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Wijeakumar S, Forbes SH, Magnotta VA, Deoni S, Jackson K, Singh VP, Tiwari M, Kumar A, Spencer JP. Stunting in infancy is associated with atypical activation of working memory and attention networks. Nat Hum Behav 2023; 7:2199-2211. [PMID: 37884677 PMCID: PMC10730391 DOI: 10.1038/s41562-023-01725-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Accepted: 09/13/2023] [Indexed: 10/28/2023]
Abstract
Stunting is associated with poor long-term cognitive, academic and economic outcomes, yet the mechanisms through which stunting impacts cognition in early development remain unknown. In a first-ever neuroimaging study conducted on infants from rural India, we demonstrate that stunting impacts a critical, early-developing cognitive system-visual working memory. Stunted infants showed poor visual working memory performance and were easily distractible. Poor performance was associated with reduced engagement of the left anterior intraparietal sulcus, a region involved in visual working memory maintenance and greater suppression in the right temporoparietal junction, a region involved in attentional shifting. When assessed one year later, stunted infants had lower problem-solving scores, while infants of normal height with greater left anterior intraparietal sulcus activation showed higher problem-solving scores. Finally, short-for-age infants with poor physical growth indices but good visual working memory performance showed more positive outcomes suggesting that intervention efforts should focus on improving working memory and reducing distractibility in infancy.
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Affiliation(s)
| | | | | | - Sean Deoni
- Maternal, Newborn and Child Health Discovery & Tools, Bill & Melinda Gates Foundation, Seattle, WA, USA
- Advanced Baby Imaging Lab, New England Pediatric Institute of Neurodevelopment, Rhode Island Hospital, Providence, RI, USA
| | - Kiara Jackson
- School of Psychology, University of East Anglia, Norwich, UK
| | | | | | | | - John P Spencer
- School of Psychology, University of East Anglia, Norwich, UK.
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Xia Y, Wang K, Billing A, Billing M, Cooper RJ, Zhao H. Low-cost, smartphone-based instant three-dimensional registration system for infant functional near-infrared spectroscopy applications. NEUROPHOTONICS 2023; 10:046601. [PMID: 37876984 PMCID: PMC10593123 DOI: 10.1117/1.nph.10.4.046601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 10/05/2023] [Accepted: 10/06/2023] [Indexed: 10/26/2023]
Abstract
Significance To effectively apply functional near-infrared spectroscopy (fNIRS)/diffuse optical tomography (DOT) devices, a three-dimensional (3D) model of the position of each optode on a subject's scalp and the positions of that subject's cranial landmarks are critical. Obtaining this information accurately in infants, who rarely stop moving, is an ongoing challenge. Aim We propose a smartphone-based registration system that can potentially achieve a full-head 3D scan of a 6-month-old infant instantly. Approach The proposed system is remotely controlled by a custom-designed Bluetooth controller. The scanned images can either be manually or automatically aligned to generate a 3D head surface model. Results A full-head 3D scan of a 6-month-old infant can be achieved within 2 s via this system. In testing on a realistic but static infant head model, the average Euclidean error of optode position using this device was 1.8 mm. Conclusions This low-cost 3D registration system therefore has the potential to permit accurate and near-instant fNIRS/DOT spatial registration.
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Affiliation(s)
- Yunjia Xia
- University College London, HUB of Intelligent Neuro-Engineering, CREATe, Division of Surgery and Interventional Science, Stanmore, United Kingdom
- University College London, DOT-HUB, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Kui Wang
- University College London, HUB of Intelligent Neuro-Engineering, CREATe, Division of Surgery and Interventional Science, Stanmore, United Kingdom
- University College London, DOT-HUB, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Addison Billing
- University College London, DOT-HUB, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
- University of Cambridge, Prediction and Learning Laboratory, Department of Psychology, Cambridge, United Kingdom
| | - Matthew Billing
- London South Bank University, School of Engineering, London, United Kingdom
| | - Robert J. Cooper
- University College London, DOT-HUB, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Hubin Zhao
- University College London, HUB of Intelligent Neuro-Engineering, CREATe, Division of Surgery and Interventional Science, Stanmore, United Kingdom
- University College London, DOT-HUB, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
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Su WC, Dashtestani H, Miguel HO, Condy E, Buckley A, Park S, Perreault JB, Nguyen T, Zeytinoglu S, Millerhagen J, Fox N, Gandjbakhche A. Simultaneous multimodal fNIRS-EEG recordings reveal new insights in neural activity during motor execution, observation, and imagery. Sci Rep 2023; 13:5151. [PMID: 36991003 PMCID: PMC10060581 DOI: 10.1038/s41598-023-31609-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2022] [Accepted: 03/14/2023] [Indexed: 03/31/2023] Open
Abstract
Motor execution, observation, and imagery are important skills used in motor learning and rehabilitation. The neural mechanisms underlying these cognitive-motor processes are still poorly understood. We used a simultaneous recording of functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) to elucidate the differences in neural activity across three conditions requiring these processes. Additionally, we used a new method called structured sparse multiset Canonical Correlation Analysis (ssmCCA) to fuse the fNIRS and EEG data and determine the brain regions of neural activity consistently detected by both modalities. Unimodal analyses revealed differentiated activation between conditions; however, the activated regions did not fully overlap across the two modalities (fNIRS: left angular gyrus, right supramarginal gyrus, as well as right superior and inferior parietal lobes; EEG: bilateral central, right frontal, and parietal). These discrepancies might be because fNIRS and EEG detect different signals. Using fused fNIRS-EEG data, we consistently found activation over the left inferior parietal lobe, superior marginal gyrus, and post-central gyrus during all three conditions, suggesting that our multimodal approach identifies a shared neural region associated with the Action Observation Network (AON). This study highlights the strengths of using the multimodal fNIRS-EEG fusion technique for studying AON. Neural researchers should consider using the multimodal approach to validate their findings.
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Affiliation(s)
- Wan-Chun Su
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - Hadis Dashtestani
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - Helga O Miguel
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - Emma Condy
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - Aaron Buckley
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - Soongho Park
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - John B Perreault
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - Thien Nguyen
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - Selin Zeytinoglu
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, USA
| | - John Millerhagen
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA
| | - Nathan Fox
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, USA
| | - Amir Gandjbakhche
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, USA.
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Lin CC, Bair WN, Willson J. Age differences in brain activity in dorsolateral prefrontal cortex and supplementary motor areas during three different walking speed tasks. Hum Mov Sci 2022; 85:102982. [DOI: 10.1016/j.humov.2022.102982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2020] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 11/16/2022]
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Ayaz H, Baker WB, Blaney G, Boas DA, Bortfeld H, Brady K, Brake J, Brigadoi S, Buckley EM, Carp SA, Cooper RJ, Cowdrick KR, Culver JP, Dan I, Dehghani H, Devor A, Durduran T, Eggebrecht AT, Emberson LL, Fang Q, Fantini S, Franceschini MA, Fischer JB, Gervain J, Hirsch J, Hong KS, Horstmeyer R, Kainerstorfer JM, Ko TS, Licht DJ, Liebert A, Luke R, Lynch JM, Mesquida J, Mesquita RC, Naseer N, Novi SL, Orihuela-Espina F, O’Sullivan TD, Peterka DS, Pifferi A, Pollonini L, Sassaroli A, Sato JR, Scholkmann F, Spinelli L, Srinivasan VJ, St. Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report. NEUROPHOTONICS 2022; 9:S24001. [PMID: 36052058 PMCID: PMC9424749 DOI: 10.1117/1.nph.9.s2.s24001] [Citation(s) in RCA: 40] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Hasan Ayaz
- Drexel University, School of Biomedical Engineering, Science, and Health Systems, Philadelphia, Pennsylvania, United States
- Drexel University, College of Arts and Sciences, Department of Psychological and Brain Sciences, Philadelphia, Pennsylvania, United States
| | - Wesley B. Baker
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Giles Blaney
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - David A. Boas
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Heather Bortfeld
- University of California, Merced, Departments of Psychological Sciences and Cognitive and Information Sciences, Merced, California, United States
| | - Kenneth Brady
- Lurie Children’s Hospital, Northwestern University Feinberg School of Medicine, Department of Anesthesiology, Chicago, Illinois, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - Sabrina Brigadoi
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
| | - Erin M. Buckley
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Robert J. Cooper
- University College London, Department of Medical Physics and Bioengineering, DOT-HUB, London, United Kingdom
| | - Kyle R. Cowdrick
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Ippeita Dan
- Chuo University, Faculty of Science and Engineering, Tokyo, Japan
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Anna Devor
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Turgut Durduran
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
- Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Spain
| | - Adam T. Eggebrecht
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Lauren L. Emberson
- University of British Columbia, Department of Psychology, Vancouver, British Columbia, Canada
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Sergio Fantini
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Maria Angela Franceschini
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Jonas B. Fischer
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
| | - Judit Gervain
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Joy Hirsch
- Yale School of Medicine, Department of Psychiatry, Neuroscience, and Comparative Medicine, New Haven, Connecticut, United States
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Keum-Shik Hong
- Pusan National University, School of Mechanical Engineering, Busan, Republic of Korea
- Qingdao University, School of Automation, Institute for Future, Qingdao, China
| | - Roarke Horstmeyer
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
- Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
- Duke University, Department of Physics, Durham, North Carolina, United States
| | - Jana M. Kainerstorfer
- Carnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States
- Carnegie Mellon University, Neuroscience Institute, Pittsburgh, Pennsylvania, United States
| | - Tiffany S. Ko
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Daniel J. Licht
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
| | - Adam Liebert
- Polish Academy of Sciences, Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Robert Luke
- Macquarie University, Department of Linguistics, Sydney, New South Wales, Australia
- Macquarie University Hearing, Australia Hearing Hub, Sydney, New South Wales, Australia
| | - Jennifer M. Lynch
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Jaume Mesquida
- Parc Taulí Hospital Universitari, Critical Care Department, Sabadell, Spain
| | - Rickson C. Mesquita
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Noman Naseer
- Air University, Department of Mechatronics and Biomedical Engineering, Islamabad, Pakistan
| | - Sergio L. Novi
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Western University, Department of Physiology and Pharmacology, London, Ontario, Canada
| | | | - Thomas D. O’Sullivan
- University of Notre Dame, Department of Electrical Engineering, Notre Dame, Indiana, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behaviour Institute, New York, United States
| | | | - Luca Pollonini
- University of Houston, Department of Engineering Technology, Houston, Texas, United States
| | - Angelo Sassaroli
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - João Ricardo Sato
- Federal University of ABC, Center of Mathematics, Computing and Cognition, São Bernardo do Campo, São Paulo, Brazil
| | - Felix Scholkmann
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Lorenzo Spinelli
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Vivek J. Srinivasan
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- NYU Langone Health, Department of Ophthalmology, New York, New York, United States
- NYU Langone Health, Department of Radiology, New York, New York, United States
| | - Keith St. Lawrence
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Yunjie Tong
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Milan, Italy
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Tara Urner
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Heidrun Wabnitz
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Martin Wolf
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Ursula Wolf
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Shiqi Xu
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Changhuei Yang
- California Institute of Technology, Department of Electrical Engineering, Pasadena, California, United States
| | - Arjun G. Yodh
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
| | - Meryem A. Yücel
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Wenjun Zhou
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- China Jiliang University, College of Optical and Electronic Technology, Hangzhou, Zhejiang, China
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Fu X, Richards JE. Age-related changes in diffuse optical tomography sensitivity profiles from childhood to adulthood. JOURNAL OF BIOMEDICAL OPTICS 2022; 27:083004. [PMID: 35810323 PMCID: PMC9270691 DOI: 10.1117/1.jbo.27.8.083004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 06/22/2022] [Indexed: 06/15/2023]
Abstract
SIGNIFICANCE Diffuse optical tomography (DOT) uses near-infrared light spectroscopy to measure changes in cerebral hemoglobin concentration. Anatomical interpretations of the brain location that generates the hemodynamic signal require accurate descriptions of the DOT sensitivity to the underlying cortex. DOT sensitivity profiles are different in infants compared with adults. However, the descriptions of DOT sensitivity profiles from early childhood to adulthood are lacking despite the continuous head and brain development. AIM We aim to investigate age-related differences in DOT sensitivity profiles in individuals aged from 2 to 34 years with narrow age ranges of 0.5 or 1 year. APPROACH We implemented existing photon migration simulation methods and computed source-detector channel DOT sensitivity using age-appropriate, realistic head models. RESULTS DOT sensitivity profiles change systematically as a function of source-detector separation distance for all age groups. Children displayed distinctive DOT sensitivity profiles compared to older individuals, and the differences were enhanced at larger separation distances. CONCLUSIONS The findings have important implications for the design of source-detector placement and image reconstruction. Age-appropriate realistic head models should be used to provide anatomical guidance for standalone DOT data. Using age-inappropriate head models will have more negative impacts on estimation accuracy in younger children.
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Affiliation(s)
- Xiaoxue Fu
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
| | - John E. Richards
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
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McKay C, Wijeakumar S, Rafetseder E, Shing YL. Disentangling age and schooling effects on inhibitory control development: An fNIRS investigation. Dev Sci 2021; 25:e13205. [PMID: 34865293 DOI: 10.1111/desc.13205] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 11/17/2021] [Accepted: 11/19/2021] [Indexed: 12/11/2022]
Abstract
Children show marked improvements in executive functioning (EF) between 4 and 7 years of age. In many societies, this time period coincides with the start of formal school education, in which children are required to follow rules in a structured environment, drawing heavily on EF processes such as inhibitory control. This study aimed to investigate the longitudinal development of two aspects of inhibitory control, namely response inhibition and response monitoring and their neural correlates. Specifically, we examined how their longitudinal development may differ by schooling experience, and their potential significance in predicting academic outcomes. Longitudinal data were collected in two groups of children at their homes. At T1, all children were roughly 4.5 years of age and neither group had attended formal schooling. One year later at T2, one group (P1, n = 40) had completed one full year of schooling while the other group (KG, n = 40) had stayed in kindergarten. Behavioural and brain activation data (measured with functional near-infrared spectroscopy, fNIRS) in response to a Go/No-Go task and measures of academic achievement were collected. We found that P1 children, compared to KG children, showed a greater change over time in activation related to response monitoring in the bilateral frontal cortex. The change in left frontal activation difference showed a small positive association with math performance. Overall, the school environment is important in shaping the development of the brain functions underlying the monitoring of one own's performance.
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Affiliation(s)
- Courtney McKay
- Division of Psychology, University of Stirling, Stirling, Scotland
| | - Sobanawartiny Wijeakumar
- Division of Psychology, University of Stirling, Stirling, Scotland.,School of Psychology, University of Nottingham, Nottingham, UK
| | - Eva Rafetseder
- Division of Psychology, University of Stirling, Stirling, Scotland.,Department of Psychology, University of Konstanz, Konstanz, Germany
| | - Yee Lee Shing
- Department of Psychology, Goethe University Frankfurt, Frankfurt, Germany.,Center for Individual Development and Adaptive Education of Children at Risk (IDeA), Frankfurt, Germany
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Hu XS, Nascimento TD, DaSilva AF. Shedding light on pain for the clinic: a comprehensive review of using functional near-infrared spectroscopy to monitor its process in the brain. Pain 2021; 162:2805-2820. [PMID: 33990114 PMCID: PMC8490487 DOI: 10.1097/j.pain.0000000000002293] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Accepted: 03/29/2021] [Indexed: 11/27/2022]
Abstract
ABSTRACT Pain is a complex experience that involves sensation, emotion, and cognition. The subjectivity of the traditional pain measurement tools has expedited the interest in developing neuroimaging techniques to monitor pain objectively. Among noninvasive neuroimaging techniques, functional near-infrared spectroscopy (fNIRS) has balanced spatial and temporal resolution; yet, it is portable, quiet, and cost-effective. These features enable fNIRS to image the cortical mechanisms of pain in a clinical environment. In this article, we evaluated pain neuroimaging studies that used the fNIRS technique in the past decade. Starting from the experimental design, we reviewed the regions of interest, probe localization, data processing, and primary findings of these existing fNIRS studies. We also discussed the fNIRS imaging's potential as a brain surveillance technique for pain, in combination with artificial intelligence and extended reality techniques. We concluded that fNIRS is a brain imaging technique with great potential for objective pain assessment in the clinical environment.
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Affiliation(s)
- Xiao-Su Hu
- University of Michigan, School of Dentistry, Biologic & Materials Sciences Department, Hedache & Orofacial Pain Effort Lab
| | - Thiago D. Nascimento
- University of Michigan, School of Dentistry, Biologic & Materials Sciences Department, Hedache & Orofacial Pain Effort Lab
| | - Alexandre F. DaSilva
- University of Michigan, School of Dentistry, Biologic & Materials Sciences Department, Hedache & Orofacial Pain Effort Lab
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Fu X, Richards JE. devfOLD: a toolbox for designing age-specific fNIRS channel placement. NEUROPHOTONICS 2021; 8:045003. [PMID: 34881349 PMCID: PMC8647945 DOI: 10.1117/1.nph.8.4.045003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2021] [Accepted: 11/09/2021] [Indexed: 05/20/2023]
Abstract
Significance: Near-infrared spectroscopy (NIRS) is a noninvasive technique that uses scalp-placed sensors to measure cerebral hemoglobin concentration. Commercial NIRS instruments do not allow for whole-head coverage and do not intrinsically indicate which brain areas generate the NIRS signal. Hence, the challenge is to design source-detector channel arrangement that maximizes sensitivity to a given brain region of interest (ROI). Existing methods for optimizing channel placement design have been developed using adult head models. Thus, they have limited utility for developmental research. Aim: We aim to build an application from an existing toolbox (fOLD) that guides NIRS channel configuration based on age group, stereotaxic atlas, and ROI (devfOLD). Approach: The devfOLD provides NIRS channel-to-ROI specificity computed using photon propagation simulation with realistic head models from infant, child, and adult age groups. Results: Cortical locations and user-specified specificity cut-off values influence the between-age consistency and differences in the ROI-to-channel correspondence among the example infant and adult age groups. Conclusions: The study highlights the importance of incorporating age-specific head models for optimizing NIRS channel configurations. The devfOLD toolbox is publicly shared and compatible with multiple operating systems.
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Affiliation(s)
- Xiaoxue Fu
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
| | - John E. Richards
- University of South Carolina, Department of Psychology, Columbia, South Carolina, United States
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Jackson ES, Wijeakumar S, Beal DS, Brown B, Zebrowski PM, Spencer JP. Speech planning and execution in children who stutter: Preliminary findings from a fNIRS investigation. J Clin Neurosci 2021; 91:32-42. [PMID: 34373047 DOI: 10.1016/j.jocn.2021.06.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 05/03/2021] [Accepted: 06/14/2021] [Indexed: 10/21/2022]
Abstract
Few studies have investigated the neural mechanisms underlying speech production in children who stutter (CWS), despite the critical importance of understanding these mechanisms closer to the time of stuttering onset. The relative contributions of speech planning and execution in CWS therefore are also unknown. Using functional near-infrared spectroscopy, the current study investigated neural mechanisms of planning and execution in a small sample of 9-12 year-old CWS and controls (N = 12) by implementing two tasks that manipulated speech planning and execution loads. Planning was associated with atypical activation in bilateral inferior frontal gyrus and right supramarginal gyrus. Execution was associated with atypical activation in bilateral precentral gyrus and inferior frontal gyrus, as well as right supramarginal gyrus and superior temporal gyrus. The CWS exhibited some activation patterns that were similar to the adults who stutter (AWS) as reported in our previous study: atypical planning in frontal areas including left inferior frontal gyrus and atypical execution in fronto-temporo-parietal regions including left precentral gyrus, and right inferior frontal, superior temporal, and supramarginal gyri. However, differences also emerged. Whereas CWS and AWS both appear to exhibit atypical activation in right inferior and supramarginal gyri during execution, only CWS appear to exhibit this same pattern during planning. In addition, the CWS appear to exhibit atypical activation in left inferior frontal and right precentral gyri related to execution, whereas AWS do not. These preliminary results are discussed in the context of possible impairments in sensorimotor integration and inhibitory control for CWS.
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Affiliation(s)
- Eric S Jackson
- Department of Communicative Sciences and Disorders, New York University, 665 Broadway, 9th Floor, New York, NY 10012, USA.
| | | | - Deryk S Beal
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, 150 Kilgour Road Toronto, Ontario M4G 1R8, Canada; Department of Speech-Language Pathology, Faculty of Medicine, University of Toronto, 160-500 University Avenue, Toronto, ON M5G 1V7, Canada
| | - Bryan Brown
- Department of Communication Sciences and Disorders, University of Wisconsin-Eau Claire, 239 Water Street, Eau Claire, WI 54702, USA
| | - Patricia M Zebrowski
- Department of Communication Sciences and Disorders, Wendell Johnson Speech and Hearing Center, Iowa City, IA 52242, USA
| | - John P Spencer
- School of Psychology, University of East Anglia, Lawrence Stenhouse Building 0.09, Norwich NR4 7TJ, UK
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11
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Zhao Y, Xiao X, Jiang Y, Sun P, Zhang Z, Gong Y, Li Z, Zhu C. Transcranial brain atlas-based optimization for functional near-infrared spectroscopy optode arrangement: Theory, algorithm, and application. Hum Brain Mapp 2021; 42:1657-1669. [PMID: 33332685 PMCID: PMC7978141 DOI: 10.1002/hbm.25318] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 11/30/2020] [Accepted: 12/01/2020] [Indexed: 11/23/2022] Open
Abstract
The quality of optode arrangement is crucial for group imaging studies when using functional near-infrared spectroscopy (fNIRS). Previous studies have demonstrated the promising effectiveness of using transcranial brain atlases (TBAs), in a manual and intuition-based way, to guide optode arrangement when individual structural MRI data are unavailable. However, the theoretical basis of using TBA to optimize optode arrangement remains unclear, which leads to manual and subjective application. In this study, we first describe the theoretical basis of TBA-based optimization of optode arrangement using a mathematical framework. Second, based on the theoretical basis, an algorithm is proposed for automatically arranging optodes on a virtual scalp. The resultant montage is placed onto the head of each participant guided by a low-cost and portable navigation system. We compared our method with the widely used 10/20-system-assisted optode arrangement procedure, using finger-tapping and working memory tasks as examples of both low- and high-level cognitive systems. Performance, including optode montage designs, locations on each participant's scalp, brain activation, as well as ground truth indices derived from individual MRI data were evaluated. The results give convergent support for our method's ability to provide more accurate, consistent and efficient optode arrangements for fNIRS group imaging than the 10/20 method.
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Affiliation(s)
- Yang Zhao
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
| | - Xiang Xiao
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- Neuroimaging Research Branch, National Institute on Drug AbuseNational Institutes of HealthBaltimoreMarylandUSA
| | - Yi‐Han Jiang
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
| | - Pei‐Pei Sun
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
| | - Zong Zhang
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
| | - Yi‐Long Gong
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
| | - Zheng Li
- Center for Cognition and Neuroergonomics, State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal University at ZhuhaiZhuhaiChina
- IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
- Center for Collaboration and Innovation in Brain and Learning SciencesBeijing Normal UniversityBeijingChina
| | - Chao‐Zhe Zhu
- State Key Laboratory of Cognitive Neuroscience and LearningBeijing Normal UniversityBeijingChina
- IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
- Center for Collaboration and Innovation in Brain and Learning SciencesBeijing Normal UniversityBeijingChina
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12
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Benitez-Andonegui A, Lührs M, Nagels-Coune L, Ivanov D, Goebel R, Sorger B. Guiding functional near-infrared spectroscopy optode-layout design using individual (f)MRI data: effects on signal strength. NEUROPHOTONICS 2021; 8:025012. [PMID: 34155480 PMCID: PMC8211086 DOI: 10.1117/1.nph.8.2.025012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 05/11/2021] [Indexed: 05/20/2023]
Abstract
Significance: Designing optode layouts is an essential step for functional near-infrared spectroscopy (fNIRS) experiments as the quality of the measured signal and the sensitivity to cortical regions-of-interest depend on how optodes are arranged on the scalp. This becomes particularly relevant for fNIRS-based brain-computer interfaces (BCIs), where developing robust systems with few optodes is crucial for clinical applications. Aim: Available resources often dictate the approach researchers use for optode-layout design. We investigated whether guiding optode layout design using different amounts of subject-specific magnetic resonance imaging (MRI) data affects the fNIRS signal quality and sensitivity to brain activation when healthy participants perform mental-imagery tasks typically used in fNIRS-BCI experiments. Approach: We compared four approaches that incrementally incorporated subject-specific MRI information while participants performed mental-calculation, mental-rotation, and inner-speech tasks. The literature-based approach (LIT) used a literature review to guide the optode layout design. The probabilistic approach (PROB) employed individual anatomical data and probabilistic maps of functional MRI (fMRI)-activation from an independent dataset. The individual fMRI (iFMRI) approach used individual anatomical and fMRI data, and the fourth approach used individual anatomical, functional, and vascular information of the same subject (fVASC). Results: The four approaches resulted in different optode layouts and the more informed approaches outperformed the minimally informed approach (LIT) in terms of signal quality and sensitivity. Further, PROB, iFMRI, and fVASC approaches resulted in a similar outcome. Conclusions: We conclude that additional individual MRI data lead to a better outcome, but that not all the modalities tested here are required to achieve a robust setup. Finally, we give preliminary advice to efficiently using resources for developing robust optode layouts for BCI and neurofeedback applications.
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Affiliation(s)
- Amaia Benitez-Andonegui
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
- Maastricht University, Laboratory for Cognitive Robotics and Complex Self-Organizing Systems, Department of Data Science and Knowledge Engineering, Maastricht, The Netherlands
- Address all correspondence to Amaia Benitez-Andonegui,
| | - Michael Lührs
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
- Brain Innovation B.V., Research Department, Maastricht, The Netherlands
| | - Laurien Nagels-Coune
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
| | - Dimo Ivanov
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
| | - Rainer Goebel
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
- Brain Innovation B.V., Research Department, Maastricht, The Netherlands
| | - Bettina Sorger
- Maastricht University, Maastricht Brain Imaging Center, Department of Cognitive Neuroscience, Maastricht, The Netherlands
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13
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Forbes SH, Wijeakumar S, Eggebrecht AT, Magnotta VA, Spencer JP. Processing pipeline for image reconstructed fNIRS analysis using both MRI templates and individual anatomy. NEUROPHOTONICS 2021; 8:025010. [PMID: 35106319 PMCID: PMC8786393 DOI: 10.1117/1.nph.8.2.025010] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 05/18/2021] [Indexed: 05/29/2023]
Abstract
Significance: Image reconstruction of fNIRS data is a useful technique for transforming channel-based fNIRS into a volumetric representation and managing spatial variance based on optode location. We present an innovative integrated pipeline for image reconstruction of fNIRS data using either MRI templates or individual anatomy. Aim: We demonstrate a pipeline with accompanying code to allow users to clean and prepare optode location information, prepare and standardize individual anatomical images, create the light model, run the 3D image reconstruction, and analyze data in group space. Approach: We synthesize a combination of new and existing software packages to create a complete pipeline, from raw data to analysis. Results: This pipeline has been tested using both templates and individual anatomy, and on data from different fNIRS data collection systems. We show high temporal correlations between channel-based and image-based fNIRS data. In addition, we demonstrate the reliability of this pipeline with a sample dataset that included 74 children as part of a longitudinal study taking place in Scotland. We demonstrate good correspondence between data in channel space and image reconstructed data. Conclusions: The pipeline presented here makes a unique contribution by integrating multiple tools to assemble a complete pipeline for image reconstruction in fNIRS. We highlight further issues that may be of interest to future software developers in the field.
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Affiliation(s)
- Samuel H. Forbes
- University of East Anglia, School of Psychology, Lawrence Stenhouse Building, Norwich, United Kingdom
| | | | - Adam T. Eggebrecht
- Washington University, Mallinckrodt Institute of Radiology, St Louis, Missouri, United States
| | | | - John P. Spencer
- University of East Anglia, School of Psychology, Lawrence Stenhouse Building, Norwich, United Kingdom
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14
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Condy EE, Miguel HO, Millerhagen J, Harrison D, Khaksari K, Fox N, Gandjbakhche A. Characterizing the Action-Observation Network Through Functional Near-Infrared Spectroscopy: A Review. Front Hum Neurosci 2021; 15:627983. [PMID: 33679349 PMCID: PMC7930074 DOI: 10.3389/fnhum.2021.627983] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 01/18/2021] [Indexed: 12/19/2022] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is a neuroimaging technique that has undergone tremendous growth over the last decade due to methodological advantages over other measures of brain activation. The action-observation network (AON), a system of brain structures proposed to have “mirroring” abilities (e.g., active when an individual completes an action or when they observe another complete that action), has been studied in humans through neural measures such as fMRI and electroencephalogram (EEG); however, limitations of these methods are problematic for AON paradigms. For this reason, fNIRS is proposed as a solution to investigating the AON in humans. The present review article briefly summarizes previous neural findings in the AON and examines the state of AON research using fNIRS in adults. A total of 14 fNIRS articles are discussed, paying particular attention to methodological choices and considerations while summarizing the general findings to aid in developing better protocols to study the AON through fNIRS. Additionally, future directions of this work are discussed, specifically in relation to researching AON development and potential multimodal imaging applications.
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Affiliation(s)
- Emma E Condy
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - Helga O Miguel
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - John Millerhagen
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - Doug Harrison
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - Kosar Khaksari
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
| | - Nathan Fox
- Department of Human Development and Quantitative Methodology, University of Maryland, College Park, MD, United States
| | - Amir Gandjbakhche
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), National Institutes of Health, Bethesda, MD, United States
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15
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McKay CA, Shing YL, Rafetseder E, Wijeakumar S. Home assessment of visual working memory in pre-schoolers reveals associations between behaviour, brain activation and parent reports of life stress. Dev Sci 2021; 24:e13094. [PMID: 33523548 DOI: 10.1111/desc.13094] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 10/28/2020] [Accepted: 01/13/2021] [Indexed: 01/07/2023]
Abstract
Visual working memory (VWM) is reliably predictive of fluid intelligence and academic achievements. The objective of the current study was to investigate individual differences in pre-schoolers' VWM processing by examining the association between behaviour, brain function and parent-reported measures related to the child's environment. We used a portable functional near-infrared spectroscopy system to record from the frontal and parietal cortices of 4.5-year-old children (N = 74) as they completed a colour change-detection VWM task in their homes. Parents were asked to fill in questionnaires on temperament, academic aspirations, home environment and life stress. Children were median-split into a low-performing (LP) and a high-performing (HP) group based on the number of items they could successfully remember during the task. LPs increasingly activated channels in the left frontal and bilateral parietal cortices with increasing load, whereas HPs showed no difference in activation. Our findings suggest that LPs recruited more neural resources than HPs when their VWM capacity was challenged. We employed mediation analyses to examine the association between the difference in activation between the highest and lowest loads and variables from the questionnaires. The difference in activation between loads in the left parietal cortex partially mediated the association between parent-reported stressful life events and VWM performance. Critically, our findings show that the association between VWM capacity, left parietal activation and indicators of life stress is important to understand the nature of individual differences in VWM in pre-school children.
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Affiliation(s)
- Courtney A McKay
- Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, UK
| | - Yee Lee Shing
- Institute of Psychology, Goethe University Frankfurt, Frankfurt, Germany.,Center for Individual Development and Adaptive Education of Children at Risk (IDeA), Frankfurt, Germany
| | - Eva Rafetseder
- Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, UK
| | - Sobanawartiny Wijeakumar
- Psychology, Faculty of Natural Sciences, University of Stirling, Stirling, UK.,School of Psychology, University of Nottingham, Nottingham, UK
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16
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Pecukonis M, Perdue KL, Wong J, Tager-Flusberg H, Nelson CA. Exploring the relation between brain response to speech at 6-months and language outcomes at 24-months in infants at high and low risk for autism spectrum disorder: A preliminary functional near-infrared spectroscopy study. Dev Cogn Neurosci 2020; 47:100897. [PMID: 33338817 PMCID: PMC7750322 DOI: 10.1016/j.dcn.2020.100897] [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: 05/08/2020] [Revised: 11/03/2020] [Accepted: 11/30/2020] [Indexed: 11/19/2022] Open
Abstract
Brain response distributed across regions in infants at high risk for autism. Brain response localized to anterior regions in 6-month-old low risk infants. Comparing groups, high risk infants had reduced response in anterior regions. High risk infants had greater response than low risk infants in right posterior. Brain response to speech predicted language outcomes in low risk infants only.
Infants at high familial risk for autism spectrum disorder (ASD) are at increased risk for language impairments. Studies have demonstrated that atypical brain response to speech is related to language impairments in this population, but few have examined this relation longitudinally. We used functional near-infrared spectroscopy (fNIRS) to investigate the neural correlates of speech processing in 6-month-old infants at high (HRA) and low risk (LRA) for autism. We also assessed the relation between brain response to speech at 6-months and verbal developmental quotient (VDQ) scores at 24-months. LRA infants exhibited greater brain response to speech in bilateral anterior regions of interest (ROIs) compared to posterior ROIs, while HRA infants exhibited similar brain response across all ROIs. Compared to LRA infants, HRA+ infants who were later diagnosed with ASD had reduced brain response in bilateral anterior ROIs, while HRA- infants who were not later diagnosed with ASD had increased brain response in right posterior ROI. Greater brain response in left anterior ROI predicted VDQ scores for LRA infants only. Findings highlight the importance of studying HRA+ and HRA- infants separately, and implicate a different, more distributed neural system for speech processing in HRA infants that is not related to language functioning.
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Affiliation(s)
- Meredith Pecukonis
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02215, USA.
| | - Katherine L Perdue
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA 02215, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02215, USA
| | - Jillian Wong
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Helen Tager-Flusberg
- Department of Psychological & Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Charles A Nelson
- Division of Developmental Medicine, Boston Children's Hospital, Boston, MA 02215, USA; Department of Pediatrics, Harvard Medical School, Boston, MA 02215, USA; Harvard Graduate School of Education, Cambridge, MA, 02138, USA
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17
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HU XINHUA, XIAO GANG, ZHU KEXIN, HU SHUYI, CHEN JIU, YU YUN. APPLICATION OF FUNCTIONAL NEAR-INFRARED SPECTROSCOPY IN NEUROLOGICAL DISEASES: EPILEPSY, STROKE AND PARKINSON. J MECH MED BIOL 2020. [DOI: 10.1142/s0219519420400230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The functional near-infrared spectroscopy (fNIRS) technology is an optical imaging technology that applies near-infrared light to measure the oxygenated and deoxygenated hemoglobin concentration alteration in cortical brain structures. It has the ability to directly measure changes in the blood oxygen level of the high temporal resolution associated with neural activation. Thus, it has been utilized in different neurological diseases, such as epilepsy, stroke, and Parkinson. The work of this paper will focus on the application of the fNIRS in the three neurological diseases and the principle of fNIRS. Moreover, the difficulties and challenges that the technology is currently experiencing have been discussed.
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Affiliation(s)
- XINHUA HU
- Department of Neurosurgery, the Affiliated Brain Hospital of Nanjing Medical University, Nanjing Medical University, Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
| | - GANG XIAO
- The Key Laboratory of Metabolism and Molecular Medicine of the Ministry of Education, Department of Biochemistry and Molecular Biology of School of Basic Medical Sciences and Department of Endocrinology, Fudan University, Shanghai, 200032, P. R. China
| | - KEXIN ZHU
- The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
| | - SHUYI HU
- The First Affiliated Hospital of Nanjing Medical University, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
| | - JIU CHEN
- Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
| | - YUN YU
- Department of Medical Informatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Institute of Brain Functional Imaging, Nanjing Medical University, Nanjing, Jiangsu, 210029, P. R. China
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18
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Rahman MA, Siddik AB, Ghosh TK, Khanam F, Ahmad M. A Narrative Review on Clinical Applications of fNIRS. J Digit Imaging 2020; 33:1167-1184. [PMID: 32989620 PMCID: PMC7573058 DOI: 10.1007/s10278-020-00387-1] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2019] [Revised: 08/06/2020] [Accepted: 09/14/2020] [Indexed: 01/08/2023] Open
Abstract
Functional near-infrared spectroscopy (fNIRS) is a relatively new imaging modality in the functional neuroimaging research arena. The fNIRS modality non-invasively investigates the change of blood oxygenation level in the human brain utilizing the transillumination technique. In the last two decades, the interest in this modality is gradually evolving for its real-time monitoring, relatively low-cost, radiation-less environment, portability, patient-friendliness, etc. Including brain-computer interface and functional neuroimaging research, this technique has some important application of clinical perspectives such as Alzheimer's disease, schizophrenia, dyslexia, Parkinson's disease, childhood disorders, post-neurosurgery dysfunction, attention, functional connectivity, and many more can be diagnosed as well as in some form of assistive modality in clinical approaches. Regarding the issue, this review article presents the current scopes of fNIRS in medical assistance, clinical decision making, and future perspectives. This article also covers a short history of fNIRS, fundamental theories, and significant outcomes reported by a number of scholarly articles. Since this review article is hopefully the first one that comprehensively explores the potential scopes of the fNIRS in a clinical perspective, we hope it will be helpful for the researchers, physicians, practitioners, current students of the functional neuroimaging field, and the related personnel for their further studies and applications.
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Affiliation(s)
- Md. Asadur Rahman
- Department of Biomedical Engineering, Military Institute of Science and Technology (MIST), Dhaka, 1216 Bangladesh
| | - Abu Bakar Siddik
- Department of Biomedical Engineering, Khulna University of Engineering & Technology (KUET), Khulna, 9203 Bangladesh
| | - Tarun Kanti Ghosh
- Department of Biomedical Engineering, Khulna University of Engineering & Technology (KUET), Khulna, 9203 Bangladesh
| | - Farzana Khanam
- Department of Biomedical Engineering, Jashore University of Science and Technology (JUST), Jashore, 7408 Bangladesh
| | - Mohiuddin Ahmad
- Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology (KUET), Khulna, 9203 Bangladesh
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19
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Hu XS, Wagley N, Rioboo AT, DaSilva AF, Kovelman I. Photogrammetry-based stereoscopic optode registration method for functional near-infrared spectroscopy. JOURNAL OF BIOMEDICAL OPTICS 2020; 25:JBO-200049R. [PMID: 32880124 PMCID: PMC7463164 DOI: 10.1117/1.jbo.25.9.095001] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 08/11/2020] [Indexed: 05/24/2023]
Abstract
SIGNIFICANCE Functional near-infrared spectroscopy (fNIRS) is an emerging brain imaging technique due to its small size, low cost, minimum scanning sonic noise, and portability. Unfortunately, because this technique does not provide neuroanatomical information to accompany the functional data, its data interpretation remains a persistent challenge in fNIRS brain imaging applications. The two most popular approaches for fNIRS anatomical registration are magnetic resonance imaging (MRI) and three-dimensional (3-D) digitization. MRI scanning yields high-precision registration but reduces the cost-effectiveness and accessibility of fNIRS imaging. Alternatively, the low cost and portable 3-D digitizers are affected by magnetic properties of ambient metal objects, including participant clothing, testing equipment, medical implants, and so forth. AIM To overcome these obstacles and provide accessible and reliable neuroanatomical registration for fNIRS imaging, we developed and explored a photogrammetry optode registration (POR) method. APPROACH The POR method uses a consumer-grade camera to reconstruct a 3-D image of the fNIRS optode-set, including light emitters and detectors, on a participant's head. This reconstruction process uses a linear-time incremental structure from motion (LTI-SfM) algorithm, based on 100 to 150 digital photos. The POR method then aligns the reconstructed image with an anatomical template of the brain. RESULTS To validate this method, we tested 22 adult and 19 child participants using the POR method and MRI imaging. The results comparisons suggest on average 55% and 46% overlap across all data channel measurements registered by the two methods in adult and children, respectively. Importantly, this overlap reached 65% and 60% in only the frontal channels. CONCLUSIONS These results suggested that the mismatch in registration was partially due to higher variation in backward optode placement rather than the registration efficacy. Therefore, the photo-based registration method can offer an accessible and reliable approach to neuroanatomical registration of fNIRS as well as other surface-based neuroimaging and neuromodulation methods.
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Affiliation(s)
- Xiao-Su Hu
- University of Michigan, School of Dentistry, Department of Biologic and Materials Sciences and Prosthodontics, Headache & Orofacial Pain Effort (H.O.P.E.) Lab, Ann Arbor, Michigan, United States
- University of Michigan, Center for Human Growth and Development, Ann Arbor, Michigan, United States
| | - Neelima Wagley
- University of Michigan, Department of Psychology, Ann Arbor, Michigan, United States
| | - Akemi Tsutsumi Rioboo
- University of Michigan, Center for Human Growth and Development, Ann Arbor, Michigan, United States
| | - Alexandre F. DaSilva
- University of Michigan, School of Dentistry, Department of Biologic and Materials Sciences and Prosthodontics, Headache & Orofacial Pain Effort (H.O.P.E.) Lab, Ann Arbor, Michigan, United States
- University of Michigan, Center for Human Growth and Development, Ann Arbor, Michigan, United States
| | - Ioulia Kovelman
- University of Michigan, Center for Human Growth and Development, Ann Arbor, Michigan, United States
- University of Michigan, Department of Psychology, Ann Arbor, Michigan, United States
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20
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Blaney G, Sassaroli A, Fantini S. Design of a source-detector array for dual-slope diffuse optical imaging. THE REVIEW OF SCIENTIFIC INSTRUMENTS 2020; 91:093702. [PMID: 33003793 PMCID: PMC7519873 DOI: 10.1063/5.0015512] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 08/23/2020] [Indexed: 05/27/2023]
Abstract
We recently proposed a dual-slope technique for diffuse optical spectroscopy and imaging of scattering media. This technique requires a special configuration of light sources and optical detectors to create dual-slope sets. Here, we present methods for designing, optimizing, and building an optical imaging array that features m dual-slope sets to image n voxels. After defining the m × n matrix (S) that describes the sensitivity of the m dual-slope measurements to absorption perturbations in each of the n voxels, we formulate the inverse imaging problem in terms of the Moore-Penrose pseudoinverse matrix of S (S+). This approach allows us to introduce several measures of imaging performance: reconstruction accuracy (correct spatial mapping), crosstalk (incorrect spatial mapping), resolution (point spread function), and localization (offset between actual and reconstructed point perturbations). Furthermore, by considering the singular value decomposition formulation, we show the significance of visualizing the first m right singular vectors of S, whose linear combination generates the reconstructed map. We also describe methods to build a physical array using a three-layer mesh structure (two polyethylene films and polypropylene hook-and-loop fabric) embedded in silicone (PDMS). Finally, we apply these methods to design two arrays and choose one to construct. The chosen array consists of 16 illumination fibers, 10 detection fibers, and 27 dual-slope sets for dual-slope imaging optimized for the size of field of view and localization of absorption perturbations. This particular array is aimed at functional near-infrared spectroscopy of the human brain, but the methods presented here are of general applicability to a variety of devices and imaging scenarios.
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Affiliation(s)
- Giles Blaney
- Department of Biomedical Engineering, Tufts University,
Medford, Massachusetts 02155, USA
| | - Angelo Sassaroli
- Department of Biomedical Engineering, Tufts University,
Medford, Massachusetts 02155, USA
| | - Sergio Fantini
- Department of Biomedical Engineering, Tufts University,
Medford, Massachusetts 02155, USA
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21
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Delgado Reyes L, Wijeakumar S, Magnotta VA, Forbes SH, Spencer JP. The functional brain networks that underlie visual working memory in the first two years of life. Neuroimage 2020; 219:116971. [PMID: 32454208 PMCID: PMC7443700 DOI: 10.1016/j.neuroimage.2020.116971] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 05/14/2020] [Accepted: 05/16/2020] [Indexed: 01/23/2023] Open
Abstract
Visual working memory (VWM) is a central cognitive system used to compare views of the world and detect changes in the local environment. This system undergoes dramatic development in the first two years; however, we know relatively little about the functional organization of VWM at the level of the brain. Here, we used image-based functional near-infrared spectroscopy (fNIRS) to test four hypotheses about the spatial organization of the VWM network in early development. Four-month-olds, 1-year-olds, and 2-year-olds completed a VWM task while we recorded neural activity from 19 cortical regions-of-interest identified from a meta-analysis of the adult fMRI literature on VWM. Results showed significant task-specific functional activation near 6 of 19 ROIs, revealing spatial consistency in the brain regions activated in our study and brain regions identified to be part of the VWM network in adult fMRI studies. Working memory related activation was centered on bilateral anterior intraparietal sulcus (aIPS), left temporoparietal junction (TPJ), and left ventral occipital complex (VOC), while visual exploratory measures were associated with activation in right dorsolateral prefrontal cortex, left TPJ, and bilateral IPS. Results show that a distributed brain network underlies functional changes in VWM in infancy, revealing new insights into the neural mechanisms that support infants’ improved ability to remember visual information and to detect changes in an on-going visual stream. A distributed brain network underlies functional changes in VWM in infancy and toddlerhood. This network shows robust engagement of similar brain regions identified in fMRI studies with adults as early as four months. Working memory related activation was centered on bilateral anterior intraparietal sulcus, left temporoparietal junction, and left ventral occipital complex Visual exploratory measures were associated with activation in right dorsolateral prefrontal cortex, bilateral anterior intraparietal sulcus, and left temporoparietal junction.
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Affiliation(s)
- Lourdes Delgado Reyes
- School of Psychology, University of East Anglia, UK; Department of Psychology, University of Pennsylvania, USA
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Jiang Y, Li Z, Zhao Y, Xiao X, Zhang W, Sun P, Yang Y, Zhu C. Targeting brain functions from the scalp: Transcranial brain atlas based on large-scale fMRI data synthesis. Neuroimage 2020; 210:116550. [PMID: 31981781 DOI: 10.1016/j.neuroimage.2020.116550] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 12/16/2019] [Accepted: 01/14/2020] [Indexed: 12/28/2022] Open
Abstract
Transcranial brain mapping techniques, such as functional near-infrared spectroscopy (fNIRS) and transcranial magnetic stimulation (TMS), have been playing an increasingly important role in studies of human brain functions. Given a brain function of interest, fNIRS probes and TMS coils should be properly placed on the scalp to ensure that the function is effectively measured or modulated. However, since brain activity is inside the skull and invisible to the researcher during placement, this blind targeting may cause the device to partially or completely miss the functional target, resulting in inconsistent experimental results and divergent clinical outcomes, especially when participants' structural MRI data are not available. To address this issue, we propose here a framework for targeting a designated function directly from the scalp. First, a functional brain atlas for the targeted brain function is constructed via a meta-analysis of large-scale functional magnetic resonance imaging datasets. Second, the functional brain atlas is presented on the scalp surface by using a transcranial mapping previously established from an structural MRI dataset (n = 114), resulting in a novel functional transcranial brain atlas (fTBA). Finally, a low-cost, portable scalp-navigation system is used to localize the transcranial device on the individual's scalp with the guidance of the fTBA. To demonstrate the feasibility of the targeting framework, both fNIRS and TMS mapping experiments were conducted. The results show that fTBA-guided fNIRS positioning can detect functional activity with high sensitivity and specificity for working memory and motor systems; Moreover, compared with traditional TMS targeting approaches (e.g. the International 10-20 System and the conventional 5-cm rule), the fTBA suggested motor stimulation site is closesr to both the motor hotspot and the center of gravity of motor evoked potentials (MEP-COG). In summary, the proposed method unblinds the transcranial function targeting process using prior information, providing an effective and straightforward approach to transcranial brain mapping studies, especially those without participants' structural MRI data.
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Affiliation(s)
- Yihan Jiang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zheng Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
| | - Yang Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xiang Xiao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Wei Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Peipei Sun
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, USA
| | - Chaozhe Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China.
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Putt SS, Wijeakumar S, Spencer JP. Prefrontal cortex activation supports the emergence of early stone age toolmaking skill. Neuroimage 2019; 199:57-69. [DOI: 10.1016/j.neuroimage.2019.05.056] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 05/20/2019] [Accepted: 05/21/2019] [Indexed: 01/01/2023] Open
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Wijeakumar S, Kumar A, Delgado Reyes LM, Tiwari M, Spencer JP. Early adversity in rural India impacts the brain networks underlying visual working memory. Dev Sci 2019; 22:e12822. [PMID: 30803122 PMCID: PMC6767418 DOI: 10.1111/desc.12822] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2018] [Revised: 12/26/2018] [Accepted: 02/12/2019] [Indexed: 12/16/2022]
Abstract
There is a growing need to understand the global impact of poverty on early brain and behavioural development, particularly with regard to key cognitive processes that emerge in early development. Although the impact of adversity on brain development can trap children in an intergenerational cycle of poverty, the massive potential for brain plasticity is also a source of hope: reliable, accessible, culturally agnostic methods to assess early brain development in low resource settings might be used to measure the impact of early adversity, identify infants for timely intervention and guide the development and monitor the effectiveness of early interventions. Visual working memory (VWM) is an early marker of cognitive capacity that has been assessed reliably in early infancy and is predictive of later academic achievement in Western countries. Here, we localized the functional brain networks that underlie VWM in early development in rural India using a portable neuroimaging system, and we assessed the impact of adversity on these brain networks. We recorded functional brain activity as young children aged 4-48 months performed a VWM task. Brain imaging results revealed localized activation in the frontal cortex, replicating findings from a Midwestern US sample. Critically, children from families with low maternal education and income showed weaker brain activity and poorer distractor suppression in canonical working memory areas in the left frontal cortex. Implications of this work are far-reaching: it is now cost-effective to localize functional brain networks in early development in low-resource settings, paving the way for novel intervention and assessment methods.
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Affiliation(s)
| | - Aarti Kumar
- Community Empowerment LabUttar PradeshLucknowIndia
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Jackson ES, Wijeakumar S, Beal DS, Brown B, Zebrowski P, Spencer JP. A fNIRS Investigation of Speech Planning and Execution in Adults Who Stutter. Neuroscience 2019; 406:73-85. [DOI: 10.1016/j.neuroscience.2019.02.032] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 02/25/2019] [Accepted: 02/26/2019] [Indexed: 01/05/2023]
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Chevalier N, Jackson J, Revueltas Roux A, Moriguchi Y, Auyeung B. Differentiation in prefrontal cortex recruitment during childhood: Evidence from cognitive control demands and social contexts. Dev Cogn Neurosci 2019; 36:100629. [PMID: 30913498 PMCID: PMC6969260 DOI: 10.1016/j.dcn.2019.100629] [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: 09/06/2018] [Revised: 02/26/2019] [Accepted: 02/26/2019] [Indexed: 12/11/2022] Open
Abstract
Using fNIRS, we examined how children recruit PFC while engaging cognitive control. Activation increased with cognitive control demands more in left than right PFC. It was higher in left PFC in competitive than cooperative contexts, and in right PFC in cooperative and neutral compared to competitive contexts. Older children showed greater variations in PFC activation than younger children. Cognitive control is supported by more differentiated PFC recruitment with age.
Emerging cognitive control during childhood is largely supported by the development of distributed neural networks in which the prefrontal cortex (PFC) is central. The present study used fNIRS to examine how PFC is recruited to support cognitive control in 5–6 and 8-9-year-old children, by (a) progressively increasing cognitive control demands within the same task, and (b) manipulating the social context in which the task was performed (neutral, cooperative, or competitive), a factor that has been shown to influence cognitive control. Activation increased more in left than right PFC with cognitive control demands, a pattern which was more pronounced in older than younger children. In addition, activation was higher in left PFC in competitive than cooperative contexts, and higher in right PFC in cooperative and neutral than competitive contexts. These findings suggest that increasingly efficient cognitive control during childhood is supported by more differentiated recruitment of PFC as a function of cognitive control demands with age.
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Affiliation(s)
- Nicolas Chevalier
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
| | - Judith Jackson
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Alexia Revueltas Roux
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Yusuke Moriguchi
- Graduate School of Education, Kyoto University, Yoshidahoncho, Kyoto, 606-8501, Japan
| | - Bonnie Auyeung
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
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Zhang F, Roeyers H. Exploring brain functions in autism spectrum disorder: A systematic review on functional near-infrared spectroscopy (fNIRS) studies. Int J Psychophysiol 2019; 137:41-53. [DOI: 10.1016/j.ijpsycho.2019.01.003] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2018] [Revised: 01/11/2019] [Accepted: 01/11/2019] [Indexed: 10/27/2022]
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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: 16] [Impact Index Per Article: 2.7] [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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Xiao X, Yu X, Zhang Z, Zhao Y, Jiang Y, Li Z, Yang Y, Zhu C. Transcranial brain atlas. SCIENCE ADVANCES 2018; 4:eaar6904. [PMID: 30191174 PMCID: PMC6124906 DOI: 10.1126/sciadv.aar6904] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/17/2017] [Accepted: 07/26/2018] [Indexed: 05/15/2023]
Abstract
We introduce here the concept of a transcranial brain atlas (TBA), a new kind of brain atlas specialized for transcranial techniques. A TBA is a probabilistic mapping from scalp space to atlas label space, relating scalp locations to anatomical, functional, network, genetic, or other labels. TBAs offer a new way to integrate and present structural and functional organization of the brain and allow previously subsurface and invisible atlas labels visible on the scalp surface to accurately guide the placement of transcranial devices directly on the scalp surface in a straightforward, visual manner. We present here a framework for building TBAs that includes (i) a new, continuous proportional coordinate system devised for the scalp surface to allow standardized specification of scalp positions; (ii) a high-resolution, large sample-based (114-participant) mapping from scalp space to brain space to accurately and reliably describe human cranio-cortical correspondence; and (iii) a two-step Markov chain to combine the probabilistic scalp-brain mapping with a traditional brain atlas, bringing atlas labels to the scalp surface. We assessed the reproducibility (consistency of TBAs generated from different groups) and predictiveness (prediction accuracy of labels for individuals without brain images) of the TBAs built via our framework. Moreover, we present an application of TBAs to a functional near-infrared spectroscopy finger-tapping experiment, illustrating the utility and benefits of TBAs in transcranial studies. Our results demonstrate that TBAs can support ongoing efforts to map the human brain using transcranial techniques, just as traditional brain atlases have supported magnetic resonance imaging and positron emission tomography studies.
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Affiliation(s)
- Xiang Xiao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Xiaoting Yu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zong Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yang Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yihan Jiang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Zheng Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD 21224, USA
| | - Chaozhe Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
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Machado A, Cai Z, Pellegrino G, Marcotte O, Vincent T, Lina JM, Kobayashi E, Grova C. Optimal positioning of optodes on the scalp for personalized functional near-infrared spectroscopy investigations. J Neurosci Methods 2018; 309:91-108. [PMID: 30107210 DOI: 10.1016/j.jneumeth.2018.08.006] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 08/07/2018] [Accepted: 08/08/2018] [Indexed: 12/21/2022]
Abstract
BACKGROUND Application of functional Near InfraRed Spectroscopy (fNIRS) in neurology is still limited as a good optical coupling and optimized optode coverage of specific brain regions remains challenging, notably for prolonged monitoring. METHODS We propose to evaluate a new procedure allowing accurate investigation of specific brain regions. The procedure consists in: (i) A priori maximization of spatial sensitivity of fNIRS measurements targeting specific brain regions, while reducing the number of applied optodes in order to decrease installation time and improve subject comfort. (ii) Utilization of a 3D neuronavigation device and usage of collodion to glue optodes on the scalp, ensuring good optical contact for prolonged investigations. (iii) Local reconstruction of the hemodynamic activity along the cortical surface using inverse modelling. RESULTS Using realistic simulations, we demonstrated that maps derived from optimal montage acquisitions showed, after reconstruction, spatial resolution only slightly lower to that of ultra high density montages while significantly reducing the number of optodes. The optimal montages provided overall good quantitative accuracy especially at the peak of the spatially reconstructed map. We also evaluated real motor responses in two healthy subjects and obtained reproducible motor responses over different sessions. COMPARISON WITH EXISTING METHODS We are among the first to propose a mathematical optimization strategy, allowing high sensitivity measurements. CONCLUSIONS Our results support that using personalized optimal montages should allow to conduct accurate fNIRS studies in clinical settings and realistic lifestyle conditions.
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Affiliation(s)
- A Machado
- Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Canada.
| | - Z Cai
- Physics Department and PERFORM center, Concordia University, Montreal, Canada
| | - G Pellegrino
- Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Canada; IRCCS Fondazione Ospedale San Camillo Via Alberoni, Venice, Italy
| | - O Marcotte
- GERAD, École des HEC, Montréal, Canada; Département d'informatique, Université du Québec à Montréal, Canada; Centre de Recherches Mathématiques, Université de Montréal, Québec, Canada
| | - T Vincent
- Physics Department and PERFORM center, Concordia University, Montreal, Canada
| | - J-M Lina
- École de technologie supérieure de l'Université du Québec, Canada; Centre de Recherches Mathématiques, Université de Montréal, Québec, Canada
| | - E Kobayashi
- Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Canada
| | - C Grova
- Multimodal Functional Imaging Laboratory, Biomedical Engineering Department, McGill University, Canada; Physics Department and PERFORM center, Concordia University, Montreal, Canada; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Canada; Centre de Recherches Mathématiques, Université de Montréal, Québec, Canada
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Brigadoi S, Salvagnin D, Fischetti M, Cooper RJ. Array Designer: automated optimized array design for functional near-infrared spectroscopy. NEUROPHOTONICS 2018; 5:035010. [PMID: 30238021 PMCID: PMC6135986 DOI: 10.1117/1.nph.5.3.035010] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2018] [Accepted: 08/06/2018] [Indexed: 05/08/2023]
Abstract
The position of each source and detector "optode" on the scalp, and their relative separations, determines the sensitivity of each functional near-infrared spectroscopy (fNIRS) channel to the underlying cortex. As a result, selecting appropriate scalp locations for the available sources and detectors is critical to every fNIRS experiment. At present, it is standard practice for the user to undertake this task manually; to select what they believe are the best locations on the scalp to place their optodes so as to sample a given cortical region-of-interest (ROI). This process is difficult, time-consuming, and highly subjective. Here, we propose a tool, Array Designer, that is able to automatically design optimized fNIRS arrays given a user-defined ROI and certain features of the available fNIRS device. Critically, the Array Designer methodology is generalizable and will be applicable to almost any subject population or fNIRS device. We describe and validate the algorithmic methodology that underpins Array Designer by running multiple simulations of array design problems in a realistic anatomical model. We believe that Array Designer has the potential to end the need for manual array design, and in doing so save researchers time, improve fNIRS data quality, and promote standardization across the field.
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Affiliation(s)
- Sabrina Brigadoi
- University College London, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
- University of Padova, Department of Developmental Psychology, Padova, Italy
| | - Domenico Salvagnin
- University of Padova, Department of Information Engineering, Padova, Italy
| | - Matteo Fischetti
- University of Padova, Department of Information Engineering, Padova, Italy
| | - Robert J. Cooper
- University College London, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
- NeoLAB, Rosie Hospital, The Evelyn Perinatal Imaging Centre, Cambridge, United Kingdom
- Address all correspondence to: Robert J. Cooper, E-mail:
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Delgado Reyes LM, Bohache K, Wijeakumar S, Spencer JP. Evaluating motion processing algorithms for use with functional near-infrared spectroscopy data from young children. NEUROPHOTONICS 2018; 5:025008. [PMID: 29845087 PMCID: PMC5963607 DOI: 10.1117/1.nph.5.2.025008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 04/30/2018] [Indexed: 05/20/2023]
Abstract
Motion artifacts are often a significant component of the measured signal in functional near-infrared spectroscopy (fNIRS) experiments. A variety of methods have been proposed to address this issue, including principal components analysis (PCA), correlation-based signal improvement (CBSI), wavelet filtering, and spline interpolation. The efficacy of these techniques has been compared using simulated data; however, our understanding of how these techniques fare when dealing with task-based cognitive data is limited. Brigadoi et al. compared motion correction techniques in a sample of adult data measured during a simple cognitive task. Wavelet filtering showed the most promise as an optimal technique for motion correction. Given that fNIRS is often used with infants and young children, it is critical to evaluate the effectiveness of motion correction techniques directly with data from these age groups. This study addresses that problem by evaluating motion correction algorithms implemented in HomER2. The efficacy of each technique was compared quantitatively using objective metrics related to the physiological properties of the hemodynamic response. Results showed that targeted PCA (tPCA), spline, and CBSI retained a higher number of trials. These techniques also performed well in direct head-to-head comparisons with the other approaches using quantitative metrics. The CBSI method corrected many of the artifacts present in our data; however, this approach produced sometimes unstable HRFs. The targeted PCA and spline methods proved to be the most robust, performing well across all comparison metrics. When compared head to head, tPCA consistently outperformed spline. We conclude, therefore, that tPCA is an effective technique for correcting motion artifacts in fNIRS data from young children.
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Affiliation(s)
| | | | | | - John P. Spencer
- University of East Anglia, School of Psychology, Norwich, United Kingdom
- Address all correspondence to: John P. Spencer, E-mail:
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Zimeo Morais GA, Balardin JB, Sato JR. fNIRS Optodes' Location Decider (fOLD): a toolbox for probe arrangement guided by brain regions-of-interest. Sci Rep 2018; 8:3341. [PMID: 29463928 PMCID: PMC5820343 DOI: 10.1038/s41598-018-21716-z] [Citation(s) in RCA: 131] [Impact Index Per Article: 21.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Accepted: 01/08/2018] [Indexed: 12/13/2022] Open
Abstract
The employment of functional near-infrared spectroscopy (fNIRS) as a method of brain imaging has increased over the last few years due to its portability, low-cost and robustness to subject movement. Experiments with fNIRS are designed in the face of a limited number of sources and detectors (optodes) to be positioned on selected portion(s) of the scalp. The optodes locations represent an expectation of assessing cortical regions relevant to the experiment’s hypothesis. However, this translation process remains a challenge for fNIRS experimental design. In the present study, we propose an approach that automatically decides the location of fNIRS optodes from a set of predefined positions with the aim of maximizing the anatomical specificity to brain regions-of-interest. The implemented method is based on photon transport simulations on two head atlases. The results are compiled into the publicly available “fNIRS Optodes’ Location Decider” (fOLD). This toolbox is a first-order approach to bring the achieved advancements of parcellation methods and meta-analyses from functional magnetic resonance imaging to more precisely guide the selection of optode positions for fNIRS experiments.
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Affiliation(s)
| | - Joana Bisol Balardin
- Instituto do Cérebro, Hospital Israelita Albert Einstein, 05652-900, São Paulo, Brazil
| | - João Ricardo Sato
- Center for Mathematics Computing and Cognition, Universidade Federal do ABC, 09210-180, São Bernardo do Campo, Brazil
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Zhao H, Cooper RJ. Review of recent progress toward a fiberless, whole-scalp diffuse optical tomography system. NEUROPHOTONICS 2018; 5:011012. [PMID: 28983490 PMCID: PMC5613216 DOI: 10.1117/1.nph.5.1.011012] [Citation(s) in RCA: 55] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 08/28/2017] [Indexed: 05/23/2023]
Abstract
The development of a whole-scalp, high sampling-density diffuse optical tomography (DOT) system is a critical next step in the evolution of the field of diffuse optics. To achieve this with optical fiber bundles is extremely challenging, simply because of the sheer number of bundles required, and the associated challenges of weight and ergonomics. Dispensing with optical fiber bundles and moving to head-mounted optoelectronics can potentially facilitate the advent of a new generation of wearable, whole-scalp technologies that will open up a range of new experimental and clinical applications for diffuse optical measurements. Here, we present a concise review of the significant progress that has been made toward achieving a wearable, fiberless, high-density, whole-scalp DOT system. We identify the key limitations of current technologies and discuss the possible opportunities for future development.
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Affiliation(s)
- Hubin Zhao
- University College London, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Robert J. Cooper
- University College London, Biomedical Optics Research Laboratory, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
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35
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Modulating perceptual complexity and load reveals degradation of the visual working memory network in ageing. Neuroimage 2017. [DOI: 10.1016/j.neuroimage.2017.06.019] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
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Wijeakumar S, Huppert TJ, Magnotta VA, Buss AT, Spencer JP. Validating an image-based fNIRS approach with fMRI and a working memory task. Neuroimage 2017; 147:204-218. [DOI: 10.1016/j.neuroimage.2016.12.007] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2015] [Revised: 11/15/2016] [Accepted: 12/03/2016] [Indexed: 10/20/2022] Open
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Ambrose JP, Wijeakumar S, Buss AT, Spencer JP. Feature-Based Change Detection Reveals Inconsistent Individual Differences in Visual Working Memory Capacity. Front Syst Neurosci 2016; 10:33. [PMID: 27147986 PMCID: PMC4835449 DOI: 10.3389/fnsys.2016.00033] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2015] [Accepted: 03/29/2016] [Indexed: 11/17/2022] Open
Abstract
Visual working memory (VWM) is a key cognitive system that enables people to hold visual information in mind after a stimulus has been removed and compare past and present to detect changes that have occurred. VWM is severely capacity limited to around 3–4 items, although there are robust individual differences in this limit. Importantly, these individual differences are evident in neural measures of VWM capacity. Here, we capitalized on recent work showing that capacity is lower for more complex stimulus dimension. In particular, we asked whether individual differences in capacity remain consistent if capacity is shifted by a more demanding task, and, further, whether the correspondence between behavioral and neural measures holds across a shift in VWM capacity. Participants completed a change detection (CD) task with simple colors and complex shapes in an fMRI experiment. As expected, capacity was significantly lower for the shape dimension. Moreover, there were robust individual differences in behavioral estimates of VWM capacity across dimensions. Similarly, participants with a stronger BOLD response for color also showed a strong neural response for shape within the lateral occipital cortex, intraparietal sulcus (IPS), and superior IPS. Although there were robust individual differences in the behavioral and neural measures, we found little evidence of systematic brain-behavior correlations across feature dimensions. This suggests that behavioral and neural measures of capacity provide different views onto the processes that underlie VWM and CD. Recent theoretical approaches that attempt to bridge between behavioral and neural measures are well positioned to address these findings in future work.
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Affiliation(s)
- Joseph P Ambrose
- Department of Applied Mathematics and Computational Sciences, University of Iowa, Iowa City IA, USA
| | | | - Aaron T Buss
- Department of Psychology, University of Tennessee, Knoxville TN, USA
| | - John P Spencer
- School of Psychology, University of East Anglia Norwich, UK
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Nishiyori R. fNIRS: An Emergent Method to Document Functional Cortical Activity during Infant Movements. Front Psychol 2016; 7:533. [PMID: 27148141 PMCID: PMC4837143 DOI: 10.3389/fpsyg.2016.00533] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2015] [Accepted: 03/30/2016] [Indexed: 02/02/2023] Open
Abstract
The neural basis underlying the emergence of goal-directed actions in infants has been severely understudied, with minimal empirical evidence for hypotheses proposed. This was largely due to the technological constraints of traditional neuroimaging techniques. Recently, functional near-infrared spectroscopy (fNIRS) technology has emerged as a tool developmental scientists are finding useful to examine cortical activity, particularly in young children and infants due to its greater tolerance to movements than other neuroimaging techniques. fNIRS provides an opportunity to finally begin to examine the neural underpinnings as infants develop goal-directed actions. In this methodological paper, I will outline the utility, challenges, and outcomes of using fNIRS to measure the changes in cortical activity as infants reach for an object. I will describe the advantages and limitations of the technology, the setup I used to study primary motor cortex activity during infant reaching, and example steps in the analyses processes. I will present exemplar data to illustrate the feasibility of this technique to quantify changes in hemodynamic activity as infants move. The viability of this research method opens the door to expanding studies of the development of neural activity related to goal-directed actions in infants. I encourage others to share details of techniques used, as well, including analyticals, to help this neuroimaging technology grow as others, such as EEG and fMRI have.
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Affiliation(s)
- Ryota Nishiyori
- Developmental Neuromotor Control Lab, School of Kinesiology, University of MichiganAnn Arbor, MI, USA
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