ArticleHuman brain mapping2014
Atomic dynamic functional interaction patterns for characterization of ADHD.
Article in Human brain mapping, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed.
- Identifying individuals with attention deficit hyperactivity disorder based on temporal variability of dynamic functional connectivity.Scientific reports · 2018Trial
- Abnormal and Changing Information Interaction in Adults with Attention-Deficit/Hyperactivity Disorder Based on Network Motifs.Brain sciences · 2023Article
- Tools of the trade: estimating time-varying connectivity patterns from fMRI data.Social cognitive and affective neuroscience · 2021Review
- Fundamental functional differences between gyri and sulci: implications for brain function, cognition, and behavior.Psychoradiology · 2021Review
- Constructing Dynamic Brain Functional Networks via Hyper-Graph Manifold Regularization for Mild Cognitive Impairment Classification.Frontiers in neuroscience · 2021Article
- The Profiles of Non-stationarity and Non-linearity in the Time Series of Resting-State Brain Networks.Frontiers in neuroscience · 2020Article
- Functional Neuroimaging in the New Era of Big Data.Genomics, proteomics & bioinformatics · 2019Review
- Recognizing Brain States Using Deep Sparse Recurrent Neural Network.IEEE transactions on medical imaging · 2019Article
- Functional Brain Connectivity Revealed by Sparse Coding of Large-Scale Local Field Potential Dynamics.Brain topography · 2019Article
- Abnormal dynamic properties of functional connectivity in disorders of consciousness.NeuroImage. Clinical · 2019Article
- Extracting Reproducible Time-Resolved Resting State Networks Using Dynamic Mode Decomposition.Frontiers in computational neuroscience · 2019Article
- Large-Scale Circuitry Interactions Upon Earthquake Experiences Revealed by Recurrent Neural Networks.IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society · 2018Article
- Neural and metabolic basis of dynamic resting state fMRI.NeuroImage · 2018Review
- Spatio-temporal modeling of connectome-scale brain network interactions via time-evolving graphs.NeuroImage · 2018Review
- Time-Resolved Resting-State Functional Magnetic Resonance Imaging Analysis: Current Status, Challenges, and New Directions.Brain connectivity · 2017Review
- Intrinsic Functional Connectivity in Attention-Deficit/Hyperactivity Disorder: A Science in Development.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2016Article
- Bayesian Inference for Functional Dynamics Exploring in fMRI Data.Computational and mathematical methods in medicine · 2016Review
- Disrupted functional connectivity of cerebellar default network areas in attention-deficit/hyperactivity disorder.Human brain mapping · 2015Article
- Highly adaptive tests for group differences in brain functional connectivity.NeuroImage. Clinical · 2015Article
Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Modeling abnormal temporal dynamics of functional interactions in psychiatric disorders has been of great interest in the neuroimaging field, and thus a variety of methods have been proposed so far. However, the temporal dynamics and disease-related abnormalities of functional interactions within specific data-driven discovered subnetworks have been rarely explored yet. In this work, we propose a novel computational framework composed of an effective Bayesian connectivity change point model for modeling functional brain interactions and their dynamics simultaneously and an effective variant of nonnegative matrix factorization for assessing the functional interaction abnormalities within subnetworks. This framework has been applied on the resting state fmagnetic resonance imaging (fMRI) datasets of 23 children with attention-deficit/hyperactivity disorder (ADHD) and 45 normal control (NC) children, and has revealed two atomic functional interaction patterns (AFIPs) discovered for ADHD and another two AFIPs derived for NC. Together, these four AFIPs could be grouped into two pairs, one common pair representing the common AFIPs in ADHD and NC, and the other abnormal pair representing the abnormal AFIPs in ADHD. Interestingly, by comparing the abnormal AFIP pair, two data-driven abnormal functional subnetworks are derived. Strikingly, by evaluating the approximation based on the four AFIPs, all of the ADHD children were successfully differentiated from NCs without any false positive.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.