Testing If Brain Rot ACTUALLY Rots Your Brain

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Here are the full results of the experiment: https://docs.google.com/presentation/d/1oKu2vbz2JGxg-3NAz5qkozeV5Xwsc8skR3Hmz5PDDE8/edit?usp=sharing

SCIENTIFIC DISCLAIMER
The Institute for Advanced Consciousness Studies (IACS) acknowledges that this content is primarily for entertainment purposes, though the preliminary findings may warrant future investigation. While we're excited to support content creators raising awareness about technology's potential impact on cognitive function, this study has significant limitations:

Key Limitations:

Study Design Issues: "Brainrot" was poorly defined, making group analyses potentially invalid due to numerous confounding variables. The screen time measurements were inconsistent—we distinguished between general screen time and social media time, yet excluded YouTube from social media despite YouTube Shorts being as likely to encourage doomscrolling as TikTok or Instagram. We failed to account for Netflix/TV consumption, reading habits, education levels, or mind-body/exercise practices—all critical variables needed to isolate our variable of interest.

Methodological Constraints: Our EEG metrics were overly simplified, using only univariate measures instead of connectivity or multivariate analyses. We didn't account for neurodiversity, failed to include proper rest period comparisons, and didn't consider participants' motivation levels or how much they cared about task performance. Since "brainrot" typically involves visual content, visual attention may actually be preserved or enhanced, making our tasks potentially insensitive to detecting the intended effects.

Technical and Statistical Limitations: We didn't perform proper motion artifact removal from EEG data or follow standard academic preprocessing protocols. The study was statistically underpowered to detect effects even if present, and suffered from selection bias in participant recruitment. As the saying goes, "if the brain were simple enough to understand, we would be too simple to understand it" (attributed to Lyall Watson).

Research Team Credits:

Research Assistants: Ninette Simonian, Mari Shahmanyan, Katara Dakota, Ressan Eyngel Quinto
Task Design: Mari Shahmanyan
Visualization: Intheon's Neuropype software (Sean Mullen)
EEG Analysis: Ben Zhang
Research Director: Nicco Reggente, Ph.D.
For scientific inquiries or collaboration opportunities, contact: [email protected]

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Produced by: Isabella Dake
Edited by: Brandon Voloch and Jack Gordon
Music by: Extreme Music, Jack Gordon, Artlist and Epidemic Sound
Assistant edited by: Jorge Moratal