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Iester C, Bonzano L, Biggio M, Cutini S, Bove M, Brigadoi S. Comparing different motion correction approaches for resting-state functional connectivity analysis with functional near-infrared spectroscopy data. NEUROPHOTONICS 2024; 11:045001. [PMID: 39372120 PMCID: PMC11448702 DOI: 10.1117/1.nph.11.4.045001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 07/04/2024] [Accepted: 07/26/2024] [Indexed: 10/08/2024]
Abstract
Significance Motion artifacts are a notorious challenge in the functional near-infrared spectroscopy (fNIRS) field. However, little is known about how to deal with them in resting-state data. Aim We assessed the impact of motion artifact correction approaches on assessing functional connectivity, using semi-simulated datasets with different percentages and types of motion artifact contamination. Approach Thirty-five healthy adults underwent a 15-min resting-state acquisition. Semi-simulated datasets were generated by adding spike-like and/or baseline-shift motion artifacts to the real dataset. Fifteen pipelines, employing various correction approaches, were applied to each dataset, and the group correlation matrix was computed. Three metrics were used to test the performance of each approach. Results When motion artifact contamination was low, various correction approaches were effective. However, with increased contamination, only a few pipelines were reliable. For datasets mostly free of baseline-shift artifacts, discarding contaminated frames after pre-processing was optimal. Conversely, when both spike and baseline-shift artifacts were present, discarding contaminated frames before pre-processing yielded the best results. Conclusions This study emphasizes the need for customized motion correction approaches as the effectiveness varies with the specific type and amount of motion artifacts present.
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Affiliation(s)
- Costanza Iester
- University of Genoa, Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Genoa, Italy
| | - Laura Bonzano
- University of Genoa, Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Genoa, Italy
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Monica Biggio
- University of Genoa, Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Genoa, Italy
| | - Simone Cutini
- University of Padua, Department of Developmental Psychology and Socialization, Padua, Italy
| | - Marco Bove
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy
- University of Genoa, Department of Experimental Medicine, Section of Human Physiology, Genoa, Italy
| | - Sabrina Brigadoi
- University of Padua, Department of Developmental Psychology and Socialization, Padua, Italy
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Eken A, Nassehi F, Eroğul O. Diagnostic machine learning applications on clinical populations using functional near infrared spectroscopy: a review. Rev Neurosci 2024; 35:421-449. [PMID: 38308531 DOI: 10.1515/revneuro-2023-0117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2023] [Accepted: 01/12/2024] [Indexed: 02/04/2024]
Abstract
Functional near-infrared spectroscopy (fNIRS) and its interaction with machine learning (ML) is a popular research topic for the diagnostic classification of clinical disorders due to the lack of robust and objective biomarkers. This review provides an overview of research on psychiatric diseases by using fNIRS and ML. Article search was carried out and 45 studies were evaluated by considering their sample sizes, used features, ML methodology, and reported accuracy. To our best knowledge, this is the first review that reports diagnostic ML applications using fNIRS. We found that there has been an increasing trend to perform ML applications on fNIRS-based biomarker research since 2010. The most studied populations are schizophrenia (n = 12), attention deficit and hyperactivity disorder (n = 7), and autism spectrum disorder (n = 6) are the most studied populations. There is a significant negative correlation between sample size (>21) and accuracy values. Support vector machine (SVM) and deep learning (DL) approaches were the most popular classifier approaches (SVM = 20) (DL = 10). Eight of these studies recruited a number of participants more than 100 for classification. Concentration changes in oxy-hemoglobin (ΔHbO) based features were used more than concentration changes in deoxy-hemoglobin (ΔHb) based ones and the most popular ΔHbO-based features were mean ΔHbO (n = 11) and ΔHbO-based functional connections (n = 11). Using ML on fNIRS data might be a promising approach to reveal specific biomarkers for diagnostic classification.
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Affiliation(s)
- Aykut Eken
- Department of Biomedical Engineering, Faculty of Engineering, TOBB University of Economics and Technology, Sogutozu, 06510, Ankara, Türkiye
| | - Farhad Nassehi
- Department of Biomedical Engineering, Faculty of Engineering, TOBB University of Economics and Technology, Sogutozu, 06510, Ankara, Türkiye
| | - Osman Eroğul
- Department of Biomedical Engineering, Faculty of Engineering, TOBB University of Economics and Technology, Sogutozu, 06510, Ankara, Türkiye
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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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Ma Y, Luo K, Ding P, Yin S, Li X, Li Y. Differences in symmetrical low-frequency oscillations among healthy subjects, and those with stroke or peripheral arterial disease. Heliyon 2023; 9:e17015. [PMID: 37484434 PMCID: PMC10361110 DOI: 10.1016/j.heliyon.2023.e17015] [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: 03/06/2023] [Revised: 05/30/2023] [Accepted: 06/04/2023] [Indexed: 07/25/2023] Open
Abstract
Low-frequency oscillations (LFOs) observed in near-infrared spectroscopy (NIRS) reflect autonomic physiological processes, and may serve as useful indicators for detecting and monitoring circulatory dysfunction. The aim of this study was to reveal whether LFOs can be used as vascular perfusion biomarkers to differentiate different types and degrees of vascular lesions based on clinical patient data. Materials and Methods: In this study, healthy controls, ischemic stroke patients and peripheral atherosclerosis patients completed a resting-state LFO detection experiment. LFOs were collected simultaneously at peripheral right and left earlobes, fingertips and toes, along with coherence and phase shift analyses processing. Results: The results showed that the coherence coefficients of symmetric peripheral positions and the absolute value-phase shifts of fingers and toes can be used to distinguish healthy individuals, ischemic stroke patients and peripheral atherosclerosis patients. The symmetric earlobes' absolute value-phase shifts could be used to differentiate mild and severe ischemic stroke patients; the coherence coefficients and absolute value-phase shifts of the symmetric toes could be used to differentiate mild and severe peripheral arteriosclerosis patients. The accuracy of differentiating between types of patients was 70%; those with different degrees of peripheral atherosclerosis was 85%, and those with different degrees of ischemic stroke was 72%. Conclusions: LFOs can serve as vascular perfusion biomarkers to differentiate types and degrees of vascular lesions. Therefore, LFOs have the potential to provide valuable patient information to assist researchers and clinicians in identifying specific peripheral circulatory damage subgroups.
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Affiliation(s)
- Yunfei Ma
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei, 066004, China
| | - Kexin Luo
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei, 066004, China
| | - Peng Ding
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei, 066004, China
| | - Shimin Yin
- Department of Neurology, PLA Rocket Force Characteristic Medical Center, Beijing, 100088, China
| | - Xiaoli Li
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, 100875, China
| | - Yingwei Li
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei, 066004, China
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Chang WK, Park J, Lee JY, Cho S, Lee J, Kim WS, Paik NJ. Functional Network Changes After High-Frequency rTMS Over the Most Activated Speech-Related Area Combined With Speech Therapy in Chronic Stroke With Non-fluent Aphasia. Front Neurol 2022; 13:690048. [PMID: 35222235 PMCID: PMC8866644 DOI: 10.3389/fneur.2022.690048] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 01/12/2022] [Indexed: 12/04/2022] Open
Abstract
OBJECTIVE High-frequency repetitive transcranial magnetic stimulation (HF-rTMS) to the lesional hemisphere requires prudence in selecting the appropriate stimulation spot. Functional near-IR spectroscopy (fNIRS) can be used in both selecting the stimulation spot and assessing the changes of the brain network. This study aimed to evaluate the effect of HF-rTMS on the most activated spot identified with fNIRS and assess the changes of brain functional network in the patients with poststroke aphasia. METHODS A total of five patients received HF-rTMS to the most activated area on the lesional hemisphere, followed by 30 min of speech therapy for 10 days. The Korean version of the Western aphasia battery (K-WAB) and fNIRS evaluation were done 1 day before the treatment, 1 day and 1 month after the last treatment session. Changes of K-WAB and paired cortical interaction and brain network analysis using graph theory were assessed. RESULTS Aphasia quotient in K-WAB significantly increased after the treatment (P = 0.043). The correlation analysis of cortical interactions showed increased connectivity between language production and processing areas. Clustering coefficients of the left hemisphere were increased over a sparsity range between 0.45 and 0.58 (0.015 < p < 0.031), whereas the clustering coefficients of the right hemisphere, decreased over a sparsity range 0.15-0.87 (0.063 < p < 0.095). The global efficiency became lower over a network sparsity range between 0.47 and 0.75 (0.015 < p < 0.063). CONCLUSION Improvement of language function and changes of corticocortical interaction between language-related cortical areas were observed after HF-rTMS on the most activated area identified by fNIRS with combined speech therapy in the patients with poststroke aphasia.
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Affiliation(s)
| | | | | | | | | | | | - Nam-Jong Paik
- Department of Rehabilitation Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam-si, South Korea
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Eken A. Assessment of flourishing levels of individuals by using resting-state fNIRS with different functional connectivity measures. Biomed Signal Process Control 2021. [DOI: 10.1016/j.bspc.2021.102645] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
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Resting state prefrontal cortex oxygenation in adolescent non-suicidal self-injury - A near-infrared spectroscopy study. NEUROIMAGE-CLINICAL 2021; 31:102704. [PMID: 34091351 PMCID: PMC8182302 DOI: 10.1016/j.nicl.2021.102704] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/07/2021] [Accepted: 05/18/2021] [Indexed: 12/02/2022]
Abstract
Resting prefrontal cortex (PFC) oxygenation is decreased in adolescents with non-suicidal self-injury (NSSI) compared to healthy controls. Lower PFC oxygenation (full sample) is associated with greater adverse childhood experiences and less health-related quality of life (HRQoL). On the group-level, patients show no alterations of resting state functional connectivity within the PFC. Among other clinical variables, increased PFC connectivity (full sample) is associated with greater borderline personality pathology.
Introduction Neural alterations in limbic and prefrontal circuits in association with self-injurious behavior have been studied primarily in adult borderline personality disorder (BPD). In adolescent patients, research is still sparse. Here, we used resting functional near-infrared spectroscopy (NIRS) to examine oxygenation of the prefrontal cortex (PFC) and its association with symptom severity in adolescents engaging in non-suicidal self-injury (NSSI) and matched healthy controls (HC). Methods Adolescents (12–17 years) with recurrent episodes of NSSI (n = 170) and healthy controls (n = 43) performed a low-demanding resting-state vanilla baseline task. Mean oxygenation of the PFC and functional connectivity within the PFC, were measured using an 8-channel functional NIRS system (Octamon, Artinis, The Netherlands). Various clinical variables derived from diagnostic interviews and self-reports were included in statistical analyses to explore potential associations with PFC oxygenation and connectivity. Results Adolescents with NSSI showed significantly decreased PFC oxygenation compared to HC, as indexed by oxygenated hemoglobin. Lower PFC oxygenation was associated with greater adverse childhood experiences and less health-related quality of life (HRQoL). While there was no evidence for alterations in PFC connectivity in adolescents engaging in NSSI compared to HC, increased PFC connectivity in the full sample was associated with greater adverse childhood experience, greater BPD pathology, greater depression severity and psychological burden in general, as well as lower HRQoL. Conclusion This study is the first to examine PFC oxygenation using NIRS technology in adolescents engaging in NSSI. Overall, results indicate small effects not specific to NSSI. Clinical implications of these findings and recommendations for further research are discussed.
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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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9
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Li Y, Ma Y, Ma S, Liang Z, Xu F, Tong Y, Frederick BD, Yin S, Li X. Asymmetry of peripheral vascular biomarkers in ischemic stroke patients, assessed using NIRS. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:1-16. [PMID: 32562389 PMCID: PMC7306490 DOI: 10.1117/1.jbo.25.6.065001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Accepted: 06/05/2020] [Indexed: 05/27/2023]
Abstract
SIGNIFICANCE Low-frequency oscillations (LFOs) ranging from 0.01 to 0.15 Hz are common in functional imaging studies. Some of these LFOs are non-neuronal and are correlated with autonomic physiological processes. AIM We investigate the relationships between systemic low-frequency oscillations (sLFOs) measured at different peripheral sites during resting states in ischemic stroke patients. APPROACH Twenty-seven ischemic stroke patients (ages 44 to 90; 20 male and 7 female) were recruited for the study. During the experiments, fluctuations in oxyhemoglobin concentration were measured in the left and right toes, fingertips, and earlobes using a multichannel near-infrared spectroscopy instrument. We applied cross-correlation and frequency component analyses on the sLFO data. RESULTS The results showed that embolization broke the symmetry of the sLFO transmission and that the damage was not limited to the local area but spread throughout the body. Among six peripheral sites, the power spectrum width of the earlobes was significantly larger than that of the fingers and toes. This indicates that the earlobes may contain more physiological information. Finally, the results of fuzzy clustering verified that sLFOs can serve as perfusion biomarkers to differentiate stroke from healthy subjects. CONCLUSIONS The high correlation values and corresponding delays in sLFOs support the hypothesis that (1) the correlation characteristics of sLFOs in stroke patients are different from those of healthy subjects. These characteristics can reflect patient condition, to an extent. Embolization in ischemic stroke patients breaks the symmetry of the body's sLFO transmission, disrupting the balance of blood circulation. (2) sLFOs can be used as perfusion biomarkers to differentiate ischemic stroke patients from healthy subjects. Studying these signals can explicate the overall feedback/influence of pericentral interactions. Finally, peripheral sLFOs have been shown to be an effective and accurate tool for assessing peripheral blood circulation and vascular integrity in ischemic stroke patients.
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Affiliation(s)
- Yingwei Li
- Yanshan University, School of Information Science and Engineering, Qinhuangdao, China
- McLean Hospital, McLean Imaging Center, Belmont, Massachusetts, United States
| | - Yunfei Ma
- Yanshan University, School of Information Science and Engineering, Qinhuangdao, China
| | - Shaoqing Ma
- Yanshan University, School of Information Science and Engineering, Qinhuangdao, China
| | - Zhenhu Liang
- Yanshan University, School of Information Science and Engineering, Qinhuangdao, China
| | - Fang Xu
- PLA Rocket Force Characteristic Medical Center, Department of Neurology, Beijing, China
| | - Yunjie Tong
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
| | - Blaise deB Frederick
- McLean Hospital, McLean Imaging Center, Belmont, Massachusetts, United States
- Harvard Medical School, Department of Psychiatry, Boston, Massachusetts, United States
| | - Shimin Yin
- PLA Rocket Force Characteristic Medical Center, Department of Neurology, Beijing, China
| | - Xiaoli Li
- Beijing Normal University, Center for Collaboration and Innovation in Brain and Learning Sciences, 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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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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Eken A, Çolak B, Bal NB, Kuşman A, Kızılpınar SÇ, Akaslan DS, Baskak B. Hyperparameter-tuned prediction of somatic symptom disorder using functional near-infrared spectroscopy-based dynamic functional connectivity. J Neural Eng 2019; 17:016012. [DOI: 10.1088/1741-2552/ab50b2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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13
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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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14
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Bulgarelli C, Blasi A, de Klerk CCJM, Richards JE, Hamilton A, Southgate V. Fronto-temporoparietal connectivity and self-awareness in 18-month-olds: A resting state fNIRS study. Dev Cogn Neurosci 2019; 38:100676. [PMID: 31299480 PMCID: PMC6969340 DOI: 10.1016/j.dcn.2019.100676] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Revised: 06/13/2019] [Accepted: 06/18/2019] [Indexed: 01/05/2023] Open
Abstract
How and when a concept of the 'self' emerges has been the topic of much interest in developmental psychology. Self-awareness has been proposed to emerge at around 18 months, when toddlers start to show evidence of physical self-recognition. However, to what extent physical self-recognition is a valid indicator of being able to think about oneself, is debated. Research in adult cognitive neuroscience has suggested that a common network of brain regions called Default Mode Network (DMN), including the temporo-parietal junction (TPJ) and the medial prefrontal cortex (mPFC), is recruited when we are reflecting on the self. We hypothesized that if mirror self-recognition involves self-awareness, toddlers who exhibit mirror self-recognition might show increased functional connectivity between frontal and temporoparietal regions of the brain, relative to those toddlers who do not yet show mirror self-recognition. Using fNIRS, we collected resting-state data from 18 Recognizers and 22 Non-Recognizers at 18 months of age. We found significantly stronger fronto-temporoparietal connectivity in Recognizers compared to Non-Recognizers, a finding which might support the hypothesized relationship between mirror-self recognition and self-awareness in infancy.
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Affiliation(s)
- Chiara Bulgarelli
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, UK; Department of Medical Physics and Bioengineering, University College London, UK.
| | - Anna Blasi
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, UK; Department of Medical Physics and Bioengineering, University College London, UK
| | - Carina C J M de Klerk
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, UK; Department of Psychology, University of Essex, UK
| | - John E Richards
- University of South Carolina, Institute for Mind and Brain, Department of Psychology, United States
| | - Antonia Hamilton
- Institute of Cognitive Neuroscience, University College London, UK
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15
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Lu W, Duan J, Orive-Miguel D, Herve L, Styles IB. Graph- and finite element-based total variation models for the inverse problem in diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2019; 10:2684-2707. [PMID: 31259044 PMCID: PMC6583327 DOI: 10.1364/boe.10.002684] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2019] [Revised: 03/29/2019] [Accepted: 04/17/2019] [Indexed: 05/18/2023]
Abstract
Total variation (TV) is a powerful regularization method that has been widely applied in different imaging applications, but is difficult to apply to diffuse optical tomography (DOT) image reconstruction (inverse problem) due to unstructured discretization of complex geometries, non-linearity of the data fitting and regularization terms, and non-differentiability of the regularization term. We develop several approaches to overcome these difficulties by: i) defining discrete differential operators for TV regularization using both finite element and graph representations; ii) developing an optimization algorithm based on the alternating direction method of multipliers (ADMM) for the non-differentiable and non-linear minimization problem; iii) investigating isotropic and anisotropic variants of TV regularization, and comparing their finite element (FEM)- and graph-based implementations. These approaches are evaluated on experiments on simulated data and real data acquired from a tissue phantom. Our results show that both FEM and graph-based TV regularization is able to accurately reconstruct both sparse and non-sparse distributions without the over-smoothing effect of Tikhonov regularization and the over-sparsifying effect of L1 regularization. The graph representation was found to out-perform the FEM method for low-resolution meshes, and the FEM method was found to be more accurate for high-resolution meshes.
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Affiliation(s)
- Wenqi Lu
- School of Computer Science, University of Birmingham,
UK
| | - Jinming Duan
- School of Computer Science, University of Birmingham,
UK
| | - David Orive-Miguel
- CEA, LETI, MINATEC Campus, F-38054 Grenoble,
France
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, 38000 Grenoble,
France
| | - Lionel Herve
- CEA, LETI, MINATEC Campus, F-38054 Grenoble,
France
| | - Iain B. Styles
- School of Computer Science, University of Birmingham,
UK
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16
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Mizuno M, Hiroyasu T, Hiwa S. A Functional NIRS Study of Brain Functional Networks Induced by Social Time Coordination. Brain Sci 2019; 9:brainsci9020043. [PMID: 30781426 PMCID: PMC6406867 DOI: 10.3390/brainsci9020043] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Revised: 02/12/2019] [Accepted: 02/14/2019] [Indexed: 11/16/2022] Open
Abstract
The ability to coordinate one’s behavior with the others’ behavior is essential to achieve a joint action in daily life. In this paper, the brain activity during synchronized tapping task was measured using functional near infrared spectroscopy (fNIRS) to investigate the relationship between time coordination and brain function. Furthermore, using brain functional network analysis based on graph theory, we examined important brain regions and network structures that serve as the hub when performing the synchronized tapping task. Using the data clustering method, two types of brain function networks were extracted and associated with time coordination, suggesting that they were involved in expectation and imitation behaviors.
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Affiliation(s)
- Megumi Mizuno
- Graduate School of Life and Medical Sciences, Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe, Kyoto 610-0394, Japan.
| | - Tomoyuki Hiroyasu
- Faculty of Life and Medical Sciences, Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe, Kyoto 610-0394, Japan.
| | - Satoru Hiwa
- Faculty of Life and Medical Sciences, Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe, Kyoto 610-0394, Japan.
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17
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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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18
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Li Y, Zhang H, Yu M, Yu W, Frederick BD, Tong Y. Systemic low-frequency oscillations observed in the periphery of healthy human subjects. JOURNAL OF BIOMEDICAL OPTICS 2018; 23:1-11. [PMID: 29729091 PMCID: PMC5935293 DOI: 10.1117/1.jbo.23.5.057001] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2017] [Accepted: 04/09/2018] [Indexed: 05/15/2023]
Abstract
This study investigated the relationships of systemic low-frequency oscillations (sLFOs) measured at different peripheral sites in resting state, during passive leg raising (PLR), and during a paced breathing (PB) test. Twenty-five healthy subjects (21 to 57 years old; males: 13 and females: 12) were recruited for these experiments. During the experiments, the fluctuations of oxyhemoglobin concentration were measured at six peripheral sites (left and right toes, fingertips, and earlobes) using a multichannel near-infrared spectroscopy instrument developed by our group. We applied cross-correlation and frequency component analyses on the data. The results showed that the sLFO signals in the symmetric peripheral sites were highly correlated, with time delays close to zero, whereas the correlation coefficients decreased between the sLFO signals of asymmetric sites, with delays up to several seconds. Furthermore, in PLR/PB tests, we found that PB caused wider and more robust changes in hemoglobin concentrations at peripheral sites compared to PLR. Among six peripheral sites, earlobes were the most sensitive to these perturbations, followed by fingertips, and then toes. Lastly, we showed that the perturbation signals may have different coupling mechanisms than the sLFO signals. The study deepened our understanding of the sLFO signals and establishes baseline measures for developing perfusion biomarkers to assess peripheral vascular integrity.
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Affiliation(s)
- Yingwei Li
- Yanshan University, School of Information Science and Engineering, Hebei, China
- McLean Hospital, Brain Imaging Center, Belmont, Massachusetts, United States
- Harvard Medical School, Department of Psychiatry, Boston, Massachusetts, United States
| | - Haibing Zhang
- Yanshan University, School of Information Science and Engineering, Hebei, China
| | - Meiling Yu
- Yanshan University, School of Information Science and Engineering, Hebei, China
| | - Weiwei Yu
- Yanshan University, School of Information Science and Engineering, Hebei, China
| | - Blaise deB Frederick
- McLean Hospital, Brain Imaging Center, Belmont, Massachusetts, United States
- Harvard Medical School, Department of Psychiatry, Boston, Massachusetts, United States
| | - Yunjie Tong
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
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19
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Lu W, Lighter D, Styles IB. L 1-norm based nonlinear reconstruction improves quantitative accuracy of spectral diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2018; 9:1423-1444. [PMID: 29675293 PMCID: PMC5905897 DOI: 10.1364/boe.9.001423] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 12/22/2017] [Accepted: 12/22/2017] [Indexed: 05/21/2023]
Abstract
Spectrally constrained diffuse optical tomography (SCDOT) is known to improve reconstruction in diffuse optical imaging; constraining the reconstruction by coupling the optical properties across multiple wavelengths suppresses artefacts in the resulting reconstructed images. In other work, L1-norm regularization has been shown to improve certain types of image reconstruction problems as its sparsity-promoting properties render it robust against noise and enable the preservation of edges in images, but because the L1-norm is non-differentiable, it is not always simple to implement. In this work, we show how to incorporate L1 regularization into SCDOT. Three popular algorithms for L1 regularization are assessed for application in SCDOT: iteratively reweighted least square algorithm (IRLS), alternating directional method of multipliers (ADMM), and fast iterative shrinkage-thresholding algorithm (FISTA). We introduce an objective procedure for determining the regularization parameter in these algorithms and compare their performance in simulated experiments, and in real data acquired from a tissue phantom. Our results show that L1 regularization consistently outperforms Tikhonov regularization in this application, particularly in the presence of noise.
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Affiliation(s)
- Wenqi Lu
- School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT,
UK
| | - Daniel Lighter
- Physical Sciences for Health Centre for Doctoral Training, University of Birmingham, Edgbaston, Birmingham B15 2TT,
UK
| | - Iain B. Styles
- School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT,
UK
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20
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Cao J, Liu H, Alexandrakis G. Modulating the resting-state functional connectivity patterns of language processing areas in the human brain with anodal transcranial direct current stimulation applied over the Broca's area. NEUROPHOTONICS 2018; 5:025002. [PMID: 29531963 PMCID: PMC5827696 DOI: 10.1117/1.nph.5.2.025002] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2017] [Accepted: 02/05/2018] [Indexed: 05/05/2023]
Abstract
Cortical circuit reorganization induced by anodal transcranial direct current stimulation (tDCS) over the Broca's area of the dominant language hemisphere in 13 healthy adults was quantified by functional near-infrared spectroscopy (fNIRS). Transient cortical reorganization patterns in steady-state functional connectivity (seed-based and graph theory analysis) and temporal functional connectivity (sliding window correlation analysis) were recorded before, during, and after applying high current tDCS (1 mA, 8 min). fNIRS connectivity mapping showed that tDCS induced significantly ([Formula: see text]) increased functional connectivity between Broca's area and its neighboring cortical regions while it simultaneously decreased the connectivity to remote cortical regions. Furthermore, the anodal stimulation caused significant increases to the functional connectivity variability (FCV) of remote cortical regions related to language processing. In addition to the high current tDCS, low current tDCS (0.5 mA, 2 min 40 s) was also applied to test whether the transient effects of lower stimulation current could qualitatively predict cortical connectivity alterations induced by the higher currents. Interestingly, low current tDCS could qualitatively predict the increase in clustering coefficient and FCV but not the enhancement of local connectivity. Our findings indicate the possibility of combining future studies fNIRS with tDCS at lower currents to help guide therapeutic interventions.
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Affiliation(s)
- Jianwei Cao
- University of Texas at Arlington and University of Texas Southwestern Medical Center at Dallas, Joint Graduate Program in Biomedical Engineering, Arlington, Texas
| | - Hanli Liu
- University of Texas at Arlington and University of Texas Southwestern Medical Center at Dallas, Joint Graduate Program in Biomedical Engineering, Arlington, Texas
| | - George Alexandrakis
- University of Texas at Arlington and University of Texas Southwestern Medical Center at Dallas, Joint Graduate Program in Biomedical Engineering, Arlington, Texas
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21
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FC-NIRS: A Functional Connectivity Analysis Tool for Near-Infrared Spectroscopy Data. BIOMED RESEARCH INTERNATIONAL 2015; 2015:248724. [PMID: 26539473 PMCID: PMC4619753 DOI: 10.1155/2015/248724] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2015] [Accepted: 06/18/2015] [Indexed: 11/17/2022]
Abstract
Functional near-infrared spectroscopy (fNIRS), a promising noninvasive imaging technique, has recently become an increasingly popular tool in resting-state brain functional connectivity (FC) studies. However, the corresponding software packages for FC analysis are still lacking. To facilitate fNIRS-based human functional connectome studies, we developed a MATLAB software package called “functional connectivity analysis tool for near-infrared spectroscopy data” (FC-NIRS). This package includes the main functions of fNIRS data preprocessing, quality control, FC calculation, and network analysis. Because this software has a friendly graphical user interface (GUI), FC-NIRS allows researchers to perform data analysis in an easy, flexible, and quick way. Furthermore, FC-NIRS can accomplish batch processing during data processing and analysis, thereby greatly reducing the time cost of addressing a large number of datasets. Extensive experimental results using real human brain imaging confirm the viability of the toolbox. This novel toolbox is expected to substantially facilitate fNIRS-data-based human functional connectome studies.
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22
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Tong Y, Hocke LM, Fan X, Janes AC, Frederick BD. Can apparent resting state connectivity arise from systemic fluctuations? Front Hum Neurosci 2015; 9:285. [PMID: 26029095 PMCID: PMC4432665 DOI: 10.3389/fnhum.2015.00285] [Citation(s) in RCA: 52] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2015] [Accepted: 04/30/2015] [Indexed: 11/16/2022] Open
Abstract
It is widely accepted that the fluctuations in resting state blood oxygenation level dependent (BOLD) functional MRI (fMRI) reflect baseline neuronal activation through neurovascular coupling; this data is used to infer functional connectivity in the human brain during rest. Consistent activation patterns, i.e., resting state networks (RSN) are seen across groups, conditions, and even species. In this study, we show that some of these patterns can also be generated from the dynamic, systemic, non-neuronal physiological low frequency oscillations (sLFOs) in the BOLD signal alone. We have previously used multimodal imaging to demonstrate the wide presence of the same sLFOs in the brain (BOLD) and periphery with different time delays. This study shows that these sLFOs from BOLD signals alone can give rise to stable spatial patterns, which can be detected during resting state analyses. We generated synthetic resting state data for 11 subjects based only on subject-specific, dynamic sLFO information obtained from resting state data using concurrent peripheral optical imaging or a novel recursive procedure. We compared the results obtained by performing a group independent component analysis (ICA) on this synthetic data (i.e., the result from simulation) to the results obtained from analysis of the real data. ICA detected most of the eight well-known RSNs, including visual, motor, and default mode networks (DMNs), in both the real and the synthetic data sets. These findings suggest that RSNs may reflect, to some extent, vascular anatomy associated with systemic fluctuations, rather than neuronal connectivity.
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Affiliation(s)
- Yunjie Tong
- McLean Imaging Center, McLean Hospital Belmont, MA, USA ; Department of Psychiatry, Harvard University Medical School Boston, MA, USA
| | - Lia M Hocke
- McLean Imaging Center, McLean Hospital Belmont, MA, USA ; Department of Biomedical Engineering, Tufts University Medford, MA, USA
| | - Xiaoying Fan
- McLean Imaging Center, McLean Hospital Belmont, MA, USA ; Department of Psychiatry, Harvard University Medical School Boston, MA, USA
| | - Amy C Janes
- McLean Imaging Center, McLean Hospital Belmont, MA, USA ; Department of Psychiatry, Harvard University Medical School Boston, MA, USA
| | - Blaise deB Frederick
- McLean Imaging Center, McLean Hospital Belmont, MA, USA ; Department of Psychiatry, Harvard University Medical School Boston, MA, USA
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23
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Abstract
Resting-state functional near-infrared spectroscopy (R-fNIRS) is an active area of interest and is currently attracting considerable attention as a new imaging tool for the study of resting-state brain function. Using variations in hemodynamic concentration signals, R-fNIRS measures the brain’s low-frequency spontaneous neural activity, combining the advantages of portability, low-cost, high temporal sampling rate and less physical burden to participants. The temporal synchronization of spontaneous neuronal activity in anatomically separated regions is referred to as resting-state functional connectivity (RSFC). In the past several years, an increasing body of R-fNIRS RSFC studies has led to many important findings about functional integration among local or whole-brain regions by measuring inter-regional temporal synchronization. Here, we summarize recent advances made in the R-fNIRS RSFC methodologies, from the detection of RSFC (e.g., seed-based correlation analysis, independent component analysis, whole-brain correlation analysis, and graph-theoretical topological analysis), to the assessment of RSFC performance (e.g., reliability, repeatability, and validity), to the application of RSFC in studying normal development and brain disorders. The literature reviewed here suggests that RSFC analyses based on R-fNIRS data are valid and reliable for the study of brain function in healthy and diseased populations, thus providing a promising imaging tool for cognitive science and clinics.
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Affiliation(s)
- Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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24
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Niu H, Li Z, Liao X, Wang J, Zhao T, Shu N, Zhao X, He Y. Test-retest reliability of graph metrics in functional brain networks: a resting-state fNIRS study. PLoS One 2013; 8:e72425. [PMID: 24039763 PMCID: PMC3767699 DOI: 10.1371/journal.pone.0072425] [Citation(s) in RCA: 71] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2013] [Accepted: 07/08/2013] [Indexed: 01/24/2023] Open
Abstract
Recent research has demonstrated the feasibility of combining functional near-infrared spectroscopy (fNIRS) and graph theory approaches to explore the topological attributes of human brain networks. However, the test-retest (TRT) reliability of the application of graph metrics to these networks remains to be elucidated. Here, we used resting-state fNIRS and a graph-theoretical approach to systematically address TRT reliability as it applies to various features of human brain networks, including functional connectivity, global network metrics and regional nodal centrality metrics. Eighteen subjects participated in two resting-state fNIRS scan sessions held ∼20 min apart. Functional brain networks were constructed for each subject by computing temporal correlations on three types of hemoglobin concentration information (HbO, HbR, and HbT). This was followed by a graph-theoretical analysis, and then an intraclass correlation coefficient (ICC) was further applied to quantify the TRT reliability of each network metric. We observed that a large proportion of resting-state functional connections (∼90%) exhibited good reliability (0.6< ICC <0.74). For global and nodal measures, reliability was generally threshold-sensitive and varied among both network metrics and hemoglobin concentration signals. Specifically, the majority of global metrics exhibited fair to excellent reliability, with notably higher ICC values for the clustering coefficient (HbO: 0.76; HbR: 0.78; HbT: 0.53) and global efficiency (HbO: 0.76; HbR: 0.70; HbT: 0.78). Similarly, both nodal degree and efficiency measures also showed fair to excellent reliability across nodes (degree: 0.52∼0.84; efficiency: 0.50∼0.84); reliability was concordant across HbO, HbR and HbT and was significantly higher than that of nodal betweenness (0.28∼0.68). Together, our results suggest that most graph-theoretical network metrics derived from fNIRS are TRT reliable and can be used effectively for brain network research. This study also provides important guidance on the choice of network metrics of interest for future applied research in developmental and clinical neuroscience.
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Affiliation(s)
- Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zhen Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xuhong Liao
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Jinhui Wang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xiaohu Zhao
- Imaging Department, Shanghai TongJi Hospital, TongJi University, Shanghai, China
- * E-mail: (YH); (XHZ)
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- * E-mail: (YH); (XHZ)
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25
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Wigal SB, Polzonetti CM, Stehli A, Gratton E. Phase synchronization of oxygenation waves in the frontal areas of children with attention-deficit hyperactivity disorder detected by optical diffusion spectroscopy correlates with medication. JOURNAL OF BIOMEDICAL OPTICS 2012; 17:127002. [PMID: 23232795 PMCID: PMC3518849 DOI: 10.1117/1.jbo.17.12.127002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
The beneficial effects of pharmacotherapy on children with attention-deficit hyperactivity disorder (ADHD) are well documented. We use near-infrared spectroscopy (NIRS) methodology to determine reorganization of brain neurovascular properties following the medication treatment. Twenty-six children with ADHD (ages six through 12) participated in a modified laboratory school protocol to monitor treatment response with lisdexamfetamine dimesylate (LDX; Vyvanse®, Shire US Inc.). All children refrained from taking medication for at least two weeks (washout period). To detect neurovascular reorganization, we measured changes in synchronization of oxy (HbO2) and deoxy (HHb) hemoglobin waves between the two frontal lobes. Participants without medication displayed average baseline HbO2 phase difference at about -7-deg. and HHb differences at about 240-deg.. This phase synchronization index changed after pharmacological intervention. Medication induced an average phase changes of HbO2 after first medication to 280-deg. and after medication optimization to 242-deg.. Instead first medication changed of the average HHb phase difference at 186-deg. and then after medication optimization to 120-deg. In agreement with findings of White et al., and Varela et al., we associated the phase synchronization differences of brain hemodynamics in children with ADHD with lobe specific hemodynamic reorganization of HbO2- and HHB oscillations following medication status.
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Affiliation(s)
- Sharon B. Wigal
- University of California Irvine, Child Development Center, Department of Pediatrics, 19722 MacArthur Boulevard Irvine, California 92612
| | - Chiara M. Polzonetti
- University of California Irvine, Child Development Center, Department of Pediatrics, 19722 MacArthur Boulevard Irvine, California 92612
| | - Annamarie Stehli
- University of California Irvine, Child Development Center, Department of Pediatrics, 19722 MacArthur Boulevard Irvine, California 92612
| | - Enrico Gratton
- University of California Irvine, Laboratory for Fluorescence Dynamics, Department of Biomedical Engineering, 3120 Natural Science II Building, Irvine, California 92697
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26
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Niu H, Wang J, Zhao T, Shu N, He Y. Revealing topological organization of human brain functional networks with resting-state functional near infrared spectroscopy. PLoS One 2012; 7:e45771. [PMID: 23029235 PMCID: PMC3454388 DOI: 10.1371/journal.pone.0045771] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2012] [Accepted: 08/22/2012] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND The human brain is a highly complex system that can be represented as a structurally interconnected and functionally synchronized network, which assures both the segregation and integration of information processing. Recent studies have demonstrated that a variety of neuroimaging and neurophysiological techniques such as functional magnetic resonance imaging (MRI), diffusion MRI and electroencephalography/magnetoencephalography can be employed to explore the topological organization of human brain networks. However, little is known about whether functional near infrared spectroscopy (fNIRS), a relatively new optical imaging technology, can be used to map functional connectome of the human brain and reveal meaningful and reproducible topological characteristics. RESULTS We utilized resting-state fNIRS (R-fNIRS) to investigate the topological organization of human brain functional networks in 15 healthy adults. Brain networks were constructed by thresholding the temporal correlation matrices of 46 channels and analyzed using graph-theory approaches. We found that the functional brain network derived from R-fNIRS data had efficient small-world properties, significant hierarchical modular structure and highly connected hubs. These results were highly reproducible both across participants and over time and were consistent with previous findings based on other functional imaging techniques. CONCLUSIONS Our results confirmed the feasibility and validity of using graph-theory approaches in conjunction with optical imaging techniques to explore the topological organization of human brain networks. These results may expand a methodological framework for utilizing fNIRS to study functional network changes that occur in association with development, aging and neurological and psychiatric disorders.
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Affiliation(s)
- Haijing Niu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People’s Republic of China
| | - Jinhui Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People’s Republic of China
| | - Tengda Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People’s Republic of China
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People’s Republic of China
| | - Yong He
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, People’s Republic of China
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Comparison of neural correlates of risk decision making between genders: An exploratory fNIRS study of the Balloon Analogue Risk Task (BART). Neuroimage 2012; 62:1896-911. [DOI: 10.1016/j.neuroimage.2012.05.030] [Citation(s) in RCA: 78] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2011] [Revised: 05/12/2012] [Accepted: 05/14/2012] [Indexed: 11/19/2022] Open
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28
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Zhan Y, Eggebrecht AT, Culver JP, Dehghani H. Singular value decomposition based regularization prior to spectral mixing improves crosstalk in dynamic imaging using spectral diffuse optical tomography. BIOMEDICAL OPTICS EXPRESS 2012; 3:2036-49. [PMID: 23024899 PMCID: PMC3447547 DOI: 10.1364/boe.3.002036] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/18/2012] [Revised: 08/02/2012] [Accepted: 08/04/2012] [Indexed: 05/24/2023]
Abstract
The spectrally constrained diffuse optical tomography (DOT) method relies on incorporating spectral prior information directly into the image reconstruction algorithm, thereby correlating the underlying optical properties across multiple wavelengths. Although this method has been shown to provide a solution that is stable, the use of conventional Tikhonov-type regularization techniques can lead to additional crosstalk between parameters, particularly in linear, single-step dynamic imaging applications. This is due mainly to the suboptimal regularization of the spectral Jacobian matrix, which smoothes not only the image-data space, but also the spectral mapping space. In this work a novel regularization technique based on the singular value decomposition (SVD) is presented that preserves the spectral prior information while regularizing the Jacobian matrix, leading to dramatically reduced crosstalk between the recovered parameters. Using simulated data, images of changes in oxygenated and deoxygenated hemoglobin concentrations are reconstructed via the SVD-based approach and compared with images reconstructed by using non-spectral and conventional spectral methods. In a 2D, two wavelength example, it is shown that the proposed approach provides a 98% reduction in crosstalk between recovered parameters as compared with conventional spectral reconstruction algorithms, and 60% as compared with non-spectrally constrained algorithms. Using a subject specific multilayered model of the human head, a noiseless dynamic simulation of cortical activation is performed to further demonstrate such improvement in crosstalk. However, with the addition of realistic noise in the data, both non-spectral and proposed algorithms perform similarly, indicating that the use of spectrally constrained reconstruction algorithms in dynamic DOT may be limited by the contrast of the signal as well as the noise characteristics of the system.
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Affiliation(s)
- Yuxuan Zhan
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
| | - Adam T. Eggebrecht
- Department of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St Louis, MO, 63110, USA
| | - Joseph P. Culver
- Department of Radiology, Washington University School of Medicine, 4525 Scott Avenue, St Louis, MO, 63110, USA
| | - Hamid Dehghani
- School of Computer Science, University of Birmingham, Birmingham, B15 2TT, UK
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29
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Li B, Zhou F, Luo Q, Li P. Altered resting-state functional connectivity after cortical spreading depression in mice. Neuroimage 2012; 63:1171-7. [PMID: 22986358 DOI: 10.1016/j.neuroimage.2012.08.024] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2012] [Revised: 07/18/2012] [Accepted: 08/08/2012] [Indexed: 11/17/2022] Open
Abstract
Cortical spreading depression (CSD) underlies some neurological disorders. Previous imaging work suggests that CSD is associated with functional and structural alterations in the cerebral cortex. However, the changes in cortical functional network following CSD are poorly understood. The present study examines the changes in resting-state function connectivity (RSFC) of the mouse sensorimotor cortex after the onset of CSD by using optical intrinsic signal imaging. Our results show that RSFC between ipsilateral sensorimotor cortex (the cortex where CSD spreads) and contralateral sensorimotor cortex (the cortex where CSD does not spread) was significantly reduced after CSD. Moreover, a marked connectivity increase was found after CSD not only within contralateral somatosensory cortex and contralateral motor cortex themselves, but also between contralateral somatosensory cortex and contralateral motor cortex. Amplitude of low-frequency fluctuation (ALFF) analysis revealed an increase in ALFF in the ipsilateral cortex but a decrease in the contralateral cortex after CSD, indicating different effects of CSD on the neural activity in the ipsilateral and contralateral sensorimotor cortexes. These results suggest that CSD would alter the RSFC in the sensorimotor cortexes, and functional connectivity analysis may help to understand the effect of CSD on the cerebral functional network.
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Affiliation(s)
- Bing Li
- Britton Chance Center of Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Wuhan 430074, PR China
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30
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Zhan Y, Eggebrecht AT, Culver JP, Dehghani H. Image quality analysis of high-density diffuse optical tomography incorporating a subject-specific head model. FRONTIERS IN NEUROENERGETICS 2012; 4:6. [PMID: 22654754 PMCID: PMC3359425 DOI: 10.3389/fnene.2012.00006] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/19/2012] [Accepted: 05/02/2012] [Indexed: 11/16/2022]
Abstract
High-density diffuse optical tomography (HD-DOT) methods have shown significant improvement in localization accuracy and image resolution compared to traditional topographic near infrared spectroscopy of the human brain. In this work we provide a comprehensive evaluation of image quality in visual cortex mapping via a simulation study with the use of an anatomical head model derived from MRI data of a human subject. A model of individual head anatomy provides the surface shape and internal structure that allow for the construction of a more realistic physical model for the forward problem, as well as the use of a structural constraint in the inverse problem. The HD-DOT model utilized here incorporates multiple source-detector separations with continuous-wave data with added noise based on experimental results. To evaluate image quality we quantify the localization error and localized volume at half maximum (LVHM) throughout a region of interest within the visual cortex and systematically analyze the use of whole-brain tissue spatial constraint within image reconstruction. Our results demonstrate that an image quality with less than 10 mm in localization error and 1000 m3 in LVHM can be obtained up to 13 mm below the scalp surface with a typical unconstrained reconstruction and up to 18 mm deep when a whole-brain spatial constraint based on the brain tissue is utilized.
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Affiliation(s)
- Yuxuan Zhan
- School of Computer Science, University of Birmingham Birmingham, UK
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31
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Quantitative comparison of resting-state functional connectivity derived from fNIRS and fMRI: A simultaneous recording study. Neuroimage 2012; 60:2008-18. [PMID: 22366082 DOI: 10.1016/j.neuroimage.2012.02.014] [Citation(s) in RCA: 92] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2011] [Revised: 02/02/2012] [Accepted: 02/07/2012] [Indexed: 11/23/2022] Open
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32
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Tong Y, Hocke LM, Frederick BD. Isolating the sources of widespread physiological fluctuations in functional near-infrared spectroscopy signals. JOURNAL OF BIOMEDICAL OPTICS 2011; 16:106005. [PMID: 22029352 PMCID: PMC3210192 DOI: 10.1117/1.3638128] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Physiological fluctuations at low frequency (<0.1 Hz) are prominent in functional near-infrared spectroscopy (fNIRS) measurements in both resting state and functional task studies. In this study, we used the high spatial resolution and full brain coverage of functional magnetic resonance imaging (fMRI) to understand the origins and commonalities of these fluctuations. Specifically, we applied a newly developed method, regressor interpolation at progressive time delays, to analyze concurrently recorded fNIRS and fMRI data acquired both in a resting state study and in a finger tapping study. The method calculates the voxelwise correlations between blood oxygen level dependent (BOLD) fMRI and fNIRS signals with different time shifts and localizes the areas in the brain that highly correlate with the fNIRS signal recorded at the surface of the head. The results show the wide spatial distribution of this physiological fluctuation in BOLD data, both in task and resting states. The brain areas that are highly correlated with global physiological fluctuations observed by fNIRS have a pattern that resembles the venous system of the brain, indicating the blood fluctuation from veins on the brain surface might strongly contribute to the overall fNIRS signal.
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Affiliation(s)
- Yunjie Tong
- McLean Hospital, Brain Imaging Center, 115 Mill Street, Belmont, Massachusetts 02478, USA.
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