Brain Innovation: From Science to Scale and Impact

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Welcome back to our new season of Brain Talks. Now,
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every year, groundbreaking discoveries deepen our understanding of the brain
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and create new opportunities to improve brain health. However, scientific
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excellence alone is not enough. Transforming research into solutions that
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reach patients requires collaboration across disciplines, sectors and borders. from
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fundamental neuroscience and clinical research to innovation, policy, and implementation.
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We're beginning this season of podcasts by introducing the central
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theme of this year's Brain Innovation Days, which is science, scale, impact,
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showcasing progress, confronting challenges. And to do that, we've brought
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together three leading voices from research and clinical neuroscience to
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explore what each of these three pillars really means in practice.
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We'll be discussing how scientific discoveries become innovations, what it
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takes to scale promising ideas, and how we can ensure
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that progress ultimately translates into meaningful impact for people living
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with brain disorders. So today we're setting the stage for
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the season ahead by exploring the opportunities and challenges which
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are shaping the future of brain innovation and introducing themes
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that we'll be examining in greater depth in future episodes.
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So let me introduce our excellent panel today.
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It is an absolute.
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Pleasure to join together to talk with Thomas Ryan from FENS,
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the Federation of Neuroscience Societies, Martin Kass from ECMP, the
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European College of Neuropsychopharmacology, and Frederik Deschebec from the EBC,
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European Brain Council. Martin, Thomas, and Fred, thank you so
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much for being with us today.
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My pleasure. Thank you, Sam.
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Thank you.
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Great pleasure. To be here.
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Just very quickly, Fred, Just as we open the episode,
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maybe you could just tell us very quickly, you know,
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how the theme of the Brain Innovation Days is chosen.
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Who selects that and why this year you've selected the
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theme of science scale impact?
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It's a very interesting question, Sam. And actually, it's like
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disclosing how the jury of an Oscar.
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Is making a decision. No, more seriously.
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We've got a process of idea generation and then proposals
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generation that we are trying to refine. And it's actually
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a process that we have integrated also and ultimately is
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being decided upon by the board of EBC. But it's
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inherently linked to the aggregation of all the contributions, all
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the trends, all the partners that are likely to collaborate
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with us during the Brain Innovation Days and, of course,
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the outcome of the previous editions. And the team of
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2026 was basically selected to try and have a clear
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focus that we cannot talk about innovation and innovation that
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needs to serve to address unmet needs ultimately, if we
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are not integrating the very fundamental science and research into it.
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Because it's all that value chain that needs to be
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integrated and needs to be represented. And we were thinking
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of those three words as being the best to capture
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that course of event.
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Thanks, Brad. So let's start by looking at science. Thomas,
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neuroscience is advancing at an unprecedented pace. What are the
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developments that excite you most at the moment?
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The developments that excite me most in neuroscience are in
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my own field, which is memory. I work on the
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neuroscience of long-term memory storage. And I think we're getting
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closer to understanding neuroscience how individual pieces of information are
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stored in the brain. And this is important because when
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we understand how information is stored in the brain, we
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will be, I think, of more value, not just to
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medicine and to health, but to the artificial intelligence community.
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I think we can get closer to real neuro-inspired AI
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by understanding how our brains process information. which is incidentally
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done in a much more efficient way than current LLM-based
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models do. So that's what excites me the most. But
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the wonderful thing about being a neuroscientist is that I'm
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a part of a very large community of tens of
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thousands of neuroscientists working across the world. And so I
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get to see what my friends and colleagues in other
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fields are doing and I get to collaborate with them.
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And I can see similarly exciting progress. in everything from
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people who work on emotion and consciousness and decision making
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when we're talking about at a cognitive level, but also
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people who work on the fundamental mechanistic biology of disease
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who are producing new insights into degeneration and Parkinson's disease,
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of course, into Alzheimer's and dementia in general. And more
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and more, I'm pleased to see that we're starting to
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pay more attention to development. So brains are not built.
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Brains are grown. rather slowly. And for some reason, neuroscience
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for decades has been focusing on the adult brain or
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the ready-made brain and then looking for things that are
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going wrong with that. And my view is to understand
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the brain, we need to understand how it develops. And
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we're seeing a lot more interest in developmental cognitive neuroscience
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for many different quarters, including in my own field, in
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the Ngram field. So I think those are the things
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that are exciting me most at present.
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And does neuroscience look very different now from maybe at
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the beginning of your career?
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Almost unrecognizable. Almost unrecognizable than 20 years ago. And there's
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a number of reasons for that. Most people would say
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the main reason are the toys that we're playing with.
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So the techniques that we can now use to manipulate
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brain circuits and to listen in to what the brain
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is doing are what would have seemed like Star Trek
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or some kind of science fiction movie back 20 years ago.
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And that's why neuroscience is such a fun field to
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be doing experiments in, because the things we can do
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would have never seemed possible. There's a very interesting book
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called Neuroscience Fiction, and it's a collection of vignettes on
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different movies that were produced over the past 50 years
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from The Matrix to Inception and so on. And the writer,
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who is a neuroscientist, incidentally, describes how for each of
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these science fiction films that some technology has emerged that
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allows us to do exactly what happened in that science
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fiction story. And of course, there's an important qualification here
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in mice or in some kind.
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Of animal model, which is still.
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an immense advance because mice have brain regions that are
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similarly structured to how our brains are structured. They don't
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have language areas in their brain, but they do have
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memory centers the same way we do, and they have
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emotional centers the same way we do. So being able
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to do these kinds of experiments with these tools in
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mice and other animal models has revolutionized how we understand
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many topics in neuroscience. And we're beginning to see better
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integration with the human neuroscientists. So that's the main reason
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I think neuroscience has advanced so much over the past
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two decades. Also, we have so many more young people
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who are coming in to study neuroscience. And they're incredibly agile.
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And they're not always so influenced by ideas that have
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been around for 50 or 60 years. And so they
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tend to bring a fresh perspective to things. And in general,
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that's also how science progresses. It's with new generational approaches
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to existing problems.
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You said there are things being done now that would
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have seemed impossible. What, if we turn our minds and
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our focus now to the next decade, what would you
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say you see as the biggest scientific opportunities for the
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next 10 years or so?
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I think there are several. I couldn't even list them
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all in this conversation. One thing that I'm very excited
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about is the integration of the brain with the body.
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So what we call brain-body research. I think that's going
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to come to a new level in the coming decade.
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We as neuroscientists often kind of think of the brain
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as a thing operating in itself, almost like a brain
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in a vat. And if we understood how the brain worked,
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we'd understand thought and biology better. in the body is
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very obvious. And I used to think that myself because
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when I was going through university and deciding that I
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wanted to focus on neuroscience and not, for example, genetics
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or biochemistry, it was because I had this conviction, which
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is reasonable, that I am my brain, that everything that
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is specific about me is happening in this mass of
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tissue in my skull and And we don't understand how
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it works. So we need to focus on this because
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this is where the software of the mind is embedded
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in the hardware of the brain. And around the brain
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is this big biological robot that I call my body.
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And it's pretty much the same as everyone else's body.
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We understand more or less the principles of how it works.
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And the real interesting frontier, therefore, is just in the brain.
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And I can see why I used to think that
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and I can see why much of neuroscience has had
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that kind of view, because there is huge mystery in
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the brain. I sometimes tell people, even though I'm a
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brain scientist, I can't tell you how the brain works,
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and neither can any neurologist or psychiatrist ever. or neurosurgeon,
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none of us know how the brain works, even though
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that's what we work on. But we can tell you
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how the kidneys work, and we can tell you how
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the liver works. We can tell you how the stomach works, right?
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And we can tell you how pretty much every cell
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type and organ in the body works, because scientists have
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worked out the fundamentals. But we can't tell you how
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the brain works, and that's why we want to focus
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on it, because it is, for want of a better term,
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it is the holy grail in biology.
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But there's a.
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Limitation in isolating the brain.
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On its own.
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For one thing, there's no situation where you could have
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a functional disembodied brain. And even if we were to
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make an artificial version of the brain, I don't think
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a brain in a vash type artificial intelligence situation would
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work out very well. The brain evolved to be embodied.
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It evolved to be part of ourselves. in a much
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more visceral sense, connected to our digestive systems, connected to
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our immune system, connected to other aspects of what is
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going on to keep us alive on a day-to-day basis.
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And neuroscientists like me are concerned with function. You need
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to know what the brain is doing in order to
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know what the brain is doing wrong in disease. And increasingly,
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I'm convinced that the most fundamental reasons that the brain
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evolved was not just to control complex behavior, to control thoughts,
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to control language and the kinds of conversations like the
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one we're having right now, but actually primarily evolved to
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coordinate what's happening inside our body, to coordinate all the
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different physiological things that are occurring in different parts of
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our body, and to change those things as the environment
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around us changes. And it seems to me this is
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a large part of the selective pressure that was placed
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on our brains as we went through evolution.
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So I think the understanding the.
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Brain-body interaction from a very functional perspective is going to
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be a very exciting development over the coming years. I
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think also brain-inspired AI and brain-computer interfaces are two other
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topics that are going to be quite important and that
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I'll be keeping an eye on in the coming decades
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or coming years. So it's not something I work on
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personally myself.
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Thank you, Thomas. And before I come to you, Martin,
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because I'd like to start talking about scale as well.
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Very quickly, Thomas, would you say that there are any
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areas where neuroscience is on the verge of a major breakthrough?
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About a few weeks ago, the Drosophila connectome was announced.
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So we used to hear about when genomes were fully sequenced,
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when we had solved the human genome or the genomes
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of other animals and plants. And now we're in the
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area of connectomics, which means charting the entire connectivity pattern
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of an entire brain of a given organism. And the
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Drosophila connectome is probably halfway.
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On an exponential scale between.
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A worm and a human being.
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It has about 100,000 brain cells.
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And there are numerous connections between those 100,000 brain cells.
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And they were recently solved in a very important study
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led by Greg Jeffries. In contrast, the human brain has
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billions of brain cells connected by trillions of synapses. When
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I tell people who aren't neuroscientists about the brain, I
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tell them you need to only understand two things to
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be able to imagine how complex it is. Number one,
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it's electrochemically active. which means it's really, really fast. And
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number two, it's incredibly structurally complicated because of the connectome.
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It's a network of brain cells that form a very
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complex lattice. And the human brain is the most complex
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object in the known universe. So to understand how information
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is truly processed in the brain, we need to understand
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the complete connectome of different animals. And the simplest animal
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that we know with the nervous system is a worm
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called C.
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Elegans.
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It has about 300 brain cells. But now we have
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the full connectome of a fruit fly, which has about 100,000
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brain cells. And this is a new level, new platform
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for basing neuroscience discoveries. We have the connectome, and now
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we need to understand how it processes information. And I
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think this is going to be one of the major
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battlefields for how neuroscience is going to progress in the
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coming years.
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Thanks, Thomas. Martin, let me bring you in and talk
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a little bit about scale, one of the other three
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pillars of the Brain Innovation Days. So, Martin, scientific breakthroughs
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alone can't or don't change patients' lives. What would you
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say needs to happen to move those discoveries beyond the laboratory?
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I believe that's a very important and critical question. As
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Thomas indicated earlier, neuroscience, I think, is in a very
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exciting era of novel discoveries about the brain and its function.
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But I believe that the key step is to build
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a translation pathway from discovery to implementation. So rather than
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treating clinical translations as the final stage of research. So
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this means that we need to validate promise and biomarkers
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for digital measures and treatment targets in diverse real-world patient populations,
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truly demonstrating that they improve meaningful clinical outcomes, and also
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establish how they can be incorporated into routine clinical workflows.
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So if you translate this to a precision psychiatry approach,
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where we really like to aim to bring the right
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treatment to the right patient at the right time, I
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think this requires moving from, can we identify a biological
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signal So really using high technological science to identify biology,
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but also move to the question, does using this signal
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actually change a treatment decision? And can it improve the
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outcome of the particular patient? So evidence, I think, therefore
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needs to encompass not only biological validity, but also clinical utility,
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cost effectiveness, scalability, ethics, and patient acceptability.
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And Martin, where do you see the biggest barriers to
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translating neuroscience into innovation and into clinical practice?
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Well, we know there is a huge high medical unmet need.
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And one major barrier, I think, is the complexity and
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the heterogeneity of psychiatric disorders. So the current diagnostic categories
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do not always map neatly underlying biology. And the same
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clinical presentation can arise through different biological mechanisms. So conversely,
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the same biological vulnerability can manifest differently across individuals. So
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that's one aspect. And we need to unravel this complexity
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and heterogeneity to eventually bring the right treatment to the
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right patient. And I think a second challenge relates to
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validation and reproducibility. So many promising findings emerge from relatively
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small and highly selected samples, while clinical implementation requires robust
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evidence across populations, healthcare settings, and stages of illness. So
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I think this is a second challenge that we really
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need to address. And then there's the aspect that I
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previously indicated. So it's about the translation and the implementation
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gap that we need to address. So researchers may optimize
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for mechanistic insights where clinicians need tools that are reliable, affordable, interpretable,
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and integrate into clinical decision-making. There are also fragmented data sets.
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There is some regulatory uncertainty. We need to better align
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with reimbursement mechanisms. And we need to bring together very
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valuable data sets in, for example, federated data platforms. Importantly,
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I think patients and clinicians need to be involved in
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the very early stages of understanding the biology. So indeed,
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I think we need to have a really reiterative system
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where discovery and clinical implementation works together in a continuous
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translational ecosystem.
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And when we look at all of those barriers that
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you've outlined there, how important is collaboration within that? How
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can stronger collaboration between researchers, clinicians, innovators and industry help
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address those?
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This is one of the key aspects. And I think
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what we need to think about is how to bring
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together researchers, clinicians, industry, regulators and people with lived experience
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that are working on the same mission. And In 2024,
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as ECMP president, I'll launch the Precision Psychiatry Roadmap, where
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we really try to work together, set up a steering
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committee with representation from all these different areas, and really
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come forward with a consensus on a biology-informed diagnostic framework.
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That is one way to go. First, you need to
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have consensus across these different stakeholders, but then, of course,
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it's the practical implementation of, for example, sharing relevant data
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and infrastructure, set common standards, for example, shared data cohorts,
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and reproducible analytical pipelines. So there is a lot behind it,
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but as long as we're on the same mission, I
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think this is feasible.
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Fred, let me just come to you, and we'll be
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talking about impact now, but let me start by picking
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up on that point of collaboration. Why is bringing together
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different stakeholders so important for accelerating brain innovation?
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Yeah, thanks, Sam.
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Actually, We heard from Thomas and from Martin the extent
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of the complexity of the brain and of the brain dysfunction.
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And obviously it was important, and that's also the basis
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for the creation of EBC, it's important to embed all
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the perspectives around what it takes to, I mean, respond
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to that challenge and address challenges inherent to the curve
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of the burden of brain disease. But at the same time,
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it was important in our eyes to bring in the
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first place, people living with a brain condition. Because it's
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so specific, that's something that is sometimes hard to measure, if.
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Not impossible to measure.
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But it's also, it was important in our advocacy work
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to do so. But this degree of diversity is probably
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what's necessary, as very often we say, it takes the
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world to answer to the challenges of the brain or
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to crack the brain. This aspect of collaboration And community,
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that's a word that I picked up upon in the
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conversation earlier, seems to me extremely important.
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Fred, ultimately, what does meaningful impact look like in brain health?
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We talk about impact, but what does that really mean?
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When do we know we've made an impact?
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That's an interesting one. And actually, we were debating whether
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to take it or the extent. it was capturing what
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we meant in having it in the subtitle of the
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Brain Innovation Days for this year.
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Actually, that notion of impact is.
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Relating to the inherent question as to what are the
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societal challenges that research is answering to. And this interconnect
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between science and society is exactly what could be captured
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in a sense, by that word of impact. I know
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it's a word that is very much disliked in the
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scientific community because it was not brought, I would say,
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very importantly in the evaluation process of grounds or funding decisions,
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that actually when we ask basic scientists upon application to
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determine what the impact of their research is going to be,
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that's close to impossible.
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So this notion of impact.
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Needs to be weaved really deeply across the whole value chain,
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but that value chain really needs to start at the
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fundamental understanding of the brain function at the basic levels
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of science, but also as to how ultimately we create
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that value chain that enables to strive for these improved
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outcomes for people living with a brain condition, as the
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motto of EBC says.
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So how can Europe then create that environment where scientific
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excellence does translate into better outcomes for patients and for
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society as a whole?
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Well, the hope is that we eventually achieve this recognition
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that brain health is so transversal to our needs, to
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our society, that it's actually central or at least integrated
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in every area of policymaking. Because, of course, it's important
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that we have a surge of funding in science that
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we have an acceleration of research outcomes and that translation
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into the innovation ecosystem.
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And that at the end of the day, we've got.
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The integration of research and innovation into healthcare provision. But
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this alone is not answering to the needs that we
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have identified in our space. We talked about brain development earlier.
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So that means that we should also have a view
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on maternal care, for instance, and how newborns are being
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looked after. and how young mothers are actually striving after birth.
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So these are all elements and examples of the wide
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array and interconnectivity of issues that needs to be integrated
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if we would like to have this holistic understanding and
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holistic way to address brain health in our society.
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Martin, Thomas, Fred, thank you so much for focusing and
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exploring on those three different pillars. But let me bring
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you all back in again now. as we move to
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the end of the episode. In a few short answers,
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we have a few quickfire questions to end. If you
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all had to choose one priority for the next decade
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of brain innovation, what would it be? Fred, let me
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come to you and then Thomas, I'll come to you
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and then Martin will finish with you.
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Obviously, that's the impossible question, Sam.
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It's really a catch-22 in the sense that, as each
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of us was saying, it's the interconnectivity.
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Of these three elements that are actually essential.
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And I would say that the pillar I would focus
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on is how to create the virtuous cycle across those
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three elements of the team.
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Thomas, what would be the one priority you'd choose for
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the next decade of brain innovation?
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I think the most effective thing we can do in
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brain innovation, particularly in Europe, would be to ensure that
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the priorities for brain research come in a bottom-up manner
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from the investigators, from the scientists, at every stage in
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the process. I think one of the limitations with how
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neuroscience has been progressing in Europe has been that so
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many of our funding mechanisms are what we call top-down.
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They're based on specific priorities that are negotiated either by
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government or by government in collaboration with civil society. And
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there's good reason for doing that. But the reality is
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that the most effective science comes from the most competitive
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scientists following their own intuition, their gut instinct, and competing
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with other scientists around the world. And I'm talking about
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funding mechanisms like the European Research Council and indeed the
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European Innovation Council. So what I would like to see
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is more of a prioritization on what we call bottom-up
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investigator-led research. Thanks, Thomas.
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Martin, over to you.
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Yeah, I think we're in an exciting moment of discovering
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a lot about neuroscience and the brain. I think we
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went through such a cycle for cancer research where we
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had no ways to cure cancer, but there were major
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investments in cancer research. And now I think we actually
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can pinpoint exactly what's cancer types and what type of
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interventions can be used. We're at the juncture now for
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psychiatry to make that similar transition. And I think translation
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of these novel scientific findings needs appropriate infrastructure as well
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as resourcing. Similar way that we did for cancer, we
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have to make it a priority. While setting that priority,
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I think laboratory, clinic and healthcare systems need to be
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connected from the beginning rather than sequentially. So we need
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a continuously evolving ecosystem where scientific discovery and clinical implementation
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are aligned and working together.
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And let me come to you all with a one
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sentence answer question. We've talked about the three pillars throughout
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this episode of science, scale and impact. Of those three pillars,
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which would you say currently needs the greatest attention and why?
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In one sentence, Martin, let me come back to you
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and then Fred and Thomas?
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That's a very challenging question, but I think we need
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all three of them to be being together. I mean,
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it's very hard to pick one. There is a very
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open space yet of knowledge that we do not know yet.
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We need to do this at a larger scale and
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actually bring it to the clinic to truly make the
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impact that is highly necessary at the moment. So it's
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very difficult to pick one. We need all three of
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them in parallel and very urgently.
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Fred, would you agree with Martin? We need all three
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in parallel or can you pick one?
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No, I agree totally with Martin.
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And I would probably add that what we need to
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the point he was making is this agility.
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Across the tree.
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It's like we relieve the pain points and the bottlenecks
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in order to have a seamless ecosystem in that regard.
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Thomas.
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I think we need all three. We clearly need all three,
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but I'm just going to add one feature, which is
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that all three aren't always happening at the same time
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and different versions of all three of science, scale and
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impact are happening at different times. So sometimes it's not
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about connecting science and scale and impact today. Sometimes it's
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about connecting the science today with scale in 10 years
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time and impact in 20 or 30 years time, because
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that's the time horizon that we need to engage with
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to meet these challenges. And I worry that we force
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ourselves to connect all these things and to have this
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comprehensive pipeline now, today, within the next five years for
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the people who are suffering from Alzheimer's or dementia today.
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But I'm equally concerned with the people who are going
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to suffer from Alzheimer's and dementia in 30 years and
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the people who are not born yet, perhaps my grandchildren,
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who are going to have childhood leukemia. These are the
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conditions that require 30 to 40 year timelines to adequately
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deal with. And if we don't admit that these connections
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between discovery and implementation and scaling up and impact are
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not going to be immediate, then we're going to deprive
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ourselves and future generations of the best outputs of science.
483
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And just one final word from all of you. We
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have spoken today about challenges and barriers, but also innovation
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and breakthroughs. What would you say each of you gives
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you the most hope for the future of brain innovation?
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Thomas?
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Young people, the thing that gives me the most hope
489
00:30:54.170 --> 00:30:57.369
is working with My students, my research students, and my
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00:30:57.410 --> 00:31:05.829
postdoctoral researchers in my lab, they are just so energized, innovative, collaborative,
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00:31:07.250 --> 00:31:12.089
and are always pushing themselves to find better ways of
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assimilating the science we have of making decisions, making leadership
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00:31:18.319 --> 00:31:21.220
decisions about what the next question is that they should
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prioritize their time on. And in finding very creative solutions
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00:31:25.099 --> 00:31:28.140
to all the problems that they meet along the way,
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00:31:28.160 --> 00:31:34.430
I'm seeing a much more active, much more healthy and
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00:31:34.470 --> 00:31:39.170
I think very, very team orientated generation of scientists emerging.
498
00:31:40.069 --> 00:31:41.630
That gives me the most.
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00:31:41.410 --> 00:31:42.190
Hope for the future.
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00:31:43.930 --> 00:31:46.589
Martin, how hopeful are you for the future? What gives
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00:31:46.630 --> 00:31:47.009
you hope?
502
00:31:48.289 --> 00:31:51.609
Well, about two years ago, I launched as ECMP president
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00:31:51.630 --> 00:31:55.269
this ECMP Precision Psychiatry Roadmap Initiative, where we really put
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00:31:55.349 --> 00:32:01.119
forward three elements, namely developing global alignment on principles and procedures,
505
00:32:01.859 --> 00:32:06.279
building consensus on the predictive validity from emerging data, and
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00:32:06.299 --> 00:32:11.420
actually operationalize new knowledge into an evolving biologically informed framework.
507
00:32:12.420 --> 00:32:14.720
And working now in the past two years with many
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00:32:14.839 --> 00:32:19.940
large professional organizations and people and presenting this message, I'm sensing,
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00:32:19.980 --> 00:32:22.680
and especially also with the younger people, that people become
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00:32:22.740 --> 00:32:28.509
ready to translate the exciting discoveries from neuroscience into clinical practice.
511
00:32:29.069 --> 00:32:30.769
And I really have a sense that we are at
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00:32:30.869 --> 00:32:36.230
a juncture for psychiatry, where now I think biology-informed frameworks
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00:32:36.250 --> 00:32:38.529
can actually work. And I feel that there is a
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00:32:38.549 --> 00:32:42.700
momentum that we should do this. I'm very excited about it.
515
00:32:43.140 --> 00:32:46.519
And finally, Fred, how hopeful are you? What's your big hope?
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00:32:47.500 --> 00:32:51.779
Yeah, expanding on what we just heard from Thomas and Martin,
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00:32:52.539 --> 00:32:53.539
I would really echo.
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00:32:55.700 --> 00:32:57.119
The feeling of the tipping point.
519
00:32:58.819 --> 00:33:02.579
So the change in the perspective and in the narrative
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00:33:02.700 --> 00:33:07.029
that in the past we were describing the brain as
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00:33:07.069 --> 00:33:11.470
a black box, brain disorders as incurable, untreatable, and that
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00:33:11.529 --> 00:33:16.819
we know are witnessing the first successes and as to
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00:33:16.859 --> 00:33:21.599
how discoveries in science have been able to be transformed
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00:33:22.160 --> 00:33:24.680
or were transformed into very concrete treatments.
525
00:33:24.740 --> 00:33:28.609
We have a complete shift in our understanding, in our perception.
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00:33:29.359 --> 00:33:30.740
and in the narrative.
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00:33:31.079 --> 00:33:33.220
And I believe that what I'm hopeful for is to
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00:33:33.259 --> 00:33:38.809
see that we achieve that also from the political, regulatory,
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00:33:39.789 --> 00:33:44.029
and funders' perspectives, and that the brain gets the recognition
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00:33:44.049 --> 00:33:44.710
that it deserves.
531
00:33:45.529 --> 00:33:49.539
Fred, Thomas, Martin, thank you all so much for joining
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00:33:49.579 --> 00:33:53.079
us today on Brain Talks and for such a thought-provoking
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00:33:53.220 --> 00:33:55.839
and thoughtful conversation. Thank you all to being with us.
534
00:33:56.500 --> 00:33:56.980
Thank you, Sam.
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00:33:58.039 --> 00:33:58.339
Thank you.
536
00:33:59.259 --> 00:33:59.940
Thank you, Sam.
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00:34:01.099 --> 00:34:03.079
Well, as I said, thank you so much to all
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00:34:03.119 --> 00:34:05.680
of our guests. And also thank you to you for
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00:34:05.740 --> 00:34:08.980
tuning in and listening. And if you are excited about
540
00:34:09.000 --> 00:34:12.230
the Brain Innovation Days event from this conversation, then, of course,
541
00:34:12.349 --> 00:34:17.710
you can go and register today at braininnovationdays.eu. And if
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00:34:17.730 --> 00:34:21.489
you found today's episode informative and thought-provoking, then please do
543
00:34:21.630 --> 00:34:25.679
follow and share the podcast with your networks. And join
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00:34:25.739 --> 00:34:28.280
us again next time as we continue our journey to
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00:34:28.360 --> 00:34:32.630
explore the opportunities and challenges shaping the future of brain innovation.
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00:34:33.309 --> 00:34:34.059
Until next time.
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00:34:34.320 --> 00:34:34.559
Bye bye.