This fall, Robert Reinhart of Boston University published a study finding that electrical stimulation can boost memory - and Reinhart was surprised to discover the effects lasted a full month.
Scientists believe brain circuits tend to uncouple as we age. Since brain neurons communicate by exchanging electrical impulses with each other, the breakdown of these links and associations could be what causes the “senior moment”—when you can’t remember the name of the movie you just watched.
In 2019, Boston University researchers led by Robert Reinhart, director of the Cognitive and Clinical Neuroscience Laboratory, showed that memory loss in healthy older adults is likely caused by these disconnected brain networks. When Reinhart and his team stimulated two key areas of the brain with mild electrical current, they were able to bring the brains of older adult subjects back into sync — enough so that their ability to remember small differences between two images matched that of much younger subjects for at least 50 minutes after the testing stopped.
Reinhart wowed the neuroscience community once again this fall. His newer study in Nature Neuroscience presented 150 healthy participants, ages 65 to 88, who were able to recall more words on a given list after 20 minutes of low-intensity electrical stimulation sessions over four consecutive days. This amounted to a 50 to 65 percent boost in their recall.
Even Reinhart was surprised to discover the enhanced performance of his subjects lasted a full month when they were tested again later. Those who benefited most were the participants who were the most forgetful at the start.
An older person participates in Robert Reinhart's research on brain stimulation.
Robert Reinhart
Reinhart’s subjects only suffered normal age-related memory deficits, but NIBS has great potential to help people with cognitive impairment and dementia, too, says Krista Lanctôt, the Bernick Chair of Geriatric Psychopharmacology at Sunnybrook Health Sciences Center in Toronto. Plus, “it is remarkably safe,” she says.
Lanctôt was the senior author on a meta-analysis of brain stimulation studies published last year on people with mild cognitive impairment or later stages of Alzheimer’s disease. The review concluded that magnetic stimulation to the brain significantly improved the research participants’ neuropsychiatric symptoms, such as apathy and depression. The stimulation also enhanced global cognition, which includes memory, attention, executive function and more.
This is the frontier of neuroscience.
The two main forms of NIBS – and many questions surrounding them
There are two types of NIBS. They differ based on whether electrical or magnetic stimulation is used to create the electric field, the type of device that delivers the electrical current and the strength of the current.
Transcranial Current Brain Stimulation (tES) is an umbrella term for a group of techniques using low-wattage electrical currents to manipulate activity in the brain. The current is delivered to the scalp or forehead via electrodes attached to a nylon elastic cap or rubber headband.
Variations include how the current is delivered—in an alternating pattern or in a constant, direct mode, for instance. Tweaking frequency, potency or target brain area can produce different effects as well. Reinhart’s 2022 study demonstrated that low or high frequencies and alternating currents were uniquely tied to either short-term or long-term memory improvements.
Sessions may be 20 minutes per day over the course of several days or two weeks. “[The subject] may feel a tingling, warming, poking or itching sensation,” says Reinhart, which typically goes away within a minute.
The other main approach to NIBS is Transcranial Magnetic Simulation (TMS). It involves the use of an electromagnetic coil that is held or placed against the forehead or scalp to activate nerve cells in the brain through short pulses. The stimulation is stronger than tES but similar to a magnetic resonance imaging (MRI) scan.
The subject may feel a slight knocking or tapping on the head during a 20-to-60-minute session. Scalp discomfort and headaches are reported by some; in very rare cases, a seizure can occur.
No head-to-head trials have been conducted yet to evaluate the differences and effectiveness between electrical and magnetic current stimulation, notes Lanctôt, who is also a professor of psychiatry and pharmacology at the University of Toronto. Although TMS was approved by the FDA in 2008 to treat major depression, both techniques are considered experimental for the purpose of cognitive enhancement.
“One attractive feature of tES is that it’s inexpensive—one-fifth the price of magnetic stimulation,” Reinhart notes.
Don’t confuse either of these procedures with the horrors of electroconvulsive therapy (ECT) in the 1950s and ‘60s. ECT is a more powerful, riskier procedure used only as a last resort in treating severe mental illness today.
Clinical studies on NIBS remain scarce. Standardized parameters and measures for testing have not been developed. The high heterogeneity among the many existing small NIBS studies makes it difficult to draw general conclusions. Few of the studies have been replicated and inconsistencies abound.
Scientists are still lacking so much fundamental knowledge about the brain and how it works, says Reinhart. “We don’t know how information is represented in the brain or how it’s carried forward in time. It’s more complex than physics.”
Lanctôt’s meta-analysis showed improvements in global cognition from delivering the magnetic form of the stimulation to people with Alzheimer’s, and this finding was replicated inan analysis in the Journal of Prevention of Alzheimer’s Disease this fall. Neither meta-analysis found clear evidence that applying the electrical currents, was helpful for Alzheimer’s subjects, but Lanctôt suggests this might be merely because the sample size for tES was smaller compared to the groups that received TMS.
At the same time, London neuroscientist Marco Sandrini, senior lecturer in psychology at the University of Roehampton, critically reviewed a series of studies on the effects of tES on episodic memory. Often declining with age, episodic memory relates to recalling a person’s own experiences from the past. Sandrini’s review concluded that delivering tES to the prefrontal or temporoparietal cortices of the brain might enhance episodic memory in older adults with Alzheimer’s disease and amnesiac mild cognitive impairment (the predementia phase of Alzheimer’s when people start to have symptoms).
Researchers readily tick off studies needed to explore, clarify and validate existing NIBS data. What is the optimal stimulus session frequency, spacing and duration? How intense should the stimulus be and where should it be targeted for what effect? How might genetics or degree of brain impairment affect responsiveness? Would adjunct medication or cognitive training boost positive results? Could administering the stimulus while someone sleeps expedite memory consolidation?
Using MRI or another brain scan along with computational modeling of the current flow, a clinician could create a treatment that is customized to each person’s brain.
While Sandrini’s review reported improvements induced by tES in the recall or recognition of words and images, there is no evidence it will translate into improvements in daily activities. This is another question that will require more research and testing, Sandrini notes.
Scientists are still lacking so much fundamental knowledge about the brain and how it works, says Reinhart. “We don’t know how information is represented in the brain or how it’s carried forward in time. It’s more complex than physics.”
Where the science is headed
Learning how to apply precision medicine to NIBS is the next focus in advancing this technology, says Shankar Tumati, a post-doctoral fellow working with Lanctôt.
There is great variability in each person’s brain anatomy—the thickness of the skull, the brain’s unique folds, the amount of cerebrospinal fluid. All of these structural differences impact how electrical or magnetic stimulation is distributed in the brain and ultimately the effects.
Using MRI or another brain scan along with computational modeling of the current flow, a clinician could create a treatment that is customized to each person’s brain, from where to put the electrodes to determining the exact dose and duration of stimulation needed to achieve lasting results, Sandrini says.
Above all, most neuroscientists say that largescale research studies over long periods of time are necessary to confirm the safety and durability of this therapy for the purpose of boosting memory. Short of that, there can be no FDA approval or medical regulation for this clinical use.
Lanctôt urges people to seek out clinical NIBS trials in their area if they want to see the science advance. “That is how we’ll find the answers,” she says, predicting it will be 5 to 10 years to develop each additional clinical application of NIBS. Ultimately, she predicts that reigning in Alzheimer’s disease and mild cognitive impairment will require a multi-pronged approach that includes lifestyle and medications, too.
Sandrini believes that scientific efforts should focus on preventing or delaying Alzheimer’s. “We need to start intervention earlier—as soon as people start to complain about forgetting things,” he says. “Changes in the brain start 10 years before [there is a problem]. Once Alzheimer’s develops, it is too late.”
Artificial Intelligence is already helping to grow some of the food we eat.
The chef-farmers choose from among 45 types of herb and leafy-greens seeds, plop them into grow trays, and a few weeks later they pick and serve. While success is predicated on at least a small amount of these humans’ care, the systems are autonomously surveilled round-the-clock from Babylon’s base of operations. And artificial intelligence is helping to run the show.
Babylon piloted the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off.
Imagine consistently perfect greens and tomatoes and strawberries, grown hyper-locally, using less water, without chemicals or environmental contaminants. This is the hefty promise of controlled environment agriculture (CEA) — basically, indoor farms that can be hydroponic, aeroponic (plant roots are suspended and fed through misting), or aquaponic (where fish play a role in fertilizing vegetables). But whether they grow 4,160 leafy-green servings per year, like one Babylon farm, or millions of servings, like some of the large, centralized facilities starting to supply supermarkets across the U.S., they seek to minimize failure as much as possible.
Babylon’s soilless hydroponic growing system
Courtesy Babylon Micro-Farms
Here, AI is starting to play a pivotal role. CEA growers use it to help “make sense of what’s happening” to the plants in their care, says Scott Lowman, vice president of applied research at the Institute for Advanced Learning and Research (IALR) in Virginia, a state that’s investing heavily in CEA companies. And although these companies say they’re not aiming for a future with zero human employees, AI is certainly poised to take a lot of human farming intervention out of the equation — for better and worse.
Most of these companies are compiling their own data sets to identify anything that might block the success of their systems. Babylon had already integrated sensor data into its farms to measure heat and humidity, the nutrient content of water, and the amount of light plants receive. Last year, they got a National Science Foundation grant that allowed them to pilot the use of specialized cameras that take pictures in different spectrums to gather some less-obvious visual data about plants’ wellbeing and alert people if something seems off. “Will this plant be healthy tomorrow? Are there things…that the human eye can't see that the plant starts expressing?” says Amandeep Ratte, the company’s head of data science. “If our system can say, Hey, this plant is unhealthy, we can reach out to [users] preemptively about what they’re doing wrong, or is there a disease at the farm?” Ratte says. The earlier the better, to avoid crop failures.
Natural light accounts for 70 percent of Greenswell Growers’ energy use on a sunny day.
Courtesy Greenswell Growers
IALR’s Lowman says that other CEA companies are developing their AI systems to account for the different crops they grow — lettuces come in all shapes and sizes, after all, and each has different growing needs than, for example, tomatoes. The ways they run their operations differs also. Babylon is unusual in its decentralized structure. But centralized growing systems with one main location have variabilities, too. AeroFarms, which recently declared bankruptcy but will continue to run its 140,000-square foot vertical operation in Danville, Virginia, is entirely enclosed and reliant on the intense violet glow of grow lights to produce microgreens.
Different companies have different data needs. What data is essential to AeroFarms isn’t quite the same as for Greenswell Growers located in Goochland County, Virginia. Raising four kinds of lettuce in a 77,000-square-foot automated hydroponic greenhouse, the vagaries of naturally available light, which accounts for 70 percent of Greenswell’s energy use on a sunny day, affect operations. Their tech needs to account for “outside weather impacts,” says president Carl Gupton. “What adjustments do we have to make inside of the greenhouse to offset what's going on outside environmentally, to give that plant optimal conditions? When it's 85 percent humidity outside, the system needs to do X, Y and Z to get the conditions that we want inside.”
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen.
Nevertheless, every CEA system has the same core needs — consistent yield of high quality crops to keep up year-round supply to customers. Additionally, “Everybody’s got the same set of problems,” Gupton says. Pests may come into a facility with seeds. A disease called pythium, one of the most common in CEA, can damage plant roots. “Then you have root disease pressures that can also come internally — a change in [growing] substrate can change the way the plant performs,” Gupton says.
AI will help identify diseases, as well as when a plant is thirsty or overly hydrated, when it needs more or less calcium, phosphorous, nitrogen. So, while companies amass their own hyper-specific data sets, Lowman foresees a time within the next decade “when there will be some type of [open-source] database that has the most common types of plant stress identified” that growers will be able to tap into. Such databases will “create a community and move the science forward,” says Lowman.
In fact, IALR is working on assembling images for just such a database now. On so-called “smart tables” inside an Institute lab, a team is growing greens and subjects them to various stressors. Then, they’re administering treatments while taking images of every plant every 15 minutes, says Lowman. Some experiments generate 80,000 images; the challenge lies in analyzing and annotating the vast trove of them, marking each one to reflect outcome—for example increasing the phosphate delivery and the plant’s response to it. Eventually, they’ll be fed into AI systems to help them learn.
For all the enthusiasm surrounding this technology, it’s not without downsides. Training just one AI system can emit over 250,000 pounds of carbon dioxide, according to MIT Technology Review. AI could also be used “to enhance environmental benefit for CEA and optimize [its] energy consumption,” says Rozita Dara, a computer science professor at the University of Guelph in Canada, specializing in AI and data governance, “but we first need to collect data to measure [it].”
The chef-farmers can choose from 45 types of herb and leafy-greens seeds.
Courtesy Babylon Micro-Farms
Any system connected to the Internet of Things is also vulnerable to hacking; if CEA grows to the point where “there are many of these similar farms, and you're depending on feeding a population based on those, it would be quite scary,” Dara says. And there are privacy concerns, too, in systems where imaging is happening constantly. It’s partly for this reason, says Babylon’s Ratte, that the company’s in-farm cameras all “face down into the trays, so the only thing [visible] is pictures of plants.”
Tweaks to improve AI for CEA are happening all the time. Greenswell made its first harvest in 2022 and now has annual data points they can use to start making more intelligent choices about how to feed, water, and supply light to plants, says Gupton. Ratte says he’s confident Babylon’s system can already “get our customers reliable harvests. But in terms of how far we have to go, it's a different problem,” he says. For example, if AI could detect whether the farm is mostly empty—meaning the farm’s user hasn’t planted a new crop of greens—it can alert Babylon to check “what's going on with engagement with this user?” Ratte says. “Do they need more training? Did the main person responsible for the farm quit?”
Lowman says more automation is coming, offering greater ability for systems to identify problems and mitigate them on the spot. “We still have to develop datasets that are specific, so you can have a very clear control plan, [because] artificial intelligence is only as smart as what we tell it, and in plant science, there's so much variation,” he says. He believes AI’s next level will be “looking at those first early days of plant growth: when the seed germinates, how fast it germinates, what it looks like when it germinates.” Imaging all that and pairing it with AI, “can be a really powerful tool, for sure.”
Researchers from the University of Cambridge have laid the foundations for growing synthetic embryos that could develop a beating heart, gut and brain.
The organoid revolution
In 1981, scientists discovered how to keep stem cells alive. This was a significant breakthrough, as stem cells have notoriously rigorous demands. Nevertheless, stem cells remained a relatively niche research area, mainly because scientists didn’t know how to convince the cells to turn into other cells.
Then, in 1987, scientists embedded isolated stem cells in a gelatinous protein mixture called Matrigel, which simulated the three-dimensional environment of animal tissue. The cells thrived, but they also did something remarkable: they created breast tissue capable of producing milk proteins. This was the first organoid — a clump of cells that behave and function like a real organ. The organoid revolution had begun, and it all started with a boob in Jello.
For the next 20 years, it was rare to find a scientist who identified as an “organoid researcher,” but there were many “stem cell researchers” who wanted to figure out how to turn stem cells into other cells. Eventually, they discovered the signals (called growth factors) that stem cells require to differentiate into other types of cells.
For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells.
By the end of the 2000s, researchers began combining stem cells, Matrigel, and the newly characterized growth factors to create dozens of organoids, from liver organoids capable of producing the bile salts necessary for digesting fat to brain organoids with components that resemble eyes, the spinal cord, and arguably, the beginnings of sentience.
Synthetic embryos
Organoids possess an intrinsic flaw: they are organ-like. They share some characteristics with real organs, making them powerful tools for research. However, no one has found a way to create an organoid with all the characteristics and functions of a real organ. But Magdalena Żernicka-Goetz, a developmental biologist, might have set the foundation for that discovery.
Żernicka-Goetz hypothesized that organoids fail to develop into fully functional organs because organs develop as a collective. Organoid research often uses embryonic stem cells, which are the cells from which the developing organism is created. However, there are two other types of stem cells in an early embryo: stem cells that become the placenta and those that become the yolk sac (where the embryo grows and gets its nutrients in early development). For a human embryo (and its organs) to develop successfully, there needs to be a “dialogue” between these three types of stem cells. In other words, Żernicka-Goetz suspected the best way to grow a functional organoid was to produce a synthetic embryoid.
As described in the aforementioned Nature paper, Żernicka-Goetz and her team mimicked the embryonic environment by mixing these three types of stem cells from mice. Amazingly, the stem cells self-organized into structures and progressed through the successive developmental stages until they had beating hearts and the foundations of the brain.
“Our mouse embryo model not only develops a brain, but also a beating heart [and] all the components that go on to make up the body,” said Żernicka-Goetz. “It’s just unbelievable that we’ve got this far. This has been the dream of our community for years and major focus of our work for a decade and finally we’ve done it.”
If the methods developed by Żernicka-Goetz’s team are successful with human stem cells, scientists someday could use them to guide the development of synthetic organs for patients awaiting transplants. It also opens the door to studying how embryos develop during pregnancy.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
