Episode 3 of my new podcast features Dr. Jacques Carolan, a founding Program Director at ARIA, the UK’s Advanced Research and Invention Agency. He directs two neurotech programs aimed at one of the most important opportunity spaces: developing tools and systems to interface, at scale, with the human brain.
One program is built on the idea that brain disorders are circuit problems, and funds tools to target those circuits with molecular precision across the whole brain. The other aims to deliver high-performance neurotech to the brain non-invasively or at most in a 30-minute outpatient procedure.
We dig into the engineering and biology behind both programs, potential scaling unlocks for the field, how ARIA programs drive breakthroughs, Jacques background, the role of media in shaping the future, and much more. I hope you enjoy the conversation!
Other links to this episode and references below.
Topics covered
00:00:00 Introduction
00:01:22 Why 20 years of neurotech breakthroughs haven’t reached patients
00:04:08 The two variables that determine whether any medical technology gets adopted
00:09:17 Brain disorders cost the UK £100B/year and we’re barely treating them
00:16:15 Using stem cells and gene therapy to build better brain interfaces
00:21:40 Self-regulating gene therapy that helps the brain quiet its own seizures
00:24:03 The non-technical reasons transformative neurotech fail to reach patients
00:31:34 Watching a 30-second brain ablation stop severe tremors
00:38:11 The case for delivering brain implants and therapies without opening the skull
00:50:56 Why high technical uncertainty makes distributed teams better than vertical integration
01:02:55 Why the UK keeps producing world-class neuroscience but not world-class neurotech companies
01:11:04 What AI-driven hypothesis generation means for breakthroughs per pound
01:20:40 From quantum computing to improv comedy to running £119M government brain programs
Other Links to the Podcast
Links from the Podcast
Jacques Carolan
Website: https://jacquescarolan.github.io/
Jacques’ Programmes at ARIA
Research Papers + Technical References
How advances in neural recording affect data analysis (2011)
The “Sewing Machine” for minimally invasive neural recording (2019)
Professor Gabriele Lignani on closed-loop gene therapy for epilepsy
Videos + Demonstrations
References Mentioned in Conversation
Harvard Designated Driver Campaign partnered with more than 160 TV shows, including Cheers and Dallas, helping popularize designated driving before Friends premiered in 1994
Books + Media
Links
Transcript
[Cold open]
Jacques Carolan
The cool thing is that is actually a Purkinje cell. I spent my neuroscience postdoc working on these neurons. Yeah. So it’s this beautiful like massive dendritic tree. They’re in the cerebellum and they like integrate inputs across that entire like dendritic structure. It’s so freaking cool. [laughter]
Juan Benet
My guest today is Jacques. Jacques is the founding program director at ARIA, the UK’s version of ARPA. Prior to joining ARIA as a founding program director, he was a discovery fellow at UCL and a Marie Skłodowska-Curie fellow at MIT. Jacques’s work involves applying the principles of physics and engineering to create next generation scalable tools that aim to radically change our understanding of the brain and ultimately to be used to repair it.
Jacques Carolan
Awesome. Thanks for having me, Juan.
Juan Benet
Welcome. Very excited to chat. Awesome. So, let’s dive in. Part of what you do enables you to have a broad view of where the entire field is going. you see recent breakthroughs, you see the original breakthroughs of the field, you see the bottlenecks. So from your perspective, how the neurotech field developed over time and what were the major breakthroughs that proved that this was a transformational field and what were the bottlenecks that either still exist or we managed to break through recently. So just give us a perspective from your mind.
Jacques Carolan
I think the you know my job as a program director is to kind of come into a space like you said and see where that white space is and I think there have been incredible things in the neurotech space like what
[1:27] Why 20 years of neurotech breakthroughs haven’t reached patients
Jacques Carolan
are the things that you know have been impactful we’ve seen incredible advances in brain computer interfaces you know from the early days in the early 2000s and now to contemporary time where we’re seeing individuals with severe motor impairments severe speech impairments being able to communicate for the first time in absolutely incredible breakthroughs.
We’re also seeing those similar things in neurom modulation, right? Technologies such as deep brain stimulation, DBS, originally used for movement disorders like Parkinson’s. Potentially, [snorts] we can use those same technologies for severe psychiatric conditions, things like treatment resistant depression. These are also breakthroughs in just the past few years.
And for me, I really think we should be quite open with our definition of neurotechnologies. I think there’s incredible work in the cell and gene therapy space as well. You know, we’ve seen incredible work from uniQure with their cure for Huntington’s disease or potential functional cure. So, all of these for me just kind of, you know, in the last 20 years, but really accelerating in the last couple of years just point to the huge potential of interfacing with the brain in a targeted way for reducing human suffering.
So, so given all of that, like what can we do? Like where is the white space? Where’s the interesting things that we can leverage? I think for me we need to take an honest look and see can we get these technologies to the people that need them the most.
So let’s think about deep brain stimulation for Parkinson’s disease. If you look if you do a make a plot of a number of people with Parkinson’s in the US and number of DBS procedures the number of people is probably about.1% that actually receive this DBS. and given kind of you know some kind of eligibility criteria significantly underpenetrated and that is a technology that’s been FDA approved 25 years it’s well-reimbursed we have an idea of who’s going to respond to it and it’s still massively under penetrated and not even increasing at the rate that we want. So my kind of starting point is that if that’s the case for one of our most well- tested neurotechnologies, emerging new technologies for new indications, they’re going to fare even worse.
So the thing that kind of occupies me and really what we’re trying to do in this space is like how do we get these things out into the world? Like what are the levers that we can pull? What is holding people back from adoption if they have been shown to work and shown to increase the quality of life for people? What are the adoption bottlenecks?
I think of it as two axes. On the first axis, you have efficacy. Deep brain stimulation for Parkinson’s. It works well, but it doesn’t cure Parkinson’s. It’s a neuronal loss. There are many other side effects. We have examples of therapeutic interventions
[4:13] The two variables that determine whether any medical technology gets adopted
Jacques Carolan
that you know are serious surgical procedures but get out into the world because they’re slam dunks. I think about like hip and knee surgeries. In the US, I think you do something like a million of these, over a million of these a year, and they’re a pretty involved procedure. But because they’re so good, because they’re so effective, they get out into the world. I think you can drive on the efficacy axis, and on the other axis, there’s something I call procedural burden. How easy are these technologies to deploy?
So, you know, we have examples of technologies such as things like SSRIs with mixed efficacy that still get out into the world. Tens of millions of prescriptions are written every year in the US for these. So I see those as the kind of two complimentary axes and they actually map reasonably well to our two programs that we’re leading.
Juan Benet
As you think about technological breakthroughs, are you thinking of trying to reach similar levels of efficacy or greater by trying new paradigms that maybe make the tech smaller, easier to like make it easier procedures? Or is it taking existing technology stacks and instead of trying to invent something new just see how you can cut those down to get to the kind of easy low burden of procedure or you kind of trying to explore both areas simultaneously or
Jacques Carolan
yeah I think we’re trying to push both sides of the face space so maybe just to begin with talking about this kind of efficacy side so many brain disorders are really disorders of circuits right so what do I mean by that I mean that there are different brain regions involved there are some like really awesome studies where they take individuals with a kind of diagnosis of depression. Many of them put them in fMRI scanners and you can actually see that there are certain circuits that are either hyperconnected or hyperconnected and potentially that could be a new therapeutic target. So different brain regions is critical multiple brain targets and cell type selectivity.
It’s actually kind of awesome having these pictures behind us because there are many different cell types within the brain, whether they’re neuronal cell types, excitatory cell types, inhibitory cell types, non-neuronal cell types. I love these kind of structural images, these EM images for connectomics where you just like do these electron microscopy slices and the brain is just jammed full of neurons and I think people really appreciate that. The neat part is that many of these cell types drive radically different downstream processes.
Something that I think a lot about is there’s a cool example in the striatum. It’s kind of a deep brain structure and there are two types of medium spiny neuron and they look exactly the same. Like morphologically you couldn’t tell the difference and they’ve just got one subtype of dopaminergic neuron receptor that’s different. Okay. If you turn one of them on D1, they’ve got these cool experiments. The mouse turns clockwise and if you turn the other one on D2, they turn anticlockwise. So there’s a radically different downstream pathway. And and these neurons are really really important. So cell type selectivity.
Juan Benet
You know, in recent years, a lot of the world has become much more familiar with artificial neural networks, which are slightly like initially inspired by organic neural networks, but are fundamentally very different in that the mathematical model is fairly simple. you almost apply the exact same structure across the entire network, the same sort of rules. What you’re getting at is like with all these different cell types, you get different behaviors that might be coming from different ways in which the neurons themselves wire together or different ways in which they learn or is not clear at all what the parameter space is actually doing. So curious if you can expand on that a bit.
Jacques Carolan
Yeah, absolutely. I mean these different subtypes have very specific functionalities. Maybe some of them are doing some kind of long range projection. Maybe some like inter neurons are just kind of locally controlling inhibition. Like so much of the brain is this kind of complex dance between excitation and inhibition. I even give you an example like when I was working in neuroscience, I was doing these optogenetics experiments and you like turn on the brain, you know, turn on like a few neurons and you see those things excite and then you see inhibition just dampen it down. So all of these circuit motifs are just critical and we understand lots of them but we’re also discovering new cell types which also kind of blows my mind as well because our technologies are advancing and when it goes wrong that can lead to pathology.
So epilepsy is a great example here. If there is this kind of buildup of excitation or if you shut down inhibition it can lead to seizures. So controlling this excitation inhibition is really critical.
Juan Benet
Maybe to have a bigger context on how significant these disorders are for humanity globally. What what’s the what’s the scale of the impact here? Like how many people are affected by this globally or even you know just in the UK or
Jacques Carolan
Yeah, absolutely. So the numbers I have best are in the UK even just from I’ll start with economic and I’ll change it to people like economic it’s estimated to cost the UK probably over a hundred billion pounds a year. That’s both direct costs. So hospital costs, this is neurological neuropsychiatric conditions and losses of earnings, things like this. Okay, but actually if you just look at the most common conditions, prevalent conditions, you have things like mood and anxiety disorders. You have things like
[9:21] Brain disorders cost the UK £100B/year and we’re barely treating them
Jacques Carolan
addiction, you have things like psychosis, you have things like epilepsy, Alzheimer’s. I think 1% of people have epilepsy, onethird of that is treatment resistant. The numbers are much much larger for psychiatric disorders. So just the disease burden, the impact, we all know people who have experience with these things or we experience them ourselves. So I think that’s the thing that I keep coming back to and the thing that just like man, we need to move quicker.
Juan Benet
Yeah. Yeah. And the cost of the quality of life of so many people around the world is gigantic. curious how much this also lines up in your interest in not just to sort of repair conditions and kind of get back to a baseline or kind of fractional return to a baseline but to potentially just improve quality of life even beyond the baseline like just getting figuring out kind of what leads to not just happiness in one particular domain but you know there’s a wide range of what the human experience is and neurotechnologies can greatly enable people to explore that entire spectrum. I’m curious to what extent like that is a role in how you’re thinking about things.
Jacques Carolan
Yeah, I would say like within ARIA it’s, you know, it is very much focused on this therapeutic endpoint. I think for that longerterm vision, it really does need to go through unhealthy individuals first. That’s how we’re going to generate those large scale data sets that are really going to allow us to be like, well, how do I perturb mood, for example, or maybe drive towards empathy? I don’t know. But at least within ARIA, I think the near term is going to be the therapeutic use case.
Juan Benet
What are some of the maybe recent advances that maybe sparked the possibility space in your mind? Meaning the things that either happened recently that you think, oh, these things need to get translated or need to get enhanced or need to get put together, you know, across different groups or what are some of the bottlenecks that you’re seeing in the in the near term of that you’re specifically trying to trying to target?
Jacques Carolan
Yeah. So I spoke about the kind of importance of circuits and that was really the driver for our first program precision neurotechnologies really the thesis there is we need to increase the precision not just like spatial temporal but the molecular precision the scale across the brain so what made me think this is possible I think there’s huge opportunities by leveraging advances in biology okay we’re funding a number of projects in the biohybrid space can you grow stem cell derived neurons like if my goal is to be able to really increase my you know make sure I can get this part of the circuit I can get the inhibitory part the excitatory part [snorts] cells naturally do that. So what if we could grow stem cell derived neurons and use that as an interface and say hey I want to control dopamine in this brain region or I want to control GABA or I want to control some other kind of neurotransmitter. I’ve always been inspired by that field. There’s been some kind of early demonstrations in it. So we’re actually funding a number of people to look at this.
Can you regrow damaged pathways in the brain? In Parkinson’s, you get the loss of the nigral pathway. What would happen if you could regrow it? Maybe you wouldn’t even need a kind of active batterypowered interface. Maybe it would just go back to a physiological state. We don’t know yet. I think that was like a big motivator.
And maybe the meta point there is just like I really think biology is our new unlock for this. We’re seeing a lot in the gene therapy space. You can now design AAVs which can potentially cross the blood-brain barrier, target specific cell types. Lots of problems that are kind of protein design problems are now much more tractable than they were just a few years ago. I think that’s really promising. Maybe even using things like ultrasound to actually target the different circuits and we’re funding a number of projects around that idea as well.
Juan Benet
How do you structure a program like this? So currently you’re leading this opportunity space at ARIA sub programs within that. what is the structure of a program because probably a lot of people out there are not familiar like what are the how do you think about running a program over time that you’re deploying some amount of capital in it you have technical areas kind of walk us through that structure
Jacques Carolan
yeah so a program this is kind of you know very much inspired by the ARPA model DARPA model there’s been a huge you know rich history of these organizations driving advances in neurotech the kind of model is that technical scientists technologists like myself come into the agency and we get the freedom to build a focused R&D effort of our own vision. Okay. So you want to set some north star some northstar where you’re like if this is true if people can do this we believe the world can change. If I knew how to do it I would just go and start a company and do it. So there needs to be some kind of technical technological uncertainty about the exact solution to it. You want to have some idea that it might be possible. You don’t want to be totally impossible but like right on the edge of possible as the kind of sweet spot. We often think about like how many miracles do you need to have to happen to make this thing work.
What we then do is I say okay this is the north star. and then I put a solicitation out and we picked projects towards realizing that. That can be across industry, it can be across academia, it can be across nonprofits, hospitals, the whole spectrum of things. I think for me the key part is that in a program so each program to give a sense of scale is about50 million pounds to $80 million to what’s like $70 million to $100 million something like that [snorts] some magic should be able to happen in a program that isn’t possible by funding these folks in isolation like there should be some kind of nonlinear things that can happen and basically like my job is to orchestrate that is to make sure we can drive towards that.
So within the program we then set different strands that we think are important and we can go into detail about that within our programs but you know that might be saying someone needs to solve the delivery problem and then someone needs to solve a performance problem. You can break things up into kind of what might be tractable subtypes. Yeah. And then we fund these things and coordinate them. I meet with the teams. If we have if there are things that are really exciting we can double down. If there are things that are not so promising we can pivot. we can terminate projects. That kind of interaction is just critical.
Juan Benet
So let’s dive into program one. you already started to give a sense of it or like some of the things that you’re funding but just for you know how would you describe it as a whole?
Jacques Carolan
Yeah. So really the vision there the insight there is that like I said many brain disorders are really disorders of circuits. Can we build better circuit level technologies? The way we’ve ended up structuring it is mostly around two main technical areas. So the first technical area says, can you just give me these breakthrough technologies? And one of the neat things is when you’re like building a program, there’s always a moment when you’re like, I think this is important. I feel this is important. And you put a solicitation out and you’re like, I don’t know if we’re going to get anything and then you see what you comes in and then you have the opportunity to really shape like where
[16:17] Using stem cells and gene therapy to build better brain interfaces
Jacques Carolan
you see a bit of momentum. So just to give you a sense of that, yeah, I spoke a bit about some of the work in biohybrids. We’ve got three teams working on biohybrid neural interfaces and I think it was kind of cool. They actually on this point of how do we get these nonline interactions the so one of the teams is based in the US and two are based in the UK. The US team all of their team members came over for a kind of biohybrid summit and it I was like sitting there I was like man I think this might be the biggest collection of people working on biohybrids in the world. I was like hell this is so cool. And then you see like you know like one student is like oh we solve things this way and they’re like oh great here like and they were showing each other doing giving each other lab tours it was so cool. So we’ve got efforts on the biohybrid approach. I think that’s like one interesting way to get you know but probably a little bit kind of like later stage to get that interface really circuit specificity.
Another one we’re looking at is like what if we don’t have to touch the brain at all. Can we think about fully non-invasive ways to interface with the brain? So one of the teams that we’re funding is a team called Sonalis and they’re using something called the acoustoelectric effect. The idea there is that you know ultrasound can be focused through the skull. You get some loss but you can focus it through the skull and [snorts] potentially through endogenous ion channels you could also modulate the brain potentially you could also read out through blood Doppler shift. These are kind of indirect proxies for neural activity.
Okay. What if you could actually read and write electrical signals anywhere in the brain? So this is their project and it’s based on this idea called the acoustoelectric effect which says that if you put an acoustic field into the brain, you focus down to the brain at 1 MHz and you then apply an electric field at 1 MHz + 10 Hz. You’ll actually get a beat frequency in the middle, an electrical drive frequency of 10 Hz. the difference. This is just something that happens in ionic media. Kind of wild. And they’re looking if we can scale this up for whole brain. Really, really exciting.
Juan Benet
Yeah. What are the limitations there? Like it’s a super interesting piece of technology. Like fully non-invasive going across the skull. You said scaling it to the whole brain like how much readout can you can you get?
Jacques Carolan
Yeah. The the challenge with any kind of like ultrasound thing is that the skull scatters. So you do get energy through it and you know and the power you get essentially as you increase your frequency the absorption gets larger. So you know and as you increase your frequency your wavelength gets smaller. That’s to say having really precise access to the brain is hard like kind of the physics is hard.
What’s kind of cool with this team is one of the professors so it’s a spin out from Imperial College. One of the professors has a background in geophysics. And in geophysics, they go around with boats and they like drag these large ultrasound transducers around the back of the boats to try and find gas pockets. And you have to solve a bunch of inverse equations to figure out where these gas pockets are. So he was like, can we apply this to the brain? Can we like figure out what the scattering matrix of the brain is, then apply the inverse of that with some kind of helmet system? Yeah, there are a few people looking at this, but I actually think it’s a really tractable problem. Then the question is like how do you do it cheaply? Like do you need a CT scan? Are there more tractable ways? But like I think it’s possible.
Juan Benet
And would this be for read only or could it could you do read write?
Jacques Carolan
You can do right as well. That’s the neat part. So you get the reverse effect which is that if you then apply a kind of like offbeat electric field, you should be able to record an electric signal at the difference. It’s hard and the electronics is hard and the ultrasound is hard but it’s not impossible. That’s kind of what RS is set up to do.
Juan Benet
That would be gigantic, right? Especially if you can target any region of the brain, you could do the deep brain stimulation type.
Jacques Carolan
Yeah. And and actually like I’ve seen more and more now really interesting work in the DBS space that requires mapping first. Pain is a big one. There’s a big pain study maybe a year ago where they initially map using these sEEG leads that are implanted these individuals who have chronic pain. They look where these pain centers are and then can target the modulation based on that.
If there was a way that you didn’t have to go through this implantation process and be in some you know center for two weeks similar for epilepsy mapping if you could do that just through this non-invasive approach potentially could be really huge similar experience to you know getting an MRI type thing and then you end up figuring out exactly how to target the pain center and restore function.
Juan Benet
Yeah. And you can even like in situ like target that thing be like oh yeah that’s the one. And how much of that is read study and then perturb or is it kind of like trying to build integrated systems of read the state and try to kind of sample try perturbing and until you kind of narrow down.
Jacques Carolan
Yeah this is a great question. So we funded this goes back to this kind of technical area structure. The TA1 was really around like let’s build these breakthrough technologies. We have biohybrid approach non-invasive approaches. we have people developing gene therapies or like micro implants things like this and then I thought to myself I was like okay if we have these like so what right and actually I think there’s an interesting point which is like can we demonstrate something that’s not possible in terms of you know reading out from the brain and controlling brain states we then funded in this second technical area a number of teams which have breakthrough technologies but also bring in computational modeling. Really, the goal
[21:41] Self-regulating gene therapy that helps the brain quiet its own seizures
Jacques Carolan
here is to say, let’s take some brain state and let’s see if we can perturb it to some desired potentially physiological away from a pathological state. I give you an example of one of those. There’s a couple of cool ones actually, but one team we’re we’re funding is led by a professor at UCL called Gabriele Lignani. They have a really novel approach which is a closed loop gene therapy. So, you know, I spoke about epilepsy earlier. It’s this buildup of excitation which leads to this seizure. They came up with this technology which said deliver a gene therapy and then the neurons can sense if there is an increase in excitation due to a seizure and if there is they can then upregulate potassium channels which kind of puts the brakes on the neurons.
So it’s like only the neurons that are involved in the seizure and once the seizure stops then they kind of transitely down express and it’s like awesome man this is so wild and it turns out there are lots of conditions that are somehow disorders of excitability schizophrenia dementia a spectrum of things.
So we’re funding them to say, can you do large scale modeling and figure out, you know, to figure out where to deliver these gene therapies to and then use ultrasound to actually target those gene therapies. And if you can do that, is it possible to actually fully restore you back to a pathological state? I don’t know if it’s possible, but I think it’s really really fascinating.
Juan Benet
And you also have a third technical area in program one around patient and stakeholder engagement. Can you talk through that?
Jacques Carolan
So maybe I can just jump into one of the TA3 projects that we’re funding. so we’re funding a someone at the University of Sheffield to look at inequities in neurotechnologies. So if you just look at the kind of like look at DBS implant Parkinson’s it’s almost all exclusively white.
So this incredible researcher Mahnaz Avarneh at the University of Sheffield she’s working with communities that typically don’t get these types of implants and trying to understand like what do they know about neurotechnologies like how like what would be the limits of them want to do something really towards just kind of addressing the disparities and inequities in neurotechnology like we’re trying to build things that everyone can access and really understanding this is
[24:03] The non-technical reasons transformative neurotech fail to reach patients
Jacques Carolan
going to be critical. She actually put together a really cool video. So if you like search I think you can find it through maybe the ARIA website as well but if you search Mahnaz Avarneh University of Sheffield neurotechnologies inequity like you’ll find that great and we’ll put the link on the description.
Juan Benet
Awesome. I think it’s a really key thing in the adoption of any technology is truly understanding how people perceive it, how they think about the cost benefit, what are the blockers. sometimes it might be slight tweaks that maybe the technologists never thought about that could dramatically increase the adoption rate.
one of the things that has been on my mind recently is the invisibility of devices. So when a device is visible, it tends to cause some amount of social stigma because you look different and you seem like you’re carrying something. And you can think of a range of technologies once they got to the invisible part of the spectrum, the adoption went through the roof.
A good example of this might be braces, right? So initially think about the old braces, not just like the on the teeth ones, but the ones that had like the wire going around and just like a like a very difficult experience that you’re putting somebody through to carry around this type of device and compare that to something like Invisalign where suddenly it’s entirely invisible or close to invisible and suddenly the people’s experience of it changes dramatically.
So yeah, curious what if you’re seeing similar things in these kinds of studies or what other vectors are you thinking about exploring?
Jacques Carolan
Yeah. Well, I mean like I think that’s a great example, but you take that and then you convolve it with a stigma that is already associated with neuropsychiatric conditions, right? Like and in certain communities that there is a huge amount of stigma having a psychiatric condition and then you have something that can like demonstrate that.
So yeah, we’re like we’re definitely seeing you know there’s some of our teams are looking at non-invasive approaches and understanding adoption there actually. Yeah, like shaving your hair is a really big deal for a lot of people and it also breaks down over different like you know if you’re a young girl you definitely don’t want to shave your hair.
The TLDDR like is from what you know I’m really not an expert in this but the thing that comes up all the time is that it’s just complicated.
Juan Benet
Yeah. And different people and different communities will have different things they care about also intersecting with different levels of severity for that indication as well. So it’s like yeah it seems like a super valuable data set for the entire field. Are you guys sort of collecting that and going to publish the whole thing or
Jacques Carolan
I was you know I was actually so surprised these things don’t exist like you know of course the field of like lived experience engagement and all of these things it’s a field and there are professionals that do this but especially when I was building this new program I was like what for something like Parkinson’s people been looking at cell therapies people looking at gene therapies people looking at DBS I couldn’t find any data sets which did large scale patient engagement across these variety technologies which is kind of wild.
So I think within our everything we produce along these lines in our TA3 is absolutely being shared publicly
Juan Benet
and is that looking primarily at the UK or you looking broader
Jacques Carolan
or most of these studies are in the UK
Juan Benet
and perhaps you can give a blueprint to of how exactly you conducted it. So then you know people elsewhere can maybe broaden it to other countries.
Jacques Carolan
Yeah.
Juan Benet
So I would imagine that there might be significant differences in you know across the world.
Jacques Carolan
Yeah. So we actually we did it in kind of a unique way which was like my instinct was that like this is an area that’s important and there are other people who are better experts than me at driving this forward. So we put a really broad call out for this just said like we’re interested in these areas like give us the best things that you have and got some really incredible efforts come through that.
So I don’t know what the mission I think that’s a unique thing that a government funer can do in this space is kind of set that and there are like you know there are organizations like the James Lind Alliance that does priority setting for different types of technologies and different types of like medical conditions. So one of the people funding is looking at priority setting for brain computer interfaces for people with motor neuron disease.
So I don’t necessarily have a good answer to your question, but I think there are people there that are experts in this and it requires some kind of forcing function to drive them in some right direction.
Juan Benet
And I also saw you include media as part of the technical area. What are you thinking there? Is that kind of is that kind of like a production of media that helps explain things to patients or what’s sort of the range there?
Jacques Carolan
Yeah, so this is and this is for our second program. So this one isn’t out yet. on the media side, it was really the observation that you know there are so many dystopian stories about neurotechnologies. and we’re in a unique moment, I think, where there are individuals who have neurotechnologies of one form of another. It just feels that there is a need to kind of get their stories out into the world.
In the UK, there’s a bunch of awesome podcasts around Parkinson’s. There is there’s like loads of people making podcasts. That’s really cool. Can we actually, you know, fund these folks or communities that work with them to create YouTube videos which kind of just show the realities of their conditions and also the technologies themselves. Like there’s probably great parts and there’s probably annoying parts and just get those stories out into the world.
So it might be videos, it might be podcast, we want to access like the influencers. I just think there’s this kind of space that I think would just be awesome.
Juan Benet
How much of it might be also normalizing it in mass media? There’s this story, I don’t know if I haven’t verified it whether it’s true, but there’s a story that I think the Friends show included a reference to drunk driving and having like a designated driver instead. And like they just threw a small comment of just making it a point that whenever they were, you know, going out drinking somewhere or whatever to just always like reference the DD. And that just that light introduction, the story goes that became a huge vector for mass adoption.
Now, I don’t know if this is exactly true or not, but I would imagine that portrayals in mass media can be super impactful to how people perceive this kind of thing broadly. I’m curious if you know to what extent it’s like reaching out to these kinds of video production or these groups to kind of include help educate those groups on like the importance of highlighting these kinds of things.
Jacques Carolan
Yeah, I think that’s really fascinating. I think there’s actually there’s a couple of examples and I’m sure there’s examples in the US but examples I know of in the UK of like famous newscasters that got Parkinson’s and got a DBS and now like and now become you know inadvertently an advocate for that.
So I think like it’s really interesting to think about how do yeah how do we leverage that to kind of normalize these types my kind of takeaway is like it’s almost like a phase transition. It’s not like one lever that’s like okay hell yeah this is going to drive it. It’s going to be, you know, both understanding the needs and the kind of boundaries of that. It’s going to be sharing stories. It’s going to be the whole spectrum of things. And then slowly we see that and I think that’s the unique thing that we can kind of do at ARIA.
Juan Benet
Yeah. And let’s maybe jump into the second program is for massively scalable neuro technologies. What is the northstar for this second program and you know kind of what was it kind of open space that you weren’t uncovering in program one that triggered you to kind of shape this new one?
Jacques Carolan
you know when I spoke about that kind of that axis that you know this like this one axis we have like efficacy and then the other a procedural burden so what do I mean by that implanting something chronically into someone’s head is a really serious thing it sounds trit to say it maybe as a footnote here
I went to go and see a couple of DBS procedures be done at the end of last year the first procedure I saw be done was called RF ablation so it’s kind of an old technology so it was a person who had very severe tremor like an essential tremor.
What you do is you go into the you put a probe into the thalamus and then you kind of do a very small
[31:39] Watching a 30-second brain ablation stop severe tremors
Jacques Carolan
ablation to kind of disrupt that circuitry. And it’s one of these remarkable things because they do it while the person’s awake. You ask the person in the surgical theater to draw a spiral or write their name and they can’t do it just because their tremor is so significant. They kind of they go in, you know, they plan this trajectory. They plan they want to go. they go into the thalamus and they like press a button for like 30 seconds and then they say, “Okay, can you draw a spiral?” And it’s just a perfect spiral.
Juan Benet
Wow.
Jacques Carolan
And you know it’s and this person is like absolutely stoked. It’s like it’s remarkable. It’s like the closest to magic that I’ve actually seen. So I feel very honored that I got to experience that.
Juan Benet
That’s amazing.
Jacques Carolan
Yeah, it’s wild. And so that was one procedure I saw be done. And I saw another procedure which was a bilateral DBS implant. So you do it in both hemispheres. And of course the person’s under anesthesia and it was just so much clearer that was a really serious surgical procedure from like a sterility point of view from like everything. [snorts] Implanting something in someone is like is really serious. Unpacking that what do I mean? I mean that there is singledigit percentage of you know likelihood of a bleed of infection. You know these things are real. What does that mean? That means that drives patient hesitancy. that potentially drive clinician hesitancy for prescribing these types of things. And then I think about the barriers of just like where these things can be done.
Yeah, in the UK we have you can’t get the number. It’s just kind of hard, but we probably have a few dozen functional neurosurgeons at consultant level that can lead these procedures. You know, changing that is like a generational time constant. Like it’s a bit better in the US, but it’s not a ton better. And just where you can do these things as well. you know basically it always requires some like large scale urban medical center where you know it’s expensive to get to and tend to live nearby and these things so I think it might be similar if it’s a brain computer interface I think it might be similar if it’s a cell and gene therapy like basically have to do the same things
that was really the starting point so I became fascinated in like what are transition points where you know we can like radically increase the scale of technologies and there’s some really cool stuff looking at like early pacemakers if you had like a heart block bas have to do like a massive kind of thoracotomy put leads on your on your on your heart and the transvenous lead essentially revolutionized that you know so you kind of go in through the veins and you radically changed the surgical procedure so you went from a kind of you know maybe [clears throat] half a dozen of these done a year to now millions of those things
Juan Benet
yeah and that’s with the stent right like you bring in a stent and
Jacques Carolan
Exactly exactly and it’s actually kind of a cool case study as well because initially these things kind of sucked like leads broke, you know, they were using like nuclear batteries, like all of these things, but it created this like innovation ecosystem just because it was so radically more scalable and that’s ultimately what drove it.
So I was looking at this and the kind of proto pacemakers were around the kind of like 1950s and in 1947 was the invention of the transistor. kind of cool like on my eyes like what is the new technologies and breakthroughs that will could drive mass adoption of technologies like what is the transistor of our modern age and I’m going to go back to something I said earlier like I really do think it’s an engineered biology like we can engineer you know vectors whether that’s cells whether that’s AAVs we can combine that with like hardware like all of these things can access the body and they can be programmed like I think there’s so much there so That was kind of a long answer. That was really the nugget by which I was like, I think there’s something here to radically increase the scale of neurotechnologies.
Juan Benet
How are you defining or thinking about what makes a neurotechnology scalable? So, you referenced the operating room and the difficulties there. You referenced potentially making it minimally invasive. So, potentially going through other access media like what is the full spectrum here that you’re looking at?
Jacques Carolan
This question of scalability is super interesting and you ask 10 people what scalable means and you’ll get like 11 different answers. So my kind of thought process is like what are the like technological leverage points which we can you know have a plausible argument that will potentially lead to scalability. Where I landed on this was this idea of you know can we avoid the craniotomy altogether and for many of these things you require you know to remove part of skull implants from it chronically can we access the brain and deploy high performance neurotechnologies without ever requiring that so [snorts] can we leverage blood vessels the vasculature can we think about leveraging the CSF can we think about like other access points we haven’t even considered
Juan Benet
what’s the CSF
Jacques Carolan
oh the cerebral fluid so you can get that through a lumbar puncture It actually goes all the way to the ventricles in the center of the brain. It actually goes all the way onto the surface of the brain. It’s like kind of an interesting space to access things. Can we think about the nasal passage? Olfactory neurons actually have processes that sit in the nasal passage. So, if you can get things to there, potentially they can kind of pass into the brain. There are many challenges with it. It’s really really hard. Our nose tries to keep things out generally. but does that kind of white space maybe be like I think there’s something here.
Juan Benet
Yeah. Yeah. And and what is the spectrum of devices that you imagine here? Is it you know primarily devices that would become implantation or it’s intersection between biology and engineering? how much of it do you expect to be just purely either chemicals or gene therapies or things like that?
Jacques Carolan
Yeah. So, and maybe I should also just like add in the north star to this program is really to say can we get high performance neuron technology to the brain in a 30-minute procedure without transcranial surgery really with the goal of like ultimately being able to do this in an outpatient procedure and people were like like why 30 minutes actually 30 minutes is kind of it’s pretty consistent with both interventional procedures and cell infusion procedures and like the amount of people who are like well okay like no craniotomy can I get like a small hole and I was like well actually like it’s important that we somehow constrain it because I do believe that like constraining things drives radical innovation.
Juan Benet
Yes.
Jacques Carolan
So yeah, your question was like do you imagine this is like devices or biologics or I imagine it’s the whole spectrum of things. We’ve only just recently closed for concept papers and the full proposal is going to open in a couple of weeks depending on when this airs. What I can say so far is like at least what inspired me that this might be true like we are seeing some interesting work on the devices. Of course companies like Synchron are doing incredible work there. How can we think about accessing deep brain targets? You
[38:12] The case for delivering brain implants and therapies without opening the skull
Jacques Carolan
know, many of the things that we care about in neuropsychiatry and neurology are in these deep brain areas. How do we access that? We think about yeah, new devices that might span different pathways to do that. On the biologic side, one area that I’m really fascinated is in immune cell engineering. So, immune cells naturally cross the blood-brain barrier during regions of inflammation. So, we’re seeing advances in synthetic biology. Could you imagine applying synbio to these things such that they can track to the brain, monitor pathology, secrete biomarkers out into the blood like potentially or even dropping off cargo like these types of things. there are early signals that it might be possible and I think it’s kind of a moonshot that’s maybe worth taking
Juan Benet
and do you imagine that being yeah the full the full gamut of possible sets of technologies of trying to kind of reach the same level of efficacy as the as the current approaches or are you also enabling I don’t know the exploration of like new types of targets or what
Jacques Carolan
I the way I set this up was we want the teams to target brain regions or brain targets where there either is like validated evidence You know, so there’s a bunch of those things in DBS, whether it’s subthalamic nucleus, whether it’s subcallosal cingulate for depression. Either it’s those sets of targets or targets where there is like a plausible kind of clinical path. And and why is that important? It’s important because like you’re solving a really hard engineering problem. If you’re solving this, you want to like at least know it’s going to be useful somewhere. That’s not to say like I think it’s really really important to find new therapeutic targets. these are just the ones that we’ve accessed and the ones that we’ve kind of validated some degree. Like there’s a whole space of finding new ones and that’s actually a bit more along the first program idea. But what we said is like let’s just hit targets that we know about.
Juan Benet
And in the in the three technical areas of this program you have like technical area one delivery and performance, tech area 2 prototyping and translation and technical area 3 adoption. Can you maybe walk us through each of these?
Jacques Carolan
Yeah. So technical area one and actually like going back to the state that’s that’s the core technology development part and my kind of thesis is that we really want to be delivery first like there have been a bunch of cool technologies for mice like and like it works really well in mice and then like it never sees the light of day like we’re serious about getting things out into the world. Okay. So I really believe that like delivery in this program is the gating factor for scale. So in the first technical area, we’ve split this up into two areas, two phases. The first phase is, can you show me you can solve this delivery problem, right? You can get to the right brain region. You could do it in a way that has the potential to fit in this 30-minute potentially outpatient procedure and it can be done safely or at least we have a handle on what the safety profile is. Even if it’s not exactly there yet, if you can’t do that, I’m not interested. like we need to get technology into the world and then based on that we can then advance the performance. So the way the way we’ve structured it is that we have this initial three-year drive where we fund a broader number of projects you know it might be across like really radically different technology streams biologics hardware nanoparticles who knows and then based on that we can then down select the things that we’re looking most promising and really think about that translation path. So that’s technical area one.
And maybe just another thing I’ll say on that as well is like you know if you speak to anyone in some kind of like ARPA agency you know they love metrics like everyone like loves a metric and like they’re valuable and sometimes you can overdo it and so what we’ve said for this program is that actually we’re indication agnostic like I want teams to select the indication that they care most about that they think they can drive the biggest you know change whether it’s in neuropsychiatry whether it’s in epilepsy they then set the metrics like what is the readout bandwidth you need to monitor Alzheimer’s. It’s probably different from the readout bandwidth you need for a motorbi, right? Like teams then set that themselves. Okay, so that’s technical area one.
Technical area two is kind of it’s a bit of an odd thing, but it’s basically looking for a series of teams to support our TA1 teams. Okay, we’ve actually seen a pretty interesting use case of that in the first program. So through a program we’ve got called activation partners I can talk a bit more about. We’re working with an organization called Emodo Design. They’re essentially an engineering design house over in Sheffield in the north of England and they can and they make like incredible hardware. They make incredible ASICs. They’re like super smart people. They work with our teams and they say you know this like widget that a grad student spends like a year and a half building like what if we could do that? what if we could give you that in 3 weeks and it’s going to work 10x better like and that mindset shift is just a really fascinating like kind of opener for people. So what we’re going to do is once we see the teams that we end up funding in TA1 we’re going to put a separate call out for these supporting teams. So it might be you know hardware engineering it might be high throughput protein design maybe in phase two where we’re thinking about regulation can we think about regulatory support can we think about organizations that can do lived experience engagement to understand what like like product profiles need to look like just that whole like kind of infrastructure around there
and then finally in TA3 it’s really thinking about you know how do we tell the stories of individuals who are living with these conditions who are maybe even using these technologies there is just a gap in my for not even like positive stories of neurotechnologies but just like realistic stories of neurotechnologies. So I really hope we can somewhat
Juan Benet
how do you think about robotics? So one way to address the surgery question which you know neural link has been pushing one of the first things they focused on was trying to decrease the cost structure looking at maybe like the eye surgeries like once they became robotic in nature then they could become like the 30-minute outpatient procedure whereas before you know it’d be incredibly difficult to try and produce that kind of change. How do you see robotics as a as an angle here? Like do you think that could be a vector to get to like the 30 minutes or do you think no specifically you’re trying to create a different innovation space where you think groups like Neuralink are already going to cover that and you instead want to try and find other things?
Jacques Carolan
This is an awesome question and I spent so long thinking about it. Yeah. And as a footnote, you know, the kind of like proto sewing machine came out of like a DARPA which is kind of cool. Anyway, actually that’s the story there.
Juan Benet
That’s fascinating.
Jacques Carolan
Yeah. So I don’t know the exact story behind it but it came out of a postdoc’s name who I’m going to forget now. It might be Tim Hansen. So had this idea implanting electrodes automatically. Flip’s lab which I think was at UCSF was like a neuroscience lab. It’s like an electrical lab had no reason like no business doing like fab or doing like deposition like totally bonkers and you know like Flip’s incredible person. He’s like yeah sure let’s try it. They got some money from DARPA and they kind of were doing these things in electrophysiology lab. That’s the story that I’ve heard. I just think that’s insanely cool.
Juan Benet
Good taste from a PI goes a long way.
Jacques Carolan
Yeah. And also been able to like support an incredible postdoc who’s got an idea kind of out there just like man go for it.
Yeah. I thought a lot about this robotic side like absolutely it’d be great if it can be automated. Where I landed on this is I actually think there’s a lot of efforts in this already and there’s a lot of capital deployed towards like some of these like medical robotics companies have like billions of dollars and are just about starting to turn profit. Like my sense was that one probably the amount we could put in there would just be a rounding error. Like I couldn’t really see the differentiated thing. Like we’re interested in things that are like catalytic and nonlinear. I couldn’t quite see that in the robotic space. like it’s cool and if it’s going to happen anyway, it can just plug into this stuff. So it’s like a catheter procedure like you know there’s a field of people developing machines for mechanical thrombectomies for stroke to remove these clots like if that’s already happening that can probably apply to devices. So given all of that I just didn’t quite see it.
Juan Benet
So you know as you do all of this and you just mentioned the process of coordinating all these groups and the way that you’ve designed and shaped the programs includes thinking about who are the labs that are bringing the kind of innovative new technology or new science and who are the groups that are going to be able to play important roles in building components of that. You know, maybe it’s like fabbing a specific device or maybe it’s solving some concrete problem or doing some kind of mapping or bringing in algorithms and AI expertise to be able to you’re trying to coordinate incredibly talented people from across many different organizations very much in the you know age-old tradition of government agencies like ARPA and others which you know at the time in you know in the ‘ 50s60s which was a very different time they managed to produce a very fast pace of engineering or very fast pace of R&D. Today we’re seeing tremendous successes in vertically integrating systems. Groups like Apple and then now Elon and others have shown that like if you try and vertically integrate the entire process, you can go usually way faster than the rest of the market. There’s something there’s some breakdown in the coordination structure of the broad contracting structure where time delays sneak in through all of the negotiations leading to, you know, this super high cost measured in time.
And so you know Elon has gone really far in the last 10 20 years by saying just no to the you know conventional wisdom of decoupling pieces and letting the market sort of solve the problem and instead just solving it yourself. and that is a huge counterpoint to how you know ARPA in the and even the precursors to ARPA you during the war efforts built so much of the of the deep R&D required to build incredible programs including all of the machinery like all the tanks and so on. then later all of those insights were set up for the Apollo program. They also influenced how the internet itself was built. There was so much R&D that was driven this way and it was actually quite fast by modern standards maybe especially by modern standards given how long everything takes today.
But and so you’re trying you’re trying this older approach and coordinating a lot of talent in a time period when other groups are having massive success by taking the counterpoint. where are the parts where like it works really well or have you seen these delays or no actually you disagree with that point of view and instead you actually have seen measurably faster approaches this way. Yeah. I just want to get a sense of how you think about this entire
Jacques Carolan
I think it’s like the first thing is it depends at what level of like technical uncertainty you’re at like when you’re ready for takeoff and to like vertically integrate you know you’ve kind of reduced the error bars on your technical directions. So I generally think like where we’re sitting with these programs is we’re kind of earlier in that pipeline where there is still technical uncertainty. Now a win for us is if we can show like one of these technologies is like a goer is massively valuable then the kind of infrastructure whether it’s through venture whether it’s through un like non-dilutive funding whatever is there to support that and allow it to take off.
My sense is that like in neuroscience at least things that we’re thinking about it doesn’t quite make sense integration precisely because we have this high levels of technical uncertainty then the question is like you know I spoke about this kind of nonlinear magic like we still do want to get to that so how can we drive that within our program towards accelerating the technologies we’re developing and I think that happens in a few ways the first is actually just kind of by like serendipity so you want to increase the surface area of interactions between the various teams such that they’re like, “Oh, you’ve got a problem to this. You’ve got a solution to this problem.” We had a workshop a few weeks ago, which is the annual meeting for our precision neurotechnologies program. Someone was like working on some kind of human tissue samples and like someone else was like, “We really need access to human tissue.” But like, I can help you out. They were actually already collaborating on a separate project, but didn’t know they had these capabilities. So that’s like serendipity and we can kind of you know I think about it as like a thermodynamically we can like increase the temperature and do that
and then there’s the other part which is like are there core technologies that are being developed across these various programs. So for example, the computational modeling side, there are a number of really incredible computational neuroscience teams that are all trying to do a similar thing. Trying to take some highdimensional data sets, trying to do some kind of dimensionality, correlate it with something you care about, and then perturb the brain towards a new state. We want to get those folks to work together to be able to like help accelerate each other. So we can kind of drive that as a fun.
And then there’s the final part which is like resources like hardware. So I’ll go back to you know this team that we’re funding a modo design they can almost be you know
[51:02] Why high technical uncertainty makes distributed teams better than vertical integration
Jacques Carolan
that like play a little bit of a role of a vertical integrator they can work across many things they have in-house mechanical design firmware design as design like they can do those things and do it quickly and do it well
Juan Benet
earlier you were mentioning bringing together a set of people and then finding you know the serendipitous insight that you know one group could help another go faster and but this was only found kind of at a workshop isn’t that also an argument just for putting all of those teams within one organization and trying to like go as fast as possible kind of like in the Elon style or not just Elon this maybe he’s the most visible version of this recently but you know many other organizations apply the same thinking of like just get all the super talented folks put them under one roof don’t do it remotely actually force everybody to move into the same facility you know this maybe even has Bell Labs hallway errors right like if you get and concentrate all of these groups into one place you can increase the collisions and get to the innovation rate faster Maybe because of the technical risk in that like when you’re contracting outside you maybe want to have things more definite working across many organizations.
Yeah. Yeah, I don’t know like how do you think about that versus maybe the reality is also could be around hey these talented people are already in a range of organizations and they’re kind of stuck in that environment today and the prospect of pulling them out of those environments you know into a separate single organization is just so energy and capital intensive that unless you have billions of dollars you can’t quite do that and so therefore like you’re you know stuck having to coordinate them in this kind of more remote environment. Yeah, curious where you land.
Jacques Carolan
You are completely right. Serendipity is highly inefficient. It’s the kind of like bane of my life. And and I actually think I think you’re totally spot on. I think what it comes down to is incentive and incentive alignment. Like a startup has venture investment. They’ve got things they need to do and they’re aligned towards doing that. Like academics need to produce papers and need to graduate and need to get tenure. Like hospitals have things hospital things they need to do and like how do you coordinate across that?
Like I think the thing I would push back on is like I still think we’re not at a point yet where we can like there is the need like because there is still so much technical uncertainty about like what is the pathway going to be that we’re ready to like stick these folks in a single place and be like hell yeah let’s do it. I love Bell Labs but I think we have a lot of nostalgia for Bell Labs as well and I think the kind of modern version of that will probably look a bit different.
Juan Benet
Yeah. It strikes me often that a lot of what makes certain companies work so well and drive so such fast R&D it’s more softer type changes things about the culture things about what meetings you actually have you know how much you protect individual contributor time to not have meetings and instead work however you provide crucial fast highly iterative cycles where they have to present results and so there’s like a lot of pressure that forces the whole team to advance quite quickly you know week to week to week you know getting up in front of the whole company every week and you have to have some results. So, I don’t know. I’m curious if you think about that sort of softer culture oriented organizational structures.
Jacques Carolan
Yeah, I think about it a lot. It’s and there’s kind of a few different examples and I would say this is like probably less towards getting you know just to be clear like we fund a bunch of what we call projects typically those might be a few different research groups or different companies working together. What I’m going to describe is less about finding connectivity between those folks but more about like driving innovation. I think first I think mission is just so important and just like driving home the reason we’re all doing this.
At my recent meeting we were working with a guy called John Nelson. John’s kind of like lived experience like advocate like a real activist incredible storyteller. He actually came to the summit. So if you search ARIA Summit John Nelson, there’s a beautiful talk that he gave and he’s someone who’s lived with treatment resistant depression for many years and he went through this kind of experimental procedure with the clinician Dr. Helen Mayberg to implant a DBS into his brain and the way he talks about it is that it saved his life.
When I see that like it’s I find it so so powerful and it’s like we need to move even quicker. And so we actually got him to come to our annual meeting and run a session around lived experience and brought in various folks. You know, someone with epilepsy, someone who was a carer for someone with Alzheimer’s, someone with Parkinson’s just for them to talk about their experience and like you know, you go to these workshops and everyone’s like on the phone or like laptop or doing stuff like just you could silence. You’d hear a pin drop and like there you know, there were lots of tears.
Why is this important? one, it does light a fire underneath you and it lights a fire under technical teams who actually very rarely interact with these folks. It helps you build better things. We’ve spoken about this before like if you’re trying to like build something for someone like you want it to be good and you want it to be usable and you want it to like people to buy it. So you chat with people that are going to buy it like you do that if you’re building any product, right? So I just think it’s I think that like in terms of driving it that’s just so important.
So what I really try and do within my programs is like create a sense of a team. You know, yeah, we’re distributed around the UK. We’re distributed around the world, but we are a team that’s like trying to solve this problem. And I genuinely believe we might have the most ambitious set of neurotechnologists in one place. In that there is some magic and just really try and impart that across them.
And then you’ve got the kind of maybe like less glamorous part of this which is teams have to report every quarter. So we get technical reports every quarter. We meet with them. They have really concrete milestones they need to hit. If they’re not hitting with them, then we work with them to try and debug it. So we are really really deep in the technical details and they’re presenting to us and every year they’re presenting to the team. So there is that pressure and that’s kind of critical to the model. So it’s a real balancing act to say, you know, it’s ambitious. We’re asking you to do really hard things in short periods of time, but it’s also supportive. So that’s the needle that we try and thread.
Juan Benet
What do you think is really special and unique about this kind of coordination approach that just can’t be done in more traditional single organization, single company setting kind of you already spoke a bit about finding a set of groups and orienting them towards this you know finding deep expertise having a wider kind of field of experimentation where maybe you couldn’t run that many programs in a single company because you have to the focus will drive narrowing of perspective but here you maybe try a lot of different bets. What are some other organizational cultural insights that you’re finding interesting or valuable about this approach that you know as a counterpoint to other structures?
Jacques Carolan
I mean we’re not driven by profit which is also interesting like I think does play an important role. It’s like the most important thing is that we have breakthroughs that we plausibly believe can change society. And it’s actually interesting as a footnote when we fund teams like fun like startups or even established kind of industries. They’ve often got the thing they need to work on because they got venture investment, they’ve got a board, they’ve got things like this and then they’ve got the thing they really want to work on. And actually just like a few million pounds or dollars can actually unlock that bigger which is kind of cool.
So we are looking for the tail of the distribution. You know if everything that I fund is wildly successful then I probably haven’t been ambitious enough which is kind of an interesting point to be in which might you’d have to have a very special type of company that can leverage things like that and can really drive with things.
So I think that combined with being really deep in the technical details and ultimately we’re not committee based like you know I work with experts to get insight into different areas. if I think that something is promising and everyone you know there’s a big group of people who are like tried it in the 80s and it never worked and I’m like I think there’s a reason it might be able to be solved now like we can take those contrarian point of views that is not a given for a government organization and I feel very fortunate that ARIA has been set up in such a way that we really do have that embedded into our DNA we really do have those levels of protections that level of ambition like it’s really in there and I at least hope that it kind of filters out to the teams.
The reality is like we’ve got some awesome programs across many different areas. Like we need to see breakthroughs on a decade horizon. Like that’s what we need to do.
Juan Benet
Can you speak a bit about the innovation ecosystem in the UK? Like one of the most significant breakthroughs on the entire planet in the in recent decades has been DeepMind and the UK had the talent insight maybe contrary and perspective at the time where Demis Hassabis and others were able to build an extraordinarily talented team there and grew DeepMind there and then you know that eventually joined up with Alphabet and so on the whole there’s a whole other story there but that to me shows an example of being way ahead of where Silicon Valley was on AI at a particular moment in time and you know historically there’s a tremendously talented scientists and engineers and so on all over the UK and you know in the complex of universities around London and so on but perhaps on the startup technology company side the UK has not been as strong counterpoint of DeepMind has not been as strong in recent you know decade or decade or two how are you seeing the ecosystem now how are you trying to maybe change that or kind of boost the technology translation to yield a better set of outcomes or kind of stimulate the growth of more neuro techch companies locally or how are you thinking about all this?
Jacques Carolan
Yeah, like you’re absolutely right and in kind of in you know of course the DeepMind but in like the neuros there’s been a bunch of like half a dozen Nobel prizes for neuroscience kind of UK or UK associated things right like neurosurgery was kind of incepted in Queen Square in London there’s incredible neuroscience generally there’s great engineering we have these like core components and when I started ARIA you know I like went all around the UK the thing that struck me the most is actually like is this like entrepreneurial appetite like there are so many young folks who like don’t want to go into academia they don’t want to go into like established industry they want to like build something wild and I actually wasn’t expecting that and just that like level of like appetite and enthusiasm
I’ll just like give you an example Imperial College London has a student society student run student organized everything and they’ve got a WhatsApp group and there’s like a thousand people on this WhatsApp group like How cool is that? And it’s kind of like a small example, but I really do believe there is this kind of like undercurrent of people wanting to do things.
Now, I see ARIA’s role as kind of like activating that talent base. There’s a kind of like slightly handwavy version of this and there’s a kind of a concrete version of this. like the handwavy version is that like I do believe that ARIA has given people to permission to dream big you know to really like think about doing a moonshot in a kind of like a non-traditional environment that’s kind of handwavy but like I get a sense of that the second part is like what actually can we do to drive that broader ecosystem and very early on we realized that was going to be an important thing in ARIA how do we actually get you know our technology into the world like can Can we build new talent pipelines? Can we have new capital in flows? Can we build new communities, new capabilities?
So, we essentially launched a very broad call for what we called activation partners. These are like organizations that we just had a feeling were like going to be important in kind of increasing momentum in our spaces. There is a bunch of different folks that are kind of towards this like activating that community.
to give a couple examples, you know, so we’re working with Convergent Research, you know, like for coming they’re developing FRO’s. they launched their first ever residency program in the UK. We’re actually
[1:02:57] Why the UK keeps producing world-class neuroscience but not world-class neurotech companies
Jacques Carolan
funding one like one FRO around in vivo connectomics. Really really cool idea and like wouldn’t have happened otherwise. Like this is just awesome. In terms of like other talent pieces, we’re working with a number of deep tech VCs based in the US. Pillar VC, 50 Years to actually run their programs in the UK taking found taking scientists turn them into founders taking top AI talent put them in dropping them in labs. The amount of people that apply to this are as much if not more than in the US which is like kind of cool. So I think there is just this like strong strong appetite like I give a couple of examples specifically in the space which is we’re also partnering with University of Cambridge and they’re setting up a neurotechnology accelerator now. So you can come on it’s a year-long residency the whole thing is paid for. You can run you know build prototypes you can chat with clinicians lived experience the whole thing towards at the end trying to raise some money. It’s still an experiment. It’s still to be seen if this is going to be the thing that drives it.
Yeah. Like I go back to this image again like it kind of is like a phase transition. We push on our technologies and of course we can reach all of our technical milestones and they don’t get out into the world. We can push on talent. We push on community. Another thing I didn’t mention is on the regulation side. One of the challenges in the UK is that neurotechnologies are still pretty new and just the kind of guidelines aren’t there. like you chat with folks and they’re kind of confused about how they submit things like this. But parts of the UK regulatory system is really innovative. Like we had the first ever CRISPR drug approved anywhere in the world. Kind of wild. So what we’re actually doing is partnering with the University of Newcastle. We’re actually seconding some people into the MHRA which are our regulators like the FDA in the UK to develop that guidelines, you know, and it’s like a small lever but potentially could be really impactful.
So yeah, it’s just I think that could be gigantic. So from my perspective, the kind of the regulatory blockers to a lot of this is where so many ideas end up dying or where the prospect looks so bleak that groups don’t even try. and so I think if you can get a much better landscape for neurotechnology in the UK and make it a just a dramatically better place than other places to advanced technology companies, that could be a huge edge in being able to reach patients dramatically faster, save way more lives, get these breakthroughs into the world.
Yeah, I give an example as well. You know, one of the things we’re funding through the program is a collaboration between Forest Neurotech, you know, nonprofit FRO developing ultrasound systems for read and write a the University of Plymouth and a hospital in London called Queens Hospital. The ultimate vision of this project is can you use ultrasound to both read out brain states associated with mood and perturb the brain to more physiological states. I think just last week they did a clinical study with about six participants in London using this like in my eyes like state-of-the-art brain computer interface and as a footnote it’s kind of neat is because like explaining the challenge of like the skull scattering ultrasound this surgeon works with people who have had their skull removed if you have traumatic brain injury you can do these large craniectomies to relieve the pressure and it means you basically walk around without bits of skull for like months at a time. So he recruits them into this clinical study and you know they’ve recruited a really large amount of people. So that’s exactly to your point like I actually think there are some like levers which can be really impactful both in regulation and clinical trial.
Give you another example. So we’re funding a collaboration between a neurotech manufacturer neurotech company in the UK called Mint. they have like incredible ASICs incredible boards and Motif Jacob Robinson’s company in the US. As part of that, a motif set up a UK office. They hired someone, but actually realized the talent is so good and to be totally honest is cheap and you can get like incredible people. They’re actually starting to hire more people in the UK just based on that. It’s like that’s great.
Yeah, it’s kind of I think there’s a load of things happening around there.
Juan Benet
Yeah. I wanted to dig into the AI for science question. you mentioned it a little bit earlier, but this is a field that I’m also extremely interested in. I see a lot of people in the in the AI field themselves are super interested in this ultimately why many of the people in the AI field are pushing on AI because they know that the breakthroughs that are that will become possible once we get to you know full AGI levels and ASI and so on are so transcendental that we’ll be able to greatly advance how so many fields go everything from like the early advancement that we’re seeing now where you’re getting LLMs capable of being great research partners in helping you do a lot of the literature reviews and thinking about ideas in the interstitial spaces to you know I’ve been fascinated by the stuff that Terry Tao and others are doing with math where like they’re actually pushing the frontier and also not just LLMs but you know Lean and other automated ways of producing results like we might see versions of something kind of like that if we build better models of the cell or better models of connectomics and so on.
So I’m curious how you think about this entire area. What are some of the interesting projects that you’re seeing? What are like your hopes and dreams for the next few years? Because I think the frontier is so ripe. the capabilities have advanced so much in recent years like even just like the last 6 months. And the capabilities will continue expanding over the next 6 12 18 24 months. And so what you say now could inspire somebody to go and like do that for you.
Jacques Carolan
I think it’s like so fascinating. I think AI for science or AI science can mean so many different things. And of course like having labs that can like be automatable that can be closed loop that can be hypothesis generation like I think that will happen and I think certain problems are very amenable to that protein design is very amenable to that like high throughput like biological screening material science there are definitely like things where you’re like I think that’s just going to happen applied to the brain I actually think it’s almost lost all meaning but like the idea of a foundation model for the brain and but like what do what do I mean with that and what do I see as like the interesting cuz I’m like starting where like I want to see like scientific signal that something is possible and for me then my spidey senses go and I’m like okay we need to drive on this and there’s some work I found really inspiring from Leanne Williams at Stanford.
Leanne Williams is a kind of like a psychiatrist like a precision psychiatrist and they take individuals with a diagnosis of depression and the challenge with firstline psychiatric treatments it’s just like basically a dice roll so you take individuals with depression put them in fMRI and then show them images and do some kind of simple tasks. And then with all of this data based on functional connectivity alone, you can actually subtype people just based on functional connectivity. And those subtypes better predict whether someone’s going to respond to a first-line treatment or not.
Juan Benet
Wow.
Jacques Carolan
And it’s like early and it’s kind of like it’s like marginal, but like it’s there. And like I think it’s just really fascinating to be like if that’s true, what does that mean? And actually like I really do think this huge leverage point is going to be in human neural data at different spatial temporal scales at different like like I just think that is going to be a critical flywheel. It’s going to help us identify new therapeutic targets.
I speaking to my friend Milan Cvitkovic and he’s telling about this idea of predictive validity. So I’m stealing it from him, but Jack Scannell has this theory where they show that like the biggest like predictor of whether a drug is going to be clinically successful is whether it’s pre-clinical models recapitulate what happens in humans. Almost sounds like trivially true, but actually the key point is that even just changing that by a few% can radically change the outcomes of whether it’s successful or not. And the challenge is that like the best model for the human brain is the human brain. So I really do believe that we need to collect large scale human neural data sets, you know, in a safe and scalable way to identify new
[1:11:07] What AI-driven hypothesis generation means for breakthroughs per pound
Jacques Carolan
therapeutic targets to have much more personalized interventions. Like I think it’s the only way. So it’s not necessarily a kind of like AI for science, but like that is just a problem that is so ripe that we need to leverage all of our tools towards.
Juan Benet
Do you have a sense of which types of recording will produce like the most interesting or most valuable data sets like what avenues like what devices or do you think it’s like new ones that might be coming through?
Jacques Carolan
I think a variety will be valuable. We want it to be able to be like accessible. So it’s not ideal if you have to like the only place you can get this recording is like in an fMRI at Stanford. you know can you do it in a lowcost way that can actually be distributed around places where there isn’t like a tertiary center. I think that is really important.
I think figuring out ways to go between different modalities like how can single neuron spike data be useful for like fMRI or focus ultron data or be you know be like upsampled for EEG like that spectrum I think is I don’t have a concrete like answer but I feel that’s going to be important.
Juan Benet
One of the questions that’s been on a lot of our minds in the last year is could we just record ample amount of neural data across a wide variety of behaviors so then be able to collect enough data points so then figure out like what matters for what types of conditions or do you think it’s like it’s much more about robust data sets on the very specific because I think most of the neural recording that is happening today is very specific and targeted to the to the a particular pathology or something like that and yeah I’m curious where you how you think about this.
Jacques Carolan
Yeah, I think you need I think you need broad access across different brain like regions. I think just I know I’m particularly interested in like therapeutics and pathology and I think you need to be able to access deep brain structures.
I think it’s a really interesting question like how much can you get from just like like behavior and physiology alone like in mice you know if you record a bunch of cortical data it turns out that pupil dilation explains 50% of the variance of neural like spiking right because basically relates to attention and a bunch of other things and like so that’s not to say that like neural data is not important but like you can actually get a huge amount from physiology and I don’t think we’ve really understood the limits of that yet.
Yeah, it’s a little bit of a copout, but I think the whole spectrum of things are going to be really important.
Juan Benet
Well, it seems to me that having very scalable recording across the whole brain with sufficient precision is this massive bottleneck in the field, not just code economics, but all the neuro AI questions. And I’m curious how much of that is either part of the current programs or potentially a future program or something like that.
Jacques Carolan
Yeah, I would say it’s like almost the it’s almost the intersection of both the programs in a way. You’re absolutely right. like if we had that it would unlock so much. I don’t know we have a path to it yet.
Juan Benet
Yeah. Yeah. You you go into it and you mentioned recording but a lot of times it’s so linked to the pathologies or so linked to a specific target. Both of your program writeups have like this very cool section around ways to plot like different metrics and how the different technologies show up when you measure them a particular way. like you see the parallel frontier of like where the technologies are now and like kind of the types of devices that you’re trying to inspire and it seems to me like we’re missing something like that for scalable and precise measurement like where you can scale like really scale up the invivo reading while retaining the precise measurement.
Jacques Carolan
Yeah, I agree like yeah, there’s this like plot I put together which is essentially like precision some metric of it’s kind of like spatial precision but it’s a little bit different and how I was a bit cautious about using the word but how invasive the procedure is and you know things that are implantable have much better precision things that are non-implantable like kind of makes sense just like the physics makes sense because you’re further away from your sources like so there is this kind of white space of like how can you have something that has like high levels of precision that can be deployed in like a scalable way I don’t think it’s impossible possible. I don’t think it’s impossible, but it’s just a really hard problem. And that’s ultimately what we’re trying to push in the program.
And there’s another axis to that as well. Like in some way, you put together a graph and you have to like make a bunch of assumptions. And [clears throat] on the y-axis of that graph, you know, I have like spatial precision, but I don’t care about spatial precision necessarily. Like I think there are other things are important, but what I really care is about functionality. Like how useful is something? Another like axis is also like what are smart ways you can process data or like churn through data like by building large scale models maybe you need to collect less maybe you need to only collect lower resolution data so I think there’s like another axis that is kind of I would love someone to like put this together about how like invas like a threedimensional graph of like invasiveness of like functionality and like data something like I don’t know there’s something there.
Juan Benet
Yeah. Is there a robust current model of where all those technologies are across all these vectors? It seems like a useful resource to maintain to like you know have like a website artifact that you can go to and see you know the plot today and you know maybe you can see the plot over time and how it changes. It reminds me of like the cost structure graphs in clean energy like when you know you were tracking the cost structure of solar coming down or like various different sources of energy and then you can start making reliable predictions about where certain technologies would be or like why invest very deeply in batteries today as opposed to you know a decade from now because like they’re actually close enough to like this frontier where suddenly they become like actually very practical to scale and so on.
Jacques Carolan
Yeah, it’s a it’s a great point that like that doesn’t exist to the best of my knowledge and I think that would be massively valuable. Like the closest that comes to it is I think it’s Konrad Kording and Stevenson where they have this graph of like number of neurons recorded as a function of time and you know you start in the 60s and people like patching cells and it’s like one or two neurons and then like like electrode arrays happen and then like optical imaging happens and this thing kind of increases exponentially and you can be like okay mouse brain is here like human brain is here how far away are we like I think it’s kind of cool but actually I think there’s a much more I think there’ be a much more useful thing that you talk about would actually like where like what is the prito frontier of our current technologies in terms of I don’t even know what the metric might be like what is it going to be like cost per like unit recording in human or something like that yeah someone needs to do that
Juan Benet
let’s just shift into your story I’d love to hear about how you got where you are now like studied versus a physicist that you’ve done a range of things maybe take us back to how you started I don’t know learning what inspired you what you end up setting across sort of over time what brought you to different fields so
Jacques Carolan
I think starting as a kid I was like always very very curious I think like I was a kind of you’re like that kind of like intro to the question is like a nice way of saying like easily gets distracted [laughter] like and I and I think that’s like I do see my kind of history as a kind of like jack of all trades and master of none like so I think I so I grew up with just my mom and I think I very much saw like the importance of education. My mom going to university like changed our circumstances in like a very very f like a very real way. So I think like the importance of education and learning not in an explicit way but like implicitly was like always kind of installed onto me
and then like when I went to university I was like you know like what were the things I was doing I was like interested in the kind of foundations of physics. I was like man you can learn physics it tells you something about the nature of reality like that’s so cool. I remember to going to going to university and I was like studying like physics and philosophy together. I got to a point where I was like I kind of want to do something useful with these tools that I’ve built and that’s when I kind of found out about the field of quantum computing.
So the first part of my like career was in applied physics and quantum computing and I was just like fascinated by this idea which I think still sticks with me today that physical systems can compute.
Juan Benet
Mhm.
Jacques Carolan
It’s kind of a bizarre thing, right? Like whether it’s capacitors in your phone full of electrons, whether it’s like a water wave computer, whether it’s quantum bits, like you know, I think it’s just really I find that just deeply fascinating. I think it tells us something very fundamental or whether it’s biological neurons.
So I did a PhD in physics and I was trying to build quantum computers using light. funnily enough I, you know, when I finished my PhD, my adviser actually moved over to Silicon Valley with a bunch of the teams there and set up this company some people might know called PsiQuantum. They’re like the biggest quantum computing company now.
And that was kind of like it’s interesting. I think after a while, after about a decade of working in that field, it became clear that like to have impact and to like solve problems, you just need a huge amount of capital. It’s semiconductors. You need billions of dollars to do that.
And I actually went on the faculty job market. I was like, I’m going to be a physics professor. I’m going to be a quantum physics professor. That’s what I want to do with my life. I like went on the job market and it happened around the time the pandemic hit and I came back and I was like, I just don’t know if this is thing I want to do. Kind of decided it when I was like 21. I like love the people. I love the problems. It’s like is this the highest leverage, most impactful thing I can do with the rest of my life?
I’d always been like interested in biology. Like I don’t have high school biology. I don’t know I didn’t know anything about biology and I actually remember during my PhD I read this paper by Adleman of like RSA and Adleman had this like cool experiments in the ‘9s around DNA computing. So you can like like the story goes he was like reading about you know a DNA polymerase in his bed and he’s like kind of like a Turing machine and you can do these cool experiments where you like somehow get DNA and you like shake it up and you can like solve a traveling salesman problem like
[1:20:44] From quantum computing to improv comedy to running £119M government brain programs
Jacques Carolan
freaking cool and I read it and was just like oh this is wild. So that was always in the back of my mind and then I around the time the pandemic hit and I was like I just don’t know if I want to be like a physicist always been fascinated in the brain and the idea that like biological sweat wetty things like can compute that’s wild.
So I basically spent some time trying to be like is it a crazy idea to become a neuroscientist? So I ended up just like reading a bunch. I read a bunch of papers, spoke to people. It was during the pandemic, so like people had time on their hands. This like random dude in a field they didn’t know would like get a message and be like, “Hey, can we have like a virtual coffee or something?” All the physicists I spoke to were like, “This is a terrible idea. You got a good career.” [laughter] And then all the neuroscientists were like, “This is an awesome idea.”
And actually one like I remember one of the conversations I was like hope I don’t like embarrass him but I read a paper by Adam Marblestone scalable principles of physical recording like a legendary paper very yeah legendary and you like the author list is wild as well right like Dario’s on it, Shapiro, George, anyone who’s on it and for me that really resonated because it was like using principles of physics to understand like what is the limits of what we can do and I actually spoke with Adam and he was like dude you just do it so I ended up doing another postdoc in systems neuroscience playing with Purkinje cells and actually yeah I learned so much about the brain it was it was awesome yeah
Juan Benet
and there’s like a similar to the what’s the expression about math is like the unreasonable effect effectiveness of mathematics in explaining the world there’s also an unreasonable effectiveness of physicists in advancing many other fields so I think like you actually it was the right thing to study physics and then go into neuroscience I think Dario has a similar point about how in early anthropic they were primarily selected physicists because they ended up being very able to like then go on and learn everything else.
There’s something about how physics itself is taught. I don’t know if this is about like the people that it draws or the or the some of the lessons of the field or some of the complex intersection between like deep math and practical real world where like you don’t get this behavior from just mathematicians alone. There’s something about how physicists develop that ends up making the whole class of you like unreasonably effective at like working in a bunch of different fields.
Great that you made the leap like you translated from physics into neuroscience and are now helping advance it. So great.
Jacques Carolan
It was it was a journey and actually on that point as well is like a lot of the physicists I really admire like they’re so good at doing quick back of the envelope calculations you know because they can keep various equations in their head. They can keep various physical constants in their head and can play with those to orders of magnitude and arrive very quickly whether something is plausible or implausible.
I would say like when I went into neuroscience it was definitely like a wakeup call like I was the only physicist there. I’ve got this wonderful photograph which is the first time I ever pipeted. And my colleagues were like cracking up. I was like, I don’t know what this thing does. And you know, I’d done a bit of fab. I And then I went into like doing mouse surgeries and like learned how to do this stuff.
My main takeaway was like a lot about being an experimental scientist is like knowing what your error bars are. you’re trying to jiggle some complex system to optimize some cost function and like at some point you need to stop jiggling and I think when I moved into biology in physics if I built something it didn’t work it’s cuz I built it wrong in biology things don’t work because of biology so the error bars were so much bigger that took me a while to like really grow and it’s actually useful doing this job now because I know like it’s just a it’s a different it’s a different beast
Juan Benet
so you got a postdoc in science and then what
Jacques Carolan
yeah so I was working there for about 3 years in London and like learned a bunch. Everyone around me was a biologist and then it was around that time that ARIA was being spun up. So I kind of had heard about it and actually I’d met some DARPA PMs when I was on the faculty job market and doing interviews and there was this kind of like you know kind of reverence associated with them and so I was like reading about it and I was like this is such a cool model and then they just
Juan Benet
is that when you first found out about that model or had you already been kind of exposed to the
Jacques Carolan
that was when I first yeah so probably only really when I so I did a postdoc in the US so I was aware of it there but like only really the kind PM le model I only found out about when I chat to these people. I still have the I found the job ad on the way back machine which is kind of I forget exactly what it is now but it was something like you know do you want to like like direct £50 million and change the world? It was like the most like audacious thing I’ve ever seen. like, “Wow, this sounds cool.”
And then went through the application process and like it was basically what like I can imagine was just like a six-month personality test like various like and I just met so many incredible people. You know, the people that had set it up, Ilan and Pippy, they just really believed that we could do something different. They were really trying to create a culture that could enable that. And I think that was the most like striking thing just like how intentional they were about the culture they were creating internally.
I remember going to this like finalist day. So all the finalists come together. This is a unique thing about the model is that they recruit in cohorts. It’s actually like awesome because you just have these group of people that are just like on this journey with you. I went to this finalist day and like 20 of us rocked up to the British Library and there were some really impressive people and I was like I don’t know what I’m doing here. And then yeah went through the day and like none of it was really technical like bits of it technical but it was more like how do you work together like what are you driven by? Yeah. And got offered the job and I think like it was that culture they created where I was like you know what like let’s just do this.
And the interesting thing was is that like all of us had kind of taken a career risk being there. were like, you know, they were like successful professors, like successful like founders, founding team, all of this had kind of like had really good careers and like rocked up at this thing that could just be a car crash, [laughter] but that creates something really special when everyone is just all in. You must see it with founders all the time. Like it’s a really special thing. There’s some m some magic happen. So yeah, I feel really fortunate for that.
Juan Benet
Yeah, it’s really magical to create a the right culture of an environment like that. And also like what an exciting journey to be a part of in shaping a new agency like that from scratch like like like you’re saying it could be you know many of these types of organizations and agencies end up ultimately not working for some reason or whatever and being able to work in the beginning of it to try and give it the best shot possible at having like the large scale impact. Like that’s awesome.
Jacques Carolan
Yeah. And you know we were like sitting around a table being like how the heck do we launch a program like what are the most important things and just like working on that together having ownership over that together like the biggest impact I might have will be like does ARIA exist in a decade and is it still exciting and do people around the [snorts] UK around the world be like man I want to be a program director like that’s real
Juan Benet
what are some of the cultural things that Ilan and Pippy or others in ARIA set up that you know in retrospect you think were super valuable.
Jacques Carolan
Yeah, it’s a great question. I think there’s a bunch of things. I think always pushing us to be as ambitious as possible. Just being like, you know, is this the singular most ambitious there? So, I think all of us that came into it had our ambitious levels raised. We had an idea of like a thing we might want to do, but like what is it a few levels on from that? And just like really instilling that into the agency and doing what you need to do to get that information to let you make that decision.
Of course, that’s like ambition in science and programs, but also in things that might not seem so sexy like procurement. Are we doing procurement in like the most ambitious way? Are we like doing contracting in a way that like can happen really quickly, really seamlessly? I think that was like really instilled into the entire agency.
The cohort part was a big part of it as well. It’s like the best job in the world, but it’s also really hard and you’re wearing a ton of hats and actually just having a bunch of people that like have your back and you can just go and say, “Man, I had a really rough day.” And like they’ve got you and you’re there for them. Like there’s so much power in that. So I think that culturally was a was a really big piece.
And then their question is like that then hopefully filters down to the teams that we’re funding. Like we’re trying to say that we’re doing things differently, that we’re there to support and there to work with them. So I hope that comes across but like the external projection of ARIA like it really is the case internally. I feel very lucky for that.
Juan Benet
That’s awesome. There is something also unreasonably effective about cohorts in shaping organizations and cultures. You see it in universities in militaries in you know in YC in things like that. There’s something about having a group of people going through a similar experience together and learning roughly the same set of things plus having the different classes of that cohort such that you can build more senior cohorts that then can help advise the younger ones or whatever. There’s something about that structure overall that I think outperforms a similar type program that just changes that one variable where it just hires people whenever it’s it doesn’t kind of build this cohorting setup and just kind of maybe has an open call and hires people immediately in their own timeline per position. Something culturally really changes when you have a group of people temporally going through the same kinds of challenges.
Jacques Carolan
Yeah. Yeah. I 100% agree and I could not sure I can articulate what it is, but it’s think about like learning rate is like you can multiplex across failure, right? Like someone’s like, “Man, I tried this. This didn’t work.” Okay, cool. We all update. And like having that component, I think, is really important and it builds relationships in a way that like I think the other approach doesn’t.
Absolutely. Like I think all of those program directors like, you know, I’d walk through Firefall and I know it’d be the same. And you’re trying to move really quickly. You’re trying to put like documents out like you’re trying to build this new thing. Being able to like iterate quickly with people that you trust, I think trust is a big part as well is so critical.
And yeah, and now we have like new program directors coming in and like we can work with them and they’ve got like awesome ideas. I actually think the you know there’s also a finite tenure at ARIA. I think that’s also really important because it brings new ideas in like you know I don’t want to be the old program director who’s like better in my day you know like so like having that iteration I think is so so critical and I’m really glad they built it in like that.
Juan Benet
Yeah, I see also that you wrote a book, the analog quantum simulation. talk to us about that.
Jacques Carolan
Oh, wow. Yeah. So, this was in my kind of philosophy days. I was always interested in the kind of philosophy of physics and then when I was doing my PhD, I kind of like left philosophy physics behind. And honestly, it’s like hard like being a philosopher is really hard. You have to like write arguments and I was like never that great at it. And I got approached by an incredible philosopher Karim who was really interested in analog simulations.
So to give an example of that like a fun one is special relativity. So it turns out that water flowing down a plug hole has similar equations like analogous equations to special relativity. Maybe general relativity. I forget exact I think it’s general. There are water analoges of like Hawking radiation. Right? So then the philosophical question is like what can water tell us about spacetime like and so that’s the kind of like line of inquiry and I was working on a field of analog quantum simulation like taking some kind of physical system maybe it’s like atoms or photons manipulating them and trying to learn something about chemical structure or learn something about a material like what can we actually learn from that
so this book was a kind of collaboration between myself Karim and another theoretical physicist just to like take some of these state-of-the-art examples and just like really unpack them through this philosophical lens and it was like it was a blast. It was actually really fun. I think we probably have I don’t know if we’ve sold a single book but it was a really fun thing to go through.
Juan Benet
How do you find like the right trade-off between applying some analogous structure too far or just right? Meaning some of like the early things that maybe held back physics in the classical to quantum leap was being too married to the analogies of when wave physics mattered and trying to think about quantum systems as either particle or wave instead of thinking of them as a totally different class of objects that had some of the properties like cur. Yeah, curious how you think about this.
Jacques Carolan
Like one of the interesting parts of kind of analoges is also just like a kind of mental playground, right? Like I think about things in this way. I don’t know. Let’s take like the classic like analog between electrical circuits and water flow, right? Like each of these things have analoges like voltage is flow rate like all those things. Actually, that’s pretty useful for a lot of situations just to think about it as like water. That’s helpful.
And there are things where it kind of falls over and you know the kind of like Kuhnian idea is that like at some point that enough [clears throat] evidence comes up and you’re like this is no longer a good model. Then you have to build new models. So like I actually think a big value is just like and we always do we all do it. We all have certain like analoges in our head of how things work. I do it in biology. I have oversimplified models. Of course we need to do that. Turns out this is maybe why I wasn’t a great philosopher. I was like I’m just a pragmatist. Like is it useful? Does it allow me to like build things or like do an experiment? And if not, like I don’t care so much.
Juan Benet
Yeah. One of the ones that I have found most interesting is or most useful is the analog leap that Dawkins made between genetic computation and then memetic computation of extending hey maybe all of the different rules and mathematical structures that emerge out of gene replication out of DNA strands and protein translation and sexual selection and all of this kind of stuff or the different types of selection over genetic strands can tell you something about how ideas propagate and replicate.
and form larger memetic complexes and you have like you know the analog of both a gene affecting and yielding a phenotype in a population and you have you know a memetic complex expressing itself in a large population of humans as it you know replicates and rips through some population. So I have found that like a super fascinating type of analog thing. Both interesting and valuable to find what properties about the two systems are similar enough where like some idea carries over or what are the practical realities that are different about both systems that then make it behave very differently. Things that are laws in one system don’t apply to the other or apply differently or like the constants are different or you know frictions are different.
Jacques Carolan
Yeah. Does it matter if it’s exactly the reality of what’s going on? Probably not. But is it useful? Is it explanatory? Like that is there’s so much power in that. I love that example. That’s a great example.
Juan Benet
You you also spent some time as an improviser.
Jacques Carolan
Oh yeah. [laughter] Some of that. Wow. Yeah. So this is once again just like jack of all trades and master of none. during my PhD I got into standup, nerds doing standup. It was like scientists doing standup and it was like very fun. And then I moved to the US for my postdoc and I was like I don’t know if I want to do standup here. There’s like cultural differences, like humor is different, but also like, you know, you spend a lot of time hanging out in some like pub by yourself or hanging out with other stand-ups. I don’t know how many stand-ups you have watching this show, but yeah. And it’s not always super fun.
So, I was like, I want to do something that’s community building and also comedy. Improv was so big in the US. It was like big in Boston where I was studying. So, I went and joined this like improv team and it was kind of like a Ponzi scheme, right? You have to like pay to do the classes and then you pay and then eventually you can like perform but like and then so it’s funny I haven’t hadn’t described it that way but it’s like yoga.
Juan Benet
Yeah. Yeah. 100% 100%. You get to the top and then like Yeah.
Jacques Carolan
You It’s just so good. You have to [laughter] keep doing it.
Juan Benet
Oh, exactly.
Jacques Carolan
And it’s kind of got a cult feel about it as well. And so I did it and like I absolutely loved it. And you know when you’re doing science it’s just like you just something to totally switch off. It’s just adults playing makebelieve. It’s like so dumb and it’s so fun and then when I moved back to the UK, London actually has a pretty big improv scene. It’s like a new thing and it’s like so I joined some of the theaters there and now I have like teams and it’s funny and it’s like also funny how it interacts with like my work. So like if I’m like this meeting’s dry, all right, everyone stand up. Let’s go. And I even do it with like my teams as well sometimes.
One lesson I take from improv, which I actually love, is that like your job as an improviser, it’s a team sport fundamentally. Your job as an improvis improviser is to make everyone else look incredible, right? Like if you come off stage and you’re like, “Man, I freaking kicked ass. You weren’t funny. You’re an asshole.” Okay. So, like if we can make other people and if you take that throughout life or take that throughout a workshop or a scientific endeavor, there’s actually so much power in that. Yeah. I don’t know what your thoughts.
Juan Benet
Yeah, I so I also did a bit of improv. I don’t keep up with it as much as I really should, but I found it to be not just the most fun but most practically useful activities that I ever undertook. I first got introduced to it through a class at Stanford where there was also this kind of like unreasonable effectiveness for improvisers where many of the people that took that class ended up being just dramatically more effective at a ton of other things. because they were able to jump into any group of people and just immediately adapt and handle problems and be able to approach all kinds of situations with this yes and mentality of that ends up being so effective and they tend to be able to teach other people. So improvisers because of the nature of the game you’re trying to help each other to construct a good scene and so on. You end up in this very helpful and friendly environment where once any team that has one improviser in it will just naturally kind of function better. So and did you end up doing it afterwards as well?
Jacques Carolan
Randomly here and there like play with friends but not I wish I wish I did.
Juan Benet
Yeah. It’s and also like there’s something about if you’ve like died on stage like you can do a lot of things like you know and that is actually you develop thick skin and it’s kind of wonderful.
Jacques Carolan
Yeah. Yeah. Yeah. [laughter] Yeah. Highly recommend it to really everyone for everything. It’s just one of those kind of unusually good things to do that tends to be applicable in almost any walk of life.
Juan Benet
Where can people watch you perform?
Jacques Carolan
Oh, okay. Wow. We actually do I normally don’t say them publicly. I’m actually not gonna say it publicly on
Juan Benet
So, so now the really committed people like seek you out, you find it, we’ll get the drink.
Jacques Carolan
I think there are ways. I think there are ways.
Juan Benet
Have you ever performed at the Fringe?
Jacques Carolan
I have never performed at the Fringe. I’m like so bummed. Yeah, we’ve got a monthly show for maybe like more tidbits for people, but I’ve never done it. I really want to, so it’s on my list.
Juan Benet
Yeah. Yeah. Well, well, we should do like a neurotech-oriented art show at some point.
Jacques Carolan
Yeah. We’ll have like, you know, wearable BCIs like responding. I think that would be so cool.
Juan Benet
Are you a reader of sci-fi?
Jacques Carolan
I’m actually like a kind of reasonably new reader of sci-fi actually. I still would argue that the great once again things need to be funny. I would argue like one of my favorite sci-fi which I read when I was a kid and I can pick up anytime is Hitchhiker’s Guide to the Galaxy.
Juan Benet
You know where this is headed.
Jacques Carolan
I just love it so much. There’s very few books I can just go back to. I’m like, “Oh, it’s extraordinary.”
Juan Benet
Yeah. And you keep finding layers. You read it again. You’re like, “Wait, hold on.”
Jacques Carolan
Yeah. I totally missed it the first time. Oh, it’s so good.
So, like I am really enjoying that and actually what I’m reading at the moment is I’m reading the Expanse books and I’m like half I’m like like book three or four and it’s like a blast and I watched the TV series but I just wanted something to get lost in and I’m really enjoying that.
Juan Benet
Yeah. Yeah. Any others?
Jacques Carolan
There’s a great book on Bell Labs. Is it like this is called the imagination factory?
Juan Benet
The idea factory.
Jacques Carolan
Yes. The idea factory. Like that.
Juan Benet
It is required reading at PL.
Jacques Carolan
Oh, really? I love it. And it’s also like one hell of a story as well. Like that’s I really really like that. And I go back to that.
Another one is like is it I imagined Worlds?
Juan Benet
Yeah, Imagined Worlds. Yeah.
Jacques Carolan
Another one is Imagined Worlds by Dyson. And it’s just like an incredible exploration into like future technologies and like what they can be. And I think he like wrote it in the 80s or something and you like look at it now and it talks about like molecular machines and like so much cool stuff. It’s like super readable but just so visionary and I think things which like this is part of the reason why I’m really enjoying sci-fi like things that expand the mind of like what is possible I just find so fascinating and it could be science books it could be like sci-fi books just that whole spectrum I think is incredible also has this other books I don’t know if it’s Imagined Worlds might be a different one it’s just a collection of essays that like take some like interesting question and take it really far that I found like super fascinating.
Juan Benet
There was like just this super contrarian perspective where Freeman Dyson was able to just like reflect back on some dogma of the scientific or academic establishment and just take a very strong counterposition and just point out how something was like broken or wrong or whatever and then just you know pursue that idea like pretty far.
Jacques Carolan
Oh yeah.
My other like recommended reading just like a call back to our early discussion is like if you are a physicist or like mathemat whatever like interested in maybe getting into neuroscience read physical principles of scalable recording. I just like that I just people should read.
Juan Benet
Yeah. Yeah. And yeah, again legendary author list. In fact, one of your PM David is also one of the authors from sci-fi. You might enjoy We Are Legion, We Are Bob, which is a story about a person who gets uploaded into a van probe and he’s trying to save the world and hilarity ensues.
It’s quite It’s like comedy as well, like Yeah. Yeah. It’s a pretty funny book. It was a little bit slowed for it probably would be slow for most people’s tastes in sci-fi because I think there’s so many advanced ideas that I don’t know if this is the case but I think the author was explaining it too much and maybe but then he realized after releasing the first couple books that the audience was totally right there with him and knew all about it and so like the later books in the series just get very fast and pretty fun. So has like a slower start in like the world building, but it is very good.
Jacques Carolan
And yeah, I feel like all of your guests will probably like suggest this, but like obviously Pantheon is incredible.
Juan Benet
Yeah, Pantheon is amazing. They did a phenomenal phenomenal job. I kind of feel this kind of sense of loss of kind of Japan had cultivated this media side to it where like when Japan was leading technologically in a bunch of areas, it cultivated this area of media through both manga and anime that explored really deep questions about reality and seeded so much of like what you know are modern stories that end up being very impactful both in sci-fi and fantasy and so on.
And as like the bubble burst in Japan and it sort of started falling behind in the technology, I feel like it’s sort of missing. Like a lot of those stories became less frontier oriented, less thinking about where the future was going. I mean, they ended up inspiring other things like Pantheon and beyond. but you know, I always wonder like what would have happened if like the bubble in Japan hadn’t happened, like if it hadn’t gone so crazy and bursted so hard, if you had just kind of kept being this intense leader and how society would be different today.
Jacques Carolan
Yeah. Well, it’s actually in like you Ryota Kanai who like is funding stuff at Araya in Japan actually funded a number of manga artists to write and illustrate pieces about BCI.
Juan Benet
Oh wow.
Jacques Carolan
And like imagining what the future it is. I can’t remember the name of it. Like I’ll just send it to you. I’ll share it with you. It’s like it’s really cool and I was like oh I just love this idea of like what we can do as a funding agent. It’s like a kind of kind of cool.
Juan Benet
Yeah. I would love to have a ton of amazing artists envision very positive futures where neuro technology is like an ever everyday sort of thing. Like sci-fi has this problem where because when you’re imagining the future and you’re thinking through the lens of some technology the it has such a big power in the story cuz as as a writer you tend to extract elements and remove elements when they’re not doing something important for the story. Therefore, for something to remain in the story, it ends up having to play a very important role.
And so, you end up in a situation where because of the level of power that some new technology gives you. And I think because I think humans are just tend to be more worried about like downsides than trying to paint positive pictures. You end up with a selective selection pressure where all media about the future tends to skew very negative because the if the technology isn’t in the story, it has to be there for a reason and that reason must be to create some dystopia you have to fight. And so we end up with this very bad skewed perspective where all of our media about the future is just like all these dystopic narratives and it really sucks. It doesn’t give us like good things to aim for.
And so we kind of need to like forcibly counterbalance that by getting a ton of artists to just paint stories of the future where there are these elements but they’re not they actually think about all the positive cases like where are all the transformative amazing stories about neurotech being able to like regrow a spinal cord or something like that or like a love story that happens to have neuro tech in it or like
Jacques Carolan
Yeah. Yeah. I’ I’ve agreed. I’d love to see that. That would be great.
Juan Benet
any advice that you would have for either people in the field today what should they think about or look at or maybe people going through university now or postdocs considering shifting fields like
Jacques Carolan
I don’t know I will say like yeah maybe I’ll give my advice to folks that are working in a different field like I think it’s valuable to like find those people that inspire you and maybe have taken a particular career path like there’s so many people who have taken really nonlinear career paths that I you know that really inspire me some of my friends some are not my friends and just kind of see if you can get time them. See if you can understand like what has driven towards that. You have a you’ll have a pretty good gut sense of where you want to go and people will tell you advice and listen to the things that resonate. Ignore the things that don’t. That’s totally fine. And it’s totally possible to make that jump.
I think be voracious, read, be excited. There is so much work to do in this field. There is so much left to do. I think that’s easy to forget given the excitement that we see in certain corners of the neurotech field. There’s so much and we need incredible talent in there. So yeah.
Juan Benet
And and if you were to you know think out to 2030, 2035, 2040 like I one of those do you have some like crisp view of how the world would be very different then and you know tell us a bit about it.
Jacques Carolan
I think if I do find it hard to project really far into the future with like neurotech and everything that’s happening but even like a kind of 5 to 10 year I do believe that we’ll I hope there will be a big c this is like a footnote a cultural push whereby neuropsychiatric conditions and neurological conditions don’t have the stigma that’s associated with them. I do believe we can be in a situation where we have significantly better treatments through large scale phenotyping through new precise tools that can be much more personalized, much much more effective. I believe that is possible like the science en like says it’s possible and it’s just a coordination problem and the signals I’m seeing is that like I think we’ll get there.
Juan Benet
Yeah. Awesome. Well, thank you very much for joining us.
Jacques Carolan
Thank you so much. It was a blast.
Juan Benet
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