Six months of action gaming alters brain networks and improves visual attention

Playing fast-paced video games over several months may lead to measurable improvements in attention and changes in resting brain activity. A small study published in the International Journal of Psychophysiology suggests that action video games alter both local brain wave power and large-scale communication between brain regions. These neural shifts can even predict how much a person’s attention will improve after extended gaming practice.

Action video games require players to constantly scan a cluttered visual environment for sudden threats while maintaining focus on specific targets. Because of these intense mental demands, cognitive scientists frequently use first-person shooter games to explore how the human brain adapts to new challenges. Playing these games repeatedly forces the brain to process spatial and temporal information at high speeds.

Past research indicates that this type of gaming enhances selective attention, which is the ability to focus on relevant information while ignoring visual distractions. It also improves distributed attention, which involves spreading mental focus across a wide spatial area to monitor multiple events at once. Both types of attention depend on isolated brain regions as well as synchronized communication across the entire brain.

Previous neuroimaging studies examining video games have often been limited to short training periods lasting only a few weeks or hours. These brief interventions are useful for capturing immediate reactions, but they miss the slow, cumulative physical changes that occur in the brain over long periods. Older studies mostly focused on local brain activity rather than the complex networks connecting different lobes. Many studies also relied on functional magnetic resonance imaging, which is expensive and physically restricts participants during training tasks.

To understand how extended video game play reshapes the brain over time, lead author Jihan Wang of the University of Electronic Science and Technology of China designed a long-term experiment. Wang and a team of researchers tracked changes in localized brain waves and whole-brain connectivity over a half-year period. The team included Yan Peng, Bin Lv, and Dezhong Yao.

The researchers recruited university students with little to no prior gaming experience. Forty-three participants completed the entire six-month protocol, making this a small study. The participants were instructed to play the game Counter-Strike: Global Offensive for one hour a day, five days a week, accumulating roughly 120 hours of play.

The researchers assessed the participants at the beginning of the study, at the three-month mark, and at the end of the six months. At each assessment point, the participants completed two distinct behavioral tasks. The first task evaluated selective attention by requiring participants to quickly scan lines of letters on a computer screen. They had to press a key only when they spotted a specific target letter, such as a “d” with two dashes, while ignoring other letters or similar characters.

The second task evaluated distributed attention by presenting six distinct shapes in the peripheral visual field around a central focal point. Participants had to identify whether a specific target shape was present among the other objects. Both tasks recorded the speed of correct responses, filtering out completely implausible reaction times to ensure accuracy.

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Reaction times on the selective attention task improved steadily between the baseline assessment and the six-month mark. Reaction times on the distributed attention task improved sharply between the baseline and the three-month mark. This metric showed continued improvement by the end of the study.

Alongside the behavioral tasks, the researchers recorded the electrical activity of each participant’s brain using electroencephalography, or EEG. These recordings were taken while the participants rested quietly with their eyes closed. Resting-state recordings provide a measure of the brain’s intrinsic, default organization rather than its reaction to an immediate stimulus. The fast response time of an EEG machine makes it an ideal tool for longitudinally tracking these gradual electrical shifts.

The team first analyzed local brain activity by breaking down the electrical signals into specific frequency bands. They focused on alpha waves, which are electrical pulses occurring eight to thirteen times per second. High alpha wave activity is generally associated with a resting state and the suppression of irrelevant visual information.

As the training progressed, alpha wave power steadily decreased, primarily in the parietal and occipital regions at the back of the brain. A reduction in resting alpha power generally reflects a state of higher brain excitability and mental readiness. The researchers noted that participants who showed the greatest reduction in alpha power also demonstrated the fastest reaction times on the selective attention task.

Next, the researchers analyzed the EEG data to map functional networks across the entire brain. They used a mathematical technique to measure how closely different brain regions synchronized the peaks and valleys of their electrical waves. Highly synchronized regions are thought to communicate more efficiently with one another.

The analysis revealed a progressive increase in synchronization between spatially separated brain regions. During the first three months, connectivity increased moderately across central areas of the brain. By six months, this synchronization became more focused and intense, particularly bridging the frontal, parietal, and occipital lobes.

The team calculated specific network properties to describe how efficiently information traveled through these newly synchronized pathways. They measured factors like the clustering coefficient, which tracks how well neighboring brain regions connect, and path length, which tracks the minimum number of steps needed for a signal to cross the network. These metrics provide a mathematical snapshot of how well the brain integrates information.

The researchers found that the overall efficiency and clustering of the brain networks improved from the baseline to the six-month mark. These structural upgrades hinted at a more integrated electrical environment. However, these network changes weakly correlated with improved performance on the behavioral tasks, and the findings were not statistically significant after adjusting for multiple comparisons.

Finally, the research team built statistical models to see if the physiological data could predict individual behavioral outcomes. They trained a program to look for associations between the electrical brain data and the reaction time improvements. To prevent the model from simply memorizing the data, they tested it by hiding one participant’s results, asking the model to predict that participant’s score, and repeating the process for everyone.

They found that both the local alpha wave changes and the global network changes accurately predicted how much a participant’s reaction time would drop over the six months. Local alpha wave features successfully predicted improvements in both the selective and distributed attention tasks. Features based on whole-brain network properties also predicted selective attention improvements.

The study relies on a single-group design without an inactive control group. Because of this, it is not possible to state with certainty that the video game training directly caused the observed neural and behavioral changes. The improvements could stem from a practice effect, where participants get naturally faster at the assessment tasks after taking them multiple times. Maturation over the six-month period might also account for some cognitive changes.

Outside factors were not strictly monitored during the half-year timeframe. Changes in daily routines, stress levels, or overall lifestyle might have influenced the physiological results. The research also only examined resting brain activity, meaning it remains unknown exactly how these neural networks operate while the participants are actively engaged in demanding cognitive tasks.

The study, “Multi-scale EEG evidence for attention enhancement following long-term action video game training,” was authored by Jihan Wang, Yan Peng, Bin Lv, and Dezhong Yao.