A new study published in Computers in Human Behavior suggests that specific structural and functional patterns within the brain’s default mode network can predict the severity of problematic smartphone use months or even years later. The findings indicate that these brain features contribute to excessive phone use through two distinct psychological pathways involving fear of missing out and negative emotional states.
Problematic smartphone use has become a widespread issue associated with anxiety, sleep disturbances, and social disruption. While it shares characteristics with behavioral addictions, such as loss of control and craving, the underlying neurobiological mechanisms remain a subject of debate. Previous scientific inquiries have implicated the default mode network in various forms of addiction. This network consists of a system of brain regions that are active during rest and engaged in self-reflection.
Most prior investigations relied on snapshots of brain activity taken at a single point in time. This cross-sectional approach makes it difficult to determine whether brain differences cause the behavior or result from it.
The authors of the new study sought to establish a timeline by using a longitudinal design. They aimed to determine if specific features of the default mode network could predict the future development of problematic smartphone use. They also sought to understand the psychological drivers linking brain biology to behavior and to explore the genetic underpinnings of these neural patterns.
“Our primary motivation came from a very concrete real-world issue: in everyday life, smartphones have become deeply embedded in learning, work, and social interaction, yet more and more young people report that they ‘can’t put the phone down,’ to the point that it affects their sleep, mood, and academic performance,” explained study author Qiang Wang, a professor of psychology at Tianjin Normal University.
“Unlike gambling or gaming, smartphones are almost universally used tools, which makes it very difficult to draw a sharp line between ‘addictive’ and ‘normal’ use. From a scientific perspective, most prior work on problematic smartphone use has relied on cross-sectional designs. There are relatively few multi-site longitudinal studies, and even fewer that integrate brain structure, resting-state function, and transcriptomics (gene expression) in the same framework.”
“At the same time, the default mode network (DMN) has repeatedly been implicated in various addictive behaviors, but it remained unclear whether the anterior and posterior DMN differentially predict future problematic smartphone use, and how these neural features operate through key psychological variables such as fear of missing out (FoMO) and negative affect.”
For their study, the research team recruited 282 young adults from four different universities and research sites in China. At the start of the study, participants underwent magnetic resonance imaging scans to measure brain structure and function. Brain structure refers to the physical architecture and density of neural tissue, while functional measures track the dynamic activity and communication patterns occurring within the brain.
The researchers specifically looked at gray matter volume. This measure represents the density of brain cells in a region. They also analyzed regional homogeneity, which measures how synchronized the activity is within a specific brain area.
Participants also completed psychological assessments to establish baseline levels of smartphone addiction symptoms, fear of missing out, and negative emotions. The researchers then followed up with the participants after intervals ranging from five months to five years.
At the follow-up stage, participants repeated the assessments regarding their smartphone use and psychological state. To ensure the data from different scanning sites was comparable, the team used advanced statistical harmonization techniques.
The data analysis revealed a specific division of labor within the default mode network regarding the prediction of smartphone habits. The researchers found that the volume of gray matter in the anterior, or front, part of this network predicted the severity of problematic smartphone use at the follow-up.
This predictive power was strongest in the ventromedial prefrontal cortex. This brain region is typically involved in emotion regulation and self-referential processing.
The analysis showed that this relationship was not direct. Instead, it was mediated by psychological factors. The structural features of the anterior default mode network predicted higher levels of fear of missing out at the follow-up.
This heightened social anxiety then predicted more severe problematic smartphone use. This pathway aligns with social cognitive models of addiction, which suggest that the need for social connection can drive compulsive behaviors.
A different pattern emerged for the posterior, or rear, part of the network. The researchers observed that the spontaneous functional activity in the posterior cingulate cortex predicted future smartphone problems through a different pathway.
In this case, the brain activity predicted higher levels of negative affect, such as anxiety or depression. These negative emotions then led to increased smartphone use. The posterior cingulate cortex is a central hub for mind-wandering and directing attention internally.
This finding suggests a double dissociation effect. This means that different parts of the same brain network drive the behavior through separate psychological mechanisms. The anterior section appears to influence social motivation, while the posterior section relates to emotional regulation.
“One particularly striking and somewhat surprising finding was the clear double dissociation between the anterior and posterior default mode network, not only at the level of structural and functional prediction, but also at the psychological level,” Wang told PsyPost.
“Structural indices in the anterior default mode network primarily exerted their influence via FoMO, which is more closely related to social motivation and relationship needs. Functional indices in the posterior default mode network mainly operated via negative affect, which is more closely tied to emotional experience.”
“We initially expected that both FoMO and negative affect would show some degree of mediation, but we did not anticipate that their corresponding neural pathways would be so distinctly ‘specialized’ and statistically independent,” Wang said. “This suggests that social motivation and emotion regulation may rely on different, yet cooperating, neural pathways that together shape how a person uses their smartphone.”
“Put simply, our findings suggest that whether someone will later find it harder to put their phone down is, to some extent, linked to how the anterior and posterior parts of their default mode network are structured and functioning at baseline—and that this influence is transmitted through their emotional state and social motivation.”
To understand the biological roots of these brain patterns, the team performed a transcriptomic analysis. They compared their imaging results with data from the Allen Human Brain Atlas. This allowed them to identify gene expression profiles associated with the brain regions identified in the study. This analysis highlighted a set of genes involved in synaptic transmission.
These genes are responsible for the regulation of glutamate, a key neurotransmitter in the brain. The analysis showed that these genes were expressed significantly in both excitatory and inhibitory neurons. This suggests that an imbalance in neural signaling may contribute to the compulsive nature of smartphone use.
Furthermore, the researchers examined the developmental timeline of these genes. They found that the expression of these specific genes peaks during infancy and adolescence. These periods are critical for brain maturation.
This finding implies that early neural development may set the stage for vulnerabilities to addictive behaviors later in life. Adolescence is a particularly sensitive period for the maturation of reward processing and emotion regulation.
Wang noted that the observed effects were small to moderate but remained statistically stable even after controlling for various demographic factors. He emphasized that these findings should be viewed as population-level risk markers rather than diagnostic tools, as no single brain region determines whether a person will develop an addiction. These neural patterns represent just one piece of a larger puzzle.
“For the average reader, an important takeaway is that problematic smartphone use is not just about ‘weak willpower,'” Wang told PsyPost. “It reflects the long-term interaction of brain systems involved in self-related processing, emotion regulation, and social motivation. Paying attention to one’s emotional state (e.g., anxiety, low mood) and to anxiety about ‘missing out’ may be a key entry point for preventing loss of control over smartphone use.”
The study sheds light on the neurobiological basis of smartphone struggles, but it has certain limitations. The reliance on self-reported surveys for smartphone use may introduce subjective bias compared to objective digital logs. The sample consisted primarily of young adult university students. This means the results might not apply to children or older adults.
Additionally, the transcriptomic analysis relied on a post-mortem brain atlas rather than genetic data from the participants themselves. This provides a general correlation rather than a direct genetic link for the specific individuals in the study.
Looking ahead, the researchers aim to integrate objective tracking of smartphone usage data to create more accurate behavioral trajectories. They also plan to investigate whether psychological interventions can modify these brain patterns. Expanding the study to include adolescents would help clarify how these brain networks develop during critical periods of maturation.
“We hope this research can help shift discussions about problematic smartphone use away from simple moral judgments and generational conflicts, and toward a more evidence-based understanding that integrates psychological and biological foundations,” Wang said. “If we treat FoMO and negative affect as key nodes in this system, we can adopt a more compassionate view of people who ‘cannot put their phones down’: they are often using their phones to compensate for emotional gaps or social worries in real life, rather than simply lacking willpower.”
“From the perspective of public policy and educational practice, we hope this line of work can inform more nuanced and gentle interventions—for example, better design of digital environments, stronger emotional education, and improved social support—rather than relying on crude, blanket bans on smartphone use.”
The study, “Anterior-posterior dissociation of default mode network predicts problematic smartphone use: A multi-site longitudinal and transcriptomic analysis,” was authored by Qiang Wang, Jinlian Wang, Xiang Li, Chang Liu, Pinchun Wang, and Weipeng Jin.
