Ricky Patel is a postdoc at Lund University, where he studies the neural basis of navigation behaviours in arthropods. In this conversation, we talk about his work on spatial navigation in Mantis Shrimp and bumblebees, the difficulty of recording from moving insects, science communication, and scientific illustrations.
BJKS Podcast is a podcast about neuroscience, psychology, and anything vaguely related, hosted by Benjamin James Kuper-Smith. In 2022, episodes will appear irregularly, roughly twice per month. You can find the podcast on all podcasting platforms (e.g., Spotify, Apple/Google Podcasts, etc.).
Timestamps
00:04: What is a Mantis Shrimp?
09:53: How Ricky started studying Mantis Shrimp navigation
16:00: Start discussing Ricky's 2020 Current Biology paper on path integration in Mantis Shrimp
25:03: A hierarchy of compass cues
34:10: Start discussing Ricky's 2020 Proceedings B paper on landmark navigation in Mantis Shrimp
38:11: Complex behaviour doesn't require a large brain
40:16: Start discussing Ricky's 2022 Current Biology paper about path integration in walking bumblebees
46:14: How well can we record neural activity from moving insects?
49:54: Twitter in academia
53:51: Rickesh's work as a scientific illustrator
57:57: There really has been a rich history of studying navigation in non-mammals
Podcast links
Ricky's links
Ben's links
References
Beetz, Kraus, Franzke, Dreyer, Strube-Bloss, Rössler, Warrant, Merlin, & El Jundi, B. (2022). Flight-induced compass representation in the monarch butterfly heading network. Current Biology.
O'Keefe & Dostrovsky (1971). The hippocampus as a spatial map: Preliminary evidence from unit activity in the freely-moving rat. Brain research.
Patel, Kempenaers & Heinze. (2022). Vector navigation in walking bumblebees. Current Biology.
Patel & Cronin (2020). Mantis shrimp navigate home using celestial and idiothetic path integration. Current Biology.
Patel & Cronin (2020). Landmark navigation in a mantis shrimp. Proceedings of the Royal Society B.
Patel & Cronin (2020). Path integration error and adaptable search behaviors in a mantis shrimp. Journal of Experimental Biology.
Santschi (1911). Obervations et remarques critiques sur le mécanisme de l'orientation chez les fourmis. Rév Suisse Zool.
Tolman (1948). Cognitive maps in rats and men. Psychological review.
Wehner (1990). On the brink of introducing sensory ecology: Felix Santschi (1872–1940) — Tabib-en-Neml. Behav Ecol Sociobiol .
Ricky Patel is a postdoc at Lund University, where he studies the neural basis of navigation behaviours in arthropods. In this conversation, we talk about his work on spatial navigation in Mantis Shrimp and bumblebees, the difficulty of recording from moving insects, science communication, and scientific illustrations.
BJKS Podcast is a podcast about neuroscience, psychology, and anything vaguely related, hosted by Benjamin James Kuper-Smith. In 2022, episodes will appear irregularly, roughly twice per month. You can find the podcast on all podcasting platforms (e.g., Spotify, Apple/Google Podcasts, etc.).
Timestamps
00:04: What is a Mantis Shrimp?
09:53: How Ricky started studying Mantis Shrimp navigation
16:00: Start discussing Ricky's 2020 Current Biology paper on path integration in Mantis Shrimp
25:03: A hierarchy of compass cues
34:10: Start discussing Ricky's 2020 Proceedings B paper on landmark navigation in Mantis Shrimp
38:11: Complex behaviour doesn't require a large brain
40:16: Start discussing Ricky's 2022 Current Biology paper about path integration in walking bumblebees
46:14: How well can we record neural activity from moving insects?
49:54: Twitter in academia
53:51: Rickesh's work as a scientific illustrator
57:57: There really has been a rich history of studying navigation in non-mammals
Podcast links
Ricky's links
Ben's links
References
Beetz, Kraus, Franzke, Dreyer, Strube-Bloss, Rössler, Warrant, Merlin, & El Jundi, B. (2022). Flight-induced compass representation in the monarch butterfly heading network. Current Biology.
O'Keefe & Dostrovsky (1971). The hippocampus as a spatial map: Preliminary evidence from unit activity in the freely-moving rat. Brain research.
Patel, Kempenaers & Heinze. (2022). Vector navigation in walking bumblebees. Current Biology.
Patel & Cronin (2020). Mantis shrimp navigate home using celestial and idiothetic path integration. Current Biology.
Patel & Cronin (2020). Landmark navigation in a mantis shrimp. Proceedings of the Royal Society B.
Patel & Cronin (2020). Path integration error and adaptable search behaviors in a mantis shrimp. Journal of Experimental Biology.
Santschi (1911). Obervations et remarques critiques sur le mécanisme de l'orientation chez les fourmis. Rév Suisse Zool.
Tolman (1948). Cognitive maps in rats and men. Psychological review.
Wehner (1990). On the brink of introducing sensory ecology: Felix Santschi (1872–1940) — Tabib-en-Neml. Behav Ecol Sociobiol .
(This is an automated transcript that contains many errors)
Benjamin James Kuper-Smith: [00:00:00] Yeah. I mean, as I told you before, we started recording, very interested in space navigation, not really for my own research, but kind of just something I'm really interested in. And I've had a few guests and they all come from the road and human research directions or approaches or whatever. And, uh, so I'm really looking forward to today to talk to you about the very different kind of species.
Uh, one that I've never, I mean, all of the, I mean the species is Manchester. All of the Manti shrimp papers for special navigation, I've read are yours. Um, yeah, I thought we could maybe start by just outlining or have you maybe briefly explain what a Manti shrimp is because, uh, I mean it's shrimp, so I'm assuming it's in water.
Um, we're quickly ending. the things I know about mantis rivers. So maybe can you, yeah, just give a brief, I dunno, like.
Rickesh Patel: Sure.
Benjamin James Kuper-Smith: Where might I find them? What do they do? Yeah. That kind of.[00:01:00]
Rickesh Patel: NA shrimp, uh, they're wonderful animals. Uh, they're CTAs, like, as you might guess from the name, they're actually not really a shrimp, but that's, that's a whole nother thing. It's, they're kind of.
separated from depo crusta, which are shrimp and crabs. their own little group. Um, but these animals are really cool.
They're predatory CTAs and they live mostly in tropical areas worldwide, but they can, uh, be found in some temperate regions as well. It's a pretty
Benjamin James Kuper-Smith: Such as like,
Rickesh Patel: so for instance, you can find them the tropics, but I grew up in Southern California and we have, uh, species that lives the Southern California coast, um, on the east coast of the United States.
There's also species that can be found as well in the Mediterranean we have, uh, Manda shrimp species. they can be found, you know, on the coast of Japan. So they're, they're pretty nicely spread worldwide in, in, in oceans. So they're only found in seawater, um, and these animals. They're best known for two things. thing is that they're very aggressive animals [00:02:00] and they had these appendages, these, uh, these raptorial appendages they're called, which are things that use to either smash things open or disappear things. Um, so they're predatory and they there's these two classes, uh, so they can, they, there there's a range of sizes for these animals.
They can be really tiny, maybe like,
half the size of your little finger up to the size of your whole, for. So there's a, there's a, quite a
Benjamin James Kuper-Smith: So how big are
Rickesh Patel: range
Benjamin James Kuper-Smith: That's a big shrimp. Yeah.
Rickesh Patel: these animals. Yeah. uh, these two classes there's Smashers that use their, uh, their arms, like hammers that will find shells or crabs or other things and smash them open. With an incredibly powerful strike. the acceleration of this, uh, of this smash is, can match that of a caliber rifle, bullet being fired. Um, so it it's extremely powerful. then there's the other class of man shrimper called Spears. And if you look at the, raptorial appendage, this arm, [00:03:00] it looks like a big. Spearing thing with a lot of barbs in it. And what they'll do is they, these animals, they live in holes in the sea floor environment. And, uh, these Spears will just sit inside their burrows and look for fish to pass by. And when they see one they'll go up and just spear the fish and pull it back into their burrows and eat them. So they, they they're only predatory, but they do a really good job at hunting and finding their prey
Benjamin James Kuper-Smith: Nice.
Rickesh Patel: very
Benjamin James Kuper-Smith: Okay. They, they eat. Anything that's smaller than them, or, I mean, do you mention snails fish? Uh,
Rickesh Patel: Yeah. Anything that they can catch that is smaller or even approaching the same size as them. So I've seen shrimp kill things that are about the same, same size as them, uh, like crabs or other shrimp, or, yeah. So that's, that's one, that's one thing that they're really well known for. the other thing that they're really well known for are their visual systems. So they have these really wonderful eyes. They have eyes stalk, their, [00:04:00] their eyes are on these stalk that are on their head they can, uh, move their eyes independently from one another. So they will twist their eyes. They'll move them around, up and down. And generally what they do is if you watch a mag shrimp, you generally see its head poking out of its burrow and its eyes are scanning of its environment. And like I said before, their eyes could be looking at different things independently, soon as something interesting, Passes their field of view. They usually have both eyes snap together and follow this interesting thing in their, their visual space. Um, so their eyes are really interesting because they have depth perception of just one eye.
So they have three parts of their, of each eye where they can estimate the field of view of something. Um, but they also have. A wide diversity of photoreceptors and these are the cells that are responsible for perception of specific information. So like colors and also something that we can't perceive.
But most animals, since most animals are not vertebrates, Uh,
can see and that's [00:05:00] polarized light. Uh, so man shrimp have the greatest diversity of these preceptors out of any animal in the. So they can see far into the UV and far into the, quite far into the reds as well, approaching like the very closest range of far red. Um, so they had this yeah, really nice diversity of spectral channels and they can see polarized light as well.
Benjamin James Kuper-Smith: I'm curious. I mean, you mentioned they have depth perception in each of their eyes. So when they find something they find interesting, but they, they still use both eyes to look at them. Is that just, I dunno, to get two slightly different perspectives on it or because, I mean, I guess usually like, I guess with other predator, animals use both eyes to get depth perception.
Right. But if they don't need that, um, is it yeah.
Rickesh Patel: Yeah, well, to tell you the truth, I don't know how accurate, um, a single eyes depth deception versus having two eyes might be it, it it's better to estimate these sorts of depth information, or they can better track their prey if they use both eyes. not really quite sure why, um, they do this, but they do.
If something [00:06:00] interesting passes their field of view, they usually do like both eyes will snap onto that. And in the. There's a certain region, same as our eyes that have higher acuity or like, uh, resolution than the rest of your eye would have.
Benjamin James Kuper-Smith: yeah.
Rickesh Patel: And in Manti shrimp and in most, uh, animals, there's an area of the compound eye that has higher acuity as well. it's perhaps to keep the high acuity vision in, in, uh, in both their eyes as
Benjamin James Kuper-Smith: Yeah.
Rickesh Patel: Yeah.
Benjamin James Kuper-Smith: Okay. I mean, one thing I'm curious about, so you, in one of the, uh, I think this might be your current biology paper that we'll talk about in a bit more detail in a second. Um, I think you mentioned the beginning that there hadn't really been any. Study of path integration in purely aquatic animals until your matters from paper.
And that, that was kind of interesting. Or that, that, that aquatic animals are interesting in that regard because visual cues are much harder to use because you can't see as far as you can on land or these kind of things. And I know this just makes me wonder, like, if. I dunno if it is harder to see [00:07:00] underwater, uh, I mean this almost a silly question, but like why do they have such amazing eyes?
If, uh, you can see less in the environment they're in
Rickesh Patel: Yeah,
Benjamin James Kuper-Smith: or, you
Rickesh Patel: that's
Benjamin James Kuper-Smith: know,
Rickesh Patel: question. So, um, So Manda shrimp, most species live in fairly shallow water, uh, and fairly shallow tropical water. It's quite clear water. So it is still the visibility. Isn't And you have a good amount of spectral formation in very shallow coral reefs where you can often find
Benjamin James Kuper-Smith: So very shallow means, uh, what, like what humans could stand in or what does shallow mean in the cause the sea can go very deep. Right? So
Rickesh Patel: Yeah.
Benjamin James Kuper-Smith: yeah.
Rickesh Patel: So shallow water. I mean, farther than people can stand in, I would say, but maybe within diving range, regular diving range from like 30 meters depth and then even shallow air. And in these very shallow reefs in like, which you could probably swim and just free dive a couple meters down to a lot of managers from species live in this kind of range as well. Um, so the Nu the other thing that I haven't told you about magic shrimp is that many [00:08:00] species are also flamboyantly colored. Um, so you might see that there's colorful structures on their bodies. Since man shrimp are so aggressive, they're actually quite territorial over their homes, these boroughs as well. And, uh, man shrimp will make these visual or signals to one another where they have, for instance, one, one, uh, that they all do is they do this threatening response where they lift both their smashing arms and they show the inner sides of their arms and in the inner sides of many species. There's this circular, um, pattern like an IPO kind of, um, and in different species, they that have a bright color.
So my species I use mostly for the papers we're gonna talk about had this bright purple, IPO surrounded by a white, uh, ring. They will show this at one another or at me like I've had net shrimp show me this as well as like a threat, kind of to follow you around and show you their arms like this. Um, so, so it can be really important to be able to communicate, to show intention, especially when you have weapon. that may be, uh, destructive
Benjamin James Kuper-Smith: Hmm. Okay. [00:09:00] This now makes me think of a very important question. Have you ever been attacked by a Amanda shrimp? . Okay.
Rickesh Patel: been smacked a couple times by magic shrimp. They've both been kind of grazes one time. I had a fairly thick glove on and they hit me in the, in the finger and it SW up a little bit, uh, on the other time, I was also struck on this very side of my, uh, index finger. And even though it wasn't a direct hit my fingers, SW a good amount. Uh, I have had a, I have a colleague that had got hit in the center of their, of his thumb and blood just poured down his arm after that.
Benjamin James Kuper-Smith: Nice.
Rickesh Patel: so, so it can
Benjamin James Kuper-Smith: okay.
Rickesh Patel: Yeah.
Benjamin James Kuper-Smith: Okay. Yeah. I never thought that working with shrimps would be that dangerous, but I guess they were,
Rickesh Patel: If it's a,
Benjamin James Kuper-Smith: um,
Rickesh Patel: then maybe
Benjamin James Kuper-Smith: yeah, yeah, yeah. Okay. Um, yeah. Getting to, to the actual papers you wrote in the research we've done on spatial navigation. Um, I mean, yeah. Why use man shrimp for this though? I mean, [00:10:00] so that you.
Investigating path integration, which we can explain in a second, maybe, but yeah, I'm just curious, like why this particular species for this task, is it just as you were working on the species and thought this would be cool experiment or is a.
Rickesh Patel: Yeah. I mean, it was, that's a good question. Um, so it actually kind of happened by accident, really? Um, so when I started my PhD, I had an idea. So I was interested in how complex physiology evolves. And I was thinking about doing some sort of project like this. So while I was collecting man shrimp in the field, I noticed that they seem to have a really great spacial awareness of their surroundings.
Like when you try to catch them, they won't always run away from you. Sometimes they'll run, even an angle, somewhat towards you to the nearest cover. Um, and I just, I guess just seeing this while I was collecting magic shrimp as like, Starting off PhD student made me think about, well, how are they doing this?
How do they keep track of their surroundings? And was never someone that ever thought about navigation or spatial [00:11:00] orientation before, but I don't know. I just thought that was interesting. And I started devising like little experiments where I made these arenas and it was all really exploratory to begin with.
And I never even thought about really path integration, uh, until the data started kind of showing me that these are the questions I should be asking. Um, so I guess I could talk more about like how this, uh, happened if you want, or unless you have a very specific
Benjamin James Kuper-Smith: Yeah. Yeah.
Rickesh Patel: Yeah.
So, um, so after I kind of noticed this and started having these ideas, the species that I worked with, um, I work with they're, they're found they're the closest man shrimp species that are, that were available to me.
So I did my PhD. At the university of Maryland Baltimore county. So this is on the east coast of the United States, not too far from Washington DC, right outside of Baltimore. And, uh, in the Florida of the keys, that's the, that's like the closest Caribbean you can get to from, um, Baltimore. Uh, there's a species of very shallow water magic shrimp called neon D [00:12:00] swords die.
That the species that I work. They're about the size of your index finger. That's how big they can get to. They can just from between half that size to about that size and, uh, these animals, they live in a really shallow water. They live in rubble or sponges, really? Anything that you can have little holes in. They spend most of their day in these holes where they safely conceal from their predators and they're just looking out in their environment. every now and again, they do have to leave for hunting, for instance. So they'll leave their burrows and hunt and, it's presumed that they would get back to them again, but we didn't really know this.
So I've some of these animals and I built these circular arenas, which are just these baby pools are about a meter and a half in diameter. I filled them with sand. Then I made these artificial burrows out of PVC pipe and I put them in, in the arena I stood them up. So that way the burrows were hidden from view, uh, because like the rim of the burrow was about the co plainer with the surface of the sand. So [00:13:00] if the animal is away from it, it couldn't necessarily see its home. It'd have to find it by some other means. Um, so I put this borough there and then I included a landmark right next to. And then I put the animal in and I wanted to see if it would be happy living in this little borough in this environment. it did it adopted it really quickly. So that was really nice. Uh, and then I wanted to see, okay, well, what happens if I put some food in the arena, will the animal actually like to go and find the food? Um, and man shrimp, they don't really like being out in the open very much. They prefer being near edges and under rocks and things like this.
But if there was no rocks available, like would they just hug the wall of the pool or would they eventually find the. So I got some snail shells and I stuffed it with pieces of like white leg shrimp, like what people eat. and I put them the center of the arena I, uh, that the man shrimp would eventually leave the burrows. kind of would walk around and I would do this thing, uh, where they, they have, uh, So man shrimp head, what it looks like are two big eyes. And then they have a couple, uh, projections below [00:14:00] their eyes. called N antenna and tens. There's two pairs of these things, but the tens the parts of their bodies that they use for chemo sensation. So you'll so you could see that they'll come outta their
Benjamin James Kuper-Smith: Smelling or
Rickesh Patel: yeah,
Benjamin James Kuper-Smith: basically okay.
Rickesh Patel: Yeah. So they'll, they'll flick their intens, like, and that's kind of like analogous to us, sniffing, you know, sampling their environment for any chemicals. see them kind of flick their intens, move a bit, flick it again, and eventually find the food. Um, and I found that once with the landmark there, when they found the food, they would get the food and then just make this really beautiful quick path back to the home. So they made these really slow tortuous, twisty paths away from the home to find the food. And once they found the food, they made a nice straight path back to the burrow once more. Um, so that was really cool. That was maybe one of the most exciting parts of my PhD was seeing that this thing actually kind of worked and there was okay.
there's a system here that I can actually work with and I can figure out, well, how are they doing this? [00:15:00] Um, so that was like how the whole, this whole thing started.
Benjamin James Kuper-Smith: Yeah. I mean, one, one thing I always found interesting that's in, in both your current biology paper and in the proceedings B paper, I think you have this phrase that might. Torturous path to the food. I was just curious, like, what do you want, what does that exactly mean? Um, but torturous, does that just mean,
Rickesh Patel: Twisty
Benjamin James Kuper-Smith: uh, okay.
To say it doesn't mean like, they, it sounded like there were like a, I don't know, like a, like a hero in a fairy tale or something where they had to like, overcome huge barriers or fight off other things or.
Rickesh Patel: You know, uh, sometimes how long it takes the animals to find the food. It feels like that, right. It's just like featureless environment and they're just searching and searching and searching. Uh, sometimes it could extend for a while to like half an hour in this little space, before finding the food.
But even after that, once they find the food, they'll make a straight direct path back.
Benjamin James Kuper-Smith: Yeah. I mean maybe do you wanna then, um, just briefly [00:16:00] kind of describe kind of the main findings from the current biology paper. So.
Rickesh Patel: So after, after the story, I just told you, I found that even without this landmark around the mag shrimp, even after finding the food will make a nice, really straight path back either to the home or near the home they make this straight line, but once they get close to the home, they will stop and they'll turn and then they'll make these or that are composed of these loops that. Seemed to increase in size over time before finding their home eventually. So even without the landmark, they were still finding the home. Uh, and this made me wonder, okay, how exactly are they doing this? Um, so this is the paper that you're talking about now, the current biology paper. um, I found that they use path integration to be able to locate their homes. What path integration is, uh, in human navigation terms like sailors, they call this dead reckoning. But what this means it's this is called vector navigation, where, when an animal has some sort of interesting place in their environment. for the [00:17:00] Manchester shrimp, they'll be their borough. That's a reference point for their navigational system.
And when they leave their reference point, their home, will continually monitor both the angles that they turn and the distances they travel and all those angles to continually update. Where they think their home should be. And this is the straightest path back to. Reference location back to their home. So if, uh, so if they're continually integrating both the turns they make and the distances that they travel along, these discrete directions, then calculate at any point in time, the most direct path, both direction and to get back to where they started again. And this is called path integration. Uh, So.
this is adding up all these vectors to be able to calculate this direct vector vector back.
Benjamin James Kuper-Smith: Yeah. And I mean, like in the, the literature I'm familiar with, with rodents, I mean the, the, one of the earliest studies of, um, yeah, one of the like integral studies by, um, Edward Tolman, he kind of used this with rats to figure out [00:18:00] whether they did this and they had this like, Um, what was it? Um, I can't remember right now off the top of my head, this specific example, but basically they figured you figured out that rats could use shortcuts.
So they have to like use a kind of so way. And then once they realize like, oh wait, there's a shortcut. So this kind of again is kind of like some sort of evidence that they, they know, like, uh, yeah, just where they are relative to where they came from. Yeah. I mean, it's just like a it's , it's funny because it's like just such a fundamental aspect of, uh, life, you know, when you walk somewhere, you know, like, oh, I can just walk that way again and then I'll come back to where I started off, even though it's not the way I came there first.
And I guess you kind of, to some sense maybe or path integrations, let's say very useful for that.
Rickesh Patel: Yes. Yeah, yeah, And I think different animals have different, uh, resolutions for how accurate they can be while path integrating. But yes, it, it is something that many of not [00:19:00] most animals have some at least basic sense of, uh,
Benjamin James Kuper-Smith: Yeah. And by the way, do you know if has this been done and I guess not, but has this been done in Phish or something like that? I don't know. It seems like it would've been, but.
Rickesh Patel: No, not that I know of at least. Um, no. And I think, uh, so a good example of an animal that can, that's been studied for a while that really does this extremely well, resolution than any vertebrate that I know could ever do. these, uh, small desert ants that live in the Sahara desert and they all travel hundreds and hundreds of meters, like up to kilometers, kilometer away from their nests in this featureless environment and be able to. Back to their nests again, using these straight line paths, um, and for an animals like these like magic shrimp, too, that to be able to do this, you have to have some sort of, some sort of directional sense, some sort, some sort of way of estimating the angles that you turn and some way of estimating the distances you travel.
So you have to have a biological odometer and a biological compass of some sort. Um, and [00:20:00] I think it depends on which you use. You can be quite accurate with it depending. How you do this. Exactly. And if you use something like your vestibular system, maybe you might not be as accurate as if you were using some sort of stable structure in your, in your near environment.
Like the sun, for instance, that's a lot more predictable.
Benjamin James Kuper-Smith: Yeah, exactly. I mean, one thing I was curious about is that, I mean, maybe we're to mix up the papers now is that, um, I mean, one thing you show in the car paper is that man shrimp used the sun, um, to, I guess, correct their path integration or as a. Yeah, they kind of use the sun to, to do path integration, let's say.
Rickesh Patel: Exactly.
Benjamin James Kuper-Smith: um, and then you have this other paper in proceeding speed where you say, um, they are also can use landmarks. Right. Um, which is, uh, in a way like a very standard kind of, uh, two different ways that animals can use to navigate. And usually I don't, I mean, I, don't not an expert in this field, but I feel.
Everything I've read species can do both. I think , [00:21:00] I'm not sure. Um, but one question I had was like, do they, is the sun just at den? Right. Yeah, Yeah,
Rickesh Patel: yeah,
So, so when I talk about landmarks, I think of them as some sort of marker that can mark a specific on the planet. So it's a, it's a place it's a positional marker. Well, the sun. well, it can never be this because it's at least to something that's earthbound seems instantly far away, it can give you a direction, but it can't really give you a position on, on the planet. Does that make sense to you?
Benjamin James Kuper-Smith: yeah. Yeah. That's a fair point. It's not something you walk. And then you go like, okay, I'll walk until the sun. And then after that I go left.
Rickesh Patel: Yeah,
Benjamin James Kuper-Smith: Um, yeah. Okay. I guess that's, that's a good way of differentiating it. Yeah.
Rickesh Patel: no matter how, how many, how long you walk towards the sun, it will not look different. Right? It will look the same if as if, if the sun stayed in the same place in the sky, can never ha walk towards it and have it grow larger while with landmarks, you can, right? So this gives you, this can give you information of where to go.
Exactly. [00:22:00] A landmark can while the sun can only give you a directional information. So in this way, it's a good compass because it can give you ULAR displacement. So the turns you make really accurately, but it will never tell you a position in
Benjamin James Kuper-Smith: Right.
Rickesh Patel: the planet. Right.
Benjamin James Kuper-Smith: Yeah. Um, so yeah, I mean, I guess you had like kind of a series of questions in this paper first was like, whether they use path integration and the second was then kind of, how did they do this? Um, or what factors influenced it. So, yeah, maybe can you just a brief, I mean, you use a few kind of fairly straightforward and I think fairly standard experiments for testing, like.
Yeah, where the animals use bath integration, that kind of thing. Um, could you just briefly describe the, the rotations you do with the animals and, uh, other mean confusing things?
Rickesh Patel: Just like, just talk about how to prank man shrimp. Uh, yeah, I can tell you this. Yeah. So, um, after I found that they were still able to make these nice straight lines back home, even with no landmark there, I was interested if they, if man shrimp were [00:23:00] using path integration. Uh, so to do this, um, I built this track. And I had a platform that I, I put on this track on the center of the platform, I placed their food. Uh, and I'd wait for man shrimp to find the food on this platform. And once they found the food, slowly pulled them along this track to a new location in the arena, uh, very slowly. So, um, I. are extremely flighty animals. So if see you all of a sudden, or they, they will just run in the, in some direction. so you have to be very sneaky when you're doing this, But yeah, so you carefully move them to new location of the arena you wait to see how they, go home. And if they're using path integration, this vector based navigation, uh, that if they weren't, if they didn't notice they were being moved, they should, travel parallel to had they not been displaced to be able to find their. But if they were able to, um, integrate this movement or they weren't using path integration, but they were using some other queues in the environment that I hadn't accounted for or odor or something along [00:24:00] these lines, they should still be able to go home even after the displacement. So after pulling the, the man shrimp on the track, I found that they made these paths that were parallel to how they not been displaced.
And even these search patterns, I talked about they make these search points that are centered around where they think the home should be were generally centered around that spot, where the home should have been if they had not been moved. So this really showed that they were using this path integration behavior to find, uh, the strategy to find their way.
Benjamin James Kuper-Smith: But they, they always had the sun, uh, the sun was at the same point, right. Or.
Rickesh Patel: Actually. So for these experiments, I had them under, in a greenhouse under open Uh, so the sun was available, but it's not the same point in every time. So it could be moving. It could move around a bit. Um, the sky had other things in it, obviously, depending on the day. Um, but regardless they were making these nice paths back home, uh, or at least where home should have been, had they not been displaced after the displacement. So this showed that they were using that integration. [00:25:00]
Benjamin James Kuper-Smith: And then, uh, one thing I found kind of interesting, um, Another thing I found kind of interesting is, um, you mentioned, yeah, this one abstract called a hierarchy of cues. Um, so yeah, what's the hierarchy and, um,
Rickesh Patel: Sure. Yeah, we could talk about this. So, um, so I mentioned before, So since management freezing path integration, they have to have two things. At least to be able to do this, they have to have some sort of sense, some sort of way of monitoring the angles they turn, and then an odometer as well. So in the paper I then investigated what kind of orientation cues were they using to measure the, the angles they turned? I mean, animals can use all sorts of cues for orientation. animals can use things from. Celestial cues like the sun in the sky their vestibular systems or any sort of appropriate, receptive information.
They use the earth geomagnetic field for directional information as well. So, um, since these were all potential options, I, uh, used an experiment, um, where I, instead [00:26:00] of having this platform that could be pulled along a track, I placed in the center of the arena, a platform that can be rotated on its access, and I place food on that platform.
So once mag shrimp. Found the food. would rotate them 180 degrees, very, very slowly. Um, and, uh, I did this under open skies outdoors, um, and I did this under different environmental conditions as well. I did this when there was a overcast day when there's no sky visible. I did this on a nice clear day with the sun was clearly visible in the sky and also did this on days when the sun was blocked by clouds, but there were still big patches of blue sky available. let them find the food and find their way home. And then I let them find the food and rotated them 180 degrees as. And I found that I didn't manipulate them, if I just let them find the food and find their way home without turning them under all these conditions, they were able to find the food and return back home just fine. However, after I rotated the animals on the platform, I found that after rotation, man shrimp would still go home correctly. Despite being rotated 180 degrees. [00:27:00] If there was either the sun in the sky or patches of blue sky in the. But if there was a heavily overcast day with no sky information at all, shrimp generally oriented in the opposite direction of their home. So from this information, I could tell that there was some information in the sky that they could use for orientation. but they also had some sort of backup system that they seemed to use that wasn't celestial information based, but it seemed that there was something that we call idiopathic information. And this is, uh, ways of using your self motion to determine the direction you've moved. Kind of like your vestibular system. If I closed, if you closed your eyes and I turned you left, even though you hadn't sort of left yourself, could probably tell you were turned left because of your inner. Right. Um, so they might have some sort of system like this in order to estimate how they've turned as well. Perhaps they could feel some of their turn in some sort of way, and I'm not sure how this is the case, but since they're orienting the opposite direction, after it being turned degrees, it showed that this system is there. Uh, but they [00:28:00] clearly preferred to use celestial information since queues in the sky were visible. They were orienting to them since they were going correctly home, even after being rotated. So in order to determine which celestial cues they're using, uh, there's a couple queues that they could potentially use the first being the sun in the sky, but there are also other information, the sky that may not be. Obvious to us, to other animals may be very obvious. And, uh, one thing that I mentioned before is that man shrimp, as well as many invertebrate animals, um, can detect light. So they're able to ask to determine the polarization of light, which is just another quality of light, light color is, uh, color is, is how our brain processes different wavelengths of light or the energy of these photons moving in space while polarized light is, uh, It, it talks about the polarization or the, um, the orientation of we call this electric vectors or magnetic vectors of these food photons moving in space.
And if all the [00:29:00] photons are moving in the same direction, have the same electric vector. Then the high light is very polarized. While if, uh, if these photons are moving with different orientations, UN polarized. And sunlight isn't UN polarized, but by some sort of processes that's due to scattering, there becomes a very strong polarization pattern in the sky that if you had polarization vision, you'd be able to observe. So generally 90 degrees from the sun's position of the sky. If you had polarized vision, you'd be able to see that there's a band of highly polarized light, and some animals can use this for orientation. So one animal that's been shown to use this for orientation is the honeybee. I think it's one of the first animals that was showed to be able to orient using this kind of cue. And man shrimp have polar polarization vision that this has been shown before. and, most of their eye is a good polarization sensor. So because of this, um, that was a potential option of what Meri could have been using as well. So in order to test to see if they were using the sun or these polarization cues, um,
I used this experiment that actually [00:30:00] done the first time, I think maybe 1910 with ants. this
Benjamin James Kuper-Smith: Yeah.
Rickesh Patel: he was a, I think he was like a Swiss French guy that was living in Tunisia the French had that as a colony at one time, he, uh, with, with desert ants, he, uh, He did this really clever trick where he covered the sun with the board and then used a mirror to reflect the sun on the opposite side of the sky from the sun actually was to make it appear to the, an that the sun was on the opposite sky of the sky from where it was located. So I used the same trick to see if Manchester shrimp put organ using the sun. So I had this where I had a whiteboard that I tied with the rope. And when the Manchester shrimp finally got to the center of the arena, a mirror in my hand as well. I flipped the board up, took shade, the, the, um, arena from the sun and then used the mirror to flip it to the other side. after doing this, I found that most man shrimp would navigate to the other side of the arena from their. Their boroughs before searching. So this showed they were using the sun for orientation, [00:31:00] but they could also orient even when the sun wasn't present as long as there's patches of blue sky available. Um, so I also wanted to test if magic shrimp could use polarized light for orientation as well. And to do this, I built a slightly different setup where I put it in a dark room and I made this artificial polarized light field above the set. The magic shrimp were in, and once magic shrimp found the food, I rotated this polarized light field that I created 90 degrees. And I found that when I did this, magistrate would also orient 90 degrees in response to this polarized light field as well. So this really gave this hierarchy that you asked about it, it took shape where it seems that at least most magistrate prefer to orient to the sun when it's available, but when it's not available, they still prefer to orient Tolu, geo cues, like the polar light field that's present in the sky. And then finally, when all PLU cues are obscured, like under a really heavily over. Day, seem to rely on other information like idiopathic or this self motion information to estimate the turns that they make. And [00:32:00] it does seem hierarchical nature, at least within the setup that I have in the conditions I gave the management. And they may be able to use more cubes as well, like water currents, if there were any available, but I didn't
Benjamin James Kuper-Smith: Right judge. Yeah.
Rickesh Patel: Mm-hmm
Benjamin James Kuper-Smith: Yeah. Yeah. I mean, it's yeah. Found interesting because it's, I mean, the, the hierarchy that you describe is also in terms of like how reliable. The signal kind of is right. The sun's, I mean, it moves relative to, you know, or the earth relative the sun, but , but it's very predictable right.
Where the sun's gonna be. Um, so if you can, if it's there, you might as well use that because it's just super reliable signal. Right. And it seems to me like, basically they go from like the most reliable and external cue to then at some point, just like, wow, I guess I've only got like my own body now. Now I just have to use that to figure out where I am.
Rickesh Patel: Yeah. Yeah. These idiopathic self motion cues are a lot less reliable than these external cues, because you only can refer to. Your turns based off your [00:33:00] previous measurement of your turn. So if you, And every time you make a measurement of some sort, gonna be some amount of error associated with it. these errors will compound hugely over a very short period of time. If you're using these, the self motion cues, while can be a lot more stable or
Benjamin James Kuper-Smith: And I guess also the thing is.
Rickesh Patel: as.
Benjamin James Kuper-Smith: I guess the point that you, the, the, I think the crucial point is almost what you said that, um, if you use your own bodily signals, then you can only that the errors can just accumulate. Right. Whereas if you have something that's stable, like the sun, or like a specific landmark in your environment, then you can just, uh, you know, the errors don't have to accumulate.
You can just reassess kind of newly every time you see that queue. Um, so I think that's why it's super useful to yeah. Correct. Part integration errors. Something external that you can, where you don't have accumulating errors, I guess that's kind of.
Rickesh Patel: Yeah. Yeah. That's right. So if you can use the source of path integration are these two, sorry. Adometry [00:34:00] or, uh, angular measurements. And if you can use a really reliable queue for either of.
these two things. Should ideally.
Benjamin James Kuper-Smith: Yeah. And, uh, so to maybe, uh, finish off the, the, the man room discussion, the, yeah, the second paper that I already mentioned is the in proceedings B the landmark navigation, um, and. Yeah, I mean, is, is the brief summary that they can also use Denmark
Rickesh Patel: Yes. Yeah. Yeah. So that's that's yeah, that's the brief summary is that they can use landmarks to be able to locate their boroughs as well. And, uh, a landmark is really nice. Like If it's if it's reliable, then, uh, a landmark is a stable structure that, sorry. Yeah.
Benjamin James Kuper-Smith: If it's no, it's just, I was just laughing. Cuz you said if it's reliable, which hints at what you're gonna do with the landmarks in your study, where suddenly the landmarks move.
Rickesh Patel: Yeah, So if the landmarks are li it's, it's a nice positional marker. So it's a much more thing [00:35:00] than path integration even can be because it gives you a very, it gives you an actual place in your environment that you need to go to. Um, so like those very first, uh, experiments I did with the landmark and without them. They were able, the mentorship were able to make these really nice paths back to their homes in both cases with, and without the landmark, the, with the landmark, they were able to go exactly to their homes almost every time while without the landmark, they would get close, but they'd often make some error and they wouldn't be directly to the exact point of their burs. Um, so a landmark is a really nice way of getting. To a very specific point very quickly. And like you just mentioned, uh, so in this experiment or in the, in the paper, I had the landmark there. I didn't have the landmark there, when I saw that they were being, the paths were much more accurate with the landmark. I then moved the landmark away from the home when the animal was feeding. And in this case, like, even though you might predict that they would always go to the land. I found that that wasn't always the case. Surprisingly, they [00:36:00] would often go to the landmark, but AF at a certain point, once going to the landmark, I found that sometimes they would stop along that like they would stop following the landmark and then turn and go to where their borough should be. So it does seemed like that that first is very cool because it shows both the landmark navigation and path integration systems are present and they operate independently of one another. They can both work together, but these are two independent systems that the Manchester have at the same time that they can use.
Benjamin James Kuper-Smith: Yeah, I really like that part because it's, I mean, at some point when you read these studies that, you know, you, you. Rotate the animal or you change landmark, whatever. At some point you go like, don't, they like have some sort of memory of what it looked like five seconds ago, or I dunno how long, you know, it takes for you to make this change.
But at some point I feel like surely they must realize at some point that like things have changed. And I really liked that there were, I think you said like three out of 10 or something like that. Like, it wasn't like all of them, but, um,
Rickesh Patel: right. I can't quite remember, but yeah.
Benjamin James Kuper-Smith: Um, well, at least like some of them, right. It wasn't like all of them necessarily [00:37:00] figured out.
Yeah.
Rickesh Patel: of them.
Benjamin James Kuper-Smith: Um, and I re I kind of really, he had this one example, which I really liked of this, this one, uh, uh, what was it that the one shrimp. Kind of realized halfway to the landmark, like, wait a minute, this isn't where I thought it was, then went back to get a snack and then went straight home. And, um, I really like this kind of like, I really imagine going like, wait a minute, this is not where I'm supposed to go better, get a snack and then I'm gonna go home again.
Rickesh Patel: Yeah.
Benjamin James Kuper-Smith: Uh,
Rickesh Patel: or, yeah, just get to the position that you last, uh,
Benjamin James Kuper-Smith: I guess all of that. Yeah,
Rickesh Patel: Yeah,
Benjamin James Kuper-Smith: no, that's a bit.
Rickesh Patel: they're doing, but yeah, Yeah.
Maybe
Benjamin James Kuper-Smith: Um,
Rickesh Patel: Yes, it's, uh, it's, it's really nice because landmarks, the, their positional, uh, information absent of error. Really. While path integration always has some attributed to it, it might be very minor. Um, but it's there. Mm-hmm
Benjamin James Kuper-Smith: Yeah, especially the accumulation. I mean, you [00:38:00] can obviously have errors in estimating how far the land mic is away from you, that kind of stuff, but it doesn't accumulate every step of the way necessarily. Yeah. I mean, one question that, I mean, the, the reason I also find, uh, to kind of have a slightly more general discussion about match trip navigation, that kinda stuff is that as I, as I said in the beginning, most of the stuff I've read or pretty much all of the stuff I've read has been with rodents or with humans.
I mean maybe some monkey studies, but I think it's pretty much rodents. And, but one thing I find really interesting is that, you know, we in the special navigation to think about like, They AKA and then enter, enter a cortex and these like neural structures. And it's really, um, they show up in, in rats and in humans.
And it's very similar, but what I've found really interesting is that, you know, Manti shrimp or bumblebees, which we can get to in the second, you know, have much, much simpler brains. Or you mentioned the answer earlier have so much simpler brains and they can still do the same thing. Well, even with, as [00:39:00] you mentioned, probably much better than humans ever could.
Rickesh Patel: Probably bees and man shrimp as well, better than a mammal could.
Benjamin James Kuper-Smith: And
Rickesh Patel: No,
Benjamin James Kuper-Smith: I find that really interesting because I feel like, especially when something seems complex, like, you know, navigating through MAs and remembering where you came from and those kind stuff, I think at least I tend to have a tendency to think like, you need a complex brain for that, but I find it really interesting that like, with, with Manda Stroms, there seems to be this sense of, or like with all these, uh, studies you mentioned with the different species, like you can have a very simple brain that can still do all this really complex stuff.
Rickesh Patel: that's that's, that's really interesting. Yeah. You have these very simple brains and. Much simpler than any vertebrate
Benjamin James Kuper-Smith: Yeah. Just going off size basically. That's what I'm doing. Yeah.
Rickesh Patel: or even number of neurons. It's just extremely, uh, uh, simplified. But you have this really robust behavior that out shines vertebrates and path integration at least. Um, so like how do you encapsulate this behavior in a very limited number of neurons And do it robustly, [00:40:00] um,
Benjamin James Kuper-Smith: And I'm curious, do you know much about that? I mean, uh, no problem. If you don't. I mean, but
Rickesh Patel: Well, this is, uh, this is actually like what, why I'm working with bumblebees now.
Benjamin James Kuper-Smith: okay.
Rickesh Patel: uh,
Benjamin James Kuper-Smith: Yeah.
Rickesh Patel: Yeah.
Benjamin James Kuper-Smith: I mean, though, I was gonna make a, so maybe to, to switch to the bumblebee paper then very briefly. I mean, you had this, uh, again, it's yeah, again in car, um, this year, um, where used vector navigation in walking bumblebees. And I was slightly confused at first when I started reading the paper, because I thought, cuz you know, you start off saying like, well, when these can fly around and they use path integration and those kind of thing, or vector navigation, whatever wanna call it.
And I. Kind of obvious that they have it when walking, right? Like why is this such a big deal? Kind of like, I would kind of be Sur I would be more surprised if they didn't have it when walking than if they, at least from my naive, not knowing anything about bumblebees or anything really perspective. Um, but then it seems to me when I.
[00:41:00] Read more of the paper. It seems to me it is almost more methods paper to, in to figure out whether you can use bumblebees to study neural procedures. Because from what I understand the problem. Studying flying bumblebees is that you need a very large area, which is not exactly ideal for your recordings.
Right. Whereas if they're just walking around, you have much smaller space, so it's much simpler to, um, well, not simpler, but you can just actually do it in a lab. Um, and so, I mean, am I correct in that, in, in assuming that this is almost more like a methods development so that you can then do this or.
Rickesh Patel: yeah, I mean, first off it does show that this works really nicely over small distances, um, in animals that usually flab or large So that's a finding of itself. But I think our conversation that we talked about earlier is, uh, is AC it relates to it really nicely. So I might just go back to that about how. How does a simple brain a very complex task and, uh, [00:42:00] with bumblebees and with insects now, generally have very detailed, we're starting to have very detailed anatomical descriptions of how the brains, the, the, the, the neurobiology of the brains at, at the cellular level we can. Uh, so for instance, very recently with fruit flies, they have of the whole Hemi brain, uh, where you can see not only. All the neurons and where they go and who talks to who, but also which synapses there are. And you have this at a resolution that you just cannot get with a vertebra. Um, and, uh, we all, we have this with the Bumble D as. So, um, so we have this detailed anatomical understanding of where these brain regions that we know are important for navigation, they look like, who talks to who as far as neurons go. Um, and with this information, we can make computational models for how well, depending on how the neuro circuitry and how these neurons are wired, might the brain of these animals then be able to [00:43:00] perform this complex behaviors? So you can computationally model how this might happen. So we have really robust behaviors that are atomically grounded, these computational models that are atomically grounded, that can perform the behaviors that animals do in real life. But we have right now, we didn't really have a way of testing to see if these, uh, these models are true. You know, these are so, so, uh, what I was, what I've come here to do is to really figure out well, can we devise a situation or.
advise a setup to be able to test these models? So can we, can we perform really nice, clear vector navigation, this path integration behaviors in the laboratory.
And then can we record from these animals in early? Why they. So we can then test some of the hypotheses that they raise that certain cell types storing vector memories in a certain way, for Um, so, uh, so this paper really the, the motivation behind this is to see, well, can we get a reliable system working in the laboratory?
Can we show that bumblebees perform nice vector navigation [00:44:00] in the small space? Um, and the reason I chose walking bumblebees is because it's, uh, logistically a lot simpler to, to work with animals that Aren. Flying in three dimensions, but rather constrained to two dimensions. Right? So we get, and, and it's easier to record from their behaviors and then to do neuro recordings this way as well. Um, so in, in some ways it is, uh, a
Benjamin James Kuper-Smith: Yeah.
Rickesh Patel: paper in that we we're tr the end goal is to see if we can get a system working where we can test. neurally and behaviorally. Uh, some of our idea, our ideas for how the brains of these animals are actually performing these complex vector navigation behaviors in a very small package.
Benjamin James Kuper-Smith: Yeah, I guess I agree. Like it is, um, just to, to, I guess I did kind of slightly underplay the, uh, finding that they actually use in walking, because I guess it is a very. They're using different joints and all this kind of stuff. Right. Or different limbs or whatever you call this with bumblebees, uh, wings versus feet or whatever you [00:45:00] call
Rickesh Patel: Like,
Benjamin James Kuper-Smith: Yeah. Okay. Yeah. Um, I dunno whether there's a specific term for it and I guess yeah, if the distance is that different, then you might just actually use a very different system. That's yeah, that's a fair point.
Rickesh Patel: So you had to show that they actually were using it over a very small space. This is the, is on, the scale of about a square meter, right? While in nature, they're travel. Kilometer or so, you know, kilometers. would the vector navigation be what they are preferring to or what they do use over the small space as well? And can we predictably manipulate these behaviors, both the distance, uh, estimations and the orientation estimations as well that the bees are using. So if you have a really robust, uh, malleable behavioral system, then we can. You know, manipulate this system when we're recording from the brain to be able to see if any of these things that we think might be happening are actually happening there.
Benjamin James Kuper-Smith: And that's what you're working on right now.
Rickesh Patel: Yeah. Yeah. Currently that's what I'm working towards to see. Well now can we get some sort of system working where [00:46:00] we can reliably record from these brains, uh, for the brains of these animals while they're not completely fixed and tethered in place, like has been done the past, but to move a bit.
Benjamin James Kuper-Smith: Yeah. Is the, I mean, I've, I've never really, I'm sure I've actually ever read a paper where they use. Neuro recordings from insects or anything like that. But, um, is I'm just curious, like, because, because I guess my question is like how well you can actually record neurons from creatures that are so light.
Um, because, you know, I guess we have, I don't know, because in a, in a rat or mouses, there's still red, quite heavy relative to the tiny, uh, electrodes, you can insert into the brain, but I'm just curious, like how well can you actually record. Neural activity from species that, I mean, how does a bumblebee weigh like a gram?
I dunno, like I have no idea. Like what, yeah.
Rickesh Patel: this, this is a good question, but it actually has been done for quite a while now. Typically in the past, what people have done is they've restrained the animal. They'll [00:47:00] expose the brain and they'll use really thin glass electrodes to be able to record from single cells, the recordings. Um, but this is a problem for moving animals. Like what you're talking about. If you, if this animal has a recording, Device that's on the animal while it moves, then how do you do this? Well, and, uh, recently some people have done this with insects, so I have a couple colleagues. One has done this in walking cockroaches before with a, road, essentially with a, bundle of wires, uh, four, five wires that are. really small, but, uh, bundled together. And you can then use the distances between these wires to be able to estimate which cells you're recording from. And, uh, I have a colleague that also just had a paper come out, uh, recording, using Ted roads in Monarch butterflies that are flapping their wings.
Benjamin James Kuper-Smith: Like the, the electrodes and the storage. Of the, I mean, the, is the memory storage, like, I mean, is there like, there's not like a long cable or is there,
Rickesh Patel: there, there, is.
Benjamin James Kuper-Smith: so they're still not flying [00:48:00] the butterflies or,
Rickesh Patel: They are flapping in place. So they have a magnet on their
Benjamin James Kuper-Smith: okay. Yeah.
Rickesh Patel: needle. So they're able to turn and flap, but they can't fly away. Yeah.
Benjamin James Kuper-Smith: Okay.
Rickesh Patel: still tethered in some way, but they're, their limbs are, are able to move just fine.
Benjamin James Kuper-Smith: Hmm. Yeah, it was interesting because I guess this is it kind of, I mean, this is the problem that was solved just before John Key found play sales in rats. And then later on in large part won the no prize for that one paper, I guess. Because I think just before that there was the same problem with RAs as like, how do you record from a moving animal?
Rickesh Patel: Mm-hmm
Benjamin James Kuper-Smith: figured out how to do it. And then suddenly you can do all these new experiments now, but I guess you're getting to, or you are at that point now where you can record from a walking Bumble or
Rickesh Patel: no, I'm not quite there yet. working on it, working on getting there, but
Benjamin James Kuper-Smith: okay.
Rickesh Patel: but the technology is, is around and people have used this to record from animals while they had some free motion. So this is, uh, so it's not like we have to. meant [00:49:00] something completely from scratch. You know, the, there is this available and now we can see, well, can we incorporate it in this system, which is quite a challenge, nonetheless, but at least it's something that is feasible.
I think.
Benjamin James Kuper-Smith: I mean, if that's what you're
Rickesh Patel: Yeah, but you know, you can never be like with these kinds of things, you're
never, you never know if something's gonna actually work at the end of it all. So there's always risk As long as you pair that risk with some things that you feel a little more confident about, there will be something out of it, you know?
Benjamin James Kuper-Smith: working on UTOPES are right. yeah. So you've, you've got like your secure project and your rescue project or.
Rickesh Patel: Yeah, pretty much with the behavioral work now that I, that with this paper that we're talking about, since the behavioral work works really well, now I can continue this secure in this sort of respect. And then see if we can get these, this other stuff. That's a little unsure going as well.
Benjamin James Kuper-Smith: Okay. I have a really random question, which is, I think this is the first paper I've seen where, you know, you have the authors and the affiliations [00:50:00] and the unusually email address. And in here, in this case for you and for, uh, Stanley Lee Hein. So you have a Twitter handle also on the paper that I think that's the first time I've seen that is that,
Rickesh Patel: I,
Benjamin James Kuper-Smith: uh,
Rickesh Patel: was kind of surprised by that too, to tell you the truth. I don't know how long current biology has been including that, but they
Benjamin James Kuper-Smith: they asked you.
Rickesh Patel: yeah. They like when you.
put your information in, they also have, a field for Twitter handle and I put both mine and Sam heza, who is the PI of the lab that I'm working in now.
Benjamin James Kuper-Smith: Right. So let's say whether, yeah, you can put email or like, or Kidd or whatever. However it's pronounced, um, links. You can put Twitter.
Rickesh Patel: yeah, exactly. Yeah. Your, your, your email, your orchid, your affiliation and your Twitter handle. That was
Benjamin James Kuper-Smith: I guess I haven't been reading car biology recently. so, okay. Yeah. Uh, yeah. I was curious how that came about whether you were like I have, because I mean, you also do seem to be super active on Twitter, right. Um, so it's.
Rickesh Patel: I, I would, I wouldn't say I'm super active on it, but I'll, I'll post things every now and [00:51:00] again.
Benjamin James Kuper-Smith: Okay. Yeah, I guess. Yeah. Yeah. Um, unless yeah, I guess there's what I notice. I, yeah, there's people who post like multiple things every day. And with them, I wouldn't be so surprised for them to put it there, but, um, I guess you are more like me than the kind of
Rickesh Patel: I kind
Benjamin James Kuper-Smith: re reading. And then when something, you have something to publish, then you put it there or.
Rickesh Patel: Yeah. That's most that's most of the time, I honestly am pretty bad at Twitter. I'm not like a huge fan of social media in generally, but once I started publishing friend, my friends were like, you definitely should be getting a Twitter and putting things down. And I agreed with them. It's it's, it's a, it's a good thing.
Yeah.
Benjamin James Kuper-Smith: I mean, that's the only thing I basically use it for. It's just, uh, I mean, yeah, if have a paper or podcast episode, that's pretty much it.
Rickesh Patel: Yeah. Yeah,
Benjamin James Kuper-Smith: Um,
Rickesh Patel: some people are really good at, at doing this and like with people over these, uh, uh,
Benjamin James Kuper-Smith: Yeah. And it's, it's really valuable. I mean, I think if I remember correctly, the reason I found out about you and your work is cause Hugo Spears tweeted about it. [00:52:00] And Hugo Spears has been on the podcast before and. Very active on Twitter and
Rickesh Patel: Okay. Well,
Benjamin James Kuper-Smith: a lot, you know, he always has like stuff about memories based navigation, that kind of thing, roughly.
And so I think he might have tweeted about your, the bumblebee paper or something like that, not sure. Um, and that's that, that's how I found out about it. Right. Um, and there's yeah, I think it's, it's really valuable for finding new stuff. It's just, I'm not someone who. Posting things there, I guess. Yeah. I mean, I guess I also don't read lots of new papers.
I feel like half the papers I read are like 30 years old. I know, I guess that might be worth reposting, like tweeting about them. So, you know, not just posting the new stuff,
Rickesh Patel: Yeah.
Benjamin James Kuper-Smith: I dunno in some way it feels more appropriate for new stuff, but I don't know.
Rickesh Patel: Yeah, I mean, you know, I never really thought about it, but I honestly, if you're excited about something, including an old paper, I guess, why not? Right?
Benjamin James Kuper-Smith: yeah, but yeah, I'm not, I feel like I'm not gonna get into Twitter. It's not, it's not my thing. Yeah.
Rickesh Patel: Yeah.
Benjamin James Kuper-Smith: Um, I think, I think this is my science communication [00:53:00] yeah,
Rickesh Patel: which is great. I think that's, uh, it's, it's a lot of, a lot more effort I had to, would imagine, but it's also probably more reward too. You get some interesting
Benjamin James Kuper-Smith: exactly. Exactly.
Rickesh Patel: and.
Benjamin James Kuper-Smith: It's definitely more effort per output. Let's say
Rickesh Patel: Oh, yeah,
Benjamin James Kuper-Smith: um, yeah, yeah, but, um, in a, yeah, it's weird, weird in a way this is science communication, but I don't almost don't think about it that way. For me, it's more like, it's just like stuff I find interesting. And then I want to talk to the people who did it
Rickesh Patel: which is
Benjamin James Kuper-Smith: have conversations about it.
Rickesh Patel: honestly, most people
Benjamin James Kuper-Smith: Yeah. Yeah, exactly, exactly. Um, it's weird. Like, I, I feel like I attend far fewer talks now than I used to just because it's like, oh, I can just invite them on the podcast. obviously not, not everyone says yes and I don't always invite people, but, um, yeah. As a kind of last kind of smaller topic. I was just curious.
I mean, you seem to have, uh, I mean, drawings in illustration seem to be something you've been doing for a while. And I saw on your CV, you have a [00:54:00] biomedical illustration certificate in your ness. From what I can tell, it seems like it's not only for your own work right there, there was some things that seemed to be for other labs or publications, the way you did illustrations.
Rickesh Patel: Yeah. Yeah. So,
Benjamin James Kuper-Smith: yeah. I'm just curious, like how did, uh, something you've just always been doing and then realized you. Do it also for your own papers or? Yeah.
Rickesh Patel: Uh, it was kind of funny, but in my, under my, uh, undergraduate work, um, I was a biology degree. but I also wanted to take some art classes too, because I never had done that before. Um, but I always like, kind of just like doodling and stuff. So my undergrad
Benjamin James Kuper-Smith: I
Rickesh Patel: was really had a really nice art school as well, but you could only take art classes if you were an art. And I saw that this certificate was an option. So I was like, oh, maybe I can do this. Like as a degree and take some art classes just to see if I like it or not. Um, and I ended up loving it. Like I did a lot. I
probably did enough or almost enough for an art degree as a whole anyways. But, like I took other classes too, like drawing and painting and just doing this and,
Benjamin James Kuper-Smith: [00:55:00] really sorry. Brief question. The certificate. I thought it was like a single course or like a single module at university.
Rickesh Patel: it's,
Benjamin James Kuper-Smith: sounds like it's a lot more,
Rickesh Patel: Yeah. Yeah. It's like a, it's pretty much a full degree almost. It's a, uh, I think like every school semester I had like at least two art classes.
Benjamin James Kuper-Smith: huh? Okay. And that was so by maker, illustration means, uh, like spec courses specific to that, or.
Rickesh Patel: Yeah. So I had maybe three or four of these specific courses. I think three, it was, um, but most of my classes were generally, uh, Drawing or These are also things that I was kind of interested in as well. so this is, uh, so I, I would say that I would. Maybe consider myself more than just a biomedical illustrator, but I have done this, uh, a few times for like jobs, like for papers from other people's labs.
A couple times I was hired to do this and yeah, it's, it's something I enjoy, but I have to say more than illustration. I really just like drawing and painting generally. [00:56:00] Uh, but illustrations are nice too. Cuz you can actually have like a job and focus on it and do it even though it's been a while since my last, uh, the last time I was paid to do this,
Benjamin James Kuper-Smith: Right. Um, but like other, I'm just curious. I know the, yeah, I guess all the figures in your, I guess they're less illustration often like plots and that kinda stuff, right?
Rickesh Patel: Yeah. Yeah.
So All my figures,
Benjamin James Kuper-Smith: Yeah.
Rickesh Patel: I, I guess what did I do? I guess I did a B head for the surgery experiment. Oh yeah.
Benjamin James Kuper-Smith: All right. Yeah, here it is. Yeah, of course. Yeah. Yeah.
Rickesh Patel: one I, I did. And. my man shrimp paper. There's like an illustration of the man shrimp. I put on the front of
Benjamin James Kuper-Smith: Yeah.
Yeah, yeah.
Rickesh Patel: yeah.
So, so I gotta throw it in every now and again.
Um, yeah.
Benjamin James Kuper-Smith: I mean, it's, I really like that kind of stuff. I think it's always cool. When I guess just people have skills that you wouldn't necessarily expect just from the job description, which I feel like pretty much most people have, but not necessarily to this degree. And, um, often you don't know about them.
Rickesh Patel: Right. Yeah, I think, uh, I [00:57:00] think it's actually surprising. I've I feel like a lot of scientists seem to be able to, uh, draw really well. Like I've come across a good number of my colleagues that fairly nice drawings too. Um, I'm not sure if there is something That draws these kinds of people together in this
Benjamin James Kuper-Smith: That was a great
Rickesh Patel: yeah,
Benjamin James Kuper-Smith: pun, but yeah,
Rickesh Patel: unintentional
Benjamin James Kuper-Smith: um,
Rickesh Patel: clever.
So
Benjamin James Kuper-Smith: um, but actually this reminds me, there's a, there's a biography that came out recently of. LA Kao. Um, uh, like there's like a big biography that came out about him, um, that I wanna read at some point and reminds me, I have to stuff to all that book. sounds really interesting.
Rickesh Patel: Yeah. Yeah.
Benjamin James Kuper-Smith: Um, yeah, I guess I think I've kind of come to the end of my questions. Uh, my points. I dunno if there's anything else you want to add, otherwise I'll just stop recording.
Rickesh Patel: Yeah. Yeah, I guess like the only thing I guess I would add is that though you, we were talking about how you were familiar with the [00:58:00] human and rodent, uh, navigation systems, there really has been a rich, uh, of studying these, uh, sorts of processes and other animals and in arthropods as well.
So like, like I said, of the, an, the, an, uh, orientation work, ones were done in the late 18 hundreds. the, I mean, I think VRE, Karl VRE super famous for all his work with bumblebee or honeybee. Sorry. so, you know, it's, it's been happening for a while and there's a lot of people that have been doing this kind of work.
So, you know, I didn't want, I don't want it to make it seem like I'm this strange outlier that is
Benjamin James Kuper-Smith: Yeah. Yeah, of course.
Rickesh Patel: is. Yeah. yeah,
Benjamin James Kuper-Smith: Yeah. I mean, I guess the, the first stuff was the, like the, the dancers and that kind of stuff. Right. And the bees was, did he do that?
Rickesh Patel: yes,
Benjamin James Kuper-Smith: I guess that.
Rickesh Patel: he did some, a lot of orientation work as well, showed the polarized light was actually used for the first time in any animal, uh, which is I think a huge thing
Benjamin James Kuper-Smith: Yeah. And that's interesting. I just never really put, [00:59:00] yeah, there were always like different topics in my mind, you know, you like separate things. So like the special navigation, there's like the, I mean, not that I know this in any detail, but I, I knew of them. Right. But I never considered this to be part of the space navigation for me, this was more like me communication kind of thing.
Rickesh Patel: Yeah, no,
Benjamin James Kuper-Smith: Yeah.
Rickesh Patel: the dances, what they're communicating is. What they interpret as their spacial
Benjamin James Kuper-Smith: Yeah.
Rickesh Patel: so the dance is actually giving the path integration vector in a way. It,
Benjamin James Kuper-Smith: Yeah,
yeah,
Rickesh Patel: of the dance and how far the dance goes is what direction you should go relative to a cue, like the sun and how far you should go in that direction. So it's very cool. yeah,
Benjamin James Kuper-Smith: yeah. Great. There's another entire feud of literature I can add to my reading list then. , that's good to know.