Richard Edden on Hunting for GABA by Magnetic Resonance Spectroscopy of the Brain

and thinking, oh hang on, maybe I could do things in a different way that retrieved the thing I used to think was lost. So that as a general idea is something I sort of say to all researchers, is can you think of ways that what you're doing is wasteful because those things you can get back for free, you don't have to pay for those things. Hi, welcome to the Science Fair Podcast. I'm your host, Susan Keatley. I'm a PhD chemist, writer, and I love talking to scientists. On the Science Fair Podcast, I aim to bring you conversations with scientists doing fascinating, cutting-edge work on all kinds of interesting phenomena, ranging from physics to chemistry to biology and even the nature of science itself. In this third season of the podcast, every other week two episodes will come out. On Mondays, there will be a shorter 10-minute episode linking the scientists' research to what's happening in the classroom and then on Thursday, the full-length interview. So come along and tune in for some Science Fair. Our guest today is Richard Edden. Richard is a professor in the Department of Neuro Radiology at Johns Hopkins University. He uses a technology called Magnetic Resonance Spectroscopy, MRS, to study the brain. His group focuses on both method development, how can they make MRS better, more informative, and also what the specific findings mean for brain health. Today, Richard is going to talk to us about his path as a scientist, his research, and how it relates to what some of you may be learning in your high school and early college science classes. So Richard, welcome to the show. Thank you very much for having me on. Can you start by telling us about your path becoming a scientist, starting from the beginning, growing up in Hampshire, England? Yes, so I started out, I suppose, at what is here, elementary school level. I went to a small school in a town called Hazelmeer, which was a great school. I was there from when I started, I think maybe H4 to H13. And this was a school where I received great teaching. I was interested in a lot of things. I did well at school. I think particularly I found science and maths to be interesting, and I mainly liked the things that didn't involve a lot of writing. So I veered away from the humanities, shall we say. And then at the end of that school, I did that school kind of a year up on my age, and there was an opportunity at the end of that school to stay an extra year to be coached for scholarship exams. And so I went, sort of, re-did the final year, but in a sort of an additional class to take scholarship exams for secondary school. And I got a scholarship to one of the best academic schools in the area, which is Guildford Grammar School, which was kind of a call historic school. It was set up by, I don't know, King Edward the something about 500 years ago. He decided that they needed to have some grammar schools to train people. And there still is at that school, kind of the original old building on the high street in Guildford. And it's got kind of the old old chain library and whatever. And the headmaster's office is up in the old building for when you get in trouble. And yeah, that's something I ve, we ve gone back to to look at with my kids when we visited England in the summer now. So I went to that school. It was a great school, very competitive, very academic. I decided to stay onto that school in what we would call sixth form. So I suppose what would be the last two years of high school here. And studied for the main exams to get you into college. And from there I went on to Cambridge University, which is, I suppose, one of the two best universities in England that people try to go to. And again, like a wonderful historic place. Cambridge was very much my kind of town. I grew up in relatively, not fully rural, but not urban. A small village I grew up in and it was not really, and still not really a big city person. So Cambridge is a small town that you could cycle out so quite easily. Sooted me just fine. And I suppose in a similar way, Baltimore now suits me as a city that it's a great city. Has a lot of things, but also is a city you can escape and live outside of and enjoy. All the green things that make life better. So yeah, I do college. I suppose in my eight of us at school, so the last two years of high school you specialise very early in the UK. So last two years of high school I only took physics chemistry and double maths. And then for college, most of the time in college at the start of college you fully specialise. So you would do, for example, an undergraduate degree in chemistry and would only do chemistry for the duration of your undergrad. In Cambridge they did things a little differently. So the degree I took was Natural Sciences which involved. In my first year I took a little bit of biology which I hadn't touched since I was 16. I took a little bit of chemistry, a little bit of physics, a little bit of maths. And then in my second year I did just chemistry in maths. And third and fourth years I did just chemistry. But as the chemistry got harder I suppose they got more maths in it. And at the end of that I really enjoyed Cambridge as a town and the university as a community. And I did well enough in my studies to convince one of the professors there to take me on to do a PhD. And so a PhD is a graduate degree. In the US system PhD involves quite a lot of advanced taught courses. And you have maybe for the first couple of years a lot of learning involved. And then you really deep into your research. In the UK the PhD is just the research part of that. So I think by specialising earlier we'd probably by the end of an undergraduate get to a greater level of depth but much more narrow. And that kind of has interesting implications for how my career is developed. And yes so I did a PhD. Before I went to university as an undergraduate I remember I was sitting at a high school chemistry class and the teacher put out an advertisement to say oh there's a sort of a gap year job opportunity coming up in the labs of Eli Lilly who are a pharmaceutical company based in Indianapolis, not anapolis, Indianapolis, Indiana. And they had a research site in the UK. And it was a medicinal chemistry site where they're trying to develop new drug molecules. I think Prozac was one of the big blockbuster drugs of that company. And actually after the Prozac era one of the big drugs that came out of that particular site was a Lanzapine which is a sort of anti-psychotic drug. So I applied for this job, I got this job so I spent a year before I went to university just kind of working as a lab monkey cleaning test tubes and running running stuff in a spectroscopy lab. So this was a service lab supporting the medicinal chemistry and basically your chemist does their chemistry. chemistry is hard, often doesn't work, especially when you're trying to do new molecules that no one's made before. And so they want to know at each step whether they have made the stuff they wanted to, how pure it is, and whether they can go onto the next stage in this insist to make their molecule, and the methods that you use to figure all of that out are basically spectroscopy methods and mass spectrometry. And these are physical chemistry methods that allow us to figure out the structure of molecules allow us to figure out whether the stuff in it's all like some yellow oil in the bottom of a test tube is that yellow oil, the specific yellow oil I was intending to make. And so I worked in this lab, as I said I did a lot of cleaning test tubes, I also ran tests so there was an infrared spectrometer in that lab which is looking at vibrational modes of the molecule, can tell you whether you've got carbon oxygen double bonds that kind of thing. And there was an ultraviolet spectrometer there which is looking at absorption of ultraviolet light by bonds in the molecule. And so I would run these experiments which were quite boring to do with a long stack of test tubes and it didn't want to do. And in the corner of this lab there was the big NMR machine which is this sort of six foot tall metal pan of an instrument which was very much the exciting and valuable instrument that I was not allowed to touch. And so I was quite interested in that interested in that piece of equipment, interested in the methodology and it seemed to me that in terms of really figuring out the structure of the molecules that was where a lot of the power was in the lab and also a lot of the intellectual challenge of interpreting the spectra figuring out what experiments to run in order to figure out exactly what's going on with the structures. So I became really interested in that technology and entirely by chance when I applied to Cambridge University to do my undergrad the college that I ended up at and there are about 20 different colleges. My director of studies there was a professor whose research was in NMR spectroscopy. So this was kind of exciting and he was ultimately the person who I was able to persuade at the end of the thing to take me on as a PhD student and that's Professor James Keeler who is yes an incredible man and intellectually thoroughly intimidating in the best of ways. So he was a wonderful mentor to me so that is I suppose my pathway to graduate school. At the end of graduate school I sort of had a couple of pieces of advice. One was if you're going to get a job now's a good time to go and get a job and another one was if you want to carry on in academia the next step is to do a post-doctoral fellowship and I was advised to try and do something that is as different as possible from what you do now but that you still remain qualified to do it and so the thinking behind that I think is that the further you move sideways the more you will benefit in the future from a different perspective on things and the more you will be challenged to develop new knowledge and learn new stuff and not just carry down this narrow path that you're doing and so at that stage I sort of jump ship from chemistry physical chemistry into medical sciences and I did a post-doctoral fellowship here in Baltimore in the radiology department and as we'll get into in the discussion later what I do now magnetic resonance spectroscopy is really just the in vivo or in the body application of NMR spectroscopy so at the same time that they were developing this technology to figure out the structure of molecules some other people figured out oh well if we stick a bit of a body in one of these instruments we can detect those same signals from the hydrogens in the body and we can use this for imaging so MRI medical imaging, magnetic resonance imaging is the same basic technology that was that big silver tin can in the quarter of the lab I worked in before undergraduate and MRI turns out in addition to looking at water to make a picture of the brain you can also detect signals from chemicals in the brain and so that's what I do now so I jumped from using this technology to figure out the structure of molecules in a test tube to using this technology to figure out well what can this tell us about the brain how it works when it's healthy and how it doesn't work when it's not healthy. That is super interesting and I also remember at the end of my graduate work I did not want to continue in academia but I thought it was interesting that when people were looking at postdocs it was just as you described you know kind of go to the edge of what you're still qualified to do but you know think about a new area where you can focus and that would kind of be where your career would center from that point forward. I think it's great advice and you know one of the great things I love about my work now is that all of us have done this have moved sideways so within my group I have some engineers I have people who are coming through with more of a computer science way of thinking about things I have people who've come through neuroscience and biology I have medical doctors who are sort of come through you know the medical training through radiology physicists chemists and we all share some common knowledge but we each of us have some knowledge that the others don't have and each of us has a perspective the way we think about things that is slightly different and I I definitely know that having come through chemistry I have a a particular perspective that sort of my physicist colleagues don't share and that is sometimes an advantage overall I think it's an advantage that you have all of these perspectives because I have blind spots that they can fill in they have blind spots that I can fill in and the best ideas come when you are thinking about difficult problems with people from a wide range of perspectives and to do what we do we couldn't do it without people who know like what the different bits of the brain do and we couldn't do it without people who know how that scanner works and we couldn't do it without people who know how to build software and so by bringing everyone together each of whom has had a specific training and then sort of jumped sideways into this thing it really it really enhances the work yeah it's kind of like a big lab like your sort of functions as a as a company in a way I mean you know really trying to get all these different skills and backgrounds to get to come together to work as a team I'm not sure how much this does look like a company having never really worked in one I have a great friend from college who has started up his own companies and I do think that there is some similarity to when you are trying to develop a career in academia if the thing is worth doing it hasn't been done before and and that is the same whether it is sort of a new startup company as an entrepreneur or whether it is academic research and so I do sort of often talk to him and think about his progress in a similar way and I think it is quite a helpful way to think about what you're trying to do certainly the structures around you and the pressures are different in business than in academia but I think there are certainly some similarities also yeah I was reflecting on NMR in preparing for this podcast and thinking about my own journey and chemistry so I remember in high school loving chemistry more than I had loved any other class because I loved the detail I loved knowing that this molecule is made of these particular atoms and they're bound together in this way it just everything became clear and then I think for me that happened again when I took organic chemistry in college and for our labs we would run infrared spectra we would we didn't NMR lab and I loved it I felt like it was sort of like the chemical rosetta stone like you get this printout and you see these peaks I mean you know it almost looks like for people who haven't seen these like I don't know like a like a lie detector test or like a you know one of my seismograph but these peaks are telling you ah you have this ad I mean it's bound to this atom and then what's around it. And it felt like just translating one language to another and then getting this incredibly detailed view of sort of what you say. Like you have a yellow oil and a test tube. And now this instrument is telling you exactly what's inside. So I just, and I think it's really interesting that you saw the power of that in this year at a pharmaceutical company, you know, and how important it was in their process. I mean, I think a lot of, a lot of what I have ended up doing has been guided by what I like and what I don't like. So I've been towards the science because I would take history exams and I knew that the person that came top in the history exam was the person who could write fast, just in the class. Like it just was simply a matter of, how do you get all that information onto the page and you've got one hour and you're just writing as much as possible. So it irritated me that I couldn't pump up in history 'cause I couldn't write fast, but also I didn't really find it interesting. And along the way, I have probably more often had science teachers that I connected with, but the nature of the work of science has correct answers. And so for me, having a black and white kind of mentality, I'm not discussing the causes of the Second World War. I'm thinking about things that are a little more black and white, I suppose maths especially, I appreciate it because of that. Outside of work, I have always enjoyed puzzles and logic puzzles and still like my Saturday morning at the moment is I get up, I make myself a coffee when I call my mother in England to do a crossword puzzle over Skype call with her. So puzzles are something that I really appreciate and that sort of pure logic of, oh this means this means this means this. And that really plays out very powerfully in NMR spectroscopy. It is a logic puzzle. You probably in front of you have all of the information necessary to decide is it what it should be. The question of is it what it should be is a good question and normally the answer is yes and you confirm it and you move on. When things get really exciting is when the answer is no, it isn't what it should be because usually then you want to try and figure out, well, if not that, what is it? And that's when you start getting into some two-dimensional NMR methods where you sort of have, I guess like a bunch of dots spread out across a two-dimensional map and you can actually trace relationships through the molecule. So you can say, well, this hydrogen is adjacent in the molecule to this hydrogen and this one is adjacent to this and you can actually sort of caterpillar along the carbon backbone of a molecule and figure out what is next to what, and start to piece things together. And so I love that puzzle aspect of the spectroscopy and you mentioned organic synthesis as an undergraduate. I didn't like making stuff in a test tube. I don't have this attention to detail and sort of focus on process. So I would sort of, you know, I do fine in my organic labs, but I wouldn't do great and I wouldn't do as well as I wanted to, but the puzzle aspect of designing organic synthesis, retro synthetic analysis to figure out, okay, well, how did this thing turn into this thing? What is going on inside the molecules? Those puzzle questions, I really, I really loved. - I love the comparison to a puzzle. So before we talk about the specific molecules you're using MRS to identify. I want to talk about how NMR relates to some of the chemistry classes that our listeners might be taking, whether they're in high school or early college. And so something that students in 10th grade learn and then they learn in other chemistry classes is this idea of electronegativity. So this is the idea that when two atoms are bound together in a chemical bond, one of them may hold onto those electrons a little bit more tightly. And as students know, if you were to look at the periodic table, elements that are on the top right, so we're talking about fluorine, chlorine, they're very electronegative. They're really going to hold on to electrons when they're in a chemical bond with something else. And then conversely, the elements on the lower left are less electronegative. They're not going to hold onto the electrons. So this is something students learn. I think sometimes students might wonder, okay great, why do we care? Why do we need to know that? But this plays a huge role in how NMR actually works. So Richard, it would be great if you could kind of connect what is the role of electronegativity in making NMR work as well as it does? - Absolutely. So I was actually, I would take maybe a step backwards first of all to talk about spectroscopy. So what do we mean when we say spectroscopy? Literally it means looking at the spectrum. I was out for a run last night and there was some incredible double rainbows. I was like stuffing my run to take photos of these rainbows. So the rainbow is the light spectrum. Visible white light is made up of a bunch of different colors of light or we would say different frequencies of light. Each color has a particular frequency. And so when you separate the white light into the spectrum, you are basically separating it along a frequency axis. So spectroscopy, normally the output is sort of a y-axis that says how much of this frequency is there and the x-axis is what is the frequency? So if that is infrared spectroscopy, the frequencies are in infrared light. If it's ultraviolet spectroscopy, the frequencies are ultraviolet light. And these different wavelengths of light interact with molecules in different ways. NMR spectroscopy is a little different in that you're not shining some frequency of light and seeing how it interacts with the molecule. But it is still a spectroscopy in the sense that the x-axis of these plots we are making is a frequency. And so the way that this interacts with electro-negativity is that the frequency we are measuring with spectroscopy with NMR is how fast is the nuclear magnetization processing. So there's a bunch of words there. So each hydrogen atom, so you have a molecule. The molecules made up of atoms, some of those will be hydrogens, especially if these are organic molecules like our living systems are made of. Each hydrogen has, as it's nucleus, a proton. And associated with that nucleus, there is what we call a nucleus spin. This is very complex idea. I honestly still don't know what this is having worked on it for 25 years. That is so good to hear. Basically, the nucleus acts as if it was a tiny magnet. And so it can interact with magnetic fields that you put it in. So the big shiny tin can in the corner of the lab that I first experienced. Or the big donut that you see when you look on medical dramas on TV and see somebody traveling into to do an MRI scan, what is that big machine? It basically is a big magnet. And so these magnets have quite strong magnetic fields. They are generally the engineering of them is that they are superconducting magnets. So you have an electromagnet current going round in a coil. And if you cool that down to very, very low temperatures and you make the coil out of some special, special alloys, you can make that wire have no resistance. So rather than needing a power source to shove the current around and make a magnetic field for an electromagnet, you can just have an infinite current loop, which makes a superconducting magnet. So that's what the magnet is. And because the nucleus of the hydrogen has this kind of magnetic property associated with it, it can interact with magnetic fields from that machine. And you can cause a signal to come out of the thing, which you can detect. And so the signal that comes out is in the radio frequency range. And it turns out that the signal you detect is directly proportional to the magnetic field that you put your sampling. So. The bigger your magnet is, the higher the frequency of radio frequency that you are detecting. But also, within that same magnet, very, very small perturbations in the magnetic field will slightly change the frequency of the signal that you are detecting. And one of the big perturbations that we have is even within the same molecule, different hydrogens within that molecule, their nucleus will be experiencing a different magnetic field. And why is that? Well, now we get through to this electron negativity idea. So, as you said, electron negativity is the characteristic of atoms to suck electron density towards them. And so what that means is we know that bonds within a molecule are made up of electron density. The electron density, in the anomaly, we draw a bond as a line. We have a carbon and then a line to a hydrogen. Then as we sort of develop our understanding of what chemistry is, we know well, the electrons don't lie along that line. It's kind of a cloud that sits outside of everything. And that cloud gets kind of sucked through the molecule towards the things that are more electronegative. And so it goes towards, for example, in our organic molecules, one of the most electron, sorry, in the molecules of our body, one of the most electronegative atoms in there is oxygen. So if there is an oxygen in this molecule, it's just going to suck electron density towards it. And what does that mean for a hydrogen nearby? It means that hydrogen is going to have less electron density around the outside of it. And because electrons have electrical qualities, electrome, electrical and magnetic properties are kind of two faces at the same magical thing. What that means is the magnetic field that is experienced at the nucleus is changed by the amount of electron density in that cloud around the nucleus. And so we call this shielding. So the electron density around the outside of the atom is shielding the nucleus from the main magnetic field. So if I have this magnet, which is like a three-tessler magnetic field, what I did, what I experienced at the nucleus is slightly less than three-tessler. And the amount by which is slightly less is determined by the amount of shielding electron density around the outside. So if I have this electronegative element nearby in the molecule, it sucks away some of that shielding electron density, allows my nucleus to experience a little bit more magnetic field than it would otherwise. Makes that frequency shift along the spectrum axis, because we know that the frequency of these signals is proportional to the magnetic field that's experienced. And so that is how you get from chemistry of, you know, chemistry is all about what atoms are where in the molecule. And the sort of physical chemistry aspect of electron density, which is the bonding, sort of map of the molecule being sucked around by different atoms with different electron negativities. You can then interpret the spectrum. So I know, for example, that this hydrogen is coming along my frequency axis at four parts per million. I know it shifted up to that end because it is right up close in the molecule to an oxygen. It is really getting sort of slid along because there is something really electronegative close by. Whereas some other signal further away in the molecule might be down the other end of the spectrum at one ppm, because it isn't close to any electronegative things. And so you can interpret the frequencies of the signals in the spectrum in terms of how the molecule looks. And I loved your comment about the periodic table and the top right being where the, where the most electronegative stuff is. And I have literally that slide of when I'm talking to neuroscientists about how this methodology works in a course that I give. I have that sort of, you know, here's the periodic table. All you need to know about electronegativity is stuff near the top right, sucks electron, electron density towards it. And that tends to de-shield hydrogen signals and moves them up the spectrum. And so when you look at that NMR spectrum of a region of brain tissue, you can sort of break it down into this part of the spectrum is hydrogens that are close to an oxygen. Then the next sort of region of the spectrum is hydrogens that are close to a nitrogen, which is not so electronegative as a oxygen, but still quite electronegative. And, you know, in the organic molecules that our living system works on, they all have carbon backbones and carbon is sort of electronegative neutral. They have hydrogens sort of filling the gaps off the sides, being also neutral and not so interesting from an electronegativity point of view. And then the exciting chemistry is mostly oxygens and nitrogens. They're a little bit of sulfur chemistry in vivo, but it's mostly oxygens and nitrogens. And so you can tell this end of the spectrum is near oxygen. This end of the spectrum is near nitrogen. This end of the spectrum is not completely boring, but maybe too clicks away. So it's sort of an extra bond in the network away from an oxygen or an oxygen. And then there's the kind of dull end where there's no interesting chemistry nearby in the molecule. For example, in liquid chains, liquids or fat molecules are basically just endless hydrocarbon chains. Carbon with a couple of hydrogens joined to it next to a carbon with a couple of hydrogens joined to it. And these long snakes of super borin chemistry that have an important function in building cell membranes and allowing the living systems to work. It's so interesting. And thank you for that wonderful explanation. I would love to now talk about what you are looking for in the brain. If you could tell us a little bit about GABA and why you're interested in it, what that tells us about brain health. Yes. So when you put a person in an MRI scanner, you can detect these signals from water and get a beautiful image of the inside of the head. And I remember when I first moved into doing in Bebo science, my desk was sort of right in the waiting area of an MRI scanner. And just the, you know, I remember one guy, one time a FedEx guy came in to deliver a package to the person who was running the scanner. And he kind of looked on the screen and he was like, so I guess that's the inside of somebody's head then. And the, and the technology said, yes, he said, man, that is some crazy. And I think we probably don't need the bleak technology. But there is that sort of sense of medical imaging allows you to look inside stuff that you can't look inside of. This is still like just a wonderful, kind of thrilling thing for me. I can, you know, the other week my kids came into to jump in the scanner to get some some spending money. And you can see the inside of their heads. I don't know what's going on in there and maybe not that much, but you know, we can actually get an image of the size of the head. So you can use the imaging to look at the water. But the same signal that comes out of the water to do that MRI imaging comes from those hydrogens in the water molecules. Or there's a bunch of other molecules which are actually sustaining the sort of mechanics of the cells. All of those have hydrogens in them and we can detect those hydrogen signals with magnetic resonance spectroscopy. So that's what we are doing. When you put a lump of brain tissue, hopefully still inside a head. But if you put a lump of brain tissue in this machine and say, what NMR signals do I get from this? You get a spectrum and there are different peaks in the spectrum that come from different kinds of molecules. So one of the strongest peaks in brain tissue is from creatin. And so anyone who is into going to the gym and that kind of stuff knows the creatin is one of the important energy carrying molecules in the body. You have a creatin molecule. If you strap a phosphate group onto it, then this can be like an important sort of instant access energy storage is why people take creatin before they go to the gym to try and maximize the levels of creatin available. That is also the same in the brain. The brain is using creatin to store energy in an instant access way the same that muscles do. And it turns out that one of the, or maybe the second strongest signal in brain tissue is creatin. And so in the historic development of this methodology, looking at the brain chemistry with spectroscopy for maybe the sort of first 30 years of this. Most people focused on the three, four or five strongest signals. And this makes sense because the method that we have is not very sensitive. We are looking at chemicals in the brain that are present at millimolar concentrations. So 80% of the brain or so, don't shoot me for the percentage. 80% of the brain is water. So there is a ton of water. And in concentration terms, that's like 40 molar. So a super concentrated signal. And you can get a strong signal and do great imaging with it. If you want to look at the chemicals that are dissolved in cells in that water, these are at most 10 millimolar concentration chemicals. So we are maybe four orders of magnitude or 10,000 times weaker signals. And we are looking at weak things. And so that is why for the first 30 years or so, people really focused on the strongest signals, the easiest things to look at. And so we looked at creating, we looked at the strongest signal, which is from N-acetyl, a spartate. And that's a funny story in itself because nobody really knows why this is the strongest signal in the brain. It's definitely not the most interesting molecule in the brain. And it's also definitely not the most important molecule in the brain. It's sort of a kind of an accident of cellular physiology that it just accumulates and gets a high strong signal in the spectrum. But people have focused on it a lot because it's one of the things you can get at. And so in my career, what I have ended up doing, because of the jump that I took sideways from chemistry into in vivo, during my PhD, I was designing new experiments to kind of unlock the puzzle of the structure of molecules. Well, when I jumped in vivo, I was using some of the same ideas to look at the spectrum and say, okay, maybe those strongest signals have been a little bit, I don't know. We've looked at those strong signals for enough time. Let's ask the question about some of the weakest signals in the brain. And it turns out that when you jump down from the 10-millimolar level to the 1 or 2-millimolar level, there are some chemicals at that level that are really biochemically interesting. And I basically spent 10 years focused on trying to improve methods for looking at GABA in the brain. So GABA, we're interested in GABA because it is an inhibitory neurotransmitter. So what does that mean? Well, a neurotransmitter is a molecule that one neuron or nerve cell releases in order to send a chemical signal to another nerve cell. So anybody who has done sort of biology of nerve cells might know that nerve cells often are kind of long and thin. If you like, and along the long, thin part of the nerve cell, there is an electrical signal that jumps along the membrane. So within a particular nerve cell, it is an electrical signal being sent. But there is a compartmentalization of that electrical signal so that when that nerve cell wants to talk to the next one, it needs to release a chemical signal, which is the neurotransmitter. And then that neurotransmitter molecule docs on the next cell and starts the electrical signal whizzing along that next nerve cell. So this is a neurotransmitter, a small chemical messenger released by a cell. What does inhibitory neurotransmitter mean? Well, it inhibits the transmission of a signal by the next cell. And the opposite of that would be an excitatory neurotransmitter. So if I release an excitatory neurotransmitter and it docs on the cell that I'm communicating with, then it makes it more likely that that cell sends off an electrical pulse. So there will be some synapses or connections between cells that are excitatory synapses making the next cell more likely to fire. But there will also be some inhibitory synapses which are making that next cell less likely to fire. And when you get into the neuroscience of how does this lump of meat in our head, do all of the incredible cognitive tasks that thinking and the calculating that we're capable of, it is, I think, in large part because there is this incredible complexity of a very large number of cells with very tightly controlled activity. And so it is the inhibitory neurotransmitter which is sort of the important pullback on the C-saw. So there's this really important idea that you have to have a balance between excitation which is the go signal and inhibition which is the stop signal. And that balance is what enables the brain to function well. If that balance gets out of kilter, if you have too much go signal and not enough stop signal from the inhibitory side of the equation, then the excitation in the brain can just balloon and get out of control. And this is what happens when you have an epileptic seizure. A seizure is basically just a blossoming of uncontrolled electrical activity in the brain because the inhibitory system has not tampted down and got things under control. And so most of the medications that you take to control seizures are dabbour acting drugs that they will sort of supplement the natural GABA communication in the brain with some additional GABA, and GABA acting input into the system to try and sort of control that runaway activity. I was not very interested in GABA from a neuroscience perspective. Let's be honest. So I started looking at this brain because I was interested in the methods and the what can we do with this technology that I am able to do and interested in. And actually I was so so not interested in the neuroscience that I stood up at an international conference like the biggest conference in our area. And I had spent weeks and weeks preparing my slides had beautiful slides. I practiced endlessly and I stood up with my introduction slide. Now an introduction slide over talk like this is sort of like you have to do an introduction, but you don't really care about that. You care about the meat of what did I do, what did I find, what did I show, what's the new stuff. So maybe this is revealing my terrible attitude to the whole process, but I stood up confidently at this conference and I said my first sentence GABA is the main excitatory neurotransmitter in the brain. Now I carried on with my 10-15 minute talk. I did a great job with the talk, but somebody very kind after the talk came up to me and said, you know, I really appreciated your talk. Great work, but I feel like I have to point out to you that GABA is not an excitatory neurotransmitter. It's an inhibitory neurotransmitter. And so I should have been absolutely mortified by this. I wasn't mainly because I didn't really understand the difference between inhibition and exo-excitation because I haven't come through this sort of neuroscience direction towards what we do. And so sometimes in your ignorance, you don't even know what you don't know and how important it is. So this is also another aspect of the work that I really love is we have to learn while we're going. I know what I know, but now I've got to learn what the difference in an excitatory neurotransmitter is. Or I need to know what is this bit of the brain do or what does this disease process look like and this learning from the people around me who've come at this from a different direction is really wonderful. So now I know it is an inhibitory neurotransmitter and we've done a bunch of really interesting experiments looking at, well, how does changes between people in the amounts of inhibitory tone in an area of the brain? Relate to people's ability to do particular tasks. And so it turns out that the ability of the brain to faithfully and accurately represent information is reliant on this gabrogic inhibition. It's this control, it's this tightening down of information representation in the brain and you can literally do a task and how well you are able to do some of these low level, for example, a low level visual task will actually directly relate to how much of this inhibitory transmitter you have in visual areas. And so we've done some of these experiments that really get into the mechanism by which the brain can do some of the amazing things that it does. And also in not just in epilepsy, but in a number of brain disorders because this idea of the balance between excitation and inhibition is so fundamental to the brain working well. You know, it can go off the charts and have way too much of a difference. runaway excitation as a seizure, but even just small imbalances in certain systems can be a part of the picture that is involved in some complex psychiatric disorders and developmental disorders and so forth. So I came together because I knew the technology and it turned out I could look at that. And along the way I found something that was a super interesting intellectual puzzle to try and learn more about the neuroscience and more about the neuro transmission. So it's often that way. You have to justify your work in terms of why it's important. And that's reasonable. It's not reasonable for you to be doing stuff that is of no use to anybody. But normally you're doing the thing that is interesting to you and that you are equipped to do. And often the why it is useful is sort of a bit of a post hoc justification, but then a few years in you know why it's important and then you carry out. - Yeah, that's very interesting. So when we were talking about this podcast, you said your group takes this approach where you're kind of developing modifications to the method based on the results you're getting. I would love for you to talk us through that work cycle. And if you could do so with this Hermes experiment tell us how you use this approach there and what problem that helped you solve. - Yeah, so at the heart of what we do, we tinker with applying these methods to look at the brain, but mostly we are sort of like the people who are enabling the people that know about the brain to do those experiments. So we are trying to make methods that allow people to answer interesting questions about the brain. So with this GABA molecule, I said the concentration of GABA is about one to two millimolar. If you want to detect that signal and really measure it, you've somehow got to get rid of all the other stuff. So we use this methodology called edited magnetic spectroscopy. And all we mean by edited is we are going to change the information content of the spectrum, mostly to simplify it and reveal this one isolated signal that we can quantify and associate with the GABA molecule. So the way we do this editing is really just a subtraction of two experiments. We do one experiment where we get all of the signals and then we do another experiment where we also get all of the signals that we've changed the GABA signal a little bit. And so if we do two experiments where most of the signals are exactly the same, but the GABA signal has changed when we subtract those two experiments, we're going to get a spectrum which only contains the signals you changed. Okay, and so you have two halves of an experiment, you subtract them and that shows you the GABA signal. So this is different editing. And this is a great methodology. Like I said, I spent 10 years trying to make it better, trying to broaden access to it, implementing it on different systems, sharing software to analyze data or all of this stuff. It's also super slow. So if I want a measurement of GABA from the visual area of the brain at the back, I need to spend 10 minutes measuring GABA over there. And that is 10 minutes to measure one molecule. If I also am interested in another molecule, so maybe I'm interested in looking at a different system of the brain, for example, the antioxidant system, the ability of the brain to sort of stay safe and get rid of free radicals that can come up in the brain. If I'm interested in doing that, I might want to look at a molecule called glutathione. So I can also use this edited methodology to get a glutathione. It's also at that sort of one to two millimolar level in the brain. And so then I've got to spend another 10 minutes doing my glutathione measurement. And in hindsight, this was sort of a stupid way of working because that first GABA experiment, I was detecting glutathione signal there. The first half of the experiment had some glutathione in it. The second half of the experiment had some glutathione in it. I was then subtracting those two things away. And the glutathione was in the majority of signal I was throwing out to just reveal that isolated GABA signal. And then when I did the second one to go look at glutathione, like I was detecting GABA all that time and throwing it away. And so one of the amazing things we figured out when we developed this Hermes experiment is, oh, wouldn't it be great if rather than throwing those signals away, we could find a way to edit the GABA signal at the same time that we're editing the glutathione signal. And so then we can throw away most of the stuff but keep the GABA signal and keep the glutathione signal and do so in a way that keeps those two channels separate. And so there's this amazing sort of thread of mathematics called sort of, it was discovered, I suppose, by a guy called Hadamard. He's probably French because a lot of this mass is French. And this is a way of encoding different signals into data which they are mixed up but can be separated out at the other end. That's sort of what we're doing. So one good example is that difference experiment at the beginning, the simplest possible Hadamard matrix. It's two by two matrix. One side is adding and the other side is subtracting. So in those, that first experiment I described where we are acquiring signal we don't want and signal we do want at the same time. If we change the signal we do want, then that is gonna end up in the subtraction experiment. If we added the two halves of these experiment, that would give us everything else. So this is what we start to think about, we think, oh, well maybe we don't throw that stuff away and ignore it and just measure Gabba. Maybe we start to retain that other stuff. And it turns out that there is a four by four Hadamard matrix which is a bunch of plus ones and minus ones. And based on that, you can design an experiment where we have four different parts of the experiment now, not two. And those four different parts of the experiment are going to mess around with the Gabba molecule during some parts, mess around with the glutes of thion molecule in another step. There's a step where we don't touch either of those molecules. There's a step where we touch both of those molecules. And then there's a complicated plusing and minusing of those four different experiments. And if you add and subtract them in one way, you get this Gabba spectrum out. And if you add and subtract them in a different way, you get the glutes of thion spectrum out. And so this was super, super interesting. We've got all these collaborators who are using our methods to look at the brain. And they're fighting with their other people in their area who they want to do imaging of the diffusion of water in the brain or they want to look at some function in the brain or they want to look at different things. So everybody, you know, the subject's only in the scanner for an hour. Everyone wants their part of it. You want to get as much information as possible in that part. And they're saying, "This is too slow. It's terrible. We want more information." So we found a way of combining two experiments that used to take sort of 20 minutes to do to into one package where we're doing both things at the same time, but we can also separate out the other side. And for me, when I give my talk about our research, you know, sometimes I'm talking to technical people that are really into the weeds of what we do. Sometimes I'm talking to clinicians who are interested in, well, what can this do for me and my research? And sometimes I'm in the room. There's people that don't have any sort of point of connection with the work and are just there to be polite, to feel a seat. But what I sort of say to them is-- and this is, like, I think a really wonderful general thing-- is the reason that we were able to make that experiment twice as fast wasn't because we magically changed the physics of the universe to make things twice as good. What we managed to do was find, like, a weakness in the old way of doing things which was wasteful. And so the way we make things two times as good is that we remembered that actually the signal was there all along. It's just that we weren't saving it. And so by finding an aspect of what we were doing that was wasteful, we were getting that extra signal all along, but throwing it away. And we find a way. Now we retrieve that signal rather than throwing it away. We're able to do things that are two times, four times, eight times as fast. because we are finding signal that we used to throw away and keeping it back. So in every aspect of our life, I think if you can find ways that you are being wasteful, this is a great sort of thing to focus on and thing to eliminate. It's quite hard to convince your boss to spend to pay you 10% more, but you can probably find ways of getting your groceries in a different way that is 10% lower price and suddenly you've got 10% more money. So waste and the understanding of waste, the thinking about what you're doing in a way that is thoughtful and it's analysing things in a different way and thinking, "Oh, hang on, maybe I could do things in a different way that retrieved the thing I used to think was lost." So that as a general idea is something I sort of say to all researchers, "Can you think of ways that what you're doing is wasteful because those things you can get back for free? You don't have to pay for those things with time or with money or whatever." That's a wonderful perspective on discovery as well. I think many people would think of scientists making discoveries as you said before, doing something completely new, but this is looking at what you've been doing and fixing it in this very precise way. It's already there, you're just kind of rescuing it. Yeah, this idea of rescuing, I guess it speaks to me as a person as well. I love that. One of the things that is funny about this is this idea of the hadamard encoding of signals. I played with this in some experiments during my PhD and then quite early on, like quite soon within a year after I had first started looking at these GABA experiments, I had this idea, I had this idea that I could do hadamard editing, but I didn't know that it related to GABA and due to thio, and I thought of it for a particular other set of molecules. I had the idea and then I ended up moving back to the UK for a job. I got distracted. I ended up after a while coming back to Johns Hopkins as faculty. Another two or three years go by and suddenly I've got a new student who needs a project and is not, you know, has sort of got a bit of time to play with some ideas. I said, "Oh, well, how about maybe we go back to that idea of hadamard encoding of these sort of pluses and minuses?" And so she was an amazing student. She implemented the original idea I had and it was only by doing it once in the idea I'd had like five years before by doing that once and we showed that it worked. And I was like, "Oh, hang on, we can also do this, not for those two sort of niche molecules that maybe no one's so interested in. We can do this for the big two targets. We can do this for GABA and due to thio." And so often you don't know the importance of what you've done until you've done it. And so it's often, you know, often you sit there and you're like, "I don't know what to do." And in research, I think in life also, it's always much better to be doing something than not doing something because the doing something, even if it's a stupid thing to be doing, starts you thinking and then you can come up with the ideas of, "Okay, well, maybe this thing is not that useful, but the next thing that builds on top of it, that might really be useful." So that was kind of an interesting lesson because this is an experiment now that we are doing experiments. We built from this idea in some really large studies. There's a wonderful study going on at the moment called the Healthy, I've got to get this right, the Healthy Brain and Childhood Development Study, which is a national level study. There are maybe 25 universities around the country. Each university is recruiting 300 pregnant mothers. So in total, this study is going to be following thousands of babies through the first years of their life. They're getting multiple imaging sessions, maybe four imaging sessions during the first five years of life. And we're really going to get for the first time an understanding of what is happening chemically in the brain, sort of, seriously as the brain is developing. And when you're a 20-year-old adult, until you're a, sort of, I don't know, 70 or so year-old adult, your brain is relatively the same. It's getting a little bit worse every year, relatively the same. And then, as you get older, maybe you notice in older relatives that things start to become more challenging as you're older. But again, things are happening relatively slowly. When the baby is developing and the brain is developing before birth and just after birth, you look at a one-month-old baby and it can't do anything. It's like it's alive and it can lie there. And basic bodily functions are happening. And then over that first two or three months, the brain is really, really developing fast. And the baby goes from lying there doing nothing to all now, it can follow an object that you hold in front of it. Or it will engage with your face or it will smile when you smile. And as you go grow up, you know, those first two years, these sort of, you know, the incredible changes that happen in the brain in those first two years are happening so fast. And that's reflected in the biochemistry of the brain. You can actually see the spectrum changing in those early months. And you can, you know, if you are somebody that looks a lot of these spectrum, you can actually look at the chemicals in the brain and say, "Oh, this is a newborn baby." "Oh, this is a six-month-old baby." Or you can really, the changes are so dynamic in the chemistry of what's going on in the brain. That is super interesting. And I love the perspective of if you don't know what to do, just do something. Yeah. I mean, I think about that a lot as a writer. And when I'm coaching people on writing and they say, "Well, I don't know what to write." And well, you don't need to. Just start moving your fingers on the keyboard or just start making motions with the pen. And that action will then get things going. But I would assume it's very similar in what you're describing. Just start doing something. Yeah, absolutely. Because the only thing you know for sure is if you don't do anything, you won't get anything done. That's right. And, you know, you miss 100% of the shots you don't take. Yes. And I think that it's a hard lesson to learn. It's an easy lesson to tell somebody else. But when you're in that moment of inactivity and you're like, "Oh, I'm not feeling it. Maybe I'll go on YouTube." It is a hard discipline to have to say no. I'm going to rain myself in. I'm going to focus on this thing. Maybe those of us who have a little bit of the attention deficit going on, you know, I'm going to focus. I'm going to do this thing. And maybe I don't know exactly what I'm trying to achieve. But by doing something, I will start to, you know, I'll do something. I will be able to critique that something and say, "Well, no, that's not it. Why isn't it it? What is it? Not." Right. And so then from asking, "Well, what is this not?" Then says, "Well, therefore, the thing I should be doing is this other thing." And you know, it's true of research. It sounds like it's true in your writing. It's definitely true in high school homework and all of this stuff. Like, get it done and then do something more fun later. So I have a question from a listener. This is from Lucy Poll. She's a rising junior at the Nightingale Bamford School in Manhattan. And her question for you is, "What issues and science have become more significant to you as a result of your research?" I think you've touched on some of this, but. What issues and science have become more significant to you as a result of your research? I think that for me, there has been this sort of gradual drift through my career from very physical-based things. So I did my PhD in physical chemistry, like the real nuts and bolts of how do these experiments work. And then I made this jump into the brain and I told the story of how I stood up a conference and I didn't know what I didn't know because I hadn't got far enough to sort of even [BLANK_AUDIO] to care about that stuff, I was still so focused on the methodology, whereas now I think increasingly I'm focused on what this methodology can do for science and for our knowledge and understanding of the brain. And some of that is I have learnt more along the way. Some of it is just a sort of a growing confidence or a boldness to allow myself to think bigger. It is difficult at the beginning of things to understand what is possible. And actually I think this is something I really love about the American mentality is that Americans tend to have an optimism and a thinking big approach to the world. And this is not my way of doing things is okay. Let's start small. Let's build incrementally, let's stay where I feel safe and able. And over time things snowball and you can build them up. But for me, I started very much in that technical, okay, this is what I know. I'm going to focus on making these experiments a bit bigger and so a bit better. So you make the experiment a little bit better, a little bit better. You add this, you add this. Over the years, you figure out, oh, we've actually come quite a long way. And now we have a set of technologies that can actually be sort of ready to be applied in these huge national studies to actually change what anybody knows about the developing brain. It's sort of super exciting. So definitely for me, I have drifted from the very technical stuff to the, what can that do as a result of having sort of accumulated a bunch of stuff over time. I suspect maybe Americans starting out in the same place I was were always thinking in a big picture way or you know. But for me, it's definitely that sort of drift from the technical through to the implications of it and the science that can be done with this method. Not to say that one thing is better than the other. We still need that technical knowledge because without that we can't do any of this stuff. But it really is important to be thinking in both ways. And my last question is what advice do you have for students in high school and college who are interested in the career in science? Do some science. It's that simple. So I've got an amazing story. So my group here is almost entirely made up of postdoctoral fellows. So people who have done a PhD, they've decided they want to pursue a career in science. And then the final part of their professional training is called a postdoctoral fellowship. And from that they advance into junior faculty positions and up as professors during research in various places. So my group is mostly people at that final training stage. I mentioned Kim Chan who was this amazing student I worked with who developed the Hermes experiment. She was a graduate student working towards her PhD. So she was really the one of very few graduate students that I've worked with in my career. Well I was at a conference earlier this year and I went to a hackathon before the conference which is basically a bunch of people sitting in a room with donuts trying to work together on sort of team development of some code that the field would benefit from having. And I ended up in a group with a couple of undergraduate students. So these were students who were, I think they were at Harvard, so like Super Fancy University. But they had basically reached out to a professor who does research in my area and said okay we want to have some hands on experience doing science. Is there anything we can do in your lab? And they were incredibly incredibly able. They brought a very different perspective than mine because they're like there's a whole bunch of stuff they don't know but they have grown up in sort of a completely different era to me with respect to like their ability with computers. And they were spending a lot more time on chat GPD than I was trying to solve things and like it was it was a real eye opening experience for me. And then later that week I went to a poster presentation of a piece of work by another member of their group who was a high school student. So this is somebody who is a high school student who had similarly reached out to that professor and said I'm interested in doing some research. I think what you're doing looks kind of cool. Is there some way that I can contribute? And like I mean I was I was I was like jaw dropping on the floor at this kid. Just like just I didn't I sort of didn't know this is possible you know you so you become a little enamored with oh well what we do is super clever and super like you know you got you need all this like 20 years of technical training to get here or whatever you know like you and then all of a sudden you you find out some of what you do is super hard and evolves those years and years and years of like hard physics and all of this but some of what you do doesn't need that and so that's the same of all science you know some of it is super hard and super difficult but some of it can be done by a lot of different people if they are just sort of smart willing to come in learn try and do things and so you know that he was and I forget his name which is embarrassing but you know just incredibly impressive and the the work he was presenting was like amazing work not just amazing because he was a high schooler but you know amazing work anyway if this was somebody in my group as a post-op presenting this work I would be pretty proud of it and I would say you know this is a great great piece of work so if you are a high school student what I would say is you know if you are interested in a career of science try and find some science that you can get involved in now all professors get a bunch of emails from people so you will have to find a way to get in contact with a professor and make your email stand out so what you don't want to do is copy and paste the same email to 3000 professors and say I really loved your website can I do some science you could actually find out what am I interested in who is the people who are doing this kind of stuff read a little bit about their stuff and you really get get to grips with well what specifically is it they're doing and write a specific email to that particular professor and say okay I know what you do I find it really interesting I pulled up this paper that you did recently and I thought it would like actually focus on what the work is and say you know I'm a high school student I want to pursue a career in science I understand that what you're doing is really challenging but is there some way that I could get involved and one of the great things now about you know there's so much sort of communication it's very easy to get on a video chat with people and talk about stuff it's very easy to share code through like GitHub repositories so that you can work on projects in different locations and so I think these things are easier if you live in a big city near a big university that that makes it easier but if you live you know even outside of outside of that then you know you are still enabled by by email and by by video conferencing and by by code to do that and I think a lot of professors are motivated by that you know for me when people apply to work in our group I am very interested in where they are from because I think that tells you a lot about who they are and how far they've come and what are the challenges and so you know I think that if you are like your your last listener who sent in the questions from Manhattan right so they can write an email to some professor at Columbia and say look I'm here I'm in Manhattan I'd love to do some science so writing to you maybe they're already doing some science in lab I don't know so so that stuff is very accessible but those professors at Columbia might get a bunch of emails from people that live in Manhattan and maybe they would be more interested if they received an email from somebody who is in Idaho saying look I've read what you're doing I'm interested in it I would love to develop a career in science and I'm wondering if there's a way that I can contribute to the work of your lab. Then, you know, I think that you never know until you send those emails how they will turn out. Wonderful. Richard, thank you so much. If listeners would like to learn more about your group's work, how could they do that? Ha ha, great question. So this is where I should say, I have an excellent website, but I'm not sure what I do have an excellent website. So I do have a website from my group, which is called gaba-mrs.com, g-a-b-a-m-r-s.com. So that is one way. Another way which works more generally looking for professors and work that you're interested in is if you want to see science in an area, especially in medical sciences, there is a wonderful database of all the papers which is called pubmed. That will allow you to look in a particular area and look for papers and start to get a sense of what is interesting. A lot of people will have a little bit of something on YouTube. So YouTube is kind of a good general place and you know, I think it gets sort of poopued because mostly it's about, I don't know, videos, escape orders or whatever, but I use YouTube a lot for learning new stuff and finding people in an area or things like that. So just look for people and try and find stuff. And one of the amazing things as Americans is if your research is funded by the American government, which for most of us, that is the case. Part of the sort of quid pro quo of that is that you need to make all of your papers available to be read. So mostly when we write up a piece of work and send it off to a journal, that journal is run by some publishing conglomerate and they sell those journals for like hundreds of dollars to university libraries and the whole thing is a big racket. Well the government said, okay, this is absurd. We are paying for the work. We also want to retain access to the information that comes out from that work. And so PubMed has this offshoot arm called PubMed Central, which is a repository of all of those papers. So if you start to get interested in a particular area, you think, oh, this professor might be interesting, like look on PubMed for some of their papers. And if you're looking from within the US, you can click through and you can go through PubMed Central links to access those papers and and sort of maybe really start to get to some of the information. Thank you very much for the discussion and the fascinating stories, explanations. This was amazing. Thank you. That was Richard Edden talking with us about spectroscopy, his work on using spectroscopy to find out about the brain and some broader reflections on discovery and how following your interests and taking steps forward can lead to unexpected success. Listeners, please consider filling out a survey so we can continue to bring you great content. You can find a link to the survey in the show notes of this podcast and you can also find it on the Instagram page. The account is @ScienceFairPodcast. Thank you for tuning in to today's episode of ScienceFair. Please rate and review the episode on the podcast app of your choice. See you next time.