Decoding Memory with Annabelle Singer

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Annabelle Singer discusses neural decoding and how it can help advance Alzheimer’s therapies.


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Steve McLaughlin: I’m Steve McLaughlin, dean of the Georgia Tech College of Engineering, and this is The Uncommon Engineer.

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Male Speaker: [archival recording]— We're just absolutely pleased as punch to have you with us. Please say a few words.


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♪ Old memories on my mind, on my mind, on my mind ♪

Steve McLaughlin: The human brain starts creating memories as early as 20 weeks after conception. It’s really hard to believe that a baby's memories are forming while in the womb. Our memories really do make us who we are, you know, in many ways they define us which is why Alzheimer's and other diseases that affect memory are so devastating to so many people.

I’m Steve McLaughlin, dean of the Georgia Tech College of Engineering, and this is The Uncommon Engineer, our deep dive into ways Georgia Tech engineers make a difference in our world, in our daily lives, and in ways that we may not expect.

Dr. Annabelle singer does that, in part, by finding effective therapies for Alzheimer's disease. She is an assistant professor in the Coulter Department of Biomedical Engineering which is joint between Georgia Tech and Emory. In that department she is a professor and neuro engineer. Welcome to the program, Annabelle.

Annabelle Singer: Thank you.

Steve McLaughlin: Annabelle, we hear lots about Alzheimer's and, you know, the memory challenges that many people, unfortunately, have to experience. Before we talk about your research, can you talk a little bit about some of the things that are exhibited in Alzheimer’s that then your work is going to address?

Annabelle Singer: Many people have interfaced with the disease personally, and people know of it as a memory impairment. So people with advanced forms of Alzheimer's will even forget their family members. But some of the earliest signs of the disease are what we call “deficits in spatial navigation,” so people get lost in a familiar place; people have trouble finding words that they commonly use. And these are the kinds of memory impairment that we see early in the disease, and we think are signs of the neural networks, in particular the hippocampus and related structures, going wrong early in the disease.

We think that what's going wrong is several levels. So on the one hand, there are these proteins called “amyloid beta” that accumulate. And on the other hand, the connections between neurons are failing, they degrade, and that means neurons can't communicate; they can't encode information properly. And on another hand, we also think that the machinery in the brain that clears out pathogens like these proteins is also failing. So there are several different levels at which things seem to be going wrong. It's not entirely clear at this point which one of those things is the key or if it's all three or if one person with Alzheimer's has one thing going on, and a different person with Alzheimer's has one of the other things going on; they might all be playing a role in different ways.

Steve McLaughlin: I know we're going to talk about kind of how engineering overlaps with that, but your kind of identifying several different properties that then, as an engineer or as a scientist, you would try to both better understand, gather information about it, and take what the doctors have learned and then develop your own, maybe, therapies?

Annabelle Singer: We are trying to understand how neural activity fails in Alzheimer's, and typically in animal models of Alzheimer's disease because we can control them and manipulate them significantly more than in human patients. And people have long-studied Alzheimer's from the point of view of proteins that accumulate but, over the past few years, it's become more and more obvious that it's not just protein accumulation that's going on—there seems to be things that are going wrong with how neurons talk to each other, how neurons encode information, and all of that plays a role in how we end up with memory impairment. It also, really surprisingly, seems to play a role in protein accumulation itself. So this amyloid beta that forms plaques, we're now finding we can manipulate that by manipulating neural activity.

The engineering part—you know engineering plays several key roles in our research. First, at a most fundamental level, engineering is a key part of how we think about how the brain works. We think about, when we're trying to understand memory, we're trying to understand how the brain encodes information, how it stores that information, and how it recalls that information. And that kind of information processing is really heavily informed by engineering in terms of the brain is in many ways an electrical organ. It's also a chemical organ, so that information is encoded with electrical signals. Sometimes we think of them as 0’s and 1’s—it's actually not quite that simple, but that's a key way that we think about the brain.

We also use engineering in a lot of the methods that we use. So we use extensive data analysis. We write code to analyze a vast array of data that we get. We do a lot of signal processing, machine learning, things like that. We build devices to manipulate brain activity to record brain activity. So it plays a role at several different levels.

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Steve McLaughlin: So can you say a little bit about why the brain is so hard to understand, and why we are so slow to find effective therapies for some of these neurological conditions?

Annabelle Singer: I think, at the most fundamental level, the brain is hard to understand because it's complicated. There are about 100 billion neurons in the brain—in the human brain—about 100 billion glia, which is another cell type in the brain. And each one of those neurons can have several thousand synapses; those are connections between neurons, which we think there's probably about a quadrillion of these connections between neurons. So that, you know, is a very complicated organ. It's also very diverse. We don't even at this point have a, what I would call a “parts list” of the brain; we don't know in excruciating detail what all the different cell types are, what all the different proteins are. and the other level of complexity is that it functions on many different levels from the DNA and RNA to cells, to cells communicating together in networks, to you know, the brain interfacing with the rest of the body. So all of those different levels are complicated, and we don't really have good ways to understand how we go all the way from these high levels of organ interacting with the body, all the way down to through the neural networks to DNA.

Steve McLaughlin: Unbelievably complicated and complex. And then, for folks like yourself, to try to then develop therapies or to try to better understand then move towards those therapies, just extremely complex. So I'd like to move towards your own research. And first of all, how did you get interested in doing research in Alzheimer's?

Annabelle Singer: Initially it grew out of my interest in learning and memory. I had long been interested in learning and memory. I used to think that the brain or, rather, we as people, were infinitely plastic; we could adapt to anything. And the more I learned about diseases, the more I discovered that there are limits to how plastic we are to what we can adapt to. And Alzheimer's disease is a really great example of how the learning circuits and learning capacity fails.

I also had some really great experiences in graduate school. I was at UCSF Memory and Aging Center. There, it was really wonderful in that they would let me come and observe them working with patients, diagnosing patients. And it was a really transformative experience for me. It's one thing to read about a disease; it's another thing to see patients dealing with the disease, see their families. And so that was a moving experience for me.

The last part, actually, I didn't really come to start studying Alzheimer's disease until the way that we've been thinking about the disease has changed. People used to focus a lot on the proteins that accumulate, which is not really the way that I think about the brain; I think about the brain as this electrical organ that stores information. And more recently, people like myself and a few others have been putting forward that really we need to be thinking about these electrical signals and how they're going wrong in the disease. And then in our own research we found manipulating these electrical signals actually has an effect on these proteins that accumulate. So that really changed the game for me that suddenly the way that I think about the brain, really jived with what might be going on at a fundamental level with this disease.

Steve McLaughlin: I think a lot of people who maybe came into the middle of this conversation thinking it’s like, well, two doctors talking to each other, but it's not; you're in engineering. Being an engineer, you're doing something different, and I'd like to think it’s because you're an engineer. Can you talk about why being an engineer is so important to the work you're doing?

Annabelle Singer: You know, and an engineer can really be whatever you want it to be; it's not limited. And that's one of the things I like about being at Georgia Tech; people don't seem to have a limited view of what engineering is. To me, it's really about working on practical problems, and I would say taking kind of maybe esoteric or pie-in-the-sky questions and ideas and problems, and then turning them into a really practical set of things you can do, whether that's a thing you can build or an experiment you can do to answer that question. And that, to me, is one thing I love to do, and I think that the key part of engineering is that practical application.


Steve McLaughlin: How did you find your way to being an engineer?

Annabelle Singer: My path is kind of convoluted. So I grew up in a small town. We didn't have like robotics teams and things like that. We had a theater. so I like building things; I did a lot of technical theater. I think that was probably the first place where I learned to build things and problem solve in this very practical way, and I loved it. But I ended up doing my Ph.D. in neuroscience; it’s not engineering. and it wasn't until my postdoctoral work that I worked in a neuro engineering lab. The reality is, because I had this background building things, I knew how to make circuits, you know, et cetera. It's always been a part of what I've done. I've always been comfortable doing math and writing code—well, not always—I learned how to do those things, but it's been it's been a long-term part of my career. It wasn't until the end of my Ph.D. where I realized I really wanted to be able to build my own tools; it's a key part of my research. To answer the questions I wanted to answer, I had to be able to build new tools. And I had been doing that on the side, but I wanted to be in a lab where that was the focus. And so that was that was my postdoc. And then, you know, I would say sometimes I call myself a scientist; sometimes I call myself an engineer. I think that I'm both things. I don't really think that there's necessarily an easy way to put a dividing line between the two.

Steve McLaughlin: How are you moving towards human patients? Can you say a little bit about that?

Annabelle Singer: Yes. So there's two key things we had to do to be able to move to human patients.  One is develop noninvasive ways to drive this neural activity, this electrical activity, and we've done that at this point. And then the other is developing noninvasive readouts, so we're working on that as well. And we have a study that we're going to start shortly with the Emory Brain Health Center, where we'll be trying out driving this kind of activity in human patients with early stages of Alzheimer's disease and seeing if it does have similar effects as we've observed in mice.

Steve McLaughlin: So when you say a noninvasive way of getting that signal into a human patient, how would you do that?

Annabelle Singer: We're using set forms of sensory stimulation at different frequencies. And there's been decades of research that shows if you drive flickering lights or sounds trains of tones at different frequencies, you can get those same frequencies in what we call “sensory brain regions,” so parts of a cortex. And what we found that was quite surprising is that you can also do that and drive activity in much deeper brain regions—so regions that are essential for episodic memory or memories of experiences like the hippocampus, regions that are essential for what we call “executive function,” planning, like the prefrontal cortex. So that was a big surprise. And so now we are trying that in humans. And we'll see if it has the same effect, but it's an incredibly simple manipulation in the end.

Steve McLaughlin: I have experienced being somewhere in the lights like you said, the lights flickering resulted in a migraine or something lie that. You're saying that same thing, so whether you put on a headphone or you flicker the lights in a way that maybe even the patient doesn't recognize it, that signal will find its way magically to the spot for which you are applying this therapy. That doesn't sound painful at all, not invasive at all. Just sounds like, you know, like you said, I think you said it could be done through sound—put on a pair of headphones, put some sound in the right way, and that sound will make its way to the right part of the brain. Just like my headache was caused by the flickering lights, it can have a therapeutic. Do I have that right?

Annabelle Singer: Yes, you have that right.

Steve McLaughlin: That is so cool.

Annabelle Singer: It's totally noninvasive. The key part is the frequency. So the flickering lights you've probably experienced before are probably a slow frequency. And they may even have bad consequences we don't fully—we haven't fully characterized every frequency yet. But the frequencies that we have been finding have beneficial effects are about 40 hertz, which is pretty fast. For lights, it's just barely—you can see it but, but if you went to 60 hertz, you can't see it anymore. And it's true, some people might like it; some people might hate it as an experience, so one of things we'll be doing in the future is figuring out how to make it so it's not just therapeutic but enjoyable.

Steve McLaughlin: I think the public sees kind of so little advance or success in the treatment of Alzheimer's and there's so many families that are experiencing that, are you seeing the results that are hopeful? You know, this sounds like totally new approach to doing that. Can you say where's this headed? I mean it sounds really, really hopeful.

Annabelle Singer: Yes, it is a totally new approach. And it's—we're trying to translate it from mice to humans as quickly as possible; we feel that urgency from that community. The tricky part is that to really prove this has a beneficial effect in humans, is going to require, ultimately, some large, multi-center clinical trials. So our first studies are going to be small. There's still a lot of questions that we need to address in terms of figuring out how, even if it does readily translate from mice to humans, how to make it work in humans the absolute best way we can is really a big question. There's going to be several more years of research. The upside for us is it is noninvasive, so that makes it easier to make this leap from mice to humans. If it was an invasive approach or we thought it had some significant side effects, it would take us much longer.

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Steve McLaughlin: In short, how would you describe yourself in terms of being an uncommon engineer? What does that mean for you?

Annabelle Singer: Yeah, what does that mean? I mean I feel like you just summed it up really well which is, you know, just working on being inspired by the problem and doing whatever it takes to get there. You know, sometimes that is building my own tools; sometimes that is working with clinicians, you know, to have access to patients and get new tools and new approaches into those patients. To me, I guess I'm an uncommon engineer in that my research and my work is very interdisciplinary; it doesn't take from just one discipline or one approach, and we just have to figure it out as we go to figure out how to put all these different parts together.

Steve McLaughlin: And so what kind of—yeah, I mean everything, we've talked about just exudes the need for our interdisciplinarity, people with all kinds of skills, all kinds of perspectives and backgrounds. And can you say a little bit about the kinds of students that come in and work in your lab and where they come from or what their backgrounds are?

Annabelle Singer: Yeah. So people come to my lab from many different backgrounds. I have students who are in biomedical engineering and students who are in the neuroscience program at Emory, and a postdoc who comes from a math background. So my students come from backgrounds—some might have a neuroscience undergrad; some might have chemical engineering; they might have electrical engineering, math, et cetera. And I tell them at the outset, nobody comes in knowing everything they need to know to do the work we do, and they have to be able to work together; it's a key part of my lab culture. I try, at least, for it to be a key part of lab culture, that people come—you come with your own expertise, and you exchange that knowledge because there's no way you can do it with just one part.

Steve McLaughlin: We talked a little bit about your research group and the kinds of students that might come into your group. Can you say a little bit about it? Give maybe one example of if a student came to you and said, “Hey, I want to work in your lab.” What would they do?

Annabelle Singer: Yeah. So they do a wide variety of things. Some of the undergrads in my lab, I mentioned before, building these devices that we use to drive neural activity as well as read out neural activity, so some of these devices that we use to recruit these immune cells and clear pathogens from the brain, and we've been really we've had really great success with undergrads in the lab working on that. My graduate students—so went two of my graduate students are doing a lot of the groundwork on these mouse studies to figure out what are the effects of driving these different frequencies, both on neural circuits and on the immune system, and that's directly feeding into the human research that we're planning to do.

Steve McLaughlin: What a fantastic experience that would be for our students. And so for the students out there, anybody who has a—I'm sorry I'm making an ad for encouraging all the students to show up at your door—but this sounds really fantastic opportunity.

Dr. Singer, we're so happy that you were here today, and we're really grateful to have folks like you, you know, here at Georgia Tech really making a difference for patients in uncommon ways. But we're really, really lucky to have folks like yourself on our campus. Thank you so much for coming today.

Anabelle Singer: Thank you for having me. It's been great.

Steve McLaughlin: Well that's it for The Uncommon Engineer this time. Next time, we'll shift from our inner biology to outer space, or at least our stellar neighborhood. Professor Brian Gunter comes to us to talk about space exploration and what it means for our species. Absolutely, this is one you won't want to miss.

For now, I'm Steve McLaughlin. Thanks for listening to The Uncommon Engineer.

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♪ Old memories on my mind, on my mind, on my mind, and I promise to do no wrong ♪

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