scholarly journals Developmental Factors That Predict Head Movement During Resting-State fMRI in Preschool-Age Children

2021 ◽  
Author(s):  
Chelsea A. Johnson ◽  
Emily O. Garnett ◽  
Ho Ming Chow ◽  
Gregory J. Spray ◽  
David C. Zhu ◽  
...  
Keyword(s):  
Young Children ◽  
Resting State ◽  
Neurodevelopmental Disorders ◽  
Head Movement ◽  
Effortful Control ◽  
Near Infrared ◽  
Resting State Fmri ◽  
Preschool Age ◽  
Imaging Data ◽  
Functional Near Infrared Spectroscopy

Abstract Background: Early childhood marks a period of dynamic neurocognitive development. The preschool age coincides with the onset of many childhood disorders and is a developmental period that is frequently studied to determine markers of neurodevelopmental disorders. Magnetic resonance imaging (MRI) is often used to explore typical brain development and the neural bases of neurodevelopmental disorders. One advantage of MRI is that it provides comprehensive imaging data with high spatial resolution that is not possible with “child-friendly” techniques such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). However, acquiring high-quality MRI data in young children is challenging. The enclosed space and loud sounds can trigger unease and cause excessive head movement. A better understanding of potential factors that predict successful MRI acquisition would increase chances of collecting useable data in children with and without neurodevelopmental disorders.Methods: We investigated whether age, sex, stuttering status, and childhood temperament as measured using the Child Behavioral Questionnaire, could predict movement extent during resting-state functional MRI (rs-fMRI) in 76 children aged 3 to 7 years, including 42 children who stutter (CWS). Results: The CWS did not differ significantly from controls in temperament or head movement during scanning. Boys exhibited significantly more movement than girls, and younger age was a consistent predictor of increased movement, unless temperament was considered. Effortful control and negative affectivity significantly predicted movement especially in young boys. Conclusions: Considering temperament, age, and sex may help predict the success of acquiring useable rs-fMRI data in young children and inform future studies developing better desensitization techniques for pediatric MR neuroimaging.

scholarly journals A Paradigm for Measuring Resting State Functional Connectivity in Young Children Using fNIRS and Freeplay

2020 ◽  
Author(s):  
Jaeah Kim ◽  
Alexander Ruesch ◽  
Nin Rebecca Kang ◽  
Theodore J. Huppert ◽  
Jana Kainerstorfer ◽  
...  
Keyword(s):  
Functional Connectivity ◽  
Young Children ◽  
Resting State ◽  
Near Infrared ◽  
Functional Networks ◽  
Resting State Networks ◽  
New Paradigm ◽  
Resting State Functional Connectivity ◽  
Functional Near Infrared Spectroscopy ◽  
Test Retest Reliability

AbstractResting state functional connectivity (RSFC) reflects the organization of functional networks in the brain. Functional networks measured during “resting”, or task-absent, state are correlated with cognitive function, and much development of these networks occurs between infancy and adulthood. However, RSFC research in the intermediate years (especially between ages 3 and 5 years) has been limited, mainly due to a paucity of child-appropriate neural measures and behavioral paradigms. This paper presents a new paradigm to measure RSFC in young children, utilizing functional near-infrared spectroscopy (fNIRS) and Freeplay, a simple behavioral setup designed to approximate resting state in children. In Experiment 1, we recorded fNIRS data from children aged 3-8 years and adults aged 18-21 years and examined feasibility and validity of our measure of RSFC, and compared measures across the two groups. In Experiment 2, we recorded longitudinal data at two points (approximately 3 months apart) from children aged 3-5 years, and examined reliability under a variety of measures. In both experiments, all children were able to complete testing and provide usable data, a significant improvement over fMRI-based RSFC measurement in children. Results suggest this paradigm is practical and has good construct validity and test-retest reliability, and may contribute towards increasing the availability of reliable data on resting state networks in early childhood. In particular, these are some of the first positive results on the feasibility of reliably measuring functional connectivity in children aged 3-5 years.

scholarly journals Graph Ricci Curvatures Reveal Disease-related Changes in Autism Spectrum Disorder

2021 ◽  
Author(s):  
Pavithra Elumalai ◽  
Yasharth Yadav ◽  
Nitin Williams ◽  
Emil Saucan ◽  
Jürgen Jost ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Resting State ◽  
Neurodevelopmental Disorders ◽  
Data Exchange ◽  
Meta Analysis ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
The Brain

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders that pose a significant global health burden. Measures from graph theory have been used to characterise ASD-related changes in resting-state fMRI functional connectivity networks (FCNs), but recently developed geometry-inspired measures have not been applied so far. In this study, we applied geometry-inspired graph Ricci curvatures to investigate ASD-related changes in resting-state fMRI FCNs. To do this, we applied Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and healthy controls (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We performed these comparisons at the brain-wide level as well as at the level of individual brain regions, and further, determined the behavioral relevance of region-specific differences with Neurosynth meta-analysis decoding. We found brain-wide ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures. For Forman-Ricci curvature, these differences were distributed across 83 of the 200 brain regions studied, and concentrated within the Default Mode, Somatomotor and Ventral Attention Network. Meta-analysis decoding identified the brain regions showing curvature differences as involved in social cognition, memory, language and movement. Notably, comparison with results from previous non-invasive stimulation (TMS/tDCS) experiments revealed that the set of brain regions showing curvature differences overlapped with the set of brain regions whose stimulation resulted in positive cognitive or behavioural outcomes in ASD patients. These results underscore the utility of geometry-inspired graph Ricci curvatures in characterising disease-related changes in ASD, and possibly, other neurodevelopmental disorders.

scholarly journals Amplitude of fNIRS Resting-State Global Signal Is Related to EEG Vigilance Measures: A Simultaneous fNIRS and EEG Study

2020 ◽  
Vol 14 ◽  
Author(s):  
Yuxuan Chen ◽  
Julia Tang ◽  
Yafen Chen ◽  
Jesse Farrand ◽  
Melissa A. Craft ◽  
...  
Keyword(s):  
Human Brain ◽  
Resting State ◽  
Near Infrared ◽  
Low Frequency ◽  
Temporal Correlation ◽  
Frequency Range ◽  
Functional Near Infrared Spectroscopy ◽  
Physical Constraints ◽  
Global Signal ◽  
Eeg Data

Recently, functional near-infrared spectroscopy (fNIRS) has been utilized to image the hemodynamic activities and connectivity in the human brain. With the advantage of economic efficiency, portability, and fewer physical constraints, fNIRS enables studying of the human brain at versatile environment and various body positions, including at bed side and during exercise, which complements the use of functional magnetic resonance imaging (fMRI). However, like fMRI, fNIRS imaging can be influenced by the presence of a strong global component. Yet, the nature of the global signal in fNIRS has not been established. In this study, we investigated the relationship between fNIRS global signal and electroencephalogram (EEG) vigilance using simultaneous recordings in resting healthy subjects in high-density and whole-head montage. In Experiment 1, data were acquired at supine, sitting, and standing positions. Results found that the factor of body positions significantly affected the amplitude of the resting-state fNIRS global signal, prominently in the frequency range of 0.05–0.1 Hz but not in the very low frequency range of less than 0.05 Hz. As a control, the task-induced fNIRS or EEG responses to auditory stimuli did not differ across body positions. However, EEG vigilance plays a modulatory role in the fNIRS signals in the frequency range of less than 0.05 Hz: resting-state sessions of low EEG vigilance measures are associated with high amplitudes of fNIRS global signals. Moreover, in Experiment 2, we further examined the epoch-to-epoch fluctuations in concurrent fNIRS and EEG data acquired from a separate group of subjects and found a negative temporal correlation between EEG vigilance measures and fNIRS global signal amplitudes. Our study for the first time revealed that vigilance as a neurophysiological factor modulates the resting-state dynamics of fNIRS, which have important implications for understanding and processing the noises in fNIRS signals.

scholarly journals Resting-state neural network disturbances that underpin the emergence of emotional symptoms in adolescent girls: resting-state fMRI study

2019 ◽  
Vol 215 (3) ◽  
pp. 545-551 ◽  
Author(s):  
Gin S. Malhi ◽  
Pritha Das ◽  
Tim Outhred ◽  
Richard A. Bryant ◽  
Vince Calhoun
Keyword(s):  
Emotional Disorders ◽  
Adolescent Girls ◽  
Resting State ◽  
Early Adulthood ◽  
Network Connectivity ◽  
Resting State Fmri ◽  
Imaging Data ◽  
Emotional Symptoms ◽  
Fmri Study ◽  
The Right

BackgroundSubsyndromal emotional symptoms in adolescence may represent precursors for full-blown emotional disorders in early adulthood. Understanding the neurobiological mechanisms that drive this development is essential for prevention.AimsSelf-referential processing and emotion regulation are remodelled substantively during adolescence, therefore this study examined integration of key neural networks involved in these processes.MethodAt baseline, clinical and resting-state functional magnetic resonance imaging data were collected for 88 adolescent girls (mean age 15 years), and 71 of these girls underwent repeat clinical assessment after 2 years. These 71 girls were then partitioned into two groups depending on the presence (ES+) or absence (ES−) of emotional symptoms, and differences in dynamic functional network connectivity were determined and correlated with clinical variables.ResultsThe two groups displayed a differential pattern of functional connectivity involving the left lateral prefrontal network (LPFN). Specifically, in the ES+ group this network displayed positive coupling with the right LPFN but negative coupling with the default mode network, and the inverse of this pattern was found in the ES− group. Furthermore, the coupling strengths between left and right LPFN at the irst time point predicted follow-up depression and state anxiety scores.ConclusionsOur findings suggest that in adolescent girls, emotional symptoms may emerge as a result of impaired integration between networks involved in self-referential information processing and approach-avoidance behaviours. These impairments can compromise the pursuit of important goals and have an impact on emotion processing and finally may lead to the development of emotional disorders, such as anxiety and depression in adulthood.Declaration of interestNone.

scholarly journals Median Nerve Electrical Stimulation–Induced Changes in Effective Connectivity in Patients With Stroke as Assessed With Functional Near-Infrared Spectroscopy

2019 ◽  
Vol 33 (12) ◽  
pp. 1008-1017 ◽  
Author(s):  
Congcong Huo ◽  
Xinglou Li ◽  
Jing Jing ◽  
Yanping Ma ◽  
Wenhao Li ◽  
...  
Keyword(s):  
Electrical Stimulation ◽  
Infrared Spectroscopy ◽  
Median Nerve ◽  
Near Infrared Spectroscopy ◽  
Resting State ◽  
Near Infrared ◽  
Cerebral Oxygenation ◽  
Effective Connectivity ◽  
Stroke Patients ◽  
Functional Near Infrared Spectroscopy

Background. The cortical plastic changes in response to median nerve electrical stimulation (MNES) in stroke patients have not been entirely illustrated. Objective. This study aimed to investigate MNES-related changes in effective connectivity (EC) within a cortical network after stroke by using functional near-infrared spectroscopy (fNIRS). Methods. The cerebral oxygenation signals in the bilateral prefrontal cortex (LPFC/RPFC), motor cortex (LMC/RMC), and occipital lobe (LOL/ROL) of 20 stroke patients with right hemiplegia were measured by fNIRS in 2 conditions: (1) resting state and (2) MNES applied to the right wrist. Coupling function together with dynamical Bayesian inference was used to assess MNES-related changes in EC among the cerebral low-frequency fluctuations. Results. Compared with the resting state, EC from LPFC and RPFC to LOL was significantly increased during the MNES state in stroke patients. Additionally, MNES triggered significantly higher coupling strengths from LMC and LOL to RPFC. The interregional main coupling direction was observed from LPFC to bilateral motor and occipital areas in responding to MNES, suggesting that MNES could promote the regulation function of ipsilesional prefrontal areas in the functional network. MNES can induce muscle twitch of the stroke-affected hand involving a decreased neural coupling of the contralesional motor area on the ipsilesional MC. Conclusions. MNES can trigger sensorimotor stimulations of the affected hand that sequentially involved functional reorganization of distant cortical areas after stroke. Investigating MNES-related changes in EC after stroke may help further our understanding of the neural mechanisms underlying MNES.

Bilingual effects on cognitive shifting and prefrontal activations in young children

2019 ◽  
Vol 24 (4) ◽  
pp. 729-739 ◽  
Author(s):  
Yusuke Moriguchi ◽  
Kanda Lertladaluck
Keyword(s):  
Second Language ◽  
Executive Function ◽  
Young Children ◽  
Near Infrared ◽  
Nursery School ◽  
Bilingual Children ◽  
Neural Processing ◽  
Language Experience ◽  
Functional Near Infrared Spectroscopy ◽  
Cognitive Shifting

Aims and objectives: Bilingual children constantly experience spontaneous switching between languages in everyday settings, and some researchers suggest that this experience leads to an advantage in task performance during executive function tasks. Neural processing during executive function tasks remains largely unknown, especially in young bilingual children. Methodology: Using functional near-infrared spectroscopy, this study examined whether young children who attended an immersion second-language program demonstrated enhanced cognitive shifting and lateral prefrontal activation. Data and analysis: We recruited children ( N = 24) who attended an international nursery school, and examined whether their performance on cognitive shifting, and whether the oxygenated hemoglobin changes in the prefrontal regions during the task, were correlated with the children’s second-language verbal age and the length of time the children had been speaking the second language. Findings: Results revealed that the verbal age of the second language and the length of time speaking it were significantly correlated with behavioral performances of cognitive shifting tasks. However, they were not correlated with the activations in the lateral prefrontal regions. Originality: We examined the neural correlates of bilingual effects on cognitive shifting and prefrontal activations in young children. Implications: The results suggest that second-language experience may not be directly related to neural processing in the lateral prefrontal cortex, at least in young children.

Sign in / Sign up

Export Citation Format

Share Document