The study underscores the necessity of large, collaborative data to advance psychedelic science beyond small, inconsistent studies and improve interpretation of results.

Subcortical regions tied to perception, motivation, and reward showed altered activity, indicating widespread brain changes beyond localized effects.

A large international meta-analysis across five psychedelics—psilocybin, LSD, mescaline, DMT, and ayahuasca—found a common brain activity signature, a shared neural fingerprint, despite their different chemical structures.

The work suggests psychedelics reconfigure large-scale brain network interactions rather than simply dissolving neural connections, challenging existing theories of how these drugs alter consciousness.

Psychedelics increase cross-talk between brain regions, enhancing connectivity among high-level cognitive networks and sensory processing networks.

Lead researcher Dr. Danilo Bzdok emphasizes the common effects across the drugs and the need to establish reliable foundations for future clinical use.

Despite variability, there is substantial overlap in how psychedelics alter brain network communication, notably increasing cross-talk between high-level networks and those involved in vision and sensation.

Clinical implications point to informing future drug design and mental health applications for depression, anxiety, and addiction by understanding shared brain mechanisms across psychedelics.

Deeper brain regions involved in habits, learning, and movement also showed changes, with little reliable evidence that specific networks disintegrate under psychedelics.

Findings suggest psychedelics flatten the brain's hierarchical organization by promoting widespread cross-network communication, potentially underpinning experiences of expanded consciousness.

The findings contribute to the revival of psychedelic research by providing a clearer, quantifiable denominator across drugs, which could help justify regulatory loosening as evidence builds.

Researchers developed methods to combine scans and analyze time-varying activity to understand how network interactions unfold during psychedelic experiences.