JMIR Publications

ABSTRACT

Background:

Non-invasive brain stimulation may alleviate social media addiction, but its efficacy requires accurate individual targeting and real-time brain monitoring. The neural mechanisms underlying the effects of social media use (SMU) remain unclear, limiting intervention development. Understanding how different levels of SMU modulate brain activity could guide personalized neuromodulation strategies.

Objective:

This study investigated a cohort of young adults using a multi-stage design, with concurrent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) to examine the effects of SMU on brain activity. It aims to characterize static and dynamic neural changes at baseline and after a standardized SMU task in in individuals with different daily social media usage durations.

Methods:

Participants were divided into a heavy SMU group (HSMU) and a light SMU group (LSMU) based on self-reported daily SMU duration. All participants underwent baseline EEG-fMRI scanning, followed by a second session immediately after a 2-hour controlled SMU task. Analyses were performed on the static and dynamic amplitudes of low-frequency fluctuations (sALFF, dALFF), static and dynamic functional connectivity (sFC, dFC), and EEG microstates.

Results:

At baseline, compared to the LSMU group, the HSMU group showed lower dALFF in the medial frontal gyrus. After the immediate-effect task, the LSMU group exhibited increased sALFF in the temporal gyrus and decreased sALFF in the medial and superior frontal gyrus. The HSMU group showed increased sALFF in temporal lobe and decreased sALFF in the inferior temporal gyrus, left superior parietal gyrus, and prefrontal cortex. Regarding dALFF variability, the LSMU group showed a decrease in medial part of the superior frontal gyrus, whereas the HSMU group showed a decrease in the middle frontal gyrus. sFC analysis revealed increased connectivity across nearly all networks in the LSMU group. Conversely, the HSMU group showed reduced sFC between the visual and default mode networks. EEG microstate analysis indicated decreased duration and coverage of microstates A and C in the HSMU group.

Conclusions:

This study is the first to characterize the distinct neural patterns associated with different levels of daily social media use, using both EEG and fMRI to assess static and dynamic ALFF alterations, widespread functional connectivity changes, and EEG microstate reorganizations. These findings demonstrate the unique value of multimodal assessment in identifying potential neural targets for personalized neuromodulation in social media addiction. Non-invasive brain stimulation therefore represents a promising and scalable strategy for intervention development. Future studies should explore whether modulating these identified neural markers can effectively alleviate addictive behaviors and improve clinical outcomes across diverse populations.