Are Brain Implants the Future of Treatment for Depression and Anxiety?
When she woke up after a procedure involving drilling small holes in her skull, a woman suffering from chronic depression reported feeling “euphoric”. The holes were made to fit the wires that connected her brain with a matchbox-sized electrical implant; this would deliver up to 300 short-lived electricity bursts per day to specific parts of her brain.
Over a year later, Sarah, 36, says the brain implant has turned her life around. A sense of alertness and energy have replaced suicidal thoughts and feelings of despair, which had persisted despite antidepressants and electroconvulsive therapy. Sarah is the first person to have received a brain implant to treat depression, a breakthrough that happened during an experimental study published recently in Nature Medicine.
“What we did was use deep-brain stimulation (DBS), a technique used in the treatment of epilepsy,” says Andrew Krystal, professor of psychiatry at University of California, San Francisco (UCSF), and one of the study’s researchers. DBS typically involves implanting electrodes into specific areas of the brain to reduce seizures not controlled with medication or to remove the part of the brain that causes the seizures. Instead of choosing and stimulating a single brain site though, the UCSF team took a different approach.
They first used 10 electrodes to map Sarah’s brain activity, a phase that lasted 10 days, during which they developed a neural biomarker, a specific pattern of brain activity that indicated the onset of depression symptoms (in Sarah, this was detected in her amygdala, an almondlike structure located near the base of the brain). But they also saw that delivering a tiny burst of electricity to the patient’s ventral striatum, an area of the brain that sits in the center, above and behind the ears, dramatically improved these symptoms. What they had to do was outfit Sara’s brain with a DBS-device programmed to propagate small waves of electricity to the ventral striatum only when it discerned the pattern.
“We are not trying to take away normal responses to the world. We are just trying to eliminate this one thing, which is depression, which impedes patients’ ability to function and deal with normal stuff.”
“It was a personalized treatment not only in where to stimulate, but when to stimulate,” Krystal says. Sarah’s depression translated to low amounts of energy, loss of pleasure and interest in life, and feelings of sluggishness. Those symptoms went away when scientists stimulated her ventral capsule area. When the same area was manipulated by electricity when Sarah’s symptoms “were not there” though, she was feeling more energetic, but this sudden flush of energy soon gave way to feelings of overstimulation and anxiety. “This is a very tangible illustration of why it's best to simulate only when you need it,” says Krystal.
We have the tendency to lump together depression symptoms, but, in reality, they are quite diverse; some people feel sad and lethargic, others stay up all night; some overeat, others don’t eat at all. “This happens because people have different underlying dysfunctions in different parts of their brain. Our approach is targeting the specific brain circuit that modulates different kinds of symptoms. Simply, where we stimulate depends on the specific set of problems a person has,” Krystal says. Such tailormade brain stimulation for patients with long-term, drug-resistant depression, which would be easy to use at home, could be transformative, the UCSF researcher concludes.
In the U.S., 12.7 percent of the population is on antidepressants. Almost exactly the same percentage of Australians–12.5–take similar drugs every day. With 13 percent of its population being on antidepressants, Iceland is the world’s highest antidepressant consumer. And quite away from Scandinavia, the Southern European country of Portugal is the world’s third strongest market for corresponding medication.
By 2020, nearly 15.5 million people had been consuming antidepressants for a time period exceeding five years. Between 40 and 60 percent of them saw improvements. “For those people, it was absolutely what they needed, whether that was increased serotonin, or increased norepinephrine or increased dopamine, ” says Frank Anderson, a psychiatrist who has been administering antidepressants in his private practice “for a long time”, and author of Transcending Trauma, a book about resolving complex and dissociative trauma.
Yet the UCSF study brings to the mental health field a specificity it has long lacked. “A lot of the traditional medications only really work on six neurotransmitters, when there are over 100 neurotransmitters in the brain,” Anderson says. Drugs are changing the chemistry of a single system in the brain, but brain stimulation is essentially changing the very architecture of the brain, says James Giordano, professor of neurology and biochemistry at Georgetown University Medical Center in Washington and a neuroethicist. It is a far more elegant approach to treating brain disorders, with the potential to prove a lifesaver for the 40 to 50 percent of patients who see no benefits at all with antidepressants, Giordano says. It is neurofeedback, on steroids, adds Anderson. But it comes with certain risks.
Even if the device generating the brain stimulation sits outside the skull and could be easily used at home, the whole process still involves neurosurgery. While the sophistication and precision of brain surgeries has significantly improved over the last years, says Giordano, they always carry risks, such as an allergic reaction to anesthesia, bleeding in the brain, infection at the wound site, blood clots, even coma. Non-invasive brain stimulation (NIBS), a technology currently being developed by the Defense Advanced Research Projects Agency (DARPA), could potentially tackle this. Patients could wear a cap, helmet, or visor that transmits electrical signals from the brain to a computer system and back, in a brain-computer interface that would not need surgery.
“This could counter the implantation of hardware into the brain and body, around which there is also a lot of public hesitance,” says Giordano, who is working on such techniques at DARPA.
Embedding a chip in your head is one of the finest examples of biohacking, an umbrella word for all the practices aimed at hacking one’s body and brain to enhance performance –a citizen do-it-yourself biology. It is also a word charged enough to set off a public backlash. Large segments of the population will simply refuse to allow that level of invasiveness in their heads, says Laura Cabrera, an associate professor of neuroethics at the Center for Neural Engineering, Department of Engineering Science and Mechanics at Penn State University. Cabrera urges caution when it comes to DBS’s potential.
“We've been using it for Parkinson's for over two decades, hoping that now that they get DBS, patients will get off medications. But people have continued taking their drugs, even increasing them,” she says. What the UCSF found is a proof of concept that DBS worked in one depressed person, but there’s a long way ahead until we can confidently say this finding is generalizable to a large group of patients. Besides, as a society, we are not there yet, says Cabrera. “Most people, at least in my research, say they don't want to have things in their brain,” she says. But what could really go wrong if we biohacked our own brains anyway?
In 2014, a man who had received a deep brain implant for a movement disorder started developing an affection for Johnny Cash’s music when he had previously been an avid country music fan. Many protested that the chip had tampered with his personality. Could sparking the brain with electricity generated by a chip outside it put an end to our individuality, messing with our musical preferences, unique quirks, our deeper sense of ego?
“What we found is that when you stimulate a region, you affect people’s moods, their energies,” says Krystal. You are neither changing their personality nor creating creatures of eternal happiness, he says. “’Being on a phone call would generally be a setting that would normally trigger symptoms of depression in me,’” Krystal reports his patient telling him. ‘I now know bad things happen, but am not affected by them in the same way. They don’t trigger the depression.’” Of the research, Krystal continues: “We are not trying to take away normal responses to the world. We are just trying to eliminate this one thing, which is depression, which impedes patients’ ability to function and deal with normal stuff.”
Yet even change itself shouldn't be seen as threatening, especially if the patient had probably desired it in the first place. “The intent of therapy in psychiatric disorders is to change the personality, because a psychiatric disorder by definition is a disorder of personality,” says Cabrera. A person in therapy wants to restore the lost sense of “normal self”. And as for this restoration altering your original taste in music, Cabrera says we are talking about rarities, extremely scarce phenomena that are possible with medication as well.
Maybe it is the allure of dystopian sci-fi films: people have a tendency to worry about dark forces that will spread malice across the world when the line between human and machine has blurred. Such mind-control through DBS would probably require a decent leap of logic with the tools science has--at least to this day. “This would require an understanding of the parameters of brain stimulation we still don't have,” says Cabrera. Still, brain implants are not fully corrupt-proof.
“Hackers could shut off the device or change the parameters of the patient's neurological function enhancing symptoms or creating harmful side-effects,” says Giordano.
There are risks, but also failsafe ways to tackle them, adds Anderson. “Just like medications are not permanent, we could ensure the implants are used for a specific period of time,” he says. And just like people go in for checkups when they are under medication, they could periodically get their personal brain implants checked to see if they have been altered or not, he continues. “It is what my research group refers to as biosecurity by design,” says Giordano. “It is important that we proactively design systems that cannot be corrupted.”
Two weeks after receiving the implant, Sarah scored 14 out of 54 on the Montgomery-Åsberg Depression Rating Scale, a ten-item questionnaire psychiatrists use to measure the severity of depressive episodes. She had initially scored 36. Today she scores under 10. She would have had to wait between four and eight weeks to see positive results had she taken the antidepressant road, says Krystal.
He and his team have enrolled two other patients in the trials and hope to add nine more. They already have some preliminary evidence that there's another place that works better in the brain of another patient, because that specific patient had been experiencing more anxiety as opposed to despondency. Almost certainly, we will have different biomarkers for different people, and brain stimulation will be tailored to a person’s unique situation, says Krystal. “Each brain is different, just like each face is different.”
A new type of cancer therapy is shrinking deadly brain tumors with just one treatment
Few cancers are deadlier than glioblastomas—aggressive and lethal tumors that originate in the brain or spinal cord. Five years after diagnosis, less than five percent of glioblastoma patients are still alive—and more often, glioblastoma patients live just 14 months on average after receiving a diagnosis.
But an ongoing clinical trial at Mass General Cancer Center is giving new hope to glioblastoma patients and their families. The trial, called INCIPIENT, is meant to evaluate the effects of a special type of immune cell, called CAR-T cells, on patients with recurrent glioblastoma.
How CAR-T cell therapy works
CAR-T cell therapy is a type of cancer treatment called immunotherapy, where doctors modify a patient’s own immune system specifically to find and destroy cancer cells. In CAR-T cell therapy, doctors extract the patient’s T-cells, which are immune system cells that help fight off disease—particularly cancer. These T-cells are harvested from the patient and then genetically modified in a lab to produce proteins on their surface called chimeric antigen receptors (thus becoming CAR-T cells), which makes them able to bind to a specific protein on the patient’s cancer cells. Once modified, these CAR-T cells are grown in the lab for several weeks so that they can multiply into an army of millions. When enough cells have been grown, these super-charged T-cells are infused back into the patient where they can then seek out cancer cells, bind to them, and destroy them. CAR-T cell therapies have been approved by the US Food and Drug Administration (FDA) to treat certain types of lymphomas and leukemias, as well as multiple myeloma, but haven’t been approved to treat glioblastomas—yet.
CAR-T cell therapies don’t always work against solid tumors, such as glioblastomas. Because solid tumors contain different kinds of cancer cells, some cells can evade the immune system’s detection even after CAR-T cell therapy, according to a press release from Massachusetts General Hospital. For the INCIPIENT trial, researchers modified the CAR-T cells even further in hopes of making them more effective against solid tumors. These second-generation CAR-T cells (called CARv3-TEAM-E T cells) contain special antibodies that attack EFGR, a protein expressed in the majority of glioblastoma tumors. Unlike other CAR-T cell therapies, these particular CAR-T cells were designed to be directly injected into the patient’s brain.
The INCIPIENT trial results
The INCIPIENT trial involved three patients who were enrolled in the study between March and July 2023. All three patients—a 72-year-old man, a 74-year-old man, and a 57-year-old woman—were treated with chemo and radiation and enrolled in the trial with CAR-T cells after their glioblastoma tumors came back.
The results, which were published earlier this year in the New England Journal of Medicine (NEJM), were called “rapid” and “dramatic” by doctors involved in the trial. After just a single infusion of the CAR-T cells, each patient experienced a significant reduction in their tumor sizes. Just two days after receiving the infusion, the glioblastoma tumor of the 72-year-old man decreased by nearly twenty percent. Just two months later the tumor had shrunk by an astonishing 60 percent, and the change was maintained for more than six months. The most dramatic result was in the 57-year-old female patient, whose tumor shrank nearly completely after just one infusion of the CAR-T cells.
The results of the INCIPIENT trial were unexpected and astonishing—but unfortunately, they were also temporary. For all three patients, the tumors eventually began to grow back regardless of the CAR-T cell infusions. According to the press release from MGH, the medical team is now considering treating each patient with multiple infusions or prefacing each treatment with chemotherapy to prolong the response.
While there is still “more to do,” says co-author of the study neuro-oncologist Dr. Elizabeth Gerstner, the results are still promising. If nothing else, these second-generation CAR-T cell infusions may someday be able to give patients more time than traditional treatments would allow.
“These results are exciting but they are also just the beginning,” says Dr. Marcela Maus, a doctor and professor of medicine at Mass General who was involved in the clinical trial. “They tell us that we are on the right track in pursuing a therapy that has the potential to change the outlook for this intractable disease.”
Since the early 2000s, AI systems have eliminated more than 1.7 million jobs, and that number will only increase as AI improves. Some research estimates that by 2025, AI will eliminate more than 85 million jobs.
But for all the talk about job security, AI is also proving to be a powerful tool in healthcare—specifically, cancer detection. One recently published study has shown that, remarkably, artificial intelligence was able to detect 20 percent more cancers in imaging scans than radiologists alone.
Published in The Lancet Oncology, the study analyzed the scans of 80,000 Swedish women with a moderate hereditary risk of breast cancer who had undergone a mammogram between April 2021 and July 2022. Half of these scans were read by AI and then a radiologist to double-check the findings. The second group of scans was read by two researchers without the help of AI. (Currently, the standard of care across Europe is to have two radiologists analyze a scan before diagnosing a patient with breast cancer.)
The study showed that the AI group detected cancer in 6 out of every 1,000 scans, while the radiologists detected cancer in 5 per 1,000 scans. In other words, AI found 20 percent more cancers than the highly-trained radiologists.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu
But even though the AI was better able to pinpoint cancer on an image, it doesn’t mean radiologists will soon be out of a job. Dr. Laura Heacock, a breast radiologist at NYU, said in an interview with CNN that radiologists do much more than simply screening mammograms, and that even well-trained technology can make errors. “These tools work best when paired with highly-trained radiologists who make the final call on your mammogram. Think of it as a tool like a stethoscope for a cardiologist.”
AI is still an emerging technology, but more and more doctors are using them to detect different cancers. For example, researchers at MIT have developed a program called MIRAI, which looks at patterns in patient mammograms across a series of scans and uses an algorithm to model a patient's risk of developing breast cancer over time. The program was "trained" with more than 200,000 breast imaging scans from Massachusetts General Hospital and has been tested on over 100,000 women in different hospitals across the world. According to MIT, MIRAI "has been shown to be more accurate in predicting the risk for developing breast cancer in the short term (over a 3-year period) compared to traditional tools." It has also been able to detect breast cancer up to five years before a patient receives a diagnosis.
The challenges for cancer-detecting AI tools now is not just accuracy. AI tools are also being challenged to perform consistently well across different ages, races, and breast density profiles, particularly given the increased risks that different women face. For example, Black women are 42 percent more likely than white women to die from breast cancer, despite having nearly the same rates of breast cancer as white women. Recently, an FDA-approved AI device for screening breast cancer has come under fire for wrongly detecting cancer in Black patients significantly more often than white patients.
As AI technology improves, radiologists will be able to accurately scan a more diverse set of patients at a larger volume than ever before, potentially saving more lives than ever.