Podcasts

Podcast – Smart New Ways To Diagnose Dementia

Hosted by Dr Amanda Heslegrave

Reading Time: 25 minutes

Great progress has been made over the past decade in the development of blood based bio-markers to diagnose Alzheimer’s disease and other forms of dementia. However, other areas have been quietly working away, and have also made significant progress.

In this podcast we explore two of the newest and most innovative technologies being applied to detect biomarkers for dementia – looking at the retina and brainwaves.

Dr Amanda Heslegrave, Senior Research Fellow at the UK Dementia Research Institute, University College London and one of the people behind the progress being made in blood-based biomarker field is out guest host.

This weeks guests are:

Dr Catherine Bornbaum, Head of Clinical Operations and Partnerships at Retispec. Catherine, uses innovative imaging technology combined with robust machine learning and artificial intelligence (AI) to detect biomarkers of neurodegenerative disease throughout the eye. The eye provides a simple and non-invasive way to measure the central nervous system; it is also the only organ where both neurons and blood vessels can be directly visualized at micron-level resolution.

Dr George Stothart, Senior Lecturer at University of Bath. George is a cognitive neuroscientist who translates the findings of cognitive neuroscience into useful tools for clinicians and the wider world. His primary research focus is the development of a new EEG technique, known as Fastball, for the assessment of cognitive deficits in dementia. Fastball EEG is a completely passive test which measures brain waves the patient looks at a series of images on a computer screen over two minutes – a completely new assessment technique.

For more information go to:

https://www.retispec.com/

https://www.bath.ac.uk/projects/fastball-mci/


Click here to read a full transcript of this podcast

Voice Over:

Welcome to the Dementia Researcher Podcast, brought to you by University College London, and the NIHR and Association with Alzheimer’s Research UK, Alzheimer’s Society, Race Against Dementia, and the Alzheimer’s Association supporting early career dementia researchers across the world.

Dr Amanda Heslegrave:

Welcome to the Dementia Researcher Podcast. I’m Dr. Amanda Heslegrave, and I’m a senior researcher at University College London. It’s my pleasure to be guest hosting this week’s show. Normally, I can be found at the UK Dementia Research Institute, biomarker Factory, and I work out how best to accurately identify dementia biomarkers from blood samples. But today I’ll be doing something a little different. I’m going to be joined by two people who’ve got new and clever ways to look at the challenge of biomarkers for Alzheimer’s disease. And they’re both probably trying to put me out of work, although I think that’s not going to happen. My wonderful guests have got some high tech, amazing new approaches to diagnosing Alzheimer’s disease and other dementias. So, in this show, we’re going to discuss these approaches, their work and how they might be applied. So, let’s meet the guests. I’m delighted to welcome Dr. Catherine Bornbaum and Dr. George Stothard. Did I say that correctly, George?

Dr George Stothart:

You did.

Dr Amanda Heslegrave:

Oh, perfect. Okay. So, let’s do some introductions. And Catherine, would you like to go first, please? Just tell us a bit about yourself.

Dr Catherine Bornbaum:

Sure. Thank you. So, I’m really fortunate to serve as the Head of Clinical Operations and Partnerships at a company called RetiSpec. So, the company’s headquartered in Toronto, Canada. And the company is an AI medical imaging company where we’re developing algorithms for the detection of neurodegenerative diseases, specifically Alzheimer’s, based on a very simple eye exam that leverages existing imaging infrastructure in eyecare settings. And so the focus of my work is on the clinical validation of this technology, where we compare it to clinical gold standards. So things like PET scans or lumbar puncture, cerebral spinal fluid analysis.

Dr Amanda Heslegrave:

Okay, thank you very much for that. And then George, can I come to you?

Dr George Stothart:

Yeah. Hi, I’m George Stothard. I’m a cognitive neuroscientist. I work at the University of Bath, and my research is on developing functional biomarkers of dementia. So primarily using EEG to try and improve the sensitivity of our measures of brain function. And so, I’ve been working on a technique known as Fast Pull for a few years now, which is a passive and implicit measure of cognitive function.

Dr Amanda Heslegrave:

Okay. No, that’s perfect. Because we’re going to come onto that in a bit more detail very soon. But first of all, I guess, we’ve been talking about biomarkers. I need to set the scene really for why this is important. Now, in previous times, even now, if people have problems or worries, suspicions that they might be getting some kind of dementia or Alzheimer’s disease, normally they’ll see their GP. Or perhaps they’ll try and ignore it, because we all know that actually there are still currently no really tried and tested cures for the disease. So there’s always been a bit of a stigma with being diagnosed with dementia, and people are quite worried about that. So the person finally decides they’re going to go to their GP and then they will get, hopefully, passed on to a secondary medical care like a neurologist or a psychiatrist, for further tests.

And these tests, they might be brain scans, they might be cognitive testing, or they could be something like a lumbar puncture. We do use lumbar punctures to look for biomarkers of Alzheimer’s disease. But this, very much, I think, depends probably on where you live and the access to healthcare. It’s not always equitable. But also the diagnosis isn’t that accurate. It doesn’t, for example, diagnose between different types of dementia. That’s not something that’s readily done or easily done.

And also, by the time someone actually goes to their care provider with symptoms of a neurodegenerative disease such as a dementia, they’ve already got that disease, and it’s not likely that you’ll be able to have much effect on its progression. So what we need are different biomarkers, earlier biomarkers, and more accurate biomarkers able to differentiate between the different dementias. I think that that’s really important. And so, we need lots of people coming at this from many different angles. And I think that a small example of that is what we’ve got here today. And so, I think now we’ll move to Catherine, who’s going to tell us a bit more in detail about your research, and how this fits in.

Dr Catherine Bornbaum:

Sure. Thank you. So the work that’s being done by RetiSpec to bring this type of technology to the market, and by that I mean our retinol scan for detection of early Alzheimer’s disease, is actually technology that has a deep history of development that started more than a decade ago at the Center for Drug Design at the University of Minnesota. And so, the researchers there, Dr. Robert Vince and Swati More, developed an earlier version of this retinal hyperspectral imaging, which is what we use. And this was to measure early changes in soluble amyloid, for an amyloid target therapeutic that they were actually trying to develop. So they were trying to see if there were ways that they could measure the change of the therapeutic. And they invented this approach, for diagnostic purposes, out of necessity for evaluating their therapeutic. And so at RetiSpec, we licensed that initial technology, and have gone on to further develop it and incorporate the machine learning and artificial intelligence methodologies as well.

And so what we essentially do is, combine retinal imaging with novel tissue spectroscopy methods, in order to identify the optical signature of Alzheimer’s disease. And these are the specific changes that are measurable through the eye. And so, because the eye can be imaged at micron level resolution, our hyperspectral imaging enables measurement of many biophysical, biochemical properties such as specific proteins, so things like amyloid and tau. We can see signatures of cell degeneration, microvascular changes, and other spectral and spatial biomarkers of the eye, that we can see in individuals who have been confirmed to have the pathologic signs of Alzheimer’s disease. So we compare these against clinical gold standards of amyloid PET or CSF, or cerebral spinal fluid. And we use these gold standards to ensure that when we’re validating this technology, we can have a high degree of confidence that what we’re detecting is sound.

And what we do through this analysis is, we really take these incredibly rich images and we apply our machine learning and AI driven techniques to classify the raw data that we capture into broad categories. And so these are then used to perform the detection of the specific retinal biomarkers. So in essence, from a patient perspective, you come into an eye clinic or a clinic where this; it’s called a fundus camera, is, you sit down, you have a couple images of your eye taken, similar to what you would have in your eye doctor’s office. But what’s different is that we have software that’s working in the backend to capture this additional data. We replace the normal sensor in a fundus camera.

So normally you would have three color channels, red, green, and blue, and we capture those plus over a hundred additional channels. So the patient experience isn’t any different, but we capture this extra information, and apply the software that allows us to compute a score and to indicate whether or not that person is likely to have the same sort of protein composition as someone who has Alzheimer’s disease. And the reason we’re able to do this is because the retina, which is the back of the eye, is directly connected to the central nervous system and shares nervous tissues and vasculature with the brain. So it’s a really wonderful way to be able to understand what’s happening in the brain, in a very non-invasive and simple way.

Dr Amanda Heslegrave:

Okay. So that gives me a question. The first one would be, is this something that is already in the; you call it eye doctor offices, I would say opticians, but would it be something that they already have today? Be there?

Dr Catherine Bornbaum:

Yeah, that’s a great question. So, the cameras that we use, the fundus cameras, yes, absolutely. What’s different about what we do is there’s a different sensor, so the hyperspectral sensor. So we work with a wonderful company called Topcon, and they have a very, very significant footprint in optician clinics, eye doctor clinics. Here in Canada, we have optometrists and ophthalmologists. And so we’re able to leverage that existing footprint. So doctors don’t necessarily have to buy a whole new camera, we just add on our [inaudible 00:10:15] and software.

Dr Amanda Heslegrave:

And then does this technology allow you to pick up an Alzheimer’s signature before anything else? Or would you suddenly pick up this on someone, and then have to tell them?

Dr Catherine Bornbaum:

There’s great, great questions there. So, I’ll answer the first one first and then we can chat about disclosure in just a moment. So relative to the early detection, yes. So we have completed some work just very recently that was supported by the Alzheimer’s Drug Discovery Foundation. And we were looking at whether or not we could detect the signature of the proteins of Alzheimer’s disease were specific to amyloid, prior to symptom onset. And we both, in clinical validation, and in tissue samples of matched retina and brain tissues from those throughout the continuum of the disease. And I’m very pleased to say that yes, we were able to detect it before symptom onset in both instances. So it does have very promising capabilities for future screening purposes on a wide scale. And you asked a very important question also about disclosure. And what does this mean if we’re detecting this in eyecare settings where folks don’t normally have complex brain health discussions?

And so that’s something that we’re exploring right now through another project that’s supported by the Davos Alzheimer’s Collaborative, where we actually have a system deployed here in Toronto at an optometry clinic. And essentially folks who are 65 and older, which is the age here in Canada where routine screening is recommended and covered by the government, when folks come in, they’re asked an extra screening question during the history taking process about whether they’ve noticed significant changes in their memory. And if so, then they’re invited to have a scan. So we’re actually testing this in the real world, in eyecare settings. For now, we’re not having the optometrist provide the results, but we are referring to primary care for that discussion. And so we’re not trying to completely disrupt, but we are using it as a way to facilitate the measurement. And then the conversations happen with someone’s general practitioner afterwards.

Dr Amanda Heslegrave:

I suppose when you ask that question, this is just me and a bug bear I have, about significant memory problems. That’s too late, isn’t it? In my opinion, which is already too late. But that’s unimportant. That’s what makes, I think, the neurodegenerative diseases so difficult, is that they’re there, and then you can’t do anything about them. So I guess what will make it easier is when drugs like Lecanemab are proved to be useful and safe, and you can take them from a younger age. That would be the key. Sorry, I realize I’ve like hijacked that with my ideas. And I feel like we need to bring George in now, so he can explain a bit about his technology and how that would make things different.

Dr George Stothart:

Can I just ask Catherine a question first? So, if there’s a cascade, or a definite process of amyloid accumulation through the brain, it doesn’t arrive equally across the brain on any particular day, right? We have areas of the brain unknown to aggregate amyloid early. Where does the [inaudible 00:14:06] in that process?

Dr Catherine Bornbaum:

No, it’s a great question. And so, what we’re seeing, at least from the results of the work that was supported by the Alzheimer’s Drug Discovery Foundation, is that we see an increase in the soluble amyloid up to the; I’ll call it intermediate stage, of what we would see in brain amyloid aggregation. So, it’s certainly in the earlier to mid-phases of that buildup. And that also is likely because we’re looking into the soluble versus the plaques. Yeah.

Dr George Stothart:

Okay. Is it as good at detecting tau and other markers as well? Or is it better at picking up amyloid?

Dr Catherine Bornbaum:

That’s a great question. So, we don’t have the results public yet, but our team has been working very, very diligently on both total tau and phosphoryl-related tau comparators. And while I can’t share the sensitivity and specificity, though I do know them, they’re very, very promising. So I will say amyloid is certainly not a catchall, it’s not the only measure we need. What we’re building towards is even beyond amyloid and tau, looking at things like TDP and other types of markers that we know are important in neurodegenerative diseases. And we’re looking to really develop a single user experience, where we can provide a profile of scores for each of these markers. So certainly not limited to amyloid. And the hyperspectral retinal imaging is really quiet a powerful tool for elucidating optical signatures of various proteins and underlying biological processes within the eye, which give us an indication of what’s happening in the brain.

Dr Amanda Heslegrave:

That could be amazing for differentiation, if that could work for things like TDP, that could be-

Dr Catherine Bornbaum:

That’s our goal. So far, the evidence is indicating that we may have some promising options here. We’re starting with amyloid, but that’s certainly what we’re looking towards in the future.

Dr Amanda Heslegrave:

Okay. So now, George, you can’t get away with it any longer. You have to tell us about your research.

Dr George Stothart:

Yeah, that’s one thing researchers’ always very good at, right, talking about their own research. Yeah. So, as I said at the top, I’m psychologist. I’m within psychology. I specialize in cognitive neuroscience side of psychology, and I spent my PhD using EEG to try and look at non-memory-related signatures of dementia. So my supervisor at the time was looking at vision and visual attention. And so I was trained to use EEG in traditional ways, things like event related potentials. These are measures that we can take, and they reflect the brain’s responses to particular stimuli and events in time. And I spent four or five years testing dementia patients with these techniques to try and see whether EEG could be a more sensitive marker of certain cognitive deficits than; and it’s always weird comparing to something else, more sensitive than pen and paper tests.

So, our traditional neuropsych measures of cognitive function. And I learned a lot and hit a lot of barriers. And by the time I finished my PhD, I couldn’t see the way in which I’d been trained to use EEG ever translating through to being a clinical tool. The sensitivity of these measures was just, it was never there. And while you could learn interesting things about groups of patients versus controls, for example, the reliability of these measures on an individual subject level were always terrible. You always had to record for up to an hour worth of stimulation. You then had to go through lots of reductive averaging processes, and so on. So, there’s lots in the signal processing that just didn’t really add up. And I’m not a great theorist. I’m not smart enough to be that type of academic.

I always wanted to translate what more intelligent people than me discovered, into viable clinical tools. And that’s definitely what I got sense of in my PhD. I saw this huge gap between the way we used EEG in the lab, and with the way it was being used in hospitals. So, the way EEG is used diagnostically, doesn’t look an awful lot different from the 1970s, I don’t think, in most neurology clinics at the moment. There is this massive chasm between experimental EEG and clinical EEG. So I saw that as a gap. And I finished my PhD thinking, “Well, there’s all these barriers to conventional approaches.” And so I spent a few years as a postdoc trying different ways, different techniques. And then in 2015, I went to a conference in [inaudible 00:19:38], and a very, end of the day, poorly attended poster session. I came across this poster by an academic, a French or Belgium academic, called Bruno Rossion.

And he was presenting this technique called Fast Periodic Visual Stimulation. And it was a way of using EEG, and specifically a way of presenting stimuli with EEG, that seemed to solve all of the problems that I’d been hitting in the lab. And what these fast periodic visual stimulation experiments had shown, was that if you presented stimuli in a very specific way; so a fixed periodic rates of flashing images of stimuli, and you embedded rare novel images or different images, within that stimulus training, and recorded EEG at the same time, using that technique and working purely in the frequency domain as opposed to the time domain, so it’s a technical difference in the way you’re using the EEG data, but it made a fundamental difference to how quickly you could get reliable measures. He was claiming that using this technique, you could get significantly stable responses from individual subjects in minutes, in completely passive tasks, that reflected, in his case, it was reflecting face processing.

That was the particular cognitive function that he was working on. So to me, as an experimental EEG person, this was a method that could give us a measure of how well a brain was doing a task. But it could do it quickly, it could do it passively, and it could do it with all the signal to [inaudible 00:21:24] ratio benefits that you would need, if you were ever going to use something like that in clinic. So that really caught my attention, but at the time it was, he had about two or three papers and they were all on face processing. Now, face processing isn’t really a cognitive function that drops off too badly in dementia. So it’s a neat tool, but it’s not right for dementia. That’s not a cognitive function we need to measure, in the early stages. So I came back to the UK from that conference and thought, can I adapt this to measure any cognitive function that might be useful for dementia?

And so that’s what I’ve spent… Since 2015, that’s what I’ve been doing. So, I started small, I started with semantic memory, and I’ve built up over time, a battery of tests that all use the same approach, but to measure different cognitive functions. And my ultimate end goal is an equivalent battery that covers the same cognitive bases as something like the Mini Mental State Exam or the Adam Brooks Cognitive Exam, these general capsule cognitive neuropsych exams. But that we could do in minutes, and passively. And so the most success I’ve had, or the thing that’s probably the most developed, is a recognition memory version of this task, called Fastball. And the way Fastball works is, you see up to eight images presented on screen. You don’t do anything, you simply watch the images. And then they are embedded in an image stream that subsequently appears, where lots of images flash up very quickly on screen, nearly all of them you haven’t seen before, but occasionally these previously seen images pop up.

And hopefully, if your medial temporal lobe is working as it should, you’ll get a little recognition flash to those images. Your brain will implicitly, quickly go, “I’ve seen that before.” And it’s that function that drops out in early Alzheimer’s disease. And so what we’ve been able to show is, using that technique, in two minutes, in a completely passive task where the subject gets no task construction, provides no response, either behaviorally or verbally, we can measure their recognition memory. And we’ve shown this response drops right out in Alzheimer’s disease patients, and more recently in mild cognitive impairment patients as well. So yeah, so that’s the core of it.

Dr Amanda Heslegrave:

With that recognition one, do you think that you could define an AD and a MCI, you’ve got a clear enough cut off to do that?

Dr George Stothart:

We can, with our current Alzheimer’s disease data, and there is small sample sizes, so there’s a heavy caveat on it. But with our pilot Alzheimer’s data, comparing Alzheimer’s patients versus controls, we can get a classification accuracy of 92% using that recognition.

Dr Amanda Heslegrave:

Okay. And how long does it take to put the head on? You know what I mean.

Dr George Stothart:

Depends how fancy your EEG equipment is? And so, there’s a really broad range these days. When I did my PhD, there wasn’t. There was lab-based EEG, very expensive to buy, took a long time to put on, got great data, but was not a easily usable tool. In the last 10 years, the more mobile, simpler systems have come through, and we are on the verge now of really wearable EEG. That’s where a lot of the product development, and a lot of companies are moving towards, is really simple, low level wearable EEG that you could pop in your ear or wear on a headband. So really low profile you can wear while you sleep or whatever. So there’s a real range, and if you use one of those low-burden simple headsets, it is minutes.

Dr Amanda Heslegrave:

And so I know that you are kicking off this study in a few weeks. I know this, because I’m going to come. Can we try it out when we come? Will you have it there?

Dr George Stothart:

Yeah. So, what you are talking about is, well, the contracts aren’t signed yet. I can’t actually say who’s funding it, and who’s involved, but that’s okay. I can say something’s going to happen.

Dr Amanda Heslegrave:

Okay.

Dr George Stothart:

So yeah, we’re on the cusp of starting a really large-scale clinical validation of Fastball using exactly one of these low burden, easy to use headsets. Yeah.

Dr Amanda Heslegrave:

That’s great. So, you’ve got the recognition here. There are going to be other aspects. Cognition that you’re developing tests for at the moment, I guess.

Dr George Stothart:

Yeah, absolutely. So, it’s very well set up, obviously, to measure vision and visual attention. So those are two bases that we’re trying to cover quite comprehensively, because there are also a lot of use for other neurological diseases as well. So there could be opportunities to use those in other degenerative disorders. Memory, language, vision, and attention. We have versions of the task for. The only one that is not very well suited to, is anything that requires, what psychologists call executive function. And so that means doing a task, so remembering instructions, or providing a response, or decision-making. Because the nature of the task means stimuli have to be presented very quickly, multiple images per second. And so, you don’t have the time in that to discriminate, say between two stimuli, or decide on the new stimuli.

Dr Amanda Heslegrave:

Okay. So this is something that would work alongside other tests, but potentially making those tests quicker and easier. Because I know that cognitive testing can be quite lengthy, or that the people I know who do research, call them in for a whole day of tests and it sounds like-

Dr George Stothart:

Yeah, absolutely. Yeah, it does take a long time. I don’t anticipate this ever being… I think it’s very unlikely that any biomarker will be the silver bullet and there will just be one. It will be a combination of the best things that make it through this, the next 10 years’ worth of research and development. But my hope for this is that it could, to some extent, replace lengthy neuropsychological testing in situations and environments where you don’t have the time or resources to do it. And because it requires no comprehension of the task or response, it means it’s completely independent. No language, education, and culture. That could be really useful. So, if you wanted to test in countries with less well-funded healthcare systems, EEG is cheap. And you could use this test equitably across populations, in theory. Haven’t tested that yet. But in theory.

Dr Amanda Heslegrave:

How easy is it to interpret the results from it? Or do you need to be, I don’t know, what do you need to be, to interpret the results?

Dr George Stothart:

You need to be a neurophysiologist really, to take the raw data. But what we hope to do in the project that’s coming up, by working with a tech company that does a similar thing to what Catherine’s company do, is put a lot of smart processing and AI behind the tech, so that you remove the need for someone like me in the room. And instead, you just provide a clinician or a healthcare technician with a score.

Dr Amanda Heslegrave:

Oh. So, I feel like I’m the only person here who’s not using AI or out to…

Dr George Stothart:

Well, I don’t know the first thing about me. Again, people cleverer than me do.

Dr Amanda Heslegrave:

I feel I might become defunct soon, except that you guys all keep asking us to come and validate your work. So, we’re okay for a while. You’re Not just going to take my job away immediately. Yeah?

Dr Catherine Bornbaum:

No, no, no.

Dr Amanda Heslegrave:

Yeah. Okay. So that was all really, really interesting and it’s good to hear about the different strands that go up to make all of what we do good. But I suppose we should now ask just a few nice questions such as, what inspired you to the work in the dementia field that you do? Catherine, first.

Dr Catherine Bornbaum:

Thank you. So, on a personal level, I really appreciate a very complex problem, just it’s what drove me as a scientist back when I focused exclusively on that. And it still motivates me here. I do have some personal connections with loved ones, so I’ve seen what the disease can look like. And even I’m seeing people that seem younger and younger, and maybe that’s just because I’m getting older and older, but the number of folks that I know and love that are impacted by this disease, both with a diagnosis and as a caregiver, it really motivates me to wake up every day, very early, start very long days, and remain focused on bringing accessible, scalable, accurate, easy diagnostics to the market. And to support other champions who are working on therapeutics. So, it’s deeply personal for me.

Dr Amanda Heslegrave:

Okay. Thank you very much. And George?

Dr George Stothart:

Yeah, I think initially my inspiration were my two PhD supervisors. So, I didn’t come to them with a predisposition to what to work in dementia. It was my supervisor, a lady called Andrea Tales, who’s now professor in Swanzi, and she was just explaining her EG work with Alzheimer’s patients, and it seemed fascinating. I was always interested in biological psychology and neurodegenerative disease, and that just seemed like a really worthwhile thing to be spending my working time on. And the other supervisor was a lady called Dr Nina Kazanina, who taught me how to use EG and is just incredibly smart. And very lucky with my two supervisors, they really inspired me, but then as I spent more time in the dementia research field, it just reinforced that desire to keep working in here. And then as time progresses, nearly everybody, eventually someone in your family develops it.

So yeah, I’ve seen close family members develop and die from different forms of dementia and that certainly motivates you, but so does working face to face with patients as well. The one upside to working with what can be a very devastating disease is, you do see, or I certainly saw some very, very heartwarming size of human partnerships, I suppose. So whenever I would test people, they would nearly always come with their partners. And you would see, for somebody who had real short-term memory problems and would repeat themselves endlessly and get stuck in verbal repetition loops, ask the same question 30 times in five minutes, you would see their partners demonstrate just the patience of saints. And that was really, really lovely to see. You see these couples that have been together for 50, 60 years and the patients and the tolerance they have, they never lost their temper. There was never a cross word. They always just answered the same question again, even though they’ve just been asked it 29 times previously.

Dr Amanda Heslegrave:

Oh, I think sometimes actually, I like to remember that the samples that we get are from people, because sometimes it is a step away from it. And so, whenever I go to a conference and there’s a real life; so someone will come in who is living with dementia and speak, it’s always like, “Yep, yep. That’s why we do what we do. That is why we’re here.” So, it’s-

Dr George Stothart:

Absolutely. Otherwise, it would just become acronyms, isn’t it? It’s AD and RB and-

Dr Amanda Heslegrave:

Yeah, AD, CSF, and yeah, exactly. Well, I just want you to just consider the ECRs, or Early Career Researchers, who are listening to this podcast and what advice would you give to them? Very brief piece of advice, you’d go into them if they were coming into the field today? Catherine, first.

Dr Catherine Bornbaum:

Sure. That’s a great question. So, I think a few things, perhaps. So first, to identify a problem that you feel very strongly that there’s a solution there for. And by that, whether it’s a specific protein or a mechanism or an implementation challenge, whatever your area of expertise is, to really target that problem. And also to ensure that you’re working with great mentors who can advise you, give you feedback on your grant proposals, things like that. People who’ve been very successful in hitting the milestones that are important for an early career researcher.

I think it’s also really important, aside from the sort of academic or the scientific focus, to make sure that you maintain a part of your life that is separate from your work. I think it can be very all-consuming at times, especially in those early career years where you might be working towards tenure, or really ambitious aims, or trying to carve out your first big projects that you’re running independently. It is important to make some time for life in there as well, whether it be with family or friends or just something for yourself. I think a lot of early career researchers can get lost in that. So trying to target something specific that’s just yours, above and beyond. So hopefully that’s helpful.

Dr Amanda Heslegrave:

Oh no. And especially the bit about work-life balance. Honestly, some people really do need to hear that. Look after themselves. And George, your advice?

Dr George Stothart:

Yeah. Well, just to continue the work-life balance theme. I always got, especially as a PhD student, I often saw an example of reinforcing attitudes that academia required total and absolute dedication. That if you weren’t working weekends and evenings, you weren’t doing it right. That’s rubbish, and it’s just not true. And don’t get drawn down that path, because it’s not healthy, it’s not productive, and it’s not needed. I think if you are organized enough with your time, it shouldn’t be this life consuming career. It doesn’t have to be at all. And Catherine’s absolutely right to make sure that work-life balance is maintained. I think, just for my field, just for ECRs and cognitive neuroscience, I think you’re lucky, because I think the employment opportunities you have in 10 years’ time or five years’ time are going to be very different and broader perhaps than when I finished my PhD.

I think the role of industry and health technology companies in employing PhD students and furthering research, I’ve seen that really start to explode in cognitive neuroscience. And I don’t think that was really there 10 years ago, or it was just starting. And I find that exciting. I like that. I think it’s good that you can potentially finish your PhD and have a range of different places to go and work. And you don’t have to just stay in academia necessarily if you want an exciting career in research.

Dr Amanda Heslegrave:

Yeah. Okay. Well, this has been a really interesting conversation, but I think we’re going to start to wrap it up now. But I need to say, if anyone’s watching or listening, and they feel like they would like to host a podcast in whatever area of neuroscience they want, then that’s fine. Or dementia that they want, that’s fine. Or if they want to be a guest. So please contact dementia researcher. Also, I’m looking here, there’s also plans for a new series where mentees interview their very inspiring mentors. And so, if that’s something that you’d want to be involved with, have a think about whose inspired you or who continues to inspire you, and who would agree, obviously, to be interviewed by you as well. That’s got to happen. So yes, in the meantime, I’d like to thank both my guests, Catherine Bornbaum and George Stothart, who’ve been absolutely amazing. And it’s been really, really fun to hear about your research, and I’ve really enjoyed hosting today. So, thank you very much.

Dr George Stothart:

Cheers. Thank you, Amanda.

Dr Catherine Bornbaum:

Thank you.

Dr Amanda Heslegrave:

I’m Amanda Heslegrave and you’ve been listening to the Dementia Research Podcast. Please remember, leave us a review and let us know what you thought about the show. Thank you.

Voice Over:

Brought to you by dementiaresearcher.nihr.ac.uk, in association with Alzheimer’s Research UK, Alzheimer’s Society, Race Against Dementia, and the Alzheimer’s Association. Bringing you research, news, career tips, and support.

END


Like what you hear? Please review, like, and share our podcast – and don’t forget to subscribe to ensure you never miss an episode.

If you would like to share your own experiences or discuss your research in a blog or on a podcast, drop us a line to dementiaresearcher@ucl.ac.uk or find us on twitter @dem_researcher

You can find our podcast in your favourite podcast app – our narrated blogs are now also available as a podcast.

This podcast is brought to you by University College London / UCLH NIHR Biomedical Research Centre in association with Alzheimer’s Association, Alzheimer’s Research UK, Alzheimer’s Society and Race Against Dementia who we thank for their ongoing support.

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