World’s largest fetal-brain mapping dataset is being built here in India! | Dr Richa Verma on S2E10

1. 0:00 – 0:42

   Intro

   1. RVDr. Richa Verma0:00

      we are able to go equivalent of that house level within the brain, which is at cell level, but across the whole brain.

   2. SPSpeaker0:08

      It sounds simple to say imaging of a human brain.

   3. RVDr. Richa Verma0:11

      Yep.

   4. SPSpeaker0:11

      Uh, and but it's a huge engineering challenge.

   5. RVDr. Richa Verma0:14

      Yes. Currently, the largest, most detailed brain map of the developing human brain in second trimester.

   6. SPSpeaker0:22

      So the Dharani dataset for each brain, we'll be able to track these eighty billion odd neurons?

   7. RVDr. Richa Verma0:27

      It's in the largest collection in the world.

   8. SPSpeaker0:31

      Hi, this is Amrit. We are at IIT Madras, my alma mater, and India's top university for people who like to build. We are here to meet some builders, ask them: "What are you building? What does it take to build?

2. 0:42 – 1:11

   Welcome to the Best Place to Build Podcast

   1. SPSpeaker0:42

      And what makes IIT Madras the best place to build?" [upbeat music] Hello, and welcome to the Best Place to Build Podcast. Today, we have with us Dr Richa Verma, chief scientific officer of the Sudha

3. 1:11 – 1:40

   Introducing Dr. Richa Verma | CSO, Sudha Gopalakrishnan Brain Centre | IITM

   1. SPSpeaker1:11

      Gopalakrishnan Brain Centre at IIT Madras, which does brain imaging. We'll learn about it. It does brain imaging at point five micron level or cellular level. The research group has a wet lab, an engineering lab, an optics lab, an imaging lab, a software team, and an ana- analytics team. So it's a large team, multidisciplinary. Um, Dr Richa, welcome to the podcast.

   2. RVDr. Richa Verma1:31

      Thank you, Amrit. Thanks for having me here.

   3. SPSpeaker1:34

      Uh, Doctor, I have to ask you, what is brain mapping, uh, what is brain imaging, and why do we need it?

4. 1:40 – 4:30

   What is brain mapping and why it matters?

   1. RVDr. Richa Verma1:40

      Okay, that's, uh, good and something good to start this conversation with. When we talk about human brain, or any brain for that matter, it's an organ which is very heterogeneous, which means, uh, it has different cell types, there are different regions. So to understand the brain, you want to know how these cells are organized and how each of these organization makes different brain regions. So just like world map, you identify different countries, states, towns, and cities, and you then create maps, right? And then you put different countries map together to create the big atlas. If you remember in your school, you would have, in geography, the atlas-

   2. SPSpeaker2:32

      Mm

   3. RVDr. Richa Verma2:32

      ... which would comprise maps of different countries. So same way, we are creating human brain maps, where we have detailed information about different brain regions, and we-- when we put all of this together, what we are doing is generating brain atlases.

   4. SPSpeaker2:50

      Nice. You gave me the analogy earlier of, uh, moving from an atlas to something like Google Maps.

   5. RVDr. Richa Verma2:56

      Yes-

   6. SPSpeaker2:57

      Uh, so-

   7. RVDr. Richa Verma2:57

      Or the other way around. [chuckles]

   8. SPSpeaker2:59

      Right.

   9. RVDr. Richa Verma2:59

      Okay. [chuckles]

   10. SPSpeaker3:00

       So in, in, in, in the sense, what I want to understand is... I mean, in the introduction, I read that it's at a point five micron level. How much does the impact of the resolution matter?

   11. RVDr. Richa Verma3:15

       Okay, so the closest analogy, which works with a lot of people, we have had world maps for centuries, right? People used to navigate from one country to the other, and those maps have also evolved over a period of time. Now, if you compare the world map two hundred years ago versus what you see in Google Map-

   12. SPSpeaker3:40

       Mm.

   13. RVDr. Richa Verma3:41

       Google Map, you are able to go to the street level, to individual house level.

   14. SPSpeaker3:46

       Mm.

   15. RVDr. Richa Verma3:46

       Right? So what we are generating in terms of human brain maps, we are able to go equivalent of that house level within the brain, which is at cell level, but across the whole brain, and that is super, super critical. The reason being, you want to understand several brain diseases, different developmental disorders, and if we don't understand the organization of each of these brain region in normal brain, it's very hard to crack the problem when it comes to diseases.

   16. SPSpeaker4:20

       Very interesting. I've read somewhere, I mean, I don't know where, but, you know, you get all this information from different places-

   17. RVDr. Richa Verma4:26

       Yeah

   18. SPSpeaker4:26

       ... that a certain kind of activity lights up certain kind of the

5. 4:30 – 8:30

   What does the brain centre at IITM do?

   1. SPSpeaker4:30

      brain or certain kind of diseases are caused when certain parts of the brain are not functioning properly. Uh, so are you saying that a detailed brain map will go much more detailed in saying that this part of that part, and at this address in the brain, there is some malfunction?

   2. RVDr. Richa Verma4:47

      Yeah. So what... As of now, what we are doing is, when you create these normal brains map at different age groups, and we are doing it from prenatal stage, that create becomes a reference maps. So if you are looking a brain at, say, in third trimester or second trimester, you have created a very detailed map of a normal brain. Now, that can be used as a reference to look at different disease conditions, or in this particular case, developmental disorders, and see which region does not match with this particular normal brain. What are the cell types which has been affected? Are there numbers which are less, or the overall brain thickness which has been... or what we call as the gray matter thickness, that's been compromised, et cetera, et cetera. So hence, this is super critical when I said that, you know, you need these reference map across the entire age group within the developing human brain, but also as we are born all the way up to when we age.

   3. SPSpeaker5:56

      Okay, so-

   4. RVDr. Richa Verma5:56

      And this is what we are doing.

   5. SPSpeaker5:58

      Okay, so at the very simplistic level, uh, the, the first level impact of your work is that we will be able to compare two different brains-

   6. RVDr. Richa Verma6:06

      Yeah

   7. SPSpeaker6:06

      ... find out what's different, and associate-... the, the manifestations of that difference onto-

   8. RVDr. Richa Verma6:11

      Yes

   9. SPSpeaker6:12

      -some causative or-

   10. RVDr. Richa Verma6:13

       Yes

   11. SPSpeaker6:13

       -some correlation in the way the brain.

   12. RVDr. Richa Verma6:15

       Cause, and then look at the, what has, what has really got changed in this particular disease condition, in which region, and then you investigate that further.

   13. SPSpeaker6:26

       Nice.

   14. RVDr. Richa Verma6:27

       Yeah.

   15. SPSpeaker6:27

       Okay, so I get that.

   16. RVDr. Richa Verma6:29

       Thank you. [chuckles]

   17. SPSpeaker6:29

       And we'll go into detail in a bit, but before that, with this background, can you tell me what the Brain Centre does?

   18. RVDr. Richa Verma6:35

       Okay, excellent. So the overarching goal of the Brain Centre is to map the whole human brain, all the way from prenatal stage to hundred years.

   19. SPSpeaker6:47

       Okay.

   20. RVDr. Richa Verma6:47

       And very happy to share that this work started five years ago, but the physical center, the Brain Centre, is now three years old, and we have been successfully, you know, mapping different types of brains. And one of the data which we released early this year is from the second trimester developing human brain, and that's called as Dharani. It's an open-source data.

   21. SPSpeaker7:15

       Dharani.

   22. RVDr. Richa Verma7:15

       Dharani, D-H-A-R-A-N-I. And that's currently the largest, most detailed brain map of the developing human brain in second trimester. More importantly, the data has been made freely open-access datasets. So if you go and browse Dharani Atlas, you can access the entire dataset. So, um, that's, uh... So when we started this work of brain mapping, we did not limit ourselves to only look at the normal brains. In parallel, we have been studying the developmental disorders, we have been looking at brains affected by stroke or ischemia, and specific, what we are currently looking at, neurodegeneration, but also mapping the aging brain all the way from fifty to hundred years old.

   23. SPSpeaker8:11

       Interesting. Um, so many questions come up-

   24. RVDr. Richa Verma8:15

       Yeah

   25. SPSpeaker8:15

       ... in my mind. I'm wondering, I, I met Professor Mohan, uh, on the podcast. He had come last year sometime, uh, and he said that, uh, it sounds simple to say imaging of a human brain-

   26. RVDr. Richa Verma8:27

       Yep

   27. SPSpeaker8:27

       ... uh, and, but it's a huge engineering

6. 8:30 – 12:21

   Why is imaging the brain a huge engineering challenge?

   1. SPSpeaker8:30

      challenge.

   2. RVDr. Richa Verma8:30

      Yes.

   3. SPSpeaker8:31

      Can you explain to us why it's an engineering challenge?

   4. RVDr. Richa Verma8:34

      Okay. So if we look at what is currently... how do we image human brain, especially I'm talking here in living human brain. Most of you would be familiar with MRI or a CT scan, which is often used to look at different diseases, different conditions in living human brain.

   5. SPSpeaker8:55

      Yeah.

   6. RVDr. Richa Verma8:56

      And, you know, in the last twenty, thirty years, that has been, you know, the impact of doing MRI has been quite profound. You can look at human brain and study where the problem is. The problem with this sort of imaging is, the resolution at which you can see the entire brain is at, at the best, at one millimeter.

   7. SPSpeaker9:18

      Mm.

   8. RVDr. Richa Verma9:19

      Now, one millimeter, you will not be visualize the different cell types within the brain. If you look at the basic science research, specifically in animal work, and I used to work on monkey brains, there you can, uh, you know, um, you can do many things, many type of intervention to study the whole human, uh, sorry, the whole brain. But the big gap in terms of when you look at post-mortem brain, people often study small regions-

   9. SPSpeaker9:55

      Mm

   10. RVDr. Richa Verma9:55

       ... or small areas within the brain at cell level. So what we have developed here is closing the gap between the volume and the cellular resolution. And what that means is, we are working on post-mortem brains. We get these post-mortem brains in a very good condition from our clinical partners, of course, after the written consent.

   11. SPSpeaker10:21

       Mm.

   12. RVDr. Richa Verma10:22

       Once we acquire these brain, we also do a post-mortem structural MRI-

   13. SPSpeaker10:27

       Okay

   14. RVDr. Richa Verma10:27

       ... where you get a reference of the brain region inside the skull in many cases.

   15. SPSpeaker10:32

       Hold on, hold on. Hold on, hold on, hold on.

   16. RVDr. Richa Verma10:34

       Okay.

   17. SPSpeaker10:34

       You're going too fast for me.

   18. RVDr. Richa Verma10:35

       All right. All right.

   19. SPSpeaker10:35

       So I need to, I need to dial back.

   20. RVDr. Richa Verma10:37

       Sorry.

   21. SPSpeaker10:37

       So I, I did some studying before coming-

   22. RVDr. Richa Verma10:39

       Yeah

   23. SPSpeaker10:39

       ... and I understand that, uh, when we-- I have not had a brain MRI.

   24. RVDr. Richa Verma10:44

       Yes, me neither. [chuckles]

   25. SPSpeaker10:45

       Yeah. [chuckles] But I have seen it on TV... [chuckles]

   26. RVDr. Richa Verma10:48

       Yes, yes

   27. SPSpeaker10:48

       ... in these medical shows-

   28. RVDr. Richa Verma10:49

       Yes, yes

   29. SPSpeaker10:50

       ... where they show these, uh, black-and-white sort of images which you put on-

   30. RVDr. Richa Verma10:54

       Correct
7. 12:21 – 16:15

   Taking a look inside the Dharani dataset of the brain

   1. SPSpeaker12:21

      this twelve hundred cc?

   2. RVDr. Richa Verma12:22

      So as of now, the best-known information is eighty-six billion neurons.

   3. SPSpeaker12:28

      Eighty-six billion?

   4. RVDr. Richa Verma12:29

      Neurons are there in the adult human.

   5. SPSpeaker12:34

      So the Dharani dataset, for each brain, I will be able to track these eighty billion odd neurons?

   6. RVDr. Richa Verma12:41

      Yeah. So first thing, the Dharani b- dataset is the developing human brain-

   7. SPSpeaker12:45

      Okay

   8. RVDr. Richa Verma12:45

      ... in the second trimester. But yes, we are working on really estimating the total number of cells at different ages across the entire lifespan.

   9. SPSpeaker12:57

      Okay.

   10. RVDr. Richa Verma12:57

       Yes.

   11. SPSpeaker12:57

       That's fantastic.

   12. RVDr. Richa Verma12:58

       Yes.

   13. SPSpeaker12:58

       Thank you so much. Um, I got a sense of that. So you were talking to us about the engineering process of doing this imaging.

   14. RVDr. Richa Verma13:05

       Okay, yeah. So-

   15. SPSpeaker13:08

       Do you have-

   16. RVDr. Richa Verma13:08

       As-

   17. SPSpeaker13:08

       -with consent? You have a-

   18. RVDr. Richa Verma13:10

       We got the brain-

   19. SPSpeaker13:11

       Post-mortem brain

   20. RVDr. Richa Verma13:12

       ... We did the structural post-mortem MRI.

   21. SPSpeaker13:15

       Okay.

   22. RVDr. Richa Verma13:15

       Then the brain has to be... And, you know, this is a biological tissue, which is, uh, soft, but also has a very high water content. And the goal here is to slice this twelve hundred cc or fifteen hundred cc biological tissue in very thin sections, as thin as ten micron or twenty micron. To do so, there are different steps, which, you know, is normally used, and the w- what we do with these tissue is, we put it-

   23. SPSpeaker13:49

       What, what do you mean by normally use? Is, is this a-

   24. RVDr. Richa Verma13:52

       So, you know, this type of work has happened before.

   25. SPSpeaker13:55

       Okay.

   26. RVDr. Richa Verma13:55

       It's just that it has not happened at this scale.

   27. SPSpeaker13:58

       Okay.

   28. RVDr. Richa Verma13:59

       And it has not happened at this speed and this resolution for the whole brain.

   29. SPSpeaker14:03

       Okay.

   30. RVDr. Richa Verma14:04

       Yeah. And, uh, what we use here is, um, we actually first take the water out of the brain, and we call that, uh, you know, cryoprotection.
8. 16:15 – 26:50

   The innovative processes that went into creating the dataset

   1. RVDr. Richa Verma16:15

      Many, many things. So even when I spoke about freezing such large, uh, tissue, that has not been done. Uh, the reason is people have often worked on animal tissue or human tissue. They slice it much thinner, so that you don't have to worry about a very large volume-

   2. SPSpeaker16:32

      Mm

   3. RVDr. Richa Verma16:32

      ... of a biological tissue to be frozen at minus eighty degree centigrade.

   4. SPSpeaker16:37

      Mm.

   5. RVDr. Richa Verma16:37

      And if you think about it, that's a very specific process-

   6. SPSpeaker16:43

      Mm

   7. RVDr. Richa Verma16:43

      ... because tissue is, you know, still has a lot of water in it, even though-

   8. SPSpeaker16:47

      So it can expand.

   9. RVDr. Richa Verma16:48

      Tissue can expand, and depending on if you go too fast-

   10. SPSpeaker16:52

       Mm

   11. RVDr. Richa Verma16:52

       ... it can just crack.

   12. SPSpeaker16:53

       Yeah.

   13. RVDr. Richa Verma16:54

       If you go too slow, you will have these freezing artifacts. So we had to optimize that, and that took a while to be really able to freeze such large organ, and, um-

   14. SPSpeaker17:05

       I can imagine that, like, if, if it's, it's, it's about this big, right?

   15. RVDr. Richa Verma17:09

       Yes.

   16. SPSpeaker17:09

       So if it starts freezing from the middle or starts freezing from-

   17. RVDr. Richa Verma17:11

       Yes, exactly. You will end up seeing the artifacts, and that's of no use to us because we want to image the whole human brain at cell level.

   18. SPSpeaker17:19

       Mm.

   19. RVDr. Richa Verma17:19

       So those cells just start bursting and that's, you know-

   20. SPSpeaker17:24

       Mm

   21. RVDr. Richa Verma17:24

       ... that's pointless for the effort, what we are trying to achieve here.

   22. SPSpeaker17:27

       And I guess if that does happen, you will see it at the end, uh, you may not realize-

   23. RVDr. Richa Verma17:31

       No, when you start slicing, you will see it.

   24. SPSpeaker17:34

       Okay.

   25. RVDr. Richa Verma17:34

       But now, the way we have optimized, uh, doing all the experiments, the rate and the time it took, you know, to freeze, we have a very good idea that if the freezing has gone well or not. And to be honest, we have done this now across hundred plus brains.

   26. SPSpeaker17:50

       Okay.

   27. RVDr. Richa Verma17:50

       And this is quite a standardized process in our lab.

   28. SPSpeaker17:53

       I can understand now why you have such a multidisciplinary team.

   29. RVDr. Richa Verma17:56

       Yeah.

   30. SPSpeaker17:56

       So post-mortem, uh, cryoprotection, freezing, slicing, transfer, and then?
9. 26:50 – 28:55

   Who are the collaborators of this project?

   1. SPSpeaker26:50

      partners who use-

   2. RVDr. Richa Verma26:52

      These data?

   3. SPSpeaker26:53

      Uh, yeah.

   4. RVDr. Richa Verma26:53

      So yeah, as I said, this atlas got released early this year. We now have, uh, collaborators in India and overseas who have been looking at the developing brain in humans as well as in animal model, who are using these different datasets to query their questions, what they have been asking. And that's the first step, and as I said, because this is just six months old atlas, we have already got a lot of attention because, uh, you know, seeing a developing human brain in such detail has not been done before, and that's what, uh, is attracting a lot of collaborators who really want to use this reference datasets.

   5. SPSpeaker27:39

      Can you give us a sense of who these collaborators are? Where do they sit? Are they labs? Are they-

   6. RVDr. Richa Verma27:44

      Yeah, mostly-

   7. SPSpeaker27:45

      Company

   8. RVDr. Richa Verma27:45

      ... are these labs, neuroscience people. So company is a different... That dataset would be used in different context, but in terms of neuroscience research, we have people in Instem, uh, Dr. Bhavna Murdli dharan, she is working closely with us. We have collaborator in UCSF. We are now collaborating with, uh, people in Canada, so different groups across the globe.

   9. SPSpeaker28:13

      Mm.

   10. RVDr. Richa Verma28:14

       And I'm happy to share, or if you go on our website, the entire list of collaborators-

   11. SPSpeaker28:18

       Okay

   12. RVDr. Richa Verma28:18

       ... which is close to twenty plus.

   13. SPSpeaker28:21

       Uh, this is a postmortem intervention.

   14. RVDr. Richa Verma28:23

       Yeah.

   15. SPSpeaker28:23

       Um, is it possible that, uh, MRI kind of techniques will develop to a level that this can be done while the person is alive? You know, the head MRI machine is like one science fiction machine-

   16. RVDr. Richa Verma28:36

       Mm

   17. SPSpeaker28:36

       ... which sits like this, right? And you're saying that that is a one mm resolution.

   18. RVDr. Richa Verma28:41

       The clinical one. So people use higher magnetic strength for animal study.

   19. SPSpeaker28:46

       Mm.

   20. RVDr. Richa Verma28:47

       I don't know if you have heard. So in clinical setup, specifically in India, the highest magnetic strength is three Tesla.

10. 28:55 – 32:00

    Could a living human brain be studied like this someday?

    1. SPSpeaker28:55

       Okay.

    2. RVDr. Richa Verma28:56

       Uh, in animal studies, you can go to eleven Tesla, et cetera, which can give you at a very high cellular resolution. But in living human, putting a human through such a high magnetic strength, I don't think so that's going to happen.

    3. SPSpeaker29:10

       Okay.

    4. RVDr. Richa Verma29:10

       However, what we are hoping as we generate these atlases, you can overlay the cellular information-

    5. SPSpeaker29:19

       Mm

    6. RVDr. Richa Verma29:19

       ... on the MRI, and then create different models to predict what you are seeing in MRI, what would happen at cell level. That's the big goal.

    7. SPSpeaker29:29

       I want to just note here in my notes, it says that the inventor of the CT scan and the MRI both got the Nobel Prize, and they were teams. And-

    8. RVDr. Richa Verma29:36

       Yeah, and the CT scan guy got Nobel Prize for something different than the CT.

    9. SPSpeaker29:40

       Oh, is it?

    10. RVDr. Richa Verma29:41

        Yeah. [chuckles] But don't worry. [chuckles]

    11. SPSpeaker29:42

        Fine, fine. Should have noted this down here. [chuckles]

    12. RVDr. Richa Verma29:45

        Yes. [chuckles]

    13. SPSpeaker29:46

        Um, what, uh... I, I have a question here, but before this, I want to ask you a question. This-- all of this sounds really expensive. Like, does it-- how much... If you can share, I don't know if it's something you can share, but how much does it cost to take one brain through all of this process?

    14. RVDr. Richa Verma30:01

        It is a very expensive, uh, affair, [chuckles] in terms of all the process, the consumable, the chemicals, et cetera. I'm not talking about the equipments yet. And we are looking at, in Indian rupees, each brain would cost you roughly... Again, it also depends on the different protein markers which we are using, but if I can share, it's close to two crores per brain.

    15. SPSpeaker30:27

        Per brain. And we are not even talking of the center cost and the equipment cost-

    16. RVDr. Richa Verma30:29

        No, we are not

    17. SPSpeaker30:30

        ... the people cost.

    18. RVDr. Richa Verma30:30

        We are just talking the consumable.

    19. SPSpeaker30:32

        ... this is a hugely expensive affair then?

    20. RVDr. Richa Verma30:35

        Yes, it is. It is.

    21. SPSpeaker30:36

        Um, and you're saying that the entire dataset is released publicly?

    22. RVDr. Richa Verma30:40

        Yep.

    23. SPSpeaker30:41

        So then my question is, who funds it?

    24. RVDr. Richa Verma30:44

        Oh, we have a long list of funders, and I think in Mohan's, uh, podcast, you have got more of those detailed information. But-

    25. SPSpeaker30:55

        Yeah, he talks about, uh, of course, Go- uh, Kris Gopalakrishnan.

    26. RVDr. Richa Verma30:58

        Yeah. So this work started with the support from Principal Scientific Advisors office-

    27. SPSpeaker31:05

        Mm

    28. RVDr. Richa Verma31:05

        ... which funded the project in twenty twenty Feb, and the work started in March twenty twenty. And of course, the Pratiksha Trust by Kris Gopalakrishnan. We have, uh, specific ischemia work funded by Prem Watsa, who is based in Canada.

    29. SPSpeaker31:25

        Who's also an alumnus.

    30. RVDr. Richa Verma31:26

        Yes. Yes, exactly. And since then, we have got a whole list of different fundings, which has come through, and a lot of philanthropists who are really funding this work because they can really see the potential in what the center can do, and we are very grateful for that.
11. 32:00 – 38:40

    How is neuroscience and brain studies a booming field of research?

    1. SPSpeaker32:00

       like, forty, fifty-

    2. RVDr. Richa Verma32:01

       Absolutely

    3. SPSpeaker32:01

       ... a hundred, two hundred years back to, like, eighty, ninety, we are-

    4. RVDr. Richa Verma32:04

       Yes

    5. SPSpeaker32:04

       ... seeing more and more brain conditions come up.

    6. RVDr. Richa Verma32:07

       Oh, yes.

    7. SPSpeaker32:07

       Um, there's a lot of data that autism itself is a probably something we'll learn more about-

    8. RVDr. Richa Verma32:13

       Yep

    9. SPSpeaker32:14

       ... uh, if we know more about the brain. So I guess this is an area of research that is booming, right?

    10. RVDr. Richa Verma32:19

        It is booming, and it is also booming for several reasons. So there are few organs in our body where we have understood it much better, like the heart. But when it comes to brain, human brain, we understand very, very less. Primary reason, the most of the neuroscience research has been on animal model.

    11. SPSpeaker32:40

        Mm.

    12. RVDr. Richa Verma32:41

        And there are limited things, what you can do on living human brain. And the nature of the human brain, the way it is organized, as I said earlier, it is very heterogeneous. If you take the brain portion from the front of the brain versus the back of the brain, it's very different. So due to several of these factors, we have understood the brain quite well, but we are still far, far away when you really want to understand the organization, the functioning of the human brain. And hence, this particular field of research is, what you called it, as booming.

    13. SPSpeaker33:19

        Mm.

    14. RVDr. Richa Verma33:20

        But it's going to continue, and especially when we add the modern-day computational tools. We are all hoping to address a lot of unresolved questions for decades.

    15. SPSpeaker33:33

        Mm.

    16. RVDr. Richa Verma33:33

        Because when you have these large datasets, uh, you really want good AI models to be looking at these patterns, which, you know, human eye just can't pick it up.

    17. SPSpeaker33:46

        Mm.

    18. RVDr. Richa Verma33:46

        So yes, this particular field is expanding, expanding at different aspects, and that is something which I can say for youngsters, is a good place to be if you want to pursue a career in neuroscience or computational research within neuroscience group.

    19. SPSpeaker34:05

        Mm. Yeah. Yeah, I can imagine that. It's, uh... it's-- I, I want to ask you a little bit of detail here.

    20. RVDr. Richa Verma34:14

        Yeah.

    21. SPSpeaker34:14

        This is very foundational research in the sense that-

    22. RVDr. Richa Verma34:16

        Yes, basic science

    23. SPSpeaker34:17

        ... we talk of foundation and translation research-

    24. RVDr. Richa Verma34:19

        Yes, yeah

    25. SPSpeaker34:20

        ... usually, the criticism of research from Indian labs or IITs is that it's more translational.

    26. RVDr. Richa Verma34:27

        Mm-hmm.

    27. SPSpeaker34:27

        Uh, it's, you know, application.

    28. RVDr. Richa Verma34:30

        Yep.

    29. SPSpeaker34:30

        But this is not application research. This is-

    30. RVDr. Richa Verma34:32

        Not yet
12. 38:40 – 41:20

    Dr. Richa’s journey to neuroscience research

    1. SPSpeaker38:40

       uh, I, I want to ask you, what is your background? How did you land up here? [laughing]

    2. RVDr. Richa Verma38:44

       Right one. [laughing]

    3. SPSpeaker38:46

       What is this journey that you have taken, and how can people take the same journey as you've taken?

    4. RVDr. Richa Verma38:50

       Nice. Nice. So, going back, I don't know how far do I have to go back. But-

    5. SPSpeaker38:57

       Why don't you start as an undergrad student?

    6. RVDr. Richa Verma38:59

       Yeah. Undergrad.

    7. SPSpeaker38:59

       Or a high school student.

    8. RVDr. Richa Verma39:00

       No, high school, we'll skip it. But undergrad, I actually did it in Chennai, Sri Sankar 眼 Netralya.

    9. SPSpeaker39:07

       Okay.

    10. RVDr. Richa Verma39:07

        I did my undergrad in optometry, and then I went to Australia to do my PhD at University of Melbourne in retinal electrophysiology. Retina, which is part of the eye.

    11. SPSpeaker39:22

        Okay.

    12. RVDr. Richa Verma39:22

        And, uh, that's sort of, you know, motivated me to go deeper at cell level, and sort of the retina is the neural tissue of the eye, and that's connected to the brain, and that's where I started getting interested. And I did my postdoc at Monash University in Melbourne, working on monkey brain.

    13. SPSpeaker39:43

        Ah, you mentioned monkey brain. [laughing] I wanted to ask you about that.

    14. RVDr. Richa Verma39:46

        So I used to work on doing the electrophysiology, where we would do recordings from single neuron, but also then do the similar work, slicing the brain and looking at different brain regions-

    15. SPSpeaker39:59

        Hmm

    16. RVDr. Richa Verma39:59

        ... within the monkey brain. And I was also looking at the retina. Then, I joined as a faculty at School of Medicine, School of Optometry at Deakin University, where I was doing a lot of higher education, teaching, learning, et cetera. And that was a very good experience because, you know, only when you teach, you learn more. [chuckles] And, uh, that was the time when we sort of heard about Computational Brain Research Center-

    17. SPSpeaker40:29

        Okay

    18. RVDr. Richa Verma40:29

        ... coming up here. And, um, I was in Australia for fourteen, fifteen years, so it was a big step, you know, taking this decision. So I did move here in 2017, mid of 2017. I was working with Teaching Learning Center, IIT Madras, L.V. Prasad Eye Institute in Hyderabad, and happy that the funding came through and the Brain Centre work started. So when we started the work at Brain Centre in 2020, it was just five of us, including Professor Mohan.

    19. SPSpeaker41:04

        Yeah.

    20. RVDr. Richa Verma41:04

        Yeah. And today, as I said, we are looking at hundred and twenty plus people.

    21. SPSpeaker41:08

        Hmm.

    22. RVDr. Richa Verma41:09

        So it has really been an exponential rise.

    23. SPSpeaker41:12

        Yeah. You, you sort of gave us a little bit of breakup here, but Professor Mohan is the principal investigator.

    24. RVDr. Richa Verma41:17

        Yes, absolutely.

    25. SPSpeaker41:18

        And, uh, Professor Jayaraj is the

13. 41:20 – 43:35

    The interdisciplinary nature of brain imaging studies

    1. SPSpeaker41:20

       co-principal investigator. They, they are both electrical engineering professors.

    2. RVDr. Richa Verma41:23

       Yes. Yes.

    3. SPSpeaker41:24

       I'm always fascinated by the fact that Professor Mohan is an electrical prof, who has such a high impact on the-

    4. RVDr. Richa Verma41:30

       Hmm

    5. SPSpeaker41:30

       ... on the biosciences.

    6. RVDr. Richa Verma41:32

       Yes. Yes.

    7. SPSpeaker41:32

       And-

    8. RVDr. Richa Verma41:33

       So I think you would have... I mean, you know this, Mohan has another-- he heads the another center-

    9. SPSpeaker41:38

       Yeah

    10. RVDr. Richa Verma41:38

        ... Health Technology Innovation Centre-

    11. SPSpeaker41:40

        Mm

    12. RVDr. Richa Verma41:40

        ... which is located at the research park. And that work, I think, if I'm not wrong, started around two thousand eleven and twelve. So he's very well connected to the medical faculty-

    13. SPSpeaker41:53

        Field

    14. RVDr. Richa Verma41:54

        ... field in India, developing technologies, et cetera, for a long time.

    15. SPSpeaker41:57

        Hmm.

    16. RVDr. Richa Verma41:58

        So I'm glad he got interested in the brain. And, uh, uh, to process this whole human brain, we had to build a lot of equipments. So if you look in the market, most of these steps which I spoke about, staining, sectioning, et cetera, most of it is designed for small brains or small portions of human brain. So we had to develop a lot of technology and equipments, and if you have visited our center, you will be, you know, able to spot most of those equipments were all built here, R&D in progress, but we have been using for the last three years.

    17. SPSpeaker42:35

        Hmm.

    18. RVDr. Richa Verma42:35

        So that's where the entire engineering experience-

    19. SPSpeaker42:38

        Comes in

    20. RVDr. Richa Verma42:39

        ... comes in picture. And then, once the data starts coming, coming out-... the whole computational team is now expanding because we are building very strong analytics. Lot of youngsters are joining our team, trying to build different AI models to understand the brain. And as I said, this is a tougher problem because the brain is very heterogeneous. Uh, if your model works very well in this part of the brain, in a small-

    21. SPSpeaker43:06

        It may not work.

    22. RVDr. Richa Verma43:07

        -portion of the tissue, it will not work there, and it will not work so easily from one brain to the other.

    23. SPSpeaker43:12

        Mm.

    24. RVDr. Richa Verma43:13

        Yeah, so...

    25. SPSpeaker43:15

        Thank you for sharing so much. I just want to note that looking at your career-

    26. RVDr. Richa Verma43:19

        Yeah

    27. SPSpeaker43:19

        ... and, uh, Professor Mohan's career, and I'm sure the other people-

    28. RVDr. Richa Verma43:21

        Many more people, yeah.

    29. SPSpeaker43:22

        Maybe you can tell us a little bit more.

    30. RVDr. Richa Verma43:23

        Yes.
14. 43:35 – 49:40

    Can you really stick to your degree when most things are so interdisciplinary now?

    1. SPSpeaker43:35

       too stuck about the degree that they get.

    2. RVDr. Richa Verma43:37

       [laughing]

    3. SPSpeaker43:37

       And, and I, I can see that you started with the I.

    4. RVDr. Richa Verma43:40

       Yes.

    5. SPSpeaker43:40

       And there's so much movement, right?

    6. RVDr. Richa Verma43:42

       Yep.

    7. SPSpeaker43:43

       And to-- and, and for me, that's so obvious. You cannot stick to the first-year course-

    8. RVDr. Richa Verma43:49

       No, not at all

    9. SPSpeaker43:50

       ... that you did. It's not going to be one linear path.

    10. RVDr. Richa Verma43:52

        No, no, not at all.

    11. SPSpeaker43:53

        Mm.

    12. RVDr. Richa Verma43:54

        No, I'm glad you're asking these questions because, you know, if you look at the Western education system, and I'm not talking about that's the best system, uh, there are many things which is really good-

    13. SPSpeaker44:07

        Yeah, there are pros and cons.

    14. RVDr. Richa Verma44:08

        There are pros and cons of every system. But one of the thing which was very obvious to me when I went to Australia was, people were joining medicine with arts background. That is just unheard in our country. And if you look deeper into it, the-- it's the training which happens at undergrad level or even at school level, you need to train us-- or rather, we need to train our students more into critical thinking, problem solving, so that they can move from one field to the other based on their interest.

    15. SPSpeaker44:41

        Mm.

    16. RVDr. Richa Verma44:42

        And if you think about when you are, you know, sixteen, eighteen years, twenty year old, you yourself don't know what is your passion, what you're really interested, except for few.

    17. SPSpeaker44:51

        Yeah.

    18. RVDr. Richa Verma44:51

        So if we equip our students where they can move from one field to the other, they should not be limited: "Oh, I did my undergrad in biology-

    19. SPSpeaker45:02

        Mm.

    20. RVDr. Richa Verma45:02

        -so I can't do coding," et cetera.

    21. SPSpeaker45:05

        Yeah.

    22. RVDr. Richa Verma45:05

        And as you see, most of the people are scientists, who do really well. They have this, uh, you know, interdisciplinary switch very easily. They can understand, and if you look into it, they know how to solve the problem.

    23. SPSpeaker45:19

        Yeah.

    24. RVDr. Richa Verma45:19

        They have learned how to learn.

    25. SPSpeaker45:21

        Yeah, I agree with you. But I want to add that in my mind-

    26. RVDr. Richa Verma45:24

        Yeah

    27. SPSpeaker45:24

        ... the, the conversation at a sixteen, seventeen-year-old-

    28. RVDr. Richa Verma45:28

        Mm

    29. SPSpeaker45:28

        -maybe a little later, till twenty-

    30. RVDr. Richa Verma45:29

        Yeah
15. 49:40 – 50:50

    Dr. Richa’s message to the youth

    1. SPSpeaker49:40

       low-

    2. RVDr. Richa Verma49:40

       Yeah

    3. SPSpeaker49:40

       ... and you always felt like, "Oh, my God, I have to get out of here."

    4. RVDr. Richa Verma49:43

       Yes, yes.

    5. SPSpeaker49:44

       Uh-

    6. RVDr. Richa Verma49:45

       No, so that way we are open, but we definitely, you know, I hope even this reaches to a lot of youngsters, and they write to us. They can go on our website, or they can even send an email directly on my email account, which they will find on the website.

    7. SPSpeaker50:01

       Mm.

    8. RVDr. Richa Verma50:02

       And, you know, we are really open in hiring great group of people across the different disciplines.

    9. SPSpeaker50:09

       Mm. Okay, I'm going through my notes-

    10. RVDr. Richa Verma50:12

        Yeah

    11. SPSpeaker50:12

        ... and I realize that one thing we've not spoken about, it's sort of sitting aside. I was searching online-

    12. RVDr. Richa Verma50:20

        Mm-hmm

    13. SPSpeaker50:20

        ... which is, I mean, I use Perplexity because... Sorry, I wanted to say I use Perplexity [chuckles] because there's an IITM co-founder in Perplexity. So did you know that? Uh, one of the Perplexity co-founders was a undergrad here.

    14. RVDr. Richa Verma50:33

        Ah, okay.

    15. SPSpeaker50:34

        Yeah.

    16. RVDr. Richa Verma50:34

        Okay.

    17. SPSpeaker50:34

        So we have a little bit of a bias towards Perplexity.

    18. RVDr. Richa Verma50:37

        Okay. [chuckles]

    19. SPSpeaker50:38

        So, um, I was, I was plexing it-

    20. RVDr. Richa Verma50:42

        Yeah

    21. SPSpeaker50:42

        ... and I realized that at some point, uh, Brain Centre came up in an NVIDIA announcement.

    22. RVDr. Richa Verma50:48

        Ah, okay, yes.

    23. SPSpeaker50:49

        And there's a presenter.

16. 50:50 – 53:16

    Nvidia X Dharani collaboration

    1. SPSpeaker50:50

       She takes about two minutes to explain, saying that, "Oh, we are collaborating with this-

    2. RVDr. Richa Verma50:54

       Yeah

    3. SPSpeaker50:54

       ... Brain Centre at IIT Madras in Chennai," and she talks about something called a Neurovoyager.

    4. RVDr. Richa Verma50:58

       Mm-hmm.

    5. SPSpeaker50:59

       Um, I'm curious because we spoke about Dharani, and we spoke about Atlas.

    6. RVDr. Richa Verma51:03

       Yeah.

    7. SPSpeaker51:03

       Uh, we never spoke about the Neurovoyager. So what is this thing? And my bigger question was: [chuckles] Why does it need a collaboration with NVIDIA?

    8. RVDr. Richa Verma51:09

       NVIDIA. Excellent question. So as I said, you know, we are digitizing these dataset at very high resolution. We spoke about 0.5 micron, and if you think about 10,000 of these slices, each one digitized at 0.5 micron resolution, when the entire whole adult brain data is digitized, we are talking the data size as few petabytes.

    9. SPSpeaker51:35

       Mm.

    10. RVDr. Richa Verma51:36

        Now, how do you manage these large data site, uh, sorry, datasets? How do you visualize? How do you perform different analytics? Because it's not just the size, the speed at which we are generating these datasets, and as I said, our goal is to get the 100 human brain digital datasets out soon. That's where NVIDIA come into picture. The tools and the computational tools which they are providing us is really helping to put all of this together.

    11. SPSpeaker52:05

        Nice. It becomes- it goes from a biology engineering problem to a data science problem.

    12. RVDr. Richa Verma52:10

        Yes, yes.

    13. SPSpeaker52:10

        And I can, I can imagine what you're saying. If I'm a data s- researcher, if I'm a brain researcher, and I'm accessing your data-

    14. RVDr. Richa Verma52:17

        Mm-hmm

    15. SPSpeaker52:17

        ... and I'm looking at slices, and if it takes me, like, half a day-

    16. RVDr. Richa Verma52:22

        Yes

    17. SPSpeaker52:22

        ... to just look at the slices, that-

    18. RVDr. Richa Verma52:24

        That's, that's of no use.

    19. SPSpeaker52:25

        Yeah.

    20. RVDr. Richa Verma52:26

        You are better off just coming and asking me here.

    21. SPSpeaker52:28

        Yeah.

    22. RVDr. Richa Verma52:28

        So that's, that is something... And as I said, hence, as this process of, you know, generating these digital datasets got standardized in the lab, our computational work has expanded again exponentially. Because, A, these datasets are unique. These are at very high resolution and very large datasets, which for in a neuroscience community, literally every brain slice could be a PhD project. There's so much of information there. But how do you get all of this information? How do you do this analysis? That's where you need very strong, robust, reliable computational tool and visualization tool, and that's where NVIDIA comes into picture. Sorry, you asked about the Neurovoyager.

17. 53:16 – 54:10

    What is the Neurovoyager?

    1. SPSpeaker53:16

       Yeah.

    2. RVDr. Richa Verma53:16

       So if you... Yeah, so if you go on our website, Neurovoyager allows you to explore all our datasets, but also query questions related to a particular brain condition, which then uses datasets or publications or information which has been available online.

    3. SPSpeaker53:33

       Oh, right. So I could just type, saying, "Show me this."

    4. RVDr. Richa Verma53:35

       Yes, yes.

    5. SPSpeaker53:36

       Yeah.

    6. RVDr. Richa Verma53:36

       And it also gives you access to a lot of un- not currently with datas which we have not released. You can access those.

    7. SPSpeaker53:43

       Okay. Cool, this is amazing. So the interdisciplinary team has engineers from mechanical, computational, electrical, uh, life sciences, people from life sciences background, neuroscience background, radiology background, image processing background, technicians of all the equipment you use, plus you have collaborators with hospitals, you have medical collaborators, you have research lab collaborators.

    8. RVDr. Richa Verma54:05

       Yeah.

    9. SPSpeaker54:06

       This is a huge effort.

    10. RVDr. Richa Verma54:07

        Massive, massive.

    11. SPSpeaker54:08

        Um, thank you for speaking to us.

18. 54:10 – 55:52

    Closing thoughts & reflections

    1. SPSpeaker54:10

       I just want to close a little bit by learning about Dr. Jay-

    2. RVDr. Richa Verma54:14

       Yeah

    3. SPSpeaker54:14

       ... who's your co-conspirator, per se, right?

    4. RVDr. Richa Verma54:16

       [laughing] Yeah.

    5. SPSpeaker54:19

       What is his background? How did he come in?

    6. RVDr. Richa Verma54:20

       So Jay has got very similar background, but he has spent more time in neuroscience. He used to work on monkey and cat brains, and he's really developed as a computational neuroscientist, working with the center again for... He actually moved here twenty sixteen, so much longer. And, um, yeah, so he comes with the skill of understanding the brain, but also understanding the computational tools and techniques required to do these sort of analysis.

    7. SPSpeaker54:56

       Hmm. I got it.

    8. RVDr. Richa Verma54:58

       You got it?

    9. SPSpeaker54:59

       I hope, [chuckles] I hope the audience follows.

    10. RVDr. Richa Verma55:01

        Yes.

    11. SPSpeaker55:02

        Okay, Dr Richa, thank you so much for joining us. Uh, it was a pleasure.

    12. RVDr. Richa Verma55:06

        Thank you, first, for having me here. Uh, I'm not a person who goes often, or rather, hardly any time, on social media or anything, so this is a big step for me. But I'm very passionate in trying to attract young minds in our country to come and work with us and put this word out, the type of work which is happening at the Brain Centre. So thank you for giving me this opportunity, and looking forward to having more of these sessions.

    13. SPSpeaker55:35

        You're welcome.

    14. RVDr. Richa Verma55:35

        Thank you, Amrit.

    15. SPSpeaker55:36

        Okay, so there you have it. Please like, share, subscribe, comment below, and, uh, if you want to doc- reach Dr Richa, please look up the Brain Centre website and contact them. Thank you so much. [upbeat music]

Episode duration: 55:52