ArticleHuman brain mapping2021
Age-related and individual variations in altered prefrontal and cerebellar connectivity associated with the tendency of developing internet addiction.
Article in Human brain mapping, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Structural and Functional Neural Correlates in Individuals with Excessive Smartphone Use: A Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2022Pooled it
- The Effect of Overcoming the Digital Divide on Middle Frontal Gyrus Atrophy in Aging Adults: Large-Scale Retrospective Magnetic Resonance Imaging Cohort Study.Journal of medical Internet research · 2025Article
- Algorithm-associated digital addiction among older adults: mechanisms and public health implications for healthy aging.Frontiers in public health · 2025Article
- Negative emotions mediate the association between the topology of the complex brain network and smartphone use disorder: A resting-state EEG study.Journal of behavioral addictions · 2024Article
- Risks and protection: a qualitative study on the factors for internet addiction among elderly residents in Southwest China communities.BMC public health · 2024Article
- Connectome-based predictive modeling of Internet addiction symptomatology.Social cognitive and affective neuroscience · 2024Article
- Psychosocial Basis of Human Sufferings and Poverty in Patients with Neurological and Psychiatric Disorders.Medical research archives · 2023Article
- Physical exercise/sports ameliorate the internet addiction from college students during the pandemic of COVID-19 in China.Frontiers in public health · 2023Article
- Age-related and individual variations in altered prefrontal and cerebellar connectivity associated with the tendency of developing internet addiction.Human brain mapping · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Internet addiction refers to problematic patterns of internet use that continually alter the neural organization and brain networks that control impulsive behaviors and inhibitory functions. Individuals with elevated tendencies to develop internet addiction represent the transition between healthy and clinical conditions and may progress to behavioral addictive disorders. In this network neuroscience study, we used resting-state functional magnetic resonance imaging (rs-fMRI) to examine how and whether individual variations in the tendency of developing internet addiction rewire functional connectivity and diminish the amplitude of spontaneous low-frequency fluctuations in healthy brains. The influence of neurocognitive aging (aged over 60 years) on executive-cerebellar networks responsible for internet addictive behavior was also investigated. Our results revealed that individuals with an elevated tendency of developing internet addiction had disrupted executive-cerebellar networks but increased occipital-putamen connectivity, probably resulting from addiction-sensitive cognitive control processes and bottom-up sensory plasticity. Neurocognitive aging alleviated the effects of reduced mechanisms of prefrontal and cerebellar connectivity, suggesting age-related modulation of addiction-associated brain networks in response to compulsive internet use. Our findings highlight age-related and individual differences in altered functional connectivity and the brain networks of individuals at a high risk of developing internet addictive disorders. These results offer novel network-based preclinical markers of internet addictive behaviors for individuals of different ages.
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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.