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Neural network connectivity in ADHD children: an independent component and functional connectivity analysis of resting state fMRI data.

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Abstract

Resting-state functional magnetic resonance imaging (rsfMRI) is a novel approach that has the potential to examine abnormalities in the default mode network (DMN) component. Two different approaches were used in the present study to characterize the functional connectivities of various DMN components in 16 non-medicated ADHD and a similar number of TD (typically developing) children. rsfMRI data were analysed using independent component analysis (ICA) and region-of-interest (ROI) seed to voxel correlation analysis. ICA results indicated a strong coherence of the left dorsal anterior cingular cortex (dACC) with the DMN components in children with ADHD. In addition, seed-to-voxel functional connectivity analysis using the left dorsal anterior cingulate as a seed region suggested higher temporal coherence with other neural networks upon comparison with TD children. These results imply children with ADHD exhibit a higher dispersed resting state connectivity pattern in DMN and other networks.

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Acknowledgements

We thank Dr. Alka Shukla and Vikram Singh for their technical assistant in data collection.

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Authors and Affiliations

  1. Department of Neuroimaging, Centre of Bio-Medical Research, Sanjay Gandhi Postgraduate Institute of Medical Sciences Campus, Lucknow, Uttar Pradesh, 226014, India

    Uttam Kumar

  2. Department of Psychiatry, King George Medical University, Lucknow, India

    Amit Arya & Vivek Agarwal

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  1. Uttam Kumar
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Correspondence to Uttam Kumar.

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Kumar, U., Arya, A. & Agarwal, V. Neural network connectivity in ADHD children: an independent component and functional connectivity analysis of resting state fMRI data.. Brain Imaging and Behavior 15, 157–165 (2021). https://doi.org/10.1007/s11682-019-00242-0

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