ArticleSensors (Basel, Switzerland)2019
Neural Activities Classification of Human Inhibitory Control Using Hierarchical Model.
Article in Sensors (Basel, Switzerland), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.JAMA network open · 2023Pooled it
- The effect of transcranial random noise stimulation (tRNS) over bilateral parietal cortex in visual cross-modal conflicts.Scientific reports · 2025Trial
- Sampling inequalities affect generalization of neuroimaging-based diagnostic classifiers in psychiatry.BMC medicine · 2023Article
- Evaluation of Emotions from Brain Signals on 3D VAD Space via Artificial Intelligence Techniques.Diagnostics (Basel, Switzerland) · 2023Article
- Alzheimer's Disease Analysis Algorithm Based on No-threshold Recurrence Plot Convolution Network.Frontiers in aging neuroscience · 2022Article
- Neural Dynamics of Target Detection via Wireless EEG in Embodied Cognition.Sensors (Basel, Switzerland) · 2021Article
- Data Augmentation: Using Channel-Level Recombination to Improve Classification Performance for Motor Imagery EEG.Frontiers in human neuroscience · 2021Article
- Global Neural Activities Changes under Human Inhibitory Control Using Translational Scenario.Brain sciences · 2020Article
- Exploration of User's Mental State Changes during Performing Brain-Computer Interface.Sensors (Basel, Switzerland) · 2020Article
- Exploration of Brain Connectivity during Human Inhibitory Control Using Inter-Trial Coherence.Sensors (Basel, Switzerland) · 2020Article
- The Study of Influence of Sound on Visual ERP-Based Brain Computer Interface.Sensors (Basel, Switzerland) · 2020Article
- In Quest of Pathognomonic/Endophenotypic Markers of Attention Deficit Hyperactivity Disorder (ADHD): Potential of EEG-Based Frequency Analysis and ERPs to Better Detect, Prevent and Manage ADHD.Medical devices (Auckland, N.Z.) · 2020Review
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Authors and funding
2 authors.
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Abstract
Human inhibitory control refers to the suppression of behavioral response in real environments, such as when driving a car or riding a motorcycle, playing a game and operating a machine. The P300 wave is a neural marker of human inhibitory control, and it can be used to recognize the symptoms of attention deficit hyperactivity disorder (ADHD) in human. In addition, the P300 neural marker can be considered as a stop command in the brain-computer interface (BCI) technologies. Therefore, the present study of electroencephalography (EEG) recognizes the mindset of human inhibition by observing the brain dynamics, like P300 wave in the frontal lobe, supplementary motor area, and in the right temporoparietal junction of the brain, all of them have been associated with response inhibition. Our work developed a hierarchical classification model to identify the neural activities of human inhibition. To accomplish this goal phase-locking value (PLV) method was used to select coupled brain regions related to inhibition because this method has demonstrated the best performance of the classification system. The PLVs were used with pattern recognition algorithms to classify a successful-stop versus a failed-stop in left-and right-hand inhibitions. The results demonstrate that quadratic discriminant analysis (QDA) yielded an average classification accuracy of 94.44%. These findings implicate the neural activities of human inhibition can be utilized as a stop command in BCI technologies, as well as to identify the symptoms of ADHD patients in clinical research.
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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.