A team of researchers from Harrisburg University, the National Institutes of Health (NIH), and Southwest University, Chongqing, China, recently published a video game addiction research paper in the Wiley Online Library journal (Brain and Behavior Journal).
The article, titled, “Gaming behavior and brain activation using functional near-infrared spectroscopy, Iowa gambling task, and machine learning techniques,” examines brain activity to identify the characteristics of addictive behavior in gaming and eSports (competitive gaming).
The spread of computer gaming among adolescents and young adults can result in potential negative impacts on normal brain development. The research team, led by HU Professor Dr. Siamak Aram, investigated the use and performance of machine learning (ML) algorithms in the cognitive task of finding the correlation between numerical parameters of human brain activity during gaming.
The team, which includes HU Professors Dr. Stanley Nwoji, Dr. Roozbeh Sadeghian, Dr. Saeed Esmaili-Sardari, and Ph.D. student Denis Kornev, sought to explain the specific origins of addictive gaming behavior.
The researches, which also include Hadis Dashtestani and Amir Gandjbakche of the NIH and Professor Qinghua He of Southwest University, hypothesize that the brain study platform they developed can distinguish between different psychosomatic conditions in the gaming process as measured by the functional near-infrared brain imaging technique. The study found that the application of machine learning models is a powerful technique to evaluate the cognitive neuroimaging task result.
To learn more about the study, visit the research journal link.
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