The minimum resting-state fNIRS imaging duration for accurate and stable mapping of brain connectivity network in children

Resting-state functional near-infrared spectroscopy (fNIRS) is a potential technique for the study of brain functional connectivity (FC) and networks in children. However, the necessary fNIRS scanning duration required to map accurate and stable functional brain connectivity and graph theory metrics in the resting-state brain activity remains largely unknown. Here, we acquired resting-state fNIRS imaging data from 53 healthy children to provide the first empirical evidence for the minimum imaging time required to obtain accurate and stable FC and graph theory metrics of brain network activity (e.g., nodal efficiency and network global and local efficiency). Our results showed that FC was accurately and stably achieved after 7.0-min fNIRS imaging duration, whereas the necessary scanning time for accurate and stable network measures was a minimum of 2.5 min at low network thresholds. These quantitative results provide direct evidence for the choice of the resting-state fNIRS imaging time in children in brain FC and network topology study. The current study also demonstrates that these methods are feasible and cost-effective in the application of time-constrained infants and critically ill children.

[1]  Yong He,et al.  Identifying and Mapping Connectivity Patterns of Brain Network Hubs in Alzheimer's Disease. , 2015, Cerebral cortex.

[2]  Alan C. Evans,et al.  Topological Organization of Functional Brain Networks in Healthy Children: Differences in Relation to Age, Sex, and Intelligence , 2013, PloS one.

[3]  Tianwei Yu,et al.  K-Profiles: A Nonlinear Clustering Method for Pattern Detection in High Dimensional Data , 2015, BioMed research international.

[4]  Abraham Z. Snyder,et al.  Resting-state functional connectivity in the human brain revealed with diffuse optical tomography , 2009, NeuroImage.

[5]  Ross E. Vanderwert,et al.  The use of near-infrared spectroscopy in the study of typical and atypical development , 2014, NeuroImage.

[6]  Kaustubh Supekar,et al.  Development of Large-Scale Functional Brain Networks in Children , 2009, NeuroImage.

[7]  Nora D. Volkow,et al.  Temporal Evolution of Brain Functional Connectivity Metrics: Could 7 Min of Rest be Enough? , 2016, Cerebral cortex.

[8]  PHILIPPE J. GIABBANELLI.  The Small-World Property in Networks Growing by Active Edges , 2011, Adv. Complex Syst..

[9]  R. Kahn,et al.  Efficiency of Functional Brain Networks and Intellectual Performance , 2009, The Journal of Neuroscience.

[10]  Alan C. Evans,et al.  Small-world anatomical networks in the human brain revealed by cortical thickness from MRI. , 2007, Cerebral cortex.

[11]  Jinrui Zhang,et al.  FC-NIRS: A Functional Connectivity Analysis Tool for Near-Infrared Spectroscopy Data , 2015, BioMed research international.

[12]  E. Bullmore,et al.  Behavioral / Systems / Cognitive Functional Connectivity and Brain Networks in Schizophrenia , 2010 .

[13]  G. Taga,et al.  Development of Global Cortical Networks in Early Infancy , 2010, The Journal of Neuroscience.

[14]  Alan C. Evans,et al.  Structural Insights into Aberrant Topological Patterns of Large-Scale Cortical Networks in Alzheimer's Disease , 2008, The Journal of Neuroscience.

[15]  F. Jöbsis.  Noninvasive, infrared monitoring of cerebral and myocardial oxygen sufficiency and circulatory parameters. , 1977, Science.

[16]  Dongchuan Yu,et al.  Weak network efficiency in young children with Autism Spectrum Disorder: Evidence from a functional near-infrared spectroscopy study , 2016, Brain and Cognition.

[17]  Liang Wang,et al.  Altered small‐world brain functional networks in children with attention‐deficit/hyperactivity disorder , 2009, Human brain mapping.

[18]  J. Maldjian,et al.  Effect of resting-state functional MR imaging duration on stability of graph theory metrics of brain network connectivity. , 2011, Radiology.

[19]  D. Delpy,et al.  System for long-term measurement of cerebral blood and tissue oxygenation on newborn infants by near infra-red transillumination , 1988, Medical and Biological Engineering and Computing.

[20]  A. Villringer,et al.  Non-invasive optical spectroscopy and imaging of human brain function , 1997, Trends in Neurosciences.

[21]  Jesse A. Brown,et al.  Altered functional and structural brain network organization in autism☆ , 2012, NeuroImage: Clinical.

[22]  Yong He,et al.  Revealing Topological Organization of Human Brain Functional Networks with Resting-State Functional near Infrared Spectroscopy , 2012, PloS one.

[23]  Catie Chang,et al.  Time–frequency dynamics of resting-state brain connectivity measured with fMRI , 2010, NeuroImage.

[24]  Yong He,et al.  Convergence and divergence across construction methods for human brain white matter networks: An assessment based on individual differences , 2015, Human brain mapping.

[25]  Norihiro Sadato,et al.  A NIRS–fMRI study of resting state network , 2012, NeuroImage.

[26]  E. Bullmore,et al.  A Resilient, Low-Frequency, Small-World Human Brain Functional Network with Highly Connected Association Cortical Hubs , 2006, The Journal of Neuroscience.

[27]  Massimo Marchiori,et al.  Economic small-world behavior in weighted networks , 2003 .

[28]  R. Aslin,et al.  Developmental Cognitive Neuroscience Near-infrared Spectroscopy: a Report from the Mcdonnell Infant Methodology Consortium , 2022 .

[29]  Brian R. White,et al.  Bedside optical imaging of occipital resting-state functional connectivity in neonates , 2012, NeuroImage.

[30]  Yong He,et al.  Test-Retest Reliability of Graph Metrics in Functional Brain Networks: A Resting-State fNIRS Study , 2013, PloS one.

[31]  Robert M. Kantner,et al.  An EEG Study , 1981 .

[32]  Arjan Hillebrand,et al.  Different functional connectivity and network topology in behavioral variant of frontotemporal dementia and Alzheimer's disease: an EEG study , 2016, Neurobiology of Aging.

[33]  Yong He,et al.  Topological organization of the human brain functional connectome across the lifespan , 2013, Developmental Cognitive Neuroscience.

[34]  Olaf Sporns,et al.  Complex network measures of brain connectivity: Uses and interpretations , 2010, NeuroImage.

[35]  B. Biswal,et al.  Functional connectivity in the motor cortex of resting human brain using echo‐planar mri , 1995, Magnetic resonance in medicine.

[36]  B. Jacobs,et al.  Structure and function of the brain serotonin system. , 1992, Physiological reviews.

[37]  Theodore J. Huppert,et al.  Real-time imaging of human brain function by near-infrared spectroscopy using an adaptive general linear model , 2009, NeuroImage.

[38]  Hanli Liu,et al.  Dynamic functional connectivity revealed by resting-state functional near-infrared spectroscopy. , 2015, Biomedical optics express.

[39]  V Latora,et al.  Efficient behavior of small-world networks. , 2001, Physical review letters.

[40]  Tomer Fekete,et al.  Small-world network properties in prefrontal cortex correlate with predictors of psychopathology risk in young children: A NIRS study , 2014, NeuroImage.