Parkinson’s Disease Destroyed My Life. Then I Tried Deep Brain Stimulation.
[Editor's Note: On June 6, 2017, Anne Shabason, an artist, hospice educator, and mother of two from Bolton, Ontario, a small town about 30 miles outside of Toronto, underwent Deep Brain Stimulation (DBS) to treat her Parkinson's disease. The FDA approved DBS for Parkinson's disease in 2002. Although it's shown to be safe and effective, agreeing to invasive brain surgery is no easy decision, even when you have your family and one of North America's premier neurosurgeons at your side.
Here, with support from Stan, her husband of the past 40 years, Anne talks about her life before Parkinson's, what the disease took away, and what she got back because of DBS. As told to writer Heather R. Johnson.]
I was an artist.
I worked in mixed media, Papier-mâché, and collage, inspired by dreams, birds, mystery. I had gallery shows and participated in studio tours.
Educated in thanatology, I worked in hospice care as a volunteer and education director for Hospice Caledon, an organization that supports people facing life-limiting illness and grief.
I trained volunteers who helped people through their transition.
Parkinson's disease changed all that.
My hands and my head were not coordinating, so it was impossible to do my art.
It started as a twitch in my leg. During a hospice workshop, my right leg started vibrating in a way I hadn't experienced before. I told a friend, "This can't be good."
Over the next year, my right foot vibrated more and more. I could not sleep well. In my dreams people lurked in corners, in dark places, and behind castle doors. I knew they were there and couldn't avoid the ambush. I shrieked and woke everyone in the house.
An anxiety attack—something I had also never experienced before—came next.
During a class I was teaching, my mouth got so dry, I couldn't speak. I stood in front of the class for three or four minutes, unable to continue. I pushed through and finished the class. That's when I realized this was more than jiggling legs.
That's when I went to see a doctor.
A Diagnosis
My first doctor, when I suggested it might be Parkinson's, didn't believe me. She sent me to a neurologist who told me I had to meditate more and calm myself.
A friend from hospice told me to phone the Toronto Western Hospital Movement Disorders Clinic. In January 2010, I was diagnosed with Parkinson's disease.
The doctor, a fellow, got all my stats and asked a lot of questions. He was so excited he knew what it was, he exclaimed, "You've got Parkinson's!" like it was the best thing ever. I must say, that wasn't the best news, but at least I finally had a diagnosis.
I could choose whether to take medication or not. The doctor said, "If Parkinson's is compromising your lifestyle, you should consider taking levodopa."
"Well I can't run my classes, I can't do my art, so it's compromising me," I said. And my health was going downhill. The shaking—my whole body moved—sleeping was horrible. Two to four hours max a night was usual. I had terrible anxiety and panic attacks and had to quit work.
So I started taking levodopa. It's taken in a four-hour cycle, but the medication didn't last the full time. I developed dyskenisia, a side effect of the medication that made me experience uncontrolled, involuntary movements. I was edgy, irritable, and focused on my watch like a drug addict. I'd lie on the couch, feel crummy and tired, and wait.
The medication cycle restricted where I could go. Fearing the "off" period, I avoided interaction with lifelong friends, which increased my feeling of social isolation. They would come over and cook with me and read to me sometimes, and that was fine, as long as it was during an "on" period.
There was incontinence, constipation, and fatigue.
I lost fine motor skills, like writing. And painting. My hands and my head were not coordinating, so it was impossible to do my art.
It was a terrible time.
The worst symptoms—what pushed me to consider DBS—were the symptoms no one could see. The anxiety and depression were so bad, the sleeplessness, not eating.
I projected a lot of my discomforts onto Stan. I reacted so badly to him. I actually separated from him briefly on two separate occasions and lived in a separate space—a self-imposed isolation. There wasn't anything he could do to help me really except sit back and watch.
I tried alternative therapies—a naturopath, an osteopath, a reflexologist and a Chinese medicine practitioner—but nothing seemed to help.
I felt like I was dying. Certain parts of my life were being taken away from me. I was a perfectionist, and I felt imperfect. It was a horrible feeling, to not be in control of myself.
The DBS Decision
I was familiar with DBS, a procedure that involves a neurosurgeon drilling small holes into your skull and implanting electrical leads deep in your brain to modify neural activity, reducing involuntary movements.
But I was convinced I'd never do it. I was brought up in a family that believed 'doctors make you sick and hospitals kill you.'
I worried the room wouldn't be sterile. Someone's cutting into your brain, you don't know what's going to happen. They're putting things in your body. I didn't want to risk possible infection.
And my doctor said he couldn't promise he would actually do the operation. It might be a fellow, but he'd be in the background in case anything went wrong. I wasn't comfortable with that arrangement.
When filmmakers Taryn Southern and Elena Gaby decided to make a documentary about people whose lives were changed by cutting-edge brain implants--and I agreed to participate—my doctor said he would for sure do the operation. They couldn't risk anything happening on the operating table on camera, so most of my fears went away.
My family supported the decision. My mother had trigeminal neuralgia, which is a very painful facial condition. She also had a stroke and what we now believe to be Parkinson's. My father, a retired dentist, managed her care and didn't give her the opportunity to see a specialist.
I felt them running the knife across my scalp, and drilling two holes in my head, but only as pressure, not pain.
When we were talking about DBS, my son, Joseph, said, "How can you not do this, for the sake of your family? Because if you don't, you'll end up like Grandma, who, for the last few years of her life, just lay on a couch because she didn't get any kind of outside help. If you even have a chance to improve your life or give yourself five extra years, why wouldn't you do that, for our sake? Are we not worth that?"
That talk really affected me, and I realized I had to try. Even though it was difficult, I had to be brave for my family.
Surgery, Recovery, and Tweaking
You have to be awake for part of the procedure—I was awake enough that my subconscious could hear, because they had to know how far to insert the electrodes. DBS targets the troublemaking areas of the brain. There's a one millimeter difference between success and failure.
I felt them running the knife across my scalp, and drilling two holes in my head, but only as pressure, not pain.
Once they were inside, they asked me to move parts of my body to see whether the right neurons were activated.
They put me to sleep to put a battery-powered neurostimulator in my chest. A wire that runs behind my ear and down my neck connects the electrodes in my brain to the battery pack. The neurostimulator creates electric pulses 24 hours a day.
I was moving around almost immediately after surgery. Recovery from the stitches took a few weeks, but everything else took a lot longer.
I couldn't read. My motor skills were still impaired, and my brain and my hands weren't yet linked up. I needed the device to be programmed and tweaked. Until that happened, I needed help.
The depression and anxiety, though, went away almost immediately. From that perspective, it was like I never had Parkinson's. I was so happy.
When they calibrated the electrodes, they adjusted how much electrical current goes to any one of four contact points on the left and right sides of the brain. If they increased it too much, a leg would start shaking, a foot would start cramping, or my tongue would feel thicker. It took a while to get it calibrated correctly to control the symptoms.
First it was five sessions in five weeks, then once a month, then every three months. Now I visit every six months. As the disease progresses, they have the ability to keep making adjustments. (DBS controls the symptoms, but it doesn't cure the disease.)
Once they got the calibration right, my motor skills improved. I could walk without shuffling. My muscles weren't stiff and aching, and the dyskinesia disappeared. But if I turn off the device, my symptoms return almost immediately.
Some days I have more fatigue than others, and sometimes my brain doesn't click. And my voice got softer – that's a common side effect of this operation. But I'm doing so much better than before.
I have a quality of life I didn't have before. Before COVID-19 hit, Stan and I traveled, went to concerts, movies, galleries, and spent time with our growing family.
Anne in her home studio with her art, 2019.
I cut back the levodopa from seven-and-a-half pills a day to two-and-a-half. I often forget to take my medication until I realize I'm feeling tired or anxious.
Best of all, my motivation and creative ability have clicked in.
I am an artist—again.
I'm painting every day. It's what is keeping me sane. It's my saving grace.
I'm not perfect. But I am Anne. Again.
Massive benefits of AI come with environmental and human costs. Can AI itself be part of the solution?
The recent explosion of generative artificial intelligence tools like ChatGPT and Dall-E enabled anyone with internet access to harness AI’s power for enhanced productivity, creativity, and problem-solving. With their ever-improving capabilities and expanding user base, these tools proved useful across disciplines, from the creative to the scientific.
But beneath the technological wonders of human-like conversation and creative expression lies a dirty secret—an alarming environmental and human cost. AI has an immense carbon footprint. Systems like ChatGPT take months to train in high-powered data centers, which demand huge amounts of electricity, much of which is still generated with fossil fuels, as well as water for cooling. “One of the reasons why Open AI needs investments [to the tune of] $10 billion from Microsoft is because they need to pay for all of that computation,” says Kentaro Toyama, a computer scientist at the University of Michigan. There’s also an ecological toll from mining rare minerals required for hardware and infrastructure. This environmental exploitation pollutes land, triggers natural disasters and causes large-scale human displacement. Finally, for data labeling needed to train and correct AI algorithms, the Big Data industry employs cheap and exploitative labor, often from the Global South.
Generative AI tools are based on large language models (LLMs), with most well-known being various versions of GPT. LLMs can perform natural language processing, including translating, summarizing and answering questions. They use artificial neural networks, called deep learning or machine learning. Inspired by the human brain, neural networks are made of millions of artificial neurons. “The basic principles of neural networks were known even in the 1950s and 1960s,” Toyama says, “but it’s only now, with the tremendous amount of compute power that we have, as well as huge amounts of data, that it’s become possible to train generative AI models.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries.
In recent months, much attention has gone to the transformative benefits of these technologies. But it’s important to consider that these remarkable advances may come at a price.
AI’s carbon footprint
In their latest annual report, 2023 Landscape: Confronting Tech Power, the AI Now Institute, an independent policy research entity focusing on the concentration of power in the tech industry, says: “The constant push for scale in artificial intelligence has led Big Tech firms to develop hugely energy-intensive computational models that optimize for ‘accuracy’—through increasingly large datasets and computationally intensive model training—over more efficient and sustainable alternatives.”
Though there aren’t any official figures about the power consumption or emissions from data centers, experts estimate that they use one percent of global electricity—more than entire countries. In 2019, Emma Strubell, then a graduate researcher at the University of Massachusetts Amherst, estimated that training a single LLM resulted in over 280,000 kg in CO2 emissions—an equivalent of driving almost 1.2 million km in a gas-powered car. A couple of years later, David Patterson, a computer scientist from the University of California Berkeley, and colleagues, estimated GPT-3’s carbon footprint at over 550,000 kg of CO2 In 2022, the tech company Hugging Face, estimated the carbon footprint of its own language model, BLOOM, as 25,000 kg in CO2 emissions. (BLOOM’s footprint is lower because Hugging Face uses renewable energy, but it doubled when other life-cycle processes like hardware manufacturing and use were added.)
Luckily, despite the growing size and numbers of data centers, their increasing energy demands and emissions have not kept pace proportionately—thanks to renewable energy sources and energy-efficient hardware.
But emissions don’t tell the full story.
AI’s hidden human cost
“If historical colonialism annexed territories, their resources, and the bodies that worked on them, data colonialism’s power grab is both simpler and deeper: the capture and control of human life itself through appropriating the data that can be extracted from it for profit.” So write Nick Couldry and Ulises Mejias, authors of the book The Costs of Connection.
The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
Technologies we use daily inexorably gather our data. “Human experience, potentially every layer and aspect of it, is becoming the target of profitable extraction,” Couldry and Meijas say. This feeds data capitalism, the economic model built on the extraction and commodification of data. While we are being dispossessed of our data, Big Tech commodifies it for their own benefit. This results in consolidation of power structures that reinforce existing race, gender, class and other inequalities.
“The political economy around tech and tech companies, and the development in advances in AI contribute to massive displacement and pollution, and significantly changes the built environment,” says technologist and activist Yeshi Milner, who founded Data For Black Lives (D4BL) to create measurable change in Black people’s lives using data. The energy requirements, hardware manufacture and the cheap human labor behind AI systems disproportionately affect marginalized communities.
AI’s recent explosive growth spiked the demand for manual, behind-the-scenes tasks, creating an industry described by Mary Gray and Siddharth Suri as “ghost work” in their book. This invisible human workforce that lies behind the “magic” of AI, is overworked and underpaid, and very often based in the Global South. For example, workers in Kenya who made less than $2 an hour, were the behind the mechanism that trained ChatGPT to properly talk about violence, hate speech and sexual abuse. And, according to an article in Analytics India Magazine, in some cases these workers may not have been paid at all, a case for wage theft. An exposé by the Washington Post describes “digital sweatshops” in the Philippines, where thousands of workers experience low wages, delays in payment, and wage theft by Remotasks, a platform owned by Scale AI, a $7 billion dollar American startup. Rights groups and labor researchers have flagged Scale AI as one company that flouts basic labor standards for workers abroad.
It is possible to draw a parallel with chattel slavery—the most significant economic event that continues to shape the modern world—to see the business structures that allow for the massive exploitation of people, Milner says. Back then, people got chocolate, sugar, cotton; today, they get generative AI tools. “What’s invisible through distance—because [tech companies] also control what we see—is the massive exploitation,” Milner says.
“At Data for Black Lives, we are less concerned with whether AI will become human…[W]e’re more concerned with the growing power of AI to decide who’s human and who’s not,” Milner says. As a decision-making force, AI becomes a “justifying factor for policies, practices, rules that not just reinforce, but are currently turning the clock back generations years on people’s civil and human rights.”
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement.
Nuria Oliver, a computer scientist, and co-founder and vice-president of the European Laboratory of Learning and Intelligent Systems (ELLIS), says that instead of focusing on the hypothetical existential risks of today’s AI, we should talk about its real, tangible risks.
“Because AI is a transverse discipline that you can apply to any field [from education, journalism, medicine, to transportation and energy], it has a transformative power…and an exponential impact,” she says.
AI's accountability
“At the core of what we were arguing about data capitalism [is] a call to action to abolish Big Data,” says Milner. “Not to abolish data itself, but the power structures that concentrate [its] power in the hands of very few actors.”
A comprehensive AI Act currently negotiated in the European Parliament aims to rein Big Tech in. It plans to introduce a rating of AI tools based on the harms caused to humans, while being as technology-neutral as possible. That sets standards for safe, transparent, traceable, non-discriminatory, and environmentally friendly AI systems, overseen by people, not automation. The regulations also ask for transparency in the content used to train generative AIs, particularly with copyrighted data, and also disclosing that the content is AI-generated. “This European regulation is setting the example for other regions and countries in the world,” Oliver says. But, she adds, such transparencies are hard to achieve.
Google, for example, recently updated its privacy policy to say that anything on the public internet will be used as training data. “Obviously, technology companies have to respond to their economic interests, so their decisions are not necessarily going to be the best for society and for the environment,” Oliver says. “And that’s why we need strong research institutions and civil society institutions to push for actions.” ELLIS also advocates for data centers to be built in locations where the energy can be produced sustainably.
Ironically, AI plays an important role in mitigating its own harms—by plowing through mountains of data about weather changes, extreme weather events and human displacement. “The only way to make sense of this data is using machine learning methods,” Oliver says.
Milner believes that the best way to expose AI-caused systemic inequalities is through people's stories. “In these last five years, so much of our work [at D4BL] has been creating new datasets, new data tools, bringing the data to life. To show the harms but also to continue to reclaim it as a tool for social change and for political change.” This change, she adds, will depend on whose hands it is in.
DNA gathered from animal poop helps protect wildlife
On the savannah near the Botswana-Zimbabwe border, elephants grazed contentedly. Nearby, postdoctoral researcher Alida de Flamingh watched and waited. As the herd moved away, she went into action, collecting samples of elephant dung that she and other wildlife conservationists would study in the months to come. She pulled on gloves, took a swab, and ran it all over the still-warm, round blob of elephant poop.
Sequencing DNA from fecal matter is a safe, non-invasive way to track and ultimately help protect over 42,000 species currently threatened by extinction. Scientists are using this DNA to gain insights into wildlife health, genetic diversity and even the broader environment. Applied to elephants, chimpanzees, toucans and other species, it helps scientists determine the genetic diversity of groups and linkages with other groups. Such analysis can show changes in rates of inbreeding. Populations with greater genetic diversity adapt better to changes and environmental stressors than those with less diversity, thus reducing their risks of extinction, explains de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
Analyzing fecal DNA also reveals information about an animal’s diet and health, and even nearby flora that is eaten. That information gives scientists broader insights into the ecosystem, and the findings are informing conservation initiatives. Examples include restoring or maintaining genetic connections among groups, ensuring access to certain foraging areas or increasing diversity in captive breeding programs.
Approximately 27 percent of mammals and 28 percent of all assessed species are close to dying out. The IUCN Red List of threatened species, simply called the Red List, is the world’s most comprehensive record of animals’ risk of extinction status. The more information scientists gather, the better their chances of reducing those risks. In Africa, populations of vertebrates declined 69 percent between 1970 and 2022, according to the World Wildlife Fund (WWF).
“We put on sterile gloves and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says Alida de Flamingh, a postdoctoral researcher at the University of Illinois Urbana-Champaign.
“When people talk about species, they often talk about ecosystems, but they often overlook genetic diversity,” says Christina Hvilsom, senior geneticist at the Copenhagen Zoo. “It’s easy to count (individuals) to assess whether the population size is increasing or decreasing, but diversity isn’t something we can see with our bare eyes. Yet, it’s actually the foundation for the species and populations.” DNA analysis can provide this critical information.
Assessing elephants’ health
“Africa’s elephant populations are facing unprecedented threats,” says de Flamingh, the postdoc, who has studied them since 2009. Challenges include ivory poaching, habitat destruction and smaller, more fragmented habitats that result in smaller mating pools with less genetic diversity. Additionally, de Flamingh studies the microbial communities living on and in elephants – their microbiomes – looking for parasites or dangerous microbes.
Approximately 415,000 elephants inhabit Africa today, but de Flamingh says the number would be four times higher without these challenges. The IUCN Red List reports African savannah elephants are endangered and African forest elephants are critically endangered. Elephants support ecosystem biodiversity by clearing paths that help other species travel. Their very footprints create small puddles that can host smaller organisms such as tadpoles. Elephants are often described as ecosystems’ engineers, so if they disappear, the rest of the ecosystem will suffer too.
There’s a process to collecting elephant feces. “We put on sterile gloves (which we change for each sample) and use a sterile swab to collect wet mucus and materials from the outside of the dung ball,” says de Flamingh. They rub a sample about the size of a U.S. quarter onto a paper card embedded with DNA preservation technology. Each card is air dried and stored in a packet of desiccant to prevent mold growth. This way, samples can be stored at room temperature indefinitely without the DNA degrading.
Earlier methods required collecting dung in bags, which needed either refrigeration or the addition of preservatives, or the riskier alternative of tranquilizing the animals before approaching them to draw blood samples. The ability to collect and sequence the DNA made things much easier and safer.
“Our research provides a way to assess elephant health without having to physically interact with elephants,” de Flamingh emphasizes. “We also keep track of the GPS coordinates of each sample so that we can create a map of the sampling locations,” she adds. That helps researchers correlate elephants’ health with geographic areas and their conditions.
Although de Flamingh works with elephants in the wild, the contributions of zoos in the United States and collaborations in South Africa (notably the late Professor Rudi van Aarde and the Conservation Ecology Research Unit at the University of Pretoria) were key in studying this method to ensure it worked, she points out.
Protecting chimpanzees
Genetic work with chimpanzees began about a decade ago. Hvilsom and her group at the Copenhagen Zoo analyzed DNA from nearly 1,000 fecal samples collected between 2003 and 2018 by a team of international researchers. The goal was to assess the status of the West African subspecies, which is critically endangered after rapid population declines. Of the four subspecies of chimpanzees, the West African subspecies is considered the most at-risk.
In total, the WWF estimates the numbers of chimpanzees inhabiting Africa’s forests and savannah woodlands at between 173,000 and 300,000. Poaching, disease and human-caused changes to their lands are their major risks.
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes.
“One of the threats is mining near the Nimba Mountains in Guinea,” a stronghold for the West African subspecies, Hvilsom says. The Nimba Mountains are a UNESCO World Heritage Site, but they are rich in iron ore, which is used to make the steel that is vital to the Asian construction boom. As she and colleagues wrote in a recent paper, “Many extractive industries are currently developing projects in chimpanzee habitat.”
Analyzing DNA allows researchers to identify individual chimpanzees more accurately than simply observing them, she says. Normally, field researchers would install cameras and manually inspect each picture to determine how many chimpanzees were in an area. But, Hvilsom says, “That’s very tricky. Chimpanzees move a lot and are fast, so it’s difficult to get clear pictures. Often, they find and destroy the cameras. Also, they live in large areas, so you need a lot of cameras.”
By analyzing genetics obtained from fecal samples, Hvilsom estimated the chimpanzees’ population, ascertained their family relationships and mapped their migration routes based upon DNA comparisons with other chimpanzee groups. The mining companies and builders are using this information to locate future roads where they won’t disrupt migration – a more effective solution than trying to build artificial corridors for wildlife.
“The current route cuts off communities of chimpanzees,” Hvilsom elaborates. That effectively prevents young adult chimps from joining other groups when the time comes, eventually reducing the currently-high levels of genetic diversity.
“The mining company helped pay for the genetics work,” Hvilsom says, “as part of its obligation to assess and monitor biodiversity and the effect of the mining in the area.”
Of 50 toucan subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching.
Identifying toucan families
Feces aren't the only substance researchers draw DNA samples from. Jeffrey Coleman, a Ph.D. candidate at the University of Texas at Austin relies on blood tests for studying the genetic diversity of toucans---birds species native to Central America and nearby regions. They live in the jungles, where they hop among branches, snip fruit from trees, toss it in the air and catch it with their large beaks. “Toucans are beautiful, charismatic birds that are really important to the ecosystem,” says Coleman.
Of their 50 subspecies, 11 are threatened or near-threatened with extinction because of deforestation and poaching. “When people see these aesthetically pleasing birds, they’re motivated to care about conservation practices,” he points out.
Coleman works with the Dallas World Aquarium and its partner zoos to analyze DNA from blood draws, using it to identify which toucans are related and how closely. His goal is to use science to improve the genetic diversity among toucan offspring.
Specifically, he’s looking at sections of the genome of captive birds in which the nucleotides repeat multiple times, such as AGATAGATAGAT. Called microsatellites, these consecutively-repeating sections can be passed from parents to children, helping scientists identify parent-child and sibling-sibling relationships. “That allows you to make strategic decisions about how to pair (captive) individuals for mating...to avoid inbreeding,” Coleman says.
Jeffrey Coleman is studying the microsatellites inside the toucan genomes.
Courtesy Jeffrey Coleman
The alternative is to use a type of analysis that looks for a single DNA building block – a nucleotide – that differs in a given sequence. Called single nucleotide polymorphisms (SNPs, pronounced “snips”), they are very common and very accurate. Coleman says they are better than microsatellites for some uses. But scientists have already developed a large body of microsatellite data from multiple species, so microsatellites can shed more insights on relations.
Regardless of whether conservation programs use SNPs or microsatellites to guide captive breeding efforts, the goal is to help them build genetically diverse populations that eventually may supplement endangered populations in the wild. “The hope is that the ecosystem will be stable enough and that the populations (once reintroduced into the wild) will be able to survive and thrive,” says Coleman. History knows some good examples of captive breeding success.
The California condor, which had a total population of 27 in 1987, when the last wild birds were captured, is one of them. A captive breeding program boosted their numbers to 561 by the end of 2022. Of those, 347 of those are in the wild, according to the National Park Service.
Conservationists hope that their work on animals’ genetic diversity will help preserve and restore endangered species in captivity and the wild. DNA analysis is crucial to both types of efforts. The ability to apply genome sequencing to wildlife conservation brings a new level of accuracy that helps protect species and gives fresh insights that observation alone can’t provide.
“A lot of species are threatened,” Coleman says. “I hope this research will be a resource people can use to get more information on longer-term genealogies and different populations.”