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Your Brain on Mushrooms: Study Reveals What Psilocybin Does to the Brain—and for How Long
Magic mushrooms have recently had a reputation revamp. Often considered a hippie drug, their main active component, psilocybin, is being tested in a variety of clinical trials as a therapy for the likes of depression and post-traumatic stress, bipolar, and eating disorders.
Psilocybin joins ketamine, LSD (commonly known as acid), and MDMA (often called ecstasy or molly) as part of the psychedelic therapy renaissance. But the field has had some ups and downs.
In 2019, the FDA approved a type of ketamine for severe depression that was resistant to other therapies. Then in early June, the agency rejected MDMA therapy for post-traumatic stress disorder, although it has been approved for limited use in Australia. Meanwhile, healthcare practitioners in Oregon are already using psilocybin, in combination with counseling, to treat depression, although the drug hasn’t yet been federally approved.
Despite its potential, no one knows how psilocybin works in the brain, especially over longer durations.
Now, a team from Washington University School of Medicine has comprehensively documented brain-wide changes before, during, and after a single dose of psilocybin over a period of weeks. As a control, the volunteers also took Ritalin, a stimulant, at a different time to mimic parts of the psilocybin high.
An fMRI scan shows the effect of psilocybin on the brain. Yellows, oranges, and reds indicate an increasingly large departure from normal activity. Image Credit: Sara Moser/Washington UniversityIn the study, psilocybin dramatically reset brain networks that hum along during active rest—say, while daydreaming or spacing out. These networks control our sense of self, time, and space. Although most effects were temporary, one connection showed changes for weeks.
In some participants, the alterations were so drastic that their brain connections resembled those of completely different people.
Normally, the brain synchronizes activity across regions. Psilocybin disrupts these connections, in turn making the brain more malleable and ready to form new networks.
This could be how magic mushrooms “contribute to persistent changes…in brain regions that are responsible for controlling a person’s sense of self, emotion, and life-narrative,” wrote Petros Petridis at the NYU Langone Center for Psychedelic Medicine, who was not involved in the study.
Magical Mystery TourThe brain’s 100 billion neurons and trillions of connections are highly organized into local and brain-wide networks.
Local networks tackle immediate tasks such as processing vision, sound, or motor functions. Brain-wide networks integrate information from local networks to coordinate more complex tasks, such as decision-making, reasoning, or self-reflection.
Previous psilocybin studies mainly focused on local networks. In rodents, for example, the drug regrew neural connections that often wither away in people with severe depression. Scientists have also pinpointed a receptor—which psilocybin grabs onto—that triggers this growth.
But psilocybin’s effects on the whole human brain remained a mystery.
Several years back, one team sought an answer by giving people with severe depression a dose of psilocybin. Using functional MRI (fMRI), a type of imaging that captures brain activity based on changes in blood flow, they found the chemical desynchronized neural networks across the entire brain, essentially “rebooting” them out of a depressive state.
Daydream BelieverThe new study used fMRI to track brain activity in seven adults without mental health struggles before, during, and for three weeks after they took psilocybin. The researchers gave participants a single dose on par with that commonly used in clinical trials for depression.
During the scans, the participants had two tasks. One sounds easy: They kept still and focused their gaze on white crosshairs on a computer screen, but remained otherwise relatively relaxed. Even so, tripping on mushrooms inside a noisy, claustrophobic machine is hardly relaxing—heart rate skyrockets, nerves are on high alert, and anxiety rapidly builds. To control for these side effects, the participants also took Ritalin—a stimulant commonly used to manage attention deficit hyperactivity disorder—at another point in time during the study.
The other task required more brain power. Like an audio version of a CAPTCHA, the researchers asked volunteers to match an image and a word prompt—for example, they’d have to pick a photo of a beach after hearing the word “beach.”
Throughout the study, each person had their brains scanned roughly every other day, on average totaling 18 scans.
Mapping brain connections over time in the same person can “minimize the effects of individual differences in brain networks organization,” wrote Petridis.
The study found psilocybin immediately desynchronized a brain-wide network, generating a brain activation “fingerprint” of sorts that differentiates it from a sober brain.
Dubbed the default mode network, this neural system is active when the mind is alert but wanders, like when reliving previous memories or imagining future scenarios. The network is distributed across the brain and is often studied for its role in consciousness and a sense of self. The chemical also desynchronized local networks across the cortex, the outermost layer of the brain that supports perception, reasoning, and decision-making.
However, the chemical partially lost its magic when the volunteers were focused on the image-audio task, at which point the scans showed less disruption to the default mode network.
This has implications for psilocybin-assisted treatment. Clinical studies have shown that during psychedelic therapy, a challenging experience—a bad trip—can be overcome by a method called “grounding,” which reconnects the person to the outside world.
These results could explain why adding eye masks and ear plugs can enhance the therapeutic experience by blocking outside stimulation, while grounding pulls one out of a bad trip.
Psilocybin’s effects lingered for a few days, after which most brain networks returned to normal—with one exception. A link between the default mode network and a part of the brain involved in creating memories, emotions, and a sense of time, space, and self was disrupted for weeks.
In a way, psilocybin opens a window during which neural connections become more malleable and easier to rewire. People with depression or post-traumatic stress disorder often have a rigid and maladaptive thought pattern that’s hard to shake off. With therapy, psilocybin allows the brain to reorganize those networks, potentially helping people with depression to escape negative ruminations or for people suffering from addiction to consider a new perspective on their relationship to substances.
“In other words, psilocybin could open the door to change, allowing the therapist to lead the patient through,” wrote Petridis.
Although the study offered a higher resolution image of the brain on mushrooms over a longer timeframe than ever before, it only captured scans of seven people. As the participants did not have mental health issues, their responses to psilocybin may differ from those most likely to benefit therapeutically.
Ultimately, larger studies in diverse patient populations—as in several recent MDMA trials—could offer more insights into the efficacy of psilocybin therapy. For example, the one persistent brain network disruption could be an indicator of treatment efficacy. Investigating whether other psychedelics alter the same neural connection is a worthy next step, wrote Petridis.
With the field of psychedelic therapy projected to reach over $10 billion by 2027, understanding how the drug affects the brain could bring new medications with fewer side effects.
Image Credit: Sara Moser/Washington University
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Apple Intelligence doesn’t use YouTube, but does it matter?
Apple has confirmed recent claims that it might have used subtitle data from YouTube videos to train one of its artificial intelligence (AI) tools, but says the tool is not used in Apple Intelligence.
Apple confirmed a report from Proofnews that it had used this YouTube data to train one of its models. The company explained that it did so to train the open-source OpenELM models released earlier this year. The information was included within a larger collection maintained by the EleutherAI non-profit company that supports AI research.
Apple used YouTube once, but not nowHowever, Apple told 9to5Mac that models trained using that information don’t power any of its own AI or machine learning tools, including Apple Intelligence. This was a research project originally created by Apple’s AI teams and then shared, including via the company’s own Machine Learning Research site.
What’s important is that it shows the extent to which Apple wants to be seen as keeping its promise that Apple Intelligence models are trained on licensed data.
But that’s not the big picture. As mentioned earlier in the week, Apple Intelligence does also train its models using “publicly available data collected by our web-crawler.”That admission reflects the extent to which tech companies are using information published online to create new AI products from which they subsequently profit.
Making public data privateThe issue is that by turning other people’s creative works into data, and then profiting from that data, tech firms aren’t playing fair.
Speaking to Proofnews, Dave Farina, the host of “Professor Dave Explains,” put it this way: “If you’re profiting off of work that I’ve done [to build a product] that will put me out of work or people like me out of work, then there needs to be a conversation on the table about compensation or some kind of regulation.”
To some extent, the focus on YouTube data distracts from that critical argument, which is that the generative AI (genAI) tools coming into common use today are likely to have been trained by information created by humans and shared online. That’s the kind of information picked up by webcrawlers, including Apple’s.
But data quality is a real issue here, and the search for the best data inherently means that the best data sources are the highest octane of fuels to power training AI.
The drive for quality means content is kingConsider just two of the challenges AI researchers face.
- Automated data grading systems might reject old, out-of-date, or false information, but some still gets through, which is why AI systems so often develop hallucinations (the current descriptor for fake information) or exhibit questionable morality (racist or gender-biased language).
- Data also has a finite lifespan. Facts can and do change over time, and maintaining high-quality data is an essential bulwark against the classic “garbage out” generated by irrelevant information, or high-grade information that becomes irrelevant over time.
What this means is that in their quest for high-quality information, AI companies inevitably seek high-quality data sources. When you translate that into activity picked up from the open public web, that in itself implies that creatives currently battling against tech firms for compensation for use of their material in training AI systems have a good point.
Because the best and most current information they create is worth something, both to the creators, those who consume it, and also to the people who own and train the machines that harvest their data from it. Indeed, given that AI by its nature becomes a tool directly available to everyone and across every supported language, it seems plausible to think the value of that information might actually grow once it is used to train an AI model.
So, while Apple might not be using YouTube data for its Apple Intelligence models, it will be using other data curated across the public web. And while Apple might at least try to avoid using data it should not exploit this way — and is honest enough to have responded to the current YouTube controversy — not every AI firm does the same. And once the machine is trained it cannot be untrained.
Please follow me on Mastodon, or join me in the AppleHolic’s bar & grill and Apple Discussions groups on MeWe.
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