Amazing Science

AI's remarkable abilities, like those seen in ChatGPT, often seem conscious due to their human-like interactions.

The question is whether the language model also perceives our text when we prompt it. Or is it just a zombie, working based on clever pattern-matching algorithms? Based on the text it generates, it is easy to be swayed that the system might be conscious. However, in this new research, Jaan Aru, Matthew Larkum and Mac Shine take a neuroscientific angle to answer this question.

All three being neuroscientists, these authors argue that although the responses of systems like ChatGPT seem conscious, they are most likely not. First, the inputs to language models lack the embodied, embedded information content characteristic of our sensory contact with the world around us. Secondly, the architectures of present-day AI algorithms are missing key features of the thalamocortical system that have been linked to conscious awareness in mammals. Finally, the evolutionary and developmental trajectories that led to the emergence of living conscious organisms arguably have no parallels in artificial systems as envisioned today.

The existence of living organisms depends on their actions and their survival is intricately linked to multi-level cellular, inter-cellular, and organismal processes culminating in agency and consciousness. Thus, while it is tempting to assume that ChatGPT and similar systems might be conscious, this would severely underestimate the complexity of the neural mechanisms that generate consciousness in our brains.

Researchers do not have a consensus on how consciousness rises in our brains. What we know, and what this new paper points out, is that the mechanisms are likely way more complex than the mechanisms underlying current language models. For instance, as pointed out in this work, real neurons are not akin neurons in artificial neural networks. Biological neurons are real physical entities, which can grow and change shape, whereas neurons in large language models are just meaningless pieces of code. We still have a long way to understand consciousness and, hence, a long way to conscious machines.

For the first time, scientists have demonstrated that the brain’s electrical activity can be decoded and used to reconstruct music. Artificial intelligence has turned the brain’s electrical signals into somewhat garbled classic rock"

"Neuroscientists have reconstructed recognizable audio of a 1979 Pink Floyd song by using machine learning to decode electrical activity in the brains of listeners. As study participants undergoing surgery listened to “Another Brick in the Wall (Part 1),” electrodes placed on the surface of the brain captured the activity of regions attuned to the song’s acoustic profile. "

Neuroscientists have worked for decades to decode what people are seeing, hearing or thinking from brain activity alone. In 2012 a team that included the new study’s senior author—cognitive neuroscientist Robert Knight of the University of California, Berkeley—became the first to successfully reconstruct audio recordings of words participants heard while wearing implanted electrodes. Others have since used similar techniques to reproduce recently viewed or imagined pictures from participants’ brain scans, including human faces and landscape photographs. But the recent PLOS Biology paper by Knight and his colleagues is the first to suggest that scientists can eavesdrop on the brain to synthesize music.

“These exciting findings build on previous work to reconstruct plain speech from brain activity,” says Shailee Jain, a neuroscientist at the University of California, San Francisco, who was not involved in the new study. “Now we’re able to really dig into the brain to unearth the sustenance of sound.”

To turn brain activity data into musical sound in the study, the researchers trained an artificial intelligence model to decipher data captured from thousands of electrodes that were attached to the participants as they listened to the Pink Floyd song while undergoing surgery. Why did the team choose Pink Floyd—and specifically “Another Brick in the Wall (Part 1),”? “The scientific reason, which we mention in the paper, is that the song is very layered. It brings in complex chords, different instruments and diverse rhythms that make it interesting to analyze,” says Ludovic Bellier, a cognitive neuroscientist and the study’s lead author. “The less scientific reason might be that we just really like Pink Floyd.”

A study of a lizard species in Arizona revealed that nearly 70 years' worth of climate-related extinction occurred in just seven years.

Researchers surveyed populations of the Yarrow’s spiny lizard in 18 mountain ranges in southeastern Arizona and analyzed the rate of climate-related extinction over time. “The magnitude of extinction we found over the past seven years was similar to that seen in other studies that spanned almost 70 years,” says John J. Wiens, a professor in the ecology and evolutionary biology department at the University of Arizona and senior author of the study in Ecology Letters.

The Yarrow’s spiny lizard native to the southwestern US and western Mexico can be spotted in oak and pine forests in 18 of Arizona’s Sky Islands mountain ranges. Wiens and his group did initial surveys of the Yarrow’s spiny lizard in these mountain ranges in 2014 and 2015.

In 2021 and 2022, Wiens, along with Kim Holzmann, his former master’s student and the new study’s lead author, and Ramona Walls, a part-time researcher at the University of Arizona’s BIO5 institute, resurveyed to investigate if there had been any changes in the lizard populations since then.

They found that about half of the lizard populations at lower elevations had disappeared. This is because temperatures are warmer at lower elevations, Wiens says, and the lizards at lower elevations were presumably not able to tolerate the increasing heat. This loss of low-elevation populations is a signature pattern of climate change, he says. “The rate of extinction in such a short time period was shocking,” Wiens says.

After comparing the findings to historical records from the same mountain ranges, Wiens’ group found that the average extinction rate of the lizard populations at low elevations had tripled over the past seven years, relative to the preceding 42 years. Although previous studies have predicted that climate-related extinctions will increase with the rising pace of global warming, Wiens says he hasn’t seen any showing that this acceleration of extinction has already happened.

Also, a distinct 3-million-year-old lineage of the Yarrow’s spiny lizard from the Mule Mountains, near Bisbee, may be completely extinct by 2025, Wiens says. “The low-elevation populations in the Mules were fine in 2014. Now the only ones that we have found left were within about 300 feet of the top of the mountain in 2022, and they appear to have been losing about 170 feet per year,” he says.

However, not all low-elevation populations went extinct between the surveys, Wiens says. For example, two populations that occurred at very low elevations survived. Before they disappeared, the research group had collected genomic data from most of those populations in 2014 and 2015. They found that those populations that were less genetically variable and were exposed to greater climate change effects were the ones that tended to go extinct. This suggests that the populations with less genetic variation had less ability to adapt to climate change.

Turn a radio telescope to the stars in the sky, and it's instantly deafened. From pulsars to radio galaxies, and ionospheric disturbances in the atmosphere to radio-frequency interference (RFI) from our own technology, the sky is a cacophony of radio noise. And somewhere, among all that, may lie a needle in a haystack: a signal from another world.

For over 60 years scientists have been scanning the skies in the search for extraterrestrial life but have yet to find any aliens. When you consider the sheer volume of search space — all those stars, all those radio frequencies — versus our limited searches so far, then it's little wonder we've not found ET yet. It's a daunting task, especially for a human. Thankfully, we've got some non-human intelligence to join the search.

The use of artificial intelligence (AI) is reaching critical mass, in our everyday lives and in science, so it is no surprise that it's now being employed in Search for Extraterrestrial Intelligence (SETI). AI is already helping astronomers make incredible discoveries. Here's how. We're not talking about Skynet, or the machines from The Matrix movies, or even Star Trek: The Next Generation's Data. The AI that is so in vogue at present is based on machine-learning algorithms designed to do very specific jobs, even if it's just to talk to you on ChatGPT.

To explain how AI is assisting in SETI, astronomer and SETI researcher Eamonn Kerins of the University of Manchester compares it to the needle in a haystack problem. "You basically treat the data as though it's the hay," Kerins told Space.com Space.com. "Then you're asking the machine-learning algorithm to tell you if there is anything in the data that isn't hay, and that hopefully is the needle in the haystack — unless there's other stuff in the haystack too."

That other stuff is usually RFI, but the machine-learning algorithm is trained to recognize all the types of RFI we already know about. Those signals — the familiar patterns of mobile phones, local radio transmitters, electronics and so on — are the hay. The training involves "injecting signals into the data and then the algorithm learns to look for signals that are like that," Steve Croft, an astronomer with the Breakthrough Listen SETI project at the University of California, Berkeley, told Space.com The algorithm learns to spot the patterns of these familiar signals and disregard them. Should it spot something in the data that it hasn't been trained on, then it flags this up as something interesting that requires a human to follow up on.

"There have been attempts recently at sifting through some of the Breakthrough Listen data with a machine-learning algorithm," said Kerins. "The data had already been combed through quite carefully previously by more conventional means, but yet the algorithm was still able to pick out new signals after being trained on the stuff that we know about."

This project was led by Croft and an undergraduate student, Peter Ma of the University of Toronto, who wrote the algorithm and put it to work analyzing data from 820 stars observed by the 100-meter radio telescope at Green Bank Observatory in West Virginia. The data, totaling 489 hours' worth of observations, contained millions of radio signals, almost all of which were human-made interference. The algorithm checked every single one of them and found eight signals that did not match anything it had been trained on and which had been missed by earlier analyses of the data.

In 1960, while preparing for the first meeting on the Search for Extraterrestrial Intelligence (SETI), legendary astronomer and SETI pioneer Dr. Frank Drake unveiled his probabilistic equation for estimating the number of possible civilizations in our galaxy—aka The Drake Equation. A key parameter in this equation was ne, the number of planets in our galaxy capable of supporting life—aka "habitable." At the time, astronomers were not yet certain other stars had systems of planets. But thanks to missions like Kepler, 5,523 exoplanets have been confirmed, and another 9,867 await confirmation.

Based on this data, astronomers have produced various estimates for the number of habitable planets in our galaxy—at least 100 billion, according to one estimate. In a recent study posted to the arXiv preprint server, Professor Piero Madau introduced a mathematical framework for calculating the population of habitable planets within 100 parsecs (326 light-years) of our sun.

Assuming Earth and the solar system are representative of the norm, Madau calculated that this volume of space could contain as much as 11,000 Earth-sized terrestrial (aka rocky) exoplanets that orbit within their stars' habitable zones (HZs).

Prof. Madau is a professor of astronomy and astrophysics at the University of California, Santa Cruz (UCSC). Central to his study is the Copernican Principle, named for famed Polish astronomer Nicolaus Copernicus, inventor of the heliocentric model. Also known as the Cosmological Principle (or Mediocrity Principle), the principle states that neither humans nor Earth are in a privileged position to observe the universe. In short, what we see when we look upon the solar system and out into the cosmos is representative of the whole.

For his study, Madau considered how time-dependent factors have played a vital role in the emergence of life in our universe. This includes the star formation history of our galaxy, the enrichment of the interstellar medium (ISM) by heavy elements (forged in the interior of the first population of stars), the formation of planets, and the distribution of water and organic molecules between planets.

As Madau explained to Universe Today, the central role of time and age are not explicitly stressed in the Drake Equation:

• "The Drake equation amounts to a useful pedagogical summary of the factors (probabilities) that may affect the likelihood of detecting life-bearing worlds—and eventually technologically advanced extraterrestrial civilizations—around us today. But that likelihood and those factors depend, among other quantities, on the star formation and chemical enrichment history of the local Galactic disk, as well as on the timeline of the emergence of simple microbial and eventually complex life."

COVID-19, the disease caused by SARS-CoV-2, has caused significant morbidity and mortality worldwide. The betacoronavirus continues to evolve with global health implications as we race to learn more to curb its transmission, evolution, and sequelae. The focus of this review, the second of a three-part series, is on the biological effects of the SARS-CoV-2 virus on post-acute disease in the context of tissue and organ adaptations and damage. We highlight the current knowledge and describe how virological, animal, and clinical studies have shed light on the mechanisms driving the varied clinical diagnoses and observations of COVID-19 patients. Moreover, we describe how investigations into SARS-CoV-2 effects have informed the understanding of viral pathogenesis and provide innovative pathways for future research on the mechanisms of viral diseases.

No one had ever seen one virus latching onto another virus, until anomalous sequencing results sent a UMBC team down a rabbit hole leading to a first-of-its-kind discovery. It's known that some viruses, called satellites, depend not only on their host organism to complete their life cycle, but also on another virus, known as a "helper," explains Ivan Erill, professor of biological sciences.

The satellite virus needs the helper either to build its capsid, a protective shell that encloses the virus's genetic material, or to help it replicate its DNA. These viral relationships require the satellite and the helper to be in proximity to each other at least temporarily, but there were no known cases of a satellite actually attaching itself to a helper—until now.

In a paper published in The ISME Journal, a UMBC team and colleagues from Washington University in St. Louis (WashU) describe the first observation of a satellite bacteriophage (a virus that infects bacterial cells) consistently attaching to a helper bacteriophage at its "neck"—where the capsid joins the tail of the virus. In detailed electron microscopy images taken by Tagide deCarvalho, assistant director of the College of Natural and Mathematical Sciences Core Facilities and first author on the new paper, 80 percent (40 out of 50) helpers had a satellite bound at the neck. Some of those that did not had remnant satellite tendrils present at the neck. Erill, senior author on the paper, describes them as appearing like "bite marks." "When I saw it, I was like, I can't believe this," deCarvalho says. "No one has ever seen a bacteriophage—or any other virus—attach to another virus."

A long-term virus relationship

After the initial observations, Elia Mascolo, a graduate student in Erill 's research group and co-first author on the paper, analyzed the genomes of the satellite, helper, and host, which revealed further clues about this never-before-seen viral relationship. Most satellite viruses contain a gene that allows them to integrate into the host cell's genetic material after they enter the cell. This allows the satellite to reproduce whenever a helper happens to enter the cell from then on. The host cell also copies the satellite's DNA along with its own when it divides. A bacteriophage sample from WashU also contained a helper and a satellite. The WashU satellite has a gene for integration and does not directly attach to its helper, similar to previously observed satellite-helper systems. However, the satellite in UMBC's sample, named MiniFlayer by the students who isolated it, is the first known case of a satellite with no gene for integration. Because it can't integrate into the host cell's DNA, it must be near its helper—named MindFlayer—every time it enters a host cell if it is going to survive. Given that, although the team did not directly prove this explanation, "attaching now made total sense," Erill says, "because otherwise, how are you going to guarantee that you are going to enter into the cell at the same time?" Additional bioinformatics analysis by Mascolo and Julia López-Pérez, another Ph.D. student working with Erill, revealed that MindFlayer and MiniFlayer have been co-evolving for a long time. "This satellite has been tuning in and optimizing its genome to be associated with the helper for, I would say, at least 100 million years," Erill says, which suggests there may be many more cases of this kind of relationship waiting to be discovered.

Research is published in ISME (October 31, 2023):

https://doi.org/10.1038/s41396-023-01548-0 

Genetic changes to avian influenza viruses have led to spread among many wild species, creating an uncontrollable global outbreak. Researchers studying the evolution of the bird flu virus over the past 18 years have shown how the strain currently circulating worldwide, an extremely deadly form of the H5N1 subtype, has become increasingly infectious to wild birds. The strain emerged in Europe in 2020, and has spread to an unprecedented number of countries. The study, published in Nature on the 18th October 2023 looked at changes to the virus’s genome over time and used data on reported outbreaks to track how it spread. In 2020, the rate of spread among wild birds was three times faster than that in farmed poultry, because of mutations that allowed the virus to adapt to diverse species. “What was once very clearly a poultry pathogen has now become an animal-health issue much more broadly,” says Andy Ramey, a wildlife geneticist at the US Geological Survey Alaska Science Center in Anchorage. “That has implications for wildlife and domestic poultry as well as us humans that rely upon these resources.”

Persistent outbreaks

H5N1, classified as a highly pathogenic avian influenza (HPAI) virus because of its high death toll in poultry, was first detected in birds in China in 1996. Outbreaks are usually seasonal, synchronizing with bird migration in Northern Hemisphere autumn. But since November 2021, they have become persistent. In 2022, the virus killed millions of birds across five continents and seeded outbreaks among farmed mink and various marine mammals. To study changes in the virus’s behaviour, the authors examined data reported to the Food and Agricultural Organization of the United Nations and the World Organisation for Animal Health between 2005 and 2022, and analysed more than 10,000 viral genomes. Their work reveals that in mid-2020, a new H5N1 strain evolved from an earlier variety, called H5N8, which first emerged in poultry in Egypt between 2016 and 2017 and caused global flare-ups throughout 2020 and 2021 (see ‘Bird flu outbreaks’). The new H5N1 virus mutated through interactions with non-deadly varieties of bird flu, called low-pathogenic avian influenza (LPAI) viruses, that had been circulating among wild birds in Europe since 2019. It developed two subtypes in 2021 and 2022. One spread across the northern coastal regions of central Europe and was eventually carried to North America by birds migrating across the Atlantic Ocean. The other was carried around the Mediterranean Sea and into Africa. Many bird flu outbreaks begin in poultry, but spillover into wild birds has spread the disease into larger areas, creating a global challenge that is difficult to manage, the study found. “Once it’s adapted to wild birds, we have no mechanism to control the virus. And I think that’s the biggest impact that has changed now,” says co-author Vijaykrishna Dhanasekaran, an evolutionary biologist and virologist at the University of Hong Kong. Louise Moncla, an evolutionary virologist at the University of Pennsylvania in Philadelphia, agrees. “Regardless of how much outbreak response you do in poultry, if it’s coming in from wild birds repeatedly, this is going to be really hard to manage.” “This is really something that most of the world at this point has skin in the game,” adds Ramey.

Mixing viruses

LPAI viruses often circulate freely in poultry and wild birds. Previous infection with these non-deadly strains is thought to encourage population immunity in wild birds. “You can think of it as an imperfect vaccine, that doesn’t stop infection, but it helps mitigate the effects of disease,” says Ramey. But “there’s probably two sides of the coin here”, he adds. HPAI viruses can mutate through interactions with LPAI ones. In both, the genome is split into eight segments that can be mixed and matched. “When two viruses co-infect the same cell, they could swap their genes when the virus is getting packaged,” says Dhanasekaran. Because of this, LPAI viruses — especially a strain called H9N2 — play a major part in the evolution of H5N1, he adds. But they are not well monitored. “Eradication or elimination strategies that target these low pathogenic viruses would be a huge step forward in terms of controlling avian influenza itself,” says Dhanasekaran.

Research Cited published in Nature (Oct. 18, 2023):

 https://doi.org/10.1038/s41586-023-06631-2 

Scientists have observed a rare quadruple star system in formation, revealing new insights into how multi-star systems form.

In a surprising find, the international ALMA Survey of Orion Planck Galactic Cold Clumps (ALMASOP) team recently observed a young quadruple star system within a star-forming region in the Orion constellation. The discovery was made during a high-resolution survey of 72 dense cores in the Orion Giant Molecular Clouds (GMCs) using the Atacama Large Millimeter/submillimeter Array (ALMA) in Chile. These observations provide a compelling explanation for the origins and formation mechanisms of binary and multiple-star systems.

It’s a well-known fact among astronomers and astrophysicists that roughly half of the stars in the Milky Way reside in binary systems. Knowing how multiple star systems form is essential to understanding galactic evolution, planetary formation, and the emergence of life. The most widely accepted theory regarding star formation (the Nebular Hypothesis) states that stars form in the densest regions of molecular clouds (aka. “dense core”). While this theory accounts for individual star systems very well, the mechanisms that drive the formation of multi-star systems are not yet well understood.

It is currently thought that multiple star systems form via the fragmentation of cloud cores during their early evolution, but observations are historically lacking. To investigate this mystery, the ALMASOP team examined 72 young and cold cores in the GMCs in the Orion constellation for thermal emissions corresponding to a wavelength of 1.3 mm – in the extremely high frequency (EHF) range. When observing a dense cold core in Orion B GMC about 1,500 light-years from Earth (designated G206.93-16.61E2), they observed a system of four stellar objects. These consisted of two protostars and two gas concentrations that are likely to undergo gravitational collapse in the near future. They further observed that the largest separation between the four objects in the system was about 1,000 Astronomical Units (AUs), over 33 times the distance between the Sun and Neptune (30 AUs). This stands in contrast to the last time a quadruple system was observed in 2015 by another international team using ALMA. In that case, the discovery team observed a young protostar and three gravitationally-bound dense gas clouds that would form new stars in ~40,000 years.