BJKS Podcast

64. Gareth Barnes: MEG, OPM-MEG and the beauty of tinkering

November 17, 2022
BJKS Podcast
64. Gareth Barnes: MEG, OPM-MEG and the beauty of tinkering
Show Notes Transcript Chapter Markers

Gareth Barnes is a professor at University College London, where he is Head of  Magnetoencephalography. We talk about how Gareth randomly stumbled into working on MEG, what MEG is, and some of his recent projects, including the exciting new generation of MEG scanners: OPM-MEG.

BJKS Podcast is a podcast about neuroscience, psychology, and anything vaguely related, hosted by Benjamin James Kuper-Smith. In 2022, episodes appear roughly twice per month. You can find the podcast on all podcasting platforms (e.g., Spotify, Apple/Google Podcasts, etc.). 

0:00:03: How I found out about Gareth's work
0:02:31: What is MEG?
0:07:04: Flexible headcasts for MEG
0:19:49: How Gareth accidentally  started working on MEG (after writing fiction in France)
0:28:46: The early days of MEG at Aston University (starting with a  single channel)
0:40:58: The new generation of MEG:  Optically pumped magnetometers (OPM-MEG)
1:13:33: Mouth MEG and measuring hippocampus with MEG
1:21:06: The relationship between methods development and discovery in basic science

Podcast links

Gareth's links

Ben's links

MEG in the UK:
MEG image:
Cerca MEG:
Fieldline MEG:
Young Epilepsy:
Sphenoidal electrodes:

Boto, ... & Brookes (2018). Moving magnetoencephalography towards real-world applications with a wearable system. Nature.
Boto, ... & Brookes (2019). Wearable neuroimaging: Combining and contrasting magnetoencephalography and electroencephalography. NeuroImage.
Hill, ... & Brookes (2019). A tool for functional brain imaging with lifespan compliance. Nature Communications.
Meyer, ... & Barnes (2017). Flexible head-casts for high spatial precision MEG. Journal of neuroscience methods.
Sander, ... & Knappe (2012). Magnetoencephalography with a chip-scale atomic magnetometer. Biomedical optics express.
Seymour, ... & Maguire (2021). Using OPMs to measure neural activity in standing, mobile participants. NeuroImage.
Stangl, ... & Suthana (2021). Boundary-anchored neural mechanisms of location-encoding for self and others. Nature.
Tierney, ... & Barnes (2019). Optically pumped magnetometers: From quantum origins to multi-channel magnetoencephalography. NeuroImage.
Tierney, ... & Barnes (2021). Mouth magnetoencephalography: A unique perspective on the human hippocampus. NeuroImage.
Vivekananda, ... & Walker (2020). Optically pumped magnetoencephalography in epilepsy. Annals of clinical and translational neurology.

(This is an automated transcript that contains many errors)

Benjamin James Kuper-Smith: [00:00:00] Yeah, I thought somewhat unusually. I'll start with a, with a small or short story about how kind of I found out about some of the work you're doing and, um, I think that will, Yeah, it relates to quite a few different things that I guess we'll be talking about today. So I did my, uh, masters at, so I did the dual masters, that's one year at UCO and WA in Paris, and the dual masters in Britain, Mind Sciences. 

And in each of those cities you do a masters project. For my masters' project at ucl, I worked in S lab and I worked with , uh, Avi, I, I was gonna apologize to the Polish people, but then again you, you made the language. Don't blame me, . Um, I tried my hardest anyway, so , um, he was my supervisor and then we, we had a meeting one day and then, you know, said like, Hey, how you doing? 

And he's like, Oh good, we just had this, So this was 2000 and. Maybe 15. Um, and he said, Oh yeah. So we just came from this meeting with these physicists and they taught us about this like, new [00:01:00] imaging system that, uh, it's like really small, you know, it's the size of remote control. You can, you don't need to cool it. 

It's pretty cool. And I mean, at the time I was like, Yeah, whatever. Because I didn't really know much about imagery. I never used it. I studied psychology where, I dunno, imagery seemed a bit distant and we didn't have one at Goldsmiths. But that was the first time I kind of, I guess I, I heard about that thing. 

And then, uh, for my second project in, in Paris, then I worked at Nespin with Aaron Schroer. And there I actually work used simultaneous eeg. And, and so then as I was working with Meg, I suddenly realized like, you know, lots of the problems that come along with Meg. And then suddenly this, this brief explanation he gave me of the future of MG seemed a lot more interesting than it had, um, at the beginning. 

So, um, Yeah. And it seems in general that like a lot of the problems we had, you are working on solving in various ways. So yeah, I'm looking forward to to talking about all the different stuff you've [00:02:00] been able to. Yeah. I dunno whether you actually gave the talk in London or whether it 

Gareth Barnes: I, I, I was wondering yeah, where, which meeting Rich is talking about, but it was about that time, 2015 when we were just all trying to, it was before we got any money to do the research. So we were inviting people, giving talks to ourselves, everything like that. It was. There was a lot of, Yeah, it was a really exciting time. 

And I think we had maybe one channel, maybe by then, maybe one channel, but that was it. Yeah. 

Benjamin James Kuper-Smith: Yeah, so I mean, I guess we'll be talking about Meg, which is what you work on, uh, today. Um, I mean, we'll be talking today. You've been working on it for a while. Maybe just to briefly introduce Meg to listeners who aren't quite as familiar. I guess it seems to me always Meg's, like, it seems like a slightly exotic and less well known cousin of eeg. 

Um, I guess because it's much more expensive and does something vaguely similar, and most places don't have an imaging machine. So maybe can you just Yeah. Briefly outline kind of what ISG and maybe how does it relate to EEG from a scientific perspective. Like what's [00:03:00] the differences in what we can measure and practically, like why would you use one or the other, 

Gareth Barnes: yeah. So that's a good, it's a good place to, EG is a very good place to start because, um, EG and G are measuring the same underlying phenomenon. Current flow along a neuronal cell body. What EEG measures are the, the currents that go to cancel that primary current flow, The currents that reach your scalp, you know, you have current flow one direction, but you need to cancel it somehow. 

And you get lots of secondary currents set up that, that from a pattern on your scalp, and you can measure the, the potential difference on your scope with eeg. And EEG, as you know, is super, uh, affordable and it's clinically used around the world. It's a fantastic technique and, um, and it's been around for like a hundred years or so. 

So it's, and, and it's still going strong. The main motivation for EEG is it's really tricky to, to follow where those secondary curr are going because they, they get diverted by your tissues and your eyeballs and they just go over the place. So with EEG [00:04:00] it's, it's, it can be really tricky to find it exactly what's giving rise to the, the pattern you see on the scalp. 

The nice thing about Meg is that we're not measuring, Oh, The majority of the thing we're measuring rather, is due to the, the primary current for the, the flow in the neuronal cell body. And the great thing about the that is that this current flow in the neuron cell body creates a magnetic field. And that magnetic field is, is relatively immune to the different conductivities of the head. 

And all these other squishy medium, it's gonna squishy media, it's gonna pass through. And so what you see outside the head when this, the, this, this neural activity is going on, If you imagine them both at the same time, see an EEG pattern on your scalp, but you also see a magnetic field pattern at 90 degrees to that which is the, the consequence of current flowing down effectively, current flowing down a wire. 

It's, um, it's this, this, I think it's the right hand rule where the current flows this way and the magnet field goes around the wire. Um, so the great thing, so with Meg, I mean the, the main [00:05:00] problem with is that the fields are trying to measure, you know, something like a hundred millionth of the, the earth field that we're sitting in us. 

They're tiny, tiny. Feels. Um, so you can't do it on a shoestring, like in EEG system. You can pick up in, you could probably pick it up on the high street. That would work really well. But an EEG system is a, you know, is, is a lot more ex, traditionally been a lot more expensive. And part, a significant part of that expense is just trying to put yourself into an environment where there's no interfering magnetic fields. 

Because even a car driving past on the road outside would be a thousand times bigger than what you could ever measure from somebody's brain, for example. So that's, that's the challenge. So you basically pay an extra million pounds for an MEG system, but you, if you can measure what's coming out of outta somebody's head, the, the problem of finding out where it is much simpler. 

So you, you're paying for that simplicity of, of working out where things. 

Benjamin James Kuper-Smith: Yeah. And I guess because of this, like additional cost, meg's [00:06:00] pretty rare. I mean, I, I looked it up. There's this why I randomly came across this with. UK do UK or something like that. And I think there's 10 sites in the entire UK or something that have mg 

Gareth Barnes: that they took a long time to come. I mean, I started MG in the, in the 1990s and for a long time it was just basically one or two sites with mg and it was take, you know, I think, I think Germany, for example, is a lot faster on the uptake with mg, but again, there's, there's not many sites per country. 

And, and that's, you know, that's a shame. And the science hasn't been able to propagate very quickly because it's kind of a, a bit of a, a rich, you know, a rich person's kit. You know, it, it's, you know, you need a lot of cash and a lot of expertise to get one running, but hope, hopefully the OPMs will change that to a certain 

Benjamin James Kuper-Smith: Yeah, exactly. Exactly. I mean, that's, that's part of why I invited you because I guess the, the new generation of Meg Sense seems to. I should say maintain a lot of the advantages while taking away a lot of the disadvantages. [00:07:00] Um, yeah. But I guess, um, I wanted to get to that later. First, I thought I'd, um, I wanna talk a little bit about a different project you did, which is still within traditional MHG scanners. 

Um, I just wanted to ask about, so, um, about the, the flexible head casts, 

Gareth Barnes: Oh, alright. Yeah. Yeah. 

Benjamin James Kuper-Smith: you and your team developed. Uh, back to me doing my master's project with Aaron sch, I'm, I'm like 99% sure that when we, when I was there, he ordered or someone from your lab helped to make on or something like that, because I remember him saying, so. 

I mean, so the problem with eeg, I guess you have this cap on, right? So you can, different head sizes and all that kind of stuff accounts for if you move your head, it's not that big of a problem because the electrodes move with you. Whereas in Meg you have this fixed, uh, I dunno what you call it exactly. 

Gareth Barnes: A Duer. It's called a duer. Yeah, it's like a big thermos. Fast care duer. Yeah. 

Benjamin James Kuper-Smith: Yeah, and you kind of just put your head into it and then, you know, I mean, my head is almost too big for it. , [00:08:00] I have very little space to move, but if you're smaller, then you have quite a lot of sideway space, especially to move. Uh, yeah. So part of that, um, so what, what Aaron then did, he basically said like, Yeah, there's these people, you know, you see how at the imaging group they're making these head casts basically, that you can, you make specific for a person to, um, reduce the movement, that kinda stuff. 

So, um, I, I'm, it really annoys me that, I can't remember this more precisely, but I'm pretty sure he got it and then tried it out and we were just like already excited about it. But, um, yeah. Can you kind of introduce the project and 

Gareth Barnes: Yeah, Yeah, 

Benjamin James Kuper-Smith: how it works? 

Gareth Barnes: I, I think I even remember our visiting us actually. Yeah. Yeah. So, so first of all, they didn't start off as flexible head cast. They were solid, solid nylon head cast to start off with. But as you, as you, as you say that, that one of the. , one of the issues with MG is, is that you, what the great thing about MG is you don't have to stick any electrodes on. 

Okay, that's brilliant. So just stick somebody's head in this kind of cylindrical hollow vessel [00:09:00] and you start measuring their brain activity. We do have, you know, coils on their face so that we know where their head is, but we only know where the head is. You know, when you account for how difficult it's to put, um, a collar at a specific landmark, you know, especially into between operators, it's really difficult to know precisely where that person's brain is with respect to the sensors. 

And often, for example, what we were doing, a lot of, you know, in the, in the nineties and two thousands, we were doing a lot of comparison with FMRI and, you know, other brain imaging pictures. And we'd always see that like they didn't match up the, the fmri or the MEG and some other hypothesis weren't quite there. 

So, you know, half a centimeter centimeter difference. And there, there was always this. This thing that, oh, that's co-registration error. You know, that's, that's just the error for not knowing where somebody's head is. Um, and it always, it always, it still does seem like a big, like a bit of a fiddle, a fiddle factor to [00:10:00] me. 

And, and it's a shame because, you know, image's a direct measure of neuronal activity, and, and it, it should, it should, you know, if we have a model, if we make it the correct model of what's going on in the brain, we should be precise about it. And it just seemed a shame that you've got this fantastic, you know, fantastically sensitive piece of equipment, but it's, you know, but you, but then you, you lose all the resolution and all your modeling, everything just goes out the window cuz you let the subject, you give the subject comfort basically. 

Um, uh, and it's a bit like, imagine trying to look, buying a really expensive telescope, but then putting on your bed and trying to look at the stars with it, you know, it's just, you lose all that precision. So that's the problem I I we saw with M E G. And so we tried to mitigate that by, by forbidding the subject to move their head and effectively building them into the scanner. 

So we, we built nylon cast that fit my head on the inside, for example. And the, and the meg, the inside of the meg is kind of the outside. So [00:11:00] I went into the scanner, like, like a stopper in a bottle, you know, and I couldn't see, you know, it was completely obscured, my eyes and, and my ears, everything. I was just in a, like in my head, in a cork effectively that went into this system. 

And, you know, that's brilliant for engineers, but you know, clearly we couldn't do very much, you know, the, the psychologists and other people were a bit, you know, there's the thing, well, you can't see, you can't hear what's the point of that. And also the trouble with the, the, the rigid head cast was, was when we first tried it because it, it's like these things are tricky to build because if you, and this was also when 3D printing was kind of cool, so it was one of the first 3D printers we used. 

But if you build it, You can build it too. You can, you can allow too much. You can build it. Um, you can either build, it's either too big to go into the, the MG scanner or too tight on your head, or it's too loose on your head and too loose on the scanner. So there's a really fine margin of getting it. And so you, you, you're at the level where you, you you, you're almost stuck inside the, once [00:12:00] you get in, it's difficult to get you out again sometimes with these solid things. 

So that was another kind of, you know, concern. Um, 

Benjamin James Kuper-Smith: Especially if like me, or at least vaguely claustrophobic 

Gareth Barnes: well, exactly. Yeah, exactly. I mean, yeah, exactly. I mean, the only, yeah, maybe it's not a thing, but the only good thing I think is you couldn't see anything. So as soon as you put it on, you didn't know you were jammed into a, into a, you know, you just knew you had something around your face. Um, but, uh, yeah, so that, that was the motivation for the, the more flexible. 

Arrangement. And I, I should say that we did lots, we did lots of simulations to try to work out what was, what was holding back. Cuz everybody kind of tries or likes to dismiss MG as having high temporal resolution, but low spatial resolution. And that I don't really buy that. It's, it's, it's, it's got high temporal resolution, but the spatial resolution only really limited by how well you can explain the data or model the data. 

And so that was the, uh, that was the motivation is try to get rid of this fiddle factor, the code registration. Also try to get some really good high quality data [00:13:00] so you could really test whether, you know, or really prove to everybody else that MG was better than the, the pub talk, if you like. Uh, and, and so that was the motivation for it. 

And then we went to the flexible head caster, allow more people to sit in it. Uh, and then we were able to do some nice experiments with those flexible head casts, had more people that, you know, not just me in, in the scanner. Uh, and it was, yeah, very, it was very exciting. Um, but of course, as you say, you know, There's only certain bunch of people you can get to do this kind of stuff, because every, you know, even people that don't realize they're claustrophobic when you, when you jam them into this scanner, it's quite an intimidating experience. 

And there's not many, you know, not a huge nu number of people that can remain calm and focused on the task at hand. 

Benjamin James Kuper-Smith: I mean, that was pretty much the first time I, I realized that when I was in the, and I was without the head cars. Right. But I mean, I'm also very tall, so I pretty much am the size of whatever you can fit into the imagery scanner. But yeah, 

Gareth Barnes: Yeah, yeah, yeah, Exactly. And that room in Hamburg is not, not a huge [00:14:00] room, is it? It's not a huge shielded room there either, is it? So it's, I can see that. 

Benjamin James Kuper-Smith: that was a right, and, and that wasn't the problem I spent, It was, yeah, it was the size of a room. But yeah, just the kind of like, I felt like, I'm not sure I could get out of this really without help 

Gareth Barnes: okay. Yeah. So it's not a good, it's not not a good look. I mean, and also the, the other, I mean the, the, I mean the other head cast, I think they were really. They really exciting. At the time, the main limitation was you could only scan healthy young people, you know, because you had to be limb enough to, to, to get yourself into po 

Benjamin James Kuper-Smith: Red. 

Gareth Barnes: into position with, because the danger, because you are so constrained that we had to do loads of safety and publish load. 

And I spent all my, I spent most of my time telling people how dangerous it could be if you didn't follow all the safety instructions, because you don't wanna, you'd wanna move the, the MEG system while somebody's head's inside it, basically. 

Benjamin James Kuper-Smith: Uh, right. So is it because like your, your head is stuck, so 

Gareth Barnes: your head stuck. Yeah, exactly. It's really, you know, it's, it's [00:15:00] like meg's great cuz it's not invasive and, you know, compared to many other new imaging techniques, it's so, it's super safe. But, but, but the head cast made it dangerous, you 

Benjamin James Kuper-Smith: Yeah. I mean, so yeah, the, yeah, especially I guess the one in a near bin, you know, you, you, you lower, you, you put the seat to the lowest position, right? And then you kind of pedal people up 

Gareth Barnes: Oh, I see. Okay. 

Benjamin James Kuper-Smith: thing. I dunno whether all of them do that, but yeah, I could see like if your head's kind of stuck and you pedal incorrectly or something, then 

Gareth Barnes: yeah, yeah. Exactly. What we had to do in the end, what we had to do is we had to get the position, get, get the, get the, the, the system, the chair and the, the, the, the meg system at the right level so your head would fit in right. Then get the person that put on their head cast, and then get them to squish in themselves, you know, use their own force to push them in, because just the thought of using those hydraulics to move anything once somebody's head was enclosed, was, was, you know, just too, too 

Benjamin James Kuper-Smith: Uh, maybe just briefly, I guess I'll, I'll try and link to like a photo of an, [00:16:00] for the people who haven't like seen one, because I guess this might be vaguely confusing now, but I think once you maybe see it and once you've like sat in one, this will make a lot more sense. But I'll try and find a like nice photo that kind of maybe shows a bit better what it looks 

Gareth Barnes: Cool. 

Benjamin James Kuper-Smith: Um, but, but so the, um, so I think the one that um, Aaron got was he sent you an MRI scan and then you used that to create the, a mold of the outer of his head. Is that still what ended up being the flexible ones or is that still the rigid ones? 

Gareth Barnes: Uh, so, so, so yeah, we, we used, we used, um, well, was the only one ever put on a flexible one, I'm sorry, a rigid one, I think, I think the ones that Aaron got. Yeah. So we, we, we typically do an anatomical scan of the person with an MRI and then take the out there, the scalp outline. And then also, I mean, later we tr we've, initially we also did it with optical scanning, which was also worked fine, you know, so just wearing a, somebody subject wearing a swimming cap and then optical scanning the upside of the head, that worked okay as well. 

But with, we often get an mri, so [00:17:00] it was, it was an easy win. Just to take the outline of the, the, the anatomical. 

Benjamin James Kuper-Smith: so is that still required? Because I guess one question that we had kind of around is like, how usable is this? Like, okay, it might increase the, the signal that you, the precision of the signal you get from the imaging machine, but if every participant needs to have to do an MRI first, and then you wait until you get the like head cast made for them, that kinda stuff. 

And it just makes it very burdensome, even more expensive. Right. So is that still like, Factor here, or 

Gareth Barnes: Yeah, I mean, I, I, I, it's not, it's, it's, I I'd say it's, now we've got alternative technologies, which we'll talk about later. It's, it's not a very good, it's not, not the way to go for the future, I think. Um, but the, what it would be good for would be to do study one subject or a small number of subjects over a long period of time. 

Cause you, you have to, like you say, you have to invest a huge amount in each person. And so if you had to get them to, to learn something or grow old or something like that, you know, then it's worth it. But actually, [00:18:00] For a group study, uh, for example, you don't gain a lot because of course there's, there's all the variability then isn't in the meg signals between the people, you know, So, so you don't gain much by short scans on lots of people. 

You might as well just not, it doesn't really matter where their head is then it's all, it's all lost in the individual variability. But, but if you're really interested in, say, what happened when you, you know, when you amputated one of my fingers and whether my brain would reorganize, then, then it would be a with one investment. 

But not, not for larger groups only, Only for, you know, very similar to the way they do things in the animal physiology world where they use one or two animals and show that it, it works on one and then also on another, basically. Uh, so that would be the way I would use it. Um, if, but we, we haven't used them again. 

Um, for, I think for five years now. We've not used them. Since, since that, since that time. And, and it was, I think it, [00:19:00] and, and most of it really was just, as you say, it was hugely burdensome. Burdensome, you know, on the, the researcher and, and the participants. And it also adds a level of danger that is not acceptable. 

Um, when you don't need it. When you don't need it. 

Benjamin James Kuper-Smith: To say it sounded like such a cool thing, uh, when, when it was made, but I 

Gareth Barnes: it sounded, it does sound great, but it's, it's, you know, I think it's probably also getting old. You realize all the things that can go wrong, You know, you think all the things that can go wrong. When I was younger, I never realized how many things, how can go wrong, and now I see 

Benjamin James Kuper-Smith: and then actually will. Yeah. 

Gareth Barnes: Yes, exactly. Yeah. Yeah, 

Benjamin James Kuper-Smith: Yeah. I mean, I guess, yeah, also, I guess part of the problems that this solves also solved with the new system for energy anyway. Um, so yeah. I guess, and before we get to that, I just wanted to ask just briefly kind of like how. Yeah, I like to kind of know like how people get into what they do. 

Um, so my kind of, it's not really a theory, but I feel like most of the people I know who do [00:20:00] maths developments started off as a physicist or an engineer, and then at some point became interested in kind of biological applications of this or something like that. Um, so I don't actually know what you did. 

I couldn't find like a, a full CV or something. So I'm curious, like is um, Yeah, kind of what. 

Gareth Barnes: so you're quite right. I mean, I, I was an electronic engineer. I did electronic engineering in, in York University, but when I, when I left York, I saw I'd never enter a university again or touch a computer again cuz I was just so, Well, I, I dunno, I just really, I had, I just felt I didn't fit into academia and I didn't, you know, I probably didn't pay as much attention as I should have during my degree probably. 

But, um, it really put me, well maybe, maybe it was my, maybe myself, I put myself off engineering I think cuz I, it was my hobby when I was younger. Then I went, did my university degree, and then I just lost interest in it. Uh, and then I had a couple of viewers where I wasn't, you know, where I was trying to be, [00:21:00] you know, trying to live a romantic kind of life, like kind of thing. 

And, um, maybe you don't want to broadcast this in your podcast, but I ended up in, in science completely randomly. I, I, I was trying to get to America to pick oranges. Um, 

Benjamin James Kuper-Smith: Okay. Why American Oranges? 

Gareth Barnes: I, it was all the Steinbeck kind of stuff, you know, And it was like one of those things that I thought, you know, I, I'd been living in France for a couple of years and, and then I thought time to go to America, and then I went back to Wales and spent all my money. 

And so I thought, I, I need to get to America. And then there was the, this advert. My, my, my dad was also trying to get me to get a proper career, and he said, Just apply for some stuff and if it doesn't, you know, if it doesn't come off, then it doesn't matter. And I applied for a PhD, uh, studentship, and it said five it in the, in the advert, which is a very short advert, it said, it mentioned 5,000 pounds in it. 

It's a studentship. And I thought, That'll [00:22:00] get me to America. That'll be, that'll be enough. Um, and that, that happened to be in M Meg that just happened to be in Meg because somebody had dropped out of M meg in Aston University. They dropped out. It was a funded studentship. The person thought there was no future in Meg and they dropped out of it. 

And the studentship had just come up. It happened to be the right time for me, and that's how I ended up doing M meg. It was just a, you know, a series of happy coincidences. 

Benjamin James Kuper-Smith: Okay, this is, this is really interesting. I did not expect this. Um, I really love when when you ask a question that is often answered with, you know, Well, I did engineering and then I saw this, like one of this, you know, professors mentioned this and then I got interested in this and so I did it. That's often, you know, what the story is, but this is a lot more interesting. 

Um, if you don't mind, like what were you doing? I mean, you said you went France for a few years, being living a romantic life. 

Gareth Barnes: Yeah. I was trying, I was, I thought I could be a writer. I thought I could be a writer, so I had 

Benjamin James Kuper-Smith: what kind of writer? 

Gareth Barnes: well, I guess a [00:23:00] fiction writer of fiction. I think, I thought I could be. Um, that was my kind of, that's, that's how I saw myself, you know, And I, but I was, um, I was, I did various jobs in France, but I, I was, you know, um, caretaker and a night watchman and worked in McDonald's and, um, taught English and stuff like that. 

And I had a little typewriter in. You know, lovely French, uh, you know, flat, which I tap on and, you know, pointlessly, uh, Yeah. And that, that, and that's, that's, and I, yeah, I've had a quite a lovely time, but I never, I, I thought that would be, that was my corner and I thought, well, I'll just be sitting around, you know, smoking cigarettes if I could and typing, you know, you know, typing away. 

But it never really worked out for me. 

Benjamin James Kuper-Smith: Did you ever finish anything or like, why? Why did it all work? Did you not finish, did you, did you finish? And no one liked it? 

Gareth Barnes: No, I think I just never wrote much. I think I, I used to write, I used to try to discipline myself to write every day and stuff like that, and I used to write lots of little short [00:24:00] things, and I sent a couple off to magazines and stuff like that. Um, but they, they, you know, they got very nice. It was a time when you could send stuff to people and they'd send you a nice rejection letter and stuff, so that was nice, you know, all by post. 

But, yeah. But I think I, I think I would've, you know, if, if, if I had, if I got to America to pick these oranges, you know, then that would've continued This. You know, this kind of quest to just do, you know, just, you know, just, uh, well just be, Yeah, just, I don't think I had a very good idea what life was about. 

I didn't really get the link between earning money and stuff like that and, you know, and so I would just go, go from overdraft to overdraft, and then I'd get a, you know, Rubbishy job to pay that overdraft off. And then, so I, I was just, I was trying to live a fantasy life, really. But, uh, but, but anyway, I had a nice time. 

A lovely time. 

Benjamin James Kuper-Smith: Okay. Did you, uh, seems to be quite the contrast between like this like romantic ideal lifestyle of like, you know, living freely doing these [00:25:00] things. And then also engineering, which to me always seems very much more like applied and get, like, make it work rather than, you know. So, I mean, there's quite a contrast it seems to me, right. 

Gareth Barnes: Yeah. I, I can't, I can't really resolve it for you, but except I think it is kind of, um, It, there's, there's, well, there's, there's, there's creativity in both. And maybe the creativity in, in the engineering solutions that, that suits me better. It's just they're, they're very, you know, you don't have to have a huge imagination, you know, and, and, and you can put your, and, and they're practical solutions to them, basically. 

And I, and I'm not, you know, and, and I've realized I'm not a particularly good writer. I'm not particularly good at expressing myself, but that, that's the nice thing about engineering is you can, you can bash something together and it will more or less work, you know? And, and that's, and that's satisfying. 

You know, you can get something done. You can, you can fix things basically. Um, but yeah, you're [00:26:00] right. It's, it's a contrast between my younger kind of idealistic stuff and then realizing what you can actually do, you know, in life. 

Benjamin James Kuper-Smith: Has that experience helped you in your job? Now this kind, I mean, you must have like learned quite a lot of stuff that I guess many people who go the like traditional academic route of basically be in school for most of their life might not have had. 

Gareth Barnes: Yeah. Well, I must say, I tell you the one thing I really liked about academia, um, because during my PhD I spent a lot of time in, in, in Moscow, in Russia, you know, working with the guy, I traveled so much. I mean, and that was the best thing about academia for me. That was the thing that kept me in academia was the ability just to keep traveling and, you know, meeting all these people. 

And it's such a shame now. You can't, you know, the traveling is, you know, it's so difficult. But, um, it, it used to be the thing that really, really excited me to, to meet all, to go around the world and to meet all these people. Yeah. And, and, and, and meet exciting, lovely people like yourself. You know? It's, it's quite a privilege, you know? 

I think, and I think that's the nice thing about academics [00:27:00] as well. They're naturally quite an. , you know, an open and straightforward, uh, bunch of people. I think it's a nice, you know, it was a, it was a lovely, and I'm sure it'll get back to being a lovely life academia, but I think it's just the, the lack of travel for young people. 

I really feel sorry for, for you guys that, you know, you can't do as much traveling as we used to do. 

Benjamin James Kuper-Smith: I mean because of Covid or because. 

Gareth Barnes: Yeah. Because of covid and because of air miles and things, you know, because of the, the pollution, the planet and stuff like that, which we didn't think about at all, unfortunately in the, in the nineties, you know, just didn't, didn't even cross my mind at all. 

But now, now I feel, you know, feel bad about it. Definitely. You know, and interesting. Well, just diversion. But interestingly, last time I, we met, uh, in Eppendorf, uh, we went out for dinner, uh, with TOAs Donna and, um, Alte and, and another colleague, and Tobias was, was. I just read this article and it was saying that maybe in a year or two or in the future, flying will be [00:28:00] frowned upon. 

And, you know, people won't be going to academic conferences. And I never think, Oh, that's just crazy. What would be the fun in that? And, you know, it's came true within a month of him saying it, you know, so it was quite, um, quite, it was quite, quite prophetic kind of conversation. Yeah. But he was, he was right. 

He was dead, right? Yeah. 

Benjamin James Kuper-Smith: And I guess you can still use trains and stuff. I mean, Yeah, depending where you want to go. 

Gareth Barnes: Yeah, yeah. Yeah. 

Benjamin James Kuper-Smith: us very prohibitive, but at least I guess within Europe you can still 

Gareth Barnes: it's, I think it's, it's really great. And, but it's compounded for us in uk it's a bit, it's compounded by the Brexit thing, you know, it's just, it's a bit, we're a bit little bit isolated. Um, but it was, it is fantastic just to get on a train or, or go somewhere. 

Benjamin James Kuper-Smith: Yeah. I mean, one, one question I, um, wanted to ask in, in terms of like how you, you know, got to what you're doing right now, is that one thing I found really interesting is that, you know, I mean, I said I couldn't really find much about you, like severe or anything, but on, I guess the UCL page, it did say PhD as university and [00:29:00] it said you worked at Aston University and then at ucl. 

My, I hope I'm not offending too many people with this, but my initial reaction was what is Aston University? And I mean, I'll say this with kind of a caveat in two parts. The first is I didn't really grow up in England, only the first four years of my life and then my university studies, but not my school years. 

And secondly, once you cross a aboard, the fame or reputation of university basically disappears unless your Oxford, Cambridge, 

Gareth Barnes: Yeah, yeah, 

Benjamin James Kuper-Smith: Apart from that, there's, I mean, I'm still amazed at how many, not just people in general or people who went to university, but people who actually do psychology or neuroscience don't know what UCLA is. 

When I tell them, like, it's still amazes me whether like in Germany, right, Whether like you see like, I dunno where uc is, right? It's 

Gareth Barnes: Okay. Yeah. Yeah. Okay. 

Benjamin James Kuper-Smith: yeah. So it's maybe not that surprising that many places are well known, but yeah, I was just curious like. I didn't check this systematically, but it seems to me that basically everyone [00:30:00] at UCL, who's English and a professor did their PhD at basically ucl, Oxford, Cambridge, um, 

Gareth Barnes: that's probably, you're probably not far wrong. Yeah. Yeah. So I mean, I, I, so I, I'm very, I must say I, I spent a lot of my life in bi of as university, um, and I'm so proud to have worked there, but it is a very, you know, it's a small university and. It, it specializes in kind of vocational training, so, you know, it trains a lot of chemists and, um, engineers and, you know, practical, It's very practical university, but it's one of the new universities. 

So I think it was only created in the, you know, in the fifties or something like that. But what was quite, what was quite lovely, I think it's quite lovely. Anyway, we were always the kind of the underdogs, you know, we were, we, firstly we were doing Meg, which nobody, everybody thought was kind of a waste of time and a waste of money, you know, And secondly, we were in as university. 

So it was, you know, it was quite kind of nice that nobody had very [00:31:00] high expectations 

Benjamin James Kuper-Smith: Yeah, 

Gareth Barnes: not anybody in. And any of the better universities who took a lot longer to take up technology actually. So it was a really nice, kind of pioneering spirit. But what was, what was also nice though, was because we were the only place in the UK that was doing imaging for so long, we, everybody used to come to us. 

So a lot of the people I know from, you know, all these great universities, they all, they all came and joined us at Aston to do studies and things like that. And that's how the technology propagated outta Aston to the rest of the country. And that was, that was also an amazing time because we had some Yeah. 

Incredible visitors and, and you know, loads of fun. Just loads, loads of fun. Really. 

Benjamin James Kuper-Smith: But how did, sorry, How did Aston then, I mean, I guess they must have, have imaging machine 

Gareth Barnes: Yeah. Yeah. Yeah. So, so 

Benjamin James Kuper-Smith: how did like a small university get a hold of this? 

Gareth Barnes: so all thanks to my super, my old supervisor who's, who's recently passed away, Graham Harding. But he, um, he, he basically ran a neurophysiology [00:32:00] clinic at Aston University. So he used to make, you know, basically, um, it was a clinical service, uh, for the, the NHS used to use for testing people's hearing and vision and, you know, and he used evoked potentials to diagnose different diseases, you know, like MS or, or whatever, or, or alcohol induced, um, visual problems, those kinds of things. 

So, so it was a, it was a proper neurophysiology clinic. And, and his idea, what, what, I think what he didn't like about EG was he needed a ref, you know, a reference for everything. He needed to put a reference somewhere and everything. And the great, what he thought was excited about imagery was he did need a reference. 

So you could just, you'd measure direct measure of neuronal activity with, with one sensor. And that's how it started. We, um, he got a system for a single channel system that was kept in a, in a cupboard with a hole. So it was a big cupboard and it was a hole in it, and then you put your head underneath it. And then we just repeated the same experiment. And I was, I got a slide from my old [00:33:00] colleague, Paul, Phil Long the other day. And it basically showed how, which I remember people don't believe me. When I first went to Aston in 1992, they'd used this system to measure an evoked response to, to a visual stimulus, for example. 

And then we had some machine that would do the averaging, but then we had a, the, the data came up was output on in aScope, and you tune up the luminance really brightly. And then we get a piece of tracing paper, we trace the evoked response from it, and then you'd go with a ruler and pencil and you'd take, you'd measure the amplitude and, and the latency, and you'd write those numbers down. 

And then you might type them into another computer to make a, a brain map of what had happened at that particular time. So that was the, the level of, we had one channel of m e. You know, and you have to do the experiments 30 times, Same experiment 30 times. You get 30 different channel measurements, and then you'd tracing paper, everything, type all the numbers in, you'd get a, a picture basically. 

Benjamin James Kuper-Smith: I remember, I think like in primary school, we, [00:34:00] we trace things like, you know, images like against the window. I never thought that that would be legitimate scientific 

Gareth Barnes: know, I know. It was, it was, it's, it's, it's kind of, I mean, it's quite, it's incredible to me that that's what we did. Um, uh, but, um, that, that was the state, the, I mean, that was the state of the technologies before the internet. And, you know, and, and of course, I mean, uh, I was an engineer and, and, and I thought, I, I did think it was, you know, I had to think that. But, but, but, but the fact was we had, there were so many other technical issues, like getting the single channel system to. The, the recording that seemed like straight, the straightforward bit, the actual measure, you know, the recording, the measurements was a nice, straightforward bit. 

It was actually getting the, the single channel system to work. So that was where it started. And then Graham, um, he got money from, from the Europe, I believe, to buy an MEG system. And at the time the Russians had just, it was 19, the [00:35:00] 1990s. Goof had just come in and everything had opened up. And he, he got in touch with a, a Russian team who then built us, uh, you know, a Russian, Russian 19 channel MEG system. 

And again, that was a, that, you know, very affordable, uh, because they not had any contact with the West, um, up until that point. And we hadn't any contact with, with, with Russia either. And very super exciting, cuz, you know, and everybody had a wonderful time. Again, it was, um, 

Benjamin James Kuper-Smith: I mean, just for comparison, uh, the, the one I think we used in Paris had what? And 70 channels or something like that. So like even 19 is still 

Gareth Barnes: but 19 for us was luxury. Cuz that means that 19 times, you know, we'd have had to do the same experiment 19 times with the previous, uh, you know, iteration of the things. Um, so, so this, this was already quite amazing that, to get that. So, and that, that was really innovative actually. So, you know, cuz Graham got the money together and he found these, this amazing group in Moscow to build it for us. 

Um, so that, that, you know, another good few [00:36:00] years and then probably about 10 years later or less, then these, these multichannel systems came, came out with over a hundred channels, which change 

Benjamin James Kuper-Smith: somehow I thought like, like I know it's not like it's, it's a fairly new technology, but somehow I always assumed it existed. Like the, the more or less the machines we have today already existed, like in the nineties or 

Gareth Barnes: Oh well, yeah. Well, they did. No, I mean, the, the, I think that the, the, the first. I think there were, there were different versions, but the, the, the first whole head system I think came around the late nineties, maybe, you know, very late nineties. Uh, but up until then we had lots of different shapes of systems, including ones which are just like conical or one hanging from the ceiling or one raising up the frost. 

Put them on both sides of your head or, you know, there were lots of different, different interesting arrangements of imagery system. 

Benjamin James Kuper-Smith: Hm. Um, do you, I mean, yeah, maybe last question before we get to the OPM stuff. I mean, do you, I mean, it seems like you did a lot of very small [00:37:00] scale tinkering then with the kind of imaging systems. I mean, it seems to me that must have been like a big advance in terms of like really understanding how everything worked about it from the bottom up. 

Gareth Barnes: Yeah. I, I, I, I mean, I think so. I think, but I think that's also, that's, I, I, I begin to realize that's what I enjoy about the science is actually the, the tinkering bit. That's the, the bit I get the most satisfaction from, that there's, you have a relatively small scale, like loads of relatively small scale problems, but, but you can get through them and, and in the end, you, you have a working system. 

But yeah, I mean, that was really, for me, I learned so much just from being in, in, in Moscow. And the super intelligent, super friendly people there who really taught me everything about the system from the, from the squid design right up to the, the cryogenics and everything. And it, and they'd all come from, you know, you know, they'd all been trained in, uh, these special military academies. 

Um, you know, and they fund your projects with things like launching sub missile submarines and things [00:38:00] like that. But they, they'd all go, gone into, you know, engineering and it was, and everybody was excited that we were actually all doing science together. So it was really, really lovely. 

Benjamin James Kuper-Smith: Okay, so I just said, uh, last question, but I have a final last question before we topic is, uh, so how did you then maybe like when you then moved to ucl, to the fill, I mean, I mean, did they already have an imaging system when you were 

Gareth Barnes: Yes. Yeah, They had, they had, I think they've had one since about 2005, I think, in the fill. And, uh, yeah. So that was, that was really good. And the recent, again, I'm afraid there's, It. I moved cuz my wife, my wife, um, moved from Birmingham to, to London and I followed her basically. And that's why, that's why I went to ucl. 

You know, I was quite happy, you know, I'm very happy in ucl but I was also very happy in Aston. Uh, 

Benjamin James Kuper-Smith: I mean it, but it also sounds in terms of scale, I mean, I imagine, I mean, the fill was probably one of the, I mean, I guess it's not like the biggest neuro imaging center of the world. . I mean, I realized when I was a neuro spin, [00:39:00] that's crazy in terms of how much neuro imaging they have. But I mean, it seems to me being head of Ebg at the Fill is a pretty cool title to 

Gareth Barnes: Yeah. But, but I'm, I think it's, it's, it's, yeah, it's very, but it's also, Well when I, I must say I was, um, and I think I still am, I'm super nervous being there because full of smart people, they're super smart, much smarter than I am. And, um, it, you know, you can, what I think what's great about it is you ne you're never comfortable cuz there's always somebody smarter than you in the room, you know? 

And so I think it was more, you know, anxiety inducing than, you know, than anything coming, coming to London actually for me. Just because you realize how, you know, how brilliant, you know, everybody else is that, you know, you know, a bit like, you know, I dunno going from skills university kind of, you think you're smart in school until you get to university and there's, there's smart, even smarter people and so on. 

And I think it was just the next level up, not, there aren't brilliant people. But I think I, I think there were fewer, [00:40:00] there were fewer of, it was a much smaller place, you know, and, and we were much more, you know, it was a small, it was a smaller crowd, smaller specialist crowd. Whereas uc, our neuroscience is huge, you know, as you know. 

Benjamin James Kuper-Smith: Sounds like you're, you're still coming to terms with the fact that you might be one of the brilliant people, 

Gareth Barnes: No, I know. I'm, No, that's the 

Benjamin James Kuper-Smith: It seems to be a slow process of accepting that. 

Gareth Barnes: no. Yes. Well, I wouldn't, I definitely wouldn't accept it because, but, but I must say, what's good about UCL is it, I think it keeps you, or being anywhere surrounded by people who are a bit, have got the edge on you, is it kind of keeps you young, you know, you can't relax, You know, you've got, you've, you think, you know, you've actually got work a bit harder. 

And I think, um, but it's, it's been really good for me cuz it, it pushes me to, you know, not, not just sit on my hands and, but try, try to, you know, try to keep up with everybody else really. 

Benjamin James Kuper-Smith: Yeah. Okay. Well, I mean, it seems like you've managed to do that. Uh, that's my transition now, uh, with [00:41:00] the new MG Systems that you've been one of the, as far as I can tell, one of the main people involved in it. Um, it seems, I mean, the way I see it is it's basically your group at UCL and Matthew Brooks's group at Nottingham. 

Yeah, from the outside. That's what seems like other two groups really pushing this forward. So yeah, I mean, we, we've briefly already elude. To it occasionally, uh, throughout this conversation. Uh, but maybe we can talk about it properly now. Um, so I mean, one thing is maybe, uh, we, we won't, we probably don't have the time, and in my case also not really the interest in discussing the physics, because that's something I'm, uh, yeah, I mean you'd have to be very basic to explain it to me. 

Um, but yeah, maybe from a more practical perspective, kind of what are these optically pumped image systems? Um, and yeah, I guess easiest is in, in contrast to the regular system, the squid systems that we've been discussing so far. 

Gareth Barnes: Yeah, certainly. So, so one thing I haven't, I haven't mentioned about the, the [00:42:00] systems up until now that we've used traditionally is that, uh, inside this big, uh, thermo flas or, or du containing all these channels, um, it, it, it is full of liquid helium because the sensors traditionally have to be super cold. 

They've gotta be a minus 270, around minus two 70 degrees centigrade. And so consequently, the, the, these, you have to build these scanners with a hole in them, a head sized hole, that's, that's a bit too big for everybody cuz you want most people's heads to fit in it. But the problem with that, of course, is that, um, there's two problems. 

The first problem is it's a bit too big for everybody. The second problem is the magnetic feel from your brain falls off with a square of distance. If you. If you could get twice as close to the brain, you'd get four times as big a signal basically. And so what we've wanted for ages and what, you know, what we had with the old single channel Meg systems, at least you could get right up to the scalp. 

You know, you could put that single channel right onto the scalp or within a centimeter of it, you know, given the liquid heli and [00:43:00] everything. Uh, and you could measure nice signals, but with these generic systems that fit your whole head in, especially for younger people or with small heads, that you lose loads of signal. 

And of course, um, uh, as with most traditional U imaging have to stay, um, really still, uh, while you're being scanned. And so what, what's what's been really what was really brilliant is the people that that built. This atomic, this, these optically pump magnetometers, they've been around for a long time and they've been around for about 50 years, probably as long as Meg has. 

But what changed was, was how the cells were manufactured. And that was driven by advances in atomic clock technology. So basically what you need, what you need for, for atomic clock and, and an OPMs, you need a cell of gas, you need a laser and you need something to measure the laser light out the other side. 

And put simply, you use the laser to excite the gas, okay? And you, once the gas is super [00:44:00] excited, the laser light goes straight through transparently. But if you put a magnet, you feel across the gas, you get less laser out the other side. Uh, so that's how it works. Uh, but until now, these things are about the size of microwave oven. 

Basically. And then Atomic Cox came along and the group in NIST was Venia Knap and Visual Char Tiland in Berlin. And what, what they were able to do is they were able to build, um, optically pump magnetometers that were about the size of, you know, your thumb or smaller than that. Uh, and that that's what the, the change, the huge change was for Forg. 

Firstly, what's brilliant is you where their old systems, you had to fill in with liquid helium or you have to very expensive reifying processes. And, and of course, but with, with these systems, they'll just keep working for as long, as long as they work for. Uh, there's, there's no, there's much less maintenance. 

But also importantly, cuz they're small enough, you can just actually, instead of having to put the person into the system, you can then build a sys, build a system onto the person. And that's the brilliant thing about them. So you gain all the [00:45:00] advantages of getting closer to the head and subsequently what we're able to show is you gain those advantages cuz you can. 

Now, now that now the MEG system doesn't weigh half a turn, you can actually, people can move with the MEG system on, and that's, that's a big, that's a big, um, mind shift in mentality for newer imaging. I think because we are so used to just getting people to lie in a tube, stay still, try not to move. 

Whatever you do, don't move your head is what we tell people. Um, so suddenly, uh, with, with the OPMs now we can actually start to, to study people as they, as they're having a conversation, as we are moving our heads around, which would be completely crazy. And traditional, newer imaging, that's the biggest thing I think that that's changed in, in my lifetime is just this. 

Ideally you might be able to do imaging with people, people behaving normally. Is that enough about, Is that, does that describe 

Benjamin James Kuper-Smith: Yeah, I think it's a good starting point. Yeah. And I guess, yeah, what I'd like to kind of explore is this kind of what the consequences are of these changes [00:46:00] and what it means for, um, what you can do with them, what you maybe can't do with them, or where maybe the traditional one is more suited or these kind of things. 

Gareth Barnes: So, so, so give you a concrete example. One of the really exciting things is we know that Meg is really good for epilepsy surgery planning. It's, it's huge advantage to have the meg, sorry. Uh, so the surgeon knows, for example, which bit of the brain is creating the epileptogenic activity and which bit of the brains are really useful for hand movement or language and so on. 

And traditionally that's done with a new imaging technique. And imaging's really good at doing that. The, the trouble is the, the good thing, this is brilliant for adults, okay? But the, the, the, the patient group that stands to benefit the most are young children. And the younger the child, the more they'll benefit from the neuros. 

Okay. But the trouble is the young children, the most difficult ones to, to get to stay still in a traditional scanner. And 

Benjamin James Kuper-Smith: Well, and the scan is so 

Gareth Barnes: a [00:47:00] scanner is way too big for them anyway. Exactly, yeah. So you lose loads of sensitivity as well. So that's, that's the exciting thing about, um, clinically exciting thing about MG is suddenly we, we hope it will in tremendously increase the compliance rate of these younger children so that they, they, the neurosurgical team get the information much earlier in the child's life and they can consequently have the surgery before the child's education starts even possibly, or early on in the education rather than later on when, when lots of education opportunities are, are lost. 

So, so that's, that's one good concrete clinical example. But, but I think there are many examples of things that we don't very little about, like we know very little. You know, keeping on the children. We don't really know much about human developments. We can't do new imaging on these two and three year olds who are just learning to, well probably let, let's say it again. 

We, we don't, when, when children starting to learn language or their memories are start to form, they're at the, they're at [00:48:00] toddler age where you just can't pin them down. So we, we, we, we know very little about the, the new imaging of what's going on at that stage in development, which is really exciting. 

But now maybe with the OPMs we'll be able to unlock that. And then later on in life, um, you know, people develop, you know, dementias, movement disorders, you know, many issues that that mean they can't comply with traditional scanners. And so, so, and ga, you know, gait issues arising from these dementias, you know, some movement problems. 

Benjamin James Kuper-Smith: So you mean like for example, someone with Parkinson's is gonna have a hard time lying still 

Gareth Barnes: Exactly. And those people with Parkinson's, we can scan in the MEG scanner. They're probably, you know, it's, they're probably not, you know, they're probably not as representative if, uh, as, as other people, you know, And so, so we, we can begin to study lots of people who've got either moving disorders or compliance issues or whatever. 

So it, it, I think it brought, I think the [00:49:00] most, for me, the most neuro scientifically exciting thing is it completely broadens the cohorts of people that, that, that we can study. Uh, but also it, it really, it's a bit of a mind shift in the sense that we, we, we stop, maybe we, we can stop concentrating on very efficient paradigms that, you know, because we had to keep people still for say, 10 minutes at a time in traditional reimaging and, um, And the only, and the way, and people, a compliant outlook can certainly do that. 

And the way that we do that is we really focus our experiment to get just examining one variable of interest at any one time, but it's not particularly natural probing of somebody. Uh, or, or, or how, how they're operating. And so maybe now, um, we can start to think of doing things in a, you know, a less, less efficient way, but maybe more natural way in terms of scanning people for longer while they do tasks in, in a normal, in a normal way. 

Rather than thinking all the time, I must not move my head or, or try not to acknowledge that or, [00:50:00] or whatever, you know, whatever they're normally thinking of. 

Benjamin James Kuper-Smith: Yeah, it's really interesting to me also in, I, one of my former guests, um, was Mattia stronger. He, um, is first author on a nature paper that came out like half a year ago or something where they had, he's at UCLA right now and they had, I'm assuming epilepsy patients, I can't remember right now. But yeah, so that intracranial recordings and they recorded basically neuro signals whilst the people were actually moving around. 

Whereas, you know, before it was always you, you play a video game and you kind of move through the video game world, but they kind of were the first people to actually like, get these, I don't, I can't actually remember whether it was like, Was that grid sound like activity? I can't remember actually. Um, but yeah, they were basically 

Gareth Barnes: Yeah, 

Benjamin James Kuper-Smith: to, you know, they, but they could only do it because they had access to this very specific group of patients. 

And I guess it's really cool the, the, the i, the potential that you can do this with basically anyone once you have the system running, I mean, maybe not to that precision of course, but yeah. 

Gareth Barnes: Yeah, I think that's, that's really exciting. And, and that, I mean, and of course [00:51:00] with, um, with the rodden studies, they, you know, we're probably a bit, we're a bit behind them. They've been doing this with, with implanted things, with mice running around for a long time, you know, Uh, but then they need the mice to behave. 

Cause the mice can't tell 'em anything, you know, so they need the behavior. Uh, but we're, we're, you know, kind of, kind of closing the gap now in, in the sense we can have humans behaving naturally and also do brain kind of noninvasive brain measurements, but get, get some idea of what's going on in the brain whilst people are behaving natural. 

Benjamin James Kuper-Smith: I, One question I have, um, if we can get slightly into the, kinda the practical difficulties here is about the whole movement because it seems to me that, so when, when I did EG studies, You obviously, I mean, their people can move because they're wearing the EG cap and so they have this flexibility, but you still don't want to move them to move that much because then you get these kind of movement artifacts. 

And the thing I usually showed participants as an example is I'd say like, you know, just bite on your teeth right now. And then they bite it on their teeth and the entire screen would just go crazy because the, the jaw is such a strong [00:52:00] muscle. And so now I'm curious, like if you're moving your entire body around, doesn't that introduce all sorts of problems there? 

Gareth Barnes: yeah, yeah, yeah. Well, 

Benjamin James Kuper-Smith: I mean, also problems that you can't really then take, filter out easily, Right? I would 

Gareth Barnes: Yeah, so, so, so I think it's really interesting and it's one of the differences between MEG and eg. That that's never I've, It's, it's an empirical difference. Um, but it is difficult to depend down exactly. Uh, Exactly what it arises from. But, but Meg seems to be about 10 times less influenced by muscle than, than eg. 

So, so part of the reason is clearly eg you need a reference. And so that if, if the signal gets onto your, if this muscle signal is on your reference channel or a signal channel, the then it then tends to go everywhere. Part of the reason is, is the, as I say, the sensitivity profile is very well defined. 

So in the, in the source level images, if you like, the muscle, [00:53:00] anything happening in the muscle, localizes to the muscle. But also something I read the other day, which I thought rung true was, was, the other thing is, is that the signal falls off very quickly with distance. You know, and if you think about the eeg, the EEG electrodes are pinned onto the, you know, they're effectively stuck on the muscle, whereas the, the sensors, even, even the OPMs are, you know, six or eight millimeters away. 

If it's two versus eight millimeters, for example, that's a fact. That's four. But that's the 16 times smaller signal that you might expect from the muscle in the 

Benjamin James Kuper-Smith: does EEG not have the dis the, the exponential fall off with discs or, 

Gareth Barnes: Yeah, it does. It does have it. But it's like the electros actually stuck on, you know, they're 

Benjamin James Kuper-Smith: Okay. Okay. That's 

Gareth Barnes: Yeah, yeah, yeah. Um, but of course we, we have other mis, we have plenty of other mystery with, with the meg, the, the art. We still see artifacts and we still see muscle artifacts. Um, they're just pos they, they're, they're more vocally distributed over a smaller number of [00:54:00] sensors. 

Yeah. And they do cause lots of problems. They, it do cause us lots of problems, but the, the, the main source of our main source of artifacts due to movement are actually due to simply the movement of the sensors within the static fields basically. And that, although, although that's really destructive, It's very simple. 

It's very simple to model, so we know what the fields are around the person, and we, we can watch the head movements. We know exactly what the fields should be for a particular head position, so we can, we can correct for that. But the, but the EEG side of it, it's the physiological, like, like you say, it's the physiologic artifacts that, that really constrain you. 

It's the muscles and they're much more difficult to model, to, to explain where, where all those currents are flowing from. And, and that's why it's tricky. That's why it's tricky. We also do get problems with our, with our leads in the imagery as well. It's the, the wire seem to be a problem, whichever domain you're in, you know. 

Benjamin James Kuper-Smith: Okay. Yeah, I mean, I was gonna ask about the, the room as kind of the next [00:55:00] question because it seems to me that when, as you said, like the signal you're measuring is tiny compared to all the other magnetic stuff that's going on, uh, all the time anyway. So you need like these specially shielded rooms within which you can record this. 

So it seems to me that that kind of slightly mitigates part of the advantage of the new system. Because one of the advantage is you, you don't have to have this huge machine anymore, but you still have to have a huge room. I mean, the room still has to be the same, right? So, um, 

Gareth Barnes: metal box. Yeah, you're right. You're quite right. So yeah, you, you, you're absolutely right. So first of all, you know, the, the, the room is quite, I mean, our room is is three by four meters. So we're in central London. That's, you know, that's, that's a good size room. So, so you can, and the great thing about the room is there's nothing else 

Benjamin James Kuper-Smith: that's a studio apartment. 

Gareth Barnes: Yeah, exactly. Yeah, there's nothing else in there. So there's no, there's no lumbering piece of equipment in the middle. It's just, you're just sitting there with the, the helmet on and that's it. So it's, you, you could, you could fit a lot of, you [00:56:00] could fit other people in there, or, or, you know, probably about the size. 

It's probably, um, a table tennis table. You could just about fit in there, probably, I imagine something like that. So, so the room, but you're quite right. I mean, what the, the main barrier to entry for this technology is, is this lumbering, shielded room that, that people have to sit in. That, that, that's very expensive. 

It's about half million pounds, 

Benjamin James Kuper-Smith: Oh, really? Okay. 

Gareth Barnes: And what we would like, what definitely what one thing we pla we would like to do in the future is to get rid of that room. We just, we'd like to get rid of it, and we think it's possible. And that's basically two factors. The, the first thing is we think that the, um, that the, well, the great thing is that the, the OPM sensors themselves have become about, 10 to a hundred times more resilient to magnetic noise since we started. 

So, so for example, our, um, system at the moment, we have to stay within about two nano Teslas of, [00:57:00] I, I've not mentioned this, but the OPMs have to work in a zero field environment. So they're a bit even fussier than, than squid systems as to how they will operate. But, uh, basically we've gone from two nano Teslas to now sensors are available to say that have a closed loop bandwidth of 200 nano Teslas. 

So you can get a lot more data into the OPMs themselves. And of course, the other good thing is, is that with, with our colleagues in nodding, we've experimented a lot with, with shield trying to shield the, the earth's field or mitigate the effects of the US field to some degree. And so we think that maybe, maybe it might be possible to build a room like a normal room, a relatively normal room that that's got some low level, low level shielding in it that. 

That would allow OPMs to operate in the real world, which would be, which would be the next step. 

Benjamin James Kuper-Smith: It seems to me if you want to do my, my kind of intuitive guess here would be that, you know, the, the larger the room is exponentially more you can do within [00:58:00] it, but also exponentially more expensive. It gets to she . I dunno whether that's quite right, 

Gareth Barnes: Yeah. It's, it's, it's, it's, yeah, it comes down to the cur. Yeah. So what's good is the, you're right, the larger the room is, well, probably the more expensive is to shield it. Yeah. But the, the good thing is you, the, the, it turns out with the, you know, you're basically building helm huts or Maxwell cos. But basically the larger the room is, the, the more space you have in the middle of the room to play with, and probably the less precise you need to be with building these big coils. 

You know? So if you had really big coils, Maybe, maybe, maybe I'm saying that incorrectly, but basically big coils, larger space, bigger cos larger space, you're free to move in the middle of the room, but you either, then you need more current in the coil. So ecologically, you know, you, you're burning up electricity or, or you need to do more turns, just have more, more wind turnings on your coils. 

And so, and that's more work. But that, that's, that's definitely the way we'd like to go is just to try to [00:59:00] try to get these systems to work and shield, you know, at least semi shielded without the expense of the shielded room. One thing to point out, of course, is that people have already made measurements without any shielding at all with these devices in, um, in America, in the woods in America from the, I think ALS lab. 

And basically they, they, they've built a magnetometer that, that measured, they've measured auditory evoke responses in the woods without any shielding at all. It is possible, it is the future, but there's certain, you know, there's certain, even on that design, there's certain constraints that, that we'll have to kind of work around basically. 

Benjamin James Kuper-Smith: It'd be great now. You'd just see neuroscientists with their participants in the middle of the woods now everywhere doing their science rather than inner city. 

Gareth Barnes: It's, it's funny cuz um, cuz I was talking about, um, I was talking to one of the conferences, one of our biomark imagery conference. I was talking to one of the, the first, one of the pioneers of Meg in, um, in North America. And I think he was based in Halifax. I'm sorry I've forgotten his name [01:00:00] now. But, um, but he said that because they used to do all their measure before Shirley Dreams. 

Everybody used to go to the woods, you know, in Finland they go to the woods and in, but in, in North Amer 

Benjamin James Kuper-Smith: That's why there's so many Finnish 

Gareth Barnes: yeah, probably. 

Benjamin James Kuper-Smith: I always wondered why it seems random. 

Gareth Barnes: but in the, um, in North America, the main constraint, cuz I was talking about the constraints on recording for us, I can't remember why, but, um, but the main constraints for them was with the mosquitoes. 

It was how long you could bear the mosquitoes for in the woods and that, that was what the recording time was limited by. But basically we're going back to where we started, you know, 50 years ago and go back to the woods, uh, to try to get these devices working again. 

Benjamin James Kuper-Smith: Okay. I mean, is it on the horizon that. In 10 years, we will be able to have one of these wearable systems and kind of be just walking through a house and record or is that still science fiction 

Gareth Barnes: I, I, well, I'd like it to be, I mean, I think, I think you've gotta, you've gotta, you've got Dream Big Avenue and I think that's where we'd want the technology to be. I think [01:01:00] already you could probably build a system like that. You could probably build, but it would only measure the half of your head that was pointing to you north. 

That would be the only thing at the moment. So as long as you, you're doing lots of rotations of the, you know, of that space, you know, that, that you, you could make up for that under sampling. Um, but I think that that would be the aspiration, you know, because I think, you know, coming back to EEG that, you know, the big shoes to fill and what's brilliant about EEG is it can go all around the world in any hospital, any clinic, and it just works. 

And I think that that would be the way that, that if, if the technology's gonna take off and get cheaper, then it has to, it has to show some clear benefits over that. Really. 

Benjamin James Kuper-Smith: Yeah. Um, brief question about the kind of practical aspects of getting a machine and financing it. From what I understand, this is quite a lot cheaper than the 

Gareth Barnes: Yeah. Yeah, yeah. 

Benjamin James Kuper-Smith: machines, but you know, when I think when you gave the talk in handbook, I think you said that [01:02:00] you kind of can't buy one. It's not like, you know, you go to a company and you just buy a machine, you kind of have to build it yourself or something like that. 

So I'm just curious whether you could comment on like, what is. Yeah, like how do you get a, how do you get one of those systems and how much does it cost? 

Gareth Barnes: Yeah. So actually, yeah, I remember that. And um, since, since that talk now there are now two commercial companies that sell OPM systems. 

Benjamin James Kuper-Smith: Oh, already. 

Gareth Barnes: Yeah. Yeah. And one of them, Isir, that's in, that's was VE Knapp and she was one of the original, um, The person that effectively built the first, you know, went from atomic clocks to opm, so that one of the first sensors. 

And there's another system which is called Circa, that's based in the uk, which is our NOTAM collaborators and magnetic shields, which build, build the rooms. And, uh, and they sell the, the, the, uh, a system that's put together using sensors made by one of ten's former colleagues, vi sh who, who builds, who builds OPMs as well in America. 

And so, so there are two [01:03:00] companies now that, that will sell you an OPM system. I think even with shielding, um, I can't tell you, I dunno how much they cost of not, not looked into it, but I can tell you that, that roughly the, and to buy, um, a two or three channel OPM device, you know, that's about the size of your thumb at the moment. 

It costs about 5,000 pounds, something like that. You need a, uh, you need at least fif say you need at least a hundred channels around the head, basically. So you'd need. At least 50 of these device, probably 50 of these thumb size devices. 

Benjamin James Kuper-Smith: So 

Gareth Barnes: So that's 50 times 5,000. So that's quarter for a million. Yeah. And then, then you need a shielded room. 

So the shielded room, unfortunately that's expensive, kind of built from expensive alloys, that's a bit more expensive. But again, a young epilepsy with these colleagues I mentioned, uh, magnetic shields and noting university, we've put together a shielded room that, that uses about 40% of the expense of alloy. 

So it's a cheaper room already, uh, but it's got more active [01:04:00] shielding in it, you know, constructed by, by Nile and Richard at noting them. And, and that's, that's absolutely brilliant. So, so I think things are, things are moving away from the, you wanna move away from the expense of Alloy to get the room cost down, and ideally to go to No, all at all, And that would be brilliant. 

But the OPMs themselves, go back to the atomic clock analogy. Atomic clock also used to be about 5,000 pounds each, and now they're less than a hundred dollars each. So that, and that's because they're useful, you know, there's, there's a market for them. And so if the OPM technology were to take off, then, then hopefully the price of the individual centers would come down. 

They'd be a lot more affordable. Um, and of course it's already more affordable technology than squid technology cuz you, you know, you don't have to pay for all the, the helium and all that, that, that expense. 

Benjamin James Kuper-Smith: Or the maintenance of, 

Gareth Barnes: all the maintenance. Yeah, exactly. Um, uh, so, you know, so it's, it, it's definitely, it's definitely getting there, but who knows which way things will go. 

But what's also really exciting is now, oh, you know, I should mention there's also a [01:05:00] French company, Mag four Health that makes helium based magnetometers now. And I think there's a Finish Orec based consortium that's also building magnetometers. So there, there are at least two, two places, two or three places in Europe that are building, uh, OPM systems. 

So actually from, and that's quite a change cuz I was in Hamburg, as you say, in 20 18, 20 19. So, 

Benjamin James Kuper-Smith: Yeah. I started in 2019, so it must 

Gareth Barnes: There we go. 

Benjamin James Kuper-Smith: that. Yeah. 

Gareth Barnes: So in the last, Yeah, less than three years. There, there are, there are quite a few companies on the scene that are selling this, this gear. 

Benjamin James Kuper-Smith: mean that's, yeah, that's really cool because I remember like asking that question then, and it was kind of, it seemed like this slight disappointment with like, it's kind of cool, but like you kind of have to be like an engineer and build them yourself. But that's, Yeah, it's great that that's happened so quickly. 

Gareth Barnes: Yeah. I'm kind of disappointed. I mean, it's nice, it's, it's kind of nice when it's all in, you know, when you have to fiddle with it, you know, it's, once it all gets turnkey and stuff like that, it's, um, you know, it, it loses some allure, but it, but it, 

Benjamin James Kuper-Smith: Well, for some [01:06:00] people. Yeah. 

Gareth Barnes: yes, but not for, but obviously it's completely useless when it, when it's not working. 

So I can completely see why, why, why every, you know, you want a turnkey system. 

Benjamin James Kuper-Smith: Yeah. Um, I had a question. Wait, I forgot what it was. Um, yeah, maybe. Okay. Maybe then as a kind of, Sorry, this was the question I remember. Is the analysis the same? Like can you use the same tools that use for the squid imaging, or do you have to like, you know, you have to basically create a whole new toolbox for analyzing OPM 

Gareth Barnes: fortunately the analysis is, is almost identical to the, to the squi squid level analysis. The, the only, the, the only additional analyses are, are getting rid of all the, the external noise basically. So, so you have to put, um, you have to put a couple of, uh, noise reduction steps before you get to the traditional squid analyses. 

But yeah, fortunately we use the same, basically the same [01:07:00] soft, it's the same algorithms even for eeg, when you get right down to the bottom level. Um, but it's the same. It's so that, that's really good. And so, I mean, that's very positive for the community. I think the these, once, once you've got, you're familiar with Meg or eeg, then, then you, you'd be able to use OPMs without any, any problems at all? 

Benjamin James Kuper-Smith: Yeah, that was kind of my slack concern there, that basically like all the, uh, not like obviously all of it, but that you have to, Yeah, just rebuild the whole analysis machine, 

Gareth Barnes: Uh, no, Fortunately not. Fortunately not. I mean, the only, the only tricky thing is now, now we're actually with the newest senses, we're measuring three directions at once. And we, we were only used to measuring just one direction, which we got used to reading the, the maps of brain activity, you know, feel going out, feel going in. 

But now you've got feel going in three directions and it's very difficult to get your head around us. So we may convert it all back to the old style pictures just to make it interpretable. 

Benjamin James Kuper-Smith: Yeah, I dunno how, how easy this question is to answer per se. But I was curious just as a kind of maybe [01:08:00] summary of this entire discussion about the OPM GE system is kind of like, what kind of studies is this? Particularly well suited for. And what is it less well suited for? I mean, you already mentioned different populations like children or people with who for whatever reason can't get into MG Scanner. 

Are, are these two systems of good at measuring different things or do they fundamentally measure the same thing? Exactly. And what would that mean for like study, not just study design, but Yeah, for like what kind of questions you can try to answer. 

Gareth Barnes: Yeah. Yeah. Yeah. So I, I think I, I, I guess at the moment, the, at the moment, the major distinction is, is that is the amount of time you have to spend per subject, probably. So in a traditional system, you can, you can do, you know, you could probably, you could you get through eight, you know, if you were pushing it, you get through eight subjects a day almost in one experiment, and you put every subject you put in the gear would work beautifully and you, you'd [01:09:00] get something out of that subject just because the systems have now been around for over 20 years and, and they work really well. 

And, and you have 300 channels of data already there. So for the, for the OPM systems, it is still a bit, it can still be a bit flaky, you know, and so still spend a fair amount of time getting the things working once the subject has arrived. Uh, and of course at the moment we're building, um, we're building helmets for them, you know, for each individual subject in the same way. 

We used to build the, the head cast. We, we, we take their MRI or the optical scan, we build it. So that take, that's another additional step you do per subject. 

Benjamin James Kuper-Smith: Do you have to do that? Like with eg you don't do it right? You have like three size caps or something? 

Gareth Barnes: Yeah, you don't have to do it. And hopefully we won't have to do it in the future. And the main reason for doing it is the, is the miserable wires. Again, you know, there's, well, there's two reasons. The first reason is if you've got the sensors held down, you know where they are, you know exactly where they are, the respect to the brain. 

And so it [01:10:00] makes, it makes the noise cancellation and the source reconstruction a lot more straightforward. And the second more practical reason is it just holds a sensor still so they can't wobble independently of one another. Cuz if one's wobbling to the left and one's wobbling to the right, you can't really correct for that, that noise, if they're both wobbling together, you can correct for it. 

And the, the, the other reason is, is that the, the wires coming off the sensor. They, they interact to some degree in the schematics. It looks great when you've got like a hundred channels on your head. You's just got a hundred Do. You know, but when you, when you put the wires on, it's a real mess. And all the wires tend to interact with each other and you, you hear them, you know, you're moving your head around freely. 

But you can also, you feel not only some resistance, but you can also hear the wires, you know, rusting with each other. And that also creates some electromagnetic noise. So essentially building, building a bespoke helmet just mitigates all of those problems. But what we would hope is that in the future, you know, when the, basically, when we know more about the sensors, [01:11:00] we, we'll be able to work out where they are individually and we'll be able to mitigate these noise problems better. 

But at the moment, we're at this level where it's just easier to know everything about the sensors and where they are. It's almost, I'd say it's probably essential that we get this sorted out for the future in, in young epilepsy. This, this is, um, in Surrey, they're a clinical site that have adopted OPM technology for, for pediatric epilepsy. 

What they have there, and it's the CIR solution is they've got three different, like you would for eg, you've got three different size helmets and before the child arrives, they put the helmet into one of three different sizes of helmets. So that's really good. You still have this issue that the helmet's slightly bit too big for the, the child, but it makes a lot of sense practically. 

You know, then you, you can, you can get once, once the child arrives, you can scan them very quickly and we have, we have a kind of a policy at our center that, that we, we not allow, you know, you're not, we try to discourage people from doing OPM scanning if they could possibly do it on the, the [01:12:00] traditional system. 

Just because generally will be be if you, if you're not, if you, if you don't want somebody to move their head, if you don't need somebody to move their head, then it will be better on the digital energy system. Even though you do lose the sensitivity to some degree, you kind of win because you can get more subjects through. 

Through, through the gear, you know, see winter statistical power and you win on, you know, time per subject as well. Probably clearly that will change, you know, that will change in the future as that the OPMs get, you know, better and faster and easier to use. But at the moment it's basically, it's the OPMs are, are best suited, a bit like they're head cast, they're best suited for, you know, small numbers of people where you're gonna keep doing the same thing over and over again or, you know, or watch the brain changing over time, for example. 

Benjamin James Kuper-Smith: Yeah, but it's, as you said, like that seems more like a current problem rather than a in principle problem with a 

Gareth Barnes: Yeah, yeah, exactly. Yeah, I mean, I mean, the exciting things about the OPMs is, as you pointed out, is what you can't do with, with normal images. You can't put the sensors anywhere [01:13:00] except where they are. You're stuck with the sensors all around the head. And that's a great thing about the OPMs is now we can start to, to experiment measuring, you know, down the spinal cord or, or wherever. 

And so that, that's really exciting. Or for example, around face area, To access these frontal structures better, maybe. And we, we haven't been able to do that with, with traditional meg. So, so you've got the flexibility of the OPMs, but with that flexibility comes a lot of, you know, of trial and error trying to get it to work. 

Benjamin James Kuper-Smith: Yeah. Uh, but that was a good transition to the next, uh, paper of yours or project I wanna talk about, which is the mouth imaging. 

Gareth Barnes: Oh yes. Yeah, yeah, 

Benjamin James Kuper-Smith: so I found that really fascinating. I mean, again, I saw this the first time when, when I attended your talk in handbook and I went through this like brief period where I was, I just started wondering about like how you might improve in your imaging. 

And I always wondered like, why no one with EEG or something. I mean, this. A very, it's probably a very good physical explanation for this, but like, why did no one put, like electrodes, like in someone's nose or in the mouth or in the ears, was like, something to [01:14:00] get like, you know, to to not just have the, the surface of the scalp, but to get it from the other direction. 

Gareth Barnes: But, but they do, they do. 

Benjamin James Kuper-Smith: they do. Okay. At least I, I hadn't heard of it. 

Gareth Barnes: It's, it's mostly, uh, clinical, but I think it's called OID electrodes. And they stick them in your just, it just, they stick them. I think it's somewhere around here. They stick them around. You got right into your temporal lobe basically. Yes. But, but it's, of course, it's kind of a clinical thing and it's, so I think it's mostly for epilepsy. 

I mean, it's not something you do on your, your undergraduate students or anything like that, you know, It doesn't, it's a big needle, you know, effectively. 

Benjamin James Kuper-Smith: It's actually like a a, it's not on the surface. You insert it into the skin. Oh, okay. Okay. Yeah. 

Gareth Barnes: So it's not, not not as, it makes our, you know, what, we did seem quite, you know, quite, you know, 

Benjamin James Kuper-Smith: Yeah. But I mean, so the, from what I understand, the mouth energy is a system where, Basically take, I don't know, one or multiple, I'm not sure of the regular census, and you just let someone bite on them. 

Gareth Barnes: Yeah, exactly. I mean what, so what this, this was, [01:15:00] so the sensors are now about the size of a Lego brick or the size of my thumb. But, um, they used to be, uh, much bigger, but the size of a marker pen, I haven't got, um, a marker pen. But they used to be about this long. Yeah. And so that, that's how, that's how it'd end up in my ma we can only put one in my mouth cuz that was the only num that was the maximum number you can get into a mouth basically of those sensors. 

Now the sensors a lot smaller, uh, and every so often somebody does say, We should put more into your mouth. You know, the reason we did that, and we were lucky, we a few happy coincidences there. We were working with a dentist and Andrew Levy and so he was able to build a say, um, a, a kind of a dental prosthesis for, for myself that had a, had a sense of slot in it. 

So be able to you, something fit to my upper jaw and then the sense of slot into. And the sensor touched the, you know, exactly the roof of my mouth. So that was one good thing. That was one good thing. And the other lucky thing was we were working with, um, Ellen McGuire and Daniel Barry, and they had a really [01:16:00] nice paradigm for, for exciting the hip, engage in the hippocampus. 

And so it, so we were able to kind of test whether that sensor gave us a bit more information. And it's really unusually place for Meg as, as you know, you know, you can never do that with a, with a traditional system. Um, and what was quite incredible, it, it, it turned out that the roof of mouth was a really, was a really good place to put it, you know. 

Um, you know, I think we, I can't remember whether we did the experiment first or the simulations first, but that we didn't think a lot, We didn't think very detail, in much detail about it before we did it, put it like that. But it turned out that, um, the, the signals generated by the hippo Campi, they create. 

Maxima that the one is on the temporal lobe and the other one is, is on the roof of your mouth, on each side, basically. And so for, we were very, you know, I think it was partly luck as well that we happened to get the sensor in the right place. But that's, I think that's exciting because if, if you had, uh, epilepsy and, and, and, and the alternative, [01:17:00] you know, it was, was invasive surgery then, although it wasn't very comfortable putting the sensor in my mouth, you know, it, it's definitely a lot, lot better than kind of any kind of surgery. 

Um, and, you know, minimally, minimally invasive, you know, And, and we, and like you say, we could fit a lot more sensors in now with the current design 

Benjamin James Kuper-Smith: Yeah. Do you, um, And this is a general question I wanted to talk about briefly is kind of like how well are you able to, uh, measure neural activity from deeper brain regions with Meg? And how much does adding this sensor, you know, the other side of the brain, basically relative to the on your scalp, how much does that help help that you. 

Gareth Barnes: Yeah, well, I, I, two good questions. Uh, so all I can tell you was that the center in the roof of the mouth explained a lot more variance in experimental variance than any sensors we put on the scalp. So I can't give you a localization answer, but I can tell you it definitely helped in, in terms, so it is picking up [01:18:00] very relevant signal from these deep brain structures. 

So it's very important. But the, the, the, the space resolution question is always a difficult one. One forg, cuz it, it kind of depends on how much data you've got and how many sensors you've got. But what it, what it looks like from many, well not from many, but from other studies, is that the. We're very comfort, We're very confident in localizing structures like the hippocampus, anterior versus posterior left versus right, that kind of thing. 

But, um, what the trickier structures are, stuff that, that are right in the middle, the brain stem, for example, things like that. Uh, but even that has been measured with amg. But, but coming back to the EEG example, the auditor STEM response is done on toddlers, with an EEG system that costs about 20 pounds, probably without any problem every day in every hospital in the world, you know, And that's no problem at all. 

Whereas the MEG effort was, was huge. And that was, that was the finish goes Lowry pack on colleagues. So the, the MEG [01:19:00] localization of very deep things is definitely trickier, but the nice thing. About the MEG over the EG. Is, is is that urate? The EG guys know where, where the auditory, they know that the response they get is from the auditory brainstem because it's very, got a very characteristic latency. 

And they've, they've built up that data through lesion models over the years. They know exactly which part of the pathway that signal's coming from. But if you were to see that signal with Meg, you'd also be able to localize where it was in the brain. And that would be the thing. So with EEG it might be more difficult to say exactly where it was, but with the meg you'd be able to say precisely where it was. 

Uh, so we are getting less signal from the deeper brain. But the great thing is with these new sensors is we can have a lot of them and we can also recover a long time, which is a luxury we've never had before. And this is where we were trying to get, to bring this back to the head casts. We were saying, What happened? 

What point would Meg break? You know, when can you break Meg? How, how long would you have to record for in it, in order for this thing to stop improving? And what, what's the obstacle, [01:20:00] what's the barrier? And I think we still, with OPMs now, we can really kind of explore that we, because theoretically the longer we record for the, the source localization, our models, everything should just keep getting well, everything should keep, keep, keep getting better as long as our modeling assumptions are correct. 

Okay. And what we, what we'd like to do is to, to hit that point where we think, Oh, it's not getting better. We need to change something and then we know what to change. But up until now, we've never really got, you know, we've never been able to get enough data to really see that, that transition or we've said, Oh, it's registration error, it's something else. 

But having the OPM to me, we actually really can push the system to, to challenge how we model these current, this current flow in the head. So that'd be kind of cool, I think, but for a cool, from an engineering point of view, not from anybody else's point. 

Benjamin James Kuper-Smith: Yeah, but I mean, if it, if it leads to us being able to find out more stuff with than we could before then, 

Gareth Barnes: Yeah. Yeah. I mean, it's, it's still, it is still [01:21:00] very exciting. Definitely. Yeah. 

Benjamin James Kuper-Smith: Um, maybe as a kind of last point, uh, I wanted to ask kind of more broadly about how methods development and basic science kind of interact and how, you know, developments and methods often allow you. I mean, the kind of a necessary condition often to find out interesting new stuff. I mean, some of the, you know, grand examples from science might be something like, um, I think Galio had his, some of his discoveries briefly after. 

I think he actually, what did, he made his own telescopes? I'm not sure. But he had like a new telescope that no one else had or something like that. Um, or from, from neuroscience. I don't think it's a given coincidence that, uh, John Ike found play cells a few years after it was first possible to record from moving rats. 

Um, who that can just move freely around in a certain area now. I mean, so the, the, the OPM meg is maybe not quite as much a step because it's still stillg, but it's, I think it's still a significant step. It's a big [01:22:00] step with what you can do with e uh, so yeah, I was just curious first Yeah, kinda the two related question, like how you think about methods development and then also what you think maybe can, what some of the basic questions that can be answered. 

Using this new technology that maybe couldn't have been answered other. 

Gareth Barnes: Yeah. Yeah. Wow. That's a big one. But I, uh, I, So I, for me, for me, I, I, I mean, what I'm really lucky, I work in a place where there's loads of cognitive neuroscientists and loads of clinicians. Were always asking questions and kind of pushing the technology. So it's very difficult to say, you know, what, what comes first? 

Because I, I, you know, often feel like, Oh, well we should, you know, people say, Can we do that? Why can't we do that? You know, why, why is that not possible? And, and, uh, you know, just thinking of the, um, you know, a lot of the, the motivation for OPMs that came from Ellen McGuire and her group who were saying, Well, you know, we, we can't really study, um, memory cause we've got [01:23:00] no vestibular stuff or we've got no, you know, that it's, it's not, it's, it's not a realistic kind of situation. 

And it's likewise with the children, with epilepsy that'd be able to study those because kids are moving too much so often. Um, so the reason, let's put it this way. Well, maybe one of the reasons we got the funding to do the OPM stuff in the first place was because there was a really good scientific or clinical motivation for it. 

But I, I'd basically, I'd be, I'd be out of a job if it wasn't for the cognitive neuroscientists and, and the clinicians thinking about. You know, brilliant things to do with the gear, then I wouldn't have a place in this world. You know, because they, you know, it's, it's that, it's that interaction, that exchange that, that they say, these are the, these are the important questions. 

This is what we don't know. And that's what, that's why it's interesting. I think if, probably if you are brilliant like Galileo, then you can build the gear around our society, ask the right questions as well. But I've always, I, I've always felt like I can just about keep my, you know, clinging on by fingernails here. 

I can just about keep [01:24:00] control of the, the engineering methodological science of it. But I have to leave the, the neuroscience innovation to, to the professionals really. But I, I must say, I think, yeah, I, I, I'm really excited by how the, the two things, uh, intertwine and I think that's also kind of the measure often of a really. 

Kind of, or the kind of neuroscientist or clinician we like to often like to work with. They're the kind of people who just say, Well, you know, we know it's a bit a bit risky and it's a bit tricky and we know it's not gonna work first time, but this is what we'd really like to study. This is the, this is the question. 

And, and it's the question that, that, that drives most of the stuff. Um, it's, it's, it's answering those particular questions that I could not frame, uh, given my knowledge of the brain. And my family's always appalled with how little I know about the actual brain itself. You know, they always look at me when something's on the radio and I just say, I dunno where that is. 

Even, you know, in the brain. So [01:25:00] it's, uh, so, so I, I think, I think, uh, yeah, I, I think, I think it's a really good symbiosis and I think I, hopefully it will, it will always continue like this, the kind of geeky people that enjoy the methods also hang around with the geeky people that enjoy the, the science. I think. 

Benjamin James Kuper-Smith: It's funny that you, the way you framed it in terms of like, Yeah, I mean the, the basic scientists asking researchers to, you know, why can't we do this or can we do that, or whatever. Because I interviewed, uh, Christopher a few months ago and he, he, he basically said like, one of his jobs was, was getting Cal first and to do stuff like, like lot to do stuff, but like, like to do the impossible. 

Like, I really want this to happen and can you, can you make it work please, 

Gareth Barnes: that's nice. That's 

Benjamin James Kuper-Smith: Yeah. So it's nice that that tradition is, is continuing at the. 

Gareth Barnes: That's really nice. Oh, that's lovely.

How I found out about Gareth's work
What is MEG?
Flexible headcasts for MEG
How Gareth accidentally started working on MEG (after writing fiction in France)
The early days of MEG at Aston University (starting with a single channel)
The new generation of MEG: Optically pumped magnetometers (OPM-MEG)
Mouth MEG and measuring hippocampus with MEG
The relationship between methods development and discovery in basic science