The Shiny–and Potentially Dangerous—New Tool for Predicting Human Behavior

Studies of twins have played an important role in determining that genetic differences play a role in the development of differences in behavior.
[Editor's Note: This essay is in response to our current Big Question, which we posed to experts with different perspectives: "How should DNA tests for intelligence be used, if at all, by parents and educators?"]
Imagine a world in which pregnant women could go to the doctor and obtain a simple inexpensive genetic test of their unborn child that would allow them to predict how tall he or she would eventually be. The test might also tell them the child's risk for high blood pressure or heart disease.
Can we use DNA not to understand, but to predict who is going to be intelligent or extraverted or mentally ill?
Even more remarkable -- and more dangerous -- the test might predict how intelligent the child would be, or how far he or she could be expected to go in school. Or heading further out, it might predict whether he or she will be an alcoholic or a teetotaler, or straight or gay, or… you get the idea. Is this really possible? If it is, would it be a good idea? Answering these questions requires some background in a scientific field called behavior genetics.
Differences in human behavior -- intelligence, personality, mental illness, pretty much everything -- are related to genetic differences among people. Scientists have known this for 150 years, ever since Darwin's half-cousin Francis Galton first applied Shakespeare's phrase, "Nature and Nurture" to the scientific investigation of human differences. We knew about the heritability of behavior before Mendel's laws of genetics had been re-discovered at the end of the last century, and long before the structure of DNA was discovered in the 1950s. How could discoveries about genetics be made before a science of genetics even existed?
The answer is that scientists developed clever research designs that allowed them to make inferences about genetics in the absence of biological knowledge about DNA. The best-known is the twin study: identical twins are essentially clones, sharing 100 percent of their DNA, while fraternal twins are essentially siblings, sharing half. To the extent that identical twins are more similar for some trait than fraternal twins, one can infer that heredity is playing a role. Adoption studies are even more straightforward. Is the personality of an adopted child more like the biological parents she has never seen, or the adoptive parents who raised her?
Twin and adoption studies played an important role in establishing beyond any reasonable doubt that genetic differences play a role in the development of differences in behavior, but they told us very little about how the genetics of behavior actually worked. When the human genome was finally sequenced in the early 2000s, and it became easier and cheaper to obtain actual DNA from large samples of people, scientists anticipated that we would soon find the genes for intelligence, mental illness, and all the other behaviors that were known to be "heritable" in a general way.
But to everyone's amazement, the genes weren't there. It turned out that there are thousands of genes related to any given behavior, so many that they can't be counted, and each one of them has such a tiny effect that it can't be tied to meaningful biological processes. The whole scientific enterprise of understanding the genetics of behavior seemed ready to collapse, until it was rescued -- sort of -- by a new method called polygenic scores, PGS for short. Polygenic scores abandon the old task of finding the genes for complex human behavior, replacing it with black-box prediction: can we use DNA not to understand, but to predict who is going to be intelligent or extraverted or mentally ill?
Prediction from observing parents works better, and is far easier and cheaper, than anything we can do with DNA.
PGS are the shiny new toy of human genetics. From a technological standpoint they are truly amazing, and they are useful for some scientific applications that don't involve making decisions about individual people. We can obtain DNA from thousands of people, estimate the tiny relationships between individual bits of DNA and any outcome we want — height or weight or cardiac disease or IQ — and then add all those tiny effects together into a single bell-shaped score that can predict the outcome of interest. In theory, we could do this from the moment of conception.
Polygenic scores for height already work pretty well. Physicians are debating whether the PGS for heart disease are robust enough to be used in the clinic. For some behavioral traits-- the most data exist for educational attainment -- they work well enough to be scientifically interesting, if not practically useful. For traits like personality or sexual orientation, the prediction is statistically significant but nowhere close to practically meaningful. No one knows how much better any of these predictions are likely to get.
Without a doubt, PGS are an amazing feat of genomic technology, but the task they accomplish is something scientists have been able to do for a long time, and in fact it is something that our grandparents could have done pretty well. PGS are basically a new way to predict a trait in an individual by using the same trait in the individual's parents — a way of observing that the acorn doesn't fall far from the tree.
The children of tall people tend to be tall. Children of excellent athletes are athletic; children of smart people are smart; children of people with heart disease are at risk, themselves. Not every time, of course, but that is how imperfect prediction works: children of tall parents vary in their height like anyone else, but on average they are taller than the rest of us. Prediction from observing parents works better, and is far easier and cheaper, than anything we can do with DNA.
But wait a minute. Prediction from parents isn't strictly genetic. Smart parents not only pass on their genes to their kids, but they also raise them. Smart families are privileged in thousands of ways — they make more money and can send their kids to better schools. The same is true for PGS.
The ability of a genetic score to predict educational attainment depends not only on examining the relationship between certain genes and how far people go in school, but also on every personal and social characteristic that helps or hinders education: wealth, status, discrimination, you name it. The bottom line is that for any kind of prediction of human behavior, separation of genetic from environmental prediction is very difficult; ultimately it isn't possible.
Still, experts are already discussing how to use PGS to make predictions for children, and even for embryos.
This is a reminder that we really have no idea why either parents or PGS predict as well or as poorly as they do. It is easy to imagine that a PGS for educational attainment works because it is summarizing genes that code for efficient neurological development, bigger brains, and swifter problem solving, but we really don't know that. PGS could work because they are associated with being rich, or being motivated, or having light skin. It's the same for predicting from parents. We just don't know.
Still, experts are already discussing how to use PGS to make predictions for children, and even for embryos.
For example, maybe couples could fertilize multiple embryos in vitro, test their DNA, and select the one with the "best" PGS on some trait. This would be a bad idea for a lot of reasons. Such scores aren't effective enough to be very useful to parents, and to the extent they are effective, it is very difficult to know what other traits might be selected for when parents try to prioritize intelligence or attractiveness. People will no doubt try it anyway, and as a matter of reproductive freedom I can't think of any way to stop them. Fortunately, the practice probably won't have any great impact one way or another.
That brings us to the ethics of PGS, particularly in the schools. Imagine that when a child enrolls in a public school, an IQ test is given to her biological parents. Children with low-IQ parents are statistically more likely to have low IQs themselves, so they could be assigned to less demanding classrooms or vocational programs. Hopefully we agree that this would be unethical, but let's think through why.
First of all, it would be unethical because we don't know why the parents have low IQs, or why their IQs predict their children's. The parents could be from a marginalized ethnic group, recognizable by their skin color and passed on genetically to their children, so discriminating based on a parent's IQ would just be a proxy for discriminating based on skin color. Such a system would be no more than a social scientific gloss on an old-fashioned program for perpetuating economic and cognitive privilege via the educational system.
People deserve to be judged on the basis of their own behavior, not a genetic test.
Assigning children to classrooms based on genetic testing would be no different, although it would have the slight ethical advantage of being less effective. The PGS for educational attainment could reflect brain-efficiency, but it could also depend on skin color, or economic advantage, or personality, or literally anything that is related in any way to economic success. Privileging kids with higher genetic scores would be no different than privileging children with smart parents. If schools really believe that a psychological trait like IQ is important for school placement, the sensible thing is to administer the children an actual IQ test – not a genetic test.
IQ testing has its own issues, of course, but at least it involves making decisions about individuals based on their own observable characteristics, rather than on characteristics of their parents or their genome. If decisions must be made, if resources must be apportioned, people deserve to be judged on the basis of their own behavior, the content of their character. Since it can't be denied that people differ in all sorts of relevant ways, this is what it means for all people to be created equal.
[Editor's Note: Read another perspective in the series here.]
A movie still from the 1966 film "Fantastic Voyage"
In the 1966 movie "Fantastic Voyage," actress Raquel Welch and her submarine were shrunk to the size of a cell in order to eliminate a blood clot in a scientist's brain. Now, 55 years later, the scenario is becoming closer to reality.
California-based startup Bionaut Labs has developed a nanobot about the size of a grain of rice that's designed to transport medication to the exact location in the body where it's needed. If you think about it, the conventional way to deliver medicine makes little sense: A painkiller affects the entire body instead of just the arm that's hurting, and chemotherapy is flushed through all the veins instead of precisely targeting the tumor.
"Chemotherapy is delivered systemically," Bionaut-founder and CEO Michael Shpigelmacher says. "Often only a small percentage arrives at the location where it is actually needed."
But what if it was possible to send a tiny robot through the body to attack a tumor or deliver a drug at exactly the right location?
Several startups and academic institutes worldwide are working to develop such a solution but Bionaut Labs seems the furthest along in advancing its invention. "You can think of the Bionaut as a tiny screw that moves through the veins as if steered by an invisible screwdriver until it arrives at the tumor," Shpigelmacher explains. Via Zoom, he shares the screen of an X-ray machine in his Culver City lab to demonstrate how the half-transparent, yellowish device winds its way along the spine in the body. The nanobot contains a tiny but powerful magnet. The "invisible screwdriver" is an external magnetic field that rotates that magnet inside the device and gets it to move and change directions.
The current model has a diameter of less than a millimeter. Shpigelmacher's engineers could build the miniature vehicle even smaller but the current size has the advantage of being big enough to see with bare eyes. It can also deliver more medicine than a tinier version. In the Zoom demonstration, the micorobot is injected into the spine, not unlike an epidural, and pulled along the spine through an outside magnet until the Bionaut reaches the brainstem. Depending which organ it needs to reach, it could be inserted elsewhere, for instance through a catheter.
"The hope is that we can develop a vehicle to transport medication deep into the body," says Max Planck scientist Tian Qiu.
Imagine moving a screw through a steak with a magnet — that's essentially how the device works. But of course, the Bionaut is considerably different from an ordinary screw: "At the right location, we give a magnetic signal, and it unloads its medicine package," Shpigelmacher says.
To start, Bionaut Labs wants to use its device to treat Parkinson's disease and brain stem gliomas, a type of cancer that largely affects children and teenagers. About 300 to 400 young people a year are diagnosed with this type of tumor. Radiation and brain surgery risk damaging sensitive brain tissue, and chemotherapy often doesn't work. Most children with these tumors live less than 18 months. A nanobot delivering targeted chemotherapy could be a gamechanger. "These patients really don't have any other hope," Shpigelmacher says.
Of course, the main challenge of the developing such a device is guaranteeing that it's safe. Because tissue is so sensitive, any mistake could risk disastrous results. In recent years, Bionaut has tested its technology in dozens of healthy sheep and pigs with no major adverse effects. Sheep make a good stand-in for humans because their brains and spines are similar to ours.
The Bionaut device is about the size of a grain of rice.
Bionaut Labs
"As the Bionaut moves through brain tissue, it creates a transient track that heals within a few weeks," Shpigelmacher says. The company is hoping to be the first to test a nanobot in humans. In December 2022, it announced that a recent round of funding drew $43.2 million, for a total of 63.2 million, enabling more research and, if all goes smoothly, human clinical trials by early next year.
Once the technique has been perfected, further applications could include addressing other kinds of brain disorders that are considered incurable now, such as Alzheimer's or Huntington's disease. "Microrobots could serve as a bridgehead, opening the gateway to the brain and facilitating precise access of deep brain structure – either to deliver medication, take cell samples or stimulate specific brain regions," Shpigelmacher says.
Robot-assisted hybrid surgery with artificial intelligence is already used in state-of-the-art surgery centers, and many medical experts believe that nanorobotics will be the instrument of the future. In 2016, three scientists were awarded the Nobel Prize in Chemistry for their development of "the world's smallest machines," nano "elevators" and minuscule motors. Since then, the scientific experiments have progressed to the point where applicable devices are moving closer to actually being implemented.
Bionaut's technology was initially developed by a research team lead by Peer Fischer, head of the independent Micro Nano and Molecular Systems Lab at the Max Planck Institute for Intelligent Systems in Stuttgart, Germany. Fischer is considered a pioneer in the research of nano systems, which he began at Harvard University more than a decade ago. He and his team are advising Bionaut Labs and have licensed their technology to the company.
"The hope is that we can develop a vehicle to transport medication deep into the body," says Max Planck scientist Tian Qiu, who leads the cooperation with Bionaut Labs. He agrees with Shpigelmacher that the Bionaut's size is perfect for transporting medication loads and is researching potential applications for even smaller nanorobots, especially in the eye, where the tissue is extremely sensitive. "Nanorobots can sneak through very fine tissue without causing damage."
In "Fantastic Voyage," Raquel Welch's adventures inside the body of a dissident scientist let her swim through his veins into his brain, but her shrunken miniature submarine is attacked by antibodies; she has to flee through the nerves into the scientist's eye where she escapes into freedom on a tear drop. In reality, the exit in the lab is much more mundane. The Bionaut simply leaves the body through the same port where it entered. But apart from the dramatization, the "Fantastic Voyage" was almost prophetic, or, as Shpigelmacher says, "Science fiction becomes science reality."
This article was first published by Leaps.org on April 12, 2021.
How the Human Brain Project Built a Mind of its Own
In 2013, the Human Brain Project set out to build a realistic computer model of the brain over ten years. Now, experts are reflecting on HBP's achievements with an eye toward the future.
In 2009, neuroscientist Henry Markram gave an ambitious TED talk. “Our mission is to build a detailed, realistic computer model of the human brain,” he said, naming three reasons for this unmatched feat of engineering. One was because understanding the human brain was essential to get along in society. Another was because experimenting on animal brains could only get scientists so far in understanding the human ones. Third, medicines for mental disorders weren’t good enough. “There are two billion people on the planet that are affected by mental disorders, and the drugs that are used today are largely empirical,” Markram said. “I think that we can come up with very concrete solutions on how to treat disorders.”
Markram's arguments were very persuasive. In 2013, the European Commission launched the Human Brain Project, or HBP, as part of its Future and Emerging Technologies program. Viewed as Europe’s chance to try to win the “brain race” between the U.S., China, Japan, and other countries, the project received about a billion euros in funding with the goal to simulate the entire human brain on a supercomputer, or in silico, by 2023.
Now, after 10 years of dedicated neuroscience research, the HBP is coming to an end. As its many critics warned, it did not manage to build an entire human brain in silico. Instead, it achieved a multifaceted array of different goals, some of them unexpected.
Scholars have found that the project did help advance neuroscience more than some detractors initially expected, specifically in the area of brain simulations and virtual models. Using an interdisciplinary approach of combining technology, such as AI and digital simulations, with neuroscience, the HBP worked to gain a deeper understanding of the human brain’s complicated structure and functions, which in some cases led to novel treatments for brain disorders. Lastly, through online platforms, the HBP spearheaded a previously unmatched level of global neuroscience collaborations.
Simulating a human brain stirs up controversy
Right from the start, the project was plagued with controversy and condemnation. One of its prominent critics was Yves Fregnac, a professor in cognitive science at the Polytechnic Institute of Paris and research director at the French National Centre for Scientific Research. Fregnac argued in numerous articles that the HBP was overfunded based on proposals with unrealistic goals. “This new way of over-selling scientific targets, deeply aligned with what modern society expects from mega-sciences in the broad sense (big investment, big return), has been observed on several occasions in different scientific sub-fields,” he wrote in one of his articles, “before invading the field of brain sciences and neuromarketing.”
"A human brain model can simulate an experiment a million times for many different conditions, but the actual human experiment can be performed only once or a few times," said Viktor Jirsa, a professor at Aix-Marseille University.
Responding to such critiques, the HBP worked to restructure the effort in its early days with new leadership, organization, and goals that were more flexible and attainable. “The HBP got a more versatile, pluralistic approach,” said Viktor Jirsa, a professor at Aix-Marseille University and one of the HBP lead scientists. He believes that these changes fixed at least some of HBP’s issues. “The project has been on a very productive and scientifically fruitful course since then.”
After restructuring, the HBP became a European hub on brain research, with hundreds of scientists joining its growing network. The HBP created projects focused on various brain topics, from consciousness to neurodegenerative diseases. HBP scientists worked on complex subjects, such as mapping out the brain, combining neuroscience and robotics, and experimenting with neuromorphic computing, a computational technique inspired by the human brain structure and function—to name just a few.
Simulations advance knowledge and treatment options
In 2013, it seemed that bringing neuroscience into a digital age would be farfetched, but research within the HBP has made this achievable. The virtual maps and simulations various HBP teams create through brain imaging data make it easier for neuroscientists to understand brain developments and functions. The teams publish these models on the HBP’s EBRAINS online platform—one of the first to offer access to such data to neuroscientists worldwide via an open-source online site. “This digital infrastructure is backed by high-performance computers, with large datasets and various computational tools,” said Lucy Xiaolu Wang, an assistant professor in the Resource Economics Department at the University of Massachusetts Amherst, who studies the economics of the HBP. That means it can be used in place of many different types of human experimentation.
Jirsa’s team is one of many within the project that works on virtual brain models and brain simulations. Compiling patient data, Jirsa and his team can create digital simulations of different brain activities—and repeat these experiments many times, which isn’t often possible in surgeries on real brains. “A human brain model can simulate an experiment a million times for many different conditions,” Jirsa explained, “but the actual human experiment can be performed only once or a few times.” Using simulations also saves scientists and doctors time and money when looking at ways to diagnose and treat patients with brain disorders.
Compiling patient data, scientists can create digital simulations of different brain activities—and repeat these experiments many times.
The Human Brain Project
Simulations can help scientists get a full picture that otherwise is unattainable. “Another benefit is data completion,” added Jirsa, “in which incomplete data can be complemented by the model. In clinical settings, we can often measure only certain brain areas, but when linked to the brain model, we can enlarge the range of accessible brain regions and make better diagnostic predictions.”
With time, Jirsa’s team was able to move into patient-specific simulations. “We advanced from generic brain models to the ability to use a specific patient’s brain data, from measurements like MRI and others, to create individualized predictive models and simulations,” Jirsa explained. He and his team are working on this personalization technique to treat patients with epilepsy. According to the World Health Organization, about 50 million people worldwide suffer from epilepsy, a disorder that causes recurring seizures. While some epilepsy causes are known others remain an enigma, and many are hard to treat. For some patients whose epilepsy doesn’t respond to medications, removing part of the brain where seizures occur may be the only option. Understanding where in the patients’ brains seizures arise can give scientists a better idea of how to treat them and whether to use surgery versus medications.
“We apply such personalized models…to precisely identify where in a patient’s brain seizures emerge,” Jirsa explained. “This guides individual surgery decisions for patients for which surgery is the only treatment option.” He credits the HBP for the opportunity to develop this novel approach. “The personalization of our epilepsy models was only made possible by the Human Brain Project, in which all the necessary tools have been developed. Without the HBP, the technology would not be in clinical trials today.”
Personalized simulations can significantly advance treatments, predict the outcome of specific medical procedures and optimize them before actually treating patients. Jirsa is watching this happen firsthand in his ongoing research. “Our technology for creating personalized brain models is now used in a large clinical trial for epilepsy, funded by the French state, where we collaborate with clinicians in hospitals,” he explained. “We have also founded a spinoff company called VB Tech (Virtual Brain Technologies) to commercialize our personalized brain model technology and make it available to all patients.”
The Human Brain Project created a level of interconnectedness within the neuroscience research community that never existed before—a network not unlike the brain’s own.
Other experts believe it’s too soon to tell whether brain simulations could change epilepsy treatments. “The life cycle of developing treatments applicable to patients often runs over a decade,” Wang stated. “It is still too early to draw a clear link between HBP’s various project areas with patient care.” However, she admits that some studies built on the HBP-collected knowledge are already showing promise. “Researchers have used neuroscientific atlases and computational tools to develop activity-specific stimulation programs that enabled paraplegic patients to move again in a small-size clinical trial,” Wang said. Another intriguing study looked at simulations of Alzheimer’s in the brain to understand how it evolves over time.
Some challenges remain hard to overcome even with computer simulations. “The major challenge has always been the parameter explosion, which means that many different model parameters can lead to the same result,” Jirsa explained. An example of this parameter explosion could be two different types of neurodegenerative conditions, such as Parkinson’s and Huntington’s diseases. Both afflict the same area of the brain, the basal ganglia, which can affect movement, but are caused by two different underlying mechanisms. “We face the same situation in the living brain, in which a large range of diverse mechanisms can produce the same behavior,” Jirsa said. The simulations still have to overcome the same challenge.
Understanding where in the patients’ brains seizures arise can give scientists a better idea of how to treat them and whether to use surgery versus medications.
The Human Brain Project
A network not unlike the brain’s own
Though the HBP will be closing this year, its legacy continues in various studies, spin-off companies, and its online platform, EBRAINS. “The HBP is one of the earliest brain initiatives in the world, and the 10-year long-term goal has united many researchers to collaborate on brain sciences with advanced computational tools,” Wang said. “Beyond the many research articles and projects collaborated on during the HBP, the online neuroscience research infrastructure EBRAINS will be left as a legacy even after the project ends.”
Those who worked within the HBP see the end of this project as the next step in neuroscience research. “Neuroscience has come closer to very meaningful applications through the systematic link with new digital technologies and collaborative work,” Jirsa stated. “In that way, the project really had a pioneering role.” It also created a level of interconnectedness within the neuroscience research community that never existed before—a network not unlike the brain’s own. “Interconnectedness is an important advance and prerequisite for progress,” Jirsa said. “The neuroscience community has in the past been rather fragmented and this has dramatically changed in recent years thanks to the Human Brain Project.”
According to its website, by 2023 HBP’s network counted over 500 scientists from over 123 institutions and 16 different countries, creating one of the largest multi-national research groups in the world. Even though the project hasn’t produced the in-silico brain as Markram envisioned it, the HBP created a communal mind with immense potential. “It has challenged us to think beyond the boundaries of our own laboratories,” Jirsa said, “and enabled us to go much further together than we could have ever conceived going by ourselves.”