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Nozawa T, Kondo M, Yamamoto R, Jeong H, Ikeda S, Sakaki K, Miyake Y, Ishikawa Y, Kawashima R. Prefrontal Inter-brain Synchronization Reflects Convergence and Divergence of Flow Dynamics in Collaborative Learning: A Pilot Study. FRONTIERS IN NEUROERGONOMICS 2021; 2:686596. [PMID: 38235236 PMCID: PMC10790863 DOI: 10.3389/fnrgo.2021.686596] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 05/11/2021] [Indexed: 01/19/2024]
Abstract
Flow is a highly motivated and affectively positive state in which a person is deeply engaged in an activity and feeling enjoyment from it. In collaborative activities, it would be optimal if all participants were in a state of flow. However, flow states fluctuate amongst individuals due to differences in the dynamics of motivation and cognition. To explore the possibility that inter-brain synchronization can provide a quantitative measure of the convergence and divergence of collective motivational dynamics, we conducted a pilot study to investigate the relationship between inter-brain synchronization and the interpersonal similarity of flow state dynamics during the collaborative learning process. In two English as a Foreign Language (EFL) classes, students were divided into groups of three-four and seated at desks facing each other while conducting a 60-min group work. In both classes, two groups with four members were randomly selected, and their medial prefrontal neural activities were measured simultaneously using wireless functional near-infrared spectroscopy (fNIRS) devices. Later the participants observed their own activities on recorded videos and retrospectively rated their subjective degree of flow state on a seven-point scale for each 2-min period. For the pairs of students whose neural activities were measured, the similarity of their flow experience dynamics was evaluated by the temporal correlation between their flow ratings. Prefrontal inter-brain synchronization of the same student pairs during group work was evaluated using wavelet transform coherence. Statistical analyses revealed that: (1) flow dynamics were significantly more similar for the student pairs within the same group compared to the pairs of students assigned across different groups; (2) prefrontal inter-brain synchronization in the relatively short time scale (9.3-13.9 s) was significantly higher for the within-group pairs than for the cross-group pairs; and (3) the prefrontal inter-brain synchronization at the same short time scale was significantly and positively correlated with the similarity of flow dynamics, even after controlling for the effects of within- vs. cross-group pair types from the two variables. These suggest that inter-brain synchronization can indeed provide a quantitative measure for converging and diverging collective motivational dynamics during collaborative learning, with higher inter-brain synchronization corresponding to a more convergent flow experience.
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Affiliation(s)
- Takayuki Nozawa
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Research Institute for the Earth Inclusive Sensing, Tokyo Institute of Technology, Tokyo, Japan
| | - Mutsumi Kondo
- Department of British and American Studies, Kyoto University of Foreign Studies, Kyoto, Japan
| | - Reiko Yamamoto
- Department of British and American Studies, Kyoto University of Foreign Studies, Kyoto, Japan
| | - Hyeonjeong Jeong
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Graduate School of International Cultural Studies, Tohoku University, Sendai, Japan
| | - Shigeyuki Ikeda
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
| | - Kohei Sakaki
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
| | - Yoshihiro Miyake
- Department of Computer Science, Tokyo Institute of Technology, Yokohama, Japan
| | - Yasushige Ishikawa
- Department of British and American Studies, Kyoto University of Foreign Studies, Kyoto, Japan
| | - Ryuta Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
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Devezas MÂM. Shedding light on neuroscience: Two decades of functional near-infrared spectroscopy applications and advances from a bibliometric perspective. J Neuroimaging 2021; 31:641-655. [PMID: 34002425 DOI: 10.1111/jon.12877] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 04/23/2021] [Accepted: 04/30/2021] [Indexed: 12/14/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is a noninvasive optical brain-imaging technique that detects changes in hemoglobin concentration in the cerebral cortex. fNIRS devices are safe, silent, portable, robust against motion artifacts, and have good temporal resolution. fNIRS is reliable and trustworthy, as well as an alternative and a complement to other brain-imaging modalities, such as electroencephalography or functional magnetic resonance imaging. Given these advantages, fNIRS has become a well-established tool for neuroscience research, used not only for healthy cortical activity but also as a biomarker during clinical assessment in individuals with schizophrenia, major depressive disorder, bipolar disease, epilepsy, Alzheimer's disease, vascular dementia, and cancer screening. Owing to its wide applicability, studies on fNIRS have increased exponentially over the last two decades. In this study, scientific publications indexed in the Web of Science databases were collected and a bibliometric-type methodology was developed. For this purpose, a comprehensive science mapping analysis, including top-ranked authors, journals, institutions, countries, and co-occurring keywords network, was conducted. From a total of 2310 eligible documents, 6028 authors and 531 journals published fNIRS-related papers, Fallgatter published the highest number of articles and was the most cited author. University of Tübingen in Germany has produced the most trending papers since 2000. USA was the most prolific country with the most active institutions, followed by China, Japan, Germany, and South Korea. The results also revealed global trends in emerging areas of research, such as neurodevelopment, aging, and cognitive and emotional assessment.
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Panachakel JT, Ramakrishnan AG. Decoding Covert Speech From EEG-A Comprehensive Review. Front Neurosci 2021; 15:642251. [PMID: 33994922 PMCID: PMC8116487 DOI: 10.3389/fnins.2021.642251] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Accepted: 03/18/2021] [Indexed: 11/13/2022] Open
Abstract
Over the past decade, many researchers have come up with different implementations of systems for decoding covert or imagined speech from EEG (electroencephalogram). They differ from each other in several aspects, from data acquisition to machine learning algorithms, due to which, a comparison between different implementations is often difficult. This review article puts together all the relevant works published in the last decade on decoding imagined speech from EEG into a single framework. Every important aspect of designing such a system, such as selection of words to be imagined, number of electrodes to be recorded, temporal and spatial filtering, feature extraction and classifier are reviewed. This helps a researcher to compare the relative merits and demerits of the different approaches and choose the one that is most optimal. Speech being the most natural form of communication which human beings acquire even without formal education, imagined speech is an ideal choice of prompt for evoking brain activity patterns for a BCI (brain-computer interface) system, although the research on developing real-time (online) speech imagery based BCI systems is still in its infancy. Covert speech based BCI can help people with disabilities to improve their quality of life. It can also be used for covert communication in environments that do not support vocal communication. This paper also discusses some future directions, which will aid the deployment of speech imagery based BCI for practical applications, rather than only for laboratory experiments.
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Affiliation(s)
- Jerrin Thomas Panachakel
- Medical Intelligence and Language Engineering Laboratory, Department of Electrical Engineering, Indian Institute of Science, Bangalore, India
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54
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Blanco B, Molnar M, Carreiras M, Collins-Jones LH, Vidal E, Cooper RJ, Caballero-Gaudes C. Group-level cortical functional connectivity patterns using fNIRS: assessing the effect of bilingualism in young infants. NEUROPHOTONICS 2021; 8:025011. [PMID: 34136588 PMCID: PMC8200331 DOI: 10.1117/1.nph.8.2.025011] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 05/25/2021] [Indexed: 05/27/2023]
Abstract
Significance: Early monolingual versus bilingual experience induces adaptations in the development of linguistic and cognitive processes, and it modulates functional activation patterns during the first months of life. Resting-state functional connectivity (RSFC) is a convenient approach to study the functional organization of the infant brain. RSFC can be measured in infants during natural sleep, and it allows to simultaneously investigate various functional systems. Adaptations have been observed in RSFC due to a lifelong bilingual experience. Investigating whether bilingualism-induced adaptations in RSFC begin to emerge early in development has important implications for our understanding of how the infant brain's organization can be shaped by early environmental factors. Aims: We attempt to describe RSFC using functional near-infrared spectroscopy (fNIRS) and to examine whether it adapts to early monolingual versus bilingual environments. We also present an fNIRS data preprocessing and analysis pipeline that can be used to reliably characterize RSFC in development and to reduce false positives and flawed results interpretations. Methods: We measured spontaneous hemodynamic brain activity in a large cohort ( N = 99 ) of 4-month-old monolingual and bilingual infants using fNIRS. We implemented group-level approaches based on independent component analysis to examine RSFC, while providing proper control for physiological confounds and multiple comparisons. Results: At the group level, we describe the functional organization of the 4-month-old infant brain in large-scale cortical networks. Unbiased group-level comparisons revealed no differences in RSFC between monolingual and bilingual infants at this age. Conclusions: High-quality fNIRS data provide a means to reliably describe RSFC patterns in the infant brain. The proposed group-level RSFC analyses allow to assess differences in RSFC across experimental conditions. An effect of early bilingual experience in RSFC was not observed, suggesting that adaptations might only emerge during explicit linguistic tasks, or at a later point in development.
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Affiliation(s)
- Borja Blanco
- Basque Center on Cognition, Brain, and Language, Donostia/San Sebastián, Spain
- University College London, Biomedical Optics Research Laboratory, DOT-HUB, London, United Kingdom
| | - Monika Molnar
- University of Toronto, Faculty of Medicine, Department of Speech-Language Pathology, Toronto, Ontario, Canada
| | - Manuel Carreiras
- Basque Center on Cognition, Brain, and Language, Donostia/San Sebastián, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Liam H. Collins-Jones
- University College London, Biomedical Optics Research Laboratory, DOT-HUB, London, United Kingdom
| | - Ernesto Vidal
- University College London, Biomedical Optics Research Laboratory, DOT-HUB, London, United Kingdom
| | - Robert J. Cooper
- University College London, Biomedical Optics Research Laboratory, DOT-HUB, London, United Kingdom
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55
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Long Y, Zheng L, Zhao H, Zhou S, Zhai Y, Lu C. Interpersonal Neural Synchronization during Interpersonal Touch Underlies Affiliative Pair Bonding between Romantic Couples. Cereb Cortex 2021; 31:1647-1659. [PMID: 33145593 DOI: 10.1093/cercor/bhaa316] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 09/27/2020] [Accepted: 09/28/2020] [Indexed: 11/13/2022] Open
Abstract
Interpersonal touch plays a key role in creating and maintaining affiliative pair bonds in romantic love. However, the neurocognitive mechanism of interpersonal touch in affiliative pair bonding remains unclear. Here, we hypothesized that interpersonal neural synchronization (INS) during interpersonal touch underlies affiliative pair bonding between romantic couples. To test this hypothesis, INS between heterosexual romantic couples and between opposite-sex friends was measured using functional near-infrared spectroscopy-based hyperscanning, while the pairs of participants touched or vocally communicated with each other. The results showed significantly greater INS between the mentalizing and sensorimotor neural systems of two members of a pair during interpersonal touch than during vocal communication between romantic couples but not between friends. Moreover, touch-induced INS was significantly correlated with the self-reported strength of romantic love. Finally, the results also showed that men's empathy positively modulated the association between touch-induced INS increase and the strength of romantic love. These findings support the idea that INS during interpersonal touch underlies affiliative pair bonding between romantic couples and suggest that empathy plays a modulatory role in the neurocognitive mechanism of interpersonal touch in affiliative pair bonding.
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Affiliation(s)
- Yuhang Long
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Lifen Zheng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Hui Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Siyuan Zhou
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Yu Zhai
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
| | - Chunming Lu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
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56
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Wu S, Cai S, Xiong G, Dong Z, Guo H, Han J, Ye T. The only-child effect in the neural and behavioral signatures of trust revealed by fNIRS hyperscanning. Brain Cogn 2021; 149:105692. [PMID: 33540359 DOI: 10.1016/j.bandc.2021.105692] [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] [Received: 06/27/2020] [Revised: 12/30/2020] [Accepted: 01/08/2021] [Indexed: 10/22/2022]
Abstract
In daily life, trust is important in interpersonal interactions. However, little is known about interpersonal brain synchronization with respect to trust; in particular, the differences between individuals with and without siblings are not clear. Therefore, this study applied functional near-infrared spectroscopy hyperscanning in a sequential reciprocal-trust task. We divided pairs of participants (strangers) into two groups according to their only-child status. The two strangers interacted with one another in an online trust game while their brain activities in the medial prefrontal cortex (mPFC) and the right temporoparietal junction (rTPJ) were measured. The behavioral results revealed that compared with the non-only-child group, the only-child group exhibited lower repayment, less reciprocation, and less cooperative decisions during the process. In addition, the brain imaging results showed that the interpersonal synchronization of the mPFC in the only-child group was significantly weaker than that in the non-only-child group. Our findings demonstrate neurobehavioral support for the only-child effect in terms of the trust by revealing that an only child shows less trust than does a non-only-child, resulting in lower inter-brain coherence.
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Affiliation(s)
- Shijing Wu
- School of Economics and Management, South China Normal University, Guangzhou, China; Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou, China
| | - Shenggang Cai
- School of Economics and Management, South China Normal University, Guangzhou, China; Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou, China
| | - Guanxing Xiong
- School of Economics and Management, South China Normal University, Guangzhou, China; Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou, China.
| | - Zhiqiang Dong
- School of Economics and Management, South China Normal University, Guangzhou, China; Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou, China.
| | - Huan Guo
- Institute of Analytical Psychology, City University of Macau, Macau, China; Department of Applied Psychology, Guangdong University of Finance & Economics, Guangzhou, China
| | - Jingshu Han
- Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou, China
| | - Tinglin Ye
- Key Lab for Behavioral Economic Science & Technology, South China Normal University, Guangzhou, China
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57
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Zhang J, Zhang J, Ren H, Liu Q, Du Z, Wu L, Sai L, Yuan Z, Mo S, Lin X. A Look Into the Power of fNIRS Signals by Using the Welch Power Spectral Estimate for Deception Detection. Front Hum Neurosci 2021; 14:606238. [PMID: 33536888 PMCID: PMC7848231 DOI: 10.3389/fnhum.2020.606238] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Accepted: 11/30/2020] [Indexed: 11/13/2022] Open
Abstract
Neuroimaging technologies have improved our understanding of deception and also exhibit their potential in revealing the origins of its neural mechanism. In this study, a quantitative power analysis method that uses the Welch power spectrum estimation of functional near-infrared spectroscopy (fNIRS) signals was proposed to examine the brain activation difference between the spontaneous deceptive behavior and controlled behavior. The power value produced by the model was applied to quantify the activity energy of brain regions, which can serve as a neuromarker for deception detection. Interestingly, the power analysis results generated from the Welch spectrum estimation method demonstrated that the spontaneous deceptive behavior elicited significantly higher power than that from the controlled behavior in the prefrontal cortex. Meanwhile, the power findings also showed significant difference between the spontaneous deceptive behavior and controlled behavior, indicating that the reward system was only involved in the deception. The proposed power analysis method for processing fNIRS data provides us an additional insight to understand the cognitive mechanism of deception.
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Affiliation(s)
- Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Jingyue Zhang
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Houhua Ren
- China Mobile (Chengdu) Industrial Research Institute, Chengdu, China
| | - Qihong Liu
- College of Biomedical Engineering, Sichuan University, Chengdu, China
| | - Zhengcong Du
- School of Information Science and Technology, Xichang University, Xichang, China
| | - Lan Wu
- Sichuan Cancer Hospital and Institute, Chengdu, China
| | - Liyang Sai
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, China.,Department of Psychology, Zhejiang Normal University, Jinhua, China
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Taipa, China
| | - Site Mo
- College of Electrical Engineering, Sichuan University, Chengdu, China
| | - Xiaohong Lin
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, China
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58
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Struckmann W, Persson J, Gingnell M, Weigl W, Wass C, Bodén R. Unchanged Cognitive Performance and Concurrent Prefrontal Blood Oxygenation After Accelerated Intermittent Theta-Burst Stimulation in Depression: A Sham-Controlled Study. Front Psychiatry 2021; 12:659571. [PMID: 34276437 PMCID: PMC8278060 DOI: 10.3389/fpsyt.2021.659571] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 06/03/2021] [Indexed: 12/25/2022] Open
Abstract
Aim: Intermittent theta-burst stimulation (iTBS) delivered over the dorsomedial prefrontal cortex (DMPFC) has shown promise as a treatment for anhedonia and amotivation in patients with depression. Here, we investigated whether this protocol modulates cognitive performance and concurrent prefrontal blood oxygenation. We also examined whether depressed patients exhibit cognitive dysfunction and prefrontal hypoactivity at baseline compared to healthy controls. Methods: This sham-controlled study comprises 52 patients randomized to either active or sham accelerated iTBS over the DMPFC (applied twice daily) for 10 consecutive treatment days, and 55 healthy controls. Cognitive performance was assessed at baseline and once again 4 weeks later using a cognitive test battery targeting attention, inhibitory control, and numerical, verbal, and visual working memory. Concurrent prefrontal oxygenated hemoglobin (oxy-Hb) was captured with functional near-infrared spectroscopy. Results: Active iTBS over DMPFC did not affect cognitive performance or concurrent oxy-Hb change compared to sham iTBS in patients with depression. Compared to controls, patients at baseline showed impaired performance in the Trail Making Test, the Rey Auditory Verbal Learning Test, the Animal Naming Test, and the Digit Symbol Substitution Test, however no difference in prefrontal oxy-Hb was observed. Conclusion: Patients with treatment-resistant depression displayed cognitive deficits, however without prefrontal hypoactivity, compared to healthy controls at baseline. iTBS treatment did not alter cognitive performance, nor concurrent prefrontal blood oxygenation, in patients. Taken together, iTBS can likely be considered a cognitively safe treatment option in this sample of patients.
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Affiliation(s)
- Wiebke Struckmann
- Psychiatry, Department of Neuroscience, Uppsala University, Uppsala, Sweden
| | - Jonas Persson
- Psychiatry, Department of Neuroscience, Uppsala University, Uppsala, Sweden
| | - Malin Gingnell
- Psychiatry, Department of Neuroscience, Uppsala University, Uppsala, Sweden.,Department of Psychology, Uppsala University, Uppsala, Sweden
| | - Wojciech Weigl
- Anaesthesiology and Intensive Care, Department of Surgical Science, Uppsala University, Uppsala University Hospital, Uppsala, Sweden
| | - Caroline Wass
- Department of Pharmacology, University of Gothenburg, Göteborg, Sweden
| | - Robert Bodén
- Psychiatry, Department of Neuroscience, Uppsala University, Uppsala, Sweden
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Hou X, Zhang Z, Zhao C, Duan L, Gong Y, Li Z, Zhu C. NIRS-KIT: a MATLAB toolbox for both resting-state and task fNIRS data analysis. NEUROPHOTONICS 2021; 8:010802. [PMID: 33506071 PMCID: PMC7829673 DOI: 10.1117/1.nph.8.1.010802] [Citation(s) in RCA: 78] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Accepted: 01/05/2021] [Indexed: 05/27/2023]
Abstract
Significance: Functional near-infrared spectroscopy (fNIRS) has been widely used to probe human brain function during task state and resting state. However, the existing analysis toolboxes mainly focus on task activation analysis, few software packages can assist resting-state fNIRS studies. Aim: We aimed to provide a versatile and easy-to-use toolbox to perform analysis for both resting state and task fNIRS. Approach: We developed a MATLAB toolbox called NIRS-KIT that works for both resting-state analysis and task activation detection. Results: NIRS-KIT implements common and necessary processing steps for performing fNIRS data analysis, including data preparation, quality control, preprocessing, individual-level analysis, group-level statistics with several popular statistical models, and multiple comparison correction methods, and finally results visualization. For resting-state fNIRS analysis, functional connectivity analysis, graph theory-based network analysis, and amplitude of low-frequency fluctuations analysis are provided. Additionally, NIRS-KIT also supports activation analysis for task fNIRS. Conclusions: NIRS-KIT offers an open source tool for researchers to analyze resting-state and/or task fNIRS data in one suite. It contains several key features: (1) good compatibility, supporting multiple fNIRS recording systems, data formats of NIRS-SPM and Homer2, and the shared near-infrared spectroscopy format data format recommended by the fNIRS society; (2) flexibility, supporting customized preprocessing scripts; (3) ease-to-use, allowing processing fNIRS signals in batch manner with user-friendly graphical user interfaces; and (4) feature-packed data viewing and result visualization. We anticipate that this NIRS-KIT will facilitate the development of the fNIRS field.
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Affiliation(s)
- Xin Hou
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Zong Zhang
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Chen Zhao
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Lian Duan
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Yilong Gong
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
| | - Zheng Li
- Beijing Normal University at Zhuhai, Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and Learning, Zhuhai, China
- Beijing Normal University, Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing, China
| | - Chaozhe Zhu
- Beijing Normal University, IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing, China
- Beijing Normal University, Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing, China
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60
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Gut microbiota composition is associated with newborn functional brain connectivity and behavioral temperament. Brain Behav Immun 2021; 91:472-486. [PMID: 33157257 DOI: 10.1016/j.bbi.2020.11.003] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/27/2020] [Accepted: 11/01/2020] [Indexed: 12/12/2022] Open
Abstract
The gut microbiome appears to play an important role in human health and disease. However, only little is known about how variability in the gut microbiome contributes to individual differences during early and sensitive stages of brain and behavioral development. The current study examined the link between gut microbiome, brain, and behavior in newborn infants (N = 63; M [age] = 25 days). Infant gut microbiome diversity was measured from stool samples using metagenomic sequencing, infant functional brain network connectivity was assessed using a resting state functional near infrared spectroscopy (rs-fNIRS) procedure, and infant behavioral temperament was assessed using parental report. Our results show that gut microbiota composition is linked to individual variability in brain network connectivity, which in turn mediated individual differences in behavioral temperament, specifically negative emotionality, among infants. Furthermore, virulence factors, possibly indexing pathogenic activity, were associated with differences in brain network connectivity linked to negative emotionality. These findings provide novel insights into the early developmental origins of the gut microbiome-brain axis and its association with variability in important behavioral traits. This suggests that the gut microbiome is an important biological factor to consider when studying human development and health.
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61
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Zheng X, Luo J, Deng L, Li B, Li L, Huang DF, Song R. Detection of functional connectivity in the brain during visuo-guided grip force tracking tasks: A functional near-infrared spectroscopy study. J Neurosci Res 2020; 99:1108-1119. [PMID: 33368535 DOI: 10.1002/jnr.24769] [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: 11/17/2020] [Accepted: 11/23/2020] [Indexed: 11/10/2022]
Abstract
The functional connectivity (FC) between multiple brain regions during tasks is currently gradually being explored with functional near-infrared spectroscopy (fNIRS). However, the FC present during grip force tracking tasks performed under visual feedback remains unclear. In the present study, we used fNIRS to measure brain activity during resting states and grip force tracking tasks at 25%, 50%, and 75% of maximum voluntary contraction (MVC) in 11 healthy subjects, and the activity was measured from four target brain regions: the left prefrontal cortex (lPFC), right prefrontal cortex (rPFC), left sensorimotor cortex (lSMC), and right sensorimotor cortex (rSMC). We determined the FC between these regions utilizing three different methods: Pearson's correlation method, partial correlation method, and a pairwise maximum entropy model (MEM). The results showed that the FC of lSMC-rSMC and lPFC-rPFC (interhemispheric homologous pairs) were significantly stronger than those of other brain region pairs. Moreover, FC of lPFC-rPFC was strengthened during the 75% MVC task compared to the other task states and the resting states. The FC of lSMC-lPFC and rSMC-rPFC (intrahemispheric region pairs) strengthened with a higher task load. The results provided new insights into the FC between brain regions during visuo-guided grip force tracking tasks.
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Affiliation(s)
- Xinyi Zheng
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Jie Luo
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Lingyun Deng
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Bing Li
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
| | - Le Li
- Department of Rehabilitation Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Dong Feng Huang
- Guangdong Engineering Technology Research Center for Rehabilitation Medicine and Clinical Translation, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Xinhua College, Sun Yat-sen University, Guangzhou, China
| | - Rong Song
- Key Laboratory of Sensing Technology and Biomedical Instrument of Guangdong Province, Guangdong Provincial Engineering and Technology Center of Advanced and Portable Medical Devices, School of Biomedical Engineering, Sun Yat-sen University, Guangzhou, China
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62
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Chen Y, Tang J, Chen Y, Farrand J, Craft MA, Carlson BW, Yuan H. Amplitude of fNIRS Resting-State Global Signal Is Related to EEG Vigilance Measures: A Simultaneous fNIRS and EEG Study. Front Neurosci 2020; 14:560878. [PMID: 33343275 PMCID: PMC7744746 DOI: 10.3389/fnins.2020.560878] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2020] [Accepted: 11/11/2020] [Indexed: 12/21/2022] Open
Abstract
Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05-0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.
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Affiliation(s)
- Yuxuan Chen
- School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, United States
| | - Julia Tang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Yafen Chen
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Jesse Farrand
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
| | - Melissa A. Craft
- Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Barbara W. Carlson
- Fran and Earl Ziegler College of Nursing, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States
- Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States
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Karunakaran KD, Peng K, Berry D, Green S, Labadie R, Kussman B, Borsook D. NIRS measures in pain and analgesia: Fundamentals, features, and function. Neurosci Biobehav Rev 2020; 120:335-353. [PMID: 33159918 DOI: 10.1016/j.neubiorev.2020.10.023] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 09/28/2020] [Accepted: 10/19/2020] [Indexed: 02/06/2023]
Abstract
Current pain assessment techniques based only on clinical evaluation and self-reports are not objective and may lead to inadequate treatment. Having a functional biomarker will add to the clinical fidelity, diagnosis, and perhaps improve treatment efficacy in patients. While many approaches have been deployed in pain biomarker discovery, functional near-infrared spectroscopy (fNIRS) is a technology that allows for non-invasive measurement of cortical hemodynamics. The utility of fNIRS is especially attractive given its ability to detect specific changes in the somatosensory and high-order cortices as well as its ability to measure (1) brain function similar to functional magnetic resonance imaging, (2) graded responses to noxious and innocuous stimuli, (3) analgesia, and (4) nociception under anesthesia. In this review, we evaluate the utility of fNIRS in nociception/pain with particular focus on its sensitivity and specificity, methodological advantages and limitations, and the current and potential applications in various pain conditions. Everything considered, fNIRS technology could enhance our ability to evaluate evoked and persistent pain across different age groups and clinical populations.
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Affiliation(s)
- Keerthana Deepti Karunakaran
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States.
| | - Ke Peng
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States; Département en Neuroscience, Centre de Recherche du CHUM, l'Université de Montréal Montreal, QC, Canada
| | - Delany Berry
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States
| | - Stephen Green
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States
| | - Robert Labadie
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States
| | - Barry Kussman
- Division of Cardiac Anesthesia, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States
| | - David Borsook
- Center for Pain and the Brain, Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, United States.
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Jamadar SD, Ward PGD, Close TG, Fornito A, Premaratne M, O'Brien K, Stäb D, Chen Z, Shah NJ, Egan GF. Simultaneous BOLD-fMRI and constant infusion FDG-PET data of the resting human brain. Sci Data 2020; 7:363. [PMID: 33087725 PMCID: PMC7578808 DOI: 10.1038/s41597-020-00699-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 09/11/2020] [Indexed: 12/13/2022] Open
Abstract
Simultaneous [18 F]-fluorodeoxyglucose positron emission tomography and functional magnetic resonance imaging (FDG-PET/fMRI) provides the capability to image two sources of energetic dynamics in the brain - cerebral glucose uptake and the cerebrovascular haemodynamic response. Resting-state fMRI connectivity has been enormously useful for characterising interactions between distributed brain regions in humans. Metabolic connectivity has recently emerged as a complementary measure to investigate brain network dynamics. Functional PET (fPET) is a new approach for measuring FDG uptake with high temporal resolution and has recently shown promise for assessing the dynamics of neural metabolism. Simultaneous fMRI/fPET is a relatively new hybrid imaging modality, with only a few biomedical imaging research facilities able to acquire FDG PET and BOLD fMRI data simultaneously. We present data for n = 27 healthy young adults (18-20 yrs) who underwent a 95-min simultaneous fMRI/fPET scan while resting with their eyes open. This dataset provides significant re-use value to understand the neural dynamics of glucose metabolism and the haemodynamic response, the synchrony, and interaction between these measures, and the development of new single- and multi-modality image preparation and analysis procedures.
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Affiliation(s)
- Sharna D Jamadar
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia.
- Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne, Australia.
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia.
| | - Phillip G D Ward
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne, Australia
| | - Thomas G Close
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Australian National Imaging Facility, Brisbane, QLD, Australia
| | - Alex Fornito
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - Malin Premaratne
- Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC, Australia
| | - Kieran O'Brien
- Siemens Healthineers, Siemens Healthcare Pty Ltd, Bayswater, VIC, 3153, Australia
| | - Daniel Stäb
- Siemens Healthineers, Siemens Healthcare Pty Ltd, Bayswater, VIC, 3153, Australia
| | - Zhaolin Chen
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Department of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC, Australia
| | - N Jon Shah
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Institute of Neuroscience and Medicine, Forschungszentrum Jülich, 52425, Jülich, Germany
| | - Gary F Egan
- Monash Biomedical Imaging, Monash University, Melbourne, VIC, Australia
- Australian Research Council Centre of Excellence for Integrative Brain Function, Melbourne, Australia
- Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
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65
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Lu K, Yu T, Hao N. Creating while taking turns, the choice to unlocking group creative potential. Neuroimage 2020; 219:117025. [DOI: 10.1016/j.neuroimage.2020.117025] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Revised: 05/09/2020] [Accepted: 06/03/2020] [Indexed: 01/29/2023] Open
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Classification of Schizophrenia by Seed-based Functional Connectivity using Prefronto-Temporal Functional Near Infrared Spectroscopy. J Neurosci Methods 2020; 344:108874. [PMID: 32710923 DOI: 10.1016/j.jneumeth.2020.108874] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 07/13/2020] [Accepted: 07/20/2020] [Indexed: 11/24/2022]
Abstract
BACKGROUND Schizophrenia is one of the most serious mental disorders. Currently, the diagnosis of schizophrenia mainly relies on scales and doctors' experience. Recently, functional near infrared spectroscopy (fNIRS) has been used to distinguish schizophrenia from other mental disorders. The conventional classification methods utilized time-course features from single or multiple fNIRS channels. NEW METHOD The fNIRS data were obtained from 52 channels covering the frontotemporal cortices in 200 patients with schizophrenia and 100 healthy subjects during a Chinese verbal fluency task. The channels with significant between-group differences were selected as the seeds. Functional connectivity (FC) was calculated for each seed, and FCs with significant between-group differences were selected as the features for classification. RESULTS The proposed method reduced the number of channels to 26 while achieving overall classification accuracy, sensitivity and specificity values as high as 89.67%, 93.00% and 86.00%, respectively, outperforming most of the reported results. The superior performance was attributed to the cross-scale neurological changes related to schizophrenia, which were employed by the classification method. In addition, the method provided multiple classification criteria with similar accuracy, consequently increasing the flexibility and reliability of the results. COMPARISON WITH EXISTING METHODS This is the first fNIRS study to classify schizophrenia based on FCs. This method integrated information from regional modulation, segregation and integration. The classification performance outperformed most of the classification methods described in previous studies. CONCLUSIONS Our findings suggest a reliable method with a high level of accuracy and a low level of instrumental complexity to identify patients with schizophrenia.
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Lu K, Xue H, Nozawa T, Hao N. Cooperation Makes a Group be More Creative. Cereb Cortex 2020; 29:3457-3470. [PMID: 30192902 DOI: 10.1093/cercor/bhy215] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 06/20/2018] [Indexed: 12/21/2022] Open
Abstract
This study investigated how cooperative and competitive interaction modes affect the group creative performance. The participants were recruited as dyads to solve 2 problems either demanding divergent thinking (alternative uses task, AUT) or not (object characteristic task, OCT). The dyads solved 1 of the 2 problems in the cooperative mode and the other in the competitive mode. Functional near-infrared spectroscopy (fNIRS)-based hyperscanning was used to record their neural activities in the prefrontal and right temporal-parietal junction (r-TPJ) regions. Results revealed the dyads showed higher AUT fluency, AUT originality, OCT fluency, and cooperation level in the cooperative mode than in the competitive mode. The fNIRS data revealed increased (task-baseline) interpersonal brain synchronization (IBS) in the right dorsolateral prefrontal cortex (r-DLPFC) and r-TPJ, only for dyads in the AUT/cooperation condition. In both r-DLPFC and r-TPJ, the IBS of dyads in the AUT/cooperation condition was stronger than in the AUT/competition and OCT/cooperation. Moreover, a stronger IBS was evoked between the regions in prefrontal and posterior temporal regions in the AUT/cooperation condition, as compared with the competition mode. These findings suggest that enhanced IBS may underlie the positive effects of cooperation as compared with the competition in terms of group creativity.
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Affiliation(s)
- Kelong Lu
- Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Hua Xue
- Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Takayuki Nozawa
- Collaborative Research Center for Happiness Co-Creation Society through Intelligent Communications, Tokyo Institute of Technology, Tokyo, Japan
| | - Ning Hao
- Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
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68
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Duan L, Feng Q, Xu P. Using Functional Near-Infrared Spectroscopy to Assess Brain Activation Evoked by Guilt and Shame. Front Hum Neurosci 2020; 14:197. [PMID: 32587508 PMCID: PMC7298148 DOI: 10.3389/fnhum.2020.00197] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 05/01/2020] [Indexed: 11/13/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is a promising brain imaging modality for studying the neural substrates of moral emotions. However, the feasibility of using fNIRS to measure moral emotions has not been established. In the present study, we used fNIRS to detect the brain activation evoked by two typical moral emotions-guilt and shame. We presented the participants with guilt and shame context to evoke emotional responses and measured the brain activity by using fNIRS. The univariate general linear model analysis showed significant activations for both emotions in the orbitofrontal cortex, dorsolateral prefrontal cortex, and middle temporal gyrus, and specific activation for guilt in the right temporoparietal junction. The multivariate classification analysis showed an overall recognition accuracy of 52.50%, which was significantly higher than the chance level in classifying the guilt, shame, and neutral emotions. These results suggested the feasibility of using fNIRS to assess the brain activation evoked by guilt and shame and demonstrated the potentials of fNIRS in studying the neural correlates of moral emotions.
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Affiliation(s)
- Lian Duan
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China
| | - Qiudi Feng
- School of Policing Studies, Shanghai University of Political Science and Law, Shanghai, China
| | - Pengfei Xu
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Center for Brain Disorders and Cognitive Sciences, Shenzhen University, Shenzhen, China
- Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China
- Great Bay Neuroscience and Technology Research Institute (Hong Kong), Hong Kong, China
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69
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Mohammadzadeh L, Latifi H, Khaksar S, Feiz MS, Motamedi F, Asadollahi A, Ezzatpour M. Measuring the Frequency-Specific Functional Connectivity Using Wavelet Coherence Analysis in Stroke Rats Based on Intrinsic Signals. Sci Rep 2020; 10:9429. [PMID: 32523058 PMCID: PMC7286921 DOI: 10.1038/s41598-020-66246-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2019] [Accepted: 05/17/2020] [Indexed: 12/28/2022] Open
Abstract
Optical intrinsic signal imaging (OISi) method is an optical technique to evaluate the functional connectivity (FC) of the cortex in animals. Already, using OISi, the FC of the cortex has been measured in time or frequency domain separately, and at frequencies below 0.08 Hz, which is not in the frequency range of hemodynamic oscillations which are able to track fast cortical events, including neurogenic, myogenic, cardiac and respiratory activities. In the current work, we calculated the wavelet coherence (WC) transform of the OISi time series to evaluate the cerebral response changes in the stroke rats. Utilizing WC, we measured FC at frequencies up to 4.5 Hz, and could monitor the time and frequency dependency of the FC simultaneously. The results showed that the WC of the brain diminished significantly in ischemic motor and somatosensory cortices. According to the statistical results, the signal amplitude, responsive area size, correlation, and wavelet coherence of the motor and the somatosensory cortices for stroke hemisphere were found to be significantly lower compared to the healthy hemisphere. The obtained results confirm that the OISi-based WC analysis is an efficient method to diagnose the relative severity of infarction and the size of the infarcted region after ischemic stroke.
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Affiliation(s)
- Leila Mohammadzadeh
- Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, 1983969411, Iran
| | - Hamid Latifi
- Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, 1983969411, Iran. .,Department of Physics, Shahid Beheshti University, Tehran, 1983963113, Iran.
| | - Sepideh Khaksar
- Department of Plant Sciences, Faculty of Biological Sciences, Alzahra University, Tehran, 1993893973, Iran
| | - Mohammad-Sadegh Feiz
- Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, 1983969411, Iran
| | - Fereshteh Motamedi
- Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Tehran, 1983963113, Iran
| | - Amir Asadollahi
- Laser and Plasma Research Institute, Shahid Beheshti University, Tehran, 1983969411, Iran
| | - Marzieh Ezzatpour
- Department of Physics, Shahid Beheshti University, Tehran, 1983963113, Iran
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Nguyen NT, Takakura H, Nishijo H, Ueda N, Ito S, Fujisaka M, Akaogi K, Shojaku H. Cerebral Hemodynamic Responses to the Sensory Conflict Between Visual and Rotary Vestibular Stimuli: An Analysis With a Multichannel Near-Infrared Spectroscopy (NIRS) System. Front Hum Neurosci 2020; 14:125. [PMID: 32372931 PMCID: PMC7187689 DOI: 10.3389/fnhum.2020.00125] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2019] [Accepted: 03/19/2020] [Indexed: 12/11/2022] Open
Abstract
Sensory conflict among visual, vestibular, and somatosensory information induces vertiginous sensation and postural instability. To elucidate the cognitive mechanisms of the integration between the visual and vestibular cues in humans, we analyzed the cortical hemodynamic responses during sensory conflict between visual and horizontal rotatory vestibular stimulation using a multichannel near-infrared spectroscopy (NIRS) system. The subjects sat on a rotatory chair that was accelerated at 3°/s2 for 20 s to the right or left, kept rotating at 60°/s for 80 s, and then decelerated at 3°/s2 for 20 s. The subjects were instructed to watch white stripes projected on a screen surrounding the chair during the acceleration and deceleration periods. The white stripes moved in two ways; in the "congruent" condition, the stripes moved in the opposite direction of chair rotation at 3°/s2 (i.e., natural visual stimulation), whereas in the "incongruent" condition, the stripes moved in the same direction of chair rotation at 3°/s2 (i.e., conflicted visual stimulation). The cortical hemodynamic activity was recorded from the bilateral temporoparietal regions. Statistical analyses using NIRS-SPM software indicated that hemodynamic activity increased in the bilateral temporoparietal junctions (TPJs) and human MT+ complex, including the medial temporal (MT) area and medial superior temporal (MST) area in the incongruent condition. Furthermore, the subjective strength of the vertiginous sensation was negatively correlated with hemodynamic activity in the dorsal part of the supramarginal gyrus (SMG) in and around the intraparietal sulcus (IPS). These results suggest that sensory conflict between the visual and vestibular stimuli promotes cortical cognitive processes in the cortical network consisting of the TPJ, the medial temporal gyrus (MTG), and IPS, which might contribute to self-motion perception to maintain a sense of balance or equilibrioception during sensory conflict.
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Affiliation(s)
- Nghia Trong Nguyen
- Department of Otorhinolaryngology, Head and Neck Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Hiromasa Takakura
- Department of Otorhinolaryngology, Head and Neck Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Hisao Nishijo
- System Emotional Science Laboratory, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Naoko Ueda
- Department of Otorhinolaryngology, Head and Neck Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Shinsuke Ito
- Department of Otorhinolaryngology, Head and Neck Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Michiro Fujisaka
- Department of Otorhinolaryngology, Head and Neck Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Katsuichi Akaogi
- Department of Otorhinolaryngology, Toyama Red Cross Hospital, Toyama, Japan
| | - Hideo Shojaku
- Department of Otorhinolaryngology, Head and Neck Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
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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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Zhu L, Haghani S, Najafizadeh L. On fractality of functional near-infrared spectroscopy signals: analysis and applications. NEUROPHOTONICS 2020; 7:025001. [PMID: 32377544 PMCID: PMC7189210 DOI: 10.1117/1.nph.7.2.025001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 04/13/2020] [Indexed: 06/11/2023]
Abstract
Significance: The human brain is a highly complex system with nonlinear, dynamic behavior. A majority of brain imaging studies employing functional near-infrared spectroscopy (fNIRS), however, have considered only the spatial domain and have ignored the temporal properties of fNIRS recordings. Methods capable of revealing nonlinearities in fNIRS recordings can provide new insights about how the brain functions. Aim: The temporal characteristics of fNIRS signals are explored by comprehensively investigating their fractal properties. Approach: Fractality of fNIRS signals is analyzed using scaled windowed variance (SWV), as well as using visibility graph (VG), a method which converts a given time series into a graph. Additionally, the fractality of fNIRS signals obtained under resting-state and task-based conditions is compared, and the application of fractality in differentiating brain states is demonstrated for the first time via various classification approaches. Results: Results from SWV analysis show the existence of high fractality in fNIRS recordings. It is shown that differences in the temporal characteristics of fNIRS signals related to task-based and resting-state conditions can be revealed via the VGs constructed for each case. Conclusions: fNIRS recordings, regardless of the experimental conditions, exhibit high fractality. Furthermore, VG-based metrics can be employed to differentiate rest and task-execution brain states.
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Affiliation(s)
- Li Zhu
- Rutgers University, Integrated Systems and NeuroImaging Laboratory, Department of Electrical and Computer Engineering, Piscataway, New Jersey, United States
| | - Sasan Haghani
- University of The District of Columbia, Department of Electrical and Computer Engineering, Washington DC, United States
| | - Laleh Najafizadeh
- Rutgers University, Integrated Systems and NeuroImaging Laboratory, Department of Electrical and Computer Engineering, Piscataway, New Jersey, United States
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Yu JW, Lim SH, Kim B, Kim E, Kim K, Kyu Park S, Seok Byun Y, Sakong J, Choi JW. Prefrontal functional connectivity analysis of cognitive decline for early diagnosis of mild cognitive impairment: a functional near-infrared spectroscopy study. BIOMEDICAL OPTICS EXPRESS 2020; 11:1725-1741. [PMID: 32341843 PMCID: PMC7173911 DOI: 10.1364/boe.382197] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/01/2019] [Revised: 02/16/2020] [Accepted: 02/18/2020] [Indexed: 05/20/2023]
Abstract
Cognitive decline (CD) is a major symptom of mild cognitive impairment (MCI). Patients with MCI have an increased likelihood of developing Alzheimer's disease (AD). Although a cure for AD is currently lacking, medication therapies and/or daily training in the early stage can alleviate disease progression and improve patients' quality of life. Accordingly, investigating CD-related biomarkers via brain imaging devices is crucial for early diagnosis. In particular, "portable" brain imaging devices enable frequent diagnostic checks as a routine clinical tool, and therefore increase the possibility of early AD diagnosis. This study aimed to comprehensively investigate functional connectivity (FC) in the prefrontal cortex measured by a portable functional near-infrared spectroscopy (fNIRS) device during a working memory (WM) task known as the delayed matching to sample (DMTS) task. Differences in prefrontal FC between healthy control (HC) (n = 23) and CD groups (n = 23) were examined. Intra-group analysis (one-sample t-test) revealed significantly greater prefrontal FC, especially left- and inter-hemispheric FC, in the CD group than in the HC. These observations could be due to a compensatory mechanism of the prefrontal cortex caused by hippocampal degeneration. Inter-group analysis (unpaired two-sample t-test) revealed significant intergroup differences in left- and inter-hemispheric FC. These attributes may serve as a novel biomarker for early detection of MCI. In addition, our findings imply that portable fNIRS devices covering the prefrontal cortex may be useful for early diagnosis of MCI.
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Affiliation(s)
- Jin-Woo Yu
- Department of Information and Communication Engineering, DGIST, Daegu 42988, South Korea
- These authors equally contributed to this work
| | - Sung-Ho Lim
- Department of Information and Communication Engineering, DGIST, Daegu 42988, South Korea
- Brain Engineering Convergence Research Center, DGIST, Daegu 42988, South Korea
- These authors equally contributed to this work
| | - Bomin Kim
- Department of Information and Communication Engineering, DGIST, Daegu 42988, South Korea
| | - Eunho Kim
- Department of Information and Communication Engineering, DGIST, Daegu 42988, South Korea
| | - Kyungsoo Kim
- Brain Engineering Convergence Research Center, DGIST, Daegu 42988, South Korea
| | - Sung Kyu Park
- Department of Occupational and Environmental Medicine, Yeungnam University Hospital, Daegu 42988, South Korea
| | - Young Seok Byun
- Department of Occupational and Environmental Medicine, Yeungnam University Hospital, Daegu 42988, South Korea
| | - Joon Sakong
- Department of Occupational and Environmental Medicine, Yeungnam University Hospital, Daegu 42988, South Korea
- Department of Preventive Medicine and Public Health, College of Medicine, Yeungnam University, Daegu 42988, South Korea
| | - Ji-Woong Choi
- Department of Information and Communication Engineering, DGIST, Daegu 42988, South Korea
- Brain Engineering Convergence Research Center, DGIST, Daegu 42988, South Korea
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74
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Bulgarelli C, de Klerk CCJM, Richards JE, Southgate V, Hamilton A, Blasi A. The developmental trajectory of fronto-temporoparietal connectivity as a proxy of the default mode network: a longitudinal fNIRS investigation. Hum Brain Mapp 2020; 41:2717-2740. [PMID: 32128946 PMCID: PMC7294062 DOI: 10.1002/hbm.24974] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2019] [Revised: 02/12/2020] [Accepted: 02/18/2020] [Indexed: 12/18/2022] Open
Abstract
The default mode network (DMN) is a network of brain regions that is activated while we are not engaged in any particular task. While there is a large volume of research documenting functional connectivity within the DMN in adults, knowledge of the development of this network is still limited. There is some evidence for a gradual increase in the functional connections within the DMN during the first 2 years of life, in contrast to other functional resting‐state networks that support primary sensorimotor functions, which are online from very early in life. Previous studies that investigated the development of the DMN acquired data from sleeping infants using fMRI. However, sleep stages are known to affect functional connectivity. In the current longitudinal study, fNIRS was used to measure spontaneous fluctuations in connectivity within fronto‐temporoparietal areas—as a proxy for the DMN—in awake participants every 6 months from 11 months till 36 months. This study validates a method for recording resting‐state data from awake infants, and presents a data analysis pipeline for the investigation of functional connections with infant fNIRS data, which will be beneficial for researchers in this field. A gradual development of fronto‐temporoparietal connectivity was found, supporting the idea that the DMN develops over the first years of life. Functional connectivity reached its maximum peak at about 24 months, which is consistent with previous findings showing that, by 2 years of age, DMN connectivity is similar to that observed in adults.
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Affiliation(s)
- Chiara Bulgarelli
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK.,Centre for Brain and Cognitive Development, Birkbeck College, University of London, London, UK
| | - Carina C J M de Klerk
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, London, UK.,Department of Psychology, University of Essex, Colchester, UK
| | - John E Richards
- Institute for Mind and Brain, Department of Psychology, University of South Carolina, Columbia, South Carolina
| | | | - Antonia Hamilton
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Anna Blasi
- Department of Medical Physics and Biomedical Engineering, University College London, London, UK
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75
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Pinti P, Tachtsidis I, Hamilton A, Hirsch J, Aichelburg C, Gilbert S, Burgess PW. The present and future use of functional near-infrared spectroscopy (fNIRS) for cognitive neuroscience. Ann N Y Acad Sci 2020; 1464:5-29. [PMID: 30085354 PMCID: PMC6367070 DOI: 10.1111/nyas.13948] [Citation(s) in RCA: 420] [Impact Index Per Article: 105.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Revised: 07/10/2018] [Accepted: 07/13/2018] [Indexed: 01/11/2023]
Abstract
The past few decades have seen a rapid increase in the use of functional near-infrared spectroscopy (fNIRS) in cognitive neuroscience. This fast growth is due to the several advances that fNIRS offers over the other neuroimaging modalities such as functional magnetic resonance imaging and electroencephalography/magnetoencephalography. In particular, fNIRS is harmless, tolerant to bodily movements, and highly portable, being suitable for all possible participant populations, from newborns to the elderly and experimental settings, both inside and outside the laboratory. In this review we aim to provide a comprehensive and state-of-the-art review of fNIRS basics, technical developments, and applications. In particular, we discuss some of the open challenges and the potential of fNIRS for cognitive neuroscience research, with a particular focus on neuroimaging in naturalistic environments and social cognitive neuroscience.
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Affiliation(s)
- Paola Pinti
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - Ilias Tachtsidis
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
| | - Antonia Hamilton
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - Joy Hirsch
- Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUK
- Department of PsychiatryYale School of MedicineNew HavenConnecticut
- Department of NeuroscienceYale School of MedicineNew HavenConnecticut
- Comparative MedicineYale School of MedicineNew HavenConnecticut
| | | | - Sam Gilbert
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
| | - Paul W. Burgess
- Institute of Cognitive NeuroscienceUniversity College LondonLondonUK
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76
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Aihara T, Shimokawa T, Ogawa T, Okada Y, Ishikawa A, Inoue Y, Yamashita O. Resting-State Functional Connectivity Estimated With Hierarchical Bayesian Diffuse Optical Tomography. Front Neurosci 2020; 14:32. [PMID: 32082110 PMCID: PMC7005139 DOI: 10.3389/fnins.2020.00032] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2019] [Accepted: 01/13/2020] [Indexed: 12/15/2022] Open
Abstract
Resting-state functional connectivity (RSFC) has been generally assessed with functional magnetic resonance imaging (fMRI) thanks to its high spatial resolution. However, fMRI has several disadvantages such as high cost and low portability. In addition, fMRI may not be appropriate for people with metal or electronic implants in their bodies, with claustrophobia and who are pregnant. Diffuse optical tomography (DOT), a method of neuroimaging using functional near-infrared spectroscopy (fNIRS) to reconstruct three-dimensional brain activity images, offers a non-invasive alternative, because fNIRS as well as fMRI measures changes in deoxygenated hemoglobin concentrations and, in addition, fNIRS is free of above disadvantages. We recently proposed a hierarchical Bayesian (HB) DOT algorithm and verified its performance in terms of task-related brain responses. In this study, we attempted to evaluate the HB DOT in terms of estimating RSFC. In 20 healthy males (21-38 years old), 10 min of resting-state data was acquired with 3T MRI scanner or high-density NIRS on different days. The NIRS channels consisted of 96 long (29-mm) source-detector (SD) channels and 56 short (13-mm) SD channels, which covered bilateral frontal and parietal areas. There were one and two resting-state runs in the fMRI and fNIRS experiments, respectively. The reconstruction performances of our algorithm and the two currently prevailing algorithms for DOT were evaluated using fMRI signals as a reference. Compared with the currently prevailing algorithms, our HB algorithm showed better performances in both the similarity to fMRI data and inter-run reproducibility, in terms of estimating the RSFC.
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Affiliation(s)
- Takatsugu Aihara
- Graduate School of Human and Environmental Studies, Kyoto University, Kyoto, Japan
- Neural Information Analysis Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Takeaki Shimokawa
- Neural Information Analysis Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Takeshi Ogawa
- Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Yuto Okada
- Graduate School of Information Science, Nara Institute of Science and Technology, Nara, Japan
| | - Akihiro Ishikawa
- Medical Systems Division, Research and Development Department, Shimadzu Corporation, Kyoto, Japan
| | - Yoshihiro Inoue
- Medical Systems Division, Research and Development Department, Shimadzu Corporation, Kyoto, Japan
| | - Okito Yamashita
- Neural Information Analysis Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan
- RIKEN Center for Advanced Intelligence Project, Tokyo, Japan
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77
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Zhang Y, Zhu C. Assessing Brain Networks by Resting-State Dynamic Functional Connectivity: An fNIRS-EEG Study. Front Neurosci 2020; 13:1430. [PMID: 32038138 PMCID: PMC6993585 DOI: 10.3389/fnins.2019.01430] [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: 09/11/2019] [Accepted: 12/18/2019] [Indexed: 11/13/2022] Open
Abstract
The coordination of brain activity between disparate neural populations is highly dynamic. Investigations into intrinsic brain organization by evaluating dynamic resting-state functional connectivity (dRSFC) have attracted great attention in recent years. However, there are few dRSFC studies based on functional near-infrared spectroscopy (fNIRS) even though it has some advantages for studying the temporal evolution of brain function. In this research, we recruited 20 young adults and measured their resting-state brain fluctuations in several areas of the frontal, parietal, temporal, and occipital lobes using fNIRS-electroencephalography (EEG) simultaneous recording. Based on a sliding-window approach, we found that the variability of the dRSFC within any region of interest was significantly lower than the connections between region of interests but noticeably greater than the correlation between the channels with a short interoptode distance, which mainly consist of physiological fluctuations occurring in the superficial layers. Furthermore, based on a time-resolved k-means clustering analysis, the temporal evolution was extracted for three dominant functional networks. These networks were roughly consistent between different subject subgroups and in varying sliding time window lengths of 20, 30, and 60 s. Between these three functional networks, there were obvious time-varied and system-specific synchronous relationships. In addition, the oscillation of the frontal-parietal-temporal network showed significant correlation with the switching of one EEG microstate, a finding which is consistent with a previous functional MRI-EEG study. All this evidence implies the functional significance of fNIRS-dRSFC and demonstrates the feasibility of fNIRS for extracting the dominant functional networks based on RSFC dynamics.
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Affiliation(s)
- Yujin Zhang
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
- National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Chaozhe Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
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78
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Lu K, Hao N. When do we fall in neural synchrony with others? Soc Cogn Affect Neurosci 2020; 14:253-261. [PMID: 30753646 PMCID: PMC6413689 DOI: 10.1093/scan/nsz012] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2018] [Revised: 01/30/2019] [Accepted: 02/06/2019] [Indexed: 12/24/2022] Open
Abstract
This study aimed to investigate the situation in which interpersonal brain synchronization (IBS) occurs during a collaborative task and examined its trajectory over time by developing a novel functional near-infrared spectroscopy (fNIRS)-based hyperscanning paradigm. Participants were asked to perform a collaborative task in three-person groups where two of the members are real participants and one is a confederate. Compared to dyads between real participants and confederates, real-participant pairings showed greater cooperation behavior and IBS between bilateral dorsolateral prefrontal cortex. And, IBS and cooperation increased over time in real-participant pairings, whereas they remained low and constant in dyads with the confederate. These findings indicate that IBS occurs between individuals engaging in interpersonal interaction during a collaborative task, during which both IBS and cooperatively interpersonal interaction tend to increase over time.
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Affiliation(s)
- Kelong Lu
- Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Ning Hao
- Shanghai Key Laboratory of Brain Functional Genomics, School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
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79
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Sun B, Xiao W, Feng X, Shao Y, Zhang W, Li W. Behavioral and brain synchronization differences between expert and novice teachers when collaborating with students. Brain Cogn 2019; 139:105513. [PMID: 31887711 DOI: 10.1016/j.bandc.2019.105513] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Revised: 12/16/2019] [Accepted: 12/18/2019] [Indexed: 01/12/2023]
Abstract
Differences in behavior and neural mechanisms between expert and novice teachers when collaborating with students are poorly understood. This study investigated whether expert teachers do better in collaborating with students than novice teachers and explored the neural basis of such differences. Novice teacher and student (NT-S) dyads and expert teacher and student (ET-S) dyads were recruited to complete an interactive task consisting of a cooperation and an independent condition. During the experiment, neural activity in the prefrontal cortex of the participants was recorded with functional near-infrared spectroscopy. The results show higher accuracy for the ET-S dyads than the NT-S dyads in the cooperation condition; however, no difference was found in the independent condition. Increased interpersonal brain synchronization (IBS) was detected in the left dorsolateral prefrontal cortex of participants in ET-S dyads, but not in NT-S dyads in the cooperation condition. Moreover, an interaction effect of dyad type and conditions on IBS was observed, revealing IBS was stronger in ET-S dyads than in NT-S dyads. In ET-S dyads, IBS was positively correlated with the teachers' perspective-taking ability and accuracy. These findings suggest that expert teachers collaborate better with students than novice teachers, and IBS might be the neural marker for this difference.
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Affiliation(s)
- Binghai Sun
- School of Teacher Education, Zhejiang Normal University, Jinhua, Zhejiang, China; Research Center of Tin Ka Ping Moral Education, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Weilong Xiao
- School of Teacher Education, Zhejiang Normal University, Jinhua, Zhejiang, China; Research Center of Tin Ka Ping Moral Education, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Xiaodan Feng
- School of Teacher Education, Zhejiang Normal University, Jinhua, Zhejiang, China; Research Center of Tin Ka Ping Moral Education, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Yuting Shao
- School of Teacher Education, Zhejiang Normal University, Jinhua, Zhejiang, China; Research Center of Tin Ka Ping Moral Education, Zhejiang Normal University, Jinhua, Zhejiang, China
| | - Wenhai Zhang
- School of Teacher Education, Zhejiang Normal University, Jinhua, Zhejiang, China; Research Center of Tin Ka Ping Moral Education, Zhejiang Normal University, Jinhua, Zhejiang, China.
| | - Weijian Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, Zhejiang, China; Research Center of Tin Ka Ping Moral Education, Zhejiang Normal University, Jinhua, Zhejiang, China.
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80
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Machine learning: assessing neurovascular signals in the prefrontal cortex with non-invasive bimodal electro-optical neuroimaging in opiate addiction. Sci Rep 2019; 9:18262. [PMID: 31797878 PMCID: PMC6892956 DOI: 10.1038/s41598-019-54316-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Accepted: 11/09/2019] [Indexed: 02/07/2023] Open
Abstract
Chronic and recurrent opiate use injuries brain tissue and cause serious pathophysiological changes in hemodynamic and subsequent inflammatory responses. Prefrontal cortex (PFC) has been implicated in drug addiction. However, the mechanism underlying systems-level neuroadaptations in PFC during abstinence has not been fully characterized. The objective of our study was to determine what neural oscillatory activity contributes to the chronic effect of opiate exposure and whether the activity could be coupled to neurovascular information in the PFC. We employed resting-state functional connectivity to explore alterations in 8 patients with heroin dependency who stayed abstinent (>3 months; HD) compared with 11 control subjects. A non-invasive neuroimaging strategy was applied to combine electrophysiological signals through electroencephalography (EEG) with hemodynamic signals through functional near-infrared spectroscopy (fNIRS). The electrophysiological signals indicate neural synchrony and the oscillatory activity, and the hemodynamic signals indicate blood oxygenation in small vessels in the PFC. A supervised machine learning method was used to obtain associations between EEG and fNIRS modalities to improve precision and localization. HD patients demonstrated desynchronized lower alpha rhythms and decreased connectivity in PFC networks. Asymmetric excitability and cerebrovascular injury were also observed. This pilot study suggests that cerebrovascular injury in PFC may result from chronic opiate intake.
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81
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Parent M, Peysakhovich V, Mandrick K, Tremblay S, Causse M. The diagnosticity of psychophysiological signatures: Can we disentangle mental workload from acute stress with ECG and fNIRS? Int J Psychophysiol 2019; 146:139-147. [DOI: 10.1016/j.ijpsycho.2019.09.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 08/09/2019] [Accepted: 09/12/2019] [Indexed: 01/10/2023]
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82
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Applications of Functional Near-Infrared Spectroscopy in Fatigue, Sleep Deprivation, and Social Cognition. Brain Topogr 2019; 32:998-1012. [DOI: 10.1007/s10548-019-00740-w] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2019] [Accepted: 10/18/2019] [Indexed: 01/05/2023]
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83
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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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84
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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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85
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Firooz S, Setarehdan SK. IQ estimation by means of EEG-fNIRS recordings during a logical-mathematical intelligence test. Comput Biol Med 2019; 110:218-226. [PMID: 31202152 DOI: 10.1016/j.compbiomed.2019.05.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2019] [Revised: 05/20/2019] [Accepted: 05/20/2019] [Indexed: 11/17/2022]
Abstract
Intelligence differences of individuals are attributed to the structural and functional differences of the brain. Neural processing operations of the human brain vary according to the difficulty level of the problem and the intelligence level of individuals. In this study, we used a bimodal system consisting of functional Near-Infrared Spectroscopy (fNIRS) and Electroencephalogram (EEG) to investigate these inter-individual differences. A continuous wave 32-channel fNIRS from OxyMonfNIRS device (Artinis) and 19-channel EEG from (g.tec's company) were utilized to study the oxygenation procedure as well as the electrical activity of the brain when doing the problems of Raven's Progressive Matrix (RPM) intelligence test. We used this information to estimate the Intelligence Quotient (IQ) of the individual without performing a complete logical-mathematical intelligence test in a long-time period and examining the answers of people to the questions. After EEG preprocessing, different features including Higuchi's fractal dimension, Shannon entropy values from wavelet transform coefficients, and average power of frequency sub-bands were extracted. Clean fNIRS signals were also used to compute features such as slope, mean, variance, kurtosis, skewness, and peak. Then dimension reduction algorithms such as Linear Discriminant Analysis (LDA) and Principal Component Analysis (PCA) were applied to select an effective feature set from fNIRS and EEG in order to improve the IQ estimation process. We utilized two regression methods, i.e., Linear Regression (LR) and Support Vector Regression (SVR), to extract optimum models for the IQ determination. The best regression models based on fNIRS-EEG and fNIRS presented 3.093% and 3.690% relative error for 11 subjects, respectively.
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Affiliation(s)
- Shabnam Firooz
- Control and Intelligent Processing Centre of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran
| | - Seyed Kamaledin Setarehdan
- Control and Intelligent Processing Centre of Excellence, School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.
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86
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de Souza Rodrigues J, Ribeiro FL, Sato JR, Mesquita RC, Júnior CEB. Identifying individuals using fNIRS-based cortical connectomes. BIOMEDICAL OPTICS EXPRESS 2019; 10:2889-2897. [PMID: 31259059 PMCID: PMC6583329 DOI: 10.1364/boe.10.002889] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/25/2019] [Revised: 05/10/2019] [Accepted: 05/12/2019] [Indexed: 05/29/2023]
Abstract
The fMRI-based functional connectome was shown to be sufficiently unique to allow individual identification (fingerprinting). We aimed to test whether a fNIRS-based connectome could also be used to identify individuals. Forty-four participants performed experimental protocols that consisted of two periods of resting-state interleaved by a cognitive task period. Connectome identification was performed for all possible pairwise combinations of the three periods. The influence of hemodynamic global variation was tested using global signal regression and principal component analysis. High identification accuracies well-above chance level (2.3%) were observed overall, being particularly high (93%) to the oxyhemoglobin signal between resting conditions. Our results suggest that fNIRS is a suitable technique to assess connectome fingerprints.
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Affiliation(s)
- Júlia de Souza Rodrigues
- Center for Mathematics, Computation and Cognition, University of ABC, São Bernardo do Campo, SP, 09606-045, Brazil
| | - Fernanda Lenita Ribeiro
- Center for Mathematics, Computation and Cognition, University of ABC, São Bernardo do Campo, SP, 09606-045, Brazil
- School of Psychology, The University of Queensland, Brisbane, QLD 407, Australia
| | - João Ricardo Sato
- Center for Mathematics, Computation and Cognition, University of ABC, São Bernardo do Campo, SP, 09606-045, Brazil
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87
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Influences of age, mental workload, and flight experience on cognitive performance and prefrontal activity in private pilots: a fNIRS study. Sci Rep 2019; 9:7688. [PMID: 31118436 PMCID: PMC6531547 DOI: 10.1038/s41598-019-44082-w] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2018] [Accepted: 04/30/2019] [Indexed: 11/25/2022] Open
Abstract
The effects of aging on cognitive performance must be better understood, especially to protect older individuals who are engaged in risky activities (e.g. aviation). Current literature on executive functions suggests that brain compensatory mechanisms may counter cognitive deterioration due to aging, at least up to certain task load levels. The present study assesses this hypothesis in private pilots engaged in two executive tasks from the standardized CANTAB battery, namely Spatial Working Memory (SWM) and One Touch Stockings of Cambridge (OTS). Sixty-one pilots from three age groups (young, middle-aged, older) performed these two tasks from low to very high difficulty levels, beyond those reported in previous aging studies. A fNIRS headband measured changes in oxyhemoglobin (HbO2) in the prefrontal cortex. Results confirmed an overall effect of the difficulty level in the three age groups, with a decline in task performance and an increase in prefrontal HbO2 signal. Performance of older relative to younger pilots was impaired in both tasks, with the greatest impairment observed for the highest-load Spatial Working Memory task. Consistent with this behavioral deficit in older pilots, a plateau of prefrontal activity was observed at this highest-load level, suggesting that a ceiling in neural resources was reached. When behavioral performance was either equivalent between age groups or only slightly impaired in the older group, there were not any age-related differences in prefrontal activity. Finally, older pilots with extensive flying experience tend to show better preserved spatial working memory performance when compared to mildly-experienced of the same age group. The present findings are discussed in the frames of HAROLD and CRUNCH theoretical models of cognitive and neural aging, evoking the possibility that piloting expertise may contribute to preserve executive functions throughout adulthood.
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88
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Hu Z, Lam KF, Xiang YT, Yuan Z. Causal Cortical Network for Arithmetic Problem-Solving Represents Brain's Planning Rather than Reasoning. Int J Biol Sci 2019; 15:1148-1160. [PMID: 31223276 PMCID: PMC6567809 DOI: 10.7150/ijbs.33400] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 04/04/2019] [Indexed: 12/18/2022] Open
Abstract
Arithmetic problem-solving whose components mainly involve the calculation, planning and reasoning, is an important mathematical skill. To date, the neural mechanism underlying arithmetic problem-solving remains unclear. In this study, a scheme that combined a novel 24 points game paradigm, conditional Granger causality analysis, and near-infrared spectroscopy (fNIRS) neuroimaging technique was developed to examine the differences in brain activation and effective connectivity between the calculation, planning, and reasoning. We discovered that the performance of planning was correlated with the activation in frontal cortex, whereas the performance of reasoning showed the relationship with the activation in parietal cortex. In addition, we also discovered that the directional effective connectivity between the anterior frontal and posterior parietal cortex was more closely related to planning rather than reasoning. It is expected that this work will pave a new avenue for an improved understanding of the neural underpinnings underlying arithmetic problem-solving, which also provides a novel indicator to evaluate the efficacy of mathematical education.
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Affiliation(s)
- Zhishan Hu
- Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Keng-Fong Lam
- Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Yu-Tao Xiang
- Faculty of Health Sciences, University of Macau, Macau SAR, China
| | - Zhen Yuan
- Faculty of Health Sciences, University of Macau, Macau SAR, China
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89
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Hu Z, Zhang J, Zhang L, Xiang YT, Yuan Z. Linking brain activation to topological organization in the frontal lobe as a synergistic indicator to characterize the difference between various cognitive processes of executive functions. NEUROPHOTONICS 2019; 6:025008. [PMID: 31172018 PMCID: PMC6537479 DOI: 10.1117/1.nph.6.2.025008] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 03/28/2019] [Indexed: 05/17/2023]
Abstract
Executive functions (EFs) associated with the frontal lobe are vital for goal-orientated behavior. To date, limited efforts have been made to examine the relationships among the behavior, brain activation, and topological organization of functional networks in the frontal lobe underlying various EF tasks, including inhibition, working memory, and cognitive flexibility. In this study, functional near-infrared spectroscopy neuroimaging technique was used to systematically inspect the differences in the brain activation and the topological organization of brain networks between various EF tasks in the frontal lobe. In addition, the relationships between brain activation/network properties and task performances and the relationships between brain activation and network properties were, respectively, examined for different EF tasks. Consequently, we have discovered that the nodal and global properties of the resting-state and task-evoked networks, respectively, exhibited significant correlations with the activation of various brain regions during various EF tasks. In particular, the measure that links the neural activation to the topological organization of the brain networks in the frontal lobe can serve as a synergistic indicator to examine the difference between various EF tasks, which paves a way toward a comprehensive understanding of the neural mechanism underlying EFs.
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Affiliation(s)
- Zhishan Hu
- University of Macau, Faculty of Health Sciences, Macao Special Administrative Region, China
| | - Juan Zhang
- University of Macau, Faculty of Education, Macao Special Administrative Region, China
| | - Lingyan Zhang
- The Third Affiliated Hospital of China Southern Medical University, Department of Radiology, Guangzhou, China
| | - Yu-Tao Xiang
- University of Macau, Faculty of Health Sciences, Macao Special Administrative Region, China
| | - Zhen Yuan
- University of Macau, Faculty of Health Sciences, Macao Special Administrative Region, China
- Address all correspondence to Zhen Yuan, E-mail:
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90
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Lu K, Xu G, Li W, Huo C, Liu Q, Lv Z, Wang Y, Li Z, Fan Y. Frequency-specific functional connectivity related to the rehabilitation task of stroke patients. Med Phys 2019; 46:1545-1560. [PMID: 30675729 DOI: 10.1002/mp.13398] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Revised: 12/21/2018] [Accepted: 01/17/2019] [Indexed: 01/15/2023] Open
Abstract
PURPOSES Stroke survivors suffering from deficits in motor control typically show persistent motor symptoms and limited functional abilities, which affect their functional independence in daily life. Active rehabilitation training is commonly applied for stroke patients to recover from motor dysfunction. The global connectivity reflects the synchronization of cardiac and respiratory activities in the cerebral regions. However, the understanding of the patterns of frequency-specific global connectivity (GC) and functional connectivity (FC) when performing active rehabilitation training is still far from comprehensive. This study was conducted to investigate the brain network patterns of stroke patients while performing a four-limb linkage rehabilitation training using the functional near-infrared spectroscopy (fNIRS) method. METHODS Two groups of stroke patients (LH, left hemiplegia; RH, right hemiplegia) and one healthy group were recruited to participate in this study. The wavelet phase coherence (WPCO) method was used to calculate the frequency-specific GC and FC of the brain network in four frequency bands: I, 0.6-2 Hz; II, 0.145-0.6 Hz; III, 0.052-0.145 Hz; and IV, 0.021-0.052 Hz. RESULTS Results showed that the healthy group exhibited lower WPCO in the four frequency bands during the task state than during the resting state (P < 0.05). Interestingly, the stroke groups showed increased WPCO in the frequency band II during the task state than during the resting state (P < 0.05). Moreover, significantly lower WPCO values in the frequency bands III (P < 0.05) were found during task state in the RH and LH groups compared with the healthy group. The RH group showed increased WPCO values in the frequency band II during the task state compared with the healthy group (P < 0.05). In addition, the RH group showed increased WPCO in the frequency bands I (P < 0.05) and II (P < 0.05) than the LH group. Notably, the rehabilitation task did not induce significant changes in stroke groups in the frequency band IV, which implied the neurogenic activity. CONCLUSIONS The reductions in FC suggested that the brain impairments caused a disturbed neurovascular coupling regulation in stroke patients. Results in frequency band IV suggested that the limb movement rehabilitation task intrinsically may not produce remarkable effect on the neurogenic activity of stroke patients. Significant differences in WPCO between the LH and RH groups suggested that the rehabilitation task should be specifically designed for individual rehabilitation. The frequency-specific FC methods based on WPCO would provide a potential approach to quantitatively assess the effect of rehabilitation tasks.
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Affiliation(s)
- Kuan Lu
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, 100086, Beijing, China
| | - Gongcheng Xu
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, 100086, Beijing, China
| | - Wenhao Li
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, 100086, Beijing, China
| | - Congcong Huo
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids Beijing, Beijing, 100176, China
| | - Qianying Liu
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, 100086, Beijing, China
| | - Zeping Lv
- Rehabilitation Hospital, National Research Center for Rehabilitation Technical Aids, Beijing, 100176, China
| | - Yonghui Wang
- Qilu Hospital, ShanDong University, Jinan, 250061, China
| | - Zengyong Li
- Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids Beijing, Beijing, 100176, China.,Key Laboratory of Rehabilitation Aids Technology and System of the Ministry of Civil Affairs, Beijing, 100176, China
| | - Yubo Fan
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, 100086, Beijing, China.,Beijing Key Laboratory of Rehabilitation Technical Aids for Old-Age Disability, National Research Center for Rehabilitation Technical Aids Beijing, Beijing, 100176, China.,Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing, 100083, China
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91
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Lu K, Qiao X, Hao N. Praising or keeping silent on partner’s ideas: Leading brainstorming in particular ways. Neuropsychologia 2019; 124:19-30. [DOI: 10.1016/j.neuropsychologia.2019.01.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2018] [Revised: 01/07/2019] [Accepted: 01/07/2019] [Indexed: 01/27/2023]
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92
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Goldbeck F, Haipt A, Rosenbaum D, Rohe T, Fallgatter AJ, Hautzinger M, Ehlis AC. The Positive Brain - Resting State Functional Connectivity in Highly Vital and Flourishing Individuals. Front Hum Neurosci 2019; 12:540. [PMID: 30692922 PMCID: PMC6339902 DOI: 10.3389/fnhum.2018.00540] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2018] [Accepted: 12/27/2018] [Indexed: 01/19/2023] Open
Abstract
The World Health Organization has defined health as “complete physical, mental and social well-being and not merely the absence of disease or infirmity” (World Health Organization, 1948). An increasing number of studies have therefore started to investigate “the good life.” However, the underlying variation in brain activity has rarely been examined. The goal of this study was to assess differences in resting state functional connectivity (RSFC) between regular healthy individuals and healthy individuals with a high occurrence of flourishing and subjective vitality. Together, flourishing, a broad measure of psycho-social functioning and subjective vitality, an organismic marker of subjective well-being comprise the phenomenological opposite of a major depressive disorder. Out of a group of 43 participants, 20 high-flourishing (highFl) and 18 high-vital (highSV) individuals underwent a 7-min resting state period, where cortical activity in posterior brain areas was assessed using functional near-infrared spectroscopy (fNIRS). Network-based statistics (NBS) of FC yielded significantly different FC patterns for the highFl and highSV individuals compared to their healthy comparison group. The networks converged at areas of the posterior default mode network and differed in hub nodes in the left middle temporal/fusiform gyrus (flourishing) and the left primary/secondary somatosensory cortex (subjective vitality). The attained networks are discussed with regard to recent neuroscientific findings for other well-being measures and potential mechanisms of action based on social information processing and body-related self-perception.
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Affiliation(s)
- Florens Goldbeck
- Department of Psychiatry and Psychotherapy, University Hospital of Tübingen, Tübingen, Germany
| | - Alina Haipt
- Department of Psychiatry and Psychotherapy, University Hospital of Tübingen, Tübingen, Germany
| | - David Rosenbaum
- Department of Psychiatry and Psychotherapy, University Hospital of Tübingen, Tübingen, Germany
| | - Tim Rohe
- Department of Psychiatry and Psychotherapy, University Hospital of Tübingen, Tübingen, Germany
| | - Andreas J Fallgatter
- Department of Psychiatry and Psychotherapy, University Hospital of Tübingen, Tübingen, Germany.,LEAD Graduate School and Research Network, University of Tübingen, Tübingen, Germany
| | | | - Ann-Christine Ehlis
- Department of Psychiatry and Psychotherapy, University Hospital of Tübingen, Tübingen, Germany.,LEAD Graduate School and Research Network, University of Tübingen, Tübingen, Germany
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93
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Ren H, Wang MY, He Y, Du Z, Zhang J, Zhang J, Li D, Yuan Z. A novel phase analysis method for examining fNIRS neuroimaging data associated with Chinese/English sight translation. Behav Brain Res 2018; 361:151-158. [PMID: 30576722 DOI: 10.1016/j.bbr.2018.12.032] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Revised: 11/15/2018] [Accepted: 12/17/2018] [Indexed: 11/25/2022]
Abstract
In this study, a phase method for analyzing functional near-infrared spectroscopy (fNIRS) signals was developed, which can extract the phase information of fNIRS data by using Hilbert transform. More importantly, the phase analysis method can be further performed to generate the brain phase activation and to construct the brain networks. Meanwhile, the study of translation between Chinese and English has been exciting and interesting from both the language and neuroscience standpoints due to their drastically different linguistic features. In particular, inspecting the brain phase activation and functional connectivity based on the phase data and phase analysis method will enable us to better understand the neural mechanism associated with Chinese/English translation. Our phase analysis results showed that the left prefrontal cortex, including the dorsolateral prefrontal cortex (DLPFC) and frontopolar area, was involved in the translation process of the language pair. In addition, we also discovered that the most significant brain phase activation difference between translating into non-native (English) vs. native (Chinese) language was identified in the Broca's area. As a result, the proposed phase analysis approach can provide us an additional tool to reveal the complex cognitive mechanism associated with Chinese/English sight translation.
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Affiliation(s)
- Houhua Ren
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu 610065, China
| | - Meng-Yun Wang
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, China
| | - Yan He
- Centre for Studies of Translation-Interpreting and Cognition, University of Macau, Taipa, Macau SAR, China
| | - Zhengcong Du
- School of Information Science and Technology, XiChang University 615000, China
| | - Jiang Zhang
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu 610065, China; The Key Laboratory for NeuroInformation of Ministry of Education, University of Electronic Science and Technology of China, Chengdu 610054, China.
| | - Jing Zhang
- College of Electrical Engineering and Information Technology, Sichuan University, Chengdu 610065, China
| | - Defeng Li
- Centre for Studies of Translation-Interpreting and Cognition, University of Macau, Taipa, Macau SAR, China.
| | - Zhen Yuan
- Bioimaging Core, Faculty of Health Sciences, University of Macau, Taipa, Macau SAR, China
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94
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Basura GJ, Hu X, Juan JS, Tessier A, Kovelman I. Human central auditory plasticity: A review of functional near-infrared spectroscopy (fNIRS) to measure cochlear implant performance and tinnitus perception. Laryngoscope Investig Otolaryngol 2018; 3:463-472. [PMID: 30599031 PMCID: PMC6302720 DOI: 10.1002/lio2.185] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE Functional near-infrared spectroscopy (fNIRS) is an emerging noninvasive technology used to study cerebral cortex activity. Being virtually silent and compatible with cochlear implants has helped establish fNIRS as an important tool when investigating auditory cortex as well as cortices involved with hearing and language processing in adults and during child development. With respect to this review article, more recently, fNIRS has also been used to investigate central auditory plasticity following hearing loss and tinnitus or phantom sound perception. METHODS Here, we review the currently available literature reporting the use of fNIRS in human studies with cochlear implants and tinnitus to measure human central auditory cortical circuits. We also provide the reader with detailed reviews of the technology and traditional recording paradigms/methods used in these auditory-based studies. RESULTS The purpose of this review article is to summarize theoretical advancements in our understanding of the neurocognitive mechanisms underlying auditory processes and their plasticity through fNIRS research of human auditory performance with cochlear implantation and plasticity that may contribute to the central percepts of tinnitus. CONCLUSION fNIRS is an emerging noninvasive brain imaging technology that has wide reaching application that can be applied to human studies involving cochlear implants and tinnitus. LEVEL OF EVIDENCE N/A.
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Affiliation(s)
- Gregory J. Basura
- Center for Human Growth and DevelopmentUniversity of MichiganAnn ArborMichiganU.S.A
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research InstituteUniversity of MichiganAnn ArborMichiganU.S.A
| | - Xiao‐Su Hu
- Center for Human Growth and DevelopmentUniversity of MichiganAnn ArborMichiganU.S.A
| | - Juan San Juan
- Department of Otolaryngology/Head and Neck Surgery, Kresge Hearing Research InstituteUniversity of MichiganAnn ArborMichiganU.S.A
| | | | - Ioulia Kovelman
- Center for Human Growth and DevelopmentUniversity of MichiganAnn ArborMichiganU.S.A
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95
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Bae J, Shin TJ, Kim S, Choi DH, Cho D, Ham J, Manca M, Jeong S, Lee B, Kim JG. The changes of cerebral hemodynamics during ketamine induced anesthesia in a rat model. JOURNAL OF BIOPHOTONICS 2018; 11:e201800081. [PMID: 29799675 DOI: 10.1002/jbio.201800081] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/12/2018] [Accepted: 05/24/2018] [Indexed: 06/08/2023]
Abstract
Current electroencephalogram (EEG) based-consciousness monitoring technique is vulnerable to specific clinical conditions (eg, epilepsy and dementia). However, hemodynamics is the most fundamental and well-preserved parameter to evaluate, even under severe clinical situations. In this study, we applied near-infrared spectroscopy (NIRS) system to monitor hemodynamic change during ketamine-induced anesthesia to find its correlation with the level of consciousness. Oxy-hemoglobin (OHb) and deoxy-hemoglobin concentration levels were continuously acquired throughout the experiment, and the reflectance ratio between 730 and 850 nm was calculated to quantify the hemodynamic changes. The results showed double peaks of OHb concentration change during ketamine anesthesia, which seems to be closely related to the consciousness state of the rat. This finding suggests the possibility of NIRS based-hemodynamic monitoring as a supplementary parameter for consciousness monitoring, compensating drawbacks of EEG signal based monitoring.
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Affiliation(s)
- Jayyoung Bae
- Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
| | - Teo J Shin
- Department of Pediatric Dentistry, School of Dentistry, Seoul National University, Seoul, South Korea
| | - Seonghyun Kim
- Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
| | - Dong-Hyuk Choi
- Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
| | - Dongrae Cho
- Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
| | - Jinsil Ham
- Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
| | - Marco Manca
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Seongwook Jeong
- Department of Anesthesiology and Pain Medicine, Chonnam National University Medical School, Gwangju, South Korea
| | - Boreom Lee
- Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
| | - Jae G Kim
- Department of Biomedical Science and Engineering, Institute of Integrated Technology, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju, South Korea
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96
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Nakamichi N, Takamoto K, Nishimaru H, Fujiwara K, Takamura Y, Matsumoto J, Noguchi M, Nishijo H. Cerebral Hemodynamics in Speech-Related Cortical Areas: Articulation Learning Involves the Inferior Frontal Gyrus, Ventral Sensory-Motor Cortex, and Parietal-Temporal Sylvian Area. Front Neurol 2018; 9:939. [PMID: 30443239 PMCID: PMC6221925 DOI: 10.3389/fneur.2018.00939] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 10/16/2018] [Indexed: 12/31/2022] Open
Abstract
Although motor training programs have been applied to childhood apraxia of speech (AOS), the neural mechanisms of articulation learning are not well understood. To this aim, we recorded cerebral hemodynamic activity in the left hemisphere of healthy subjects (n = 15) during articulation learning. We used near-infrared spectroscopy (NIRS) while articulated voices were recorded and analyzed using spectrograms. The study consisted of two experimental sessions (modified and control sessions) in which participants were asked to repeat the articulation of the syllables "i-chi-ni" with and without an occlusal splint. This splint was used to increase the vertical dimension of occlusion to mimic conditions of articulation disorder. There were more articulation errors in the modified session, but number of errors were decreased in the final half of the modified session; this suggests that articulation learning took place. The hemodynamic NIRS data revealed significant activation during articulation in the frontal, parietal, and temporal cortices. These areas are involved in phonological processing and articulation planning and execution, and included the following areas: (i) the ventral sensory-motor cortex (vSMC), including the Rolandic operculum, precentral gyrus, and postcentral gyrus, (ii) the dorsal sensory-motor cortex, including the precentral and postcentral gyri, (iii) the opercular part of the inferior frontal gyrus (IFGoperc), (iv) the temporal cortex, including the superior temporal gyrus, and (v) the inferior parietal lobe (IPL), including the supramarginal and angular gyri. The posterior Sylvian fissure at the parietal-temporal boundary (area Spt) was selectively activated in the modified session. Furthermore, hemodynamic activity in the IFGoperc and vSMC was increased in the final half of the modified session compared with its initial half, and negatively correlated with articulation errors during articulation learning in the modified session. The present results suggest an essential role of the frontal regions, including the IFGoperc and vSMC, in articulation learning, with sensory feedback through area Spt and the IPL. The present study provides clues to the underlying pathology and treatment of childhood apraxia of speech.
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Affiliation(s)
- Naomi Nakamichi
- Department of Oral and Maxillofacial Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Kouichi Takamoto
- System Emotional Science, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Hiroshi Nishimaru
- System Emotional Science, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Kumiko Fujiwara
- Department of Oral and Maxillofacial Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Yusaku Takamura
- System Emotional Science, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Jumpei Matsumoto
- System Emotional Science, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Makoto Noguchi
- Department of Oral and Maxillofacial Surgery, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
| | - Hisao Nishijo
- System Emotional Science, Graduate School of Medicine and Pharmaceutical Sciences, University of Toyama, Toyama, Japan
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97
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Exploring brain functional connectivity in rest and sleep states: a fNIRS study. Sci Rep 2018; 8:16144. [PMID: 30385843 PMCID: PMC6212555 DOI: 10.1038/s41598-018-33439-2] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2018] [Accepted: 09/19/2018] [Indexed: 11/16/2022] Open
Abstract
This study investigates the brain functional connectivity in the rest and sleep states. We collected EEG, EOG, and fNIRS signals simultaneously during rest and sleep phases. The rest phase was defined as a quiet wake-eyes open (w_o) state, while the sleep phase was separated into three states; quiet wake-eyes closed (w_c), non-rapid eye movement sleep stage 1 (N1), and non-rapid eye movement sleep stage 2 (N2) using the EEG and EOG signals. The fNIRS signals were used to calculate the cerebral hemodynamic responses (oxy-, deoxy-, and total hemoglobin). We grouped 133 fNIRS channels into five brain regions (frontal, motor, temporal, somatosensory, and visual areas). These five regions were then used to form fifteen brain networks. A network connectivity was computed by calculating the Pearson correlation coefficients of the hemodynamic responses between fNIRS channels belonging to the network. The fifteen networks were compared across the states using the connection ratio and connection strength calculated from the normalized correlation coefficients. Across all fifteen networks and three hemoglobin types, the connection ratio was high in the w_c and N1 states and low in the w_o and N2 states. In addition, the connection strength was similar between the w_c and N1 states and lower in the w_o and N2 states. Based on our experimental results, we believe that fNIRS has a high potential to be a main tool to study the brain connectivity in the rest and sleep states.
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98
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Corp DT, Youssef GJ, Clark RA, Gomes-Osman J, Yücel MA, Oldham SJ, Aldraiwiesh S, Rice J, Pascual-Leone A, Rogers MA. Reduced motor cortex inhibition and a 'cognitive-first' prioritisation strategy for older adults during dual-tasking. Exp Gerontol 2018; 113:95-105. [PMID: 30261247 PMCID: PMC6263161 DOI: 10.1016/j.exger.2018.09.018] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Revised: 09/19/2018] [Accepted: 09/21/2018] [Indexed: 11/23/2022]
Abstract
It is well established that older adults are less able to perform attentionally demanding motor tasks, placing them at greater risk of accident-related injury. The primary purpose of this study was to investigate whether the interplay between prefrontal and motor cortex activity could predict such age-related performance deficits. Using a dual-task (DT) paradigm, 15 younger and 15 older adults participated in experiment 1, where brain activity was simultaneously measured using functional near infrared spectroscopy (fNIRS) and transcranial magnetic stimulation (TMS). Experiment 1 demonstrated poorer performance for the older group across a range of DTs combining visuomotor arm tracking with a secondary cognitive or motor task. Interestingly however, older adults' DT performance error was isolated to the motor component of DTs. TMS data revealed reduced motor cortex (M1) inhibition during DTs for older adults, and a trend for this correlating with poorer performance. In contrast, poorer performing younger adults showed significantly higher M1 inhibition. Experiment 2 was conducted given a high amount of movement artifact in experiment 1 fNIRS data. Using fNIRS to measure prefrontal, premotor, and motor cortex activity in an additional 15 older adults, we found no evidence of an interplay between these regions predicting DT performance. Nevertheless, performance data replicated experiment 1 in showing that DT error was isolated to motor tasks in older adults, with no significant cognitive task error. Overall, this study shows that older adults seemed to adopt a 'cognitive-first' prioritisation strategy during the DTs involved in our study, and that deficits in DT performance may be related to the modulation of M1 inhibitory mechanisms. We propose that clinicians advise older adults to allocate greater attention to motor tasks during activities where they may be at risk of accident-related injury.
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Affiliation(s)
- Daniel T Corp
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia; Berenson-Allen Center for Non-Invasive Brain Stimulation, Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA.
| | - George J Youssef
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia; Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Australia
| | - Ross A Clark
- School of Health and Sports Science, University of the Sunshine Coast, Sippy Downs, QLD 4556, Australia
| | - Joyce Gomes-Osman
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA; Department of Physical Therapy, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Meryem A Yücel
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Stuart J Oldham
- Brain and Mental Health Laboratory, Monash Institute of Cognitive and Clinical Neurosciences, Monash University, Clayton 3168, VIC, Australia
| | - Shatha Aldraiwiesh
- Department of Physical Therapy, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Jordyn Rice
- Department of Physical Therapy, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Alvaro Pascual-Leone
- Berenson-Allen Center for Non-Invasive Brain Stimulation, Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Mark A Rogers
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia
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99
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Jia H, Li Y, Yu D. Attenuation of long-range temporal correlations of neuronal oscillations in young children with autism spectrum disorder. NEUROIMAGE-CLINICAL 2018; 20:424-432. [PMID: 30128281 PMCID: PMC6095951 DOI: 10.1016/j.nicl.2018.08.012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Revised: 07/12/2018] [Accepted: 08/08/2018] [Indexed: 11/26/2022]
Abstract
Although autism spectrum disorder (ASD) was previously found to be associated with aberrant brain structure, neuronal amplitudes and spatial neuronal interactions, surprisingly little is known about the temporal dynamics of neuronal oscillations in this disease. Here, the hemoglobin concentration signals (i.e., oxy-Hb and deoxy-Hb) of young children with ASD and typically developing (TD) children were recorded via functional near infrared spectroscopy (fNIRS) when they were watching a cartoon. The long-range temporal correlations (LRTCs) of hemoglobin concentration signals were quantified using detrended fluctuation analysis (DFA). Compared with TD group, the DFA exponents of young children with ASD were significantly smaller over left temporal region for oxy-Hb signal, and over bilateral temporo-occipital regions for deoxy-Hb signals, indicating a shift-to-randomness of brain oscillations in the children with ASD. Testing the relationship between age and DFA exponents revealed that this association could be modulated by autism. The correlation coefficients between age and DFA exponents were significantly more positive in TD group, compared to those in ASD group over several brain regions. Furthermore, the DFA exponents of oxy-Hb in left temporal region were negatively correlated with autistic symptom severity. These results suggest that the decreased DFA exponent of hemoglobin concentration signals may be one of the pathologic changes in ASD, and studying the temporal structure of brain activity via fNIRS technique may provide physiological indicators for autism. The LRTCs of fNIRS signals are attenuated in young children with ASD. Opposite relationships between age and LRTCs of fNIRS signals are revealed in young children with ASD and TD. The LRTCs of oxy-Hb in left temporal region are negatively correlated with autistic symptom severity.
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Affiliation(s)
- Huibin Jia
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, Jiangsu, China
| | - Yanwei Li
- College of Preschool Education, Nanjing Xiaozhuang University, Nanjing, Jiangsu, China
| | - Dongchuan Yu
- Key Laboratory of Child Development and Learning Science of Ministry of Education, School of Biological Sciences & Medical Engineering, Southeast University, Nanjing, Jiangsu, China.
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Duan L, Zhao Z, Lin Y, Wu X, Luo Y, Xu P. Wavelet-based method for removing global physiological noise in functional near-infrared spectroscopy. BIOMEDICAL OPTICS EXPRESS 2018; 9:3805-3820. [PMID: 30338157 PMCID: PMC6191612 DOI: 10.1364/boe.9.003805] [Citation(s) in RCA: 39] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 06/26/2018] [Accepted: 07/02/2018] [Indexed: 05/20/2023]
Abstract
Functional near-infrared spectroscopy (fNIRS) is a fast-developing non-invasive functional brain imaging technology widely used in cognitive neuroscience, clinical research and neural engineering. However, it is a challenge to effectively remove the global physiological noise in the fNIRS signal. The global physiological noise in fNIRS arises from multiple physiological origins in both superficial tissues and the brain. It has complex temporal, spatial and frequency characteristics, casting significant influence on the results. In the present study, we developed a novel wavelet-based method for fNIRS global physiological noise removal. The method is data-driven and does not rely on any additional hardware or subjective noise component selection procedure. It consists of two steps. Firstly, we use wavelet transform coherence to automatically detect the time-frequency points contaminated by the global physiological noise. Secondly, we decompose the fNIRS signal by using the wavelet transform, and then suppress the wavelet energy of the contaminated time-frequency points. Finally, we transform the signal back to a time series. We validated the method by using simulation and real data at both task- and resting-state. The results showed that our method can effectively remove the global physiological noise from the fNIRS signal and improve the spatial specificity of the task activation and the resting-state functional connectivity pattern.
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Affiliation(s)
- Lian Duan
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
- These authors have contributed equally to this work
| | - Ziping Zhao
- College of Computer and Information Engineering, Tianjin Normal University, Tianjin, China
- These authors have contributed equally to this work
| | - Yongling Lin
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
| | - Xiaoyan Wu
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
| | - Yuejia Luo
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
| | - Pengfei Xu
- Shenzhen Key Laboratory of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China
- Center for Neuroimaging, Shenzhen Institute of Neuroscience, Shenzhen, China
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