Below the Radar Transcript
Episode 76: Neuroengineering and Brain Plasticity — with Faranak Farzan
Speakers: Paige Smith, Am Johal, Faranak Farzan
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Paige Smith 0:06
Hello everyone, I'm Paige Smith with Below the Radar, a knowledge democracy podcast. Below the Radar is created by SFU's Vancity Office of Community Engagement and is recorded on the territories of the Musqueam, Squamish and Tsleil-Waututh peoples. Today, we have guests Faranak Farzan, a faculty member in SFU's School of Mechatronics Systems Engineering, and the founding director of eBrain lab. Faranak works in the fascinating field of neuro engineering, innovating tech solutions to better diagnose and treat mental health issues. Today she speaks with am Johal about the several research initiatives she leads at SFU and beyond.
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Am Johal 0:50
Hi, everyone, welcome to Below the Radar, really excited to have Dr. Faranak Farzan with us. She's an assistant professor in the School of Mechatronic Systems Engineering and the chair in technology innovations for youth addiction recovery and mental health as well as a whole series of other things. Welcome Faranak.
Faranak Farzan 1:11
Thank you so much.
Am Johal 1:12
Yeah, wondering if we can just begin. Why don't you introduce your work a little bit and how you found yourself coming here to SFU to work on your really interesting research.
Faranak Farzan 1:25
Yeah, thank you. It's a pleasure to be here Am. Thank you for the invitation to be part of this. So as you mentioned, I am in the department of the Faculty of Applied Science School of Mechatronic Systems Engineering. Having said that, I have a background in both engineering and neuroscience. So I work in this domain of neural engineering, some may call it. So, going a little bit back and going over my background I did my electrical and biomedical engineering in McMaster University, it was one of the first dual degrees of combining the two and also the the minor in Psychology at the time that I went in and I got my PhD from University of Toronto in the area of biomedical engineering and medical science. That's when I started getting into looking at the brain of individuals who have psychiatric disorders with technologies such as non-invasive brain stimulation that I went in, and I did a postdoc at Harvard Medical School and in the domain of Cognitive Neurology. That's where I started combining technologies with each other, neurostimulation, neuro imaging, and used it toward creating and, and exploring the impact of neuro stimulation for treatment of neuropsychiatric disorders and mental health. I took up my first faculty appointment at University of Toronto, so I was an independent scientist at Center for Addiction and Mental Health and assistant professor at University of Toronto.
Faranak Farzan 3:02
So I was a neural engineer in the psychiatry department. So the idea was to leverage technology in order to advance the treatments and the solutions that we have in order for betterment of mental health across the lifespan really. And then joining SFU I was recruited for a chair and endowed chair in technology innovations for youth mental health and addiction recovery. The call for opening this position, I understand, was important because of the opioid crisis of opioid addiction that we had in the region, and mental health as being one of the underlying factors that contributes to this. So I was positioned in this very transdisciplinary position to bring visions from engineering and neuroscience and computer science and really combine disciplines to try to innovate technologies for this cause. So my program of research right now at Simon Fraser University is really heavily focused on using neuro technology and neuromodulation in particular, to study the brain and use the concept of plasticity to design new non-invasive treatments for youth depression and addiction. There are several national hats in which I work with, with scientists and clinicians and technologists across Canada and globally, to also collect large volumes of volumes of data in individuals going through various treatments, particularly for depression, to to also inform how we can streamline the process of matching patients with the right treatment, which is a hurdle in in mental health in general and more specifically in depression. It's an area that needs a lot of work and I can get into that with further questions perhaps, but just to paint a big picture. So I'm part of this national initiative called Canadian Biomarker Integration with work in depression and I work with many colleagues and investigators across Canada and leading the initiative that is responsible for collection of large volumes of brain data to inform some of these research that we conduct.
Faranak Farzan 5:24
Yes, and here locally at SFU. We do have, we work we have, I have I lead a lab I founded and direct Center for Engineering with Brain Research, eBrain lab, I can call it for short. And in eBrain lab, we have students coming from computer science, neuroscience, psychology, particularly engineering. And we do across all these various fields to develop these technologies for advancing the treatment and diagnostic approaches.
Am Johal 5:58
Yes, for many of our listeners, this is going to be a very fascinating and emergent form of research, you know, people may have had an MRI or a CAT scan, with injuries or other health issues. But in terms of the relationship of the forms of technology that you're using, I'm wondering if you can maybe speak a little bit about the field and kind of recent developments in it just to give a sense, because I think it's a fascinating area. And you've also done work related to AI, machine learning, and how certain forms of technologies can work alongside other forms of antidepressants or alternatives to antidepressants in terms of how technology can, can intervene. So it'd be great to hear a little bit about the recent history of the field or the area that you're particularly working in.
Faranak Farzan 6:56
Yes, so I can highlight a couple of advancements here. So first, I start by the context and what the need is in this domain. So let's take depression as an example. It's an area that we've been heavily focused on recently. So one of the challenges in treatment of depression across the lifespan is connecting patients with the right treatment as early as possible. So what often happens is that patients go through a trial and error approach with their physician, or through services to find out what works for them and that process can take years. What has been missing really being some sort of an objective test. So you mentioned MRI, or a blood test, or it could also be a simple sensor device that you wear on your head and collect your brainwaves. Once there's something objective that we can collect in the doctor's office that would then say, with X percent accuracy, by 80% chance, you're going to benefit from this treatment. So that has been it's missing is not really there yet. And there's a lot of research right now, in part focusing a bit on more machine learning and leveraging the power of machine learning to facilitate that. And through the work that I've been doing with some of the national initiatives in particular that I mentioned, we've been able to collect large volumes of data on patients going through antidepressant treatments. And we recently demonstrated that in fact, machine learning and data collected from patients non invasively through sensors can be used to predict whether a particular patient is going to respond to a particular treatment ahead of time. So at the beginning before the patient even starts getting treatment, and this can and this, this is one example of how machine learning can be used positively in this domain to assist physicians, not to replace physicians. So that could be something that people may fear, but just to assist physicians in making more informed decisions, we have a long way to go. I mean, by no means we can say that oh, so the AI is doing that already. We have done this for one type of antidepressant or a couple of types of antidepressants right now we're expanding that work to also include other classes of antidepressants, you can have pharmacological, you can have behavioral therapy, you can have brain stimulation. And we are very much engaged in providing these objective predictors of response to treatments for all classes of antidepressants and, and generally broadening it to include other kinds of mental health illnesses as well. So this is one area that AI has shown concrete promises, if we can call it AI, we can call it machine learning has shown concrete promises and with more research, it's quite feasible and also the methods that we have combined with machine learning includes this non invasive and rather inexpensive ways of recording data from the brain, which are far cheaper than MRI. It's called electroencephalography, for our audience here EEG in short, and this method is far cheaper and does not require a giant scanner. Right now there are portable versions of it. So it can be easily placed in a doctor's office potentially, and, and use that to sort of inform what is the best course of action for a given patient to reduce essentially with the ultimate goal of reducing the time that someone spends in untreated depression. And by doing so we really reduce a lot of burden to the patient to the society and ultimately costs that are associated with people going on with untreated depression, that can lead to suicide, it can lead to addiction. So a lot of times, what we see with addiction is self medication, in part and that leads to overdose and substance abuse and all things like that. And untreated depression is a big trigger of that. So we're hoping that in this way, technology can really help.
Faranak Farzan 11:14
So this is one way Am, that technology can help. A second way is through developing technologies that can interface with the brain, and target areas that are either somehow under functioning, over functioning, and somehow deviating from normal functioning with more targeted treatments. So, a class of treatments are pharmacological and we all know that. It's the same thing in depression. So the pills, you take it, they're good, they help quite half of the patients who who kind of benefit from it, but in some others in some groups of patients and the proportion is rather large, they may either experience side effects because of the systematic effects of the drugs or they may not or they may just not benefit from it, in part because it's just somehow their brain is not metabolizing, the pharmacological treatment or it's just, it's not the right way of treating, treating the condition. So the second class of technology that really is helpful is this more targeted, non pharmacological, more targeted brain stimulation therapies that we're working on, that allows us to focus on a particular brain region whose functions might be impaired, and through a targeted approach, tries to normalize the function toward treatment. So this, this, we're experimenting a lot with this in my program of research in youth with depression, they're the ones in whom antidepressants, for instance, have, you know, more side effects. There's a blackbox warning from FDA on some antidepressants for those 24 years and younger that it could create suicide ideation. And since for them in part, there is more need in terms of alternative treatments. So we have been experimenting with a technology called transcranial magnetic stimulation. For our audience I can abbreviate that as TMS for short, so that we can refer to that so this form of technology is non invasive, and is based on electromagnetic stimulation of the brain. So you can actually use it to target a specific area, and and, and modify its function through repetitive stimulation. So how does that look like as a as diagnostically is that you sit in a chair, you have this coil that is held over part of your brain that we're trying to study and you hear this tapping and feel this tapping sensation on your head. And what this technology is doing is stimulating a population of neurons that are cells in our brain and triggers them and activates them.
Faranak Farzan 14:01
And if we then combine that with, for instance, a monitoring device sensors that can help us listen to the brain activity, then we can actually look at the function of that particular brain area. diagnostically we've been using this technology to understand in those youth who do not respond to pharmacological treatments, what is it different in their brain compared to healthy normal youth. So if one area is working too much is one area over connected to another area, so what is going on so and recently published on that work came out in 2020, where we actually show there are concrete differences. So we can see it. It's observable with this methodology that I described and it seems to be particular to the front part of the brain in the right hemisphere for instance. Now this is the diagnostic part, then taking the same technology again, we can trick it a little bit and apply it more repetitively over multiple sessions. So here, for instance, four weeks of daily sessions of treatment targeted to that right or left part of the brain, in order to modify the circuit, or the regions that we identified as having impairments. And then that's when we actually see a reduction in symptoms of depression in youth. So we've just finished a trial and we published on that just in 2019. And there's one coming up within 2020 that we're working on that we actually show that using this methodology, those youth who do not respond to, to pharmacological treatments or refuse to receive pharmacological treatments going through this alternative treatment in non-invasive brain stimulation, their symptoms drastically reduce, and some of them become depression free. So this is another aspect of our technology, and neuromodulation technology, we can call them, is proving useful for being leveraged for helping mental health aspects.
Am Johal 16:11
How often in the research, do you combine the use of technology with other forms of treatment? Or have some studies been done where they're in simultaneous use?
Faranak Farzan 16:23
Yeah, absolutely. So in fact, there are studies that suggest that some of these technologies, if combined, they can add a benefit. And in fact, we just conducted a trial where we combined TMS that I've just mentioned, as a form of treatment with youth with a computerized cognitive training. So the idea being that in depression, there are two first lines of treatments. One is cognitive behavioral therapy and the other one is pharmacological therapy. Now, cognitive behavioral therapy, a lot of times when combined with pharmacological treatments have shown added benefit. So it's sort of essentially working with behavior. Whereas the pharmacological treatment, other treatments could be working more centrally from inside, inside the system. So we did combine in this particular trial, cognitive, a computerized version of cognitive behavioral therapy. So that is to overcome the whole accessibility in part to one on one psychological assessments that can be expensive to subparts. That's something I can get into a bit later.
Faranak Farzan 17:41
But you're absolutely right, that combinatory treatments do have some added value, particularly when it comes to non-invasive brain stimulation. If for instance, you're stimulating the frontal part of the brain, and you may be engaging your participant in doing some sort of a task that engages that part of the brain, either during the stimulation or shortly after, there is research being done in that domain that shows benefit. Now, there needs to be, you know, placebo control treatment trials to fully ascertain how much is the added benefit? When do you combine them? How do you combine them? So those are all things that take time and you're trying to address them in research, but it's one area that we're really working on now.
Am Johal 18:25
Now, I imagine in the field when you're combining technology with different forms of treatment on neurological disorders and other areas, there's in the field itself, the broader field, there are probably ethical questions that come up in the use of technology. I'm wondering if you could mention one or two, sort of broadly, in the field that have been sort of under consideration or questions that come up in the use of technology in this way?
Faranak Farzan 18:56
Yeah, there are positive effects and negative effects. The positive effect is that a lot of times technology allows us to offer treatments or interventions or solutions to a broader group of people. So in terms of inclusion, I think technology helps us be more inclusive. For instance, thinking about people who are living remotely, and they don't maybe have access to a psychologist or clinicians who can offer cognitive behavioral therapy, should we make that computerized and accessible, accessible somehow through the web? So that they can see their psychologist more online and through the web? If access to geographical location is a bottleneck or if expenses are a bottleneck. In this domain I think technology's really allowing us to be inclusive. Another positive effect, back to the original idea of machine learning or AI helping is again shortening the time spent in unsuccessful treatment trials. So that is another aspect that I think technologies can really be useful, right? Now, there's always a fear of every time we leverage technology to do something related to improving mental health or just mental health or health in general, every time we use technology to solve a problem or challenge, it can, it can also be misused or used for other purposes outside of the original purpose that it was created for.
Faranak Farzan 20:39
So, so for instance, we are using treatments to maybe improve cognition, right, in, in in patients who have cognitive impairments. So we can be using neuromodulation technologies applied to a particular part of the brain to improve cognitive deficits, for instance. But then the same technology can be used to create superhumans, for instance, and just be applied in healthy normal controls, to give them an additive advantage in performing the cognitive task, and then the question becomes who should receive that? Who will have access to that? Then is it a fair society if some people have booster treatments. Or so an analogy could mean doping in athletes. Would that be considered sort of cheating if you have access to these kinds of technologies? So there are, for instance, non-invasive brain stimulation being experimented with for creating more focus in gamers. So there's always that other aspect of argumentation that comes into picture. Now I think what is very key and that conversation is happening is to have regulations. So kind of like how to use the internet, the internet has so many positive things, but also can have negative things. So regulations are absolutely key here. Now in the area of medical technologies. Luckily, there are a lot of regulations, obviously, things need to become approved, and go through very rigorous assessments before getting into the hands of end users and patients. So that is, that is I don't foresee necessarily a problem as we're offering treatments to patients. Now, mind you, there are always controversial treatments out there that maybe they don't do a placebo controlled trial. And then they become more interested in making money out of the technology or... So that those always are there and I think that has nothing to do with technology. But the other side, we need to maybe be more careful and being more regulations around or the consumer side of things that as these technologies help the patients in need, what is the next step? And how are we going to regulate it? How technology can be embedded in our lives just for healthy individuals in general, to advance that side. So that that's my view on this. And it's a very important topic that needs to be paid a lot of attention to and we need regulations in place.
Am Johal 23:10
Now, around looking at these kind of engineering perspectives, or you know, you think of protracted existential crises like climate change, and people are talking about geoengineering, for example, similar with health related issues, technologies can be brought in and there's also the aspect of commercialization and other agendas being brought to the table. So you have figures like Elon Musk and others and I'm wondering, how in that, in the areas in which people are attempting to commercialize these technologies, what are some of the implications are or specifically people like Elon Musk?
Faranak Farzan 23:50
Yeah, yeah. So Elon Musk is an interesting one, I do teach a course on neuromodulation at SFU to engineers and, you know. So visionaries like Elon Musk make things that look a bit science fiction, look, look more tangible and real. So, that he just recently published or how to how do you call it? The press release on delink, which is the newest, he call it Fitbit of the brain, I think and, and what he created is like this very elegant, I suppose, we can call it a surgical robot that actually implants this chip in the brain. Well, he demonstrated in animals for now. And then this chip sort of has sensors that goes inside the brain and then connects with the tissue and then records and, and so now, this is a feasibility demonstration. Obviously, at the broader picture of things. The novelty here really is just putting all the pieces together and showing that this is possible for instance, through such a you know, packaged system of the surgery robot and the Fitbit that goes inside and that the animals on which this was demonstrated on are healthy and alive and nothing bad is going on. Now, the positive side of seeing things that we saw with Elon Musk's demonstration is that it's no longer sci-fi, so things are going forward and our brain is going to be connected to the computer. Now, what I think will happen is that we need, we need a long way to go, I mean, the brain is a network. So it's not just one region that you put only one sensor on, and it's good to go, it's gonna solve everything, it's gonna solve depression, and solve blindness and solve all kinds of issues like that. It's not that simple. So this is a proof of principle that shows it's possible to have a Fitbit in your brain. But what really needs the advance is at the scientific level at our knowledge of how the brain works. So it's not that simple encoding of memories, or it's not that simple where exactly in the brain depression originates from, there are many scientists working on understanding that there are many treatments that we're working on to offer and that we still have a fraction of understanding of how the brain works. So what will need to happen in the future, is that it's fantastic that the science is advanced for us to start not just imagining about how it would be like computers in our brain. But we need a lot more research done in the area of where is it in the brain that a depressed patient who's not responding to other treatments needs, is not working well? So where is that? So that is the million dollar question. And then we can use the technology that we then see with Elon Musk to sort of go to that area, or to design things, perhaps to offer treatments that way. Now, at the society level, it's true also that going beyond mental health, we are getting closer and closer to computers, I mean COVID-19 and the virtualization of social meetings, and everything like that has made this digital world more and more closer to our brain and it's true. And if and, and, you know, there is no escaping from that, that our brain needs to connect with this digital world. And there would be a positive connection. And that would be that perhaps a lot of the deficits that our organic brain may have, or the shortcomings of our organic brain around perhaps our memory fading with time. So you can think of Alzheimer's disease and things like that, or some of these unfortunate conditions of neurodevelopmental disorders, and then mental health and addiction. Those things are things that perhaps these technologies can help us a lot with, it becomes to be determined how for a healthy brain, these technologies are going to sort of push us to the next stage of being human. And that is our interaction with this digital world. And with the internet in a more seamless way.
Faranak Farzan 28:11
Right now we do it by still typing and thinking and, you know, but I think it's going to get more and more seamless with what we're seeing. And I think people like Elon Musk, they're bringing the technology closer to where we are but we need to also have a lot more research done to understand where do illnesses originated from.
Am Johal 28:35
Yeah we have philosophers of technology here at SFU, like Andrew Feinberg, that can weigh in on these questions as a former student of Herbert Marcuse. I studied with Katherine Malibu who's written about plasticity in a philosophical sense as an idea coming out of neuroscience. And also, I've been thinking about these questions a little bit more around the brain myself having had a seizure, a stroke and brain surgery over the last two years. Luckily, everything ended up alright, but these questions around brain plasticity, that the brain is plastic and can rewire itself. These are questions and thinking that you're trying to apply technology to and wondering if you can talk a little bit about how the use of technology and its sort of connection to plasticity are working themselves through research and other questions.
Faranak Farzan 29:33
Yeah, yeah. So plasticity is what makes us very adaptable, as a species. So and it's a very, it's a concept that we apply a lot in when we create interventions. Particularly I mentioned this class of neuromodulation technologies that we're experimenting with, TMS keyword, I mentioned in regards to youth depression and creating these treatments.
Faranak Farzan 30:00
So, the reason these treatments work are important because the brain is plastic. And so if you do perturb the brain one time, maybe nothing really happens. But if you reinforce this perturbation over repeated sessions, the brain has this capacity to start rewiring itself. And that is something that we have leveraged way before creating treatments. And, and that's something that also allows us to treat conditions is that function of the brain neuroplasticity. Now, plasticity itself can also be malfunctioning in some conditions. So there's a possibility of that as well that some conditions might be associated with too much plasticity. And some conditions may be associated with low plasticity. So those are areas of research that some investigators also, for instance, are looking into, in particular in our research area. So we are harnessing plasticity to make these long term changes. I mentioned the idea of combining treatments, for instance, with transcranial magnetic stimulation and computerized cognitive training. And the underlying concept here at play is that when we repeat that over time, and we do it daily, that's when the brain starts to change. And what we're really able to see is with these neuro monitoring devices that we have, we can actually monitor the changes over time. So in some of our work, that we have actually recently been accepted for publication, we actually do show that the brain changes. So before the treatment, these neuronal circuitries look, in certain ways, but then after two weeks of treatment, they look slightly different. So there's this change that happens, right. And this is important, a very powerful mechanism that the brain has the capacity to do, and it does not necessarily go away with aging, it may get a little bit weaker as we get older and older. But the plasticity does exist across the lifespan. And this is what makes it really exciting for us to use technologies. So for instance, it's possible to stimulate one part of the brain concurrently with another part of the brain. And through repeated application of such treatment, make these two brain areas start connecting with each other. Now at the big picture level, there might be conditions under which the left or right side of the brain, maybe they're not talking properly, there might be conditions under which perhaps two brain networks are not talking properly, by tailoring these neuromodulation technologies. And by sort of reinforcing these areas to start firing together, or functioning together, we're able to actually create treatments and create new connections in the brain, which sort of goes back to the whole idea of ethics of neuroscience and neuroscience of ethics, right? Because if you're able to change people's brain and maybe with that you even change their personality, or, you know, and their behavior, and the question is, so how can we make people be accountable perhaps, for some of the conditions that they have. So these are very interesting areas also that the more and more we understand how there are concrete neural circuitries in the brain that are responsible for pretty much all human behavior. And also, we need to revisit ethics. Okay, so what so we need to provide these treatments equally to everybody, we need to understand better you know, how much of what we see behaviorally is that we have full control over we are free beer, or how much of it is driven by our brain circuitries and through neuromodulation and plasticity in the brain, we can direct them to the right direction. So it could be either getting healthy from having conditions like mental health and addiction. It could also be you know, for a healthy individual wanting to, you know, be a certain way. Because we're all born with a brain you're born with, but if it's plastic, and we have the technologies to change it. So we know at the philosophical level. So what can we do with that knowledge? Right?
Am Johal 34:26
What are you most excited about in your research that you're undertaking right now?
Faranak Farzan 34:32
Yeah, so the two areas that I mentioned at the beginning around matching patients with the right treatment and creating new treatments for youth with depression and addiction. Those are areas that I'm very excited about. So we also do, I'm also very much into community engagement type of research where we do not create these technologies just as scientists wearing our scientist hat and thinking what the patients need. I do engage in community engagement campaigns to take the perspective of people with lived experience. For instance, I work with partners, such as John Wilkin Academy in Surrey, to create some of this computerized cognitive training that I mentioned earlier, with their input.
Faranak Farzan 35:22
And so that makes them to be more adherent to the treatments also, if we create technologies, that is what they need. Or what they enjoy adhering to or being compliant to or using on a daily basis. There is a higher chance that they would use these technologies. So that's another area that this community engagement piece is very exciting. To me, at least. And I see this, this concept of co-creating technology with all stakeholders, I think back to the regulation, ethics of things, when you co-create technologies with taking into account the needs and wishes of all stakeholders that are involved, there's a better chance of creating something that is both ethical, and also it is something that will be used and would actually be scaled to, to benefit Canadians and globally, people suffering from various conditions. So this aspect of my work, where I take this co creation aspect and engage various partners into this and bring various disciplines also, I mentioned my background in research, it really, I really do work with clinicians, physicians, engineers, computer scientists, to to lead this type of work. And that opens up a lot of interesting conversations. And that's in my, in my opinion, is an exciting step that is happening in this field. Areas that didn't know anything about each other are now connecting with each other. So there's an area for instance, personalities are something that we're told that you're born with. But there are a lot of personality disorders for which sometimes treatments are limited. But if we can pinpoint the brain circuitries that are perhaps underlying those, those personalities, we can create treatments for them. And we can offer solutions to a lot of people who might have been suffering from conditions that were otherwise considered untreatable or, or not having that much choice of treatments for. So offering solutions where there was none. Is what gets me going. And and I think the fact that making people, the people suffering, be much shorter in time through using machine learning, and some of these technologies that we have, and creating new treatments, I think that's something that's very exciting. Mental health and addiction issues take many years of life from individuals, not only individuals, but also their caretakers, it can be very hard.
Faranak Farzan 38:05
Historically, it's been very stigmatizing. So a lot of people have now been even talking about it. So you had a broken leg, everyone recognized or you have cancer, everyone has recognition for that you get a lot of empathy. So with mental health, there has been a lot of secrecy. And it has been a lot of, Oh, you don't know where to ask for help. So people have been suffering in silence. So if there is one thing that I hope our work would do is to break that silence and it would bring the people of different disciplines together to create something that would be of use to people who suffer.
Am Johal 38:41
Do you think that in the future, there'll be opportunities to combine technological interventions with harm reduction approaches, particularly related to addiction?
Faranak Farzan 38:53
Yes, yes, absolutely. That's one area we're also experimenting with. So we started so we have rolled out the computerized cognitive training program that I mentioned, we actually dealt with youth undergoing addiction recovery. And, yes, I mean, the next step would be okay, how can we potentially its effect, can we combine it with other harm reduction, or can we even combine neurostimulation with other harm reduction to shorten the amount of time spent in, in addiction recovery programs, or not to shorten, but even improve the benefit of existing programs and sort of give to individuals more quality life. Because, you know, at the beginning, recovering from addiction is like a very difficult task and so many people relapse, so if we can somehow combine treatments, to to, to sort of give it a more super treatment. That is absolutely an area that we're working in. We're we're we're actively in it with depression. So we have actually run trials and with addiction we're, we've done the first step of creating a computerized training and then the next steps would be combinatory treatments also.
Am Johal 40:10
Faranak, thank you so much for joining us on Below the Radar. It's a really fascinating area of research and I look forward to following your work. Thank you.
Faranak Farzan 40:19
Thank you, Am. Thank you for inviting me.
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Paige Smith 40:25
Thank you for listening to our conversation with Faranak Farzan about the exciting research being done in the emerging field of neuro engineering. Thanks again for tuning in and we'll see you next time.
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