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Brain implants to restore sight, like Neuralink’s Blindsight, face a fundamental problem − more pixels don’t ensure better vision

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theconversation.com – Ione Fine, Professor of Psychology, of Washington – 2024-08-06 07:44:42
Human vision can’t be fully reproduced with ones and zeros.
seamartini/iStock via Getty Images Plus

Ione Fine, University of Washington and Geoffrey Boynton, University of Washington

Elon Musk recently pronounced that the next Neuralink will be a “Blindsight” cortical implant to restore vision: “Resolution will be low at first, like early Nintendo graphics, but ultimately may exceed normal human vision.”

Unfortunately, this claim rests on the fallacy that neurons in the brain are like pixels on a screen. It’s not surprising that engineers often assume that “more pixels equals better vision.” After all, that is how monitors and phone screens work.

In our newly published research, we created a computational model of human vision to simulate what sort of vision an extremely high-resolution cortical implant might . A of a cat with a resolution of 45,000 pixels is sharp and clear. A movie generated using a simplified version of a model of 45,000 cortical electrodes, each of which stimulates a single neuron, still has a recognizable cat but most of the details of the scene are lost.

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The movie on the left is generated using 45,000 pixels. The one on the right is generated using a simulation of a cortical prosthesis with 45,000 electrodes, each of which stimulates a single neuron.

The reason why the movie generated by electrodes is so blurry is because neurons in the human visual cortex do not represent tiny dots or pixels. Instead, each neuron has a particular receptive field, which is the location and pattern a visual stimulus must have in order to make that neuron fire. Electrically stimulating a single neuron produces a blob whose appearance is determined by that neuron’s receptive field. The tiniest electrode – one that stimulates a single neuron – will produce a blob that is roughly the size of your pinkie’s width held at arm’s length.

Consider what happens when you look at a single star in the night sky. Each point in is represented by many thousands of neurons with overlapping receptive fields. A tiny spot of light, such as a star, results in a complex pattern of firing across all these neurons.

To generate the visual experience of seeing a single star with cortical stimulation, you would need to reproduce a pattern of neural responses that is similar to the pattern that would be produced by natural vision.

In order to do this, you would obviously need thousands of electrodes. But you would also need to replicate the correct pattern of neuronal responses, which requires knowing every neuron’s receptive field. Our simulations show that knowing the location of each neuron’s receptive field in space is not enough – if you don’t also know the orientation and size of each receptive field, then the star becomes a fuzzy mess.

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So, even a single star – a single, bright pixel – generates an immensely complex neural response in the visual cortex. Imagine the even more complex pattern of cortical stimulation needed to accurately reproduce natural vision.

Some scientists have suggested that by stimulating exactly the right combination of electrodes, it would be possible to produce natural vision. Unfortunately, no one has yet suggested a sensible way to determine the receptive field of each individual neuron in a specific blind patient. Without that information, there is no way to see the stars. Vision from cortical implants will remain grainy and imperfect, regardless of the number of electrodes.

Sight restoration is not simply an engineering problem. Predicting what kind of vision a device will provide requires knowing how the technology interfaces with the complexities of the human brain.

How we created our virtual patients

In our work as computational neuroscientists, we develop simulations that predict the perceptual experience of patients seeking to restore their sight.

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We have previously created a model to predict the perceptual experience of patients with a retinal implant. To create a virtual patient to predict what cortical implant patients would see, we simulated the neurophysiological architecture of the area of the brain involved in the first stage of visual processing. Our model approximates how receptive fields increase in size from central to peripheral vision and the fact that every neuron has a unique receptive field.

Our model successfully predicted data describing the perceptual experience of participants across a wide range of studies on cortical stimulation in people. confirmed that our model could predict existing data, we used it to make predictions about the quality of vision that possible future cortical implants might produce.

Models like ours are an example of virtual prototyping, which involves using computer to improve product design. These models can facilitate new technology and evaluate device performance. Our study shows they can also offer more realistic expectations about what kind of vision bionic eyes might provide.

First do no harm

In our almost 20 years researching bionic eyes, we’ve seen the complexity of the human brain defeat company after company. Patients pay the cost when these devices fail, left stranded with orphaned technologies in their eye or brain.

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The Food and Drug Administration could mandate that sight recovery tech companies must develop failure plans that minimize harm to patients when technologies stop working. Possibilities include requiring companies implanting neuroelectronic devices into patients to participate in technology escrow agreements and carry insurance to ensure continuing medical care and technology support if they go bankrupt.

If cortical implants can achieve anything close to the resolution of our simulations, that would still be an accomplishment worth celebrating. Grainy and imperfect vision would be -changing for many thousands of people who currently suffer from incurable blindness. But this is a moment for cautious rather than blind optimism.The Conversation

Ione Fine, Professor of Psychology, University of Washington and Geoffrey Boynton, Professor of Psychology, University of Washington

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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The Conversation

How researchers measure wildfire smoke exposure doesn’t capture long-term health effects − and hides racial disparities

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theconversation.com – Joan Casey, Associate Professor of Environmental and Occupational Health Sciences, of Washington – 2024-09-16 07:26:33

Fine particulate matter from wildfires can cause long-term health harms.
Gary Hershorn/Getty Images

Joan Casey, University of Washington and Rachel Morello-Frosch, University of California, Berkeley

Kids born in 2020 worldwide will experience twice the number of wildfires during their lifetimes compared with those born in 1960. In California and other western states, frequent wildfires have become as much a part of summer and fall as popsicles and Halloween candy.

Wildfires produce fine particulate matter, or PM₂.₅, that chokes the and penetrates deep into lungs. Researchers know that short-term exposure to wildfire PM₂.₅ increases acute care visits for cardiorespiratory problems such as asthma. However, the long-term effects of repeated exposure to wildfire PM₂.₅ on chronic health conditions are unclear.

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One reason is that scientists have not decided how best to measure this type of intermittent yet ongoing exposure. Environmental epidemiologists and health scientists like us usually summarize long-term exposure to total PM₂.₅ – which comes from power plants, industry and transportation – as average exposure over a year. This might not make sense when measuring exposure to wildfire. Unlike traffic-related air pollution, for example, levels of wildfire PM₂.₅ vary a lot throughout the year.

To improve health and equity research, our team has developed five metrics that better capture long-term exposure to wildfire PM₂.₅.

Measuring fluctuating wildfire PM₂.₅

To understand why current measurements of wildfire PM₂.₅ aren’t adequately capturing an individual’s long-term exposure, we need to delve into the concept of averages.

Say the mean level of PM₂.₅ over a year was 1 microgram per cubic meter. A person could experience that exposure as 1 microgram per cubic meter every day for 365 days, or as 365 micrograms per cubic meter on a single day.

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While these two scenarios result in the same average exposure over a year, they might have very different biological effects. The body might be able to fend off damage from exposure to 1 microgram per cubic meter each day, but be overwhelmed by a huge, single dose of 365 micrograms per cubic meter.

For perspective, in 2022, Americans experienced an average total PM₂.₅ exposure of 7.8 micrograms per cubic meter. Researchers estimated that in the 35 states that experience wildfires, these wildfires added on average just 0.69 micrograms per cubic meter to total PM₂.₅ each year from 2016 to 2020. This perspective misses the mark, however.

For example, a census tract close to the 2018 Camp Fire experienced an average wildfire PM₂.₅ concentration of 1.2 micrograms per cubic meter between 2006 to 2020. But the actual fire had a peak exposure of 310 micrograms per cubic meter – the world’s highest level that day.

Orange haze blanketing a city skyline, small silhouette of a person taking a photo by a streetlight
Classic estimates of average PM₂.₅ levels miss the peak exposure of wildfire events.
Angela Weiss/AFP via Getty Images

Scientists want to better understand what such extreme exposures mean for long-term human health. Prior studies on long-term wildfire PM₂.₅ exposure focused mostly on people living close to a large fire, following up years later to check on their health status. This misses any new exposures that took place between baseline and follow-up.

More recent studies have tracked long-term exposure to wildfire PM₂.₅ that changes over time. For example, researchers reported associations between wildfire PM₂.₅ exposure over two years and risk of from cancer and any other cause in Brazil. This work again relied on long-term average exposure and did not directly capture extreme exposures from intermittent wildfire events. Because the study did not evaluate it, we do not know whether a specific pattern of long-term wildfire PM₂.₅ exposure was worse for health.

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Most days, people experience no wildfire PM₂.₅ exposure. Some days, wildfire exposure is intense. As of now, we do not know whether a few very bad days or many slightly bad days are riskier for health.

A new framework

How can we get more realistic estimates that capture the huge peaks in PM₂.₅ levels that people are exposed to during wildfires?

When thinking about the wildfire PM₂.₅ that people experience, exposure scientists – researchers who study contact between humans and harmful agents in the environment – consider frequency, duration and intensity. These interlocking factors describe the body’s true exposure during a wildfire event.

In our recent study, our team proposed a framework for measuring long-term exposure to wildfire PM₂.₅ that incorporates the frequency, duration and intensity of wildfire events. We applied air quality models to California wildfire data from 2006 to 2020, deriving new metrics that capture a range of exposure types.

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Five heat maps of California paired with bar graphs of exposures over time
The researchers proposed five ways to measure long-term wildfire PM₂.₅ exposure.
Casey et al. 2024/PNAS, CC BY-NC-ND

One metric we devised is number of days with any wildfire PM₂.₅ exposure over a long-term period, which can identify even the smallest exposures. Another metric is average concentration of wildfire PM₂.₅ during the peak of smoke levels over a long period, which highlights locations that experience the most extreme exposures. We also developed several other metrics that may be more useful, depending on what effects are being studied.

Interestingly, these metrics were quite correlated with one another, suggesting places with many days of at least some wildfire PM₂.₅ also had the highest levels overall. Although this can make it difficult to decide between different exposure patterns, the suitability of each metric depends in part on what health effects we are investigating.

Environmental injustice

We also assessed whether certain racial and ethnic groups experienced higher-than-average wildfire PM₂.₅ exposure and found that different groups faced the most exposure depending on the year.

Consider 2018 and 2020, two major wildfire years in California. The most exposed census tracts, by all metrics, were composed primarily of non-Hispanic white individuals in 2018 and Hispanic individuals in 2020. This makes sense, since non-Hispanic white people constitute about 41.6% and Hispanic people 36.4% of California’s population.

To understand whether other groups excess wildfire PM₂.₅ exposure, we used relative comparisons. This means we compared the true wildfire PM₂.₅ exposure experienced by each racial and ethnic group with what we would have expected if they were exposed to the state average.

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We found that Indigenous communities had the most disproportionate exposure, experiencing 1.68 times more PM₂.₅ than expected. In comparison, non-Hispanic white Californians were 1.13 times more exposed to PM₂.₅ than expected, and multiracial Californians 1.09 times more exposed than expected.

Person holding child, sitting by two other people; in the foreground, a child approaches the camera
Better metrics for long-term PM2.5 exposure can help researchers better understand who’s most vulnerable to wildfire smoke.
Eric Thayer/Stringer via Getty Images News

Rural tribal lands had the highest mean wildfire PM₂.₅ concentrations – 0.83 micrograms per cubic meter – of any census tract in our study. A large portion of Native American people in California live in rural , often with higher wildfire risk due to decades of poor forestry management, legal suppression of cultural burning practices that studies have shown to aid in reducing catastrophic wildfires. Recent state legislation has removed liability risks of cultural burning on Indigenous lands in California.

Understanding the drivers and health effects of high long-term exposure to wildfire PM₂.₅ among Native American and Alaska Native people can help address substantial health disparities between these groups and other Americans.The Conversation

Joan Casey, Associate Professor of Environmental and Occupational Health Sciences, University of Washington and Rachel Morello-Frosch, Professor of Environmental Science, Policy and Management and of Public Health, University of California, Berkeley

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Genetically modified varieties are coming out of the lab and into homes and gardens

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theconversation.com – James W. Satterlee, Postdoctoral Fellow in Plant Genetics, Cold Spring Harbor Laboratory – 2024-09-16 07:26:49

Not every rose has its thorn, thanks to gene editing.
James Satterlee, CC BY-SA

James W. Satterlee, Cold Spring Harbor Laboratory

As any avid gardener will tell you, plants with sharp thorns and prickles can you looking like you’ve had a -in with an angry cat. Wouldn’t it be nice to rid plants of their prickles entirely but keep the tasty fruits and beautiful flowers?

I’m a geneticist who, along with my colleagues, recently discovered the gene that accounts for prickliness across a variety of plants, roses, eggplants and even some species of grasses. Genetically tailored, smooth-stemmed plants may eventually arrive at a garden center near you.

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Acceleration of nature

Plants and other organisms evolve naturally over time. When random changes to their DNA, called mutations, enhance survival, they get passed on to offspring. For thousands of years, plant breeders have taken advantage of these variations to create high-yielding crop varieties.

In 1983, the first genetically modified organisms, or GMOs, appeared in agriculture. Golden rice, engineered to combat vitamin A deficiency, and pest-resistant corn are just a of examples of how genetic modification has been used to enhance crop plants.

Two recent developments have changed the landscape further. The advent of gene editing using a technique known as CRISPR has made it possible to modify plant traits more easily and quickly. If the genome of an organism were a book, CRISPR-based gene editing is akin to adding or removing a sentence here or there.

This tool, combined with the increasing ease with which scientists can sequence an organism’s complete collection of DNA – or genome – is rapidly accelerating the ability to predictably engineer an organism’s traits.

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By identifying a key gene that controls prickles in eggplants, our team was able to use gene editing to mutate the same gene in other prickly species, yielding smooth, prickle- plants. In addition to eggplants, we got rid of prickles in a desert-adapted wild plant species with edible raisin-like fruits.

Two sets of two photos. First set shows a cluster of prickly fruits on a plant and the harvest of those prickly fruits. Second set shows the same plant with fruits but without prickles and the harvest of those prickle-free fruits.
The desert raisin (Solanum cleistogamum) gets a makeover.
Blaine Fitzgerald, CC BY-SA

We also used a virus to silence the expression of a closely related gene in roses, yielding a rose without thorns.

In natural settings, prickles defend plants against grazing herbivores. But under cultivation, edited plants would be easier to handle – and after harvest, fruit would be reduced. It’s worth noting that prickle-free plants still retain other defenses, such as their chemical-laden epidermal hairs called trichomes that deter insect pests.

From glowing petunias to purple tomatoes

, DNA modification technologies are no longer confined to large-scale agribusiness – they are becoming available directly to consumers.

One approach is to mutate certain genes, like we did with our prickle-free plants. For example, scientists have created a mild-tasting but nutrient-dense mustard green by inactivating the genes responsible for bitterness. Silencing the genes that delay flowering in tomatoes has resulted in compact plants well suited to urban agriculture.

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Another modification approach is to permanently transfer genes from one species to another, using recombinant DNA technology to yield what scientists call a transgenic organism.

A photo taken in the dark shows a glowing petunia plant.
The firefly petunia is genetically engineered to glow in the dark.
Ceejayoz, CC BY-SA

At a recent party, I found myself crowded into a darkened bathroom to observe the faint glow of the host’s newly acquired firefly petunia, which contains the genes responsible for the ghost ear mushroom’s bioluminescent glow. Scientists have also modified a pothos houseplant with a gene from rabbits, which allows it to host air-filtering microbes that promote the of harmful volatile organic compounds, or VOCs.

A purple tomato is sliced open to reveal purple flesh inside.
The Norfolk purple tomato is colorful to the core.
Norfolk Healthy Produce, CC BY-SA

Consumers can also grow the purple tomato, genetically engineered to contain pigment-producing genes from the snapdragon plant, resulting in antioxidant-rich tomatoes with a dark purple hue.

Risks and rewards

The introduction of genetically modified plants into the consumer market brings with it both exciting opportunities and potential challenges.

With genetically edited plants in the hands of the public, there could be less oversight over what people do with them. For instance, there is a risk of environmental release, which could have unforeseen ecological consequences. Additionally, as the market for these plants expands, the quality of products may become more variable, necessitating new or more vigilant consumer protection laws. Companies could also apply patent rules limiting seed reuse, echoing some of the issues seen in the agricultural sector.

The future of plant genetic technology is bright – in some cases, quite literally. Bioluminescent golf courses, houseplants that emit tailored fragrances or flowers capable of changing their color in response to spray-based treatments are all theoretical possibilities. But as with any powerful technology, careful regulation and oversight will be crucial to ensuring these innovations benefit consumers while minimizing potential risks.The Conversation

James W. Satterlee, Postdoctoral Fellow in Plant Genetics, Cold Spring Harbor Laboratory

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Will your phone one day let you smell as well as see and hear what’s on the other end of a call?

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theconversation.com – Jian Liu, Assistant Professor of Electrical Engineering and Computer Science, University of Tennessee – 2024-09-16 07:27:05

Phones that transmit odors seem like a great idea, but careful what you wish for!

Teo Mahatmana/iStock via Getty Images

Jian Liu, University of Tennessee

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Curious Kids is a for of all ages. If you have a question you’d like an expert to answer, send it to curiouskidsus@theconversation.com.


Is it possible to make a phone through which we can smell, like we can hear and see? – Muneeba K., age 10, Pakistan


Imagine this: You pick up your phone for a call with a friend. Not only can you see their face and hear their voice, but you can also smell the cookies they just baked. It sounds like something out of a science fiction , but could it actually happen?

I’m a computer scientist who studies how machines sense the world.

What phones do now

When you listen to music or to someone on your phone, you can hear the sound through the built-in speakers. These speakers convert digital signals into physical vibrations using a tiny component called a diaphragm. Your ears sense those vibrations as sound waves.

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Your phone also has a screen that displays images and videos. The screen uses tiny dots known as pixels that consist of three primary colors: red, green and blue. By mixing these colors in different ways, your phone can show you everything from beautiful beach scenes to cute puppies.

Smelling with phones

Now how about the sense of smell? Smells are created by tiny particles called molecules that float through the and reach your nose. Your nose then sends signals to your brain, which identifies the smell.

So, could your phone send these smell molecules to you? Scientists are working on it. Think about how your phone screen works. It doesn’t have every color in the world stored inside it. Instead, it uses just three colors to create millions of different hues and shades.

How your sense of smell works.

Now imagine something similar for smells. Scientists are developing digital scent technology that uses a small number of different cartridges, each containing a specific scent. Just like how pixels mix three colors to create images, these scent cartridges could mix to create different smells.

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Just like images on your phone are made of digital codes that represent combinations of pixels, smells produced by a future phone could be created using digital codes. Each smell could have a specific recipe made up of different amounts of the ingredients in the cartridges.

When you a digital scent code, your phone could mix tiny amounts of the different scents from the cartridges to create the desired smell. This mix would then be released through a small vent on the phone, allowing you to smell it. With just a few cartridges, your phone could potentially create a huge variety of smells, much like how red, green and blue pixels can create countless colors.

Researchers and companies are already working on digital odor makers like this.

The challenges to making smell phones

Creating a phone that can produce smells involves several challenges. One is designing a system that can produce thousands of different smells using only a few cartridges. Another is how to control how strong a scent should be and how long a phone should emit it. And phones will also need to sense odors near them and convert those to digital codes so your friends’ phones can send smells to you.

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The cartridges should also be easy to refill, and the chemicals in them be safe to breathe. These hurdles make it a tricky but exciting area of research.

An odiferous future

Even though we’re not there yet, scientists and engineers are working hard to make smell phones a reality. Maybe one day you’ll be able to not only see and hear your friend’s birthday party over the phone, but also smell the candles they blew out!


Hello, curious kids! Do you have a question you’d like an expert to answer? Ask an adult to send your question to CuriousKidsUS@theconversation.com. Please tell us your name, age and the where you .

And since curiosity has no age limit – adults, let us know what you’re wondering, too. We won’t be able to answer every question, but we will do our best.The Conversation

Jian Liu, Assistant Professor of Electrical Engineering and Computer Science, University of Tennessee

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