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Breaking connections helps ideas spread farther, says physics-based study

Sticking with the same people might feel safe and comfortable. But a new Northwestern University study suggests it can actually trap new ideas and behaviors inside tight echo chambers. By contrast, the research, published in Communications Physics, shows that when interactions shift away from familiar contacts—and toward new ones—activity can spread more widely.

To explore how activities spread across networks, physicists developed a new theoretical framework that includes simple “learning” rules. While traditional network models assume relationships do not change, the new model shows what happens when connections change with experience. As interactions strengthen or weaken relationships, they gradually reshape the entire network.

The findings apply not only to ideas moving through social networks but to a wide range of systems where activity spreads, including infections passing among people, signals traveling through the brain and behaviors proliferating through groups of animals. Ultimately, the study suggests that whether something spreads or stalls may hinge on a simple choice: revisit the same connections or explore new ones.

Children may be born with two complex cognitive functions already established, research reveals

A new study is the first to show that two of our most sophisticated cognitive functions, using and understanding language and being able to sense how other people feel, have distinct origins in the brain in young children—matching what we know about the adult brain.

The findings suggest that these separate but related ways of processing complex concepts, both uniquely human skills, do not originate from overlapping brain areas and grow more distinct as the mind matures, which challenges prior theories. Instead, our brains appear to have evolved with discrete architecture and wiring enabling these different kinds of thinking.

Self-organizing ‘pencil beam’ laser could help scientists design brain-targeted therapies

MIT researchers discovered a paradoxical phenomenon in optical physics that could enable a new bioimaging method that’s faster and higher-resolution than existing technology. They discovered that, under the right conditions, a chaotic mess of laser light can spontaneously self-organize into a highly focused “pencil beam.”

Using this self-organized pencil beam, the researchers captured 3D images of the human blood-brain barrier 25 times faster than the gold-standard method, while maintaining comparable resolution. By showing individual cells absorbing drugs in real-time, this technology could help scientists test whether new drugs for neurodegenerative diseases like Alzheimer’s or ALS reach their targets in the brain, with greater speed and resolution.

“The common belief in the field is that if you crank up the power in this type of laser, the light will inevitably become chaotic. But we proved that this is not the case. We followed the evidence, embraced the uncertainty, and found a way to let the light organize itself into a novel solution for bioimaging,” says Sixian You, assistant professor in the MIT Department of Electrical Engineering and Computer Science (EECS), a member of the Research Laboratory for Electronics, and senior author of a paper on this imaging technique.

New neuroscience research shows how slowing your breathing alters your perception of the people around you

New brain imaging reveals that taking slow, deliberate breaths alters how accurately you recognize human emotions. The phase of your breath actually rewires the brain networks responsible for visual perception and passing judgment.

New psychology research reveals your face might determine how easily people remember your name

Have you ever struggled to remember the name of someone you just met? A recent study published in the Journal of Experimental Psychology: Learning, Memory, and Cognition suggests that the natural stickiness of a person’s face plays a key role in whether you will recall their name. The findings indicate that highly memorable faces help people remember associated names, but this memory-boosting effect does not happen when names are paired with memorable photographs of places.

For decades, scientists studying human memory have focused on how the mental effort we spend processing a fact determines how well we will retain it. However, memory also depends on natural qualities belonging to the object or event itself. Some items possess an intrinsic memorability, meaning they tend to be consistently remembered better by different people regardless of how much effort is put into learning them.

“I was fascinated by the idea that some things in our environment are naturally more memorable than others, meaning most people will remember or forget the same images regardless of their individual memory skills,” explained Andrew Cook, a visiting assistant professor of psychology at Hamilton College. Cook and his colleagues designed a series of experiments to test whether seeing a memorable image would provide evidence for enhanced recall of an associated name. “We wanted to know if memorability is ‘sticky,’” Cook said.

Bing Brunton on Connecting the Connectome to the Body | Mindscape 352

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Blog post with audio player, show notes, and transcript: https://www.preposterousuniverse.com/.

The connectome is the wiring diagram of a brain, a big matrix that tells us what neurons talk to what other neurons. Understanding it is an important step to understanding how brains work, but a long way from the final answer. A big next step is understanding how neuronal circuits connect to and guide bodily behavior. Very recent work on mapping the fruit-fly connectome has brought us closer to that goal. I talk with neuroscientist Bing Brunton about the connectome, how we can study it to understand bodily motion in flies and other creatures, and where it’s all taking us.

Bing Wen Brunton received her Ph.D. in neuroscience from Princeton University… She is currently a Professor of Biology and the Richard & Joan Komen University Chair at the University of Washington, with affiliations at the eScience Institute for Data Science, the Paul G. Allen School of Computer Science & Engineering, and the Department of Applied Mathematics.

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