenic, neurogenic, and myogenic vasomotions. Significant changes induced by tPBM in spectral power of oxygenated hemoglobin concentration (Δ[HbO]), functional connectivity (FC), and global network metrics at each of the three ISO frequency bands were identified and mapped topographically for frequency-specific comparisons. Our novel findings revealed that tPBM significantly increased endogenic Δ[HbO] powers over the right frontopolar area near the stimulation site. Also, we demonstrated that tPBM enabled significant enhancements of endogenic and myogenic FC across cortical regions as well as of several global network metrics. These findings were consistent with recent reports and met the expectation that myogenic oscillation is highly associated with endothelial activity, which is stimulated by tPBM-evoked nitric oxide (NO) release.
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Affiliation(s)
- Nghi Cong Dung Truong
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
| | - Xinlong Wang
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
| | - Hashini Wanniarachchi
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
| | - Hanli Liu
- Department of Bioengineering, University of Texas at Arlington, Arlington, TX, United States
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19
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Krendl AC, Betzel RF. Social cognitive network neuroscience. Soc Cogn Affect Neurosci 2022; 17:510-529. [PMID: 35352125 PMCID: PMC9071476 DOI: 10.1093/scan/nsac020] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 01/27/2022] [Accepted: 03/10/2022] [Indexed: 12/31/2022] Open
Abstract
Over the past three decades, research from the field of social neuroscience has identified a constellation of brain regions that relate to social cognition. Although these studies have provided important insights into the specific neural regions underlying social behavior, they may overlook the broader neural context in which those regions and the interactions between them are embedded. Network neuroscience is an emerging discipline that focuses on modeling and analyzing brain networks-collections of interacting neural elements. Because human cognition requires integrating information across multiple brain regions and systems, we argue that a novel social cognitive network neuroscience approach-which leverages methods from the field of network neuroscience and graph theory-can advance our understanding of how brain systems give rise to social behavior. This review provides an overview of the field of network neuroscience, discusses studies that have leveraged this approach to advance social neuroscience research, highlights the potential contributions of social cognitive network neuroscience to understanding social behavior and provides suggested tools and resources for conducting network neuroscience research.
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Affiliation(s)
- Anne C Krendl
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN 47405, USA
| | - Richard F Betzel
- Department of Psychological & Brain Sciences, Indiana University, Bloomington, IN 47405, USA
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Abdalmalak A, Novi SL, Kazazian K, Norton L, Benaglia T, Slessarev M, Debicki DB, Lawrence KS, Mesquita RC, Owen AM. Effects of Systemic Physiology on Mapping Resting-State Networks Using Functional Near-Infrared Spectroscopy. Front Neurosci 2022; 16:803297. [PMID: 35350556 PMCID: PMC8957952 DOI: 10.3389/fnins.2022.803297] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 02/07/2022] [Indexed: 12/11/2022] Open
Abstract
Resting-state functional connectivity (rsFC) has gained popularity mainly due to its simplicity and potential for providing insights into various brain disorders. In this vein, functional near-infrared spectroscopy (fNIRS) is an attractive choice due to its portability, flexibility, and low cost, allowing for bedside imaging of brain function. While promising, fNIRS suffers from non-neural signal contaminations (i.e., systemic physiological noise), which can increase correlation across fNIRS channels, leading to spurious rsFC networks. In the present work, we hypothesized that additional measurements with short channels, heart rate, mean arterial pressure, and end-tidal CO2 could provide a better understanding of the effects of systemic physiology on fNIRS-based resting-state networks. To test our hypothesis, we acquired 12 min of resting-state data from 10 healthy participants. Unlike previous studies, we investigated the efficacy of different pre-processing approaches in extracting resting-state networks. Our results are in agreement with previous studies and reinforce the fact that systemic physiology can overestimate rsFC. We expanded on previous work by showing that removal of systemic physiology decreases intra- and inter-subject variability, increasing the ability to detect neural changes in rsFC across groups and over longitudinal studies. Our results show that by removing systemic physiology, fNIRS can reproduce resting-state networks often reported with functional magnetic resonance imaging (fMRI). Finally, the present work details the effects of systemic physiology and outlines how to remove (or at least ameliorate) their contributions to fNIRS signals acquired at rest.
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Affiliation(s)
- Androu Abdalmalak
- Department of Physiology and Pharmacology, Western University, London, ON, Canada
- Brain and Mind Institute, Western University, London, ON, Canada
- *Correspondence: Androu Abdalmalak,
| | - Sergio L. Novi
- “Gleb Wataghin” Institute of Physics, University of Campinas, Campinas, Brazil
- *Correspondence: Androu Abdalmalak,
| | - Karnig Kazazian
- Brain and Mind Institute, Western University, London, ON, Canada
| | - Loretta Norton
- Department of Psychology, King’s University College at Western University, London, ON, Canada
| | - Tatiana Benaglia
- Institute of Mathematics, Statistics and Scientific Computing, University of Campinas, Campinas, Brazil
| | - Marat Slessarev
- Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Derek B. Debicki
- Brain and Mind Institute, Western University, London, ON, Canada
- Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Keith St. Lawrence
- Department of Medical Biophysics, Western University, London, ON, Canada
| | - Rickson C. Mesquita
- “Gleb Wataghin” Institute of Physics, University of Campinas, Campinas, Brazil
| | - Adrian M. Owen
- Department of Physiology and Pharmacology, Western University, London, ON, Canada
- Brain and Mind Institute, Western University, London, ON, Canada
- Department of Psychology, Western University, London, ON, Canada
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21
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Tian F, Li H, Tian S, Tian C, Shao J. Is There a Difference in Brain Functional Connectivity between Chinese Coal Mine Workers Who Have Engaged in Unsafe Behavior and Those Who Have Not? INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19010509. [PMID: 35010769 PMCID: PMC8744879 DOI: 10.3390/ijerph19010509] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Revised: 12/27/2021] [Accepted: 12/27/2021] [Indexed: 12/31/2022]
Abstract
(1) Background: As a world-recognized high-risk occupation, coal mine workers need various cognitive functions to process the surrounding information to cope with a large number of perceived hazards or risks. Therefore, it is necessary to explore the connection between coal mine workers’ neural activity and unsafe behavior from the perspective of cognitive neuroscience. This study explored the functional brain connectivity of coal mine workers who have engaged in unsafe behaviors (EUB) and those who have not (NUB). (2) Methods: Based on functional near-infrared spectroscopy (fNIRS), a total of 106 workers from the Hongliulin coal mine of Shaanxi North Mining Group, one of the largest modern coal mines in China, completed the test. Pearson’s Correlation Coefficient (COR) analysis, brain network analysis, and two-sample t-test were used to investigate the difference in brain functional connectivity between the two groups. (3) Results: The results showed that there were significant differences in functional brain connectivity between EUB and NUB among the frontopolar area (p = 0.002325), orbitofrontal area (p = 0.02102), and pars triangularis Broca’s area (p = 0.02888). Small-world properties existed in the brain networks of both groups, and the dorsolateral prefrontal cortex had significant differences in clustering coefficient (p = 0.0004), nodal efficiency (p = 0.0384), and nodal local efficiency (p = 0.0004). (4) Conclusions: This study is the first application of fNIRS to the field of coal mine safety. The fNIRS brain functional connectivity analysis is a feasible method to investigate the neuropsychological mechanism of unsafe behavior in coal mine workers in the view of brain science.
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Affiliation(s)
- Fangyuan Tian
- Institute of Safety Management & Risk Control, Institute of Safety & Emergency Management, School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China; (F.T.); (S.T.); (C.T.)
| | - Hongxia Li
- Institute of Safety Management & Risk Control, Institute of Safety & Emergency Management, School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China; (F.T.); (S.T.); (C.T.)
- School of Management, Xi’an University of Science and Technology, Xi’an 710054, China
- Correspondence: ; Tel.: +86-152-9159-9962
| | - Shuicheng Tian
- Institute of Safety Management & Risk Control, Institute of Safety & Emergency Management, School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China; (F.T.); (S.T.); (C.T.)
| | - Chenning Tian
- Institute of Safety Management & Risk Control, Institute of Safety & Emergency Management, School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an 710054, China; (F.T.); (S.T.); (C.T.)
| | - Jiang Shao
- School of Architecture & Design, China University of Mining and Technology, Xuzhou 221116, China;
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22
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Wyser DG, Kanzler CM, Salzmann L, Lambercy O, Wolf M, Scholkmann F, Gassert R. Characterizing reproducibility of cerebral hemodynamic responses when applying short-channel regression in functional near-infrared spectroscopy. NEUROPHOTONICS 2022; 9:015004. [PMID: 35265732 PMCID: PMC8901194 DOI: 10.1117/1.nph.9.1.015004] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 02/11/2022] [Indexed: 05/06/2023]
Abstract
Significance: Functional near-infrared spectroscopy (fNIRS) enables the measurement of brain activity noninvasively. Optical neuroimaging with fNIRS has been shown to be reproducible on the group level and hence is an excellent research tool, but the reproducibility on the single-subject level is still insufficient, challenging the use for clinical applications. Aim: We investigated the effect of short-channel regression (SCR) as an approach to obtain fNIRS measurements with higher reproducibility on a single-subject level. SCR simultaneously considers contributions from long- and short-separation channels and removes confounding physiological changes through the regression of the short-separation channel information. Approach: We performed a test-retest study with a hand grasping task in 15 healthy subjects using a wearable fNIRS device, optoHIVE. Relevant brain regions were localized with transcranial magnetic stimulation to ensure correct placement of the optodes. Reproducibility was assessed by intraclass correlation, correlation analysis, mixed effects modeling, and classification accuracy of the hand grasping task. Further, we characterized the influence of SCR on reproducibility. Results: We found a high reproducibility of fNIRS measurements on a single-subject level ( ICC single = 0.81 and correlation r = 0.81 ). SCR increased the reproducibility from 0.64 to 0.81 ( ICC single ) but did not affect classification (85% overall accuracy). Significant intersubject variability in the reproducibility was observed and was explained by Mayer wave oscillations and low raw signal strength. The raw signal-to-noise ratio (threshold at 40 dB) allowed for distinguishing between persons with weak and strong activations. Conclusions: We report, for the first time, that fNIRS measurements are reproducible on a single-subject level using our optoHIVE fNIRS system and that SCR improves reproducibility. In addition, we give a benchmark to easily assess the ability of a subject to elicit sufficiently strong hemodynamic responses. With these insights, we pave the way for the reliable use of fNIRS neuroimaging in single subjects for neuroscientific research and clinical applications.
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Affiliation(s)
- Dominik G. Wyser
- ETH Zurich, Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Zurich, Switzerland
- University Hospital Zurich, University of Zurich, Biomedical Optics Research Laboratory, Department of Neonatology, Zurich, Switzerland
- Address all correspondence to Dominik G. Wyser,
| | - Christoph M. Kanzler
- ETH Zurich, Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Zurich, Switzerland
| | - Lena Salzmann
- ETH Zurich, Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Zurich, Switzerland
| | - Olivier Lambercy
- ETH Zurich, Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Zurich, Switzerland
| | - Martin Wolf
- University Hospital Zurich, University of Zurich, Biomedical Optics Research Laboratory, Department of Neonatology, Zurich, Switzerland
| | - Felix Scholkmann
- University Hospital Zurich, University of Zurich, Biomedical Optics Research Laboratory, Department of Neonatology, Zurich, Switzerland
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Roger Gassert
- ETH Zurich, Rehabilitation Engineering Laboratory, Department of Health Sciences and Technology, Zurich, Switzerland
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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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Si X, Xiang S, Zhang L, Li S, Zhang K, Ming D. Acupuncture With deqi Modulates the Hemodynamic Response and Functional Connectivity of the Prefrontal-Motor Cortical Network. Front Neurosci 2021; 15:693623. [PMID: 34483822 PMCID: PMC8415569 DOI: 10.3389/fnins.2021.693623] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Accepted: 06/07/2021] [Indexed: 11/25/2022] Open
Abstract
As a world intangible cultural heritage, acupuncture is considered an essential modality of complementary and alternative therapy to Western medicine. Despite acupuncture’s long history and public acceptance, how the cortical network is modulated by acupuncture remains largely unclear. Moreover, as the basic acupuncture unit for regulating the central nervous system, how the cortical network is modulated during acupuncture at the Hegu acupoint is mostly unclear. Here, multi-channel functional near-infrared spectroscopy (fNIRS) data were recorded from twenty healthy subjects for acupuncture manipulation, pre- and post-manipulation tactile controls, and pre- and post-acupuncture rest controls. Results showed that: (1) acupuncture manipulation caused significantly increased acupuncture behavioral deqi performance compared with tactile controls. (2) The bilateral prefrontal cortex (PFC) and motor cortex were significantly inhibited during acupuncture manipulation than controls, which was evidenced by the decreased power of oxygenated hemoglobin (HbO) concentration. (3) The bilateral PFC’s hemodynamic responses showed a positive correlation trend with acupuncture behavioral performance. (4) The network connections with bilateral PFC as nodes showed significantly increased functional connectivity during acupuncture manipulation compared with controls. (5) Meanwhile, the network’s efficiency was improved by acupuncture manipulation, evidenced by the increased global efficiency and decreased shortest path length. Taken together, these results reveal that a cooperative PFC-Motor functional network could be modulated by acupuncture manipulation at the Hegu acupoint. This study provides neuroimaging evidence that explains acupuncture’s neuromodulation effects on the cortical network.
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Affiliation(s)
- Xiaopeng Si
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China.,Tianjin International Engineering Institute, Tianjin University, Tianjin, China.,Institute of Applied Psychology, Tianjin University, Tianjin, China
| | - Shaoxin Xiang
- Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China.,Tianjin International Engineering Institute, Tianjin University, Tianjin, China
| | - Ludan Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
| | - Sicheng Li
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
| | - Kuo Zhang
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
| | - Dong Ming
- Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.,Tianjin Key Laboratory of Brain Science and Neural Engineering, Tianjin University, Tianjin, China
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25
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Huo C, Xu G, Li W, Xie H, Zhang T, Liu Y, Li Z. A review on functional near-infrared spectroscopy and application in stroke rehabilitation. MEDICINE IN NOVEL TECHNOLOGY AND DEVICES 2021. [DOI: 10.1016/j.medntd.2021.100064] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022] Open
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26
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Zhang T, Huang W, Wu X, Sun W, Lin F, Sun H, Li J. Altered complexity in resting-state fNIRS signal in autism: a multiscale entropy approach. Physiol Meas 2021; 42. [PMID: 34315139 DOI: 10.1088/1361-6579/ac184d] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 07/27/2021] [Indexed: 11/12/2022]
Abstract
Objective.Feature extraction and recognition in brain signal processing is of great significance for understanding the neurological mechanism of autism spectrum disorder (ASD). Resting-state (RS) functional near-infrared spectroscopy measurement provides a way to investigate the possible alteration in ASD-related complexity of resting-state (RS) functional near-infrared spectroscopy (fNIRS) signals and to explore the relationship between brain functional connectivity and complexity.Approach.Using the multiscale entropy (MSE) of fNIRS signals recorded from the bilateral temporal lobes (TLs) on 25 children with ASD and 22 typical development (TD) children, the pattern of brain complexity was assessed for both the ASD and TD groups.Main results.The quantitative analysis of MSE revealed the increased complexity in RS-fNIRS in children with ASD, particularly in the left temporal lobe. The complexity in the RS signal and resting state functional connectivity (RSFC) were also observed to exhibit negative correlation in the medium magnitude.Significance.These results indicated that the MSE might serve as a novel measure for RS-fNIRS signals in characterizing and understanding ASD.
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Affiliation(s)
- Tingzhen Zhang
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, People's Republic of China
| | - Wen Huang
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, People's Republic of China
| | - Xiaoyin Wu
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, People's Republic of China
| | - Weiting Sun
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, People's Republic of China
| | - Fang Lin
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, People's Republic of China
| | - Huiwen Sun
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, People's Republic of China
| | - Jun Li
- South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou 510006, People's Republic of China.,Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou 510006, People's Republic of China
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27
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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: 14] [Impact Index Per Article: 4.7] [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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28
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Relationship Between Age and Cerebral Hemodynamic Response to Breath Holding: A Functional Near-Infrared Spectroscopy Study. Brain Topogr 2021; 34:154-166. [PMID: 33544290 DOI: 10.1007/s10548-021-00818-4] [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: 05/23/2020] [Accepted: 01/06/2021] [Indexed: 10/22/2022]
Abstract
Cerebrovascular reactivity (CVR) is routinely measured as a predictor of stroke in people with a high risk of ischemic attack. Neuroimaging techniques such as emission tomography, magnetic resonance imaging, and transcranial doppler are frequently used to measure CVR even though each technique has its limitations. Functional near-infrared spectroscopy (fNIRS), also based on the principle of neurovascular coupling, is relatively inexpensive, portable, and allows for the quantification of oxy- and deoxy-hemoglobin concentration changes at a high temporal resolution. This study examines the relationship between age and CVR using fNIRS in 45 young healthy adult participants aged 18-41 years (6 females, 26.64 ± 5.49 years) performing a simple breath holding task. Eighteen of the 45 participants were scanned again after a week to evaluate the feasibility of fNIRS in reliably measuring CVR. Results indicate (a) a negative relationship between age and hemodynamic measures of breath holding task in the sensorimotor cortex of 45 individuals and (b) widespread positive coactivation within medial sensorimotor regions and between medial sensorimotor regions with supplementary motor area and prefrontal cortex during breath holding with increasing age. The intraclass correlation coefficient (ICC) indicated only a low to fair/good reliability of the breath hold hemodynamic measures from sensorimotor and prefrontal cortices. However, the average hemodynamic response to breath holding from the two sessions were found to be temporally and spatially in correspondence. Future improvements in the sensitivity and reliability of fNIRS metrics could facilitate fNIRS-based assessment of cerebrovascular function as a potential clinical tool.
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29
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Cao W, Zhu H, Li Y, Wang Y, Bai W, Lao U, Zhang Y, Ji Y, He S, Zou X. The Development of Brain Network in Males with Autism Spectrum Disorders from Childhood to Adolescence: Evidence from fNIRS Study. Brain Sci 2021; 11:120. [PMID: 33477412 PMCID: PMC7830916 DOI: 10.3390/brainsci11010120] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 01/12/2021] [Accepted: 01/15/2021] [Indexed: 11/16/2022] Open
Abstract
In the current study, functional near-infrared spectroscopy (fNIRS) was used to collect resting-state signals from 77 males with autism spectrum disorders (ASD, age: 6~16.25) and 40 typically developing (TD) males (age: 6~16.58) in the theory-of-mind (ToM) network. The graph theory analysis was used to obtain the brain network properties in ToM network, and the multiple regression analysis demonstrated that males with ASD showed a comparable global network topology, and a similar age-related decrease in the medial prefrontal cortex area (mPFC) compared to TD individuals. Nevertheless, participants with ASD showed U-shaped trajectories of nodal metrics of right temporo-parietal junction (TPJ), and an age-related decrease in the left middle frontal gyrus (MFG), while trajectories of TD participants were opposite. The nodal metrics of the right TPJ was negatively associated with the social deficits of ASD, while the nodal metrics of the left MFG was negatively associated with the communication deficits of ASD. Current findings suggested a distinct developmental trajectory of the ToM network in males with ASD from childhood to adolescence.
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Affiliation(s)
- Wei Cao
- Centre for Optical and Electromagnetic Research, South China Academy of Advanced Optoelectronics, South China Normal University (SCNU), Guangzhou 510006, China;
| | - Huilin Zhu
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Yan Li
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Yu Wang
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Wuxia Bai
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Uchong Lao
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Yingying Zhang
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Yan Ji
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
| | - Sailing He
- Centre for Optical and Electromagnetic Research, South China Academy of Advanced Optoelectronics, South China Normal University (SCNU), Guangzhou 510006, China;
| | - Xiaobing Zou
- Child Development & Behavior Center, Third Affiliated Hospital of SUN YAT-SEN University, No.2693, Kaichuang revenue, Lingnan Campuses, Guangzhou 510080, China; (H.Z.); (Y.L.); (Y.W.); (W.B.); (U.L.); (Y.Z.); (Y.J.)
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30
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Yanagi M, Shirakawa O. Application of Near-Infrared Spectroscopy for Understanding Spontaneous Brain Activity During Resting State in Schizophrenia: A Mini Review. Front Psychiatry 2021; 12:704506. [PMID: 34475831 PMCID: PMC8407079 DOI: 10.3389/fpsyt.2021.704506] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 07/20/2021] [Indexed: 11/24/2022] Open
Abstract
Spontaneous brain activity occurs at rest, as represented by the default mode network. A resting paradigm is suitable for investigating brain function of patients with psychiatric diseases who may have difficulties adhering to goal-oriented tasks. Evidence accumulated in neuroimaging studies using functional magnetic resonance imaging has shown that the resting cerebral blood flow is impaired in psychiatric diseases. Near-infrared spectroscopy (NIRS), a simple neuroimaging modality, is an optimal tool for the resting paradigm, because it can offer a comfortable environment for measurement. Recent NIRS studies have demonstrated some promising data of altered resting activity in the prefrontal cortex of patients with schizophrenia, which may be exploited to develop further applications of NIRS in clinical psychiatry. Based on these findings, we emphasize the benefits of NIRS for assessing the prefrontal pathophysiology during the resting state and some methodological issues to be noted while analyzing cerebral blood flow using NIRS; moreover, we focus on interpreting these changes based on the complex nature of the spontaneous brain activity during resting state.
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Affiliation(s)
- Masaya Yanagi
- Department of Neuropsychiatry, Kindai University Faculty of Medicine, Osakasayama, Japan
| | - Osamu Shirakawa
- Department of Neuropsychiatry, Kindai University Faculty of Medicine, Osakasayama, Japan
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31
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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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32
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Bizzego A, Balagtas JPM, Esposito G. Commentary: Current Status and Issues Regarding Pre-processing of fNIRS Neuroimaging Data: An Investigation of Diverse Signal Filtering Methods Within a General Linear Model Framework. Front Hum Neurosci 2020; 14:247. [PMID: 32760261 PMCID: PMC7373176 DOI: 10.3389/fnhum.2020.00247] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Accepted: 06/03/2020] [Indexed: 01/28/2023] Open
Affiliation(s)
- Andrea Bizzego
- Department of Psychology and Cognitive Science, University of Trento, Trento, Italy
| | - Jan Paolo M Balagtas
- Psychology Program, School of Social Sciences, Nanyang Technological University, Singapore, Singapore
| | - Gianluca Esposito
- Department of Psychology and Cognitive Science, University of Trento, Trento, Italy.,Psychology Program, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.,Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
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33
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Novi SL, Forero EJ, Rubianes Silva JAI, de Souza NGSR, Martins GG, Quiroga A, Wu ST, Mesquita RC. Integration of Spatial Information Increases Reproducibility in Functional Near-Infrared Spectroscopy. Front Neurosci 2020; 14:746. [PMID: 32848543 PMCID: PMC7399018 DOI: 10.3389/fnins.2020.00746] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2020] [Accepted: 06/24/2020] [Indexed: 11/13/2022] Open
Abstract
As functional near-infrared spectroscopy (fNIRS) is developed as a neuroimaging technique and becomes an option to study a variety of populations and tasks, the reproducibility of the fNIRS signal is still subject of debate. By performing test-retest protocols over different functional tasks, several studies agree that the fNIRS signal is reproducible over group analysis, but the inter-subject and within-subject reproducibility is poor. The high variability at the first statistical level is often attributed to global systemic physiology. In the present work, we revisited the reproducibility of the fNIRS signal during a finger-tapping task across multiple sessions on the same and different days. We expanded on previous studies by hypothesizing that the lack of spatial information of the optodes contributes to the low reproducibility in fNIRS, and we incorporated a real-time neuronavigation protocol to provide accurate cortical localization of the optodes. Our proposed approach was validated in 10 healthy volunteers, and our results suggest that the addition of neuronavigation can increase the within-subject reproducibility of the fNIRS data, particularly in the region of interest. Unlike traditional approaches to positioning the optodes, in which low intra-subject reproducibility has been found, we were able to obtain consistent and robust activation of the contralateral primary motor cortex at the intra-subject level using a neuronavigation protocol. Overall, our findings support the hypothesis that at least part of the variability in fNIRS cannot be only attributed to global systemic physiology. The use of neuronavigation to guide probe positioning, as proposed in this work, has impacts to longitudinal protocols performed with fNIRS.
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Affiliation(s)
- Sergio Luiz Novi
- “Gleb Wataghin” Institute of Physics, University of Campinas, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Edwin Johan Forero
- “Gleb Wataghin” Institute of Physics, University of Campinas, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Jose Angel Ivan Rubianes Silva
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
- School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil
| | - Nicolas Gabriel S. R. de Souza
- “Gleb Wataghin” Institute of Physics, University of Campinas, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Giovani Grisotti Martins
- “Gleb Wataghin” Institute of Physics, University of Campinas, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Andres Quiroga
- “Gleb Wataghin” Institute of Physics, University of Campinas, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
| | - Shin-Ting Wu
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
- School of Electrical and Computer Engineering, University of Campinas, Campinas, Brazil
| | - Rickson C. Mesquita
- “Gleb Wataghin” Institute of Physics, University of Campinas, Campinas, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, Brazil
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34
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Wang J, Gu Y, Dong W, Zhao M, Tian J, Sun T, Yu X, Ouyang G, Wang H. Lower Small-Worldness of Intrinsic Brain Networks Facilitates the Cognitive Protection of Intellectual Engagement in Elderly People Without Dementia: A Near-Infrared Spectroscopy Study. Am J Geriatr Psychiatry 2020; 28:722-731. [PMID: 32173205 DOI: 10.1016/j.jagp.2020.02.006] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 02/04/2020] [Accepted: 02/14/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVE Lifetime intellectual engagement may be associated with cognitive ability late in life. However, the current evidence on whether cognitive activities will improve and/or maintain cognitive function is heterogeneous. Drawing on knowledge of the brain's intrinsic small-world organization which combines regional specialization and efficient global information transfer, we aimed to explore that whether individual differences in the small-worldness of resting-state functional connectivity (rsFC) networks would explain the variability in the strength of the association between intellectual engagement and cognitive functioning. METHODS Sixty-five elderly people without dementia were enrolled and scanned with a 52-channel near-infrared spectroscopy system. The number, frequency, and participation hours of intellectual activities were investigated to measure intellectual engagement. Global cognition was assessed by the Montreal Cognitive Assessment. The general linear models and the simple slope analysis were employed to measure the modulatory role of network properties. RESULTS The small-worldness of the brain network emerged as a moderator of the association between intellectual engagement and cognition. Exclusively among elderly people with lower small-worldness, greater intellectual engagement, including the frequency and participation hours of activities, was associated with greater global cognitive function. Furthermore, we observed that elderly people with lower small-worldness exhibited decreased rsFC across the bilateral frontopolar areas and increased rsFC across the bilateral parietal cortex. CONCLUSION The individual differences in the small-worldness of rsFC networks might explain the varying strength of the association between intellectual engagement and cognitive functioning. Our findings imply that the intrinsic small-worldness of the brain network might be a potential neurobiological contributor that interacts with the intellectual engagement in enhancing the cognitive ability in late life.
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Affiliation(s)
- Jing Wang
- Peking University Institute of Mental Health (Sixth Hospital) (JW, WD, MZ, JT, TS, XY, HW), Beijing, China; National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) (JW, WD, MZ, JT, TS, XY HW), Beijing, China; Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia (JW, MZ, TS, XY, HW), Beijing, China
| | - Yue Gu
- Key Laboratory of Computer Vision and System (Ministry of Education), School of Computer Science and Engineering, Tianjin University of Technology (YG), Tianjin, China
| | - Wentian Dong
- Peking University Institute of Mental Health (Sixth Hospital) (JW, WD, MZ, JT, TS, XY, HW), Beijing, China; National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) (JW, WD, MZ, JT, TS, XY HW), Beijing, China
| | - Mei Zhao
- Peking University Institute of Mental Health (Sixth Hospital) (JW, WD, MZ, JT, TS, XY, HW), Beijing, China; National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) (JW, WD, MZ, JT, TS, XY HW), Beijing, China; Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia (JW, MZ, TS, XY, HW), Beijing, China; Department of Psychiatry, University of Melbourne (MZ), Melbourne, Australia
| | - Ju Tian
- Peking University Institute of Mental Health (Sixth Hospital) (JW, WD, MZ, JT, TS, XY, HW), Beijing, China; National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) (JW, WD, MZ, JT, TS, XY HW), Beijing, China
| | - Tingting Sun
- Peking University Institute of Mental Health (Sixth Hospital) (JW, WD, MZ, JT, TS, XY, HW), Beijing, China; National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) (JW, WD, MZ, JT, TS, XY HW), Beijing, China; Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia (JW, MZ, TS, XY, HW), Beijing, China
| | - Xin Yu
- Peking University Institute of Mental Health (Sixth Hospital) (JW, WD, MZ, JT, TS, XY, HW), Beijing, China; National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) (JW, WD, MZ, JT, TS, XY HW), Beijing, China; Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia (JW, MZ, TS, XY, HW), Beijing, China
| | - Gaoxiang Ouyang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University (GO), Beijing, China
| | - Huali Wang
- Peking University Institute of Mental Health (Sixth Hospital) (JW, WD, MZ, JT, TS, XY, HW), Beijing, China; National Clinical Research Center for Mental Disorders, NHC Key Laboratory of Mental Health (Peking University) (JW, WD, MZ, JT, TS, XY HW), Beijing, China; Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia (JW, MZ, TS, XY, HW), Beijing, China.
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Yanagi M, Hosomi F, Kawakubo Y, Tsuchiya A, Ozaki S, Shirakawa O. A decrease in spontaneous activity in medial prefrontal cortex is associated with sustained hallucinations in chronic schizophrenia: An NIRS study. Sci Rep 2020; 10:9569. [PMID: 32533029 PMCID: PMC7293286 DOI: 10.1038/s41598-020-66560-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 05/15/2020] [Indexed: 01/28/2023] Open
Abstract
In functional imaging, accumulating evidence suggests that spontaneous activity decreases during the resting state in the core brain regions of the default-mode network [e.g. medial prefrontal cortex (mPFC)] in schizophrenia. However, the significance of this decreased activity has not been clarified in relation to its clinical symptoms. In this study, near-infrared spectroscopy (NIRS), which is a simple imaging modality suitable for resting state paradigm, was used to evaluate the intensity of the spontaneous activity during the resting state in chronic schizophrenia. Consistent with previous findings of fMRI studies, spontaneous activity decreased in the mPFC of patients with schizophrenia. In addition, the decreased spontaneous activity was associated with severe hallucinations in this region where reality monitoring is fundamentally engaged. These results may encourage additional application of NIRS with the resting state paradigm into daily clinical settings for addressing the broad phenotypes and unstable course of schizophrenia.
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Affiliation(s)
- Masaya Yanagi
- Department of Neuropsychiatry, Kindai University Faculty of Medicine, Osaka-sayama, Osaka, Japan.
| | - Fumiharu Hosomi
- Department of Neuropsychiatry, Kindai University Faculty of Medicine, Osaka-sayama, Osaka, Japan
| | - Yoshihiro Kawakubo
- Department of Neuropsychiatry, Kindai University Faculty of Medicine, Osaka-sayama, Osaka, Japan
| | - Aki Tsuchiya
- Department of Neuropsychiatry, Kindai University Faculty of Medicine, Osaka-sayama, Osaka, Japan
| | | | - Osamu Shirakawa
- Department of Neuropsychiatry, Kindai University Faculty of Medicine, Osaka-sayama, Osaka, Japan
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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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37
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A low-cost multichannel NIRS oximeter for monitoring systemic low-frequency oscillations. Neural Comput Appl 2020. [DOI: 10.1007/s00521-020-04897-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
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38
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Duan L, Mai X. Spectral clustering-based resting-state network detection approach for functional near-infrared spectroscopy. BIOMEDICAL OPTICS EXPRESS 2020; 11:2191-2204. [PMID: 32341876 PMCID: PMC7173901 DOI: 10.1364/boe.387919] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/17/2020] [Accepted: 03/19/2020] [Indexed: 05/26/2023]
Abstract
In recent years, studying the resting-state network (RSN) by using functional near-infrared spectroscopy (fNIRS) has received increased attention. The previous resting-state fNIRS studies mainly adopted the seed-based correlation and the independent component analysis to detect RSN. However, these methods have several inherent problems. For example, the seed-based correlation method relies on seed region selection and neglects the interactions among multiple regions. The ICA method usually relies on manual component selection, which requires rich experience from the experimenter. In the present study, we developed a new approach for fNIRS-RSN detection based on spectral clustering. It consists of two steps. First, it calculates the individual-level partition of the fNIRS measurement region by using spectral clustering with an automatically determined cluster number. Second, the individual-level partitioning results are further clustered. Those clusters with high group consistency are determined as RSN clusters. We validated the method by using simulated data and in vivo fNIRS data. The results showed that the proposed method was effective and robust for fNIRS-RSN detection.
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Affiliation(s)
- Lian Duan
- Shenzhen Key Laboratory of Affective and Social Cognitive Science, Shenzhen University, Shenzhen, China
- The Department of Psychology, Renmin University of China, Beijing, China
- The Laboratory of the Department of Psychology, Renmin University of China, Beijing, China
| | - Xiaoqin Mai
- The Department of Psychology, Renmin University of China, Beijing, China
- The Laboratory of the Department of Psychology, Renmin University of China, Beijing, China
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Sutoko S, Monden Y, Tokuda T, Ikeda T, Nagashima M, Funane T, Atsumori H, Kiguchi M, Maki A, Yamagata T, Dan I. Atypical Dynamic-Connectivity Recruitment in Attention-Deficit/Hyperactivity Disorder Children: An Insight Into Task-Based Dynamic Connectivity Through an fNIRS Study. Front Hum Neurosci 2020; 14:3. [PMID: 32082132 PMCID: PMC7005005 DOI: 10.3389/fnhum.2020.00003] [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: 09/22/2019] [Accepted: 01/07/2020] [Indexed: 11/13/2022] Open
Abstract
Connectivity between brain regions has been redefined beyond a stationary state. Even when a person is in a resting state, brain connectivity dynamically shifts. However, shifted brain connectivity under externally evoked stimulus is still little understood. The current study, therefore, focuses on task-based dynamic functional-connectivity (FC) analysis of brain signals measured by functional near-infrared spectroscopy (fNIRS). We hypothesize that a stimulus may influence not only brain connectivity but also the occurrence probabilities of task-related and task-irrelevant connectivity states. fNIRS measurement (of the prefrontal-to-inferior parietal lobes) was conducted on 21 typically developing (TD) and 21 age-matched attention-deficit/hyperactivity disorder (ADHD) children performing an inhibitory control task, namely, the Go/No-Go (GNG) task. It has been reported that ADHD children lack inhibitory control; differences between TD and ADHD children in terms of task-based dynamic FC were also evaluated. Four connectivity states were found to occur during the temporal task course. Two dominant connectivity states (states 1 and 2) are characterized by strong connectivities within the frontoparietal network (occurrence probabilities of 40%-56% and 26%-29%), and presumptively interpreted as task-related states. A connectivity state (state 3) shows strong connectivities in the bilateral medial frontal-to-parietal cortices (occurrence probability of 7-15%). The strong connectivities were found at the overlapped regions related the default mode network (DMN). Another connectivity state (state 4) visualizes strong connectivities in all measured regions (occurrence probability of 10%-16%). A global effect coming from cerebral vascular may highly influence this connectivity state. During the GNG stimulus interval, the ADHD children tended to show decreased occurrence probability of the dominant connectivity state and increased occurrence probability of other connectivity states (states 3 and 4). Bringing a new perspective to explain neuropathophysiology, these findings suggest atypical dynamic network recruitment to accommodate task demands in ADHD children.
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Affiliation(s)
- Stephanie Sutoko
- Hitachi, Ltd., Research & Development Group, Center for Exploratory Research, Tokyo, Japan
- Faculty of Science and Engineering, Applied Cognitive Neuroscience Laboratory, Chuo University, Tokyo, Japan
| | - Yukifumi Monden
- Department of Pediatrics, Jichi Medical University, Shimotsuke, Japan
- Department of Pediatrics, International University of Health and Welfare Hospital, Nasushiobara, Japan
| | - Tatsuya Tokuda
- Faculty of Science and Engineering, Applied Cognitive Neuroscience Laboratory, Chuo University, Tokyo, Japan
| | - Takahiro Ikeda
- Department of Pediatrics, Jichi Medical University, Shimotsuke, Japan
| | - Masako Nagashima
- Department of Pediatrics, Jichi Medical University, Shimotsuke, Japan
| | - Tsukasa Funane
- Hitachi, Ltd., Research & Development Group, Center for Exploratory Research, Tokyo, Japan
| | - Hirokazu Atsumori
- Hitachi, Ltd., Research & Development Group, Center for Exploratory Research, Tokyo, Japan
| | - Masashi Kiguchi
- Hitachi, Ltd., Research & Development Group, Center for Exploratory Research, Tokyo, Japan
| | - Atsushi Maki
- Hitachi, Ltd., Research & Development Group, Center for Exploratory Research, Tokyo, Japan
| | - Takanori Yamagata
- Department of Pediatrics, Jichi Medical University, Shimotsuke, Japan
| | - Ippeita Dan
- Faculty of Science and Engineering, Applied Cognitive Neuroscience Laboratory, Chuo University, Tokyo, Japan
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Yaramothu C, Li X, Morales C, Alvarez TL. Reliability of Frontal Eye Fields Activation and Very Low-Frequency Oscillations Observed during Vergence Eye Movements: an fNIRS Study. Sci Rep 2020; 10:712. [PMID: 31959829 PMCID: PMC6971237 DOI: 10.1038/s41598-020-57597-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Accepted: 12/21/2019] [Indexed: 11/08/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS), an imaging tool that utilizes infrared light to measure changes within the concentration of oxygenated (HbO) and deoxygenated (HbR) hemoglobin, holds promise to study functional activity from motor, visual, and memory cortical regions using stimulus-induced tasks. This study investigated the reliability for fNIRS to examine cortical activations within the frontal eye fields (FEF) while initiating vergence eye movements, the inward and outward rotation of the eyes. FNIRS data were collected from twenty participants with normal binocular vision while performing vergence eye movements compared to sustained gaze fixation within a block design during two different sessions. Reliability of the experimental protocol was assessed using the intraclass correlation coefficient (ICC). The ICC values ranged from 0.6 to 0.7 for measuring the HbO activation within the vicinity of the FEF. A frequency power spectrum analysis revealed two predominant frequencies within the functional activation signals from the FEF. One high-intensity signal was present at 0.029 Hz, centering around the block design frequency. The peak-intensity signal was observed between 0.012 and 0.018 Hz where this very low-frequency oscillation (VLFO) was hypothesized to be generated by the macrovasculature present near the FEF and should be avoided as a block design frequency in future fNIRS studies to avoid false positive results.
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Affiliation(s)
- Chang Yaramothu
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Xiaobo Li
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Cristian Morales
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA
| | - Tara L Alvarez
- Department of Biomedical Engineering, New Jersey Institute of Technology, Newark, NJ, USA.
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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
| | - 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
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42
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Sutoko S, Monden Y, Tokuda T, Ikeda T, Nagashima M, Funane T, Sato H, Kiguchi M, Maki A, Yamagata T, Dan I. Exploring attentive task-based connectivity for screening attention deficit/hyperactivity disorder children: a functional near-infrared spectroscopy study. NEUROPHOTONICS 2019; 6:045013. [PMID: 31853459 PMCID: PMC6917048 DOI: 10.1117/1.nph.6.4.045013] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/02/2019] [Accepted: 11/20/2019] [Indexed: 06/10/2023]
Abstract
Connectivity impairment has frequently been associated with the pathophysiology of attention-deficit/hyperactivity disorder (ADHD). Although the connectivity of the resting state has mainly been studied, we expect the transition between baseline and task may also be impaired in ADHD children. Twenty-three typically developing (i.e., control) and 36 disordered (ADHD and autism-comorbid ADHD) children were subjected to connectivity analysis. Specifically, they performed an attention task, visual oddball, while their brains were measured by functional near-infrared spectroscopy. The results of the measurements revealed three key findings. First, the control group maintained attentive connectivity, even in the baseline interval. Meanwhile, the disordered group showed enhanced bilateral intra- and interhemispheric connectivities while performing the task. However, right intrahemispheric connectivity was found to be weaker than those for the control group. Second, connectivity and activation characteristics might not be positively correlated with each other. In our previous results, disordered children lacked activation in the right middle frontal gyrus. However, within region connectivity of the right middle frontal gyrus was relatively strong in the baseline interval and significantly increased in the task interval. Third, the connectivity-based biomarker performed better than the activation-based biomarker in terms of screening. Activation and connectivity features were independently optimized and cross validated to obtain the best performing threshold-based classifier. The effectiveness of connectivity features, which brought significantly higher training accuracy than the optimum activation features, was confirmed (88% versus 76%). The optimum screening features were characterized by two trends: (1) strong connectivities of right frontal, left frontal, and left parietal lobes and (2) weak connectivities of left frontal, left parietal, and right parietal lobes in the control group. We conclude that the attentive task-based connectivity effectively shows the difference between control and disordered children and may represent pathological characteristics to be feasibly implemented as a supporting tool for clinical screening.
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Affiliation(s)
- Stephanie Sutoko
- Hitachi, Ltd., Center for Exploratory Research, Research and Development Group, Hatoyama, Saitama, Japan
- Chuo University, Research and Development Initiatives, Applied Cognitive Neuroscience Laboratory, Bunkyo-ku, Tokyo, Japan
| | - Yukifumi Monden
- Jichi Medical University, Department of Pediatrics, Shimotsuke, Tochigi, Japan
- International University of Health and Welfare Hospital, Department of Pediatrics, Nasushiobara, Tochigi, Japan
| | - Tatsuya Tokuda
- Chuo University, Research and Development Initiatives, Applied Cognitive Neuroscience Laboratory, Bunkyo-ku, Tokyo, Japan
| | - Takahiro Ikeda
- Jichi Medical University, Department of Pediatrics, Shimotsuke, Tochigi, Japan
| | - Masako Nagashima
- Jichi Medical University, Department of Pediatrics, Shimotsuke, Tochigi, Japan
| | - Tsukasa Funane
- Hitachi, Ltd., Center for Exploratory Research, Research and Development Group, Hatoyama, Saitama, Japan
| | - Hiroki Sato
- Hitachi, Ltd., Center for Exploratory Research, Research and Development Group, Hatoyama, Saitama, Japan
| | - Masashi Kiguchi
- Hitachi, Ltd., Center for Exploratory Research, Research and Development Group, Hatoyama, Saitama, Japan
| | - Atsushi Maki
- Hitachi, Ltd., Center for Exploratory Research, Research and Development Group, Hatoyama, Saitama, Japan
| | - Takanori Yamagata
- Jichi Medical University, Department of Pediatrics, Shimotsuke, Tochigi, Japan
| | - Ippeita Dan
- Chuo University, Research and Development Initiatives, Applied Cognitive Neuroscience Laboratory, Bunkyo-ku, Tokyo, Japan
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43
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Assessment of the effect of data length on the reliability of resting-state fNIRS connectivity measures and graph metrics. Biomed Signal Process Control 2019. [DOI: 10.1016/j.bspc.2019.101612] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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Wang M, Yuan Z, Niu H. Reliability evaluation on weighted graph metrics of fNIRS brain networks. Quant Imaging Med Surg 2019; 9:832-841. [PMID: 31281779 DOI: 10.21037/qims.2019.05.08] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background Resting-state fNIRS (R-fNIRS) imaging data has proven to be a valuable technique to quantitatively characterize functional architectures of human brain network. However, whether the brain network metrics derived using weighted brain network model is test-retest (TRT) reliable remains largely unknown. Methods Here, we firstly constructed weighted brain networks on a group of 18 participants, and then applied graph-theory approach to quantify topological parameters of each weighted network. The intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of network metrics. Results We found that the reliability of the weighted network metrics is threshold-sensitive, and most of these network metrics showed fair to excellent reliability. Specifically, the global network metrics, e.g., clustering coefficient, path length, local efficiency and global efficiency were of excellent level reliability (ICC >0.75) on both HbO and HbR signals. The nodal network metrics, e.g., degree and efficiency, generally also showed excellent level reliability on both HbO and HbR signals, and the reliability of these two metrics was better than that of nodal betweenness. Conclusions Overall, these findings demonstrated that most weighted network metrics derived from fNIRS are TRT reliable and can be used for brain network research.
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Affiliation(s)
- Mengjing Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
| | - Zhen Yuan
- Faculty of Health Sciences, University of Macau, Macao 999078, China
| | - Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China
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45
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Niu H, Zhu Z, Wang M, Li X, Yuan Z, Sun Y, Han Y. Abnormal dynamic functional connectivity and brain states in Alzheimer's diseases: functional near-infrared spectroscopy study. NEUROPHOTONICS 2019; 6:025010. [PMID: 31205976 PMCID: PMC6548336 DOI: 10.1117/1.nph.6.2.025010] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 05/02/2019] [Indexed: 05/24/2023]
Abstract
Communication within the brain is highly dynamic. Alzheimer's disease (AD) exhibits dynamic progression corresponding to a decline in memory and cognition. However, little is known of whether brain dynamics are disrupted in AD and its prodromal stage, mild cognitive impairment (MCI). For our study, we acquired high sampling rate functional near-infrared spectroscopy imaging data at rest from the entire cortex of 23 patients with AD dementia, 25 patients with amnestic mild cognitive impairment (aMCI), and 30 age-matched healthy controls (HCs). Sliding-window correlation and k-means clustering analyses were used to construct dynamic functional connectivity (FC) maps for each participant. We discovered that the brain's dynamic FC variability strength ( Q ) significantly increased in both aMCI and AD group as compared to HCs. Using the Q value as a measurement, the classification performance exhibited a good power in differentiating aMCI [area under the curve ( AUC = 82.5 % )] or AD ( AUC = 86.4 % ) from HCs. Furthermore, we identified two abnormal brain FC states in the AD group, of which the occurrence frequency ( F ) exhibited a significant decrease for the first-level FC state (state 1) and a significant increase for the second-level FC state (state 2). We also found that the abnormal F in these two states significantly correlated with the cognitive impairment in patients. These findings provide the first evidence to demonstrate the disruptions of dynamic brain connectivity in aMCI and AD and extend the traditional static (i.e., time-averaged) FC findings in the disease (i.e., disconnection syndrome) and thus provide insights into understanding the pathophysiological mechanisms occurring in aMCI and AD.
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Affiliation(s)
- Haijing Niu
- Beijing Normal University, State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing, China
| | - Zhaojun Zhu
- 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
| | - Xuanyu Li
- Xuan Wu Hospital of Capital Medical University, Department of Neurology, Beijing, China
| | - Zhen Yuan
- University of Macau, Faculty of Health Sciences, Macao, China
| | - Yu Sun
- Xuan Wu Hospital of Capital Medical University, Department of Neurology, Beijing, China
| | - Ying Han
- Xuan Wu Hospital of Capital Medical University, Department of Neurology, Beijing, China
- Beijing Institute for Brain Disorders, Center of Alzheimer’s Disease, Beijing, China
- Beijing Institute of Geriatrics, Beijing, China
- National Clinical Research Center for Geriatric Disorders, Beijing, China
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46
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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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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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Resting-state functional connectivity in prefrontal cortex investigated by functional near-infrared spectroscopy: A longitudinal and cross-sectional study. Neurosci Lett 2018; 683:94-99. [DOI: 10.1016/j.neulet.2018.06.034] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 06/07/2018] [Accepted: 06/20/2018] [Indexed: 11/20/2022]
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Higgins IA, Kundu S, Guo Y. Integrative Bayesian analysis of brain functional networks incorporating anatomical knowledge. Neuroimage 2018; 181:263-278. [PMID: 30017786 DOI: 10.1016/j.neuroimage.2018.07.015] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2018] [Revised: 07/04/2018] [Accepted: 07/05/2018] [Indexed: 12/31/2022] Open
Abstract
Recently, there has been increased interest in fusing multimodal imaging to better understand brain organization by integrating information on both brain structure and function. In particular, incorporating anatomical knowledge leads to desirable outcomes such as increased accuracy in brain network estimates and greater reproducibility of topological features across scanning sessions. Despite the clear advantages, major challenges persist in integrative analyses including an incomplete understanding of the structure-function relationship and inaccuracies in mapping anatomical structures due to inherent deficiencies in existing imaging technology. This calls for the development of advanced network modeling tools that appropriately incorporate anatomical structure in constructing brain functional networks. We propose a hierarchical Bayesian Gaussian graphical modeling approach which models the brain functional networks via sparse precision matrices whose degree of edge specific shrinkage is a random variable that is modeled using both anatomical structure and an independent baseline component. The proposed approach adaptively shrinks functional connections and flexibly identifies functional connections supported by structural connectivity knowledge. This enables robust brain network estimation even in the presence of misspecified anatomical knowledge, while accommodating heterogeneity in the structure-function relationship. We implement the approach via an efficient optimization algorithm which yields maximum a posteriori estimates. Extensive numerical studies involving multiple functional network structures reveal the clear advantages of the proposed approach over competing methods in accurately estimating brain functional connectivity, even when the anatomical knowledge is misspecified up to a certain degree. An application of the approach to data from the Philadelphia Neurodevelopmental Cohort (PNC) study reveals gender based connectivity differences across multiple age groups, and higher reproducibility in the estimation of network metrics compared to alternative methods.
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Affiliation(s)
- Ixavier A Higgins
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, 30322, USA
| | - Suprateek Kundu
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, 30322, USA.
| | - Ying Guo
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, GA, 30322, USA
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Li L, Babawale O, Yennu A, Trowbridge C, Hulla R, Gatchel RJ, Liu H. Whole-cortical graphical networks at wakeful rest in young and older adults revealed by functional near-infrared spectroscopy. NEUROPHOTONICS 2018; 5:035004. [PMID: 30137882 PMCID: PMC6063133 DOI: 10.1117/1.nph.5.3.035004] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 07/02/2018] [Indexed: 05/17/2023]
Abstract
A good understanding of age-dependent changes and modifications in brain networks is crucial for fully exploring the effects of aging on the human brain. Few reports have been found in studies of functional brain networks using functional near-infrared spectroscopy (fNIRS). Moreover, little is known about the feasibility of using fNIRS to assess age-related changes in brain connectomes. This study applied whole brain fNIRS measurement, combined with graph theory analysis, to assess the age-dependent changes in resting-state brain networks. Five to eight minutes of resting-state brain hemodynamic signals were recorded from 48 participants (18 young adults and 30 older adults) with 133 optical channels covering the majority of the cortical regions. Both local and global graph metrics were computed to identify the age-related changes of topographical brain networks. Older adults showed an overall decline of both global and local efficiency compared to young adults, as well as the decline of small-worldness. In addition, young adults showed the abundance of hubs in the prefrontal cortex, whereas older adults revealed the hub shifts to the sensorimotor cortex. These obvious shifts of hubs may potentially indicate decreases of the decision-making, memory, and other high-order functions as people age. Our results showed consistent findings with published literature and also demonstrated the feasibility of whole-head fNIRS measurements to assess age-dependent changes in resting-state brain networks.
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Affiliation(s)
- Lin Li
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas, United States
- University of California at Los Angeles, David Geffen School of Medicine, Department of Neurology, Los Angeles, California, United States
| | - Olajide Babawale
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas, United States
| | - Amarnath Yennu
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas, United States
- Stanford University School of Medicine, Department of Neurology, Stanford, California, United States
| | - Cynthia Trowbridge
- University of Texas at Arlington, Department of Kinesiology, Arlington, Texas, United States
| | - Ryan Hulla
- University of Texas at Arlington, College of Science, Department of Psychology, Arlington, Texas, United States
| | - Robert J. Gatchel
- University of Texas at Arlington, College of Science, Department of Psychology, Arlington, Texas, United States
| | - Hanli Liu
- University of Texas at Arlington, Department of Bioengineering and Joint Graduate Program Between University of Texas at Arlington and University of Texas Southwestern Medical Center, Arlington, Texas, United States
- Address all correspondence to: Hanli Liu, E-mail:
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