ArticleTranslational psychiatry2021
Machine-learning-based diagnosis of drug-naive adult patients with attention-deficit hyperactivity disorder using mismatch negativity.
Article in Translational psychiatry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- A Multimodal Dataset for Neurophysiological and AI Applications.Scientific data · 2026Article
- Digital health technologies for adults with ADHD: a scoping review.Frontiers in digital health · 2026Review
- Retinal fundus imaging as biomarker for ADHD using machine learning for screening and visual attention stratification.NPJ digital medicine · 2025Article
- Are prediction error modifications domain specific in autism but domain general in ADHD?Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Virtual reality-assisted prediction of adult ADHD based on eye tracking, EEG, actigraphy and behavioral indices: a machine learning analysis of independent training and test samples.Translational psychiatry · 2024Article
- Automatic sensory change processing in adults with attention deficit and hyperactivity disorder: a visual mismatch negativity study.European archives of psychiatry and clinical neuroscience · 2024Article
- Gray matter volume associations in youth with ADHD features of inattention and hyperactivity/impulsivity.Human brain mapping · 2024Article
- Acoustic and Text Features Analysis for Adult ADHD Screening: A Data-Driven Approach Utilizing DIVA Interview.IEEE journal of translational engineering in health and medicine · 2024Article
- Gabor filter-based statistical features for ADHD detection.Frontiers in human neuroscience · 2024Article
- Deep learning based source imaging provides strong sublobar localization of epileptogenic zone from MEG interictal spikes.NeuroImage · 2023Article
- Short-term neuronal and synaptic plasticity act in synergy for deviance detection in spiking networks.PLoS computational biology · 2023Article
- Machine learning in attention-deficit/hyperactivity disorder: new approaches toward understanding the neural mechanisms.Translational psychiatry · 2023Review
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7 authors.
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Abstract
Relatively little is investigated regarding the neurophysiology of adult attention-deficit/hyperactivity disorder (ADHD). Mismatch negativity (MMN) is an event-related potential component representing pre-attentive auditory processing, which is closely associated with cognitive status. We investigated MMN features as biomarkers to classify drug-naive adult patients with ADHD and healthy controls (HCs). Sensor-level features (amplitude and latency) and source-level features (source activation) of MMN were investigated and compared between the electroencephalograms of 34 patients with ADHD and 45 HCs using a passive auditory oddball paradigm. Correlations between MMN features and ADHD symptoms were analyzed. Finally, we applied machine learning to differentiate the two groups using sensor- and source-level features of MMN. Adult patients with ADHD showed significantly lower MMN amplitudes at the frontocentral electrodes and reduced MMN source activation in the frontal, temporal, and limbic lobes, which were closely associated with MMN generators and ADHD pathophysiology. Source activities were significantly correlated with ADHD symptoms. The best classification performance for adult ADHD patients and HCs showed an 81.01% accuracy, 82.35% sensitivity, and 80.00% specificity based on MMN source activity features. Our results suggest that abnormal MMN reflects the adult ADHD patients' pathophysiological characteristics and might serve clinically as a neuromarker of adult ADHD.
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