ArticleJournal of behavioral addictions2017
Resting-state EEG activity related to impulsivity in gambling disorder.
Article in Journal of behavioral addictions, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
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- Altered long-range temporal correlations in delta oscillatory amplitude dynamics in gambling disorder.European archives of psychiatry and clinical neuroscience · 2026Article
- Resting-state EEG power and machine-learning classification in adult males with gambling disorder.Frontiers in human neuroscience · 2025Article
- Interhemispheric EEG coherence as a candidate biomarker in gambling disorder: evidence of frontal hyperconnectivity and posterior disconnectivity.Frontiers in neuroscience · 2025Article
- Neurophysiological correlates of trait and behavioral impulsivity across methamphetamine and gambling Addiction.Heliyon · 2024Article
- Machine learning-based classifying of risk-takers and risk-aversive individuals using resting-state EEG data: A pilot feasibility study.Brain and behavior · 2023Article
- Paranormal believers show reduced resting EEG beta band oscillations and inhibitory control than skeptics.Scientific reports · 2023Article
- Association between resting-state EEG oscillation and psychometric properties in perimenopausal women.BMC women's health · 2022Article
- Differentiating Individuals with and without Alcohol Use Disorder Using Resting-State fMRI Functional Connectivity of Reward Network, Neuropsychological Performance, and Impulsivity Measures.Behavioral sciences (Basel, Switzerland) · 2022Article
- Slow-Wave EEG Activity Correlates with Impaired Inhibitory Control in Internet Addiction Disorder.International journal of environmental research and public health · 2022Article
- Computer Gaming and Physiological Changes in the Brain: An Insight from QEEG Complexity Analysis.Applied psychophysiology and biofeedback · 2021Article
- Random Forest Classification of Alcohol Use Disorder Using EEG Source Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures.Behavioral sciences (Basel, Switzerland) · 2020Article
- Random Forest Classification of Alcohol Use Disorder Using fMRI Functional Connectivity, Neuropsychological Functioning, and Impulsivity Measures.Brain sciences · 2020Article
- Exploratory Analysis of Behavioral Impulsivity, Pro-inflammatory Cytokines, and Resting-State Frontal EEG Activity Associated With Non-suicidal Self-Injury in Patients With Mood Disorder.Frontiers in psychiatry · 2020Article
- Different aspects of impulsivity in chronic alcohol use disorder with and without comorbid problem gambling.PloS one · 2020Article
- Excessive discounting of delayed reinforcers as a trans-disease process: Update on the state of the science.Current opinion in psychology · 2019Review
- Computer-aided classifying and characterizing of methamphetamine use disorder using resting-state EEG.Cognitive neurodynamics · 2019Article
- Disrupted resting-state brain functional network in methamphetamine abusers: A brain source space study by EEG.PloS one · 2019Article
- Correlation between precontemplation and alpha activity in gambling disorder.Neuropsychiatric disease and treatment · 2019Article
- The Degree of Modulation of Beta Band Activity During Motor Planning Is Related to Trait Impulsivity.Frontiers in integrative neuroscience · 2019Article
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Authors and funding
7 authors.
Funding
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Abstract
Background and aims Impulsivity is a core feature of gambling disorder (GD) and is related to the treatment response. Thus, it is of interest to determine objective neurobiological markers associated with impulsivity in GD. We explored resting-state electroencephalographic (EEG) activity in patients with GD according to the degree of impulsivity. Methods In total, 109 GD subjects were divided into three groups according to Barratt impulsiveness scale-11 (BIS-11) scores: high (HI; 25th percentile of BIS-11 scores, n = 29), middle (MI; 26th-74th percentile, n = 57), and low-impulsivity (LI) groups (75th percentile, n = 23). We used generalized estimating equations to analyze differences in EEG absolute power considering group (HI, MI, and LI), brain region (frontal, central, and posterior), and hemisphere (left, midline, and right) for each frequency band (delta, theta, alpha, beta, and gamma). Results The results indicated that GD patients in the HI group showed decreased theta absolute power, and decreased alpha and beta absolute power in the left, right, particularly midline frontocentral regions. Discussion and conclusions This study is a novel attempt to reveal impulsive features in GD by neurophysiological methods. The results suggest different EEG patterns among GD patients according to the degree of impulsivity, raising the possibility of neurophysiological objective features in GD and helping clinicians in treating GD patients with impulsive features.
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