fMRI-Based Mega-Study of Psychedelics Reveals Patterns of Brain Signaling Reorganization

By Kyle Proffitt

Psychedelics are receiving increased attention for their potential to treat various mental health conditions. Just this week, an executive order was signed directing the United States FDA, DEA, and HHS to facilitate, fund, and fast track clinical research and review of psychedelics.  

Earlier this month, a new study, self-described as “the most comprehensive synthesis of psychedelic brain action to date,” appeared in Nature Medicine comparing the patterns of brain signaling elicited in hundreds of patients experiencing the effects of different psychedelics (DOI: 10.1038/s41591-026-04287-9). By using a unified processing platform and advanced statistical analysis, the researchers were able to identify both common elements of restructured brain connectivity as well as unique differences between the scope and scale of these changes among the different psychedelics. A “commonality across these drugs” was seen, such that “the usual hierarchy in the brain that separates abstract thinking from sense perception has been kind of collapsed,” explained first author Manesh Girn, who performed the research at the University of California, San Francisco. Beyond this overview, there was a lot of extra nuance.  

A Mega-Study 

Girn explained to Bio-IT World that the impetus for their study was the disjointed nature of brain imaging studies with psychedelics. Since 2012, the field has kind of blown up, he said, but many labs have performed independent studies with independent protocols. “When different groups get findings that seem to be inconsistent, it’s hard to know, is it the analysis that’s causing that, or is it actually the data?” he asked. Primarily led by Girn in combination with Danilo Bzdok, McGill University, Canada, and Emmanuel Stamatakis, University of Cambridge, an international consortium (27 authors) was created to share resting-state functional magnetic resonance imaging (fsMRI) data from individuals exposed to one of four different classic serotonergic psychedelics—psilocybin (the active component in “magic” mushrooms), lysergic acid diethylamide (LSD), dimethyltryptamine (DMT), or mescaline—or one natural mixture, ayahuasca, which contains both DMT and additional alkaloid compounds. The work included seven labs across five countries for a total of 11 datasets, spanning four drugs and over 250 people, Girn summarized.  

Raw data were procured, subjected to a unified processing platform to eliminate the variables in different labs’ processing, and then analyzed. The underlying data are rsfMRI brain scans, acquired at different centers, for different doses and different exposures, but all in acute phases of a psychedelic experience. The technique is blood-oxygen-level-dependent imaging, which differentially detects oxygenated and deoxygenated blood based on its magnetic properties. When neurons are firing, the immediate area becomes flooded with oxygenated blood a few seconds thereafter, and this signal is detected as a ratio change and considered an indicator of neuronal activity. Imaging data are collected over several minutes, and the processing pipeline specifically identifies correlations for this signaling both within and between different specific brain regions. The study designs all included placebo control measurements (most in a double-blind, randomized, controlled format), and therefore each measurement is a comparison of connectivity changes induced relative to placebo. In this way, the researchers could see if one or several psychedelics consistently altered correlated signaling between any two brain regions. 

Common Signatures 

After applying their unified processing pipeline, the researchers first computed means for drug-placebo comparisons. They analyzed the brain based on division into 17 pre-defined cortical regions (the wrinkled outer surface, having more to do with perception, complex reasoning, language, etc.), eight subcortical regions (more evolutionarily ancient, internal parts focused on movement, emotion, memory, reward, etc.), and the cerebellum, which is involved in fine-motor movement and more.  

Even averaged across all the psychedelics, a picture emerges of common connected areas that light up. For instance, enhanced coupling was seen between cortical visual networks and the subcortical putamen, a region associated with routine, habitual behavior. At the same time, averaged across treatments, within-network signaling correlation for several regions, such as the visual networks, decreased. In other words, the normally synchronized signaling that occurs within sub-regions of the visual networks and many other specific areas started marching out of step when taking psychedelic drugs. At a descriptive level, these results indicated that the psychedelics were eliciting some common brain reorganization, a change in the pattern of who’s talking to who, but greater detail was the goal. 

Bayesian Statistics Provide a Richer Picture 

Although averaging responses across all agents or within individual psychedelic treatments provided descriptive analyses, a primary focus of this report was measuring the statistical certainty of findings. For this, the group applied a Bayesian hierarchical modeling framework. This approach looks at each network pair, such as Default Network B (DN B)‒Visual Cortex A (VIS A), for example, and then calculates, per-drug, a probability distribution for that drug’s effect on this particular connection, weighting values with consideration of sample size and treatment sites. This changes the analysis from the typical p-value approach that asks if an increased connection exists to one that gives a “kind of graded sense of confidence in that effect,” Girn explained. Pooling the results from several sites and using this modeling technique can greatly reduce the confidence in results, if consistency exists across studies.  

The resulting plots contain bell-shaped curves for each treatment. In the DN B‒VIS A plot, for example, all four of the pure psychedelic compounds show curves indicating increased connectivity, because they are distributed to the right of zero. The width and height of these curves reflect the certainty based on the distribution of results. Both in this inter-network connection and as a general rule, the curves for psilocybin and LSD are narrow and tall, indicating greater certainty, whereas those of DMT and mescaline are often of similar magnitude, but with wider, flatter distributions, and thus decreased certainty. The authors state this is largely a reflection of larger sample sizes for LSD and psilocybin. Ayahausca appeared more idiosyncratic and showed the widest probability distributions, related both to sample size and the inherent mixture of compounds. “The strong convergence between LSD and psilocybin is a bit surprising,” Girn said. “You expect more differences … because LSD has a more complex pharmacology and hits more dopamine receptors, for example.” 

Girn explained that in general, across all of the drugs, there was “increasing connectivity between what we would call high-level association areas, networks such as the default mode network … which are involved in more abstract cognition, remembering past experiences, language, conceptual thinking, our internal narrative, sense of self … those parts of the brain were becoming more connected to what we call low-level sensory cortex [regions]: visual, somatomotor, and auditory.” He said that increased sharing between perceptual networks and high-level networks can explain feelings induced by psychedelics such as greater connection to our environment, the blurred distinction between inner and outer experience, and ego dissolution. The article also describes these changes as a “hierarchical flattening.” Sensorimotor signaling (unimodal) typically has to transit heteromodal networks to reach the abstract cognitive processing (transmodal) networks such as the default mode network Girn highlighted, but when these hierarchical barriers come down, the systems gain direct communication. 

Nuance and Paradigm Adjustment 

Girn explained how their study both confirmed some prior findings and provided some extra color and detail. “A common narrative or finding that’s been claimed in past studies is that the individual networks of the brain become disintegrated under psychedelics, including the default mode network,” he said. “That’s a big story, you know, default mode network disintegration.”  

The Bayesian analysis of within-network signaling showed similar results to global averaging, but with more detail and quantification to challenge this paradigm. All five treatments showed decreased within-network VIS B synchrony, for instance, but again, the confidence in this effect was highest for LSD and psilocybin. Taken together, “we found that actually these network disintegration effects were not very reliable across drugs … that particular claim has been possibly overstated, and it’s more complex and nuanced than that,” Girn explained. 

As a summary of the increased connectivity, Girn said that “we expanded past findings to show more nuance in the specific regions that connect with others and suggest that it isn’t just that the whole brain is becoming interconnected … it’s very nuanced and there are specific patterns that we uncover.” 

Psychedelics Are for More than Trips 

At one level, scientists just want to understand what’s happening in the brain during these hallucinogenic experiences. All of the agents in this study primarily target the serotonin 2A (5-HT2A) receptor. “If you block that receptor, people don’t really trip, you don’t see the brain effects,” Girn said, but there’s diversity when it comes to relative interactions with dopamine receptors or the serotonin 1A receptor. Psychedelics are also being explored increasingly in the mainstream for conditions such as depression, anxiety, substance abuse disorders, or even the avoidance of aging, and these imaging efforts may be beneficial in understanding how brain signaling reorganization influences efficacy. 

“Decreased brain modularity, which means the brain is more interconnected as a whole, has been linked to positive outcomes in two different depression trials,” Girn said. The more this interconnection persists, the better the outcomes, he explained. So these maps of brain reorganization may provide a useful framework for monitoring the persistence of changes. It is worth noting that this study is based on healthy volunteers, typically those who are not naïve to psychedelics. Additional complexity may exist in the effects of these agents on the brain of someone experiencing depression or other conditions and first-time users, and future studies would be required to probe this further. 

As a different direction, Girn is now co-founder and CEO of Five Discovery, a company seeking to treat neurological diseases such as Parkinson’s and Alzheimer’s, and even traumatic brain injury. Girn says this was born from the realization that psychedelics also have meaningful effects on brain plasticity and inflammation. To this end, they are designing molecules based on 5-MeO-DMT, an even more potent 5-HT2A agonist; however, they are designing variants that are more gentle stimulants, with the goal of producing anti-inflammatory, pro-plasticity effects while skipping the journey. “They still stimulate serotonin-2A, just not enough to make people trip,” Girn said.  

What’s Next 

“There’s a lot more nuance to be figured out,” Girn said, indicating it is early days. One avenue involves moving away from the averages. Each individual scan result is itself an average over 10 minutes of scanning, he explained. “What about all the dynamics?” Additionally, he’s interested in the inter-individual differences that will be important to understand when looking toward therapeutic intervention. “There are studies ongoing now with the same large-scale dataset; we’re looking more at individual variability and then that will better inform potential treatment allocation, predictive biomarkers, etc.” Girn said.