ArticleeNeuro
Topological Data Analysis Reveals Robust Alterations in the Whole-Brain and Frontal Lobe Functional Connectomes in Attention-Deficit/Hyperactivity Disorder.
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14 citing papers in PubMed, 32 citations in OpenAlex.
- Developmental Trajectories and Differences in Functional Brain Network Properties of Preterm and At-Term Neonates.Human brain mapping · 2025Article
- Functional connectivity is linked to working memory differences in children with reading learning disability.BMC pediatrics · 2024Article
- Persistent homology reveals robustness loss in inhaled substance abuse rs-fMRI networks.PloS one · 2024Article
- Altered topological structure of the brain white matter in maltreated children through topological data analysis.Network neuroscience (Cambridge, Mass.) · 2024Article
- Who is WithMe? EEG features for attention in a visual task, with auditory and rhythmic support.Frontiers in neuroscience · 2024Article
- Simple topological task-based functional connectivity features predict longitudinal behavioral change of fluid reasoning in the RANN cohort.NeuroImage · 2023Article
- Persistent homology-based functional connectivity and its association with cognitive ability: Life-span study.Human brain mapping · 2023Article
- Development of the Functional Connectome Topology in Adolescence: Evidence from Topological Data Analysis.eNeuro · 2023Article
- Tree representations of brain structural connectivity via persistent homology.Frontiers in neuroscience · 2023Article
- Article
- A hands-on tutorial on network and topological neuroscience.Brain structure & function · 2022Review
- From calcium imaging to graph topology.Network neuroscience (Cambridge, Mass.) · 2022Review
- Working memory and set-shifting in school-aged children classified as having attention-deficit hyperactivity disorder.The South African journal of psychiatry : SAJP : the journal of the Society of Psychiatrists of South Africa · 2022Article
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4 authors at 1 institution in 1 country.
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Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a developmental disorder characterized by difficulty to control the own behavior. Neuroimaging studies have related ADHD with the interplay of fronto-parietal attention systems with the default mode network (DMN; Castellanos and Aoki, 2016). However, some results have been inconsistent, potentially due to methodological differences in the analytical strategies when defining the brain functional network, i.e., the functional connectivity threshold and/or the brain parcellation scheme. Here, we make use of topological data analysis (TDA) to explore the brain connectome as a function of the filtration value (i.e., the connectivity threshold), instead of using a static connectivity threshold. Specifically, we characterized the transition from all nodes being isolated to being connected into a single component as a function of the filtration value. We explored the utility of such a method to identify differences between 81 children with ADHD (45 male, age: 7.26-17.61 years old) and 96 typically developing children (TDC; 59 male, age: 7.17-17.96 years old), using a public dataset of resting state (rs)fMRI in human subjects. Results were highly congruent when using four different brain segmentations (atlases), and exhibited significant differences for the brain topology of children with ADHD, both at the whole-brain network and the functional subnetwork levels, particularly involving the frontal lobe and the DMN. Therefore, this is a solid approach that complements connectomics-related methods and may contribute to identify the neurophysio-pathology of ADHD.
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