In this post, I will be expanding the scope of the topics raised in my earlier posts, and start thinking about the intersection of the research lab and the clinic (translational research). This is a topic that I would like to explore more in the future posts. Even though clinic can seem like the other end of the spectrum compared to theory, I find that both these spaces interact with experimental (basic) research in similar ways. Beyond just driving experimental questions, theory and clinic both provide a testbed for empirical findings – providing constraints to help refine our interpretations, validating our assumptions, and most of all, both of these can reveal connections between phenomenon that may not have been obvious. Especially with translational research, this is an opportunity for us to test our models and theories (of the brain) in the wild, so to speak. Studying the breakdown of any component of the nervous system in the clinic shows us a complete manifestation of what really happens when something goes awry in the brain. History of neuroscience has many such examples where we learned something deeply fundamental about the brain from observations in the clinic; famous examples include Phineas Gage, Broca’s area, Patient HM, etc. In this way, damage and disorders of the nervous system can be a very informative guide to be help connect behaviour and cognition to brain. From an article Computational neuroscience at the NIH from the National Institutes of Health, USA (NIH) - “Disorders of the nervous system are associated with diverse and complex neurobiological changes leading to profound alterations at all levels of organization… The NIH is committed to fostering the training of a new generation of basic, behavioral and clinical scientists who will bring tools and techniques from multiple disciplines to acquire new knowledge that will help prevent, detect, diagnose and treat disease and disability.” (Computational neuroscience at the NIH).
For the first post in this vein, I talk to Jasleen Jolly, who I met at a summer school this June, at the Cold Spring Harbor Laboratory summer course on Vision. Jasleen brought her clinical expertise and scientists’ mind to several of the discussions at the summer school, which really demonstrated how deeply and fundamentally she thinks about what she sees in the clinic (and learns in the class). Jasleen is an optometrist by training and has clinical experience of over 16 years and has worked with patients in several different countries, including the UK, New Zealand and Australia. She is still actively involved at the clinical end at Oxford in mainly retinal gene therapy and low vision research. At Oxford, she is also currently a doctoral fellow working with Prof Holly Bridge and Prof Robert MacLaren on her thesis titled “Development of novel tests to assess visual function in patients with inherited retinal degeneration.”
Here is a condensed and lightly edited version of my chat with Jasleen Jolly:
What are your motivations to combine your clinical background and pursue basic science research in understanding visual perception? You have mentioned that your goals are to go beyond just improving clinical outcomes, and that by understanding these disorders in the framework of visual perception could give us new insights into the disorders.
I have worked for 16 years in low vision rehabilitation. We see patients in the clinic once they’ve already lost their vision, and we’re trying to help them make the most of what they’ve got left and use it in an optimized way. From my experience over the years, talking to all these patients, I came to the realization that there’s a lot of variability in how patients react to vision loss. Part of that might be psychological, but I also feel like there’s something deeper going on there. So that’s where my interest of understanding what’s actually happening at the brain level really comes from. If you’re getting abnormal input from disease mechanisms into the brain, then surely there must be downstream changes. If we can understand those changes, then we can actually do something about it. Right now, on the clinical side, I work in the research team at Oxford that is assessing the gene therapy patients where we’re replacing a defective gene in the retina in order to protect patients from going blind, and protect them from any further vision loss. Even here, we see a diversity of outcomes: some patients improve, some patients stay stable, I would say that most patients stay stable, and then a couple continue to decline. Part of that variance can be explained by what’s happening at the level of the retina, but it can’t be explained entirely. So that’s why I got involved in the MRI work because I started thinking, well, does that mean that the way the brain is using that abnormal input is now changing in a way that may not be consistent across patients. If we can understand what’s going on downstream, maybe we can develop exercises (for rehabilitation) or somehow treat those downstream changes. Maybe then can we actually increase the potential visual outcome on retinal therapy. So that is the question that I’m kind of trying to answer at the moment.
In the MRI project, I’m doing retinal imaging and measuring various aspects of visual functions. These include mapping the visual field, measuring color vision, contrast sensitivity, visual acuity, and then obtaining five different types of MRI of the visual brain. These are T1 structural, MRSI which is a spectroscopy, PRF mapping using fMRI, so that’s mapping the visual field, then we are doing diffusion weighted imaging and resting state as well. We’re hoping to follow up with the patients after two years again so we can try to zero in on the changes. In the gene therapy patients, for the phase one trial, we gathered several visual measures at a coarse level. For the later stage at the phase two trial, I’m doing a lot of more fine detailed visual function measurements in those patients, and we’re also doing electrophysiology as well as retinal imaging, and we’re also doing adaptive optics. All those measures are being repeated one and two years after treatment across the “control” eye and the treated eye, which we can now directly compare and really try and hone in on what the therapy is doing at a cellular level.
Can you speak to your experience pursuing interdisciplinary research – your work sits at the intersection of translational approaches, clinical outcomes, and seeing patients? It is not always clear on the best ways to bridge between basic science and clinical work. I think you also might have an insight into how people within these different sectors think differently, and share some lessons you’ve learned from this interdisciplinary research process.
Working at that intersection is actually quite interesting - so I have different challenges in my work and I don’t think that’s always appreciated by people in basic science. I have to balance how much we put our patients through, what the regulatory authorities will accept, as well as how robust my work is. So sometimes I want to be more scientifically rigorous in the work that I’m doing specifically, but it’s very challenging to do that. It is hard to push work such that it can first and foremost provide data that the patients need to get approval for treatments or in a way that the clinicians can understand. There have been times when I present at clinical conferences and I’ve been told that I’m too scientific; and then at more scientific meetings, I’ve basically been told that I’m too clinical. So, it’s quite challenging to strike that balance. And I think this is why we need better communication to understand each other better. With the retinal side of things, I’m quite lucky that I work in a team that is multidisciplinary and I see the therapies being developed in the lab and then I work with the clinical team who have different skills and expertise to take them forward into first in human clinical trials. Through exposure to this integrated approach, I’m seeing the challenges they’re facing, they’re seeing the challenges I face when we get to the other end. We can actually now start planning ahead, for when the therapy gets to clinical trials, which means that our measurements are more effective, because you can have the best therapy in the world, but unless you can prove that it’s pointless. I have personally found that having a more integrated approach is really helpful because I have a better understanding of what’s happening at a cellular level.
Another big thought I have on this comes from my career trajectory which has been multidisciplinary for the most part. I’m an optometrist by working on an ophthalmology team, and a lot of my team members also work in labs doing basic science. Now I’m also working in a neuroscience research team, so I have always followed a very multidisciplinary path. One of the things I have noticed is that there’s a very core connection between the work done across these diverse areas that are very relevant, but they’re not being connected by the right people. So for example, today I was working on my very first neuroscience paper, which was exciting, but as I was doing my literature search, I realized that there’s a lot of really interesting work out there, but none of the clinicians know about it because it’s all in neuroscience journals, presented to and for other neuroscientists. It goes in the other direction too, not enough clinicians talking to scientists, whether it’s neuroscience or other fields. Because of that, we’re not making those connections that we need to. And even within the clinical professions, like the optometrist and the ophthalmologist are not necessarily talking to each other. Even though we could help each other out and there’s a lot of overlap in what we do. Not just overlap, but it’s very synergistic what we do, but it doesn’t seem to be that way in the clinical practice. I think that that’s my biggest observation from my random career that the connections aren’t being made. That got emphasized to me at Cold Springs Harbor (Vision: A Platform for Linking Circuits, Behavior & Perception) because there was all this amazing work. But again, there was such a disconnect between those in, in the clinical world versus those doing basic science.
I would love for a space where the basic scientists and the clinician sit down and go, hey, here are the questions we want to have answered. Here’s what we want to explore. How can we work together to use both experimental models and patient populations to answer these questions? What can we do that will complement each other?
One of my inspirations to pursue this blog is a podcast titled Song Exploder – “where musicians take apart their songs, and piece by piece, tell the story of how they were made.” In a similar manner, can you talk a little about your experience working at this interdisciplinary interface and collaborating with visual neuroscientists?
First and foremost, I think for me it’s the patients – they keep me going. Especially in the gene therapy projects that I am working on; patients’ future is changing drastically as these conditions have no treatment and they are guaranteed to go blind and there’s nothing that can be done about it. So, when they come back and tell you that “You’re giving me so much hope. If I don’t go blind in the future, it means that I can plan for my future and can see my children growing up and things like that”, it feels amazing. I think that’s what gives me my passion because I want to do the right thing by them
In terms of the actual research process, my first starting point is again, always the patient. Based on my observations, the things that patients tell me, I might notice they have difficulties or they’ve reported this thing, if about two or three of them have said that same thing, then I start thinking, well, what’s happening on a molecular level to cause that change and what can I do to investigate this further? The second place where I find questions is through large scale patient engagement, in the UK there is a big emphasis on patient public involvement. I’ve organized formal gatherings of our patients so that they can provide feedback to me on what they find difficult, what they found easy, what they would like us to investigate. What am I missing from that perspective? What is important? I also talk to a lot of ophthalmologists, doctors, surgeons to get a better understanding of what their questions are, what is it that they would find valuable? Then I can put all of this together. Beyond that, I also look at a lot of the rules and regulations that are published around the clinical trials from the Food and Drug Administration from NICE which governs the funding in the UK and organizations like that. In this way, I am always talking to colleagues across the world and keeping a lookout for what’s being done, where are the gaps? Can I fill the gap somewhere? Do I need to form a collaboration with someone to try and fill those gaps? Even though I’m involved in a wide variety of different projects, they’re all essentially on the theme of low vision, just tackling low vision from different aspects. And it’s only by putting those aspects together do I feel that one can really form a complete picture, which can then really shape patient care. So yeah, a lot of it is about listening to the patients i.e. listening to the end users, and then also the doctors, and the optometrists who are going to be using whatever I developed. If I don’t tackle those two audiences, I’m never going to be able to connect with them and get my research taken up in the clinic.
What are the big unknowns that you believe would shed light on understanding of the disorders you investigate?
Ah, there is so much that we need to understand – I think there’s a lot of disease processes that still aren’t well understood. A lot of basic science research is using normal models. I don’t think there are many labs that are using the techniques that can really get to grips with what’s actually happening in the disease mechanism, or if they are, they use very artificial animal models. I don’t know how translatable that is back to human beings, so I do think we need a much better understanding of the basic disease mechanisms and the impact they are having on the body at multiple different levels. AIso, once someone has a condition, I think there’s a big gap in trying to understand how individuals adapt to that and why some are different to others. We usually look at population level effects, but we’re now entering an era of individualized medicine, so we need to understand those individual differences much, much better.
Right. Do you have specific examples in mind when you talk about basic disease mechanisms that maybe someone reading the interview would think, oh, that’s actually interesting and I’d never thought about that before. And maybe there’s something I should think about when I think about future research options.
An example from Cold Spring Harbor that came up is the Charles Bonnet syndrome. A significant proportion of patients who are losing their vision report visual hallucinations, around 30-70% of the low vision population. We don’t know why some people experience these, whereas others don’t. We don’t know what’s really causing it. There are lots of theories. But since we don’t understand what’s causing it, there’s no treatment for this. We don’t understand why some people see pleasant stimuli and others see frightening images and you get everything else in between as well. I find that quite fascinating. When we were talking about feedback mechanisms in the brain, that seems to make sense that that might be the driving force, but how do we even investigate that? I don’t know. It’s also interesting that these patients who experience visual hallucinations are completely aware that these are hallucinations, which is different from other conditions where hallucinations might be a frequent occurrence (and patients are not aware of these experiences being hallucinations).
At a cognitive level, there’s also a high incidence of depression and anxiety in low vision patients, which I’m sure part of it is going to be the fact that your circumstances are changing. Again, not all patients experience this. So, we need to understand whether vision loss causes specific physical changes in the brain that increase the risk of depression?
I encountered this question that I found intriguing – “how do we know what we need to know”, and would like to hear your thoughts on. It was raised by an undergraduate while trying to determine what paths should they go on in their future research careers. The number of unknowns seem so high, and it’s not clear what manipulations are necessary and sufficient. What are your thoughts on this?
I don’t think it’s ever possible to know too much. I just don’t think that’s feasible, in fact the more you know, the more I think you learn that you don’t know. I don’t think that it’s ever possible to reach a stage where you know too much. The only way to know what do we need to know, I honestly think comes from specialists’ groups, these specialists’ symposia where you can get people together from different expertise and you can figure that out. I think we need to have these special groups that come together and actually have these discussions because without that, how do we know what we need to prioritize? Otherwise it’s just based on individual interests rather than a bigger picture. Usually what we want to know is either to advance the understanding of human beings or to improve the human condition. I tackle disease, so I have a vested interest in a second cause, literally my whole life has been about tackling disease, so I’m probably very biased in that respect.
What was your experience of attending the Vision course at CSHL?
CSHL was brilliant because it opened up a whole new world of basic science in neuroscience that I wasn’t really aware of, or really connected to before. I had so many questions and things in my work that didn’t make sense for me but suddenly made much more sense after the course. That’s what has made me realize how important it is to form these collaborations going forward and be more robust in the way I do things and try to look at things from multiple angles. I think CSHL has really given me that insight, and for a lot of the papers I’m writing at the moment, I have really changed my discussion because of CSHL. Even though I’m a clinician, it’s important not just to think in clinical terms, I need to start having a better understanding of what’s happening at a basic mechanism level. All the speakers at the course were amazing and inspirational, giving me more enthusiasm to move forward.
The big one was Charles-Bonnet, when one of the faculty (W. Marty Usrey) talked about feedback mechanisms, that’s when Charles Bonnet sprung into my head. Because I really do think there is something in there that would explain what’s going on in that condition. And the other one was Greg Field’s work that he was presenting on the bipolar cells and how they alter in different states. And that helped me make a lot more sense of some of the clinical measures I’m looking at because it’s helping me understand the driving mechanisms. I can’t give you any specifics yet because that’s still in the works and I’m still getting my head around it. But the work he presented gave me a starting point as to where I need to go and look. Whereas before I was just lost, and didn’t even know where to even look. Another was when Bevil Conway talked about was how color vision affects emotions. So, if you’ve then got abnormal color vision, does that mean it’s getting to change how you process your emotions? So much of our emotions is linked to visual stimuli. If you think of abnormalities in the input, how does that then change the processing of those visual stimuli? Our emotional states, our attentional states and so many other factors can alter and these are topics we have never even tried to touch on. Even in clinical work, we don’t talk about this side of things at all because it’s complicated and there’s nothing we can do about it anyway, so why go into it? But I think that that would be really interesting to explore further and there must be loads of other connections like that.
I read that some of your papers were also more methods oriented, like you were trying to improve the methods used for some of these outcome measures. Do you rely a lot on computational tools that have been super useful?
One domain in my work is related to color vision – we’ve been picking up early defects in the S-cone pathway. So now I’m trying to understand better what’s going on. Is that something that’s related to the disease mechanisms or is it just because there are fewer S-cones? So, I’m trying to extrapolate by incorporating a lot of other structural and functional data that we have from the eye to understand what might be happening there. The basic research has made me realize that the traditional clinical tests just aren’t sufficient to do the measurements we need to do. So, I’ve gone out and looked for commercially available kit and since to use in a clinical trial that has to be FDA approved, then I’m tweaking those test paradigms to provide best measures that are able to target what’s happening at a cellular level.
Another line of work that I’m doing at the moment is in trying to measure rod function, and it’s really, really challenging. Most of our tests are geared towards either just generic photoreceptor function, which is a combination of rods and cones, so they aren’t very specific. We haven’t really got much out there that’s rod specific. So I’ve got a lot of clinical measures, but I’m now trying to use previously reported histology and I’m trying to use models which incorporates photoreceptor density and ganglion cell, receptive field size to better understand what these measurements that I’ve got are, what are they actually driven by, where are they coming from and what are they actually telling me about these patients’ retinas. Overall, I am putting together a lot of different structural and functional measures, because I want to understand whether the changes I’m seeing are structural or functional. So, is it that the photoreceptors are dying or is it that they’re not dead but they’re not working properly? Since we can’t do any invasive work with human eyes, everything we do has to be extrapolated. So that’s where computational modeling approaches can be really useful.
How has your experience been in neuroscience as a young woman researcher? Do you think your opinions and concerns are given due respect in work meetings etc.? How about conferences or when you are attending workshops?
Yeah, so within my group when I first started there were only two women on the team and now, we are the majority. So, it’s definitely changed even in the eight years I’ve been in Oxford. Still, I think sometimes being a woman can be challenging, but there’s so much awareness now that I do feel it’s becoming easier to garner respect. Where I find that really challenging is when presenting at conferences and meetings because I look so young, I think a lot of people don’t realize the experience and the knowledge I have. So, it can be quite challenging to get taken seriously. And a lot of my invitations to speak have come from either people who I’ve directly worked with, so they know my work. Or people who have seen me present for many, many years. I do feel like I’ve had to work harder to get taken seriously and be given the same respect as maybe a man of the same age or maybe someone who looks older. So, definitely in the wider community, I feel it’s very, very challenging to get taken seriously. Especially because I also don’t like to dress up in heels and makeup and for some reason that seems to make a difference as well. I mean, in the media, when they talk about politicians, or celebrities, if you notice whenever they are commenting on women, it’s always about what she’s wearing and how she walks and how she carries herself. You don’t get the same comments about men and I feel, not always but quite often even within the clinical research community it’s exactly the same thing happening.
So, I’d never heard of the Charles Bonnet syndrome (CBS)! When Jasleen mentioned it at the summer school, most people there hadn’t heard of it either. The experience of visual hallucinations that can accompany vision loss was first described by Charles Bonnet in 1760, but there still seems to be very little understanding of its exact etiology beyond knowledge of co-occurrence usually with vision loss (mainly at the level of input), and low vision. Visual hallucinations in CBS are known to be quite diverse across patients, and also visually rich and detailed. Patients who experience visual hallucinations are generally aware of them, and can distinguish hallucinations from reality. A major driving factor might be the reduced visual input that occurs in these cases, leading to a sensory deprivation scenario. Thus, similar to the phantom limb syndrome, the brain might be filling in the blanks (due to lack of sensory input) in the form of visual hallucinations (The elephant in the room: understanding the pathogenesis of Charles Bonnet syndrome, Carpenter, Jolly, & Bridge 2019). Visual hallucinations in CBS are also distinct from hallucinations in other conditions (like schizophrenia) where the sensory input is usually not altered or sensory periphery undamaged. In the absence of external input, perhaps the brain is over-relying on its internal model. The idea of “Vision as Inference” is as old as Helmholtz (late 1800s). Thus, hallucinations in CBS seems to provide somewhat of a dissociation between externally driven (visual input) and internally driven (internal model) perception. It seems to me, then, we should be studying CBS more and understanding what’s really going on there! Not just at an abstract level, but really combining the details we are learning from the clinic at the behavioural, anatomical and physiological/functional level (using tools like EEG, fMRI).
My big take-away is that it seems that the current thoughts around low vision and vision loss are still rather simplified and paint an incomplete picture of the changes that might be occurring in the brain due to loss of sensory input (or abnormal input). We don’t know much about how chronically altered visual input affects emotional and attentional processing in these patients. Additionally, there doesn’t seem to be much focus on the high occurrence of depression and anxiety that accompanies low vision, although this co-occurrence is highly variable. Considering that more than 50% of the brain is devoted to processing visual information, I wonder if, or how much, these processes might alter over time in the absence of high-fidelity sensory inputs. Whether the computations and algorithms in the brain for processing visual information are affected? How does visual plasticity factor in (an area that’s highly unexplored, Jasleen tells me)? I’m excited to see what Jasleen finds out in her ongoing research looking at functional and structural brain data at different time points of disease progression!