Episode 30: Alison Barth, PhD

The following interview was conducted in-class, during the Spring 2024 session of Hidden Figures: Brain Science through Diversity, taught by Dr. Adema Ribic at the University of Virginia. What follows is an edited transcript of the interview, transcribed by Jack Patrick Curley, Chloe Wilson, Rina Patterson, Samantha Anne Finnegan, Lindsey Reagan Bruns, Meagan Heidi Alexus Best, Camille E Smith, Sarah Tomeh, Brooklyn Nicole Hawa, Lukash Rosato, Jacqueline Brigette Stinger, Michelle M Kang, Simran Darhele and Aidita Aida Sou, who also drafted Dr. Barth’s biography. The final editing was by Dr. Adema Ribic.

Dr. Alison Barth is a Maxwell H. and Gloria C. Connan Professor in the Life Sciences in the Department of Biological Sciences at Carnegie Mellon University in Pittsburgh, Pennsylvania. Dr. Barth received a bachelor of arts degree in biology from Brown University and later continued her studies at the University of California, Berkeley, where she earned her Ph.D. in Molecular and Cell Biology. She also conducted Post-Doctoral research in neurophysiology at Stanford University. She is the founder and principal investigator of Barth Lab, where the research focus is understanding how experience assembles and alters the properties of neural circus in the cerebral cortex, in both typical and disordered states.

Please tell us about where you are from!

I was born in Maryland, and I lived in Kansas for 7 years, Wisconsin for 2, and Ohio. I went to university on the East Coast, and then I did my graduate work on the West Coast.

How was your experience trying to become a professor?

One of the pivotal points in finding a permanent job was when I had a baby and it became really clear that it was difficult to have a young child and to be working as a postdoc. I applied for a couple of jobs at universities and industry, and the offers that I got helped me make that decision. I decided that I would go the route of Academia-I wanted to be my own boss and then the options that I had pushed me towards Academia. I've been very pleased to be at Carnegie Mellon and living in Pittsburgh.

Was there a pivotal moment in your life that made you want to pursue neuroscience?

While I was studying [at Berkeley and] living with a bunch of graduate students, a paper was released in the fall of 1991 discussing the anatomical differences in the brains of gay individuals versus straight individuals. I had never taken a neuroscience course, but I was fascinated by complex social questions and their underlying biology. At the same time, Hitoshi Sakano had a paper that provided evidence for somatic DNA recombination in the brain, and it totally captivated me. I wanted to study something revolutionary, and neuroscience seemed to be that. 

Did you have any mentors that influenced, or continue to influence, your journey in neuroscience?

Having people you respect and look up to is super important. Even though I'm a lot older now, I feel the lack of that very acutely. At some point when you get older, there aren’t many people who are that much older than you that you can look up to. Everybody else is retired or gone, so it's really important to find people whom you respect and admire when you can. When I was an undergrad, I had this really great summer research experience with somebody whom I cold-contacted by just sending a letter. She was an evolutionary biologist studying cell evolution, and she was just an incredible person. She took a chance in hiring somebody who randomly wrote her a letter. Although she said I might just end up answering the phones, I got there, and I really made the best of the situation and made myself indispensable. She was such an exciting and important thinker, and she just took me along with her to do things. She was really engaged in K-12 education. She was doing a workshop in Boston, western Massachusetts, Umass Amherst for teachers that engaged in classroom exercises for teaching genetics. This made a huge impression on me. I went back to my undergrad institution, and I started doing some of these activities with local elementary schools. I still work with students in elementary school, middle school and high school students. I find it really rewarding. So, she had a huge influence on me. Her name was Lynn Margolis. We actually ended up having a paper together about spirochetes, which is a type of bacteria, but the paper is not particularly influential. However, she herself made a big influence on me.

I read an interview article about your career and work that began by describing how you came to play the violin. They mention that this decision was influenced by both your children's interest in playing the instrument, but also a scientific interest relating to your own research in neuroplasticity. Could you speak a bit more on that? Do you still continue to play today?

I have to say I'm totally obsessed with the violin right now. My kids started taking music lessons when they were 5 or 7 years old or something. I would go with them every week, and I would take notes on their lessons, and I was so jealous that they got to do this. As they got older, they were less interested, but I became really interested. My research studies how synapses are changed upon electrical stimulation, but also in terms of experience or sensory manipulations. I started reading a lot about learning and how the brain was changing,  and I just really wanted to try... It's been a long road and I'm sure I learn much slower than my kids when they were younger, but it's been really exciting to see what is effective for me in being able to master these skills.

Could you explain in your own words what neuroplasticity means? Could you explain the difference between neuroplasticity and metaplasticity and how they relate? 

One of the really interesting things about the brain is that it is changing all the time. Everything you do is adjusting neural circuits in your brain.I think about this a lot when I'm practicing the violin. It's really important that when I'm learning something new, not just the violin, that I am doing it really intentionally and really precisely because just doing it starts to change my brain. What neuroplasticity means to me is that there are changes in behavior or perception that are manifested by changes in the properties of neurons. We study that at the level of synapses. Metaplasticity is a subset of neural plasticity, and that is the plasticity of plasticity mechanisms, which has really been very well described at the level of individual synapses. So you might change a synapse, and make it stronger, but the next time you go to that synapse and you want to change it, the rules are different. 

Could you give us a brief summary of what your lab does and what projects you are currently working on?

We're really interested in how experience changes the brain. I'm really interested in learning and memory. We have chosen the somatosensory cortex of rodents, and we look to see how synapses are being altered when the animal undergoes certain types of experiences. We have a tactile learning task in mice where we stimulate their whiskers, and then we give them a water reward to see how synapses are being altered. We're trying to figure out which specific networks are being altered as the animal is learning this association. Synapses are the key part of how experiences drive learning. Essentially, what we're trying to do is identify those synapses that are being altered by finding the specific input and the specific target cells, and that will tell us what parts of this neural circuit are important for making these learned associations.

As a researcher, what methodologies or techniques do you find most promising for studying neural plasticity and its implications for behavior and learning?

There's a lot of different ways to look at synapses. We can look at them through their activity. One of the things that I think is really exciting in neuroscience right now is that we have technologies where we can image the same cells in a living animal, and even the same synapses over time… I'm very enthusiastic about in vivo imaging and recording experiments to look at how brain activity is altered as animals are mastering some task... [In addition,] I'm really interested in quantitative anatomical techniques that show us quantitatively how synapses are changing… I think they're very democratic and we can get a lot of information from a lot of cells really quickly.

How do neural circuits and plasticity relate to learning, specifically for people with learning disabilities or for neurodivergent individuals?

We train mice with stimulus reward tasks and we found that they learn at different rates. We see very heterogeneous changes when looking at their brains. We've also performed experiments where we remove the cerebral cortex. Following the lesion, some mice seem to learn completely normal while others do not. What I think is happening is that animals have different strategies in which they learn. Most animals likely use one method, while some animals use another. If you get rid of one part of the brain in mice who learn using a certain method, they'll be pushed into using another strategy. Experiments involving animal learning are very informative because the ways in which their brains approach learning are very similar to how human brains learn. Brains probably select for one learning strategy simply because it works well for it. I think that those of us who learn differently, especially neurodivergent people, approach learning with a variety of strategies.

Can you share with us any insights or breakthroughs from your research that have challenged existing paradigms or opened up new avenues of inquiry?

One of the most important things that we've done in our lab is researching where the neurons that encode a memory are located. For a long time people thought that these neurons would be more active which would allow us to use activity-dependent gene expression. One thing we find in neurons is that when they are more active they turn on a specific set of genes. When I was a postdoc, I developed a transgenic mouse that would express a fluorescent reporter under the control of one of these activity-dependent genes. These mice have proven to be a very powerful research tool as they have been used by numerous labs and they are licensed by every major pharmaceutical company. They allowed us to record from these fluorescent cells to observe whether they were hyper-responsive. We were able to investigate if this is where synaptic changes are most concentrated, which we hypothesized was where the memory was stored. We learned that those fluorescent cells in the primary somatosensory cortex of the cerebral cortex are not where the memory lies. Synaptic changes are not concentrated in these cells. So one of our major assumptions about where we should be looking at was challenged by that study. This upended a lot of expectations that people had. More recently, we have been studying how different synaptic changes are distributed across the cortical area that represents the whiskers during learning. We're finding many interesting things about where these synaptic modifications are localized. This helps us understand and develop new hypotheses about the functionality of plasticity. 

Given your expertise in neural circuitry, could you speak to the potential implications of your research for understanding and treating neurological disorders such as Alzheimer's or Parkinson's disease?

One question for these neurological disorders that are associated with aging is, when do they really start? Particularly for Alzheimer's disease and for Parkinson's disease, it looks like they are progressive disorders and they may be initiated a decade or more before anybody even really knows that something's wrong. My lab is currently trying to study how synapses are reorganized at the very early stages of an Alzheimer's like disease in mice. We know that in Alzheimer's disease you have these plaques and tangles that are associated with neural death. We don't know if the plaques are the problem or something else is happening beforehand. One way people have studied this is to overexpress the constituent protein of those plaques and see if that does anything. What we've discovered is that very early on, like months and months before you see those Alzheimer's plaques, you actually see very significantly altered neural function and synapse distribution. Knowing that that gives us an idea of when we should intervene and how we might intervene to fix the system or to prevent progression.

What do you think about the intersection of neuroscience and computer science?

There's surprisingly little influence of neuroscience on AI, and that's mostly because AI is pretty good without knowing anything about neuroscience. I gave a lecture recently to undergrads and the title was: The Brain is not a computer. First of all, AI doesn't particularly think about neurons, and even deep learning networks are not really organized like the way that neurons are organized. So what's different about deep learning? And why aren't the AI people like, “come on neurobiologists, tell us what we should do better.” It's because they're already really good and super accurate. We can do a lot of things without knowing about the brain. Why should we know about the brain? One thing I pointed out in my lecture is that your brain is doing all of this with a thousand fold or lower energy expenditure. Initially, I did not fully realize what the difference was in energy. I'm not an engineer but it's incredible. I think the energy expenditures and cost of AI will become more clear, at which point AI will turn more to neuroscience to learn how to design more efficient systems.

How do you see these fields influencing each other in the coming years?

In my lab, a lot of people are using Chat GPT to write code for different analytical steps. It's not so reliable for writing scientific papers, but it might be useful for algorithms that might help you more rapidly analyze data. We use a lot of automated image analysis that takes advantage of advances in AI. There are also a lot of very sophisticated principal component analyses that we do using multiple variables to segregate different classes of cells and responses. 

What do you think about invasive procedures, like Neuralink implants, and how that impacts neuroscience?

Neuralink is an interesting idea, but one of the major problems in implanted devices is the very fact that they're implanted. They're invasive. I think none of you would want to have an implant in your brain if you didn't need one. I suppose there might be a world in which it's so advantageous to have that implant in your brain that you would have it done, but anything foreign in your brain is going to be a potential platform for infection, inflammation, and other long-term problems. So, that risk needs to be balanced with the benefit. 

How do you expect the field of neuroscience to change in the future?

We have been in this real revolution of data collection, and I think that we're gonna reach the limit of what having more data is going to do for us. I anticipate that over the next decade or so, we're going to be able to record everything. We are going to be able to record the activity of 100 million neurons and record all of their behaviors continuously. We're going to get to the limit of what we can do with something like that. The theory of all these molecules, cells, and behaviors, and what they're doing and how we can use them to intervene has been much slower. Also, I think we're in a phase right now where we're naming a lot of things, but we don't really understand how they all fit together. I expect in the next decade that the frustration with having lots of data will become more and more pressing. 

How do you approach interdisciplinary collaboration, particularly in fields like neuroscience and psychology? Are there any challenges or benefits you've encountered in working across disciplines?

I consider myself a neurobiologist. Biologists focus on big effects, not weak effects, and that has changed over the past decade or so as people collect more data. You can tease out weak correlations and make inferences based on those weak correlations. Biologists have direct access to the constituents that make up the brain, while psychology leans heavily on theoretical underpinnings and indirect behavioral measurements to make inferences about cognitive processes. You have to use statistical analyses to look at very small effects. There's a crisis of reproducibility in the behavioral and social sciences and some of this has to do with the kinds of indirect and correlative measurements that are made. Psychology questions are rich and relevant and they can really inform the kinds of biological experiments that we do. 

What are the properties of whiskers that make them perfect for conducting learning experiments?

Whiskers take up a large part of their cortical real estate-about a third of the neocortex-which is why they like to use them so much. -When compared to humans, the somatosensory cortex takes up much more space in the mouse brain.Therefore, when studying the somatosensory cortex in mice, it is apparent that it is the sense that they like to use. Its large size is very useful when studying the area because it allows us to look at the structures within it. 

Have you done any research on learning and memory as it relates to traumatic events and PTSD? Are there differences in encoding the mechanisms involved in synapse modification, learning, and memory for non traumatic versus traumatic experiences?

Emotional experiences appear to be encoded in a different part of the brain in the amygdala, and inputs are highly plastic. There's some really interesting therapies that have arisen from the analysis of synaptic changes during fear conditioning or traumatic experiences that have clinical usefulness. There are also ways to erase those memories that take advantage of what we know about the molecules that lie at this site. 

 What continues to spark passion for you in your field?

It was only really in the past 10 years that we moved from looking at synaptic plasticity in sort of [a] more isolated sense to looking at synaptic plasticity in a learning sense, and I am fascinated by learning…Mice spend about 10 minutes of 24 hours doing this task and that’s enough to change synapses in their brain. I am really interested in what makes that time so special… What’s the reinforcement? What is the brain looking for? That 10 minutes can reorganize neural circuits in a way that the other 23 hours and 50 minutes doesn’t undo.