Benjamin Stecher - Deep Brain Stimulation in the Treatment of Neurodegenerative Disease

Attention all healthcare professionals and patients interested in learning about deep brain stimulation for neurodegenerative conditions!

Meet Benjamin Stecher, a patient advocate, and researcher who has been living with Parkinson's disease since the age of 29.

Benjamin shared his inspiring journey and work in patient and research advocacy, and discussed the latest advancements in deep brain stimulation for neurodegenerative diseases.

This is a must-listen for anyone who wants to learn more about managing and treating neurodegenerative conditions, and gain insights from a patient's perspective.

Topics covered include:
✅ Exciting research and therapies for Parkinson's disease
✅ Patient advocacy and engagement in the development of new treatments for neurodegenerative diseases
✅ Machine learning algorithms for simulating the brain
✅ Ethical considerations of using machine learning to influence decision-making in finance and politics
✅ Neuromodulation as a potential replacement or complement to traditional drug-based therapies for neurological and psychiatric disorders
✅ Ethical concerns surrounding the use of neuromodulation technology in the treatment of mental health disorders
✅ The impact of deep brain stimulation on patients' quality of life
✅ The role of caregivers in managing neurodegenerative conditions and the support available for them
✅ Personalized care and treatment plans for patients with neurodegenerative diseases
✅ Managing the psychological and emotional impact of living with a neurodegenerative condition, and the importance of mental health support
✅ Challenges and opportunities in clinical trials and research for neurodegenerative diseases
✅ Interdisciplinary teams in the management of neurodegenerative conditions and the potential for collaboration between healthcare professionals and patients.

This is an opportunity to learn from an expert who has been living with a neurodegenerative condition who dedicated to improving the lives of patients like him.

Follow Benjamin on LinkedIn: https://www.linkedin.com/in/benjamin-stecher-86706420/
Visit Benjamin's Blog and Website: https://tmrwedition.com/

👉 See our Website: https://podcast.boomerliving.tv/
🎙 Boomer Living Podcast: https://hanhdbrown.com/
👉 LinkedIn https://bit.ly/2TFIbbd

Transcript

Hanh: 00:00:00
Hello. I'm Hanh Brown. Thank you so much for everyone that joined us. So get ready for an episode of Boomer Living Broadcast that's sure to blow your mind. Today we will go do a deep dive into the world of neurodegenerative diseases and discussing the groundbreaking technique of deep brain stimulation. And who better talk to than Benjamin Stecher, a patient advocate, research advocate, and Tomorrow Edition founder. Well, Benjamin's journey is nothing short of inspirational. Hailing from Nairobi, Kenya, and raised in Canada, he has a unique background in history and philosophy. But his life took an unexpected turn when he was diagnosed with Parkinson's disease at the age of just 29. So rather than let this setback defeat him, Benjamin returned to Canada to learn how to manage his illness. Well, along the way, he became fascinated by the world of biomedical science and started traveling the globe to learn from the field's top minds. So now, Benjamin is a speaker at academic centers and biotech companies. He also serves as a patient advisor to a range of organizations, including the Toronto Western Hospital Movement Disorder Clinic and the innovative brain tech company Rune Labs. So in this episode, he will share his thoughts on the future of health care and biomedical science, as well as discussing his work in patient advocacy and research advocacy. Plus, he also co-authored the book Brain Fables, so you know he's got a lot of wisdom to share. So tune in and join us as we explore the incredible journey of Benjamin Stecher and learn more about the cutting edge world of deep brain stimulation.

Hanh: 00:01:57
So Benjamin, welcome to the show.

Benjamin: 00:02:00
Hi, Hanh. Thank you for having me. I'm very excited to talk to you and speak to everyone who might be listening as well.

Hanh: 00:02:06
Awesome. Okay. So can you describe your experience of being diagnosed with Parkinson's disease at just 29 years old? And how did it change the trajectory of your life and career?

Benjamin: 00:02:20
Sure. So at the time I was living and working in China. I was an education consultant in Shanghai. I was working for a big Chinese company when I got the news. However, at the time, it didn't seem that bad because my symptoms were rather mild. I thought, hmm, if this is Parkinson's, then I guess it's not that bad. But the more I learned, the more I realized that and the more time in the past, the more I realized that I was in a lot of trouble. And so eventually I made the decision to come back home to explore this space full time. I've been ever since I've been kind of a nuisance to some people in the field in that I've been traveling the world, knocking on doors and asking as many prodding questions as I promised possibly could, some of the top minds in the field. And I've got myself to a point now where it's easier for me to get back into some of those doors. But it's been a difficult journey because I thought at the beginning that maybe I should go back to school and get an M.D. or Ph.D. I thought maybe I could become a doctor of some kind and advocacy or do something of that sort. But I soon realized that there's no school of advocacy that I could go to. There's no place that I could attend or get a degree in what I needed to know. And so I decided to just kind of go out into the world and learn for myself whatever it is that I thought was best for me. And that has been the calling card that I've kind of used to continue on in this journey.

Hanh: 00:03:49
Well, thank you. Thank you so much for your journey and your wealth of knowledge through your experience and sharing with us today. So let's talk about what's it like letting a machine learning algorithm run part of your brain. So as the field of neuroscience and artificial intelligence continue to overlap, researchers are exploring the use of machine learning algorithms to simulate parts of the brain. So can you describe the specific machine learning algorithm that you use to simulate a part of your brain and how did you train it?

Benjamin: 00:04:27
Sure. So I had something called a deep brain stimulator. I had that surgically implanted just under two years ago now. And actually on Friday of this week, I'm going to get my battery replaced for the first time. We can talk about that later though if you want. But it's been a very wild experience for me and in particular because one aspect of that is something called the ADAPT PD trial, which I'm the first participant in. I was the first patient enrolled in this trial and I was also the first patient to actually finish the trial as well. So my trial in that period is finished, although I'm still in the extended phase of this same trial. But essentially what it is is it's taking. So at the end of the electrodes that are placed deep inside my brain, there are sensors that allow it to read from my brain as well. So it takes those readings and it's recording something called the beta wave signals that it's getting. And those beta waves then range from 13 to 31 Hertz. And what those essentially do is they correlate with my symptoms severity. So the higher my beta waves are, tends to be the worse my symptoms are. And so at those times, I tend to need more stimulation coming from my deep brain stimulator. In the past, these kinds of devices were just something called continuous deep brain stimulators. They were kind of dumb machines that just like pulsated at a given frequency for the entirety of the day. But this new age that we're living in now has allowed for these new adaptive deep brain stimulators that do as the label says, kind of. So they take in the beta wave signaling and they modulate the amount of the amplitude of the electrical signal that I get delivered into my brain from this device. Based on that, based on the beta wave signals that it's receiving. It's a pretty wild thing to go through and it's led to a lot of weird and kind of unique side effects in me as well.

Benjamin: 00:06:26
However, it's also what's allowed me to live again. So prior to the pandemic or prior to getting this simulator inserted inside of me, I was living back in my parents basement. One, because of the pandemic, but two, just because my symptoms are so severe that I had no choice but to kind of live back in my parents house. Because I needed somebody basically to take care of me and help me with some small things in life. But since we turned on this adaptive deep brain simulator, I've been able to do the things I love again. Show things like traveling and speaking and just touring the world once again. So it's really giving me back my independence and I'm very grateful to the whole team behind me as well. Toronto Western Hospital and at the movement sort of clinic here in Toronto, because it's really been the thing that's allowed me to live again.

Hanh: 00:07:16
Wow. Well, thank you. So you're saying that using AI to control a part of the brain could have implications for the concept of free will and the boundaries between human consciousness and machine intelligence. So how did you experience of having a machine learning algorithm control part of your brain? Did that affect your perception of agency or autonomy?

Benjamin: 00:07:39
Yeah, it definitely did. And it was a bit shocking for me because I was a philosophy major in university. I thought I had a pretty good understanding of what I was and what the human experience is like. But I've realized through everything that I've gone through lately that I think we're actually simpler than I had originally anticipated us to be. You know, I thought we were very complex. I thought the brain was a very complex organ and it still is in comparison to the rest of the organs in our body. But really, it's a chemical factory that produces electricity. That's the simplest way to actually describe what it's doing. It's just a giant storm of electricity. And if there's something going wrong inside of a human being, it tends to originate somewhere in their brain. Although, you know, there's other organs as well that are also necessary. But there's a huge host of mental health problems that obviously the society is experiencing that we are all kind of trying to figure out a way to grapple with. However, I think that now, and this is something that's kind of been revelatory for me, is that basically for any of these problems that we encounter in our daily lives, whatever mental health problems it might be or neurodegenerative diseases that someone might have, it's really the loss of that electrical signaling that's driving those diseases forward. And if we can just find the right spots in which we can modulate something in the brain where we can put in one of these electrodes, I've come to believe that that will be the best solution for a lot of these different issues and problems that people face. Now, there's a lot of like, obviously, technical things that I skipped over there. Happy to go back over any one of them.

Benjamin: 00:09:19
But I just want to emphasize that point again that I've come to very strongly believe that DBS is going to be a part of not only my own future, but the future of a lot of human beings. Because currently it's approved for Parkinson's disease, DBS is anyway. Soon I hope adaptive DBS will be also approved by the FDA. That'll be later this year when Medtronic actually submits all their data to the FDA from this trial. We'll find out then if it passes the FDA's approval ratings or not. But that's just one indication as well. There are in total six or seven different indications that currently DBS is being thought for. For example, things like depression or OCD, even things like dementia as well are being tried right now using various kinds of deep brain simulators. Simply because the simple fact that, I mean, the neurons in your brain, yeah, they consume chemistry, but they produce electricity. And that was kind of a shocking fact. And I sold upon that because it sounds very simple and it's obviously more complicated than I've made it sound. But that is in essence what we're doing here. That's in essence what we are.

Hanh: 00:10:39
Now, did the experiment have any unexpected results?

Benjamin: 00:10:45
Yeah, so there's a lot of things that were unexpected. There's some kind of simpler things as well. Some of them were like things like, so I can't really swim again. Or for now anyways, I can't really swim because it requires a lot of bilateral upper and lower body control for somebody to swim properly. Before it, I could swim just fine in my parents pool or anywhere. But I remember about six months after I got this thing turned on, I tried to swim again and I almost drowned in my pool here. Because it becomes very hard at some point to actually know where your limbs are and then you have to think about so many things. And then you're trying to also paddle and it overwhelms your body and you just don't know what to do anymore. Maybe I have to relearn it as well. But that's just one of the more physical things that I've had to deal with. But there's been so many emotional and psychological things as well. I've had a couple of different bouts of mania so far. I don't know how much detail you want me to get into on those. But they've been things that I've experienced so far that I didn't expect and that my team didn't expect either.

Hanh: 00:11:56
So let's do a little deep dive on this. You touched on it a little bit. So as machine learning continues to advance and there's a growing interest in the potential of the technologies to augment human cognition and decision making. From improving memory to learning to enhancing problem solving skills. So AI could offer a range of benefits. So now how do you see the potential of using machine learning algorithms to augment human cognition and decision making in the future? Can we do a deeper dive on this?

Benjamin: 00:12:31
Yeah, I'm happy to speculate as to what I think. Although I got to caveat everything I'm about to say and say. This is all just my own speculation. I'm not an AI expert or even a neuroscientist. But from my experiences, I would say that it will play an instrumental role in understanding who we are going forward. I mean, a lot of the best minds in AI, they believe or what they're really trying to do when they're creating some of these AI machines is recreating human intelligence. Human intelligence today, it's still like the greatest frontier of intelligence that we know about. And that's essentially what they're trying to recreate either in their labs or through one of their algorithms as well. How can we recreate some process that humans are really good at right now? And then hopefully expand upon that, improve that by, you know, how can we improve upon human intelligence as well? Now, I believe that these algorithms and these DBS devices, yes, they will improve cognition and yes, they will enhance some of our abilities. But we also have to remember that that's not what they're being designed for. They're being designed to help people live a little better than they could yesterday. But I'm sure that in the future, there will be people, whether it be by DBS or by transcranial magnetic stimulation or these other techniques that's being developed, that they will then try and use that to augment their cognition in one way or another. But it'll take a lot of careful learning on the part of everyone involved because if you target one area of the brain versus like, so in my deep brain simulator, this is one example, I have at the ends of each contact, at the end of each electrode, there's four different contact points. They're about, they're spaced about 1.5 millimeters from one another. And if I move from one, if I light up one contact point versus the one above it, it has a radically different effect on not only my symptomology, but also on my cognition and on my behavior as well.

Benjamin: 00:14:31
And the fact that I can tune things to such an nth degree and modulate things in such a way, it's a scary thing to consider. But it's also, for me, it's been very, I guess the only way I can describe it, it's been very cool thing as well. Just like feel all the differences that can happen when you go from one contact point to the next. I mean, it's really an experience like nothing else I've ever experienced in my life anyway. And unless you've gone through it yourself, I just, yeah, it's a unique thing that not a lot of people have had the chance to really explore.

Hanh: 00:15:06
Right. Now, how do you see the possibility of merging multiple machine learning techniques to generate more complex brain simulation?

Benjamin: 00:15:15
Well, even for myself, so I'm imagining the future that I'm hoping soon. Well, not soon, but maybe in 10 or 20 years, this DBS, while it'll still help my motor symptoms, the disease, the Parkinson's, the underlying pathology that I'm experiencing will still be continuing. And so there'll be other parts of my brain that eventually are more impacted than they currently are. At which point I might need another electrode placed somewhere inside of my brain. Now, each part of your brain, like your brain is like a, I guess one way to describe it is like there are different modules inside of your brain. And knowing where to target each one is the key to neuroscience really. It's what a lot of people are trying to do in the neurosciences. But I think in the future that, so for one example is like the beta waves that are coming from my subthalamic nucleus, that's the part of my brain that's affected by Parkinson's disease, that algorithm that runs that part, it can't be the same algorithm then that will run like part of my frontal cortex, let's say for example, just because it's all different modules, it's all run by different programs. That's kind of a crude way of describing it, but I think that in the future I'll have maybe multiple different leads in my brain that impact me, that are each run by different algorithms. And they'll need different signals and different codes to know how to work and know where to work and know what to do.

Hanh: 00:16:41
You mentioned that machine learning algorithms can diagnose and treat mental health disorders by analyzing massive data sets. So by identifying the likelihood of mental health issues and tailoring the treatment, machine learning could improve mental health care. So how do you think machine learning algorithms can help people with mental health issues or psychological disorders?

Benjamin: 00:17:07
Well, first part is in diagnosis. I mean, we're still very bad at diagnosing these diseases, and we're still very bad at coming up with tailored solutions for each person's diagnosis. And that's simply because of the fact that we have like 20, 30 different labels maybe that we give to these mental health issues. And yet each person is really a universe themselves for the simple reason that there's no two brains that are alike because of the connections inside of a person's brain and any kind of health issues that a person is experiencing affects them individually as well. That fact I think should be one that haunts kind of this whole industry because every pharma person, most of the biotech people, they're all trying to find like one solution to something like depression. But depression is not one thing, and depression is not localized in one part of the brain either. Yes, there are certain like key nodes in the brain in which if you put an electrode inside of there, it might stimulate some central part of the brain that would help a lot of different people. But it'll have a different effect on each person that it's actually put into. Even these DBS things, even deep brain stimulators in Parkinson's, for example. Parkinson's is something that we think we have a good understanding of. But if you talk to the experts, if you know anything about this disease, you'll know how varied it is for one person to the next. Currently, there's about 20 million people in the world living with Parkinson's. I think there are about 20 million different cases of this disease as well. Well, 20 million different origin stories, 20 million different drivers of this disease going forward.

Hanh: 00:18:44
So then how do you tackle something that's that complex?

Benjamin: 00:18:47
Well, in my opinion, you have to be able to... It starts by really enabling the physicians and clinicians that are treating these people to be able to tailor solutions to them specifically. That is where AI I think can have a huge role to play because physicians, frankly, they can't understand a person's brain well enough to be able to diagnose a problem in them. The far future is one in which you have a brain scan of some kind. That brain scan will then be able to have a perfect map of your brain in it. In that perfect world then, we'll have a tailored solution to that individual. So they'll know exactly where the breaks are in that person's brain, and they'll be able to dive right into that specific spot. Probably have some narrow robots as well that would drive some kind of stimulation deep, deep, deep inside of a person's brain, and then they would be able to simulate exactly what they need. Right now, we're so far from that world, but I think that that's the world that we should be all working towards and trying to drive us towards.

Hanh: 00:19:47
Very true. As I mentioned before our call, on the receiving end of dementia and Parkinson's, there's too many people, loved ones in my life, my neighbor, people from church, my family members, my in-laws, and so forth. So it is an agonizing journey. So I appreciate you to share your journey. There is hope, there is work being done, and to bring awareness and education that despite all this, we can learn to move on and embrace life as much as we can. So thank you. Okay. So, okay. Now, can you discuss any challenges or limitations that you face in designing and implementing the experiment, and how did you overcame them?

Benjamin: 00:20:35
Do you mean in this trial, the PD trial in general? So I guess one of the bigger roadblocks for me anyway, one of the bigger zoning blocks, has been my relationship with Medtronic. I mean, I understand why there needs to be a space between patients and the companies that run trials for them, but I can't help but think that our whole experience will be enriched and that I would be able to help them a lot more if I could have a direct line of communication with them. I mean, I understand why the FDA is so scared of opening those channels and of opening those kinds of lines up, but I think it'll be fundamentally important to actually making progress in these kinds of fields because companies, because I think patients are obviously a wealth of information, but not just for their doctor, it's also for the companies that are developing these new therapies because of the simple fact that, I mean, the closest thing that they have right now is the models that they use to try and recreate these diseases, but each of the models are woefully inaccurate in a lot of different ways. I'm happy to talk about those, but I think that the human experience and the human beings that are actually in their trials, they can give them so much more information than anyone else possibly could. It would then allow them to better help the next person down the line or maybe even better help the person in front of them. So I wish that there was some way that I could actually have that direct line between me and these device manufacturers. At the moment, it's still impossible, but maybe in the future someone will come up with a better solution for actually running these trials that enables that bilateral communication between me and the companies that are designing these products.

Hanh: 00:22:22
That's true. You mentioned that the Parkinson's cases are unique to the individual, so you can't have a static model, and that's what it sounds like. And these models should be driven by AI algorithms to customize to the unique person with dementia or Parkinson's. So I'm with you on that. So now, how do you think machine learning algorithms could help people improve their creativity or problem solving?

Benjamin: 00:22:49
Well, there's a lot of things that I think humans are not very good at, but we think that we are pretty good at. I'm trying to think of some specific, like one good example is like drawing. I think that the best artists in the world, they can recreate with something like Chat, GPT, or some of these other newer AI models, these new AI systems can do simply because of the fact that I mean, the fact that I can query it and generate 20 different pictures that basically like snap of my fingers. That's something that no artist in the world could ever possibly do. So I think that there's a lot of things that we could export. A lot of the creative processes could possibly be exported to these kinds of machines. However, we also have to keep in mind that they won't be because they'll never be able to be as innovative as we can be. They'll never be able to be as creative really as we can be. I'm thinking actually about the book that I'm writing right now with Alfonso Fasano. And I just can't imagine a world in which any kind of AI could recreate what we made there because there's a lot of novelty in the book, in the book writing process. There's a lot of novelty in creative processes in general. I just can't see us living in a world in which they would actually be able to do our job for us, so to speak. But there's a lot of little things along the way that they might be able to help us with. There's a lot of drawings in our book, for example, that I wish we could kind of use AI to help us better recreate some of the things that we would like to see depicted in the book.

Hanh: 00:24:19
Very true. It certainly can give us some boost in our productivity and give us some facts. But some often you still have to fact check and so forth. So I agree with you. Now, the development of machine learning algorithm that interface with the human brain raises a range of ethical consideration. So these include questions around informed consent, data privacy, and potential harm to the individual. So now what ethical consideration do you think are important to take into account when experimenting with machine learning algorithms that interface with the human brain?

Benjamin: 00:24:59
I think the biggest one is that first point that you made. The informed consent process, it can't just be a document that you signed at the beginning of the trial. It should be a living, breathing document that is constantly updated. It's online, first of all. There should not be paper forms anymore because I'm still bound by the trial document that I signed two years ago before I had this simulator even inserted inside of me. I'm so legally bound by some of the things that are in there and also the fact that I've forgotten most of what's actually in there. I like to think that I'm a pretty well-informed patient and yet even I can't possibly keep up with these reams of documents that we get from these companies that we have to then sign our life away to essentially. So making the informed consent process a living document, I think, would help in a lot of different ways. It would also maybe allow for some of that backing forth because I wish I could inform what was in that document a little bit more prior to signing it or even after I signed it so that the next person behind me or that even I could benefit even more than I currently am. So that would be the biggest one for me is making that informed consent process into a living document rather than a stale piece of paper.

Hanh: 00:26:12
True.

Benjamin: 00:26:13
Or like a stale contract, essentially.

Hanh: 00:26:15
Very good point. All right, so I want to talk about the day in the life of one of the busiest neuromodulation clinics in the planet. So can you describe what neuromodulation is and how is it used to treat neurological and psychiatric disorders?

Benjamin: 00:26:31
Sure. Again, I'm not the expert here, but so I went to Toronto Western Hospital. It's been a day shadowing my neurologist there, Dr. Alfonso Fasano. I've spent actually this past weekend with him. We're finishing up our book together. So I've learned a lot through him, through observing him and by kind of watching his field as a whole kind of take off. I've also been to many different labs in neuromodulation all around the world. I just came back from Boston last week as well, which I got this chance to spend some time with Andreas Horn. He's a podcaster, but he's also a Harvard professor and he's got a very interesting take himself on neuromodulation. But essentially what it is, it's anything that tries to change the outputs of the brain based on the inputs that it receives. So there's a bunch of different kinds of techniques, there's invasive procedures and then there's non-invasive. But really, I mean, everything we do in our daily lives is modulating our behavior in some way. And anything that has a modulatory effect on our behavior is a neuromodulation device. From the food you eat to the things that you see in your daily life, every single thing gets imprinted on your brain and that impacts then every other thing that you're ever going to experience in your life. So yeah, so coming back to what is neuromodulation or sorry, so neuromodulation is essentially that. So it's anything that has an impact on the way that you can see the world around you. So that can be something like TBS is just one example, but then there's things like shunts for treating hydrocephalus in which there's actually a port that's inserted into your brain so that you can then change the direction and flow of CSF inside of you, of your cerebrospinal fluid. So yeah, so that's one way. There's also transcranial magnetic simulation, which I mentioned before. There's focus ultrasound, there's gene therapy. I mean, there's so many different things that are coming online pretty soon, I hope anyway. That will be classified as neuromodulation devices. There's ECG devices that can now not only record but also stimulate just by having a cap externally placed on the skull.

Benjamin: 00:28:54
So it's really a wide field. It's really wide ranging as well. However, there's also a lot of danger that comes in having all these new technologies and just giving them over to the public because no one really understands what's going on inside of another person's brain. And so that's why you really need somebody who's skilled looking after you if you're going to allow somebody to do that to you. Because I fear, for example, for a lot of people in the world, I mean, I've seen what happens when DBS, for example, goes wrong. And those instances make me very cautious about how we actually do this going forward because we can't just let anybody do whatever they want. It has to be regulated. It has to be controlled as well. But what is the best way to do that? We still haven't found exactly what the best way is. But I'm hoping going forward that we learn from our collective experiences, we get a little bit smarter each and every day about how we actually do these things.

Hanh: 00:29:57
So the field of neuromodulation is evolving and new technological advancements and innovations emerging all the time. So these developments are changing the way how we think about and treat neurological and psychiatric disorders. So can you share your thoughts on some of the most recent advancements in neuromodulation technology and how they are impacting in this field of psychiatric disorders?

Benjamin: 00:30:25
Sure. So let's say that one adaptive DBS is definitely at the forefront of a lot of these things. I mean, almost all these systems, if they're interfacing with our brains, they should be adapted. They should be what's called a closed-loop device because your brain is a closed-loop machine as well. I mean, so if you want to interface with it, you need to have something that can speak its language kind of. But then the other thing is the size of the devices as well. I mean, DBS is still a very blunt instrument in which a lead that's six centimeters long, I believe it's about 1.5 millimeters in diameter that gets inserted all the way through a person's brain. Now that causes damage along the way. So I'm hoping in the future what will happen is that much thinner devices, maybe they'll be based on graphene technologies, which are the smallest and thinnest metal, the most conductive metal that we could possibly envision. I'm hoping that soon enough those kinds of technologies will emerge as well that will allow us then to penetrate much deeper into a person's brain and tune whatever the simulator is in a much more precise way. Because like I said, it's very much imagine an olive right now. So my subthalamic nucleus is basically the size of an olive. Now imagine you have a pen or a pencil or maybe a straw even and it punctures that olive. That is essentially what we're doing right now with these latest DBS systems. In the future though, the idea is that something will come along, it'll hover kind of over the olive. So it'll be placed on top of the olive and then nanobots guided by machine learning programs will then come along and they'll extract the graphene tips that are so thin that you can't even see them.

Benjamin: 00:32:18
They're inside of the lead then and they enervate the target area in a much more precise way than we currently can do. I think that that will be a very exciting time, but we're still a long way from doing that. But there are some companies now online that are working on those solutions. Hopefully in the next 10 years or so, we'll see their products and then this field will really be able to take off.

Hanh: 00:32:43
So as the field of neurology and psychiatry continues to advance, there is an increasing curiosity surrounding the potential of neuromodulation as a treatment for neurological and psychiatric disorders. Well, given the limitations and side effects of traditional drug-based therapies, some experts suggest that neuromodulation could offer a safer and more effective alternative. So what is your thought on this? Are you hopeful? What's your take?

Benjamin: 00:33:16
Yeah, I'm very hopeful. I think that that will be the future for some people. However, chemicals will always play a role in what we're doing and pharmacists and big pharma will always be there as well. Neuromodulation, it's a very scary thing, but it's also very full of possibilities as well. But like I said before, we have to be very cautious about how we are actually doing this because there are so many examples of people that received one of these techniques. And yet, for example, they did not have the follow-up care that's necessary. Getting that crucial follow-up care is very, very important to actually developing and living with these conditions. For example, it took me five months after my surgery to recover properly. And then it was a long process. The programming as well took a long time. I mean, there's a lot of days where I just spent in my clinician's office with him. He had his iPad or his tablet in front of him and he was trying to find the right parameters for me. That was something that was very difficult to actually get through and required a lot of support as well. So somebody does not have the support system in place and it's very difficult. And then we also have to think about access to these devices. Right now, it's still very much restricted to the West and to the Western world, really. In the future, I'm hoping that someone will find a way to actually make these things more affordable for more people as well, because just Parkinson's alone, there's so many people out there in the world who could benefit from technology such as this, but they just don't have the access. They don't have the right people around them and then they don't have the funding to actually go out and get these kinds of things. It's a very expensive procedure as well.

Benjamin: 00:35:04
And so for all those reasons, I think we have to be very careful about how we actually do this, because if we just let anybody once get one like this without the proper care around them, without the proper team, without the support staff that they need, then probably have an endemic of people who are out there who are not getting the kind of care that they should be getting.

Hanh: 00:35:26
You touched on the ethical concerns earlier, but let's go through in detail. The ethical concerns and considerations surrounding the use of neuromodulation technology in treatment mental health disorders. What is your thought on that? I know that you mentioned previously that you were hopeful the contract would be a living document. Are there any other ethical concerns?

Benjamin: 00:35:56
I mean, there's a ton of other ethical concerns. A lot of them stem from just allowing like anybody wants to access these devices as well. But that was just what I just spoke about as well, because if anybody wants to can then can pick up some kind of like DBS devices, insert it into them, and start playing around with it. We'll learn a lot. That's for sure. I mean, that'll be one way to actually make progress. But at the same time, it'll destroy a lot of lives because there's people out there that that is playing with your brain. Playing with your brain is not something that anybody should be able to do. It should be something that's very difficult and very rigorous as well. Because not only does it bring me time to adjust the simulation, simulation then needs time to adjust your brain. That's what I meant by closing the loop before. There's a very intricate dance kind of between yourself and this device. And it takes time and it takes patience. And something that I don't think we'll ever be able to really speed up process of how we really do this properly. So that would be one big ethical concern for me is ensuring that people who have access to these kinds of devices, they take their time and they do it slowly.

Hanh: 00:37:11
So how may neuromodulation help us understand the brain and the causes of neurological and psychiatric disorders?

Benjamin: 00:37:21
So the cause is something that I think will be very difficult for us to actually ever get at. Because often these causes are 10 to 20 years into the past before any symptoms ever become apparent. How do we actually go back in time in terms of determining what is the actual cause? I mean, there are some epidemiological factors that are, of course, involved in this. For example, I mean, in MS, we recently learned that EBV, the Epstein-Barr virus, plays a huge role in whether or not someone will go on to develop multiple sclerosis. That's just one example, though, of kind of environmental or epidemiological factors that we need to start considering if we want to get at the cause of these actual diseases. And yeah, I don't think neuromodulation will be able to help in that regard. It will only be able to help us deal better with the symptoms that people are living with, help them live a little bit better lives down the road.

Hanh: 00:38:20
So can neuromodulation technology be used to improve cognitive or physical performance?

Benjamin: 00:38:28
Yeah, it can. Well, physically, I mean, I feel much more ape-like. So I remember that there was one point after my programming began in which I told my doctor and my whole team that was around me that I felt like going for a run in that moment. It was something I was not able to do before, but it was something I had the sudden urge to go out and do. And I felt as though I probably could have done that as well. But my team around me, they were smart enough to not let me go out and just run about and do whatever I wanted. So yes, it will definitely help improve physical mobility and help people enhance their physical performance as well. But the flip side of that is also the... And then it has also helped me in terms of like being able to smell better and taste the world around me as well. But then also my cognition, I feel like, and this is just subjective, but I feel as though it has improved. I mean, the subthalamic nucleus where the electrode in my brain is, it's involved in so many different networks and so many different processes in the brain that you can't just say like, Oh, I just want to turn on his mobility, his ability to move about the world a little bit better. That's not something that we have the precision or the know-how to be able to do right now. And so there will always be some kind of side effect or some... There will always be a knock-on effect to whatever you turn up in a person's brain that I don't think anytime soon we'll be able to understand an individual well enough to know exactly where to finally tune this person's mobility or this person's speech or behavior or any aspect of cognition.

Hanh: 00:40:12
Wow. Well, what a great wealth of knowledge and the depth that you share today on this topic. So how do you see the future of neuromodulation evolving and what are you hopeful or what's the most promising areas of research and development in this field?

Benjamin: 00:40:30
I'm hopeful that in the future we'll have much smaller devices, for one, that will be able to innovate and target the brain in a much more precise way than we currently have. They will all be run by these adaptive algorithms as well. And while they won't be used to help diagnose, they will be able to help treat and help thousands... I'm hoping to help millions of people eventually live a little bit better than they can, currently.

Hanh: 00:40:56
All right. Do you have anything else that you would like to add?

Benjamin: 00:41:01
Only that I hope that people that are listening will really take to heart that one message that every one of these people who will get diagnosed with any kind of illness, it's really you have to be able to treat them and look at them like they're individuals and that their disease is probably unique to them in one way or another. I mean, we have labels that we use and we kind of slap these diagnostic bumpers triggers on people and then they kind of like half-hazardly tell them to go about their day as if nothing happened. So you have to remember that every time you do that, there's a huge psychological toll that the patient has. And it's not only on them, it's also on their family as well. I mean, each person, there's a universe of people around them as well that we need to be considering and that needs to be cared for also.

Hanh: 00:41:49
Very true. Very true. Thank you so much. So in closing, well, are you ready to enter a world where machines can control your brains? It may sound like a science fiction, but rapid advancements in biomedical science are bringing us closer to that reality every day. This technology may impact the concept of free will and human consciousness. Can you imagine having a digital puppeteer controlling your every move? It begs the question, where does the line between human and machine begin and end? So today, in our conversation with Benjamin, we explore the use of neuromodulation, the groundbreaking technology that revolutionized the treatment of neurological and psychiatric disorders. It's like hitting a reset button on the brain, opening up new pathways to health and wellness. Think of the possibilities for improving the lives of those living with these conditions. So what's in store for us in the future? Will we become cyborgs or find a way to integrate technology with humanity? The possibilities are endless and the potential for improving lives is very exciting. So let's continue to push the boundaries of what's possible and unlock the mysteries of the brain. And thank you so much for joining us today. Next week, so please join us again, Thursday, March 9th, 11 a.m. Eastern Time, Chat GPT, AI, Automation, Revolutionize, Senior Care. Thank you again and see you next week.