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Zhou X, Planalp EM, Heinrich L, Pletcher C, DiPiero M, Alexander AL, Litovsky RY, Dean DC. Inhibitory Control in Children 4-10 Years of Age: Evidence From Functional Near-Infrared Spectroscopy Task-Based Observations. Front Hum Neurosci 2022; 15:798358. [PMID: 35046786 PMCID: PMC8762317 DOI: 10.3389/fnhum.2021.798358] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 12/13/2021] [Indexed: 12/22/2022] Open
Abstract
Executive function (EF) is essential to child development, with associated skills beginning to emerge in the first few years of life and continuing to develop into adolescence and adulthood. The prefrontal cortex (PFC), which follows a neurodevelopmental timeline similar to EF, plays an important role in the development of EF. However, limited research has examined prefrontal function in young children due to limitations of currently available neuroimaging techniques such as functional resonance magnetic imaging (fMRI). The current study developed and applied a multimodal Go/NoGo task to examine the EF component of inhibitory control in children 4-10 years of age. Cortical activity was measured using a non-invasive and child-friendly neuroimaging technique - functional near-infrared spectroscopy (fNIRS). Children's response accuracy and reaction times were captured during the fNIRS session and compared with responses obtained using the standardized assessments from NIH Toolbox cognition battery. Results showed significant correlations between the behavioral measures during the fNIRS session and the standardized EF assessments, in line with our expectations. Results from fNIRS measures demonstrated a significant, age-independent effect of inhibitory control (IC) in the right PFC (rPFC), and an age-dependent effect in the left orbitofrontal cortex (lOFC), consistent with results in previous studies using fNIRS and fMRI. Thus, the new task designed for fNIRS was suitable for examining IC in young children, and results showed that fNIRS measures can reveal prefrontal IC function.
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Affiliation(s)
- Xin Zhou
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
| | | | - Lauren Heinrich
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
| | - Colleen Pletcher
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
| | - Marissa DiPiero
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Neuroscience Training Program, University of Wisconsin–Madison, Madison, WI, United States
| | - Andrew L. Alexander
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin–Madison, Madison, WI, United States
| | - Ruth Y. Litovsky
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Medical Physics, University of Wisconsin–Madison, Madison, WI, United States
- Division of Otolaryngology, Department of Surgery, University of Wisconsin–Madison, Madison, WI, United States
| | - Douglas C. Dean
- Waisman Center, University of Wisconsin–Madison, Madison, WI, United States
- Department of Communication Sciences and Disorders, University of Wisconsin–Madison, Madison, WI, United States
- Division of Neonatology & Newborn Nursery, Department of Pediatrics, University of Wisconsin–Madison, Madison, WI, United States
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Yeung MK. An optical window into brain function in children and adolescents: A systematic review of functional near-infrared spectroscopy studies. Neuroimage 2020; 227:117672. [PMID: 33359349 DOI: 10.1016/j.neuroimage.2020.117672] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 12/12/2020] [Accepted: 12/12/2020] [Indexed: 12/14/2022] Open
Abstract
Despite decades of research, our understanding of functional brain development throughout childhood and adolescence remains limited due to the challenges posed by certain neuroimaging modalities. Recently, there has been a growing interest in using functional near-infrared spectroscopy (fNIRS) to elucidate the neural basis of cognitive and socioemotional development and identify the factors shaping these types of development. This article, focusing on the fNIRS methods, presents an up-to-date systematic review of fNIRS studies addressing the effects of age and other factors on brain functions in children and adolescents. Literature searches were conducted using PubMed and PsycINFO. A total of 79 fNIRS studies involving healthy individuals aged 3-17 years that were published in peer-reviewed journals in English before July 2020 were included. Six methodological aspects of these studies were evaluated, including the research design, experimental paradigm, fNIRS measurement, data preprocessing, statistical analysis, and result presentation. The risk of bias, such as selective outcome reporting, was assessed throughout the review. A qualitative synthesis of study findings in terms of the factor effects on changes in oxyhemoglobin concentration was also performed. This unregistered review highlights the strengths and limitations of the existing literature and suggests directions for future research to facilitate the improved use of fNIRS in developmental cognitive neuroscience research.
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Affiliation(s)
- Michael K Yeung
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Canada; Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hong Kong, China.
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Condy EE, Friedman BH, Gandjbakhche A. Probing Neurovisceral Integration via Functional Near-Infrared Spectroscopy and Heart Rate Variability. Front Neurosci 2020; 14:575589. [PMID: 33324146 PMCID: PMC7723853 DOI: 10.3389/fnins.2020.575589] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 10/19/2020] [Indexed: 11/17/2022] Open
Abstract
The neurovisceral integration model (NVM) proposes that an organism’s ability to flexibly adapt to its environment is related to biological flexibility within the central autonomic network (CAN). One important aspect of this flexibility is behavioral inhibition (Thayer and Friedman, 2002). During a behavioral inhibition task, the CAN, which comprises a series of feedback loops, must be able to integrate information and react to these inputs flexibly to facilitate optimal performance. The functioning of the CAN is shown to be associated with respiratory sinus arrhythmia (RSA), as the vagus nerve is part of this feedback system. Although the NVM has been examined through neural imaging and RSA, only a few studies have examined these measures simultaneously during the neuroimaging procedure. Furthermore, these studies were done at rest or used tasks that were not targeted at processes associated with the NVM, such as behavioral inhibition and cognitive flexibility. For this reason, the present study assessed RSA and neural activation in the pre-frontal cortex simultaneously while participants completed a behavior inhibition task. RSA and functional near-infrared spectroscopy were collected in 38 adults, and resting levels of pre-frontal activation were negatively related to RSA, but pre-frontal activation during the behavior inhibition task was not. The negative relationship between RSA and oxygenated hemoglobin is consistent with previous functional magnetic resonance imaging work examining the NVM at baseline and should be further studied. Additional research investigating how this relationship may change based on task demands or environmental contexts would help clarify the applicability of the model.
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Affiliation(s)
- Emma E Condy
- National Institute of Child Health and Human Development, Bethesda, MD, United States
| | - Bruce H Friedman
- Department of Psychology, Virginia Tech, Blacksburg, VA, United States
| | - Amir Gandjbakhche
- National Institute of Child Health and Human Development, Bethesda, MD, United States
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Anderson AA, Gropman A, Le Mons C, Stratakis CA, Gandjbakhche AH. Hemodynamics of Prefrontal Cortex in Ornithine Transcarbamylase Deficiency: A Twin Case Study. Front Neurol 2020; 11:809. [PMID: 32922350 PMCID: PMC7456944 DOI: 10.3389/fneur.2020.00809] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 06/29/2020] [Indexed: 11/30/2022] Open
Abstract
Ornithine transcarbamylase deficiency (OTCD) is the most common form of urea cycle disorder characterized by the presence of hyperammonemia (HA). In patients with OTCD, HA is known to cause impairments in domains of executive function and working memory. Monitoring OTCD progression and investigating neurocognitive biomarkers can, therefore, become critical in understanding the underlying brain function in a population with OTCD. We used functional near infrared spectroscopy (fNIRS) to examine the hemodynamics of prefrontal cortex (PFC) in a fraternal twin with and without OTCD. fNIRS is a non-invasive and wearable optical technology that can be used to assess cortical hemodynamics in a realistic clinical setting. We quantified the hemodynamic variations in total-hemoglobin as assessed by fNIRS while subjects performed the N-back working memory (WM) task. Our preliminary results showed that the sibling with OTCD had higher variation in a very low frequency band (<0.03 Hz, related to mechanism of cerebral autoregulation) compared to the control sibling. The difference between these variations was not as prominent in the higher frequency band, indicating the possible role of impaired autoregulation and cognitive function due to presence of HA. We further examined the functional connectivity in PFC, where the OTCD sibling showed lower interhemispheric functional connectivity as the task load increased. Our pilot results are the first to show the utility of fNIRS in monitoring OTCD cortical hemodynamics, indicating the possibility of inefficient neurocognitive function. This study provides a novel insight into the monitoring of OTCD focusing on the contribution of physiological process and neurocognitive function in this population.
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Affiliation(s)
- Afrouz A. Anderson
- National Institutes of Health (NIH), National Institute of Child Health and Human Development, Bethesda, MD, United States
| | - Andrea Gropman
- Children's National Medical Center, Division of Neurogenetics and Neurodevelopmental Pediatrics, Washington, DC, United States
| | - Cynthia Le Mons
- National Urea Cycle Disorders Foundation, Pasadena, CA, United States
| | - Constantine A. Stratakis
- National Institutes of Health (NIH), National Institute of Child Health and Human Development, Bethesda, MD, United States
| | - Amir H. Gandjbakhche
- National Institutes of Health (NIH), National Institute of Child Health and Human Development, Bethesda, MD, United States
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Anderson AA, Smith E, Chowdhry FA, Thurm A, Condy E, Swineford L, Manwaring SS, Amyot F, Matthews D, Gandjbakhche AH. Prefrontal Hemodynamics in Toddlers at Rest: A Pilot Study of Developmental Variability. Front Neurosci 2017; 11:300. [PMID: 28611578 PMCID: PMC5447733 DOI: 10.3389/fnins.2017.00300] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 05/15/2017] [Indexed: 01/24/2023] Open
Abstract
Functional near infrared spectroscopy (fNIRS) is a non-invasive functional neuroimaging modality. Although, it is amenable to use in infants and young children, there is a lack of fNIRS research within the toddler age range. In this study, we used fNIRS to measure cerebral hemodynamics in the prefrontal cortex (PFC) in 18-36 months old toddlers (n = 29) as part of a longitudinal study that enrolled typically-developing toddlers as well as those "at risk" for language and other delays based on presence of early language delays. In these toddlers, we explored two hemodynamic response indices during periods of rest during which time audiovisual children's programming was presented. First, we investigate Lateralization Index, based on differences in oxy-hemoglobin saturation from left and right prefrontal cortex. Then, we measure oxygenation variability (OV) index, based on variability in oxygen saturation at frequencies attributed to cerebral autoregulation. Preliminary findings show that lower cognitive (including language) abilities are associated with fNIRS measures of both lower OV index and more extreme Lateralization index values. These preliminary findings show the feasibility of using fNIRS in toddlers, including those at risk for developmental delay, and lay the groundwork for future studies.
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Affiliation(s)
- Afrouz A Anderson
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of HealthBethesda, MD, United States
| | - Elizabeth Smith
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of HealthBethesda, MD, United States
| | - Fatima A Chowdhry
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of HealthBethesda, MD, United States
| | - Audrey Thurm
- National Institute of Mental Health, National Institutes of HealthBethesda, MD, United States
| | - Emma Condy
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of HealthBethesda, MD, United States
| | - Lauren Swineford
- Department of Speech and Hearing Sciences, Elson S. Floyd College of Medicine, Washington State UniversitySpokane, WA, United States
| | - Stacy S Manwaring
- Communication Science and Disorders, University of UtahSalt Lake City, UT, United States
| | - Franck Amyot
- Center for Neuroscience and Regenerative MedicineRockville, MD, United States.,Department of Neurology, Uniformed Services University of the Health ScienceBethesda, MD, United States
| | - Dennis Matthews
- Department of Neurological Surgery, School of Medicine, University of California, DavisDavis, CA, United States
| | - Amir H Gandjbakhche
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of HealthBethesda, MD, United States
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Karamzadeh N, Amyot F, Kenney K, Anderson A, Chowdhry F, Dashtestani H, Wassermann EM, Chernomordik V, Boccara C, Wegman E, Diaz-Arrastia R, Gandjbakhche AH. A machine learning approach to identify functional biomarkers in human prefrontal cortex for individuals with traumatic brain injury using functional near-infrared spectroscopy. Brain Behav 2016; 6:e00541. [PMID: 27843695 PMCID: PMC5102640 DOI: 10.1002/brb3.541] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2016] [Revised: 05/12/2016] [Accepted: 06/23/2016] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND We have explored the potential prefrontal hemodynamic biomarkers to characterize subjects with Traumatic Brain Injury (TBI) by employing the multivariate machine learning approach and introducing a novel task-related hemodynamic response detection followed by a heuristic search for optimum set of hemodynamic features. To achieve this goal, the hemodynamic response from a group of 31 healthy controls and 30 chronic TBI subjects were recorded as they performed a complexity task. METHODS To determine the optimum hemodynamic features, we considered 11 features and their combinations in characterizing TBI subjects. We investigated the significance of the features by utilizing a machine learning classification algorithm to score all the possible combinations of features according to their predictive power. RESULTS AND CONCLUSIONS The identified optimum feature elements resulted in classification accuracy, sensitivity, and specificity of 85%, 85%, and 84%, respectively. Classification improvement was achieved for TBI subject classification through feature combination. It signified the major advantage of the multivariate analysis over the commonly used univariate analysis suggesting that the features that are individually irrelevant in characterizing the data may become relevant when used in combination. We also conducted a spatio-temporal classification to identify regions within the prefrontal cortex (PFC) that contribute in distinguishing between TBI and healthy subjects. As expected, Brodmann areas (BA) 10 within the PFC were isolated as the region that healthy subjects (unlike subjects with TBI), showed major hemodynamic activity in response to the High Complexity task. Overall, our results indicate that identified temporal and spatio-temporal features from PFC's hemodynamic activity are promising biomarkers in classifying subjects with TBI.
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Affiliation(s)
- Nader Karamzadeh
- Department of Computational and Data Sciences George Mason University Fairfax VA USA; National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA
| | - Franck Amyot
- Department of Neurology Center for Neuroscience and Regenerative Medicine Uniformed Services Bethesda MD USA
| | - Kimbra Kenney
- Department of Neurology Center for Neuroscience and Regenerative Medicine Uniformed Services Bethesda MD USA
| | - Afrouz Anderson
- National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA
| | - Fatima Chowdhry
- National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA
| | - Hadis Dashtestani
- National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA
| | - Eric M Wassermann
- National Institute of Mental Health National Institutes of Healthy Bethesda MD USA
| | - Victor Chernomordik
- National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA
| | | | - Edward Wegman
- Department of Computational and Data Sciences George Mason University Fairfax VA USA
| | - Ramon Diaz-Arrastia
- Department of Neurology Center for Neuroscience and Regenerative Medicine Uniformed Services Bethesda MD USA
| | - Amir H Gandjbakhche
- National Institute of Child Health and Human Development National Institutes of Health Bethesda MD USA
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Chernomordik V, Amyot F, Kenney K, Wassermann E, Diaz-Arrastia R, Gandjbakhche A. Abnormality of low frequency cerebral hemodynamics oscillations in TBI population. Brain Res 2016; 1639:194-9. [PMID: 26996413 PMCID: PMC9392959 DOI: 10.1016/j.brainres.2016.02.018] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2015] [Revised: 01/29/2016] [Accepted: 02/08/2016] [Indexed: 10/25/2022]
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