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Traditional brain scans only show part of the picture. They cant fully capture how different regions of the brain communicatean essential factor in detecting neurological diseases early. Dr. Rahul Biswas, a neurologist at the University of CaliforniaSan Francisco, is working to change that with AI-powered tools that map these hidden neural connections. His groundbreaking research reveals how Alzheimers disrupts brain communication in unexpected areas, challenging long-held assumptions about the disease. Now, through his company, Kaneva Consulting, Dr. Biswas is focused on transforming this science into practical diagnostic tools that can identify brain disorders long before symptoms emerge. Fast Company spoke with Biswas about how AI is revolutionizing brain health, from early disease detection to personalized treatments and everyday tech. The conversation has been edited for length and clarity. How are AI models revealing new insights about the brain that weren’t possible with traditional neuroscience methods? AI is giving us a radically clearer view of how the brain worksnot just where activity happens, but how regions interact, influence each other, and change over time. Traditional neuroscience often studied brain areas in isolation. But AI can analyze massive, complex data setslike full-brain recordings or scansand uncover subtle patterns across the whole system. For instance, it can detect a network of regions that consistently cooperate during memory formation, which might be overlooked in conventional analysis. In short, AI helps us move from snapshots to systems-level understanding, revealing hidden relationships and early warning signs of dysfunction. What are some of the most promising current applications of AI in brain health, like early detection of neurodegenerative diseases or personalized treatment strategies? One exciting use of AI is early detection of brain disorders. AI can sift through brain scans or even routine health records to spot subtle signs of disease long before symptoms show. For example, a machine learning system detected Alzheimers with over 90% accuracy on MRI scans, years earlier than traditional diagnosis. Catching such changes early means doctors can intervene sooner. Another promising area is personalized treatment. AI can help tailor therapy to each individuals brain. By analyzing a persons unique neural and genetic data, an algorithm might predict which depression medication will work best for them, reducing the usual trial-and-error in finding effective treatment. How would this brain monitoring work in practice for patients? Let’s take, for example, the brain network modeling approach. As part of their visit, a patient has an fMRI scan. And you directly feed it into the algorithm and get the network model. The beauty of this is you’re getting the brain network of the patient himself directly from his data. So you can see how the brain network is changing at every visit. Its personalized for that one patient. And over time you can really observe how the different network connections are changing. Are they getting closer to signatures of Alzheimer’s or other neurological diseases? Or are they doing fine? And if they are at the scale of any disease scenario it will be flagged. So just like if we take a blood test every visit and if the level of some parameter of the blood goes off the chart, you’ll see like a red mark out there saying “Hey, this is above the normal zone.” So something just like that can happen for brain networks, because networks are considered so good biomarkers for disease prediction. How might AI-driven predictive analytics and wearable technologies change the way we monitor and maintain brain health in daily life? AI plus wearable tech will make brain health monitoring continuous and proactive. Our smartphones and smartwatches already track sleep, heart rate, and movement. By adding AI analysis, these devices could also watch for subtle changes that signal cognitive decline or mental health issues. For example, an app might notice your typing speed has slowed or your sleep patterns have shifted and flag this as a possible early warning. Essentially, brain health checks would become a seamless part of daily lifea bit like a check engine light for your braininstead of something that only happens at the doctors office. How does your approach differ from traditional brain network analysis? Naive methods will say that, hey, two brain regions are correlated and so consider that as a connection. But perhaps those two brain regions were affected by a single parent brain region. A single brain region C was affecting both A and B together. So it just appeared that A and B are connected, but it was like a spurious connection. So causal methods try to be more specific. And they really try to say, “hey, brain regions A and B were not connected. It was brain region C which was directing influence on A and B at the same time.” You’re creating causal network models of the brain. What surprising discoveries has this approach uncovered about how information flows through neural circuits? By using causal models (which show who influences whom in the brain), we discovered some unexpected things about how signals move. In Alzheimers disease, for example, we saw a widespread communication breakdown across multiple regionsnot just the memory centers people expect. Connections through parts of the frontal and temporal lobes, and even the cerebellum, were significantly weaker in Alzheimers patients. This was surprising, since the cerebellum isnt typically linked to Alzheimers, and it suggests the disease disrupts broader networks than we realized. We also noticed the brain attempting to reroute signals when a main pathway weakened, hinting at a built-in resilience where secondary pathways try to pick up the slack. What are the practical implications of these discoveries now or in the near future? These findings have clear practical implications. Better diagnostics could be one: if we know a certain network typically weakens early in Alzheimers, doctors might use that as a biomarker. A brain scan could check the strength of that network in a person with mild symptoms to help diagnose or even predict the condition sooner. Another implication is targeted therapy. By pinpointing which brain hubs or pathways are breaking down, treatments can focus therefor example, a targeted brain stimulation or a cognitive exercise to strengthen a specific circuit. In short, understanding these causal networks lets us start addressing the root network disruptions, not just the surface symptoms. You’ve applied your brain network analysis to Alzheimer’s disease. What potential clinical impacts do you envision from this work in the next three to five years? In the next three to five years, I anticipate a few important clinical impacts: Brain network markers could be used to spot Alzheimers much sooner. An AI-analyzed scan might catch the diseases signature network disruption years before noticeable symptoms, enabling early intervention. Doctors may also monitor patients brain connectivity over time as a new vital sign. If a treatment is working, we would see the patients network decline slow or stabilize. That feedback could help adjust therapies promptly. Finally, theapies might be tailored to a persons specific network weaknesses. For example, if someones frontal network is most affected, doctors could focus medication or cognitive exercises on strengthening that regions function. This network-guided approach means more individualized and potentially effective care. Beyond medicine, how might your research on causal brain networks impact everyday technology we use? What we learn about the brains networks can directly inspire smarter everyday technology. One example is in AI software: by observing how patterns of influence between brain regions shift across different mental statessomething our causal network models help revealdevelopers can draw inspiration for digital assistants that better adapt to changing contexts or tasks, much like the brain does. Another area is brain-computer interfacestechnology that lets users control devices through neural signals. By understanding how brain regions causally influence one another during specific tasksinsights from our causal network modelsengineers can design more responsive interfaces that align with the brains natural information flow. In short, studying brain networks offers tech designers a blueprint for creating more brain-like, efficient, and user-friendly systems. What common misconceptions do people have about how the brain actually processes information, and how does your research address these? Many people think the brain works like a simple computer. Input goes in, processing happens in one place, and output comes out. But in reality, the brain is a dynamic web of interconnected regions constantly influencing one another. Our research shows that even a simple decision can involve multiple regions in complex causal chains. Its not about one brain area doing one thingit’s about networks adapting, rerouting, and interacting in context-dependent ways. How is AI enabling new kinds of scientific questions and research approaches in neuroscience that were previously impossible or impractical? With traditional tools, we were limited to studying local effectslike how one brain region responds to a stimulus. But AI lets us ask broader, system-level questions: How do signals propagate across the brain over time? How do networks reorganize in disease or under stress? These were hard to test before because of the data complexity, but now with AI, especially causal modeling and large-scale computation, we can track and test those dynamics with precision. If you could advise healthcare leaders or policymakers on one priority for ensuring AI delivers on its promise for brain health, what would it be? Build a strong foundation of data and validation. This means encouraging secure sharing of high-quality brain health data across institutions, so AI models can be trained on diverse, representative information. It also means requiring rigorous testing of AI toolslike clinical trials for algorithmsbefore theyre deployed in clinics. With richer data and strict validation, we can ensure that AI actually delivers safe, effective improvements in brain health, rather than just hype.
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Since the Trump administration first took office, the Department of Homeland Security (DHS) has followed a similar formula for most of its posts on X, which are typically celebrating mass deportations, using dehumanizing language like criminal illegal aliens, and defending Immigration and Customs Enforcement (ICE) raids. Recently, though, the account has taken a detour to post a different genre of content: aspirational pro-America artwork. On July 1, the DHS posted an image of a painting by the late Thomas Kinkade titled Morning Pledge, which shows a suburban neighborhood with a church and an American flag. Above it, the DHSs caption reads: Protect the Homeland. Then, on July 14, the DHS followed up with a piece by contemporary artist Morgan Weistling that depicted a family of early settlers in the American West. The painting, which shows two parents holding a newborn baby inside a covered wagon, is captioned: Remember your Homelands Heritage. New Life in a New Land Morgan Weistling. [Screenshot: DHS/X.com] Following the post, Weistling clarified that the DHS used his painting without permission, and that it invented an entirely new title for his work. But beyond ethical concerns about permission and copyright, the DHSs recent posts raise more pressing questions about what kind of America represents the organization’s concept of an ideal place to liveand who is included in that vision. Taken without permission After the DHS posted an image of his work, Weistling took to his official website, as well as to Facebook and Instagram, to set the record straight. (The Facebook and Instagram messages have since been deleted.) [Screenshot: Morgan Weistling/Facebook] So I was having a nice little vacation with my family when I get a message from a friend that the Department of Homeland Security has posted a painting of mine and its going viral, Weistling wrote on his Facebook page. As of this writing, the DHSs post has 19.1 million views and 34,000 likes. In a separate message on his website, Weistling added: They used a painting I did 5 years ago and re-titled it and posted it without my permission. It is a violation of my copyright on the painting. It was a surprise to me and I am trying to gather how this happened and what to do next. [Screenshot: morganweistling.com] According to Weistlings website, the painting used by the DHS is actually titled A Prayer for a New Liferather than the DHSs altered version of New Life in a New Land. This updated title, alongside the caption Remember your Homelands Heritage, places outsized emphasis on the land itself. Taken together with the paintings scene, the post seems to be skirting just around the edge of endorsing manifest destiny, or the assumption of American settlers inherent right to land in the West. Weistling did not immediately respond to Fast Companys request for a comment. A Manifest Destiny aesthetic Since the Trump administration took office in January, the DHS’s X account has become an active forum for the agency to promote President Trump’s mass deportation agenda. In early July alone, the DHS has already posted several images callously shrugging off the human suffering caused by the president’s deportation policies, which, most recently, include a new detention center for migrants built in the Florida Everglades. One repost from the White Houses official account shows a cup of coffee with the phrase Fire up the deportation planes added atop the liquid. Another image shows a border patrol vehicle in the desert, facing a distant sunset. The caption in neon green and white boasts: ZERO Releases in June. Lowest Month of Illegal Alien Encounters EVER. And a third, in a near-parody of this administrations extreme stance on immigration, shows a mock poster of the film E.T. the Extra Terrestrial with the text: Even E.T. knew when it was time to GO HOME. Take control of your departure using the CBP Home App. Between these posts are countless images of Black and brown people arrested by ICE for alleged crimes. The pivot to posting Kinkade’s and Weistlings works might be tonally jarring, but it’s indicative of the broader message the DHS account is trying to send. Weistlings body of work is almost entirely concerned with early American settlerspresenting an uncomplicated view of Americas origins, with scenes featuring a family happily riding west in a stagecoach or a rancher diligently tending his herd. Its a perspective that does not appear to include reference to Indigenous people. Meanwhile, Kinkade, who became notable for commercializing his work in the 80s and 90s, catered specifically to a Christian middle-class audience (a community that he was later criticized for allegedly exploiting). An entire section of his studios website is dedicated to Patriotic Art, the bulk of which highlights iconography like the American flag, the Statue of Liberty, and in one instance, Captain America. In Kinkades 2012 obituary in New York magazine, author Jerry Saltz wrote that the artist represented the epitome of sentimental, illustrational, conservative art. Both Weistling and Kinkade present an idyllic (and notably Eurocentric) portrayal of American societyone that, perhaps, evokes a fictional past thats implied by the phrase Make America Great Again. When the DHS urges its followers to Protect the Homeland, the question becomes: protect it for whom?
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E-Commerce
These specialty-made purses double as a mobile DJ kit. That’s because Nik Bentel Studio‘s newest purse, called the Tati Fte Bag, is actually wearable tech. The bag comes in two models: The $350 Speaker Bag, which pairs with bluetooth, and the $400 Mixer Bag, which has four input channels and is compatible with CD players, computers, phones, and amps. The bags started as a thought experiment, Nik Bentel tells Fast Company. “What if your everyday bag looked and felt like a piece of audio gear?” [Photos: Nik Bentel Studio] The resulting bags have room to hold your phone, chapstick, and mints, but they also have about three hours of play time each. Made from an acrylic shell, the material was chosen because it “allowed us to fully lean into the language of tech objects,” Bentel says. “It has this glossy, rigid, futuristic feel that instantly evokes gadgetry and display cases.” [Photo: Nik Bentel Studio] This is a purse meant to look like a gadget, not the other way around. “We wanted the bags to feel like they were pulled directly from a DJ booth,” Bentel says. Using fabric or leather would have softened the concept too much while acrylic gave the bags a “clean, synthetic, almost sci-fi finish.” The biggest challenges were precision, since acrylic has to be cut perfectly, and scale. [Photo: Nik Bentel Studio] “We wanted them to feel bold and graphic, but still functional as bags,” he says. “And of course, getting the buttons, knobs, and laser-etched details just right took a lot of back-and-forth to make sure they captured that playful realism.” Bentel has made clever, whimsical bags before like one made out of electrical cords and another for a single slice of pizza. The Tati Fte Bag brings that same sense of humor to sound. The rise of digital music and streaming has put a premium on physical music experiences like LPs and helped bring back the turntable. A boom box that’s a purse takes that impulse and makes it wearable.
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