Your brain looks fine on the outside. Reaction times hold steady, accuracy doesn’t drop, and you’d pass any basic performance test without raising a flag. A teacher watching you complete an assignment wouldn’t notice anything off. But underneath that surface, something is shifting.
A 2024 EEG study from Zhejiang University in China found that the more time people spend on short-form video platforms like TikTok, Reels, and YouTube Shorts, the weaker their brain’s executive control signals become, even when their behavior still looks normal.
That gap between what performance shows and what the brain is actually doing is what makes this study worth reading carefully. Yan et al. (2024) recruited 48 university-aged participants and measured their brain activity using EEG during an attention network test (ANT), a task designed to assess three types of attention: alerting (staying ready), orienting (directing focus), and executive control (managing conflict between competing information). Participants also completed the Mobile Phone Short Video Addiction Tendency Questionnaire (MPSVATQ) and a self-control scale.
Short-Form Video Affects Attention
The headline result: participants who scored higher on short-form video addiction tendency showed significantly weaker theta brainwave activity in the frontal region during tasks requiring executive control. Theta waves in the prefrontal cortex are tied to cognitive conflict resolution, the brain’s ability to sort through competing signals and pick the right one. When that power drops, it means fewer neural resources are being recruited for the job.
What I find particularly telling is how specific the correlation was. Yan et al. report that “a noteworthy negative correlation was only found between the activity of the frontal region and MPSVATQ scores when assessing the theta power under incongruent target condition, with neutral target conditions serving as a control baseline condition (r = −0.395, p = 0.007)” (p. 6). The effect didn’t show up during resting states. It didn’t show up during easier trials. It appeared only when the brain had to actively work to suppress conflicting stimuli. That’s a precise finding, and it points to something more troubling than general distraction.
But the behavioral data showed nothing. No significant correlation between short-form video addiction tendency and reaction times or accuracy on the ANT. Yan et al. acknowledge the task may have been too simple to reveal behavioral differences. But the neural data told a different story, one the authors frame clearly:
the significant negative correlation between MPSVATQ and theta power difference under incongruent minus neutral target condition in the frontal area suggests the use of short video has negative impact on the neural processing underlying executive control, even in the absence of observable differences in specific behavioral tasks. (p. 9)
I’ve covered a similar disconnect in my post on Kosmyna et al.’s study of brain activity during ChatGPT use. In that research, neural engagement dropped when participants relied on AI for answers, even though output quality stayed the same. The pattern keeps appearing across different technologies: the brain scales back its effort before performance catches up. By the time you see the decline in test scores or task accuracy, the underlying machinery has already been weakened for a while.
Yan et al. go further in explaining the mechanism. They argue that:
short-form videos, being self-stimulating and content-rich, capture attention with minimal psychological effort. Prolonged consumption of such content may primarily engage the lower-order cortical brain regions, such as those associated with emotional processing, and suppress activity in higher-order areas responsible for self-control and attention. (p. 9)
The logic here connects directly to what Gerlich (2025) found in his study on cognitive offloading and critical thinking erosion, where habitual reliance on AI tools weakened higher-order reasoning skills. The medium is different, short-form video versus generative AI, but the cognitive trajectory is strikingly similar: low-effort engagement feeds lower-order processing, and the higher-order systems start to atrophy.
The study also found a significant negative correlation between short-form video addiction tendency and self-control. Higher addiction scores meant lower self-control, measured by the Self-Control Scale. Yan et al. frame this as consistent with existing research on internet and social media addiction, and it tracks with what Shaw and Nave (2026) have described as cognitive surrender, the gradual yielding of self-regulated thinking to external stimulation. The difference is that Yan et al. are showing this at the neurological level, not just the behavioral one.
Limitations
Here are few limitations I noted. Let’s start with the sample used in this research. The sample was 48 participants, mostly young female university students at a single Chinese university. That’s a narrow demographic window. We don’t know if the same patterns would appear in older adults, in people from different cultural media environments, or in populations with different baseline screen habits.
The study is also correlational, not causal. We can’t say short-form video caused the reduced theta activity; it’s possible that people with weaker executive control are simply more drawn to short-form video in the first place. The direction of the relationship remains an open question. Yan et al. call for longitudinal designs, larger and more diverse samples, and complementary neuroimaging (like fMRI) to build a fuller picture. Those are the right calls, and until that work is done, the findings here should be read as suggestive, not definitive.
Still, I don’t think the correlational design diminishes the core contribution. The EEG data adds a layer of evidence that behavioral measures alone can’t provide. And when you place this finding alongside what Fan et al. (2025) documented about metacognitive laziness in AI-assisted learning, a clear picture forms: repeated exposure to low-effort, high-stimulation digital experiences is training the brain to default to passive reception. The technology doesn’t have to be AI, specifically. Short-form video, algorithmic feeds, generative chatbots: they all share the same structural feature of delivering rich content with minimal cognitive investment from the user.
Yan et al. suggest mindfulness meditation as one potential intervention, pointing to prior research linking mindfulness practice to reduced addictive behaviors and improved self-control. It’s a reasonable suggestion, and the theoretical link between mindfulness and prefrontal cortex activation is well-documented. But I’d want to see that tested in a controlled experiment specifically targeting short-form video habits before treating it as a prescription.
What feels more actionable for us educators is the broader implication: the tools and platforms students use outside the classroom are reshaping how their brains allocate attention resources. And the most concerning part is that traditional performance measures won’t catch it until the erosion is already advanced.
This paper adds a neurological dimension to a conversation that has mostly lived in behavioral and self-report data. The brain is already changing before the grades drop, before the essays get worse, before the attention span visibly shortens. That’s the finding teachers should carry with them.
References
- Fan, Y., Tang, L., Le, H., Shen, K., Tan, S., Zhao, Y., Shen, Y., Li, X., & Gašević, D. (2025). Beware of metacognitive laziness: Effects of generative artificial intelligence on learning motivation, processes, and performance. British Journal of Educational Technology, 56(2), 489–530. https://doi.org/10.1111/bjet.13544
- Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), Article 6. https://doi.org/10.3390/soc15010006
- Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X.-H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your brain on ChatGPT: Accumulation of cognitive debt when using an AI assistant for essay writing tasks. MIT Media Lab. https://www.media.mit.edu/publications/your-brain-on-chatgpt/
- Shaw, S. D., & Nave, G. (2026). Thinking fast, slow, and artificial: How AI is reshaping human reasoning and the rise of cognitive surrender. Working paper, The Wharton School, University of Pennsylvania. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646
- Yan, T., Su, C., Xue, W., Hu, Y., & Zhou, H. (2024). Mobile phone short video use negatively impacts attention functions: An EEG study. Frontiers in Human Neuroscience, 18, 1383913.