Disrupted functional brain connectivity networks in children with attention-deficit/hyperactivity disorder: evidence from resting-state functional near-infrared spectroscopy

Wang, Mengjing; Hu, Zhishan; Liu, Lu; Li, Haimei; Qian, Qiujin; Niu, Haijing

doi:10.1117/1.nph.7.1.015012

Cited by 58 publications

(43 citation statements)

References 73 publications

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“…For example, reduced gray matter volume in the right middle occipital gyrus ( Wang L. J. et al, 2020 ) and hyper-activation of occipital lobe function was found in ADHD ( Tian et al, 2008 ; Icer et al, 2019 ), indicating that atypical visual processing may play a key role. Previous study also reported that the decreased connectivity between the frontal cortex and visual cortex was associated with increased severity in ADHD symptoms ( Wang M. et al, 2020 ). Meanwhile, the interaction between the dorsal attention network and visual cortex is important for maintaining attention ( Shulman et al, 2009 ).…”

Section: Discussionmentioning

confidence: 77%

Altered Variability and Concordance of Dynamic Resting-State fMRI Indices in Patients With Attention Deficit Hyperactivity Disorder

et al. 2021

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Objective: Attention deficit hyperactivity disorder (ADHD) is a commonly diagnosed neuropsychiatric disorder in children, which is characterized by inattention, hyperactivity and impulsivity. Using resting-state functional magnetic resonance imaging (R-fMRI), the alterations of static and dynamic characteristics of intrinsic brain activity have been identified in patients with ADHD. Yet, it remains unclear whether the concordance among indices of dynamic R-fMRI is altered in ADHD.Methods: R-fMRI scans obtained from 50 patients with ADHD and 28 healthy controls (HC) were used for the current study. We calculated the regional dynamic changes in brain activity indices using the sliding-window method and compared the differences in variability of these indices between ADHD patients and HCs. Further, the concordance among these dynamic indices was calculated and compared. Finally, the relationship between variability/concordance of these indices and ADHD-relevant clinical test scores was investigated.Results: Patients with ADHD showed decreased variability of dynamic amplitude of low-frequency fluctuation (dALFF) in the left middle frontal gyrus and increased one in right middle occipital gyrus, as compared with the HCs. Besides, ADHD patients showed decreased voxel-wise concordance in the left middle frontal gyrus. Further, lower voxel-wise concordance in ADHD’s left middle frontal gyrus was associated with more non-perseverative errors in Wisconsin Card Sorting Test, which reflects worse cognitive control.Conclusion: Our findings suggest that variability and concordance in dynamic brain activity may serve as biomarkers for the diagnosis of ADHD. Further, the decreased voxel-wise concordance is associated with deficit in cognitive control in ADHD patients.

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Section: Discussionmentioning

confidence: 77%

Altered Variability and Concordance of Dynamic Resting-State fMRI Indices in Patients With Attention Deficit Hyperactivity Disorder

et al. 2021

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“…GE has been proposed and shown to be a robust and reliable biomarker in many fNIRS studies. 21 , 64 – 69 In most cases resting fNIRS data were used to calculate the FC matrices. GE values were always computed after a threshold value was adapted.…”

Section: Discussionmentioning

confidence: 99%

fNIRS-derived neurocognitive ratio as a biomarker for neuropsychiatric diseases

Akın

2021

Neurophoton.

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. Significance: Clinical use of fNIRS-derived features has always suffered low sensitivity and specificity due to signal contamination from background systemic physiological fluctuations. We provide an algorithm to extract cognition-related features by eliminating the effect of background signal contamination, hence improving the classification accuracy. Aim: The aim in this study is to investigate the classification accuracy of an fNIRS-derived biomarker based on global efficiency (GE). To this end, fNIRS data were collected during a computerized Stroop task from healthy controls and patients with migraine, obsessive compulsive disorder, and schizophrenia. Approach: Functional connectivity (FC) maps were computed from [HbO] time series data for neutral (N), congruent (C), and incongruent (I) stimuli using the partial correlation approach. Reconstruction of FC matrices with optimal choice of principal components yielded two independent networks: cognitive mode network (CM) and default mode network (DM). Results: GE values computed for each FC matrix after applying principal component analysis (PCA) yielded strong statistical significance leading to a higher specificity and accuracy. A new index, neurocognitive ratio (NCR), was computed by multiplying the cognitive quotients (CQ) and ratio of GE of CM to GE of DM. When mean values of NCR ( ) over all stimuli were computed, they showed high sensitivity (100%), specificity (95.5%), and accuracy (96.3%) for all subjects groups. Conclusions: can reliable be used as a biomarker to improve the classification of healthy to neuropsychiatric patients.

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“…It is well-established that disruptions in functional connectivity and topological network organization underlie various neurological disorders (Suo et al, 2015;Wang et al, 2020). Meanwhile, resting-state fNIRS has been widely used to capture network dysfunctions in the early stage and to aid diagnosis of many pediatric neurological conditions.…”

Section: Brain Connectome In Children With Neurological Disordersmentioning

confidence: 99%

Applications of Resting-State fNIRS in the Developing Brain: A Review From the Connectome Perspective

Liu

Dong

et al. 2020

Front. Neurosci.

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Early brain development from infancy through childhood is closely related to the development of cognition and behavior in later life. Human brain connectome is a novel framework for describing topological organization of the developing brain. Resting-state functional near-infrared spectroscopy (fNIRS), with a natural scanning environment, low cost, and high portability, is considered as an emerging imaging technique and has shown valuable potential in exploring brain network architecture and its changes during the development. Here, we review the recent advances involving typical and atypical development of the brain connectome from neonates to children using resting-state fNIRS imaging. This review highlights that the combination of brain connectome and resting-state fNIRS imaging offers a promising framework for understanding human brain development.

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Disrupted functional brain connectivity networks in children with attention-deficit/hyperactivity disorder: evidence from resting-state functional near-infrared spectroscopy

Cited by 58 publications

References 73 publications

Altered Variability and Concordance of Dynamic Resting-State fMRI Indices in Patients With Attention Deficit Hyperactivity Disorder

Altered Variability and Concordance of Dynamic Resting-State fMRI Indices in Patients With Attention Deficit Hyperactivity Disorder

fNIRS-derived neurocognitive ratio as a biomarker for neuropsychiatric diseases

Applications of Resting-State fNIRS in the Developing Brain: A Review From the Connectome Perspective

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