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How does ‘not’ affect what we understand? Scientists find negation mitigates our interpretation of phrases

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How does ‘not’ affect what we understand? Scientists find negation mitigates our interpretation of phrases


When we’re told “This coffee is hot” upon being served a familiar caffeinated beverage at our local diner or cafe, the message is clear. But what about when we’re told “This coffee is not hot”? Does that mean we think it’s cold? Or room temperature? Or just warm?

A team of scientists has now identified how our brains work to process phrases that include negation (i.e., “not”), revealing that it mitigates rather than inverts meaning — in other words, in our minds, negation merely reduces the temperature of our coffee and does not make it “cold.”

“We now have a firmer sense of how negation operates as we try to make sense of the phrases we process,” explains Arianna Zuanazzi, a postdoctoral fellow in New York University’s Department of Psychology at the time of the study and the lead author of the paper, which appears in the journal PLOS Biology. “In identifying that negation serves as a mitigator of adjectives — ‘bad’ or ‘good,’ ‘sad’ or ‘happy,’ and ‘cold’ or ‘hot’ — we also have a better understanding of how the brain functions to interpret subtle changes in meaning.”

In an array of communications, ranging from advertising to legal filings, negation is often used intentionally to mask a clear understanding of a phrase. In addition, large language models in AI tools have difficulty interpreting passages containing negation. The researchers say that their results show how humans process such phrases while also potentially pointing to ways to understand and improve AI functionality.

While the ability of human language to generate novel or complex meanings through the combination of words has long been known, how this process occurs is not well understood.

To address this, Zuanazzi and her colleagues conducted a series of experiments to measure how participants interpreted phrases and also monitored participants’ brain activity during these tasks — in order to precisely gauge related neurological function.

In the experiments, participants read — on a computer monitor — adjective phrases with and without negation (e.g., “really not good” and “really really good”) and rated their meaning on a scale from 1 (“really really bad”) to 10 (“really really good”) using a mouse cursor. This scale was designed, in part, to determine if participants interpreted phrases with negation as the opposite of those without negation — in other words, did they interpret “really not good” as “bad” — or, instead, as something more measured?

Here, the researchers found that participants took longer to interpret phrases with negation than they did phrases without negation — indicating, not surprisingly given the greater complexity, that negation slows down our processing of meaning. In addition, drawing from how the participants moved their cursors, negated phrases were first interpreted as affirmative (i.e., “not hot” was initially interpreted as closer to “hot” than to “cold”), but later shifted to a mitigated meaning, suggesting that, for instance, “not hot” is not interpreted as either “hot” or “cold,” but, rather, as something between “hot” and “cold.”

The scientists also used magnetoencephalography (MEG) to measure the magnetic fields generated by the electrical activity of participants’ brains while they were performing these phrase-interpretation tasks. As with the behavioral experiments, neural representations of polar adjectives such as “cold” and “hot” were made more similar by negation, suggesting that the meaning of “not hot” is interpreted as “less hot” and the meaning of “not cold” as “less cold,” becoming less distinguishable. In sum, neural data matched what was observed for the mouse movements in the behavioral experiments: negation does not invert the meaning of “hot” to “cold,” but rather weakens or mitigates its representation along the semantic continuum between “cold” and “hot.”

“This research spotlights the complexity that goes into language comprehension, showing that this cognitive process goes above and beyond the sum of the processing of individual word meanings,” observes Zuanazzi, now at the Child Mind Institute.

The paper’s other authors were: Pablo Ripollés, an assistant professor in NYU’s Department of Psychology and associate director of Music and Audio Research Laboratory at NYU’s Steinhardt School of Culture, Education, and Human Development; Jean-Rémi King, a researcher at France’s École Normale Supérieure; Wy Ming Lin, a doctoral student at the University of Tübingen; Laura Gwilliams, an NYU doctoral student at the time of the study; and David Poeppel, a professor in NYU’s Department of Psychology and managing director of the Ernst Strüngmann Institute for Neuroscience in Frankfurt, Germany.

The research was supported by a grant from the National Science Foundation (2043717).



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Prying open the AI black box

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Prying open the AI black box


Artificial intelligence continues to squirm its way into many aspects of our lives. But what about biology, the study of life itself? AI can sift through hundreds of thousands of genome data points to identify potential new therapeutic targets. While these genomic insights may appear helpful, scientists aren’t sure how today’s AI models come to their conclusions in the first place. Now, a new system named SQUID arrives on the scene armed to pry open AI’s black box of murky internal logic.

SQUID, short for Surrogate Quantitative Interpretability for Deepnets, is a computational tool created by Cold Spring Harbor Laboratory (CSHL) scientists. It’s designed to help interpret how AI models analyze the genome. Compared with other analysis tools, SQUID is more consistent, reduces background noise, and can lead to more accurate predictions about the effects of genetic mutations.

How does it work so much better? The key, CSHL Assistant Professor Peter Koo says, lies in SQUID’s specialized training.

“The tools that people use to try to understand these models have been largely coming from other fields like computer vision or natural language processing. While they can be useful, they’re not optimal for genomics. What we did with SQUID was leverage decades of quantitative genetics knowledge to help us understand what these deep neural networks are learning,” explains Koo.

SQUID works by first generating a library of over 100,000 variant DNA sequences. It then analyzes the library of mutations and their effects using a program called MAVE-NN (Multiplex Assays of Variant Effects Neural Network). This tool allows scientists to perform thousands of virtual experiments simultaneously. In effect, they can “fish out” the algorithms behind a given AI’s most accurate predictions. Their computational “catch” could set the stage for experiments that are more grounded in reality.

“In silico [virtual] experiments are no replacement for actual laboratory experiments. Nevertheless, they can be very informative. They can help scientists form hypotheses for how a particular region of the genome works or how a mutation might have a clinically relevant effect,” explains CSHL Associate Professor Justin Kinney, a co-author of the study.

There are tons of AI models in the sea. More enter the waters each day. Koo, Kinney, and colleagues hope that SQUID will help scientists grab hold of those that best meet their specialized needs.

Though mapped, the human genome remains an incredibly challenging terrain. SQUID could help biologists navigate the field more effectively, bringing them closer to their findings’ true medical implications.



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Iron meteorites hint that our infant solar system was more doughnut than dartboard

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Iron meteorites hint that our infant solar system was more doughnut than dartboard


Four and a half billion years ago, our solar system was a cloud of gas and dust swirling around the sun, until gas began to condense and accrete along with dust to form asteroids and planets. What did this cosmic nursery, known as a protoplanetary disk, look like, and how was it structured? Astronomers can use telescopes to “see” protoplanetary disks far away from our much more mature solar system, but it is impossible to observe what ours might have looked like in its infancy — only an alien billions of light years away would be able to see it as it once was.

Fortunately, space has dropped a few clues — fragments of objects that formed early in solar system history and plunged through Earth’s atmosphere, called meteorites. The composition of meteorites tells stories of the solar system’s birth, but these stories often raise more questions than answers.

In a paper published in Proceedings of the National Academy of Sciences, a team of planetary scientists from UCLA and Johns Hopkins University Applied Physics Laboratory reports that refractory metals, which condense at high temperatures, such as iridium and platinum, were more abundant in meteorites formed in the outer disk, which was cold and far away from the sun. These metals should have formed close to the sun, where the temperature was much higher. Was there a pathway that moved these metals from the inner disk to the outer?

Most meteorites formed within the first few million years of solar system history. Some meteorites, called chondrites, are unmelted conglomerations of grains and dust left over from planet formation. Other meteorites experienced enough heat to melt while their parent asteroids were forming. When these asteroids melted, the silicate part and the metallic part separated due to their difference in density, similar to how water and oil don’t mix.

Today, most asteroids are located in a thick belt between Mars and Jupiter. Scientists think that Jupiter’s gravity disrupted the course of these asteroids, causing many of them to smash into each other and break apart. When pieces of these asteroids fall to Earth and are recovered, they are called meteorites.

Iron meteorites are from the metallic cores of the earliest asteroids, older than any other rocks or celestial objects in our solar system. The irons contain molybdenum isotopes that point toward many different locations across the protoplanetary disk in which these meteorites formed. That allows scientists to learn what the chemical composition of the disk was like in its infancy.

Previous research using the Atacama Large Millimeter/submillimeter Array in Chile has found many disks around other stars that resemble concentric rings, like a dartboard. The rings of these planetary disks, such as HL Tau, are separated by physical gaps, so this kind of disk could not provide a route to transport these refractory metals from the inner disk to the outer.

The new paper holds that our solar disk likely didn’t have a ring structure at the very beginning. Instead, our planetary disk looked more like a doughnut, and asteroids with metal grains rich in iridium and platinum metals migrated to the outer disk as it rapidly expanded.

But that confronted the researchers with another puzzle. After the disk expansion, gravity should have pulled these metals back into the sun. But that did not happen.

“Once Jupiter formed, it very likely opened a physical gap that trapped the iridium and platinum metals in the outer disk and prevented them from falling into the sun,” said first author Bidong Zhang, a UCLA planetary scientist. “These metals were later incorporated into asteroids that formed in the outer disk. This explains why meteorites formed in the outer disk — carbonaceous chondrites and carbonaceous-type iron meteorites — have much higher iridium and platinum contents than their inner-disk peers.”

Zhang and his collaborators previously used iron meteorites to reconstruct how water was distributed in the protoplanetary disk.

“Iron meteorites are hidden gems. The more we learn about iron meteorites, the more they unravel the mystery of our solar system’s birth,” Zhang said.



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Supermassive black hole appears to grow like a baby star

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Supermassive black hole appears to grow like a baby star


Supermassive black holes pose unanswered questions for astronomers around the world, not least “How do they grow so big?” Now, an international team of astronomers, including researchers from Chalmers University of Technology in Sweden, has discovered a powerful rotating, magnetic wind that they believe is helping a galaxy’s central supermassive black hole to grow. The swirling wind, revealed with the help of the ALMA telescope in nearby galaxy ESO320-G030, suggests that similar processes are involved both in black hole growth and the birth of stars.

Most galaxies, including our own Milky Way have a supermassive black hole at their centre. How these mind-bogglingly massive objects grow to weigh as much as millions or billions of stars is a long-standing question for astronomers.

In search of clues to this mystery, a team of scientists led by Mark Gorski (Northwestern University and Chalmers) and Susanne Aalto (Chalmers) chose to study the relatively nearby galaxy ESO320-G030, only 120 million light years distant. It’s a very active galaxy, forming stars ten times as fast as in our own galaxy.

“Since this galaxy is very luminous in the infrared, telescopes can resolve striking details in its centre. We wanted to measure light from molecules carried by winds from the galaxy’s core, hoping to trace how the winds are launched by a growing, or soon to be growing, supermassive black hole. By using ALMA, we were able to study light from behind thick layers of dust and gas,” says Susanne Aalto, Professor of Radio Astronomy at Chalmers University of Technology.

To zero in on dense gas from as close as possible to the central black hole, the scientists studied light from molecules of hydrogen cyanide (HCN). Thanks to ALMA’s ability to image fine details and trace movements in the gas — using the Doppler effect — they discovered patterns that suggest the presence of a magnetised, rotating wind.

While other winds and jets in the centre of galaxies push material away from the supermassive black hole, the newly discovered wind adds another process, that can instead feed the black hole and help it grow.

“We can see how the winds form a spiralling structure, billowing out from the galaxy’s centre. When we measured the rotation, mass, and velocity of the material flowing outwards, we were surprised to find that we could rule out many explanations for the power of the wind, star formation for example. Instead, the flow outwards may be powered by the inflow of gas and seems to be held together by magnetic fields,” says Susanne Aalto.

The scientists think that the rotating magnetic wind helps the black hole to grow.

Material travels around the black hole before it can fall in — like water around a drain. Matter that approaches the black hole collects in a chaotic, spinning disk. There, magnetic fields develop and get stronger. The magnetic fields help lift matter away from the galaxy, creating the spiralling wind. Losing matter to this wind also slows the spinning disk — that means that matter can flow more easily into the black hole, turning a trickle into a stream.

For Mark Gorski, the way this happens is strikingly reminiscent of a much smaller-scale environment in space: the swirls of gas and dust that lead up to the birth of new stars and planets.

“It is well-established that stars in the first stages of their evolution grow with the help of rotating winds — accelerated by magnetic fields, just like the wind in this galaxy. Our observations show that supermassive black holes and tiny stars can grow by similar processes, but on very different scales,” says Mark Gorski.

Could this discovery be a clue to solving the mystery of how supermassive black holes grow? In the future, Mark Gorski, Susanne Aalto and their colleagues want to study other galaxies which may harbour hidden spiralling outflows in their centres.

“Far from all questions about this process are answered. In our observations we see clear evidence of a rotating wind that helps regulate the growth of the galaxy’s central black hole. Now that we know what to look for, the next step is to find out how common a phenomenon this is. And if this is a stage which all galaxies with supermassive black holes go through, what happens to them next?,” asks Mark Gorski.



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