By Rivka Galchen During his first year as a professor of computer science at the University of California, Berkeley, Ren Ng was hurriedly putting together a survey course on computer graphics. In the syllabus he had inherited, a full week had been devoted to the subject of color. Ng thought that was a bit much. “I’m, like, Come on. It’s R.G.B.,” he said, referring to the red, green, and blue subpixels that constitute anything you see on a screen—your cluttered desktop, a Sahara-desert screen saver, the stream of the Netherlands-Japan World Cup game. Ng started gathering slides that would cover the wavelengths of light, the biology of the human eye—the basics—“Blah, blah, blah,” he said. A colleague shared a slide that he thought might be useful. It included a minutely detailed photograph of a patch of retina, seen through a microscope, which was attributed to Austin Roorda, a professor of vision science and optometry just across campus. Roorda’s lab had helped develop technology that could map the layout of individual cone cells—those primarily responsible for perceiving color—and that, furthermore, could target a single cone cell with light. Eyes are constantly moving; cone cells are extremely small; how color is translated from the millions of cone cells to the mind remains pretty mysterious; this was awesome work. Roorda’s lab was using the new technology to explore eye disease and the mechanics of how we see. Ng had his own notion, though: he wondered if it could be used to see a color that had never been seen before. To understand what Ng had in mind requires knowing a bit of the blah, blah, blah of color vision. We humans experience three primary colors not because the world is fundamentally composed of three colors but because our retinas typically have three kinds of color-perceiving cone cells. L cone cells respond to the relatively longer wavelengths of visible light, M cone cells to the medium wavelengths, and S cone cells to the shorter ones. In effect, this means that L cells respond most strongly to red light, M to green, and S to blue. But when you look at your hand—or a blade of grass, or a clear blue sky, or a fire truck—it is always some mixture of L, M, and S cone cells that are being stimulated. Ng’s idea was to use the Roorda lab’s technology to stimulate an array of cone cells in a manner that would never occur naturally. Ng said, “I e-mailed him, basically, What would happen if you stimulated only the M cells? Would that be like the greenest green, or what?” Roorda did not reply. © 2026 Condé Nast.

Keyword: Vision
Link ID: 30354 - Posted: 08.01.2026

By Emily Laber-Warren When sunlight hits an octopus, it can trigger a swift color change and instant camouflage, thanks to light-sensitive molecules embedded in the creature’s skin. When sunlight falls on a bird’s skull, similar compounds deep in the animal’s brain register changes in day length and help drive decisions on when to mate or migrate. Photosensitive proteins called opsins that respond instantly to sunlight can be found within and outside the eye in nearly every animal, and they govern not only vision but also a range of behaviors. Until about a quarter-century ago, though, the scientific consensus was that in humans, the only role for opsins was to help us see. But a surge of research over the past couple of decades has increasingly revealed that, like honeybees, zebra fish, rodents and other creatures, we harbor opsins that aren’t involved in vision, both in our eyes and throughout our bodies. These molecules appear to play a broad role in human biology, affecting mood, metabolism, sleep, thinking and social behavior. Since life’s beginnings, organisms on this sunbaked planet have had to evolve ways to protect against ultraviolet light, which can damage DNA. But it shouldn’t be surprising that, as dangerous as sunlight can be, most animals also rely on it to regulate key aspects of physiology, including body temperature, navigation, growth and sexual development. Across the animal kingdom, researchers are discovering that light-sensing opsins are involved in an array of biological processes beyond vision. These include camouflage; sensing seasonal changes via lengthening or shortening day lengths; synchronizing with the 24-hour cycle — as well as mood, healing and more.

Keyword: Vision; Biological Rhythms
Link ID: 30347 - Posted: 07.29.2026

By K. R. Callaway You (probably) won’t find a monkey in a geometry class, but it looks like our fellow primates can swing the basics. Just like people, monkeys seem to grasp the abstract qualities of geometric shapes, such as whether they are symmetrical, have parallel sides or contain right angles, according to a new study published on Monday in Proceedings of the National Academy of Sciences. This ability allows the monkeys — and us — to understand when two shapes are the same, even when they’ve been rotated or resized. This finding challenges a long-held notion that humans’ geometric abilities are part of what makes our brains one of a kind. “Our hypothesis was that humans are not that unique,” in possessing this mathematical understanding, said Jialin Li, a cognitive neuroscientist at Carnegie Mellon University and the lead author of the study. In their experiment, Ms. Li and her colleagues decided to give monkeys (a total of eight rhesus macaques and olive baboons), preschoolers and adult humans with different education levels the same geometric task. That way, if humans truly had an innate advantage, it would show up when comparing the young children and the monkeys. And if the advantage was learned, it might show up when comparing the humans who had different levels of schooling. It was a challenge to find a task simple enough that even preschool-aged children and monkeys could reasonably complete it, but the team eventually decided to have all the study participants do a matching task. All were shown a shape with a specific size and geometric form on a screen. Then they were asked to pick that same shape out of a group of others. “By manipulating the similarity of the shapes, we were able to look at what kinds of rules they’re using,” said Jessica Cantlon, a cognitive neuroscientist at Carnegie Mellon University whose lab conducted the study. © 2026 The New York Times Company

Keyword: Vision; Learning & Memory
Link ID: 30337 - Posted: 07.22.2026

by Avery Hurt In 1950, researchers Hector Chevigny and Sydell Braverman set out to, as they put it, “demolish old fables about the emotional life of the blind” and demonstrate that the mental health issues of the blind are no different from those experienced by the sighted. But they did discover one big — and very surprising — difference: There have been no reported cases of schizophrenia in people blind from birth (or who became blind very shortly after birth). At the time, there was limited patient data available, so it wasn’t clear if this astonishing finding would hold up. But in the almost 80 years since, more national databases of mental illness have been maintained, and still no cases have been found, according to a study in Frontiers in Psychology. Is it just a coincidence? Or does never having been able to see somehow offer protection from schizophrenia? And if it does, how would that even work? Schizophrenia is a neurodevelopmental disorder that interferes with the way people interpret reality, Philip Corlett, a neuroscientist at Yale University who studies psychosis and delusional thinking, told Discover. Schizophrenia can cause symptoms such as hallucinations, disorganized speech and thinking, and in some cases, a lack of motivation or engagement with the world. However, the most familiar characteristic of the illness is what Corlett described as “departures from consensus reality,” or, put another way, believing things that most people in your culture don’t believe. Though the causes and mechanisms of schizophrenia are not yet well understood, one increasingly accepted theory is that the illness results from errors in prediction. To understand that, we need to take a look at how the healthy brain processes information. © 2026 Discover Magazine Inc

Keyword: Schizophrenia; Attention
Link ID: 30320 - Posted: 07.11.2026

By Claudia López Lloreda Neurons in the visual cortex decode an object’s orientation—horizontal, vertical or anything in between—using information from non-orientation-tuned neurons in the thalamus, according to David Hubel and Torsten Wiesel’s Nobel Prize-winning work in cats in the 1950s and ’60s. In other species, though, the process remained unclear. Thalamic neurons in mice, for example, show orientation selectivity, subsequent studies suggested. New mouse findings—realized by imaging individual synapses on cortical neurons and distinguishing which inputs come from the thalamus versus the neighboring cortex during visual processing—help resolve the discrepancy. Signals coming into the primary visual cortex, or V1, from the thalamus are not orientation tuned, but those from other parts of the cortex are, confirming that orientation tuning occurs in the visual cortex, the new study reveals. This study is the first “to get a map of thalamic receptive field location at the level of seeing almost all the spines that receive thalamic input,” says Jose Manuel Alonso, professor of biological and vision sciences at the State University of New York College of Optometry, who was not involved with the work. “This is unbelievably beautiful.” What’s more, the Hubel and Wiesel model of orientation selectivity “is preserved through evolution,” Alonso adds. “In the mouse, this pathway from the thalamus to the V1 is really organized as the Hubel and Wiesel suggested it should be,” says Anton Arkhipov, investigator at the Allen Institute, who was not involved with the study. © 2026 Simons Foundation

Keyword: Vision; Evolution
Link ID: 30262 - Posted: 05.30.2026

By Yasemin Saplakoglu When an optometrist shines a bright light into your eyes, a vast, branching tree sprouts in your field of vision. This is the shadow of blood vessels. Though we normally can’t perceive them, these vessels always occlude a portion of what we see, and for an important reason. They power the retina, a thin layer of nerve tissue in the back of the eye that communicates light signals to the brain. The retina is one of the body’s most energetically expensive tissues. Built from complex networks of sometimes more than 100 different types of neurons, retinal tissue consumes two to three times more energy than the same mass of typical brain tissue. That’s why most vertebrate retinas, including our own, are furrowed with dense, branching networks of blood vessels: to deliver oxygen and other ingredients for producing energy. But there’s a significant exception to this rule. Birds have retinas that mostly lack blood vessels. This may seem especially strange given birds’ exceptional vision. The bird retina is “one of the most metabolically active tissues in the animal kingdom, yet it worked with no apparent blood perfusion,” said Christian Damsgaard (opens a new tab), an evolutionary physiologist at Aarhus University. “It was a complete paradox.” For centuries this has puzzled scientists, who figured that the bird retina must obtain oxygen through a unique, undiscovered process. Damsgaard is the lead author of a study, published in the journal Nature (opens a new tab) in January 2026, that showed for the first time that bird retinas don’t have some unusual adaptation for acquiring oxygen — they survive without it entirely. Instead, to bring energy to the tissue, they use a process called anaerobic glycolysis that is significantly less efficient than oxygen-powered metabolism but gets the job done. © 2026.Simons Foundation

Keyword: Vision; Evolution
Link ID: 30247 - Posted: 05.16.2026

Ian Sample Science editor A married couple who met over a dissected brain and went on to create the first approved gene therapy for blindness have been awarded one of the most lucrative prizes in science. Molecular biologist Jean Bennett and ophthalmologist Albert Maguire share the $3m (£2.2m) Breakthrough prize for life sciences with physician Katherine High for the 25-year-long project, during which the couple adopted a pair of dogs they had treated for blindness. The therapy, named Luxturna, was approved in the US in 2017 and has transformed the lives of people born with Leber congenital amaurosis (LCA), a genetic disorder that typically causes total blindness by early adulthood. Proof that the therapy worked came in a clinical trial in which one patient described seeing their child’s face for the first time, the fine grain in wooden furniture and branches waving in the wind. Other patients reported similar profound improvements. Nine slices of bread toasted and burned to different degrees, from white to blackened. “I was overwhelmed,” said Bennett, who is now retired from the University of Pennsylvania. “It was one of the most miraculous eureka moments you can imagine.” Bennett said it was a “tremendously exciting time” for scientific and medical research, but warned that the US administration’s attacks on science could “cause damage for generations to come”, leading her to fear a brain drain that the country would struggle to recover from. “Agendas have become politicised, government agencies that support basic and applied research have been undermined, knowledgable advisers and experts have been dismissed or have fled and revised guidelines contradict decades of rigorous research,” she said. © 2026 Guardian News & Media Limited

Keyword: Vision
Link ID: 30212 - Posted: 04.22.2026

Jon Hamilton It's often called the mind's eye. "I can look at an object in the world around me, but I can also close my eyes and imagine the object," says Varun Wadia, a brain scientist at Cedars-Sinai Medical Center and the California Institute of Technology. That sort of visual imagination, Wadia says, is what allows most people to conjure the face of a loved one or navigate to work using a mental map. For 'time cells' in the brain, what matters is what happens in the moment Shots - Health News For 'time cells' in the brain, what matters is what happens in the moment But its neural underpinnings were a mystery until Wadia and a team reported in the journal Science that imagined and perceived objects appear to activate the same neurons and use the same neural code. "This has not been demonstrated before at the neural level," says Kalanit Grill-Spector, a psychology professor at Stanford University's Wu Tsai Neurosciences Institute, who was not involved in the research. With these insights, she says, scientists are one step closer to building computer models that can simulate vision as well as vision disorders like macular degeneration. These models, in turn, could help researchers develop prosthetic devices to restore sight. The research also helps explain how the brain uses imagination to augment visual information, says Thomas Naselaris, a neuroscientist at the University of Minnesota. © 2026 npr

Keyword: Vision; Consciousness
Link ID: 30210 - Posted: 04.22.2026

By Diana Kwon The ability to conjure pictures in the mind’s eye enables us to remember the past and imagine the future. It also allows us to plan, navigate and create works of art. In a study published April 9 in Science, researchers report that imagining an object reactivates some of the same neurons involved in seeing it in the first place, providing new insight into how mental imagery is produced in the brain. Previous research had hinted that the neurons involved in perceiving and imagining images overlapped. These studies used various methods, such as asking participants to view and then imagine pictures while lying in a functional MRI scanner, to show that the same brain regions were involved in these processes. But whether the same individual neurons were involved remained an open question, says Ueli Rutishauser, a neuroscientist at Cedars-Sinai Medical Center in Los Angeles. Because measuring neuronal activity requires electrodes in the brain, Rutishauser and colleagues studied 16 adults with epilepsy who had already had electrodes temporarily implanted into their brains to identify the origin of their seizures. Participants viewed hundreds of images from five categories — faces, text, plants, animals and everyday objects — while researchers recorded activity from over 700 neurons in the ventral temporal cortex, a region involved in representing visual objects. Of those, about 450 selectively responded to individual categories. Machine learning then revealed that 80 percent of those category-responsive neurons were selective to specific visual features within the images. © Society for Science & the Public 2000–2026.

Keyword: Attention; Vision
Link ID: 30195 - Posted: 04.11.2026

Ian Sample Science editor Scientists have reconstructed short movies from the brain activity of mice that watched videos for a project that aspires to lift the veil on how animals perceive the world. The brief movie clips are grainy and pixellated, but provide a glimpse of how mice processed footage that featured people taking part in various sports from gymnastics to horse riding and wrestling. The work is in its infancy, but as technology advances, scientists hope to eavesdrop on a richer suite of animal perceptions and ultimately gain fresh insights into their experiences and how brains more broadly respond to their surroundings. “The nice thing with humans is you can just ask someone, what did you dream about? What did you see? What are you hallucinating?” said Dr Joel Bauer at the Sainsbury Wellcome Centre at University College London. “But we don’t have that access with animals in the same way.” Central to the work was an artificial intelligence program that won a recent scientific competition to predict how electrical activity in the visual cortex of the mouse brain changes depending on what the animals are seeing. The visual cortex receives raw input from the retina and turns it into a coherent view of the world. To reconstruct what mice were watching, the scientists first used an infrared laser to record how neurons were firing in the visual cortex as the rodents watched 10-second-long movie clips. They then fed blank video data into the AI program and steadily altered the imagery until the AI predicted the same patterns of brain activity as those seen in the mice. Details are published in the journal eLife. Mice have poor eyesight compared with humans, so the reconstructed videos may never be as clear as the originals. But at a rough guess, Bauer suspects scientists could make the footage about seven times sharper than it is at present. © 2026 Guardian News & Media Limited

Keyword: Vision; Brain imaging
Link ID: 30157 - Posted: 03.11.2026

Jon Hamilton A human brain consumes less power than a light bulb, while artificial intelligence systems guzzle electricity to do the same tasks. Now, scientists have created a highly efficient AI model that hints at how living brains are able to do so much with so little, a team reports in the journal Nature. Light enters the compound eye of the fly, causing the photoreceptors to send electrical signals through a complex neural network, enabling the fly to detect motion The model, which mimics a part of the brain's visual system, started out using 60 million variables. But the team was able to compress it into a version that performed nearly as well using just 10,000 variables. "That is incredibly small," says Ben Cowley, an author of the study and an assistant professor at Cold Spring Harbor Laboratory. "This is something we could send in a tweet or an email." The compact model also appears to work more like a living brain, which could help scientists study what goes wrong in diseases like Alzheimer's, Cowley says. More broadly, if the AI model really does replicate strategies found in nature, it could help scientists understand the inner workings of human brains, says Mitya Chklovskii, a group leader at the Simons Foundation's Flatiron Institute, who was not involved in the study. Compact, biology-inspired models of the brain could also lead to "more powerful and more humanlike artificial intelligence," says Chklovskii, who is also on the faculty at NYU. © 2026 npr

Keyword: Robotics; Vision
Link ID: 30147 - Posted: 03.04.2026

By Carl Zimmer Look at just about any vertebrate and you’ll see two eyes looking back at you. Falcons circling overhead have two eyes, just like hammerhead sharks roving through the ocean. Scientists have long puzzled over how the vertebrate eye first evolved. A pair of new studies suggest a strange beginning: Our invertebrate ancestors 560 million years ago were cyclopes, with a single eye at the top of their head, scientists now propose, that only later split in two. Charles Darwin fretted a lot about the exquisite complexity and sophistication of the vertebrate eye as he developed his theory of evolution. “The eye to this day gives me a cold shudder,” he confided to his friend, the American botanist Asa Gray, in 1860. Somehow evolution had produced the eye from many parts, such as the lens and retina, through tiny changes through the generations. Darwin couldn’t say for sure what that sequence of changes was. But he was encouraged by the diversity of simpler eyes among invertebrates. Some are mere lumps of pigment that detect light; others are simple cups lacking lenses. “When I think of the fine known gradations,” Darwin wrote to Gray, “my reason tells me I ought to conquer the cold shudder.” Yet opponents of evolution continued to cast doubt on the idea that eyes could evolve. Even in the 1990s, creationists claimed that natural selection would need many billions of years to produce an eye — far more time than life has existed on Earth. Dan-E. Nilsson, a neurobiologist at Lund University in Sweden, grew so annoyed by these claims that he estimated how long it would actually take for a patch of light-sensitive cells to evolve into an image-forming eye. “I thought, Heck, that’s an easy calculation, let’s do that,” Dr. Nilsson recalled. In 1994 he and Susanne Pelger, a colleague at Lund, concluded that an image-forming eye could evolve in just a few hundred thousand years. “It’s not precise in any way at all, but it goes to show that there is plenty of time for eyes to evolve,” Dr. Nilsson said. © 2026 The New York Times Company

Keyword: Evolution
Link ID: 30138 - Posted: 02.25.2026

Elizabeth Quill Think about your breakfast this morning. Can you imagine the pattern on your coffee mug? The sheen of the jam on your half-eaten toast? Most of us can call up such pictures in our minds. We can visualize the past and summon images of the future. But for an estimated 4% of people, this mental imagery is weak or absent. When researchers ask them to imagine something familiar, they might have a concept of what it is, and words and associations might come to mind, but they describe their mind’s eye as dark or even blank. Systems neuroscientist Mac Shine at the University of Sydney, Australia, first realized that his mental experience differed in this way in 2013. He and his colleagues were trying to understand how certain types of hallucination come about1, and were discussing the vividness of mental imagery. “When I close my eyes, there’s absolutely nothing there,” Shine recalls telling his colleagues. They immediately asked him what he was talking about. “Whoa. What’s going on?” Shine thought. Neither he nor his colleagues had realized how much variation there is in the experiences people have when they close their eyes. This moment of revelation is common to many people who don’t form mental images. They report that they might never have thought about this aspect of their inner life if not for a chance conversation, a high-school psychology class or an article they stumbled across (see ‘How do you imagine?’). Although scientists have known for more than a century that mental imagery varies between people, the topic received a surge of attention when, a decade ago, an influential paper coined the term aphantasia to describe the experience of people with no mental imagery2. © 2026 Springer Nature Limited

Keyword: Attention; Consciousness
Link ID: 30107 - Posted: 02.04.2026

By Sachin Rawat One can spend hours looking at a calm sunset or a clear night sky. These scenes are not only effortless on the eyes — they may also be easy on the brain. People tend to like visual stimuli that require little cognitive effort to process, researchers report in the December PNAS Nexus. The brain is the most energy-guzzling organ in the body, and visual processing alone accounts for nearly half of its energy use. Researchers have long studied how the visual system conserves energy. But the new study addresses the question from a different perspective. “Not only is the visual system optimized for efficiency, but we might have aesthetic preferences for stimuli that are efficient to process,” says Mick Bonner, a neuroscientist at Johns Hopkins University who was not involved in the study. Neuroscientist Dirk Bernhardt-Walther of the University of Toronto and his colleagues suspected that such preferences could have evolved as cognitive shortcuts, helping organisms avoid excessive effort as they navigate their environment. To probe the energy consumed in visual processing, the researchers turned to an existing functional MRI dataset, in which four individuals viewed 5,000 images while their brain activity was monitored. Measurements of oxygen consumption in different parts of the brain provided an indicator of metabolic activity. The team also ran these images through an artificial neural network trained on object and scene recognition, using the proportion of activated “neurons” as a proxy for metabolic expense. The researchers then compared these metabolic cost estimates — both human and artificial — to the images’ aesthetic ratings, gathered from more than 1,000 online survey respondents who scored each picture on a five-point scale. In both cases, the metabolic effort required to process the images was inversely proportional to their aesthetic ratings. © Society for Science & the Public 2000–2026.

Keyword: Vision; Emotions
Link ID: 30072 - Posted: 01.10.2026

Miryam Naddaf Scientists have created the most detailed maps yet of how our brains differentiate from stem cells during embryonic development and early life. In a Nature collection including five papers published yesterday, researchers tracked hundreds of thousands of early brain cells in the cortices of humans and mice, and captured with unprecedented precision the molecular events that give rise to a mixture of neurons and supporting cells. “It’s really the initial first draft of any ‘cell atlases’ for the developing brain,” says Hongkui Zeng, executive vice-president director of the Allen Institute for Brain Science in Seattle, Washington, and a co-author of two papers in the collection. These atlases could offer new ways to study neurological conditions such as autism and schizophrenia. Researchers can now “mine the data, find genes that may be critical for a particular event in a particular cell type and at a particular time point”, says Zeng. “We have a very exciting time coming,” adds Zoltán Molnár, a developmental neuroscientist at the University of Oxford, UK, who was not involved with any of the studies. The work is part of the BRAIN Initiative Cell Atlas Network (BICAN) — a project launched in 2022 by the Brain Research through Advancing Innovative Neurotechnologies (BRAIN) Initiative at the US National Institutes of Health with US$500 million in funding to build reference maps of mammalian brains. Patterns of development Two of the papers map parts of the mouse cerebral cortex — the area of the brain involved in cognitive functions and perception. Zeng and her colleagues focused on how the visual cortex develops from 11.5-day-old embryos to 56-day-old mice. They created an atlas of 568,654 individual cells and identified 148 cell clusters and 714 subtypes1. “It’s the first complete high-resolution atlas of the cortical development, including both prenatal and postnatal” phases, says Zeng. © 2025 Springer Nature Limited

Keyword: Development of the Brain; Neurogenesis
Link ID: 30002 - Posted: 11.08.2025

By Kaia Glickman Anyone with a computer has been asked to “select every image containing a traffic light” or “type the letters shown below” to prove that they are human. While these log-in hurdles — called reCAPTCHA tests — may prompt some head-scratching (does the corner of that red light count?), they reflect that vision is considered a clear metric for differentiating computers from humans. But computers are catching up. The quest to create computers that can “see” has made huge progress in recent years. Fifteen years ago, computers could correctly identify what an image contains about 60 percent of the time. Now, it’s common to see success rates near 90 percent. But many computer systems still fail some of the simplest vision tests — thus reCAPTCHA’s continued usefulness. Digital artwork, one in a series displayed at CERN in Geneva. The foreground shows a particle collision event which is a possible candidate for a decay of the Higgs-like particle to a final state. The background depicts selected pages from articles published by the CMS collaboration at the LHC. Newer approaches aim to more closely resemble the human visual system by training computers to see images as they are — made up of actual objects — rather than as just a collection of pixels. These efforts are already yielding success, for example in helping develop robots that can “see” and grab objects. Computer vision models employ what are called visual neural networks. These networks use interconnected units called artificial neurons that, akin to in the brain, forge connections with each other as the system learns. Typically, these networks are trained on a set of images with descriptions, and eventually they can correctly guess what is in a new image they haven’t encountered before.

Keyword: Vision; Robotics
Link ID: 29996 - Posted: 11.01.2025

By Gina Kolata For the first time, researchers restored some vision to people with a common type of eye disease by using a prosthetic retinal implant. If approved for broader use in the future, the treatment could improve the lives of an estimated one million, mostly older, people in the United States who lose their vision to the condition. The patients’ blindness occurs when cells in the center of the retina start to die, what is known as geographic atrophy resulting from age-related macular degeneration. Without these cells, patients see a big black spot in the center of their vision, with a thin border of sight around it. Although their peripheral vision is preserved, people with this form of advanced macular degeneration cannot read, have difficulty recognizing faces or forms and may have trouble navigating their surroundings. In a study published Monday in The New England Journal of Medicine, vision in 27 out of 32 participants improved so much that they could read with their artificial retinas. The vision that is restored is not normal: It’s black and white, blurry, and the field of view is small. But after getting the retinal implant, patients who could barely see gained on average five lines on a standard eye chart. The implant gets signals from glasses and a camera that projects infrared images to the artificial retina. The camera has a zoom feature that can magnify images like letters, allowing people to read, albeit slowly because with the zoom they don’t see many letters at a time. “This is at the forefront of science,” said Dr. Demetrios Vavvas, director of the retina service at Massachusetts Eye and Ear, a specialty hospital in Boston. He was not involved in the study and emphasized that the implant was not a cure for macular degeneration. But he called it the dawn of a new technology that he predicted will significantly advance. The treatment is only for people with a loss of retinal photoreceptors, so it would not work for other forms of blindness. The study participants had an average age of 79 and had been told that once vision was lost, it was gone forever. © 2025 The New York Times Company

Keyword: Vision; Robotics
Link ID: 29981 - Posted: 10.22.2025

By Grace Lindsay Neuroscientists have spent decades characterizing the types of information represented in the visual system. In some of the earliest studies, scientists recorded neural activity in anesthetized animals passively viewing stimuli—a setup that led to some of the most famous findings in visual neuroscience, including the discovery of orientation tuning by David Hubel and Torsten Wiesel. But passive viewing, whether while awake or anesthetized, sidesteps one of the more intriguing questions for vision scientists: How does the rest of the brain use this visual information? Arguably, the main reason for painstakingly characterizing the information in the visual system is to understand how that information drives intelligent behavior. Connecting the dots between how visual neurons respond to incoming stimuli and how that information is “read out” by other brain regions has proven nontrivial. It is not clear that we have the necessary experimental and computational tools at present to fully characterize this process. To get a sense for what it might take, I asked 10 neuroscientists what experimental and conceptual methods they think we’re missing. Decoding is a common approach for understanding the information present in the visual system and how it might be used. But decoding on its own—training classifiers to read out prespecified information about a visual stimulus from neural activity patterns—cannot tell us how the brain uses information to perform a task. This is because the decoders we use for data analysis do not necessarily match the downstream processes implemented by neural circuits. Indeed, there are pieces of information that can reliably be read out from the visual system but aren’t accessible to participants during tasks. Primary visual cortex contains information about the ocular origin of a stimulus, for example, but participants are not able to accurately report this information. © 2025 Simons Foundation

Keyword: Vision
Link ID: 29970 - Posted: 10.15.2025

Asif Ghazanfar Picture someone washing their hands. The water running down the drain is a deep red. How you interpret this scene depends on its setting, and your history. If the person is in a gas station bathroom, and you just saw the latest true-crime series, these are the ablutions of a serial killer. If the person is at a kitchen sink, then perhaps they cut themselves while preparing a meal. If the person is in an art studio, you might find resonance with the struggle to get paint off your hands. If you are naive to crime story tropes, cooking or painting, you would have a different interpretation. If you are present, watching someone wash deep red off their hands into a sink, your response depends on even more variables. How we act in the world is also specific to our species; we all live in an ‘umwelt’, or self-centred world, in the words of the philosopher-biologist Jakob von Uexküll (1864-1944). It’s not as simple as just taking in all the sensory information and then making a decision. First, our particular eyes, ears, nose, tongue and skin already filter what we can see, hear, smell, taste and feel. We don’t take in everything. We don’t see ultraviolet light like a bird, we don’t hear infrasound like elephants and baleen whales do. Second, the size and shape of our bodies determine what possible actions we can take. Parkour athletes – those who run, vault, climb and jump in complex urban environments – are remarkable in their skills and daring, but sustain injuries that a cat doing the exact same thing would not. Every animal comes with a unique bag of tricks to exploit their environment; these tricks are also limitations under different conditions. Third, the world, our environment, changes. Seasons change, what animals can eat therefore also changes. If it’s the rainy season, grass will be abundant. The amount of grass determines who is around to eat it and therefore who is around to eat the grass-eaters. Ultimately, the challenge for each of us animals is how to act in this unstable world that we do not fully apprehend with our senses and our body’s limited degrees of freedom. There is a fourth constraint, one that isn’t typically recognised. Most of the time, our intuition tells us that what we are seeing (or hearing or feeling) is an accurate representation of what is out there, and that anyone else would see (or hear or feel) it the same way. But we all know that’s not true and yet are continually surprised by it. It is even more fundamental than that: you know that seemingly basic sensory information that we are able to take in with our eyes and ears? It’s inaccurate. How we perceive elementary colours, ‘red’ for example, always depends on the amount of light, surrounding colours and other factors. In low lighting, the deep red washing down the sink might appear black. A yellow sink will make it look more orange; a blue sink may make it look violet. © Aeon Media Group Ltd. 2012-2025.

Keyword: Vision; Attention
Link ID: 29961 - Posted: 10.08.2025

By Kenneth Chang After decades of brain research, scientists still aren’t sure whether most people see the same way, more or less — especially with colors. Is what I call red also red for you? Or could my red be your blue? Or maybe neon pink? If it were possible to project what I see directly into your mind, would the view be the same, or would it instead resemble a crazy-hued Andy Warhol painting? “That’s an age-old question, isn’t it?” said Andreas Bartels, a professor of visual neuroscience at the University of Tübingen in Germany. But scientists do have a good understanding of which parts of the brain handle vision. They have even figured out where various vision-processing tasks are performed, like recognizing what is moving, identifying colors and adjusting to different lighting conditions. Amazingly, it is even possible to deduce what you’re seeing by looking at an M.R.I. scan showing which parts of your brain are lighting up. “That comes out of the world of science fiction, or one would think, right?” Dr. Bartels said. “It’s amazing that this is possible, but this always has happened in individual brains.” That is, researchers pulled off this sleight of science with individuals. They would first show a subject lying in the M.R.I. machine a series of images, mapping out how that person’s brain responded. After that initial training, the researchers could randomly show one of the images and, based on just the brain activity, make a good guess at what the image was. In new research, Dr. Bartels and Michael Bannert, a postdoctoral researcher in Dr. Bartels’ laboratory, used that technique to provide a partial answer to the question of whether most of us have a shared sense of colors. They put 15 people, all with standard color vision, in an M.R.I. machine. The volunteers viewed expanding concentric rings that were red, green or yellow. © 2025 The New York Times Company

Keyword: Vision; Consciousness
Link ID: 29925 - Posted: 09.10.2025