Matthias Stangl is a postdoc at UCLA, where he studies the neural representations of spatial navigation in social situations. In this conversation, we talk about his PhD work about aging, grid cells, and path integration, about his recent Nature paper, about the difference between movement in VR and actual physical movement, and much more.
BJKS Podcast is a podcast about neuroscience, psychology, and anything vaguely related, hosted by Benjamin James Kuper-Smith. New episodes every Friday. You can find the podcast on all podcasting platforms (e.g., Spotify, Apple/Google Podcasts, etc.).
Timestamps
0:00:04: Stangl.Stangl.eu
0:02:13: Start discussing Matthias's Current Biology paper on aging, grid cells, and spatial navigation
0:07:10: The temporal stability of grid cells
0:16:10: Start discussing Matthias's Nature Communications paper on path integration errors in aging
0:26:07: Sensory effects on path integration in humans and other animals
0:37:45: Does actual movement lead to stronger grid cells firing (compared to imagined/VR)?
0:41:52: Start discussing Matthias's Nature paper on neural representations for self and other in real spatial navigation
1:00:03: Matthias's future
Podcast links
Website: https://geni.us/bjks-pod
Twitter: https://geni.us/bjks-pod-twt
Matthias's links
Google Scholar: https://geni.us/stangl-scholar
Twitter: https://geni.us/stangl-twt
Ben's links
Website: https://geni.us/bjks-web
Google Scholar: https://geni.us/bjks-scholar
Twitter: https://geni.us/bjks-twt
References
Aghajan, Z. M., Schuette, P., Fields, T. A., Tran, M. E., Siddiqui, S. M., Hasulak, N. R., ... & Suthana, N. (2017). Theta oscillations in the human medial temporal lobe during real-world ambulatory movement. Current Biology.
Barnes, C. A., Suster, M. S., Shen, J., & McNaughton, B. L. (1997). Multistability of cognitive maps in the hippocampus of old rats. Nature.
Chen, G., Manson, D., Cacucci, F., & Wills, T. J. (2016). Absence of visual input results in the disruption of grid cell firing in the mouse. Current Biology.
Kunz, L., Schröder, T. N., Lee, H., Montag, C., Lachmann, B., Sariyska, R., ... & Axmacher, N. (2015). Reduced grid-cell–like representations in adults at genetic risk for Alzheimer’s disease. Science.
Stangl, M., Achtzehn, J., Huber, K., Dietrich, C., Tempelmann, C., & Wolbers, T. (2018). Compromised grid-cell-like representations in old age as a key mechanism to explain age-related navigational deficits. Current Biology.
Stangl, M., Kanitscheider, I., Riemer, M., Fiete, I., & Wolbers, T. (2020). Sources of path integration error in young and aging humans. Nature communications.
Stangl, M., Topalovic, U., Inman, C. S., Hiller, S., Villaroman, D., Aghajan, Z. M., ... & Suthana, N. (2021). Boundary-anchored neural mechanisms of location-encoding for self and others. Nature.
Topalovic, U., Aghajan, Z. M., Villaroman, D., Hiller, S., Christov-Moore, L., Wishard, T. J., ... & Suthana, N. (2020). Wireless programmable recording and stimulation of deep brain activity in freely moving humans. Neuron.
Yoder, R. M., & Taube, J. S. (2014). The vestibular contribution to the head direction signal and navigation. Frontiers in integrative neuroscience.
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[This is an automated transcript with many errors]
Benjamin James Kuper-Smith: [00:00:00] Know, I like to kind of look up the guests and like see kind of what they did before, you know, kind of like what their education was and that kind of stuff. And, uh, whilst doing that, I found an interesting website. Are you familiar with the website? Ang Do tango.eu.
Matthias Stangl: No, it sounds funny. No, I'm
Benjamin James Kuper-Smith: not. It's, it's a website that I'm assuming someone with a surname Stang made about all the famous people called Stang.
Oh,
Matthias Stangl: I see. It's
Benjamin James Kuper-Smith: a really long list of people who are called stang with surname.
Matthias Stangl: Oh yeah. Let's hope I'm gonna end up there sometime.
Benjamin James Kuper-Smith: You are, you are. That's, that's how I found the website. You're on it. Yeah. Yeah. Um,
Matthias Stangl: no, I have to, now I have to write that down. I have to Google that. Definitely
Benjamin James Kuper-Smith: funny. Yeah, it says Mattia Strangle postdoc, facia.
So it's a, it's a general website and it briefly mentions your, in two sentences, kind of what you're doing.
Matthias Stangl: Exciting. Well, now I'm
Benjamin James Kuper-Smith: curious. Okay, so you, so you're not familiar with that [00:01:00] website?
Matthias Stangl: No, I'm not. And I'm, I didn't, I didn't, I didn't create it, so, no. Uh,
Benjamin James Kuper-Smith: yeah. I think a guy called Van might have created it.
I'm not sure. Yeah. Anyway, so you're, so you're not related to No,
Matthias Stangl: no, I'm not. No, no. I I'm definitely gonna look it up, but No, no, this
Benjamin James Kuper-Smith: is it a super common name. I mean, I don't know anyone apart. I mean, it sounds like a kind of Bavarian Austrian name.
Matthias Stangl: It is, it is. I, I am Austrian actually. So, uh, so, and, and, and it is common in Austria, but as soon as you leave Austria Bavaria, it's kind of not very common.
And, um, yeah. But yeah, in, in, so where I grew up, uh, it's a couple of people. Yeah. What's that? It is kind of a common name, um, in Syria, that's like in the south east of Austria.
Benjamin James Kuper-Smith: Mm-hmm.
Matthias Stangl: Um, a lot of like, um, mountain area. And it's, uh, so like
Benjamin James Kuper-Smith: stereotypical Austria?
Matthias Stangl: Yes, very, very much so. Okay, cool.
Benjamin James Kuper-Smith: Yeah, I mean, uh, yeah.
By the way, there's lots of great people called Ang, lots of chess [00:02:00] champions. Kegel Meister.
Matthias Stangl: Oh
Benjamin James Kuper-Smith: yeah, that, that,
Matthias Stangl: that sounds very Austrian too. Yeah. I see.
Benjamin James Kuper-Smith: Okay. Scott Meister and, anyway, so let's, let's actually talk some, some science and some research then. So, yeah, so you have the, the two main papers that I've, uh, or the two papers of yours on this topic that I've read are the current biology one and the nature Communications one.
I think it makes sense to start with the current biology one. It seems to me that,
Matthias Stangl: yeah.
Benjamin James Kuper-Smith: Yeah. I mean, it's both the historical and also conceptual kind of, uh, sensible path. Um, so yeah. Can you maybe like in, I dunno, a minute or two, just briefly kind of explain what you did in that study? Uh, maybe what the participants did and kind of what you found.
Matthias Stangl: Yeah, sure. So the, the main idea, um, what we wanted to look at is if the, the grid cell system, or, you know, as far as we can measure that in humans, we're talking about grid cell like representations because we don't have access to. So single neurons are, [00:03:00] we sometimes have, but um, not typically with like FMRI, we can only measure population activity.
So, um, we wanted to see if the grid cell system, um, was impaired in older adults. And, um, this was especially because, so the, the, the main reason why we wanted to do this is we wanted to see why. Navigation abilities are impaired in older age, we wanted to find potential causes of these impairments. And, um, if you want to do that, if you wanna research that, and there really is no way around grid cells because the grid cells are just such a key player in the navigation system.
So, and also grid cells are mainly located in, in the anine cortex, which is the, or one of the very first region regions where neurodegenerative processes start, like tau pathology and other things. Um, they start in the anine cortex. So we just felt it makes a lot of sense to look at, um, whether. Impaired grid cell, um, activation could [00:04:00] be one of the key reasons for, um, navigational decline in old age to test this very, very, um, simple idea.
Actually, we, um, we, uh, used FMRI, as I said before, so we asked people to, you know, perform a navigation task in the scanner. This was all virtual, virtual reality, so they moved around using like a joystick while they were in the scanner. Um, they moved around in a virtual environment and the task was also very simple.
They just had to learn locations within this virtual room they were in. And after a while when they had learned, you know, like whatever the soccer ball was in this corner of the room or whatever, then they were just repeatedly asked again and again to navigate to this place where they had learned that the soccer ball, um, was, and they did this for like a long time.
So, um, it was probably not the most exciting task, um, but it allowed us to get a lot of data to then look at, um, what these grid cells do while, while, um, our participants performed the task. [00:05:00]
Benjamin James Kuper-Smith: So maybe actually one thing just be before I forget it, so I did do an interview with Nicola mha. It's, I don't know, episode 38 or something like that.
Um, so just if this whole topic is interesting to the listeners, there's an entire episode on their science paper per, um, about doing this with. Basically grid cells and path integration and that kinda stuff, and spa navigation with people who are at a genetic risk of developing Alzheimer's. So just to mention that briefly, there's, if this is interesting, there's another entire episode on this, but yeah, so it seems to me there's kind of, uh, there's kind of like three main findings, right?
In some sense. So the first is the grid cell differences, or I guess you could say reduction, um, in older people compared to younger people. The second is the path integration differences, right? And the third is kind of the combination of the two.
Matthias Stangl: Yes, yes, that's correct. I mean, we, we did know before, or it has been, it has been shown several [00:06:00] times that path integration is impaired in older adults.
So that wasn't really like a new finding, but we, but we were really interested first to see whether the grid cell system might be, you know, impaired or, um, or a grid cell, like representations might be, um, reduced or compromised in older age. And then we wanted, kind of as a next step, um, we wanted to see whether this could actually cause, um, navigational impairments.
And so we looked at path integration in particular. We were so this, it wasn't surprising that older adults were worse in path integration than our younger adults, but our hypothesis really, like, were confirmed when we saw that those older adults who, um, who were worse in path integration, were also the ones who were, um, showing the reduced grid-like representations.
Now obviously this is not like a proof for like a causal relationship, but it just shows us that, um, this, this, um, these compromised [00:07:00] grid-like representations could actually really serve as a, as an explanation for navigational deficits or path integration impairments in old age.
Benjamin James Kuper-Smith: I, and so maybe to start, um, or talk about the grid cell aspect here.
Um, the, the thing that was kind of most interesting to me, I think it was this parallel finding to the Kunz 2015 science paper where you found that the grid cell activity was, um, if I understand it or remember correctly, that the, the main reason for the reduction in grid cell of activity was because it just wasn't as stable over time in terms of the direction in which the grid cells or the grid cell-like representation fired between the first and the second half of the study.
So, so kind of what do you make of that, because I have to admit, I don't know much about this temporal stability of grid cells. Um, can you maybe talk a bit more about kind of Yeah. What we know as a field about this.
Matthias Stangl: So I would say [00:08:00] like about the temporal stability, we don't know too much, but it is very obvious that like a, a, a pattern formed.
So a couple of findings come together and Lucas Kunz, Nico SMA has, and their colleagues on paper that, um, was like a first step really showing that temporal stability, um, seems to be something that is, um, is impaired, meaning that. What we can measure is, um, the orientation of this firing map. So basically the, the orientation of, of our internal coordinate system that grid cells, um, form that this is kind of, it's unstable, it kind of shifts over time.
And, um, it, so in rodent studies it has been shown typically that, you know, this is kind of stable, like when you would go into like the same environment multiple times. Um, it seems that this kind of coordinate system, um, that grid cells form that it seems to be pretty much, um, anchored to something. We don't know exactly [00:09:00] what it is, but it seems to be, um, pretty stable.
But, um, what we see is that. And that's, that's the same in our paper and in, uh, the paper from LED by Lucas Kunz is that when these, um, coordinate systems are less stable, when the temporal stability kind of is, is reduced, um, then this is kind of an indicator for, um, reduced performance. And they see this already, um, in younger, in younger, um, adults who are at risk for developing like Alzheimer's.
Uh, and we see really the same thing. So it's, it's very strikingly similar, um, that we see the same thing in older adults, and particularly in those older adults who are, who are worse in actual navigation performance or in path integration.
Benjamin James Kuper-Smith: Yeah, I mean, so yeah, so, so I, I kind of also got the id the idea from your reading paper that this is something that's pretty new.
Uh, yeah, there's just not that much done on it. I mean, you know, so I guess, uh, maybe I'm asking you to speculate a bit here, and I guess to [00:10:00] some extent you do that in the paper by suggesting that head direction cells. Maybe have something to do with it. Also, like one thing that's not entirely clear to me is why would it be a problem if grid cells aren't super stable over time?
As long as they can do it in a given moment. If I know where I'm right now, why is it a problem that five minutes late, it's different grid cells doing it, you know? I was just surprised, I guess, by the finding.
Matthias Stangl: Oh, I see. Um, so. I wouldn't interpret this as, you know, like just a different grid cell takes over with a different orientation.
I, what I would, how I would interpret this is, um, that the firing of a single cell, but this is, this is, as you said, this is speculation, right? We don don't know that we don't have access to this kind of information in fmri. But how I would interpret this, um, is that a single cell, uh, that the firing of a single cell is just not stable.
You know, these cells fire at particular locations in the environment, they form this kind of pattern. So if you [00:11:00] look at the FMI data that, that we see, I would speculate that, um, the single. Cell firing. That is the underlying basis for what we see in FMI, that the single cell firing is just not stable.
Meaning that this one particular grid cell for, um, fires at a couple of locations in the room, but then like 10 minutes later, um, it's firing at slightly different, slightly offset, um, locations, which, um, it's, it's really not clear why this is causing an issue, but we see that this is, is, it's not what kind of a, a normal, very prototypical grid cell would do, or at least what we expect it to do.
And, um, figuring out why this is the problem and then as a next step, what can we, what can we do about it? Um, it is kind of, it's kind of really the next steps. It's kind of the million dollar questions that, that we don't know.
Benjamin James Kuper-Smith: Yeah. It seems like you and the other group or groups on that paper added like [00:12:00] a.
A whole new question for people doing animal studies, particularly like, uh, animal models of neurodegenerative diseases to kind of see like yeah, whether it's the case there too and why, and yeah, all that kind of stuff.
Matthias Stangl: I will say that I think it might, so there, there are some, there are some, um, papers suggesting that it's more like a general mechanism, um, uh, related to age-related decline, at least in, um, in spatially tuned, um, cell firing.
I can't remember exactly what papers these were, but I know I have seen papers also showing similar effects in place cells, for example, and not sure about head direction cells, but definitely in place cells. There was also, I, I think it's Carol Barnes, um, who had a couple of studies on that showing that also place cells have this kind of, they, these play cells seem to, to do their job, you know, they fire at a particular location in the room.
It's just not stable over time. And in [00:13:00] younger or unhealthy or in high performing individuals, um, you see that this, these firing patterns are just more stable. So it might be that this is not something typical to grid cells. It could be that it's just a general age related issue in, in, in the firing of, you know, neurons, or at least in the firing of spatially tuned neurons that they, they actually function, but um, they are not functioning, um, in a stable way over time.
Right.
Benjamin James Kuper-Smith: Although, I guess like the. I mean, isn't the idea that play cells get their information from grid cells? So kind of if one isn't as stable, then it kind of makes sense that the other as a downstream effect wouldn't be as stable either. Right?
Matthias Stangl: It's true, it's possible. I, I have to say that it's, it's also another open question, so,
Benjamin James Kuper-Smith: yeah.
Matthias Stangl: Yeah. Initially, many, many people thought that this is the case that, you know, play cells are formed by input from al cortex and particularly grid cells. But, um, also turned out over, over the last couple of years that it's probably more [00:14:00] complicated than that. Um, but, um, yes, I, I agree. But you could say the same thing also about grid cells, and we are trying to make this point also in the paper, we don't know whether grid cells are kind of the, the, the, the source of the issue, right?
It could be that, that, um, the information that is delivered to grid cells or to the grid cell system, to the cortex, it could be that, um, the information, um, is already kind of, um, compromised before that stage. It could be that the information that is delivered to the grid cell system, um, is already, you know, like not stable, and that's why grid cells maybe can't even form this stable pattern because, you know, potentially the head direction input that is.
Then, um, delivered to the grid cell system, which obviously is important. If you think about your anchoring in an environment. You know, you, you probably, the head direction system plays an important role. It could be that, um, this is where it starts. So even in the sensory processing. Um, so it's, it's hard to say where it starts, but definitely we see in grid cells, um, or [00:15:00] in grid cell like representations.
Um, we see that at this stage, um, that the information and the information processing is already compromised.
Benjamin James Kuper-Smith: It's funny, I guess you have this like multiple streams of different things influencing, influencing each other, and you've kind of found in the middle this one thing that doesn't work and now it's Yeah, like no idea whether it is the thing or anything that happened before or Yeah, whatever.
Matthias Stangl: Exactly. This, this, this. Um, to be honest, this was one of the, one of the reasons also why we want to look into exactly this question also more with like the computational modeling study. Um, we haven't talked about this yet, but, but this was one of the, the key reasons we, we at this point knew, um, okay, there is something going wrong in the, like the grid cell system, but um, there are just so many other variables that, that we haven't, you know, like even considered or, uh, it's just a complex picture.
So we wanted to also take other variables into account and, uh, yeah, so exactly what you said, it's, it's just a [00:16:00] complicated picture. Seeing that the issue is already present at the grid cell system doesn't mean that it's the source.
Benjamin James Kuper-Smith: Yeah. Yeah, definitely. Um, yeah, maybe shall we just go there then and talk about the nature communications paper?
Yes, of course. Um, I have to admit, this is the one I'm probably least familiar with of the three we're gonna discuss today. I guess in part because the details here are in the modeling, which is probably the, the point my, my weaker point of these studies. Yeah. I guess we can still kind of discuss it and see kind of where we go.
So maybe again, do you wanna kind of briefly set the stage of Yeah, what, what this paper did, or maybe how you got, I guess you already did, but Yeah, kind of what were the main findings?
Matthias Stangl: Of course. Yeah. Uh, yeah, I mean, the main question was very similar to the paper that we talked about already. It's like, why, why is navigation impaired in old age?
Um, so we do see this, uh, many, many times, but still, we don't know what kind of processes, what kind of neural mechanisms or what, um, [00:17:00] variables do actually play a role in this age-related navigational decline. Again, what I said initially also is, um, navigation is just such a complex, um, function, such a complex ability.
Um, so we also, um, just looked at, uh, one specific sub component, which is path integration here, uh, which is just an important function in navigation, but it's, it's just one element, um, where you keep track of where you are by integrating self motion cues. And so we already knew from, um, from this current biology paper, um, that we've discussed, we already knew that the grid cell system does play an important role.
And this has also been hypothesized and shown many times before. But also we knew, or at least we thought, there are just many, many other factors and variables that could play a role, um, which were not, like, we didn't look at these yet. Um, so. Now having closely looked at the grid cell [00:18:00] system, also we wanted to know what about the other variables.
For example, you know, um, in navigation and also in path integration, for example. Memory also plays an important role because, uh, because you need to, you know, like. Continuously maintain and update, um, a location, location estimate, you know, um, information about where you are. And for that, you also need to remember, um, where you've been like, I don't know, three seconds ago, uh, these kind of things.
Also, there is, there are just many, many other, um, variables involved. Like you could over or underestimate yourself, motion speed. And this is why, why your location estimate might be, might be, um, imprecise, for example, or something very, very different like what we call reporting noise, for example. So it could be that people actually, I'm not sure how.
How plausible this is. But theoretically it could be that someone is really, really good at path integration, really good at keeping track of where they are. It's just when you ask them [00:19:00] about it, um, their report could be kind of noisy. It could be, could be kind of wrong, right? Which doesn't have anything to do with path integration per se.
It's just they're not able to translate this internal estimate to kind of an output. Or there could be something, um, which we were obviously most interested in. Um, it's kind of, we call it internal noise. Um, so this is a, a weak term, but this is what we mean by the actual. Path integration computations, which is where you take sensory information and you compute your location estimate based on, based on the change in, in, in sensory information.
So you basically move, you see that you move, you feel that you move, you take that information and then you compute your new position. And this, this process could also be noisy or could be imperfect. So, and we wanted to know, um, so now knowing, we, knowing that, um, all the adults are impaired in path integration, we didn't only want to know like.
How, or how, how [00:20:00] strong is this impairment? Um, we wanted to know what processes are going wrong. Um, what, what could be the, the sources and the causes for, um, path integration decline in older age. And so what we did is we, we teamed up with, um, computational neuroscientists, um, really, really, um, great scientists who, who built this, um, computational model.
So this was I Lata and, um, they, they were at, um, university of Texas in Austin. And I, Lata is now at MIT. And so we, we worked with them and they, they built this computational model, which takes. The variables that I have explained and a couple of others into account, and assumes that this location estimate that you continuously, continuously update and maintain during, during movement and that this location up estimate could be corrupted by these, um, sources of error, like what I said, a memory component, this internal noise, this reporting errors, these kind of things.
And, [00:21:00] um, so this model allowed us to estimate for each individual participant to estimate what was the contribution of each, um, error source on their total path integration errors. So we disentangled these, these different, um, influences of the different possible error sources. And, um, then wanted to look at which sources are actually driving, um, the navigational errors, which are drive, which are, which are the major causes of path integration errors in both in younger adults and in older adults.
The first thing, um, that we found was very surprising because previously it always, so, so a lot of studies have shown already that path integration is impaired in older adults, as I said, and always kind of, they were kind of speculating or assuming that memory plays an important role, right? That probably like memory is impaired in older age.
And this is obviously an important component for path integration. So the assumption [00:22:00] was that this memory component, which is also called memory decay or memory leak, kind of a forgetting of where you've been a little while ago, that this, this drives these navigational errors. And what we saw in our, in our task and in our model is, um, that this memory component actually did not play an important role at all.
It was, it was, um, I think even, even like the, one of the weakest sources of error in, in, um, in our participants, and this is true for both young and older adults. So this was, this was a major finding, even though it was a non kind of, it was a non finding really. But um, but it was interesting that it was so different to what everybody had assumed and expected.
Benjamin James Kuper-Smith: I mean, I guess the assumptions always that. Memory gets worse with age. Right,
Matthias Stangl: exactly. I mean,
Benjamin James Kuper-Smith: that's the kind of obvious thing, but
Matthias Stangl: Absolutely. And this, this, I think is why everybody was under the, under the belief that memory would play an important role. But for this particular [00:23:00] aspect of navigation, it seemed that, uh, memory is not the driving factor and there is something else.
And, um, we also saw that it's not these kind of, these, you know, biases. Biases and, uh, like reporting errors or over underestimation of speed or something like that. We saw that it's really this internal noise that is the main source of error, both in young and in older adults. Um, which is. In a way, also in line with, with what we, um, said earlier about, you know, the grid cell system and, and these neural processes.
So it really shows that the actual path integration computations are, um, impaired in this study. Uh, we didn't use FM I or any other neural recording, so we can't really say whether it's it's originating in the grid cell system or where it really originates, but we can tell it's really the path integration computation that goes wrong.
It's like at some stage, uh, starting from, um, where you get the sensory [00:24:00] information, where you process the sensory information and then it reaches probably like the grid cell or the path integration system, somewhere on that stage. Uh, or on these stages, there's, this seems to be like the main, um, source of error and not so much the other variables that, that we, that we looked into.
Benjamin James Kuper-Smith: And I guess the thing that's, I mean, you kind of alluded to this already, but the thing that I found interesting is that it seems to me that the, correct me if I'm wrong here, um, but like a very, very brief summary would be basically that older and younger people make the same kind of errors, but older people make more of them.
Is that fair to say that like basically, I think you said they both kind of have the same kind of reason for error, just that older people would do a bit more of it, which I don't know. Initially I also thought like in terms of clinical application, this probably is not good. Like you, you'd hope for a specific difference rather than just, you know, the same thing.
Matthias Stangl: I see, I see. Yeah. No, but I, but I, I agree. Um, I. I [00:25:00] like that summary a lot. It's, it's actually a really, a really good description of, of what we think is happening. It's not like qualitatively very different between younger and older adults. Yes, they make the same kinds of errors and in both like age groups, um, a lot of variables like memory are not driving, um, the, the navigational errors, but all the adults make more of this.
So it seems that, it seems like the problems that problems, I mean, you know, this, this is all like, um, not a pathological level, but kind of the, the problems or the sources of error that are already present at younger age just get worse, um, with older age. And, you know, it could be that this is, um, happening in the grid cell system, but again, as I said before, it could also be that it happens before.
It could be like the sensory input to the grid cell system. It could be head direction information, all these kind of things. Um. Yeah, it seems, it seems to be the, the major source of error that is already present in [00:26:00]younger adults seems to, um, get worse, um, with age.
Benjamin James Kuper-Smith: Yeah. I mean, maybe whilst you, uh, so one, one main point kind of about this one I had, or not necessarily main point, but one thing I wanted to ask about, um, that you kind of alluded to just now is, you know, this kind of like, where exactly does this noise or error come from in that sense?
And one thing I just, just from like reading the abstract I think or something, my initial thought was like, okay, like how does this relate to proprioception or something like that. Because in some sense yes. You know, proprioception being kind of your awareness of where your body is in space, I guess. I hope that's a good, uh, description.
And, um, so then the kind of what I was thinking about is, okay, like is there anything about grid sales and proprioception or, because as far as I'm aware, these are pretty r. I mean, there're different research areas, but it's fairly, there's a lot of overlap between people who do prep reception and bodily awareness and spatial navigation.
Right. It's, it's not that different. But I, I'm not, I'm unaware of [00:27:00] any studies on this. Um, I mean, I'm not in the field, but do you know of anything?
Matthias Stangl: So, I mean, the question you're asking is, is a really good one, is a really important one. It's like, where does this noise come from? Right. And, um, unfortunately it's, it's a beautiful question, but I, I don't have a, a good answer to it.
Um, particularly like with our, with our study. Yeah. Um, we didn't have any neural recordings even. Right. So we, so this is, this is the information that we get from a computational model, just, just looking at behavior. Um, so what we can say is we can exclude a couple of variables in this study, um, in terms of them not being like super important.
And we can really say, okay, it's. It's the path integration computations that drive these errors. But at what stage of these processes, at what stage exactly? Um, this noise comes in, we don't know. And it's, it's, it's very possible that what you said, [00:28:00] um, that I'm not sure it's proprioception per se. I think there are a couple of other good candidates, but yes, I, I a hundred percent agree that the sensory information that you get the processing of the sensory information even before it reaches the path integrator that, um, this can, and yeah, it's, I I think it's likely that, um, this plays, plays an important role as well and.
I'm not a hundred percent sure. Um, but I think there are, um, studies pointing towards like vestibular information, at least in rodents, um, vestibular information playing an important role. I think, um, there are studies showing that the grid cell pattern, um, breaks down when you manipulate vestibular information.
Um, or when you vestibular information is, is reduced to the animals. Um, so at the same time, I will say that reading these papers, um, it's, it's obviously very interesting, but it's [00:29:00] also not clear how it translates to humans because when it comes to exactly this like processing of. Sensory information about where we are.
I am, I am under the belief that this is something very different between, um, humans and, and, and rodents, for example. Right? So in humans, we, we kind of, we I think use different sensory cues, different sensory information to get an understanding of where we are. We are probably also easier able to imagine being somewhere where we are not, or, uh, we don't have to go to a specific place to, you know, like explore it.
We can just look at it. So I think humans are, are much more visually driven.
Benjamin James Kuper-Smith: I was about to ask, do you mean like humans more use vision more and other animals use, uh, especially smell a lot more and that kind of stuff or?
Matthias Stangl: Exactly, exactly. So I think, I think, um, the kind of sensory information that we use to keep track of where we are is probably different in, in different species and in humans in particular.
[00:30:00] So I think, um, what we know from rodent studies might not be like, um, exactly the same when we look at humans. And also I think, I think this is an important point also because if, um, these processes like also the grid cell system and uh, the processing of sensor information would be the same in in humans as it was in, in, in, in rodents, we would not actually even expect to see.
Any grid cell like representations in fmri, for example, because, because, um, these participants are not moving at all, right? They are in the scanner. Um, or with electrophysiological methods, we see that pattern also when people are like in their hospital beds, um, not moving at all, they just, they just, um, navigate pretty much in a computer game with a joystick.
So you don't have that sensor information. The only sensor information you have is, is pretty much vision, but we still see, um, grid cell, um, firing patterns. We see grid cell like [00:31:00] representations. So that already tells us that. These systems might use different information in humans than they do in rodents, which yeah.
Makes, it, makes it even more difficult to peculate about what is the driving source in humans now. Um, but yeah, again, again, it's perfectly, perfectly possible that it is sensory information. It is, um, proprioception or vestibular cues would be definitely something to look at, but also, but also on other, other sources of information.
Benjamin James Kuper-Smith: Okay. I know you are not a rodent researcher, but this is just a question that occurred to me, so maybe you have an answer, maybe not. Uh, it just occurred to me that, I mean, I'm assuming that rodents move a lot around in the dark, um, if you're in a cave or whatever, or at night and that kind of stuff. But as far as I'm aware, I think most studies are done in light.
Right. I dunno, it just occurred to me like whether the, whether we're in some sense, maybe. I guess one question is whether there's a difference in navigational strategies for rodents, for example, or whether it [00:32:00] doesn't make a difference. They just use a different sensory modality. Um, you know, when it's dark, they maybe use their smell, sense of smell more than their sense of vision.
But it also just occurred to me like, are we in some sense, maybe even testing rats? An environment they're not actually that familiar with. I mean, I, I dunno what the etiology exactly of rats is and how much they actually spend in light and dark. I was, yeah. Do you know anything about this? I don't know.
It just occurred to me whilst you said that.
Matthias Stangl: Yeah. No, it's a, it's a good point. Um, and I think that's, that's also part of the reason why it is so important to take the findings that, that we see in rodents, but then, um, or, or in, in other animals, and then try to translate it to humans, but also kind of try to be a little bit unbiased.
Right. Because things are different. We don't know exactly like what you said. I, I don't have the answer to that because I, as you said, I'm not a rodent researcher, so I don't know how. Natural it is, um, for a rodent to, to run around in light and dark in different conditions or [00:33:00] in these cases, but whatever we find, we don't know exactly whether, um, whether it's gonna be the same in humans.
And so that's something to look at very carefully. Um, I do, I do know that grid cells have been shown in rodents also to, to show their typical firing also in darkness. So it has been shown in darkness and in in light. Um, which is, which is also part of the reason why many people have started to speculate that it is kind of Daniel basis for path integration because you, you, you obviously can do perform path integration, um, also in darkness, right?
So if also as a human, like if you close your eyes, if you walk around you, you always still maintain kind of a sense of where you are. Um, and, and, and so. It does work in humans as well as in rodents, but how naturalistic these environments are in rodents. I, I, I don't know.
Benjamin James Kuper-Smith: Yeah. I think, if I remember correctly, I think when I talked to Kate Jeffrey, I think she might have mentioned that something like [00:34:00] grid cells, I hope I'm not talking nonsense here, but I think she might have said that, um, they did a study and kind of when you turn the lights off and rather than this square boxes that the grids or pattern just gets weaker or something of a time, and then when you turn the lights on again, it gets back to normal.
I think I, yeah, take this with a large grain of salt, but I think she said, might have said that on my, on my episode with her, but yeah. Um, uh, I don't know. Sorry. Did you want to add something to that or.
Matthias Stangl: No, I think, I think it makes, it makes perfect sense. It's, it's, it's, it's in line with what I think what, what I would expect.
So, um, I mean definitely, you know, we, we also know also as humans, we know it's, you know, harder to keep track of where, where you are when you close your eyes. Um, but still you're able to do it and, um, it does make sense. That may, maybe that's too easy explanation, but it does make sense that, you know, like you [00:35:00] see a similar pattern in rodents.
If you're assuming that grid cells are the source of path integration, neuronal basis for that, um, it makes sense that they do function also in darkness. But also maybe the reduced activity is kind of an expression of, you know, more uncertainty, which in the end, um, leads to, to, to, um, maybe worse behavior.
We don't know, but I think logically it, it makes sense.
Benjamin James Kuper-Smith: Yeah, I mean, I think in this hypothetical or potential scenario that I mentioned with the reds in the dark and in the light, I think one reason, may I, I would be curious to see whether, or I'm assuming that this was probably in a fairly boring square box, but if they had like different, um, olfactory cues around the place, then I could imagine that the effect would be less or something like that.
But yeah, this is, again, I'm not sure whether she said this in the first place. You know, this is the funny thing, going back to what I, what we talked about in the right, in the beginning. Like, there's just so much we don't know about this stuff. Absolutely. It, it [00:36:00] feels, the first time you hear about, it's like, okay, we figure this out.
Like we know how special navigation works. We've got places, we've got great cells, and then you actually try and you realize, I mean, there's almost nothing that we know about it.
Matthias Stangl: Yeah, I, I a hundred percent agree. I mean, I feel, I feel like that not only about, you know, grid cells or navigation, I feel honestly about the whole neuroscience field is like, uh, and that, that's what makes it so exciting because every new paper or every, every question that we are trying to address kind of opens up, um, 12 more new questions, right?
Which are maybe even more exciting. So it's, um, it's a good thing. Uh, but also it shows us all the time that, um, there is still, there is still a lot we don't know yet, and there is still not. A lot of work necessary to really understand what's going on and to, you know, then hopefully help when, you know, systems like don't work so well, like in, in old age or when it comes to interventions or, or disorders.
So [00:37:00] yeah, a a lot of work to do.
Benjamin James Kuper-Smith: Yeah. I, uh, last point of this, I remember when I, between my bachelor's and master's, I was doing like an internship. I remember talking to someone who did, um, soon I had a, I had a bachelor's in psychology, but no real, not real neuroscience at that point. And I remember talking to someone who did, uh, some sort of neuro computation at Acellular level, something like that.
And I, you know, asked her what she was doing. She said, you know, that kinda stuff. And I was like, oh, well, I, I thought you knew how that worked. You know, I, I thought, you know, if you got your action potential, like, what, what, what do you need? She's like, well, it's a bit more complicated than that. Yeah. But yeah, I guess we should probably start moving on to the next stuff.
Others, we'll never get to it today. But you already mentioned one point that actually you said you listened to my interview with Yaakov Berman, right? Yes. So you probably heard your name then, right?
Matthias Stangl: Yeah,
Benjamin James Kuper-Smith: no, I remember. Yeah. So now I'm gonna ask that question. So basically I asked Yaakov, um, whether he knew whether there's a difference between, [00:38:00] uh, basically what do we have more grid cell firing or stronger grids cell firing when people are actually moving relative to when they're may be, you know, lying in a scanner and only seeing it on a PC screen, or imagining it.
Um, and Jaakko said, I don't know why you ask. I mean, you're gonna talk to Mattia soon. Maybe he knows. So do you know.
Matthias Stangl: Uh, yeah, the, the sad answer is, I, I don't know. Okay. But, um, the good, the silver lining is, um, we are on a good, on a good path to hopefully find it out soon. Okay. Um, because what, what I've been doing under my postdoc is to work with a very unique group of patients where we kind of finally get access to these signals, right?
So to get access to deep brain oscillations, um, deep brain recordings while people are moving. And so that allows us to address these questions, but still we are like at a very basic [00:39:00] level. So we do develop paradigms and techniques and, um, experiments. Where we test these kind of things. But still, this is such a new area that we are just at the beginning try trying to basically make this work like also from a technical perspective.
And, um, we now are at a stage where we can really start, um, answering research questions. But we are at a very early stage. So we do see these grid-like patterns for example, or other things, um, that we'll probably talk about in a minute. We do see spatial representations, um, but we have not, uh, and haven't yet directly compared this between like virtual reality and ambulatory movement.
If I, if I'd have to speculate. I do think based on the data that I've seen so far, I do think that signals are, um, stronger when participants are moving. Um, so for example, I, I have analyzed the same signals in terms of umlike [00:40:00] representations in fmri, what we talked about before, and now looking at, um, brain oscillations and, um, with electrophysiology while participants are moving.
And the signals are very, very strong, um, that we see, um, while participants are walking around. But at the same time, you know, there are so many other available steps. Could cause this difference. Um, it's, I mean, you have different
Benjamin James Kuper-Smith: imaging modalities
Matthias Stangl: to begin with. Exactly. Yes, exactly. Like, like basically everything's different, right?
So, um, it's in the one case we, we, we are measuring like hemodynamic response of the brain. In the other case we're measuring brain oscillations. And yes, in the one case they are like in lying still in a scanner and just looking at a screen. In the other case, they're walking around. But, um, I am not able to tell you if, like, the fact that we see stronger signals when participants are walking around, whether that's really caused by the fact that they're walking around or it's just electrophysiological [00:41:00] methods or many, many other things that are different.
Benjamin James Kuper-Smith: Mm-hmm. If you can't tell me this, feel free to, uh, just skip this question, but, uh, so is, are you directly working right now on comparing. Physical movement to, like computer based movement or imagine movement, or is that more, um, I wasn't quite sure like how to, what you said earlier, whether this is something you're actually working on or it's more kind of an intuition based on having worked on the different parts.
Matthias Stangl: I'm, I'm not working on this particular question, so I can't really say much about it, but what I meant to say is that we finally have the techno, we as in not
Benjamin James Kuper-Smith: Yeah, yeah.
Matthias Stangl: Myself. Um, and, and maybe not our research group in general. Um, but, but you know, the whole field is now able to look at these signals and answer these questions, but it's not something that I am, um
Benjamin James Kuper-Smith: Okay.
Okay.
Matthias Stangl: Explicitly working on.
Benjamin James Kuper-Smith: I think we should probably start talking about the paper, otherwise we won't get around to it. Yeah, so I mean, I guess we've already mentioned quite a [00:42:00] lot about kind of the circumstance in terms of you're using, you, you're working with patients here who are actually moving.
But yeah, maybe as before brief summary. What did you do? What did you find?
Matthias Stangl: Sure.
Benjamin James Kuper-Smith: Um, yeah,
Matthias Stangl: yeah. Uh, so the previous studies, um, that I've done myself or in the whole field, you know, tells us a lot about, about navigation in general. Like how do we keep track of where we are, the neural mechanisms. But one thing that, that we also.
I have to acknowledge is that a lot of these studies, almost all of these studies come from, you know, neural measurements, measurements of, of brain activation that was measured in not very naturalistic environments. Not very naturalistic navigation scenarios, right? So most of the studies have, including my own, my own work.
Most of these studies, um, have been done like using virtual reality while you're actually not really moving, which is, you know, a question in itself, whether that's like, um, navigation at [00:43:00] all. Right? So. Most of people are like in hospital beds, um, while their brain activation is recorded and they do not move.
They, they, they basically play a computer game on, on a computer screen. Right? Or, or they are an EMI can, where you are kind of laying on a kind of a horizontal plane and look at a screen. So it's, it's a question. Um, how does, I'm not saying so, so a lot of the findings that come from these studies are really, really important and, and, and very exciting.
But still, we also have to see that, um. We have to, we have to ask the question to what extent this translates to actual physical navigation, to walking around in the real world, to not being in a, in a virtual environment, but being in a real room, um, maybe also with other people. That's, that's, that's another important aspect of, of, um, real world navigation, right?
You are not like playing a computer game where you drop off like a soccer ball in some corner of a virtual room. It's like, it's like you have, you have many [00:44:00] more variables. And one of this is, for example, the, the interpersonal aspect. Um, that also hasn't been addressed a lot in, in previous studies where, for example, if you, if you walk along the hallway, um, you, you know, you don't.
You do not only have to have a representation of where you are, but you also need to know where other people are in, in order to, you know, avoid running into them or these kind of things. So, so these are the two key things that we wanted to address here first, you know, um, investigate special representations and, and, and mechanisms of keeping track of where we are in the real world rather than, um, virtual reality and virtual environments.
And then also see if the same mechanisms that we use to keep track of where we are, whether the same mechanisms also allow us to keep track of where others are in an environment. It is, um, hard to study, or it has been hard to study, uh, for a very long [00:45:00] time because of, as I said, technical limitations, right?
So it's just really hard to get to this brain, um, recordings when people are just walking around in the real world. But here, when I started doing my postdoc, I, I had this really amazing opportunity to work with a very unique group of patients. I said that before. These are patients who have Chronicle implant, and this is a device that is implanted in their head, um, chronically, that means like for, for years or even decades.
Um, these are epilepsy patients. Um, who have a very severe form of epilepsy. Um, and the idea is that this device, um, this device comes with typically depth electrodes, um, that are implanted in, um, deep brain regions or in regions where their seizures might originate from. Um, which very often is hippocampus and run cortex, medial temporal lobe, which are the regions also where we are interested in a lot, um, because that's where the navigation centers are kind of, kind of located also, or many of them.
And [00:46:00] so these epilepsy patients have these electrodes with the idea, the idea is that it helps them. Um, so this device detects continuously, like 24 7, detects their, um, oscillatory activation, their brain activation in these brain regions with these electrodes. And, um, when it detects abnormal activity, then it's, then it's delivering stimulation in order to prevent seizures.
And, um, this. Helps a lot of patients that I've seen. Um, it helps them a lot. Like these patients are really able to, to, you know, go back to their jobs or have, um, very, very normal daily lives. But, so it's, it's, it's really good for them. But it's also like a very unique and great research opportunity because, because we finally have access to deep brain recordings of regions that are really essential for memory, for navigation, for all of that, while participants are, you know, doing all kinds of [00:47:00] normal daily life tasks, they can do everything.
They can just walk around and, and have a very normal daily life. The problem though is, as I said, this is a clinical system. It has been implanted, not for research, but for, um, clinical purpose. So we don't have. Easy access. It's not like you can plug in, you know, like a use B stick and, and, and get these data.
It's, it's, um, you have to work really hard. And so one of the very first things when I, when I joined this group of ANA at UCLA, one of the first things. I was involved in, um, was to develop this, um, technical platform. So that even allows us to, um, get real time recordings and also access to the stimulation capabilities of, of, of these, um, devices, which then finally in the end, really allows us to, to, to do these experiments.
So that's what I, what I said before we. Can have access to these signals, we can record them. Now is really the time [00:48:00] to think about, you know, experiments, to ask questions. Um, but there was a lot of technical development, um, necessary to get to this stage. And there is also a paper in neuron from s um, to Paulovich from our group, which basically just talks about the technical development of how, how do we do that?
And it's not, it's not trivial, but that was kind of the,
yeah,
Benjamin James Kuper-Smith: I mean, it
Matthias Stangl: sounds like the prerequisite for everything.
Benjamin James Kuper-Smith: The first half was an engineering job, and then you could do science after that.
Matthias Stangl: Exactly. Exactly.
Benjamin James Kuper-Smith: And just very briefly going back that your background in programming probably didn't know it either.
Matthias Stangl: Exactly. It, it helps, it helps with that kind of, um, stuff. And I, I mean, in, in, in our group at UCLA, you know, n like she, she manages to put together like a, a really, really awesome team of people who are, you know, like engineers and, and, and people who, who, who run experiments, who design experiments. But also there is a lot of technical development involved.
So like programmers, um, uh, electrical engineers, like literally building [00:49:00] physical devices, you know, um, it's not something that, that you do. On a daily basis, like in, um, human, you know, FMRI studies or whatever. But, um, there is a lot of technical development and engineering necessary to run these studies.
And, uh, and that's, that's what this group has done. That's what I've, um, started to do when I joined this group. And it finally allowed us to, to address research questions, which is, yeah, that was a very long introduction to get to the actual,
Benjamin James Kuper-Smith: I mean the
Matthias Stangl: actual paper. No, no worries.
Benjamin James Kuper-Smith: Yeah. So anyway, so you, uh, yeah.
So if you've got the other patients, we know what they're doing, they can move around. So what was the finding.
Matthias Stangl: What we finally were able to do is really look at these brainwaves, um, during real world navigation, during just walking around physically in a room, right? And, and, um, what we wanted to do is we wanted to see how our own location or how, how the human [00:50:00] brain during real world navigation represents location.
How do we know where we are? What are the neural representations and the mechanisms that allow us to keep track of, of, um, where we are? And one thing that we wanted to look at in particular were like theta oscillations, because it has been shown multiple times in other studies that theta oscillations is just a very prominent oscillation, um, relevant for many things, including memory, including navigation processes.
So we wanted to look at, to look at, um, how these fatal oscillations actually help us to, to keep track of where we are. And what we, what we found in this study was that when participants were walking around and we measured their brainwaves, so to say, their fat oscillations, um, while they were walking around, we found that the oscillatory power, like the amplitudes of these oscillations, um, they got stronger depending on where they were in the room.
So it basically was a representation of their location, [00:51:00] specifically. Um, Thedo Solutions had a stronger oscillatory power when you were, when participants were closer to a boundary, which in a way is a, a kind of a code for where, where we are, right, where participants were. But that was only the first part.
And the second part of this study was we asked participants to not only walk around, but also, uh, the. Different task. We ask the same participants to basically sit in the corner of the room and watch another person while this other person is walking around. Uh, which was, was me in this case, which was a very funny feeling by the way, to just walk around in the room being, being watched by someone for like an hour.
And I'm, I'm sure it was not a, not a very exciting thing for participants,
Benjamin James Kuper-Smith: but say it must have been not mu not much less weird for them.
Matthias Stangl: Yeah, no, absolutely. I, I'm not sure it, it, yeah. Who felt, um, [00:52:00] more strange. But anyways, it, it was a, it was a funny scenario, but I mean, it worked out really well because what we did find is that.
Participants used the same code to represent, um, not only their own, but really my location in this case. So they did not move at all. Um, they were just in the corner of the room, but their brain waves, their theta oscillations were modulated by, but where I was, where this other person was in the room, and this was just a really exciting finding because it was the very first time that somebody show could show that, um, you know, someone's brain activation is actually influenced by another person's location.
So, and, and, and this was a very, very strong effect. We see that in every single participant. So it seems to be like a really, a really strong, um, finding, um, that we have here since,
Benjamin James Kuper-Smith: I mean, is it fair to call it a boundary vector cell independent of. Person near the boundary or is, [00:53:00]
Matthias Stangl: um,
Benjamin James Kuper-Smith: I mean, I'm not entirely sure what the definition of boundary vector cell exactly is.
Um,
Matthias Stangl: yeah.
Benjamin James Kuper-Smith: But
Matthias Stangl: I see, um, so I, I would not call it like that, but it doesn't mean it's wrong. It's, it's po it's, it's one possibility, but at the same time, the signal that we measure here stems from, you know, like many, many cells, like again, populations of cells.
Benjamin James Kuper-Smith: Right, right. It's, uh, to clarify, you're using, uh, intracranial, EEG, not
Matthias Stangl: Yes.
Benjamin James Kuper-Smith: Uh, single
Matthias Stangl: cell, single cells depth
Benjamin James Kuper-Smith: coating or whatever. Yeah, yeah,
Matthias Stangl: exactly. Exactly. Yeah. I should have, um, mentioned this more clearly, but it's, it's population. It's, um, it's local field potentials probably, um, from, um, many, many cells together. So it's the sum signal of many cells. And, um, it's possible that this, um, signal comes from, you know, like it, it has been shown.
There are what you said, um, boundary vector cells or there are border cells, but there are also other possibilities. It's possible that it comes from play cells, which also it has been shown that play cells tend to [00:54:00] cluster around, you know, more boundaries or maybe like objects. And this is another possibility that the, the walls that we have used, not that we used the walls of this room in this experiment, right there were just.
Things on the wall. There were visual signs on the walls. There were, there were also things like, you know, like a wifi router or something like that. It could be, that's actually these objects in the room that were driving this response. We are not sure whether it's exactly the boundary per se or that it's something that is like on or near the boundary.
So, so I wouldn't go as far as saying it's boundary vector cells. Um, but it's, it's obviously, it's obviously, um, reasonable to assume that this contributes to the signal, but with this kind of population level signal, it's kind of hard to disentangle and really say what cell type is driving. That's something for, you know, then again, maybe going back to, um, single neuron [00:55:00] recordings in, in, in stationary participants.
Like this is done. For example, also in in epilepsy patients while they're in the hospital bed, you can get access to single neurons, um, which would be a very exciting next step to do that. Or hope for, um, another key technical development step, um, which would, you know, uh, hopefully at some point allow us to get not only intracranial, EEG, but really single neuron recordings.
Um, while participants are walking. And I know that there are people working on this and I know that, that hopefully soon we will have access to this data and then we can really, you know, pin this population level finding down to specific cell types. Also be more specific about brain regions, these kind of things.
Benjamin James Kuper-Smith: Maybe I'm curious, was the initial plan of this study to start also with the someone else moving in the room? Because it seems like, you know, there's this huge kind of [00:56:00]technical setup to get this to work and, and then you kind of did two things, right? You did the one thing is the people moving through the room, and then in the same study you also did, watching someone else move through the room, was that kind of planned from the beginning to not just do, I mean quotation marks, just um, so to not just do.
The one of the first, I dunno, is this the first study to have people moving freely get recordings? No. Okay.
Matthias Stangl: No, it's not, it's not the very first. Um, so there, there has been work, for example, from, um, it was Sarah Han, um, also in this lab. So I would say it's fair to say that this lab, not the lab, but UCLA is, uh, one of the pioneering labs where this has been done.
But the study that I, that I was involved in here, um, was not the first one. So it has been shown, for example, that, you know, um, movement speed is modulate or movement or that fat oscillations are modulated by movement speed when you have physically moving and that has been shown, um, in
[00:57:00] humans.
Matthias Stangl: In humans Exactly.
With, with a very similar setup. The setup gets better and better though. So we are now able to really, you know, even, even, um, as a next step, even, you know, go outside, walk in, like in the real outside world, you know, outside the lab and, and, and so it's get getting better and better. Um, and also there were some, some, some improvements in my study compared to what has been done before.
And there are also new improvements for future studies. Yeah, I also, yeah, and actually to, to answer your question, so it has been done before, um, so this time it was not only the focus to, to have someone, you know, walk around and measure their brain activation. It was really the key idea to compare spatial representations between self navigation.
And when you keep track of another person to basically answer the question of do we use the same mechanism, um, to keep track of where we are [00:58:00] and where others are? Or, um, how are the parallel is, how are the differences? Um,
Benjamin James Kuper-Smith: by the way, is the signal equally strong for self and other, or like what's the Yeah.
Relationship there?
Matthias Stangl: It's, it's not equally strong. I mean, it's also, again, you know, it's not a very fair comparison because when you're walking around, um, there is a lot more involved. Like, you know, you have this motor activity and all of that. So it's, it's not a completely fair comparison, but what we see is that the signal when you observe someone else is typically, you know, um, there is more variability.
Plus one fi finding of this paper is also, um, that you do not see exactly the same, um, frequencies that, that, um, play a role during self navigation compared to observation. Because, um, that's shown in the paper is that when you, when you walk around yourself and basically, um, your brain activation is modulated by your own.[00:59:00]
Location in the room. We see that this effect is, um, is happening on a pretty broad, um, frequency. Bandwidth, like around say three to even 12 hertz. So we do see the same effect also when you keep track of someone else, but we see that it, that the frequency band where we see this effect is narrower. We see that here, um, only in around like five to eight herts.
So. It could be now that the difference comes from the fact that in one case you're moving, in the other case you are, you are sitting. But it could also be that it's, you know, um, just a qualitative difference or, or just because the signal is maybe weaker, um, when you're keeping track of somebody else.
It's, it's something, um, also that, that, um, are good questions to address in future studies. Um, and we are not exactly sure where that difference come from, but we do see, um, we do see this difference. So it's not an identical signal and it's also not a, [01:00:00] not exactly the same strength.
Benjamin James Kuper-Smith: Yeah. Okay. It, it seems to me, uh, as if you've.
Kind of found something you really enjoy and a place that you like being in. But postdocs positions tend to not be unlimited. Uh, so kind of what's the, what's your plan there is, uh, yeah. Do you have lots of time to do more studies or is it a kind of thing where you have to like stop in the middle of it and let other people do that?
Matthias Stangl: Um, so yeah. So, so first of all, um, you, you, you, your guess is very right. Like, I, I really like where I'm now, like, um, this lab is really fantastic. It's, um, it's, it's great. People like na, the Pi, she's, she's really great and the opportunities. We have here a unique, really awesome, um, so yeah, it's, it's, it's just a really, really good place to do science and, um, I would like to, to stay also, I think we're in a good [01:01:00]position in terms of funding, um, so that we can continue with this line of work.
Um, so it seems what we do is interesting enough for, for many other people and funding agencies that, um, we hopefully get, and it, it looks, it looks good. Um, so. And, and also for me personally, it looks like I want to, and I will hopefully be able to continue this line of, of, of work and, you know, this was really a first step, like first the technical development and then, um, looking into, you know, this, this boundary related,
Benjamin James Kuper-Smith: say my first step at.
I don't think it's gonna lead to a nature publication.
Matthias Stangl: Yeah. It's a good
Benjamin James Kuper-Smith: fast step.
Matthias Stangl: You never know. You never know. I, I wouldn't have, I wouldn't have expected to. See, I'm looking forward
Benjamin James Kuper-Smith: to your second step. That's good.
Matthias Stangl: You know, from, from here, it can only go downhill, basically. So that's the other thing. No, but, um, no, but yeah, this, this was very exciting.
But I mean, you know, so many things came together. Like NAIA is like a, a really fantastic mentor. Um, the [01:02:00] opportunities we have here are just really great. Literally every single person in this lab is, is just really, really good and really, really nice. So, so that's pretty amazing. And, and, and, you know, just having these opportunities to work with these participants who are also really, really great.
They really want to do this. They really want to help us, um, doing this work. So it's a, it's just a very exciting place to be. Um, but I also think this is the secret recipe. Um, for why these things really work out. Right? Um, so having such a team, having such, such a pi, having, um, having all of these resources really makes it, makes this possible.
And then, um, yeah, of course we were also, we were also not expecting this to be so, so strong and so exciting, but yeah, maybe a bit of luck in Wolf as well.
Benjamin James Kuper-Smith: Yeah, I mean, I guess we kind of, I had like one question which is related to some of the stuff we've [01:03:00] mentioned, and I guess you've kind of. Indirectly alluded to by mentioning that funding right now is working well and people seem to be liking this stuff.
So, I mean, it's been now what, almost a year since you've had a first author publication in nature. So what's that like? Is it, I mean, for me, nature's always the, the most prestigious journal. Um, I think for me, a fairly clear number one and, uh, so I dunno, is it as good as you expected or, I don't know. Yeah.
What's, what's it like?
Matthias Stangl: Ah, that's a, that's a very good question. It's, um,
Benjamin James Kuper-Smith: I'm assuming I'll get there multiple times, but, you know, so what should I expect?
Matthias Stangl: So. It was, it was a, an incredible learning experiment experience for me. I, I have to say though, that the experience publishing in this journal was not, was not essentially different to, to other journals.
It was like, you know, the current biology paper, um, was al also very well [01:04:00] received. And, and, and, and I, I really love that paper and so it's. Uh, I don't know what to say. It was, it was just, I, I, I felt, I also felt it's more pressure to be, to be very honest, um,
Benjamin James Kuper-Smith: because to have had, to have that, to be a person who's published in it or to
Matthias Stangl: try and get it
Benjamin James Kuper-Smith: published
Matthias Stangl: Yeah.
To try and get it published in, in such a journal, because, you know, once you, first you submit it there and you just hope that people like it, you know? But at some point you get reviews and then you realize, okay, well there is an actual chance to, to squeeze it in there.
Benjamin James Kuper-Smith: It's like, oh no, don't, don't mess this up.
Matthias Stangl: Exactly. Yeah. And I mean, I, I, I worked like, this was, this was actually during COVID time, so I worked in home office literally like 24 7 to work on these reviews and to work on everything the reviewers wanted to see. And, you know, so it, it was a lot of pressure, but, but it was, at the end of the day, obviously, it was a very exciting experience.
Um, [01:05:00] also very re rewarding. Um, there was a lot of attention also after we, after we published that paper. Um,
Benjamin James Kuper-Smith: I mean, that's how I found out about your research, right? Like even the other stuff that we talked mostly about today.
Matthias Stangl: Yeah.
Benjamin James Kuper-Smith: I hadn't read that actually until then. Yeah.
Matthias Stangl: Yeah. Yeah. No, I, I, I agree. But also I think I.
I'm not sure, um, to what extent this is like, about the journal. Um, I think, I think what we, what we did here was just really, really, um, exciting for many people because what I said, it's, it's, it's basically the first time, um, or it's maybe not the first time, but it's one of the first times where we can have.
Brain activation, um, measured in participants while they're just walking around. And then we can have brain activation for, you know, like when you are in a more like, um, social or interpersonal context where you keep track of somebody else. It's just questions that, that are just really many people are probably [01:06:00]interested in.
But, um, based on so many limitations, you can't really address them very well with, um, or it wasn't really possible before. And so I think the novelty of this, um, and then obviously the findings were also really new, really exciting. Um, so I think that that, um, caused a lot of attention just based on what we did and not only where it was published, but yeah, obviously it's, it's also for me as a early, early career, it's, it's a, it's a good thing.
Benjamin James Kuper-Smith: Uh, I just saw on. Some UCLA website. There was a, just like a little profile about you or something like that. And I'm not entirely sure what it was, but there was a, one of the sentences, um, we're just gonna read it, said he has established collaborations with the National Aeronautics and Space Administration, NASA and the European Space Agency.
What's it called? Essa isa, I dunno. And serves as a co-investigator on prestigious projects to characterize neurocognitive consequence of space flight and astronauts, and [01:07:00] identify neuro behavior risks associated with future exploratory space missions and their mitigation. Uh, so, you know, you, you have a meeting to attend, but can you say like, in one minute, what's, uh, what's that, what's, what's going on
Matthias Stangl: there?
Oh, yeah, yeah, yeah, yeah. It's kind of, it's a little bit independent, but, um. Yes. Also very exciting work. Um, so that's mainly, mainly, um, I was asked by Alexander Stan from who, who originally was at, um, cite in Berlin and now is at the University of Pennsylvania. So we want to look at, um, how spatial representations change, for example, in, in extreme conditions, like for example, when you are in isolation.
Um, and so we're working on that. Um, so they're responding from ISA and um, and NASA to look at, you know, um, astronauts, you know, they're typically isolated from the rest of the world when they're in space. And so this can be both simulated on earth. Like there are, they are like for weeks, um, in isolation.
And we just wanted to [01:08:00] see how that changes. Um. How that changes spatial representations and your whole, like, you know, perception of space and, and how you keep track of where you are. And we, we do the same thing also with astronauts at the International Space Station. So we basically, so a lot of things change when you are in space.
So when astronauts come back, a lot of things, um, are not exactly the same as when they left. And, um, I am particularly interested in looking into, um, you know, their spatial, um, representations and how, how this changes, um,
Benjamin James Kuper-Smith: from kind of having moved in 3D kind of. Oh,
Matthias Stangl: exactly. Yeah. It's just, it's just a very, yeah, we, we can also see that, um, so this has been done, this, this was not by me, but it has been shown al already that, for example, being in space, you know, it has physiological consequences to your body.
And one of the cys, for example, that, that you see, um, physiological changes, changes in the hippocampus, for example. And, [01:09:00] um, and so it makes sense to, and, and obviously, you know, your whole spatial perception and, uh, your whole experience being in space is different when you are in actual outer space. So, so, um, so it makes sense to, to look at how this impacts, um, spatial representations and actual astronauts are just in these, in these very extreme conditions.
Benjamin James Kuper-Smith: Yeah. Okay. Well that. Sounds are very exciting. I think at some point I have to have you back to talk about your paper, about the Neuro Correlates movement in space or something like that.