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00:11 Tiffany Hogan: Welcome to See Hear Speak Podcast Episode 25. In this Episode I talk with Nicole Landi, Associate Professor at the University of Connecticut. Nicole and I discuss some big hot topics such as genetics, brain imaging, and poor comprehenders.
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00:57 Tiffany Hogan: Welcome to See Hear Speak podcast. I have Nicole Landi today, and I will start by having her introduce herself.
01:05 Nicole Landi: So, thank you for having me, Tiffany. My name is Nicole Landi as you just said. I am an Associate Professor of Psychological Sciences at the University of Connecticut, and I also am the director of EEG research at Haskins Laboratories.
01:20 Tiffany Hogan: Well, I am so glad to have you. We have tried to schedule this since SRCLD in June and it has been a series of unfortunate events, and today, we have pieced it together. You on the phone, me on the computer and we're making it happen, so I'm glad... Glad we are able to do that and just so happy to have you today. I'm gonna jump right in and ask you a tricky question but I know you'll be able to answer. So you study reading disorders from genes to the brain to behavior. I was wondering if you could give us an example of what this looks like, and then also what made you crazy enough to wanna tackle this complex relationship cause most researchers focus on one or two areas, and you are able to pull together all of these areas.
02:03 Nicole Landi: Yeah, thanks for the question, it's a really great one. And I can... I'll answer it with an example of a data set that we're actually reworking currently. So this is one where we initially found a relationship between a gene called BDNF that's the gene that comes from the Brain Derived Neurotrophic Factor protein. And we found in the study... And it was published in I think 2016, Jasińska et al. And we found that individuals who had the risk allele for this gene and so those are... Those that have the met allele and it's this particular... I should have said, this, this is the bell met polymorphism on the BDNF gene. So those individuals who had the risk allele, who were met carriers, they performed more poorly on some assessments, so on measures of reading comprehension and on measures of phonological memory.
03:01 Nicole Landi: And when they were reading in a scanner, they actually showed greater activation on the right hemisphere in a number of regions suggesting that they weren't utilizing the left hemisphere as we typically see for single word reading. But then we also found when we took those same regions on the right, we saw that those were actually positively correlated with a variety of different reading scores. So we published that, and that was a little bit perplexing that relationship... That relationship there between the reading scores and the activation of the level of brain. And so, with some colleagues, we just reanalyzed this data recently using a mediation analysis. And what we found... And this is what we predicted so that's really exciting. Is when you have individuals with the risk allele those individuals with the risk allele indeed overall, they have poor phonological skill and they use the left hemisphere, less. But those individuals with that risk allele who activate more on the right are better readers, so like within that group.
04:00 Tiffany Hogan: Huh.
04:02 Nicole Landi: Yeah, so it's just that for those individuals… There's some risk there with that particular allele and that you have some poor phonological processes. But maybe some of those folks are compensating on the right and that was what we were seeing in the group contrast. And that bears out in the mediation analysis.
04:18 Tiffany Hogan: Oh, that's very cool.
04:20 Nicole Landi: Yeah, it's one example of the kind of work that we've done in that area. And as you can hear from that story it does take more work. So sometimes, what you initially find makes... You find something new and a piece of it makes sense, but then there's also a piece of it that's not quite so obvious because you do have three levels of analysis, so there's more chance for that to happen.
04:40 Tiffany Hogan: Mm-hmm. What do these kids look like when you see them or how do you find these kids with this met hit?
04:48 Nicole Landi: Ahh, yeah. So, I should have specified that. So, this is a common variant.
04:50 Tiffany Hogan: Oh, okay.
04:55 Nicole Landi: Yeah, so a lot of what we study in my lab... I should have spent a little more time elaborating on this. But we study common variants. So, you can look for rare variants that have been say associated with dyslexia, but they're rare. [chuckle]
05:08 Tiffany Hogan: Right.
05:09 Nicole Landi: So that's gonna be harder to find. And if you wanna bring in kids and you wanna get multiple levels where you're getting brain and behavioral measures, and genetic measures, you gonna need a lot of kids. So to do that, we study common variants. And this particular... This bell met polymorphism, has been studied relatively extensively in other domains, it just hadn't been applied to reading, yet. So people have studied it pretty extensively in the memory literature, and so we thought, "Okay, there might be an association here." And I think it's really important that people do consider these kinds of variations, where there's an association with general cognitive function, because we know that reading draws on so many resources. So when you have a really complex skill like reading you're not... You're not gonna get something like a single gene that's responsible, you're gonna get a number of different associations between genetic variation and behavior and patterns and brain and so this is just one that we explored.
06:02 Tiffany Hogan: That makes sense, yeah. And so what is your new project then? You said you have one that you're following up, is that right?
06:08 Nicole Landi: Yeah, so the follow-up... The follow-up there, is part of a larger project, so we are... A group of us is part of the Florida Learning Disabilities Research Center so that's a big project down in Florida, headed at Florida State. And we have one project on that, P50. And in our project, we're doing both mega and meta analyses of gene, brain behavior relationship. So that second analysis that I told you about, that mediation analysis is part of that initiative. So basically, we're taking a lot of data we're aggregating it together, we're doing some reanalysis of analysis that have already been done and published and then we're also by combining lots of data together... So these are all sites that are contributing, that have a lot of imaging data, they have genetic data on the same people and they have behavioral data on the same people. Then we can go back in and interrogate the data and look for new associations, new variations in genes associated with behavior, or associated with the neuro endophenotypes because we'll have a really large data set.
07:09 Tiffany Hogan: Oh, that's fantastic. And it starts to make me think that you talk about this common variation that it goes back to looking at all these skills on a continuum and you're trying to capture some of that continuum, and think about the mechanisms driving those individual differences, correct?
07:25 Nicole Landi: Yeah, exactly.
07:27 Tiffany Hogan: Oh, that's very cool. It seems very futuristic, but I'm wondering what you think is the next frontier in this vain of understanding these relationships and how you see that impacting assessment and intervention in the future?
07:42 Nicole Landi: Yeah, no, that's a great question. There's still so much foundational work to be done here. It's funny, you find one association will get out there, people will study the mechanisms behind one association for years and years and years and still not understand it really well. So FOXP2 is a really great example of this, that a lot of your listeners will be familiar with. And there has been a lot of great work on this, but initially you just have the association. And that's with a specific family that had really severe impairment. Then you get some studies that come along and find that even in more typical populations, you do see some associations with particular snips on FOXP2 and language behavior. Then you have a lot more animal work that's really probing the mechanisms there. And so, it takes some time to really tease apart these relationships. So what's happening in terms of the next frontier? Well, there's a lot of basic foundational stuff still being done. So, there's a lot of associations that get identified. Then you have to make sure those associations are robust. Do you see them replicate right across multiple samples? So that's still ongoing.
08:55 Nicole Landi: Then you have the basic animal work, where you have to kind of explore the mechanisms. How exactly is it that this particular variation goes on to impact brain and behavior? That's still being done. And then maybe in the most futuristic sense you have the big data kind of questions. So for example, the work that I do is really... So far has boiled down these genetic variations into almost a group analysis. You'll say, "Okay these guys have the risk allele, these guys don't. How do they look differently at the level of brain and how does that relate to behavior? And that's great, but those kind of single variations they don't happen in isolation.
09:36 Nicole Landi: And we know there are... They're gonna be gene-by-gene interactions, there's gonna be multiple genes that impact reading. So really what we need to start doing is looking at those together so we can start by looking at a couple of genes that are known to have a relationship with each other. You can also do what we're doing a lot in this big data project, I mentioned to you before was trying something a little bit new which is to start with a brain endophenotype to start with something, let's say its volume in the superior temporal gyrus or something. And put that into a model and try to identify new genes using that instead of behavior, for example. So there's a lot of things that we can do that will help move the field forward and help us identify both new variants but also, identify interactions among relationships that maybe have been already identified or partially identified and then other work that's gonna further probe the mechanism for those associations that have been identified.
10:33 Tiffany Hogan: Wow, that's really cool. I love how you're taking it from so many different angles to really understand what's driving the differences we see in behavior and vice versa. That's really quite...
10:44 Nicole Landi: Yeah, it's really kind of required here, there's a lot to consider at once.
10:49 Tiffany Hogan: Yes, absolutely. It seems like... Your point's well taken. I think that you have to step back, look at some discreet pieces and then put it back into the puzzle and then at some point you can pull that puzzle together.
11:00 Nicole Landi: Yeah, that's right.
11:02 Tiffany Hogan: That makes a lot of sense. And I think... I was thinking about what we've learned from the brain studies in reading and less so in language but also in language. Some of those basic ideas that we take for... I feel like I take them for granted now. For instance, that reading is a neurobiological process that a child comes to the table with their genetic makeup and how that affects their brain, and then how that interacts with the environment is something that such a big step forward that I think we take for granted now.
11:34 Nicole Landi: Yeah, no, I agree. And I think it's funny because we know that that's the case, but exactly how it all plays out is another story. And so that takes a lot more exploration, and it's not something that can happen really quickly. And so we all have to pay for our patience unfortunately, sometimes.
11:56 Tiffany Hogan: Oh, I know. I'm not very patient. That is definitely something I struggle with is being patient, but I think science has taught me patience for sure, seeing things move over time slowly, but also kind of stay stepping back and thinking about the leaps we've made, even though they seem like they've been slow over time just the fact that now we have most people I would argue, that a lot of people in society now have a sense that... I hope they do, that a child is not lazy, when they can't read for instance. It's not something they're choosing, it's that they have... They're doing the best they can with the brain, they have. So...
12:35 Nicole Landi: Yeah, yeah, yeah. And some of that has been rapid discovery over the past 10 to 15 years but some of it has been improved dissemination.
12:45 Nicole Landi: And so it does really seem though the message has gotten out there, and more recently there's more of a paradigm shift in people's thinking that's spreading.
12:53 Tiffany Hogan: Yeah, I agree. But at the same time, I do think there is this sense that, "Oh, you can't diagnose dyslexia unless you have a brain scan."
13:03 Tiffany Hogan: If someone said that to you, what would you say?
13:05 Nicole Landi: Yeah. That's definitely not true. Right Sue. I think it's great that people are trying to make contact with the cognitive neuroscience approaches and utilize them. And they definitely have... They add value to our studies. They really add a level of understanding, especially in terms of mechanism. But when you're talking about diagnosing a child that's really a behavioral issue, right? It's about their level of reading or their level of language and that's something that our behavioral assessments are quite good at. There's always room for improvement, but I don't think that in terms of assessment or diagnosis of dyslexia right now we're adding... We are adding there in the area of neuroimaging. I think we probably are going to begin to see some value-added... Maybe value is not the right word there, some additional diagnostic value when thinking about sub-types and mechanisms for groups or classes of individuals. And maybe someday there might be something more individualistic or at the individual level. But right now we're just not there.
14:18 Tiffany Hogan: Yeah. I think that is helpful because unfortunately sometimes when I hear that argument evoked it's to have children not be diagnosed as opposed to trying to advocate for diagnosis or not get services and those kinds of things. So that's one of the myths I've been pushing to when I talk to people is that we do know a lot from the brain, but we aren't to the level now where we can just do a scan and say, "Oh yep, you definitely have it." Or that you require a scan. And kids... Yeah, doing...
14:45 Nicole Landi: Yeah.
14:46 Tiffany Hogan: And I know of course not, but I do think it's almost like the pendulum has to swing almost that far to then get the message out that it's important that the brain is... We're learning a lot from the brain when it comes to dyslexia. But it's not that far yet.
15:01 Nicole Landi: Yeah, no. I agree with you. I agree, yeah.
15:04 Tiffany Hogan: So we talking a lot about word reading versus reading comprehension, and you have done studies of children who have reading comprehension deficits or word reading deficits or both, and I wanted to talk to you a bit about those two different populations of children. So those who have word reading problems only with good language comprehension, those who have language comprehension problems with good word reading and how they're the same, how they're different and if you've done work on some of their brain patterns and what you've found?
15:31 Nicole Landi: Yeah. It's interesting. I almost start... I don't wanna say started. But early on in my graduate training I became really interested in kids with comprehension problems. And it was just timing that there had been a bunch of interesting studies coming out of the UK that had been looking at kids with comprehension specific impairments. And I found that really fascinating. And I don't know if it was just because everybody around me was studying decoding-based problems and phonological problems, but I found semantics really fascinating. I always had. And so... And the prevailing theory that was being thought about at that moment was maybe these kids have a semantic deficit, maybe it's something like what you see in semantic deficit patients. Not the same but there could be something like that going on here. And so I thought that was really interesting and that's what got me started on that.
16:30 Nicole Landi: And I have continued to study that population of kids. So, these are kids who don't have decoding problems. They don't have phonological problems, but they do have comprehension deficits. And one of the areas in which I really wanted to contribute there was to talk about this being a language problem, not a reading problem. With the idea that those who individuals are gonna have those not code-based problems with reading, are gonna be having problems with language comprehension and it's gonna be in the syntax and in the semantics. And can we find... Can we reduce it? Can we see the lowest level, piece of this puzzle? And I would say that while we have learned a lot about poor comprehenders as they're often called, I don't think we've ever reduced it to that small piece to be able to say, "Look, it's this semantic thing or this, it's the syntactic thing." It doesn't look like that. And the kind of imaging studies that have come out, there's far fewer of them relative to, say, dyslexia or some other low level phonological based reading problems.
17:36 Nicole Landi: There are far fewer of them. And many of them look at sentence processing. For example, some of them do look at word reading, and you do see some differences that look like they could be say semantic, some higher-level language processing, some more right hemispheres memory regions involved. But I wouldn't say that it's as clear cut. I feel like we have many, many years of research to look at for phonological based reading problems or word level reading problems. And where we can see reliable patterns at least, there's some differences and people are still working out the nuances of course. But with respect to comprehension problems, it's much less clear cut. And I think we just... We need a lot more work there. And as with the study of dyslexia and other reading disabilities, word level reading disability, I think it's gonna take some time in terms of those thinking about classification and who's in your sample, but also in terms of the methodology for best studying it. So I can't really make a clear cut distinction in terms of the brain in terms of how these guys differ at that level.
18:38 Tiffany Hogan: Yeah. But I think that is some exciting work. And I'll tell the listeners you and I have talked about doing that work which would be very awesome.
18:46 Nicole Landi: Yeah.
18:47 Tiffany Hogan: Because of my interest in developmental language disorder. And we know those children with developmental language disorder tend to become those poor comprehenders. It would be great to look at some of those differences because some of the kids with developmental language disorder have good word reading over time which is surprising and yet they have this language comprehension deficit. It seems like it would be a very cool approach to think about how you've studied these other relationships and apply it to developmental language disorder. In such a needed area I think.
19:15 Nicole Landi: Yeah. And I'm so glad you brought that up because I didn't mention developmental language disorder. But as you know, there's so few studies in that domain too, imaging space... There's more now. It's a little tricky cause people have used different names and such... And there's been a lot of disagreement in terms of how to classify those kids. But there's less of it relative to word reading problems. And so I do think it will take an approach where one's looking at continuous variation along multiple domains as well as looking at group level differences considering for example, like we've talked about individuals with dyslexia, individuals with language impairment, developmental language disorder and individuals who look like poor comprehenders. Cause there's gonna be overlap in some domains and not in others. But people haven't necessarily systematically compared those three groups of kids at the neurobiological level.
20:06 Tiffany Hogan: Absolutely. And you study children with brain imaging. How hard is it to work with children in the fMRI? I have people ask me that question sometimes.
20:16 Nicole Landi: Yeah. It's challenging for sure. The population of children that I've worked with tends to be a little bit older. So, I think it's even more challenging for those working with really young children. So pre-readers and kindergarteners. We've had a few studies where we start about as young as kindergarten but for the most part, we've been imaging older children. So older school-age children in adolescence with fMRI and structural MRI. When we look at younger kids, we tend to use... And even not with younger kids, with school age children too. I use a lot of EEG. And in some school-based work that I'm doing now, we're using EEG. And that is less difficult to use with children. It's a little bit more motion tolerant. You can do it in a naturalistic setting, it's less anxiety provoking. It doesn't give you the same information. So for example, you can't get as a fine grain spatial resolution with EEG that you're gonna get with MRI but you can get a lot of other information. And in particular you can get great information about the timing of when things happen in the brain. And so it's really good for some things. And so I try to use those in a complimentary way, those two approaches. But yeah, there are definitely some special challenges with all of these methods for working with children. And motion is a big one, anxiety is another one.
21:40 Tiffany Hogan: And can you tell the listeners who don't know what the difference is between the EEG versus an fMRI for instance?
21:47 Nicole Landi: Yeah. Sure. So fMRI is gonna involve magnet. And so you're gonna have to go into a very large magnet at a scanner at an imaging center. And fMRI, a functional MRI that is, is going to track the BOLD response, the blood oxygen level dependent response. And so kids lie down in the magnet and they perform a particular task and this imaging methodology can track where blood flow, where blood is flowing which is a indirect index of areas that have been using energy to do a task. And then with EEG, so that's the electroencephalogram we are putting electrodes, and these are totally non-invasive. We're just recording on the scalp and we're recording small voltage seizures. And what we're actually picking up is electrical communication, index by voltages change of the scalp from large populations of neurons. And so this is nice because it's really sensitive to timing cause it's electrical activity unlike the blood signal that you're getting with MRI because that tends to be very sluggish in response to actual neural activation.
22:58 Tiffany Hogan: And then have you used MEG before?
23:01 Nicole Landi: I have not. So I am not the right person to tell you about MEG.
23:05 Tiffany Hogan: I've done a little bit of MEG but oh, having to say it so Magne... I have to think about how to say it.
23:11 Nicole Landi: Magnetoencephalography.
23:13 Tiffany Hogan: Yeah. See, I knew you could say it. It's interesting.
23:17 Nicole Landi: But I don't do it.
23:18 Tiffany Hogan: It almost seems like I've done some attempt to do some of that work and I've had a postdoc who we just published a paper recently using the MEG. But one thing I liked about the MEG is it almost seemed like it combined some of those components cause you can get... Based on the timing you can get some fairly good timing and you can start to get based on some of the algorithms some good location. But you're still dealing with similar kinds of things that relate to motion and working with young children. But it seemed like a nice compliment to the suite of brain imaging techniques that could be used.
23:52 Nicole Landi: Yeah, yeah. For sure. For whatever reason it seems like that's caught on a lot more over in Europe than it has in the US. So, we have far fewer MEG researchers here in the US.
24:04 Tiffany Hogan: Yeah. You're right. And it really does depend on when you're doing that work. You have to work with someone who knows the MEG or you're not gonna get the work done. You really have to work with, yes, an expert in that area. And then have you ever done anything with fNIR. That's another one I dabbled in for a little bit. Yeah.
24:19 Nicole Landi: Yeah. So that we do have a couple of fNIR set-ups that have scans. And I have some... I'm tangential to some work there. So fNIR is there you're tracking the blood response as well. So, it's also the hemodynamic response and you are a little bit more directly measuring the oxy and de-oxygenated hemoglobin which gives you a tiny bit better sampling resolution in time. But really, you're still dependent on this sluggish response. So, it's still better for where than when. And then you're doing that with light and those are by probes on the scalp. And so there are some other limitations there. Scalp thickness can be a problem or hair and things like that. But again, I've been tangential to that work. So, I just know about it. I can't speak as much to its limitations or other issues.
25:13 Tiffany Hogan: Yeah. One of reasons I was drawn to it was the fact that maybe you wouldn't have to have as much influence of motion so that when you do speaking tasks, we had one that used fNIR but we still had motion issues. So, I don't think... every imaging technique has its pros and cons related to the research question you're asking. But I thought it would be nice for the listeners to hear if they haven't heard some of this discussion cause I do think we throw these words around and of course in the popular press they are thrown around as all of it’s language based or brain-based. But I do think it's interesting to contrast the pros and cons of some of these techniques that are out there.
25:52 Nicole Landi: Yeah, yeah. For sure. And both fNIR and EEG are gonna be a little bit more motion tolerant. I think the interesting thing there is that... Yeah, they're more motion tolerant in the sense of like when you look at the scans, the motion isn't as evident and it doesn't seem to be messing with your signal as much, but I think we all don't really know how it could have more subtle influences. And so, there's the whole question there on how one might look at that in greater detail.
26:21 Tiffany Hogan: Yeah, definitely, it does, yeah, yes, for sure. And then also, let's talk about the genes for a minute too. I'm just curious how do you usually collect your genetic data?
26:31 Nicole Landi: Yeah, so that's a great question, especially when you're talking about kids, right? So all of our genotyping data is, we extract DNA from saliva and that has its own set of issues, which is why it's so magical to be able to have genotyping data and neuro imaging data and behavioral data on the same set of kids. So, saliva collection you just spit essentially into a little container, and that's actually a lot harder than you would think it is, cause you have to produce a significant amount of saliva, which is just unpleasant to think about, right? And then go through the extraction process and quality control and all of that, to do the genotyping and that takes a whole other level of expertise. So you have to work with a team that can really expertly do that as well. But at least we're not collecting blood which of course is another way that people obtain genetic data and that is harder to get from children, cause it can be unpleasant to go through that experience, but also cause you need a phlebotomist on-site or you need to send them to the pediatrician, which is just a hassle. So we use saliva which really, you can do quite good genotyping on the saliva. It doesn't have quite the same quality as the blood but for most of what we're doing, it's quite efficient.
27:45 Tiffany Hogan: And have you done the cheek swabs before too, ever?
27:49 Nicole Landi: I have never used those, actually. They tend to be done with, say, infants, where you or really young children, where you can't actually get them to spit, right? [chuckle]
27:59 Tiffany Hogan: Right, yes.
28:00 Nicole Landi: So that's when you would employ that.
28:02 Tiffany Hogan: Yeah, I haven't done much with the cheek swab either, although again, I had a postdoc that did, and then as part of a study I did in working memory we did the saliva and that was quite the experience, cause like you said, it seems easy, but it's actually not, and...
28:15 Nicole Landi: Yeah, it's not. [chuckle]
28:16 Tiffany Hogan: It's a lot of work for those kids but it does...
28:20 Nicole Landi: None of this is easy.
28:21 Tiffany Hogan: No, nothing is easy, but I do think that it's like thinking about when these studies are published, what's gone into them, it's just monumental in terms of getting kids into the scanner or whatever type of brain imaging and then getting the spit and just all of that and when it's orchestrated and it's kind of amazing, but it's told us some really cool things, I think and I can't wait to continue to see what you're doing and also, hopefully, work with you on some of these questions, especially about mechanism.
28:50 Nicole Landi: Yes. Likewise.
28:51 Tiffany Hogan: But I'm looking at our time and I do wanna make sure we cover the last two questions I always ask every guest. And the first one is, what are you working on now that you're most excited about?
29:02 Nicole Landi: Oh, that is such a hard question.
29:03 Tiffany Hogan: I know.
29:04 Nicole Landi: Yeah. [chuckle]
29:06 Tiffany Hogan: It is hard.
29:07 Nicole Landi: Well, I think the most exciting project for me is this project where we're doing in school, EEG data collection.
29:15 Tiffany Hogan: Oh okay.
29:15 Nicole Landi: Just yeah, the opportunity to partner with, so these are in schools for children with language-based learning disabilities, so these are private schools where all the kids who are enrolled have some kind of language-based learning disability, and many of them have dyslexia but not all of them have dyslexia, they're all going, undergoing intervention for their reading problems and language problems and what we're trying to do is just more dynamically track them over time and maybe get a better handle on identifying precursors to intervention response, so we know that there's a significant number of kids who don't respond to even the best evidence-based interventions and we don't... We know some of the things that, we have some hypotheses about why that might be true, but I don't think we have great traction on that question or that problem. And so, what we're trying to do is really get a better dynamic model with behavioral assessments and neuro imaging measures over time as kids progress through an evidence-based intervention for a period of years, so it's really much more intensive and really longer over a period of time, with kids who have the most severe problems.
30:23 Tiffany Hogan: Wow, that's so cool, cause you'll get probably a lot of bi-directionality, I imagine, like seeing what's happening in the brain, then happening intervention and then vice versa. One of my favorite studies was by, kind of the same vein, it was by Marc Fey, gosh, I wanna say it was in the mid 2000s, but he was looking at ERP data related to some work in language therapy for children and he showed that prior to... So he had the EEG data and he had the behavioral data and he showed that the EEG was almost like a crystal ball that foretold who was gonna make the shift, so you could start to see basically a brain-shift that was occurring before the behavioral shift, and I thought that was really interesting.
31:08 Nicole Landi: Yeah, that's very cool.
31:10 Tiffany Hogan: Yeah, so...
31:11 Nicole Landi: Yeah, right? That's a very cool thing.
31:12 Tiffany Hogan: So it the what you think you might... You might show that similar or...
31:15 Nicole Landi: Yeah, I mean I think that's sort of like the holy grail, right? [chuckle] You think that you might actually be able to see something there that's giving you a hint that someone's going to respond or they're about to respond or that they're not going to respond, and then ideally, for those who are not, maybe something in there that could tell us what they might need. And so, there's sort of a multi-layered question there, and we're using a bunch of different kinds of assessments to help us answer that question.
31:42 Tiffany Hogan: That's very cool cause I don't even think we have that necessarily figured out even in the behavioral data, so it'll be great to look at, both the behavioral and the brain data together and see what you find, that's very cool.
31:54 Nicole Landi: Yeah.
31:55 Tiffany Hogan: Yeah, and I think in...
31:56 Tiffany Hogan: Yeah, the hope is that together, they'll be more than the sum.
31:58 Tiffany Hogan: Yeah, that makes a lot of sense. And you talk about working with these schools that have concentrations of children who have language-based deficits. It seems like it would be nice that you have that concentration cause you need those large numbers of kids to be able to figure out these complicated relationships.
32:12 Nicole Landi: Yeah, exactly, that's exactly why we're doing it. And not only that, just to be able to collect data in the school, it's just a totally different environment. I didn't realize how much, like the data is so clean, the kids are happy, they're enjoying it and it presents this whole STEM learning opportunity, right? They're learning about their brain and learning about how their brain changes, it's having this amazing sort of self-efficacy side effect which is so awesome. And then we're, of course, learning about the school. And how reading is actually taught, right? My background is in cognitive neuroscience, I have a theoretical understanding of how reading is taught but being able to see it in practice and interact with the teachers and talk with the students, it's just a whole different world, it's really phenomenal.
32:56 Tiffany Hogan: Oh, that's amazing and I've never thought about... I've definitely thought about the by-product like you said, of working with schools cause I come from a SLP background, but at the same time, it's not a teaching background, so when I'm in the schools, I also just am mesmerized by what's happening and all that has to be coordinated, but I did not think about the benefit to the kids in terms of learning about their brain. That's so cool!
33:17 Nicole Landi: Yeah, it's super cool, right? It's super cool. Yeah, we have this, at the one school we have these high school students, so this is with the Aims School and with the Windward School, the two projects, I should say who they are.
33:27 Tiffany Hogan: Yeah.
33:28 Nicole Landi: At the one school they have high school students and they're actually able to participate in an internship program and really gain a lot of hands-on skills and help us select the data, so it's very cool.
33:39 Tiffany Hogan: Oh, wow! And you never know what trajectory that puts the child on, maybe they'll become a brain scientist, in the future.
33:44 Nicole Landi: Well, exactly, that's exactly right. There're already a few who are pretty interested, so...
33:49 Tiffany Hogan: That's really awesome. Okay, so my last question I always ask is, what is your favorite book from childhood or now?
33:58 Nicole Landi: Yeah, what a great question again! [chuckle]
34:01 Tiffany Hogan: I like to ask the tough ones at the end, especially. [chuckle]
34:05 Nicole Landi: Yeah, childhood, I don't know, I should go back and ask my parents. I'm sure there's something good there. I remember Where the Wild Things Are, for example.
34:15 Nicole Landi: But I bet there is something I've just sort of overlooked. [chuckle]
34:19 Tiffany Hogan: You know what's funny about that Nicole, is that I rarely do this, but I'm recording two podcasts today, and you are the second person I've recorded today, that that was their favorite book. [chuckle]
34:30 Nicole Landi: Very cool.
34:33 Tiffany Hogan: That's very cool.
34:34 Nicole Landi: Popular.
34:35 Tiffany Hogan: Yeah, that's like amazing. And because I'm sure the listeners would look here both, the other one I recorded today was Nicole Patton Terry, so I have two Nicole’s, two favorite books, very cool.
34:43 Nicole Landi: Wow! Okay. [chuckle] Many coincidences.
34:45 Tiffany Hogan: I know, I should play the lottery today, cause this is a lot of coincidences happening.
34:47 Nicole Landi: Yeah.
34:48 Tiffany Hogan: I love that book too.
34:50 Nicole Landi: Yeah, and in my current life in terms of books, in my adult life, I read, you know what, I commute a lot, so I do so much Audible.
34:57 Tiffany Hogan: Oh, that's awesome.
34:58 Nicole Landi: So, what's interesting... Yeah, and so I kinda devour novels. So, what's funny about that is what plays well in an audio format is not necessarily what is going to be great to read and I found that really interesting, right? So right now, I'm listening to The Wind-Up Bird Chronicle and it is terrible in audio format, but a really great book in print, anyway, so that's just one example.
35:20 Tiffany Hogan: That is really interesting.
35:26 Nicole Landi: But I've listened to a lot of things that were really great this year. Eleanor Oliphant Is Completely Fine stands out.
35:34 Tiffany Hogan: Love that one too.
35:35 Nicole Landi: Yeah, that was really good, right? A Little Life was really great. A Gentleman in Moscow was super entertaining. I have a whole long list, if you want though.
35:43 Tiffany Hogan: Oh, I would love to have those.
35:45 Nicole Landi: Fit for Audible.
35:47 Tiffany Hogan: I also commute, but I'm kind of addicted to podcasts right now, [chuckle] so it's not all work podcasts, a lot of true crime. So, I do go in and out of Audible and the podcasts, but it's funny you said that about Audible and what you listen and what you read. I always say, when people say, "What book have you read?" I don't distinguish whether I read it by reading it with print or whether I listened to it on Audible. To me, it's like I read that book.
36:11 Nicole Landi: Yeah, I think that does happen in terms of how you consolidate on it over time, your understanding of just the story and the plot. But some things like the narrator isn't good or it just doesn't do well. Like, okay, for example, the Murakami book I mentioned that I'm listening to now, that I might not get all the way through because of this. You would read it much faster than you would tolerate, you know what I mean? But not all books are like that, so I think that that's part of it.
36:40 Tiffany Hogan: Yeah, and I think you're right, to me, I almost... I do think I have this bias to pick Audible books that are read by the author. And actually, I've heard that that's actually a bias that a lot of people have and Audible is trying now to get more authors to read because as a listener, you tend to be more interested if it's the person who wrote the book.
37:01 Nicole Landi: Yes.
37:02 Tiffany Hogan: Especially with biographies or something like that, like I read the Year of Yes, or read, I didn't read it, I listened to the Year of Yes by Shonda Rhimes and it was so cool that it was read by her. I just, I loved that cause it's like...
37:12 Nicole Landi: Yeah, I completely agree with all of that. Traver Noah's Born a Crime was so amazing in Audible format and that's a really good example of that cause you know your paucity, you know how you want it to sound. [chuckle]
37:24 Tiffany Hogan: Yes, absolutely, yeah, you're like I... Yeah.
37:28 Nicole Landi: You know where the stress goes.
37:29 Tiffany Hogan: Yeah. Yes, exactly. [chuckle] You wrote it, so you know it. It does seem to add to the depth of knowledge. So, well, that's really cool, I'm so glad Nicole we were finally able to record this podcast, thank you so much for...
37:40 Nicole Landi: Me too.
37:41 Tiffany Hogan: Being so flexible and joining me cause I think the listeners are gonna learn a lot from what you're doing and I'm gonna hang on, everything you're writing too, cause it's just so cool, such cool work.
37:54 Nicole Landi: Yeah, thank you so much for having me. This is really fun. I too I'm glad we persisted. We should have a little note next to this with our story of attempted meetups and all the little things that kept us from doing this.
38:05 Tiffany Hogan: That's right, we persevered. [chuckle]
38:08 Nicole Landi: That's right.
38:15 Tiffany Hogan: Check out www.seehearspeakpodcast.com for helpful resources associated with this podcast including, for example, the podcast transcript, research articles, & speakers bios. You can also sign up for email alerts on the website or subscribe to the podcast on apple podcasts or any other listening platform, so you will be the first to hear about new episodes.
Thank you for listening and good luck to you, making the world a better place by helping one child at a time.