A combination of functional near-infrared spectroscopy, Iowa gambling task, and machine learning techniques allows accurate assessments of brain activation during gaming.
Why this matters
Addiction to gaming is an increasing problem in modern society; people addicted to gaming perceive the game as a necessity, meeting the need for a short-term instant risk without long-term planning. A gaming simulator, the Iowa Gambling Task, was developed to distinguish gamers by their risk-acceptance strategy and diagnose them as addicted and it remains a reliable tool for estimating human behavior during gaming.
The current study incorporated functional near-infrared brain imaging capabilities to provide comprehensive neuroimaging data that, combined with Iowa Gambling Task and driven by machine learning, will facilitate more accurate and detailed analysis of game-related mental disorders.