All right. Hello, great. Thanks for joining me today. How are you doing? I'm good. How are you? I am great and we're here to talk about your awesome book that I stumbled across recently. So for those who haven't met you yet, can you kind of explain, I guess the first question I'll ask, you're a computational neuroscientist, right? Can you kind of explain what that is? Yeah, it's a little bit about what the book is supposed to do because yeah, most people have not heard the term, they don't know what it is. So I think people are familiar with the idea that there are some scientists that use math to understand the world and usually people think of those people as physicists, like physicists write down equations and it corresponds to real things in the world, but you can apply that to almost any area of science, really any area of science. And so a computational neuroscientist is just someone who uses math to understand the brain, to either model different parts of the brain or do data analysis on data that comes from the brain. Just generally, it's about using math to understand the brain. Yeah, so and yeah, so I'm not a math guy, but surprisingly, like your book, like it actually it made a decent amount of sense to me. Like I felt like I was able to keep up a little bit, but that's something else I'm curious about. Like whenever I have authors on here, like when you wrote this book talking about the models of the mind and all that, who was the target audience you had in mind? Was it like other academics, people, you know, like college students, like getting into neuroscience and all that? Like, who are you thinking of as you kind of wrote this book? Yeah, so I wanted it to, you know, as you say, kind of be readable by people without a math background and also without a neuroscience background, you know, it doesn't assume that much knowledge. And I wanted to just let people who are interested in the brain, which it seems like there's a lot of people who are, you know, books about the brain are popular, people want to understand the brain works, they want to understand psychology, they want to understand kind of all levels of it. I wanted to let those people in on this way of understanding the brain because it's becoming increasingly more important in neuroscience amongst the scientists who are actually doing the work of understanding the brain. They're using these mathematical methods, but most popular science books about the brain don't really get into them or they just like kind of gloss over very quickly. They say like a computational model was built and it supports this idea, but you don't want people to know how that works or why or anything like that. So it was really targeted yet to people who have an interest in the brain, showing them this other way of understanding that can be really fruitful and interesting, even if you don't know all the details of the math. And then on the flip side, there are people who know kind of math or come from physics and engineering who have an interest in the brain. And this kind of maybe puts it more in their language. So I think it can kind of serve a dual purpose because it is this, you know, cross-disciplinary field. If you come from the math or from an interest in the brain, you can see where they merge here. Yeah. Yeah. No, absolutely. And I think you nailed that. And you do, and you do a great job by kind of explaining some of the history and like the main figures who are like figuring out some of these models and everything, because my background, I got into neuroscience and we'll talk about this in a little bit. Like, I have an addiction background. I got sober in 2012 and I was like, okay, what's going on with me? Why am I different and stuff? And I started learning about, you know, mainly about like neurotransmitters and like dopamine systems. And I got interested in, you know, how various parts of, you know, the brain are involved in like depression and anxiety and, you know, all these other things. So that's kind of where I came in. So, so yeah, your book, it kind of brought in this other aspect. I was like, oh, okay, some stuff started making sense. But one, one thing I wanted to have you help educate me on and maybe some of the others who are more from my side is, for lack of better words, I'm like a skeptic because I come across all this other stuff, but I know there's science and I know like there's ways to research this. So the book, you know, you talk a lot about neurons in there. And as I was talking about, you know, like I'm more familiar with like neurotransmitters. So real quick, can you break down what is the main difference between neurons and neurotransmitters? What are their different responsibilities? Yeah, so neurons are kind of the main cell type in the brain. They don't actually, they're not the majority cell type. There are other cells called glia, but they're the things that as you could guess from the name, neuroscientists focus on we think that neurons are the cells that are doing a lot of the important computational work of the brain and like the information processing and all of that kind of thing. So they're just the cells that are in the brain. And the main thing that they do is communicate with each other. So they send within the neuron, there's an electrical signal that's sent within the membrane of the neuron, it uses electricity to send it from one end of the cell to the other because neurons can actually be quite long. There's like neurons running from the bottom of your spine down to your foot. So they can be quite long. So they use electricity to send messages inside a single neuron. But usually when you want to send a message from one neuron to another, you use a chemical signal, which is a neurotransmitter. So there's like at the end of one neuron, you release this chemical, it crosses this little gap called a synapse, it touches the next neuron and that starts an electrical vent in the next neuron. And so neurons go from electricity to chemical to electricity, but that chemical that they're using is a neurotransmitter. So neurons release neurotransmitters. And sometimes they release them just from one neuron to the next in this little gap, as I said, but also they can release them more broadly. And usually when they release them more broadly, they're a type of neurotransmitter called a neuromodulator. And it's not just about directly trying to send a signal from one cell to another, it's about kind of broadcasting to a broader community of neurons. Oh, this is kind of the state of the brain right now. This is the state that we're in. I'm going to send this broad signal to everybody just so we're all on the same page. So they're completely linked. You can't really have neurons without having neurotransmitters. You definitely can't have neurotransmitters without neurons because they're usually the cells that are producing them. So you need the neurotransmitters to allow the neurons to communicate. Got it. So if I'm understanding you correctly, so when the neurons are sending these neurotransmitters to the neurotransmitters, there's a variety of them like dopamine, endorphins, and all that kind of stuff. Is that what I'm getting like? Yeah, there are different types of neurotransmitters. There are ones that cause the second neuron to have this electrical event and there are other ones that try to shut it down. So it's kind of sending a positive signal or a negative signal. And then yeah, these more broader neuromodulators are sometimes like dopamine can be considered a neuromodulator. Other ones that people hear about a lot might be more the neuromodulator category than in the pure neurotransmitter. Gotcha. And totally random question. Just the other day, I introduced my 12 year old son to the movie The Matrix and you're talking about electricity. Is that like kind of the idea of what they were saying? Like the machines are sucking that kind of electricity from us. Is that what they're saying? It's been a while since I've seen The Matrix. I assume that's the best they could have gotten is that that was the electricity they needed. It is not, I mean, the brain is very energy efficient, but I don't think it was the best way to get energy. Yeah, that's why I'm here. Like I read books about, you know, just like supernatural beliefs and like skeptics and debunking it and like they talk about like our bodies being like magnetic and things like that. And like, from what I understand, like the electrical signals going through are like nowhere near strong enough to really do much. Is that correct? Yeah, I mean, there, yeah, there is certainly the electrical signal along the single neuron is weak compared to, you know, electrical signals we use in the world. Yeah, powering our house and all that. Yeah. So, so yeah, so, so now that I have a better understanding about that.  And a lot of them talk about, you know, manipulating, you know, like serotonin and all these other things. But there's a whole camp of people who are like, no, we don't know this stuff. Like, you know, we can't really, you know, change how much how, how the neurotransmitters are reacting or one of the big ones is like, we don't have really have a way of measuring it. So I was like, Grace will probably have some answers for me. So like, as far as neurotransmitters, I want to talk about neurons in a second too, because it's a lot of neuron talk, but neurotransmitters, can you, can you help me understand, like, how is it measured? How do I know, like an SSRI is doing what they say it's doing, and it's not just mainly a placebo effect? Yeah, so those are actually two very different questions, kind of how we can measure neurotransmitters and know about them versus SSRIs in humans as antidepressants, because you know, a lot of the basics of what we know about neurotransmitters and how neurons communicate are done in animal work. So in a lab that studies animals, and, you know, we kind of assume based on good reason, and you know, this has been verified, that a lot of the principles we learn in animals can be applied to humans as well, especially on this kind of cellular level of just the basics of how a neuron works. A lot of those things do translate very easily. So a lot of our understanding of just the basics of neurotransmitters and neurons comes from animal work. And so there, you know, you can kind of directly access the brain, there are markers you can use to kind of see neurotransmitters and that kind of thing and stains and all of these things that are like, you know, Petri dish biology kind of stuff. When it comes to humans, you know, we can't get that kind of access in human brain, because it requires, you know, removing the skull and then doing very invasive work that we are not going to let people sign up to be a part of. So there just the experimental access is much less.  And then there are indirect ways of measuring things in humans. So specifically about SSRIs, that's not my area. So I don't want to speak to, you know, how people do that clinically, but there are methods for kind of indirectly measuring neurotransmitter levels in humans. And obviously there's, you know, the actual output that you care about, which is a change in depression or whatever disease you're interested in. And so that, you know, you don't, you don't technically have to measure the neurotransmitters. You can just say, did this drug make this person feel better? And maybe the exact route of which, you know, by which that works, we're not fully understanding, but people need help. And so we want to have something that works for them. And we can like, you know, keep working on trying to understand exactly how it's helping them to make them better and all of that, you know, to make the drugs better and more targeted. But, you know, the direct thing that people care about when making these drugs is just does it help the patient? So yeah, so there's, you have to, it's very complicated because yeah, some people say like, we don't know anything about how the brain works just like generally, you know, but obviously there's a lot of stuff. I mean, I wrote a whole book about how the brain works. And I think it has information in it. So we do know some things, kind of just when people say we don't know, or we can't be sure, that means different things to different people. And it's like, yes, in some extreme sense, there's a lot of uncertainty in science. That's what science is. You're like at the edges of knowledge, we can still be confused, we can think we know how something works. And then in 10 years, we'll find out that that's not how it was working all along. And so yes, there is definitely uncertainty and measurements are complicated and all of that. But there are ways by combining different sources of information, doing different types of experiments to kind of triangulate what you think is happening. Yeah, that's actually really interesting. So recently I had the professor, she's a evolutionary biologist, her name's Nicola Rahini. She recently wrote a book, The Social Encyclopedia. Anyways, she helped explain that to me like studying animals and how that kind of relates to humans. So now it's kind of clicking with what you're saying. So basically, if I'm understanding you correctly, this test, the more invasive tests that we could do on animals and what we know about animal brains compared to ours or how the cells kind of react, we can kind of infer like we kind of guess like when we're doing these studies or testing the medications like okay, the work over here where we do have that knowledge, it's most there's a good chance it's working over here. Is that is that what I'm gathering? Yeah, that's definitely what you know how a lot of this research proceeds. And there are, you know, there are ways of getting more invasive information from humans. I mean, again, I'm not going to speak specifically about SSR is a depression. But in generally, generally, there are ways so when people have epilepsy, sometimes they have to have a surgery where their skull is open anyways. And so we can do some kind of basic science at the same time, you like ask the people will you be willing to participate in an experiment that's not actually about your epilepsy, it's just because we don't get this opportunity to understand human brains as well, will you let us, you know, record from your neurons and that kind of thing. Or, you know, when people die, you can section the brain and study it, and then you're getting a more cellular level understanding of the brain, even though it's no longer living, that can still provide some information as well. So yeah, there are all just many different methods for, you know, studying something directly in animals, and then verifying that what we're learning in the animals can apply to humans. And, you know, sometimes it doesn't apply. But that's why you got to do this back and forth. But yeah, people are definitely, you know, trying to make those connections and using the best information they can while still, you know, keeping our, you know, experiments with humans ethical and safe and all of that. Yeah, yeah. Okay, cool. That that that definitely helps me understand. And then and then I'm guessing like, I'm guessing, but you can help me break this down.  How do we, you know, find these computational models? Is this also mainly tested in animals? Or can we do it with brain samples and stuff like that? Yeah, so a lot of certainly when it comes to how individual neurons work, a lot of that is done in animals, because even if you have a post mortem brain, the neurons are no longer sending signals. So you can't study that process in them, you can kind of study their molecular makeup and their anatomy, but you can't study their actual signaling, which is what a lot of people who build these mathematical models are what they're kind of ultimately interested in is like, how are the neurons sending signals and how does that lead to intelligent behavior, everything else that we do, you know. So a lot of the work does come from animals, but there also is a lot of computational models that are influenced by fMRI imaging. So that's when you put someone in a scanner, and you can get a broad sense of which parts of their brain are active. Now this is very, this is like, you know, you're looking at basically like a million neurons in one little pixel of this image. So you're not getting fine resolution, but you're getting a broad sense of kind of what different brain areas might be doing when a person is doing some sort of task, you know, they're laying in a big fMRI scanner, and they're seeing a screen, and they're doing some sort of task that the experimenter asked them to do.  And then some things, we can actually get a lot of information just by collecting behavior, just by, you know, observing the choices that people make and that kind of thing, that actually can constrain a model of how the brain works, because it's like, okay, if I give it this input, it produces this output. There's only so many steps that can lead from that input to that output. So that can be helpful. Certainly, as a starting point, you know, you want to get a good characterization of the behavior. And then you can start thinking about what the brain is actually doing to produce that behavior. Got it. Okay, cool. And since we're kind of talking like, you know, technology and everything, one of the most interesting parts of the book, I'm like, okay, it is kind of nuts. You talk about, you know, there was, I believe it was a woman, she was paralyzed from the neck down and using like some computational neuroscience, I guess they made like this chip and it helped her move like move her arm by envisioning and training this chip. Can you explain it far better than I am right now, Grace? But I think, you know, part of the interest is a lot of people are curious about where the technology is going and how this can be used for, you know, medicine and helping people and all that. So, so yeah, I found that one really, really, super interesting. Yeah, so this is a woman, yeah, who was paralyzed from the neck down and she was part of this study called Brain Gate, which is at Brown University, which does this research on, it's usually called brain computer interface or brain machine interface. And what she was able to do was she was able to learn to control a robotic arm. So she couldn't control her own arm because those nerve connections weren't there. But what the scientists were doing were was putting an electrode in the motor cortex part of her brain. So the part of the brain that normally is controlling movement of the body, they were able to read out the neurons in that area. So when she thought about moving, those neurons are active. And even though they can't actually move the body, they're kind of still sending signals, which is fortunate because you can imagine if you're paralyzed for a long time, that part of the brain might just become used for something else or not be sending motor signals. But there's still enough information in those neurons that normally control the body to have her learn to control a robotic arm. So it doesn't happen immediately. It's not like you just record from those neurons and all of a sudden you can control an arm. It is a process of learning both for the human and also the algorithm that the scientists are using to translate the neural activity into robotic arm movement. So it's not like you just kind of plug in and go. And even once you have the movement, it's not perfect or smooth or necessarily exactly as you want it to be. But for someone who's paralyzed, it's a big deal to be able to do that at all, of course. So yeah, she was able to control this robotic arm to pick things up, bring it to her mouth, that kind of thing, grasp, let go just by doing what we do to control our bodies, which is user neural activity. Yeah, so that makes me curious, because something they've been trying to upgrade like prosthetics and stuff. Is this research kind of leaning in that direction or they're hoping like someone who's lost an arm or leg that can kind of help in that sense and be used for that? Is that what a further goal is down the line? Yeah, so a lot of times if people have lost just an arm, say from like the elbow down, their brain is probably still sending signals down to that elbow as though there was the rest of the body. So rather than having to go into the brain itself to get this neural activity, you can put an electrode in the arm and pick up some activity right there and use that to control. So at least for something as simple as kind of open or close the prosthetic hand, which is obviously a big action that you want to be able to control.  If you're still sending signals down that far, you kind of want to go almost to the place closest to where the real muscle was that you can still get signal. But if you're paralyzed from the neck down, that's basically the brain. So it depends on the specifics. But yeah, it's the same general idea for sure. You put an electrode in, you try to record neural activity and you use it via an algorithm. You use it to control prosthetic limb. Got it. Okay. That's super cool. And it just crossed my mind too. So Elon Musk has been working on this neural length thing. And you are an expert in this field. Like, what are your thoughts around that? Because as me, as somebody who's not too familiar and I'm trying to learn more, I see debates like people like you're insane and other people like, oh, this is so cool. What are Grace's thoughts around neural link and what Elon Musk is trying to do? Yeah. So I think there's a difference between the hype and what people are saying neural link is and what it will be and the reality of it. And even in the reality, there's some nuance. So the idea of putting an electrode into a brain and trying to read out the neural activity to control a body or to just do some sort of mind reading or whatever it is. I mean, this is what neuroscientists do to understand the brain. Like we record from neurons and then try to make sense of what the neurons are saying. And so that basic concept is not at all revolutionary. This is, you know, this is what we do to try to understand the brain's computations. So that basic thing, you know, doing it in animals is already what we do in the lab and all of that. So the basics of it are not new. It's my understanding that the actual kind of hardware that they've developed, this type of electrode they have and how they implant it are pretty big advances in electrode technology. So people in neuroscience are kind of excited about the prospect of having better electrodes that are implanted easier and can last longer and have higher signal quality and all of that. But, you know, that's it's a very technical advance. They made a cool, good hardware thing that hopefully will spread through neuroscience and people can use it. The idea that humans are going to have this implanted and they're going to, you know, interact with the world through their brain.  I don't think a lot of people are going to sign up for brain surgery just for like a casual computer interface experience. So there's just the biology of it. And also, it requires that we understand how the brain works, really, to be able to just kind of read out thoughts. That means that we know when you look at a neuron, you know, what a neuron does, I said, it has this electrical activity that it makes, it makes these little blips of electrical activity. And so basically when you look at a neuron, you just see kind of like a, you know, just a tick, like a series of ticks, like tick, tick, tick, tick, tick is just like, that's what it's doing. So if you can't look at that and say, Oh, that person's thinking about a banana, then it's not going to be useful. You need to actually be able to understand the neural activity to do something useful with it. So there are, and you know, this example of the woman with robotic arm shows that we can do that to some extent, we can try to understand her intentions and her desire to move by recording the neural activity, but it takes a lot of effort and there's a lot of other parts of the brain that if we record that neural activity, we're not going to actually have a good sense of what the person is thinking or what they're trying to do. And so you can't just magically start controlling or interacting with the world through neural activity. We need that translator that says this is what the neural activity means before it can start being a really useful way to interface with the world. Yeah. So yeah, it's kind of, it seems kind of far off and we still have a lot to learn. And so this segues perfectly into my next question because I asked a lot of people and you spoke about this a little in the book, it's like artificial intelligence, right? So I am really interested in like cognitive psychology, decision making, you know, all these other things, right? I'm actually reading right now, Anil Seth's book on consciousness, right? There's a lot of stuff and like, we still don't know a lot. And, you know, earlier, like, you know, when I started the podcast, I had Kate Darling on from MIT to talk about her book, and I asked her about AI. So there's a lot of like random fears like, Oh my God, AI is going to like take over the world. And like, based on my remedial knowledge of how the brain works and how much we don't know and decision making and how just wacky, you know, even humans are and irrational and just random, like, I'm curious your thoughts on like AI becoming this kind of like, you know, conscious thing or even AI like being like an extremely useful tool because we were talking about, you know, kind of machine learning aspect of, you know, reading the neurons and everything. So, so what are your thoughts like, like for the for the public who was like, Oh my God, terminators going to happen and we're going to be taken down. Like, what are your kind of thoughts around the current state of AI and how far off that is? Yeah, I mean, I think, I think sometimes the fears are misplaced, not that there shouldn't be any concerns about how we use AI in society, but the idea that it's going to become, you know, self aware and all of a sudden have a goal to destroy humans or whatever it is. Like, I just don't see where that would come from in the model. Basically, you have to put everything into the model that you want the model to kind of produce, you know, you tell it the tasks you want it to solve and you give it the data to train on and all of that. And you know, there is some extent to which it's doing something on its own because it is machine learning. It's we can put in data and we can train the network and it kind of figures out a way to solve the tasks that we give it. And that's why it's so powerful because you don't actually have to hand design every solution that you want. You can have a system that can learn on its own. But that doesn't mean that it's going to all of a sudden have desires or something like that or have motivations or goals that just came out of nowhere. So that kind of element of oh, it's going to take over or it's going to be sinister or it's going to try to trick us like I don't think any of that is really a concern. But you know, there are issues when you train these models and you are actually deploying them in the real world. There can be consequences and side effects when you don't fully understand how they're working. And you know, we see this kind of in terms of like things that are determining if people get a loan or not using kind of information that we wouldn't want to be included in the decision. And sometimes that's just because there are things in the data set that correlate with other things like if you put in someone's zip code to see if they should get a housing loan. It might be that that tells you something about their race. And because you know, because it is the case in the world that people live in segregated areas and all this kind of thing. So without fully understanding the entire system that you're trying to use an AI as part of, there can be unintended consequences that are happening in the model. And so that's an issue for people who are actually deploying these models. They need to be sure that the model is kind of doing actually what they want. Because even when you train a network on very simple tasks that don't have much to do with like the complexities of the real world, those models can find weird ways to solve the problem that isn't how you or I would solve the problem. And if you just look at the high level, just like, Oh, it's solving the problem. Great. I can go put it in the world. It's going to solve the problems in the world. But if it encounters, you know, something that is too different from what it was trained on, and it's solving the problem in this weird way to come up with a weird answer. And if you're not checking, that could have bad consequences, basically. So people do need to be considerate of if they're training their models appropriately, if they're testing them appropriately before they actually start deploying them in the real world. That is something to consider. But that's just kind of that in a way that's, you know, a mundane issue. It's not this global super intelligent AI is going to take over the world. It's just no, we as people need to be careful on how we use our tools. It's just it's the same with any kind of tool that you might use, especially at a large scale.  You need to reflect, you need to think about how the tool works, the impact it's having and making sure that everything's actually going how you want it to, and not, you know, glossing over the fact that the model isn't actually doing exactly what you want it to. Yeah, that's that's actually a topic I've been really interested lately with like algorithmic biases, right? Like you mentioned, like, you know, loans and, you know, just even issues of like, like sexism just built into a model. Like there was a that famous story about like Amazon, it wasn't hiring like any women based on this like algorithm they created. So with, you know, all the math involved in like computational neuroscience, is there any crossover with, you know, the work that you do or anybody in your field with kind of these algorithms that are being created? Or is like, for example, like, is, is this something like Google's looking into, you know, and stuff, because even like searches can be kind of skewed and bias and, you know, so many things. And that that's something like, like you mentioned, I don't think it's like a world ending thing, but it can, you know, for as far as like societal issues and, you know, wealth inequality and racial issues and sexism and all sorts of stuff. So, so does your field crossover with that at all? And, and what, what can we be optimistic about that aspect? Yeah. So right now, there is like a ton of interaction between computational neuroscience and artificial intelligence. It's like really a booming period for that.  And so right now, there's a ton of interaction. And the same types of models that kind of form the basis of a lot of these machine learning systems that people are using in the real world and industry, those same models can be used as models of the brain, at least very similar models, you can use kind of the same approach to build a model of the brain as you do to build an artificial intelligence. And the reason for that is just because right now, kind of the dominant form of artificial intelligence is artificial neural networks. And so they're kind of based very simply on how real neurons work. And this comes from back in the 40s and the 50s work that where at that time things were kind of close again at that time. And so the people building AI were interested in how the brain works. And so they came up with these ideas of artificial neural networks. And now we're in a time where that's really coming to fruition. And then these artificial neural networks can do a lot of interesting things. So there's definitely overlap my personal research, I train artificial neural networks to do visual tasks. And it's the same kind of style of artificial network, as Instagram would use to analyze pictures that it has on its service, that kind of thing, it's, you know, it's what's used in computer vision now. So there's definitely overlap. And there is some shared interest in understanding how these networks work. So understanding how they train and how once they're trained, kind of what functions are they using to solve the task. And just, yeah, kind of wanting to know how they work so that we can use them as models, but also just kind of a general interest in how these systems could work, which could then be applied to, you know, understanding them in the real world and making them more robust and better in the real world. So there definitely is shared interests, there's shared methods. People in computational neuroscience are paying attention to what's happening in artificial intelligence and vice versa. So maybe that's optimistic, because, you know, we're supposed to be good at trying to understand these kinds of things. But there's their hard to understand once they're trained, you still can't look at a trained artificial neural network and just be like, Oh, I know what it's doing. I know what task it's all being. It's it's hard because it's this giant system of bunch of numbers. And yeah, we need methods for for better understanding them. Yeah. And so so with, you know, in your in your book, like I started seeing how, you know, just these different like mathematical models can help us with like predictions and understanding.  But I'm curious, you know, like, as we were talking about like these unintended consequences with kind of the models that you're using. So for example, like you're talking about like visual training with some of these algorithms.  So, so are there mathematical models that you guys are using that kind of work on these kind of issues and try to predict certain unintended consequences? Or how do you, as somebody who's like focused on like the, the, the mathematical models, look at that to make sure that you're like taking things into consideration, like for like this visual style of learning. Yeah. So I mean, I would say that, you know, while there is a lot of interaction, there still are different motivations and goals. So when I build these models, I'm trying to build models that will match neural data that's recorded from animals and kind of has the same features of neural processing that those do so that I could use this as a stand in kind of for studying the animal brain and, you know, figure out how the model works and see what happens if you perturb the model and all that. So the goal is still to connect it to the biology and understanding the frameworks versus a company that wants an algorithm that can find images that shouldn't be on their website. Their goal is to train a system that does that. And this kind of relates to this general idea that you need to be careful about your tools and you need to do proper testing because if it's flagging the wrong kind of stuff, that means that it hasn't been trained correctly. And so, but that can be for a lot of reasons, it can be about the type of data that they use to train it. It can be about the type of model or the specifics of the training algorithm. And that really is kind of what a lot of the open questions in machine learning are right now is just how do we best train our models? What do we have to think about for the data? How do we test them? And it's just a lot of just kind of practical open questions in the world of applied machine learning. And they relate to some of the shared questions that computational neuroscientists and machine learning people have in just in terms of better understanding the models and understanding how they learn and all of that. There is some overlap at the more kind of theoretical level. The assumption is, you know, if we have a better theoretical understanding of how these were kind of in the abstract mathematical form, then that would translate to, you know, tips for on the ground training a model that you're actually going to deploy. We should be able to come up with better ways of kind of controlling how that process works if we have a better background understanding of how this training works in general. Got it. Okay. Cool. And that helps with my optimism a little as well. Yeah, I like seeing how those interact.  And, you know, one thing that you mentioned to I'm curious from what you've seen where like I'm a curious person, I read so many books on different topics, it's nuts. And I'm always like trying to I'm like, why am I even interested in this?  There's like brain and like psychology and all this stuff.  Or why do you think that interest is for like, the average person like, like me, like I have nothing to do with brains, like in my regular daily life, right? So I'm curious, like, what, where do you think this, this broader kind of interest comes with how our brains work and all that? Yeah, I think it can come from a lot of different directions. I think some people maybe they or someone they know had some sort of neurological disorder or psychiatric disease and they're drawn to it from that perspective, like they want to understand what's happened to them or the person they know and to understand how that person's brain works and why.  And so they want kind of reverse engineer it, because they want, you know, computers to be smarter and all of that. I think there's also just, you know, an inherent interest in understanding yourself and other people. And so that's, you know, usually, you know, at a kind of psychology level, you don't necessarily have to talk about the brain and how the brain works to talk about human behavior. But sometimes, I mean, this was kind of what happened to me, I was interested in psychology in high school, but then I kept thinking like, okay, that's kind of a description of what's happening, but what actually causes it, you know, like what's the mechanism, and then you have to go into the brain and think about how the brain works and how it's producing human behavior. And so I think it can just come from a very, you know, there's a lot of reasons why you want to understand people. I mean, they make up a big chunk of the world around you. So if you want to understand your world at all, you're going to have to understand humans and how they work. And so that naturally leads to a desire to understand psychology, which could lead to a desire to understand the brain. Yeah, yeah, it's funny because it's almost like you're just like, like you've been spying on my own background, because that's basically what happened to me. Like I mentioned, like, you know, I came from addiction background, that I want to learn about mental illness. And then like, when I was learning about the behaviors that I got deeper, and started learning a little bit more about like the neuroscience behind it and the different like, you know, when I got into mindfulness, for example, I started learning about like the prefrontal cortex and, you know, and like the amygdala and all these other things. And so, so yeah, I could definitely see that. And, and so one of my goals with this podcast too is like, just because I'm, you know, interested in all these topics and trying to see how they relate to the average person because I want more people to be interested in these kind of things rather than just, you know, as you know, like in the middle of COVID and this Delta variant spike, like there's an issue with like science communication and people's lack of understanding of science. One of the best things you said, which is very true is how science we're constantly learning and something we know now maybe different in 10 years and all that. So, so like with your book and these topics around like computational neuroscience, what would you say like the main benefits? So, so aside from the people we were just talking about, like I live in Las Vegas, I go down to the strip. Why should, if I go up to somebody, how do I sell them on the idea like, Hey, you should care about computational neuroscience. Here's why. Like what kind of real life stuff, you know, Yeah, I think maybe there are kind of two routes and one, it can just simply be put as the brain is very complicated. And I think people don't always appreciate just how complicated the brain is and therefore kind of how complicated they and their biology and their behavior are. And, you know, some of that is because there are these kind of popular science narratives that make it very simplified.  And the truth is it's just it's far more complicated and our knowledge is evolving. And to not, you know, hold on to any belief about how your brain works with so much certainty. You know, it's, it's, it's something that is complicated and very multifaceted. And if you're trying to understand yourself or others, you know, you can, like, acknowledge that complexity and it might help. So even if you don't have an interest in biology itself, just kind of the general acknowledgement that the brain is complicated and our understanding is evolving might make people see things a little bit differently. They don't have to force everything into some existing narrative that they've been told about how the brain works. And then the kind of computational side of it, in particular, I think that it would be great if more people understood kind of the very practical benefits of mathematical modeling. And it relates to the fact that things are complicated. And it's really just like, you can't hold all these ideas in your head at once.  I have to buy milk. One thing, okay, you can remember it, you go, you get it. Oh, wait, I also want bananas. I also want eggs.  It's the same thing with mathematical models, except you're just writing it down as an equation. It's like, okay, well, that neuron connects to that neuron. And that neuron has this kind of activity, but that other neuron, it kind of, it stops the other neurons from firing. It's like, oh, wait, I can't hold this all in my brain. I need to write down in code or in math what I think is happening. And you can apply that to anything in life, just the idea that when you have something complex with a lot of interacting parts, you gotta kind of be explicit and just write down how you think it's working.  You have a little diagram, but you have to be specific about, you know, how the different parts interact, you're going to eventually get to an equation. And that's all that, you know, in applied math, like people think of math as being like, so, you know, oh, I couldn't possibly understand it, but it's really, it's just like, no, it's like too much going on for me to just think it through. I just want to write it down exactly what I think is happening, and you write it down in an equation. And that's kind of the basics of it. So I think it's broadly useful. It will explain, you know, especially like with COVID and these models that were predicting cases and all of that, that's just like, that's a mathematical model that somebody's saying, I expect people to interact with this many people in their lives and the disease spreads at this rate. And if I put that together and I look at the population of my country, then this is what's going to happen over time. And it's just people having a thought about how the world works, and they're just putting it down in math, and then you can make predictions. So it's pretty powerful, but it's also not that complicated, that idea of just writing down in math, if you want to be explicit about them. Yeah. And Grace, that was, we should have started with that, because you just, you resold me on the book. Like it is, like there's so much stuff and understanding about, especially like just the different models. Like for example, I have never really been a math guy. But I, like you mentioned, like, you know, just even with, you know, COVID or like just remembering stuff when we go to the grocery store, that kind of stuff. Like, I've read a lot of books on just assessing data, right? Because especially during COVID, we're constantly hit with data, right? How many people are being infected? How many people are dying? What are these rates and da da da da. And I don't have time to figure out all the math behind it. But when I'm able to look at data and ask the right questions, understand what they mean and stuff like that, it helps me, you know, like I'm a father, right? It helps me with like risk management. Like right now, there's a conversation around, do you get vaccinated and how much research is there and all this other stuff. But when you can understand some of these models and statistics, you know, and something you talk about in the book is like probability and things like that. When we know basic, like basic things like that, life goes so much better. But one of the things you mentioned too was like, just we have this idea of how the brain works and all this, but we realize how complex it is. Because I think one thing that all of us can use is like this intellectual humility, right? And that's something I get every time I pick up a book, like especially yours, I'm just like, oh man, I don't know nearly as much as I thought I did. So it's something we can all benefit from. But one of the things like you mentioned too, like about memory, I love that part of the book. Can you give kind of a brief explanation of like pruning? Like what happens in our brain when pruning? Why that, like what it is and why it matters? Can you, because I think that is a very practical thing that we should all know about. So lay it on me Grace. Sure, yeah. So pruning is, it's kind of what it sounds like. It's the idea that you kind of, your brain is kind of overgrown and you need to prune it back. And it's particularly a strong effect during development. So like in utero and when a baby is born, they have like way more neurons and connections between neurons than you do as an adult. And so the process of pruning is just you get rid of those connections or some of those neurons die off and you're just left with a kind of smaller network that has fewer interactions. And the reason to do it is basically it's a way of, you know, finding the important connections. So you had this overgrown thing and then you go through this process of like use it or lose it. So if in the course of experiencing the world, certain pathways and certain neurons just aren't sending a lot of signals and it's like, okay, that wasn't important. We don't need that. And so it's a way of kind of creating a system that's adapted to the environment that you're in because you're only keeping the pathways that are helpful for you. And yeah, so if you were in a different environment, there might be different pathways that you need. So that's, there's a bit of that element to this kind of use it or lose it and this where, yeah, you can have more connections than you need and get rid of the ones that you don't need. But the ones that you don't need are going to be kind of dependent on what gets used in this time of pruning. So that's the basic idea of it. And how it's done in the brain. Yeah. And when I learned about that, like that was that was one of the things I learned when I first started learning about neuroscience. And it makes sense, right? Like we learned so much like there's, you know, there's like a rare amount of people who like remember everything, like literally everything and they go insane. But like with us, I'm curious, you in the neuroscience field, like, do you do anything specifically to kind of like hack the pruning and memory system? Like for example, something I've done is like I like just using social media, right? I have, I've pruned my social media. So I'm only getting important stuff. So I'm not wasting cognitive, you know, cognitive energy on nonsense, right? Like, there's certain things that I don't need to remember. I like, I have a finite space in my brain. It's like a hard drive. So it's like, get all the nonsense out. So I'm, I want to learn from the best now. Like, is there any kind of pruning hacks that you use to remember important stuff, disregard other stuff, or any tips that the listeners might be able to benefit from? Yeah, so I think that kind of as we're adults, we think that repetition isn't important anymore. Like repetition is for when you're in grade school, and you're trying to like memorize something.  So I think repetition is important. I actually feel like I, I came around to being open to repetition, like exposing myself to the same thing multiple times. Or yeah, like kind of having a social media feed that's some redundant voices or information just to like make sure that I really caught it and that I remember if it's something that's important to me. But I feel like it wasn't, I mean, it's a little bit of neuroscience that makes me appreciate like, yeah, you just sometimes have to repeat things to remember them. But it was also a book by Alon de Baton, which was a religion for atheists. I love that book so much. Yeah, so he's talking about different aspects of religion that actually make a lot of sense in terms of, you know, keeping culture and that kind of thing. And so obviously in religion, there's a lot of repetition, you say the same prayers and all of that. And it's just an explicit sense of like, yeah, you're going to do the same thing multiple times. But it's because it's important and you want to really imprint it on you. So yeah, so repetition is a very basic way just allowing yourself to see or experience the same thing multiple times so that you really get it in there. Yeah. Yeah.  So again, like I really got into neuroscience because of my addiction background. And one of the last chapters in the book talks about like reward based learning, right?  And, and yeah.  And so kind of like what you were just talking about with this repetition, you know, another like benefit is like, I found like, you know, cognitive behavioral therapy, right? A lot of that is about repetition and changing, you know, the way our reward system works and all that. So, so I guess like, you know, from, from what, what we know about the brain, like, even with just like habit building and building good habits, are there like, you know, benefits that we can learn from like behaviorism and reward based learning, if we want to build, you know, good, healthy habits, whether it's, you know, not just overcoming an addiction, but just, you know, trying to stop doing this thing. And what kind of hacks can we use to do the better thing instead, based on what we know about the brain? Yeah, I don't know if they're hacks, if it's just kind of better and you'll be better. Because as you said, a lot of it is habit building and repetition and all of that. And yeah, so the chapter on reinforcement learning, it talks, you know, about how kind of there are things that are rewarding, like primary words like food or something like that. And then there is kind of how we learn to get to those rewards, which in the terms of reinforcement learning is we have this thing called a value function. And it kind of back tracks the reward so that, you know, if you're the example I use, one of the examples I use in the book is that if you're like at an office and people are singing happy birthday, that probably means you're about to get cake. So you, yeah, you hear at the song happy birthday, you might be close to getting cake. And so if you do that a lot in life, which you know, if you attend a lot of birthday parties, you start to form that association. And so the song happy birthday has kind of some value to it, to the extent that it's tied to this reward. And that can kind of keep backtracking and backtracking and you know, it fades a little bit. So like things very far away from birthday cake have little value when it comes to if you want birthday cake, but the things that are closer to it have more value. And that's kind of how you can like follow this value function to get to a rewarding state. But what that means is then, you know, if you have these strong associations, you kind of creating this pathway that's going to lead you to that reward. And if that reward is actually something you don't want to have anymore, like you're trying to lose weight and you don't want birthday cake, it's hard to you don't have you have to kind of recognize that you're not just going to have to not eat that, but you're going to have to understand the kind of full pathway that leads you into that behavioral state. So yeah, it's a little bit. It's interesting this notion of reinforcement learning, which is also a way that you can train these artificial neural networks to have them learn how to navigate to rewarding places. It's a way of, you know, it puts some terms and language to kind of concepts that maybe we are a little subconsciously aware of or whatever. But it kind of gives you a way to talk about it and to think about it that makes clear how you're kind of learning this association and then might give you ideas of what you have to do to break the association. Yeah. So real quick out of curiosity, are you familiar with the work of Dr. Judson Brewer? His stuff. Um, he's okay. So he's he's he does some neuroscience, but yeah, he wrote a book about a lot about this and, you know, how the brain works and he's a huge BF skinner fan. But uh, but yeah, that's kind of where I learned and just kind of replacing behaviors by learning what that, you know, that pathway is and the way he kind of breaks it down is like trigger behavior reward, right? And so part of like CBT, for example, is replacing that behavior. So for example, with your cake example, right, like, uh, like what, uh, what, uh, the best way to do it, like replace it with something else that might give us a reward, like instead, like something similar, that's going to, you know, trigger dopamine or endorphins or, or something like that. Yeah. You could imagine that that's helpful because again, another part of this reinforcement learning and the way that you learn this value function is if, if I hear happy birthday and I think cake is coming and then I don't get any food at all, I have this big kind of negative reward prediction error and that's used to update the value function because it's like, Oh, maybe someone's saying happy birthday, but they weren't actually serving cake. And so now I need to stop associating the song with cake because I'm actually like in a new place where it doesn't mean cake is coming. And so you can kind of just break that association by repeatedly hearing the song and not getting, uh, what you thought you were going to get. And then you won't have this expectation when you hear the song that you're going to get that. Um, so yeah, you can kind of, you know, but yeah, the, the full drop from like cakes and nothing might be hard. So maybe it's like cake to fruit or something like that. But yeah. So there, there is this sense that you, you know, you learn your value function by these social associations happening and you can unlearn it if these associations stop happening. Gotcha. Okay. Cool.  And when I kind of learned about this, it was when I was just really into like reading books about why people have supernatural beliefs and skepticism and stuff.  Like, so does these, like, are there prediction errors that kind of explain, you know, these like, oh, I saw like a ghost or there's a UFO. Like, do you look at that kind of stuff when it comes to computational neuroscience? Does it kind of explain these like supernatural phenomena that happen with people because their brain is just predicting certain things? Because isn't that like pretty much how magic works? They know how to manipulate that. Can you break that down a little? So, yeah, so people having beliefs and kind of conspiracy theories or just things that don't have a lot of evidence and all of that, that feels, you know, to some extent, it's like personal psychology and probably has partly to do with genetics and all of that, but it also feels very social, I think. So this isn't something that I study or know a lot about. And a lot of computational neuroscience, as we talked about, kind of is informed by animal work where you can't really study those kinds of things. Like, I don't know if the, you know, mice that we're looking at, yeah, believes UFOs or anything like that. So it's not, it's not in like mainstream computational neuroscience that people are really thinking about those things. There is, there's a field called computational psychiatry, which is focused on psychiatric disorders and the mathematical modeling of those. And that might, they kind of study the basis of hallucinations and delusions and schizophrenics and that kind of thing. But yeah, I think the kind of social element of more low grade beliefs like that is, it's not super focused on in computational neuroscience. But yeah, certainly studied in, you know, psychology more broadly and all of that. Got it. Okay. Okay. So now I know where to, where to look into some of this stuff. So, so yeah, Grace, you have been awesome. I have learned so much. These are the conversations I love the most because it, it fills some gaps in my knowledge and I love it. So the book is out. So for everybody listening who wants to know more about what you're doing, upcoming projects and all that, two questions. Where's the best place to find you? And do we have any upcoming books to look forward to at all or what you're working on? Yes. So I am on Twitter. My handle is NeuroGrace. So pretty straightforward. I also have a website with information about the book and where to get it. And that's just Grace W. Lindsay, L-A-N-D-S-A-Y.com. I'm not writing another book yet. Taking a little break in between. But I do occasionally write for some online outlets and stuff like that. So that would be advertised on Twitter and on my website and all of that. And I used to have a podcast about computational neuroscience and artificial intelligence, but the episodes are, they were never very timely. So if people are interested in the topic, they can still listen to those episodes. And that's unsupervised thinking was the name of that podcast. It's a little, it's more technical. It's more in the weeds than the book is or anything like that. It was more, you know, other academics would listen to it. But if people want to get into the weeds, that's a good place to start. Beautiful. Awesome. And I will link all that stuff down below. But yeah, again, Grace, thank you so much for your time. And, and yeah, I'm sure we'll be in touch soon. Yeah, great.


Hi everyone, Joe for Jaspy's casebreaks.com coming at you with 2022, Topps Luminaries Baseball, 12 box, random team break number three, 30 spots all teams in, yes, it's only 12 in case things, the box, high risk, high reward. So fingers crossed everybody, good luck. Now, we had a tonight only special where if you bought a full spot, all right, any full spot, you have a chance to win a full spot. So let's gather all these names and congrats to the people who won spots in those two filler packs that we did. All right, so we got everybody's names here. New dice, new list, that'll be the first, second dice will be names and teams. So name on top after eight, four and a four, eight times, we'll get an extra spot, one, two, three, four, five, six, it's a hard eight, right, yeah, seven and eight. There you go, Robert, congrats. After eight, there's your extra full spot right here. Put that little rooftop next to your name so you know you won that spot. So now we've got our full 30. Now let's randomize you a team, all 30 are in. Good luck, let's roll it, randomize it, one and a three, four times, one, two, three and four. And four. Got Chad Tucker down to Chad Tucker, the spot that he won and the spot that he got straight up. Appreciate you doing both, one and a three, four times for the teams, one, two, three and four. After four times we got the Rangers down to the Red Sox. After three and a one, four times, yep, got it. All right, so Chad with the Rangers, Michael with the Cubs, Mark with the Guardians, Brian with the Orioles, Michael with the Dimebacks, Sean with the Mariners, Steve with the Twins, Robert with the extra spot you got, you got my Dodgers and you've got the Mets. Steve with the Nationals, Robert with the Astros, Ryan with the Marlins, Chad Coleman with the Angels. I might have a couple of Chads in this break. Mark with the A's, Chad Coleman with the Rays, Hans, last full, last spot mojo, Yankees, Steve with the Braves, Chad Tucker with the Cardinals, Michael with the Brew Crew, Ed with the Rockies, Ryan with the Pirates, Sean with the Lions, Lonnie with the White Sox, Royals, Phillies, Ed with the Giants, Steve with the Blue Jays, Tim with the Padres and Reds, and Chad Tucker with the Boston Red Sox. All right, let's sort by team. And we're gonna pause the video, it's a random team break. We're gonna pause the video, see if there's gonna be any trades, but remember, trade at your own risk. So be right back. All right, welcome back folks, no deals were done, so that list remains the same. Song remains the same. 24th, random team number three. Thanks everybody for making this happen, appreciate it. No trading, Steve's like, come on, no one trading. Wait, Steve, did you, you said you were on the West Coast for a bit, did you get a chance to stop by the shop? Do you have any time for that? If you were in the Venice region, I'm not sure how I'm gonna open this, so it gets from here, then you might have, we're too far away from, we're too far away from Hermosa Beach, California where we're located. Back some of these luminaries boxes way up here. Oh, you didn't, you stayed at the Marigold? Didn't know what to edit words for the rest. That's right, that's right, I wasn't sure, Red Cums, Jets, Merica. I drove by there recently on a, I was visiting my folks and my sister in Vegas. Traffic was a little weird around how I normally go, and they sent me up over and through Edwards, America. They land the space shuttle there, they used to land the space shuttle there every once in a while. Oh, we got nice sponge covering over here, hide the hit a little bit. All right, good luck, everyone. First one out of the gate is gonna be Albert Pools, seven out of 15 Cardinals edition. That's his Cardinals career hit total. That must be as of when, I don't know, as of when. Maybe this was pre-return to the Cardinals. All right, next one. Oh, they had a NASA telescope playing up there, that's pretty cool. They also have a, I drove by it.  All right, that goes to Chad Tucker, the Cardinals, by the way, the Poo Hulse autograph, legend. Next one is gonna be a one out of five A-Rot, a home run Kings card. His 600th home run, August 4th, 2010. Nice, and that's Yankee's edition. That's for Hans, last spot Mojo. Hans. All aboard the Big Head Express. Woo-hoo. Oh yeah, how long is that gonna be there? The Dark Star from Top Gun, Top Gun Magic. That there for a while was just last week, and I saw stories about that, and I was like, oh, I should go check that out. I thought that was pretty cool, but I was out of town. We got a one out of 15, Jaren Duran Rookie Auto. His first hit, July 2021. Yeah, that's what I hear. It doesn't actually fly, right? It's just a prototype. Jaren Duran going to Chad Tucker and the Red Sox. Can keep me to go to like an air show, I haven't been, there's one in, I used to live near Miramar Air Base, but I mean, enjoyed hearing the scream of F-18s. It's actually pretty cool. Sound, pinstripes here. Not, I haven't been to an air show. Gotta do that someday. We got Christian Yellich. Got a relic and autograph, 15 out of 15. Career high home run total in 2019. That's for the brew crew, Michael. Did they all go this way? One out of three. Another train whistle here for Jordan Alvarez Astros. He's the corn to Vegas and he was your 2021 ALCS MVP. Could he be a World Series MVP? That goes to the Astros. That's for Robert Flores, Robert. All aboard the Big Hit Express. Think he's the odds on favorite corn to Vegas, including the World Series MVP at plus 600, six to one or something like that. Steve at the Astros last break. Isn't that how it works? That's how it goes all the time. All right, next up, we have a Philly. It's as if, it's as if Tops knew that the Astros and Phillies were gonna be in the World Series together. Look at that. 13 out of 15, Bryce Harper. I think he's the next favorite, like plus 700 or something like that. Philly's at Ghost Elani and the fightin' Phills. All right, we are halfway through this 12 box break, full case random team. Number three, they've all been Portrait Mode, right? Well, this one might be Landscape Mode. It's Greg Maddox, nine out of 15. Four ERA titles, four National League ERA titles. Nine out of 15, this is Brave's edition. That's Steve Herrick and the Bravo's. All right, next box. And that is an Oriole that is Cal Ripken Jr. 10 out of 15, Brian with the O's. Number one career home runs as a shortstop. Is that right? Not A-Rod? No, A-Rod played third for a bit, right? All right, next one. Maybe some DH2, maybe that takes away some homers as a shortstop. We got some blue, six out of 10. Looks like another hitter. It's Ozzie Smith, the wizard. 2,460. Number three, career hits total by a switch hitting shortstop. Anyone know one and two? That'll be for the Cardinals, that's gonna go to Chad Tucker. I don't, I'm asking. All right, a few more to go here. Some loomy loom. And then we got a WWE box to close things out. I guess I could stick around. Yeah, a little bit, a little bit. We have Andrew McCutcheon, 12 out of 15. What do you think eight homers represents? I think I've seen this one. It's, I think it's walk-off homers. Number three, active walk-off homer total. Nice. The penultimate box. What do you call it in McCutcheon? McCutcheon, is that, is it a really common name? Pirates, Phillies, Darnons, and Yankees. I think it's all hit a walk-off homerome with those four teams. All right, next. Three out of three, that's Luis Robert. Ooh. Spark of light, those are so cool. That silver ink really pops, ladies and gentlemen. The spark of light autograph, that really pops.  All right, final box, good luck. See you Ramon. Thank you again. Look at the back. Last one here, red parallel. What's the red parallel number two? Ooh, it's Vladimir Guerrero Jr. one out of 10 autograph. Four grannies? Four game, Homer's streak, wow. Actually, I do remember this. 20, 20. Yeah, June of early 20, or mid-2021, 11 through the 14th. Blue Jays, and it goes to Steve Herrick with the spot that he won in the filler. There you go, Steve. And there you go, gang. That's pretty nice. We've got another luminaries, random team break loaded up in the store. As I mentioned before, we're planning on selling 12 full spots, not 12 foot spots, 12 full spots, and do three fillers. But like we did with this one, if more full spots are being picked up, we can cancel a filler, maybe add some full spots back in and do it that way. That was random team three, great break. Thanks for watching, thanks for breaking with us. I'm Joe, I'll see you next time for the next one. Bye-bye.


What's up guys and welcome to trendy updates of our SPM boys. Now onto the trendy news today is controversial video vixen Brando Alteno who alleges that there is a celebrity with a father in kids that are not his. Now we know Brando Alteno came onto the limelight when she was featured on their thiambo song by musician Bahati but now she came out to expose this musician saying that he has not paid her for appearing on that video as a video vixen. Now I'm going to drama Sana Kubu Apale Kuenyem Tandao and she says for the past year she has been looking for Bahati. I think it's a good idea for her to appear on that video but Bahati has remained silent. Now I'm going to tell her that she is not the legal way and she has indeed contacted a lawyer working on the Lezaile story. I'm going to tell her that she is not the legal way and she has been looking for Bahati. But now back on this story this controversial video vixen now says and I quote there is a celebrity in Kenya who thinks he has three kids yet he has nine. I'm about to spill the hottest tea to the world. Now she says that this celebrity is raising three kids and Bahati the artist is not paying her for appearing to that song at thiambo and by right now it has 22 million views and of course continue to kanamou. Now that he may pass a conversation your brand a case of wichisha pesos a case. And Bahati hasn't really addressed this issue and Leza who posted two video pallet and by right now thiambo at least say ma kumbe una eza kuni mok you are now mocking me by posting that video but you do not want to talk about this conversation and a brand has gone ahead to serve Bahati with a letter from her lawyer. Now we are waiting to hear what a thiambo is going to be telling us and who is that celebrity that is raising three kids that are not his. Now do you want to know why he is commenting on this video and why he is saying that he is not paying her for appearing to the world and by right now it has 22 million views and Bahati is not paying her for appearing to the world and by right now it has 22 million views and Bahati is not paying her for appearing to the world. Let's take a look at Bahati's statement.  But in Lex 214k she was saying that she is complaining of a fear of being a child. They were not saying that she calls because they were not going to invite them. She called all the girls and they were all going to maker her. Then a one-zero-zero one says don't we all know that celebrity Justin Mima 254 says what do you want to see now? M.E. Ismael Nye says, Buona na ona ki ardi hapa Alafubasikun otwana mini tunin goma kama na tashawine Na ani Sylvia wana mini, there's a new song that is coming through Let us know down on the comments section Who do you think the controversial video vixen brand out Cetino is alleging that he has three kids and yet he thinks they are his own but they are not Let us know down on the comments section and in the mean time keep it trendy update hapa SPM birds


Thank you. Thank you. Our next witness is Sarah Robinson from the Vermont network against violence. Good morning. Thank you so much for having me for the record. Sarah Robinson, deputy director at the Vermont network against domestic and sexual violence. Thank you very much for taking testimony on S 99 this morning and for the thoughtful conversation that you all have been having with the previous witnesses this morning. The network supports S 99.  And these previous claims have been really immensely helpful for victims and extending these reforms to victims of child sexual abuse. And we believe that this physical abuse will provide just one mechanism for victims to be able to seek justice when they've experienced severe child abuse by an individual or an institution entrusted with their care. And from our perspective, you know, certainly compared with the criminal processes, civil actions have the potential to provide even more child sexual abuse. And while criminal justice processes are designed to focus on individual culpability related often to specific acts. Civil actions can provide a mechanism for broader accountability and for reform. And I think you heard that earlier from the two witnesses that spoke. And importantly, so these civil actions can provide an opportunity to seek justice and not only from individuals that cost harm, but also institutions that were entrusted with keeping children safe. And in this way, we think that civil actions have an important role to play in the prevention of further or future child abuse. And this particular proposal that you're looking at today will really provide these kinds of opportunities for victims of child abuse whose lives have been irrevocably altered by their experience of abuse. And these victims can include child victims of severe household domestic violence and victims of child abuse experienced in an institutional setting. And I know you've heard several examples already of that. The current three year statute of limitations related to these particular civil actions really sets forth a timeline that has no relation to the dynamics of the sort of abuse or challenges that victims face in coming forward. For many individuals, it can take years to really fully understand the scope and impact of abuse that they experienced in childhood. And even once that is realized, it can take even longer to navigate the complicated process of taking action to seek various paths of justice against those that were entrusted with keeping them safe. And so lifting these limits really expands victims' ability to seek healing on a timeline that is more reasonable and is, frankly, more evidence-based when we look at the way, the amount of time that it does take for many victims to come forward and disclose. And I just wanted to note two additional items that had come up previously in discussion this morning. One was something that Senator Baruth brought up. And I would just offer that one additional item for potential consideration by the committee is whether Vermont statutes regarding access to records by victims after they reach adulthood, whether any of those statutes need to be strengthened. And in many cases of abuse, victims seek to really make sense of their memories and experiences by seeking available documentation about their care. And I know that in the case of the St. Joe's survivors and many others that I've spoken with, access to records has posed a significant barrier to healing for victims in the past. And so that may be an area for additional consideration. I don't have any particular language recommendations today, but if the committee was interested in pursuing that line of inquiry, I'd certainly be willing to be part of those conversations. And then the last is just in regards to child abuse and what we are seeing today, one of the things that the network does is house the program that trains nurses to provide those specialized exams to victims of domestic and sexual violence. And that also includes providing exams to pediatric patients.  And I did want to note that in 2020, 318 adults and 67 children in Vermont saw those specialized exams.  And that was almost twice as many as the cases that we saw in 2019. And I just share that by way of saying that it was a really surprising, it was really surprising for us because overall healthcare utilization was down in 2020. But what we saw was almost twice as many people seeking specialized care for exams related to abuse that they experienced. So I think that this proposal is timely and we support it. Thank you, Sarah. Are there questions for Sarah? I guess one question is frequently in domestic violence cases. We hear of where children were taken into the doctor's office and examined and sometimes it's questionable whether it was the broken arm as a result of abuse or that fall down the stairs. Is that the type of case you're talking about where the records are not available? I don't understand the record. Yep. So I think it would be those records. It could also be records related to children that are in states custody or in a placement in some kind of placement that they're unable to access those records could also be related to adoption records. And Amy Brady from Voices may be able to speak to this in greater depth. But I know that many people who experience abuse and then are placed in a different household and permanently placed with another family often have a really difficult time in going back and seeking any records related to their adoption after they are adults. And so that may be one additional area for consideration. Yeah. Well, I was a subject of the notice stated options. You can just guess how difficult it is to uncover any information from messages. Of course I'm not only the records are difficult, but I was talking more about those types of allegations of child's physical abuse.  The father's obviously the doctor can't prove that those records are there somewhere. And maybe years later that he relives those. I think that's exactly it. And so there may be. Sorry, I'm getting an echo. There may be, you know, medical records. There may be educational records or various institutional records. That could be really helpful to adult victims as they're trying to make sense of their experience. All right. Thank you, Sarah. Thank you very much. Our next witness is Mary Kehoe, an attorney with the Kehoe law firm. Mary, welcome, Senate judiciary. Morning. Thank you for having me. Yeah. Where would you like to start, Senator Sears? Well, you're interested in this bill. Okay. Thank you. I have recently. I'm sorry. I'm sorry. I'm sorry. And people that you represent how it would help. Okay. Well, I don't actually represent anyone. I've been assisting individuals who are survivors of St. Joe's on sort of an ad hoc basis. Working with Mark Wenberg and. Victims. And can you hear me? Okay. Thank you. Thank you. Thank you. So in talking with them and looking at the bill that Senator Pearson's introduced. You know, the concern is how do some of these people obtain redress for the harms that they experienced as children. And I know that Senator. Pearson is interested in this as well. And it just simply occurred to me. That one. Way of looking at this in terms of waiving the statute of limitations. Without opening. The floodgates, so to speak, would be to take a look at the standards that are in Vermont's relief from abuse statutes. As they relate to children. Most of my career was focused on helping domestic partners. Not so much children. But I do know that in order to obtain a relief from abuse order. To protect a child. One can do so if one can establish. That the harm to the child is so severe. That it impacts their emotional development. So I would encourage the Judiciary Committee. And considering Senator Pearson's bill. To take a look at that statute. To see if that is a standard. That the committee could, so to speak, wrap its arms around and considering waiving. The statute of limitations for people who experienced that. Kind of harm as children, they would have to establish the harm. And I don't think it's very easy. You would have to have someone, probably an expert. To establish that the person now at an adult. Experienced that level of harm as a child. It's worth considering. I haven't delved into it in great detail. And please let me assure you, I'm no expert at that. I know that you have other witnesses. I see Jerry O'Neill's name here as a witness. Who are have far more expertise than I do. But I just think it's one area that you could look because honestly, I know that Senator Pearson is concerned about opening the flood gates. But honestly, when I took a look at his bill. His proposed bill. It occurred to me that there are precious few people that that bill would really. At least those that I've been in contact with who are survivors of their occupancy at St. Joe's many, many years ago. Few of them experienced. Aggravated assault, but many of them experienced severe emotional trauma. Based on the way they were handled as children. So I would encourage the committee to take a look at title 33. Have ledged councillors. Take a look at that. And see if that covers. I think we could. Sorry. Go ahead. That's the sort of thing that. Well, here's my problem. Not even supposed to be taking up Senate bills right now. And because of the timeliness of this bill. I'm taking it up. We were to expand further. To the. The title 33. Relief. So I would encourage the committee to take a look at title 33. Have ledged council take a look at that and see if that covers. I think we could. Take a look at the title 33. Relief and abuse standards. I don't think we can do that this year. I think that's something that. We would need to look at. Right now. I'm just. I think. That does complicate the issue. Trying to do that night. Senator Pearson's. You know, I'm trying to. Because it seems timely to me and important. Yes. We deal with this. But getting into those types of standards. We need to. So look for, I don't think any state has gone that. Well, I'm aware of. Oh, I also think you'd have to have. Other parameters in order to avoid. In my, this is just my opinion as a citizen. To avoid. Casting too large a net. With this bill, one thought I had. And again, these are just my thoughts in speaking with these individuals who. As I'm sure you all know. You know, I have suffered some severe harm. It's hard not to feel very compassionate about them. But one thought I had is that you could limit the waiver of the statute to institutions. Right. Because institutions. Have, I think. A greater responsibility to all of us. When you're entrusting a child in their care. And they hold themselves out. As a facility that has the capacity to provide that care. I think it would be. Different when it's in a strictly private context within, for example, the scope of a family. So I would be in favor of taking a look at whether it would be. Wise to limit the scope of the waiver of the statute to. Institutions who hold themselves out as having expertise. And honestly get paid, right? Get paid or get some sort of compensation for what they do. I think they should be held to a higher standard. Next week we hope to hear from some of the survivors. Some of this time, and that may help make our judgments is about where to go. Inform us. As working with the survivors, what have you discovered that you didn't expect? Well, I know that Mr. O'Neill probably knows a lot more about this. And I do. I. Here's what I have discovered just personally that it's. With highly concerning issue. When I first got involved with these folks. As anyone I took a look at the materials they sent me. And the first thing I thought is, oh boy, this is going to take me a lot of time. And I started watching and I couldn't break myself away. From what they wrote, what they said, what, you know, songs they composed, poems they written. They've written about the experiences they had. I read the article by the. Journalists whose name I cannot recall, but I think she's from Australia. She's from Australia. She's from Australia. She's from Australia. I couldn't tear myself away. What happened to these people is honestly horrific. And they are now feeling it more now than. When they were children, of course, because they don't have a voice when they're children. I mean, it's, it's really hard not to feel extraordinarily hurtful.  I'm just doing this as a citizen who has. Time on her hands. It's hard not to want to take action to provide these people some relief. They're hurting. I, I really do hope you have a chance to. I know you're so, so busy, but to lay out the time to listen to these folks and what they have to say. You know, I, I feel comfortable in saying that I assure you, you will all react the way I did and speaking with them and reading what they had to say. And I hope you can find the time, not necessarily this year. I'm sure that will require some work. I see Mr. Fitzpatrick's name on the screen here and ledge council would have to really study this. I mean, obviously you all have to seriously consider the consequences of the actions you take. But I think this is one. Senator Sears that really deserves that time and effort. If not this year, then next year, I would certainly be happy to help in any way I can. There's been discussions between the Senate, Judiciary Committee, and Senate Education. About next steps, and that's mainly regarding the current hat and situation. Similar. We have both charges of sexual abuse and physical abuse. And whether how that moves in the, and what we do, whether it's go through the child protection committee that legislative joint. We're going to continue to look at these issues in these institutions, specifically those two. And their impact on kids in Vermont and survivors. Those. But. This bill. Is specifically one thing that. We think we could do to bring some relief. Some kids. No longer kids. Some children. Physically abused in those situations. Obviously. Because Vermont. I think was. Me proactive in this community. Some of that. On the child section. And I don't know what the impact has been of that. Whether there have been a lot of cases filed or haven't. Now we're looking at this. Child physical abuse that occurred in some of these. When it gets to the emotional trauma. It's harder to. That's what that. Again, there's where I would say that. That. Whatever we end up. With. With. I don't know what the impact has been of that. Years ago. Whether there have been a lot of cases filed or haven't. Now we're looking at this. Child physical abuse that occurred in some of these. When it gets to the emotional trauma. It's harder to. You know, Whatever we end up with. The three committees in the Senate. Looking at. Issues. Certainly. Yeah. Similar. You're really similar. Yep. Well. The. We look forward to hearing from some of those folks next week. And. You know, what's happened to them. Yeah. Well, thanks for the opportunity. And I'm grateful that you're taking a look at this and doing what you can. To address these issues for. Yeah. There's also. I should mention that in the attorney general asked for, I think a little over $25,000. Which is in. For the survivors. Yeah. Help with the wellness program. For those survivors. It's in the H3 third. Three 15 much. The Senate's past. House. Hasn't yet agreed with our. I don't think it's over that. I don't know where that. Well, thank you. Welcome. Amy's good to see you here. Thank you. Thank you for the opportunity to testify today. For the record, my name is Amy. And I'm a policy associate with voices for Vermont's children.  And support broadening the scope of that statute to include physical abuse through S 99. My intent is to keep my testimony brief. In addition to my testimony, I have sent the committee. Rosemary.  Equally devastating acts require equally solicitous statutes of limitation. Rosemary outlines other state statutes. Names and equities that exist within those statutes. Names and equities that exist within those statutes. Explains the individual and community impact of childhood trauma. Counters the common opposition to statute of limitation changes. And speaks to the necessity of developing for you. It is my understanding that this bill was drafted in response to a request from St. Joseph's restorative inquiry. I would be remiss if I didn't take this opportunity to thank them for bringing this issue forward and to extend that gratitude to all of our sponsors as well as this committee for listening to them. We know that trauma leaves people vulnerable and can often strip them of power and voice. Centering survivors and restructuring our systems redistributes power and has the potential to heal past wrongs while creating meaningful and visionary changes to our current structure. In addition to repealing the statute of limitations, voices for Vermont's children recommends looking into the current situation. We can not undo past harm. We can create the context for healing. When we allow the people who have abused others to continue to hold the stories of those they have harmed, we are getting in the way of the truth and reconciliation process. In conclusion, voices for Vermont's children fully supports S 99 and looks forward to working with this committee and others to address proactive measures to prevent abuse. We also support removing barriers to healing, especially those that have been unearthed by survivors all around the state. Thank you. Thank you. I briefly glance that the committee has put on, we have posted to the committee website. Are there particular areas that you, I mean, it's 140 pages, I think. It is. Just six or seven. And so I can highlight those and send that back. I think that she just did a really good job of kind of going through why this matters. I think it's really important to think about what has happened when they changed statutes. There's an example of Oregon in particular with a case study. And why, why this matters for kids long term as they grow up. And she speaks a lot about ACEs, which I know that the legislature has heard about for a number of years, but sort of the financial and. Lifelong impacts of trauma and how civil removal of statute of limitations can help. To at least compensate folks for, for the extra expenses that they've had to endure. They've experienced. Are there any comments regarding access to records that you could help me with? Thank you. I did hear that question. For Sarah as well. And I think, you know, for the most part, from my understanding is that medical records are fairly easy to access if people know the providers to go to. What I've heard more and more is that. Youth who transition out of state care, particularly those who don't have a permanency plan, who. Transition and independence without. A family to connect with. Often have a really hard time accessing their records. After their time in state care. And they do not even know the providers. To seek their records from. Because they don't have access to their full story. I also saw the list of. Hopes and aspirations that. The folks from St. Joe's put together. And I noted that on their list, they also asked for their own individual records. And I think that they've been working on that for some time. And still haven't been able to. Get them. It just feels like, you know, it's a common theme. Whether it's somebody who's been in state custody. Or somebody who's been an institution. Where they know where the records are kept. They've gone through. You know, do process trying to. Get access to them and have been denied. Other questions from Amy. Senator Bruce. Yeah. Quick, quick follow up. Can you specify a little, what, what is the basis under which they're denominated? So I believe, and you know, we would have to ask. I think the state probably more about this, but I believe that. Youth have transitioned out of state care in particular. Have access to specific parts of their file. They need to be redacted. I think sometimes those files are hard to locate. I think sometimes. There's been barriers. To doing that. And I don't know if it's because. The redaction process takes staff time or. I really don't know, honestly, but what I do know is that there are many youth who have repeatedly and writing and, and. You know, gone through the complaint process, trying to access the records and have not been able to do so. I think that they're supposed to be able to see them in the office and then request specific sections. To take home with them. And even the. Even seeing their educational and their medical records within the office hasn't been granted in many cases. Seems so odd to me because I usually associate redaction with national security. In this case, given that they're the individual. To whom the record pertains. I think it's hard to see the justification for. Redacting. Their own record. The reason behind that is because oftentimes a child's file includes health records of their family. And so while it's their own record, there's often information in their file that pertains to other people that they might not have access to. They might not have access to the records or sometimes so old. It may not have redacted everything they have thought they were going to. Or they may have over redacted. I don't know if I was. To find out my. My name was Stephen. Actually, my first name was. When I was born. Could have been different. You know. I don't know if I was supposed to find. Anyway, those are the types of things that are in records that. You just can't access. I don't know if Senator whites committee has. Usually does records. And that's assuming that kids were in states. Many of the kids at St. Joseph's. That is true. And I think you'll, if you ask them next week, I think you'll hear that they're having equally difficult time getting access to their files. And. In just her, I don't know. We don't deal with. Individual records, but with public records requests. In terms of somebody else requesting a record. I don't know. But individuals records are usually available to the individual. With, as Amy pointed out. The red action necessary to protect other people. Okay. Any other questions for Amy. Committee. Zoom through this. Zoom. No. We, we are at a schedule. So Eric, maybe we could talk a little bit about. Further. Are there other questions that committee wants to. Ask to look at. As we continue to work on. I just ask Eric question. I'm just thinking about cases whereby. Someone is. Emotionally unstable later in life. And they did go through. Home or they're in their own home, for instance, even. And they were. Not really severely abused by the parents, but say emotional abuse. Does that come under here too. That later on. They are experiencing problems and. Maintain that they were emotionally abused in their. Home. Are those cases, would they also come under here? The way it's written now would not apply to just emotional abuse. No. Okay. It's just. There has to be some physical injury. Right. I'm also thinking of some other cases whereby. In times past. Substantiated abuse might have been if. Apparent. I can think of one case where by.  And when the, in doing so, it must have hit them hard enough that it. It left a mark on their face. And so that case was substantiated. And so say that. The child went on in life and said, you know, I was an emotional problem. I'm still suffering. Because of this kind of thing for my parents. And that piece. About the slap in the face couldn't be substantiated. Because that might be in a record because it was founded. So are those the kind of.  But would that be considered aggravated assault? Because there was no intent. Cause serious bodily harm or. I don't know, Eric. I would say not. It's, I agree. Senator white that. It probably would not. Come under the definition of aggravated assault because. It would not. Seem to be. It wouldn't cause serious bodily injury. And. Was not conduct that was. Manifesting extreme indifference to the value of human life. So. A slap in a. Parental context doesn't, doesn't seem to me to rise to that standard. It would be assault, but not aggravated assault. Correct. Yeah. But. It may not even be assault. I mean, I. One of the charges in current hat is that the kids were. Required to stand. For long periods of time. That may also been at St. Joseph. We're required to stand at long periods of time. Stand in place. Would that be. Which. Causes. Causes. Causes. It may not even be assault. One of the charges in current hat. Is that the kids were required to stand. For long periods of time. Which. Causes. Causes. Causes. That. That sort of thing. I would seem like a difficult. Case to make her. Or to meet that standard. But then the kids. The cross. Who. Knees buckled. Would be. That's potential. Yup. That could be serious pottery entry. You know, kicking someone to the floor. Does that show extreme indifference to the value of human life? Is that. Or. Reckless conduct that. Someone might. Arguably know could.  You know, again, not an easy case to make, but you know, the more severe the. Arm. The more at least possible, it seems like. A claim could be made out. Thank you. Eric. Where we go. The only thing I had forgotten to mention, and just to, again, it's a. A legal point that the committee had talked about in the. Context of the. Childhood sexual abuse statute as well. It is just a. And you know, the mayor may not. There was a lot of testimony. About this two years ago, it may not come up again now, but there is this sort of outstanding constitutional question about. Reviving claims that have been expired. Still hasn't been resolved. I think the cases I've seen. There are cases on both sides. It seems like the majority of cases say it's okay. But there are a few that say. It causes due process problems. Just. As we always. Yeah. So the idea is that. Once. The. Statute of limitations has run. That someone gains a vested right. And not being able to be sued for that conduct anymore, because. It seems like the majority of cases say it's okay. But there are a few that say. It causes due process problems. Just. I don't know. I don't know. I don't know. I don't know anything more because the, the limitations period has run. Couple of, there's been a few courts that have said that, and that's a due process issue. But the majority of courts that I've seen Massachusetts. Supreme court, Connecticut Supreme court. For example, have said that there is no vested right. That's acquired. In that situation and distinguish it from. You may recall, we've talked about this in the criminal statute. We've talked about this in the criminal statute. We've talked about this in the criminal statute. We've talked about this in the criminal statute. Once a criminal statute of limitations expires. The person. You can't retroactively extend. For the person. But those cases have distinguished the criminal and civil statutes and said. It was not a due process problem. I just like to flag it for the committee so that it's. Not a surprise that that ever comes up. And there have been a few minority. Courts that have said that. Just so it's not a surprise later on. I think that's a good point. I think that's a good point. Yeah. Gary, did you have a comment on that? Only briefly, I haven't reread the case. In preparation for this, because I didn't expect the issue, but I believe that there was a case. That comes out of the retroactive provision of the statute. From 1989 or 1990.  I believe. And again, I'd want to reread the case on it, but I believe the Vermont Supreme court had no trouble with the retroactivity provision. And. Rule that it was lawful. I think the distinction there is that it hadn't expired yet. That's true that they were, they were. They retroactively extended it. But, but the, I don't think the statute. I don't think that was the case. I don't think that was the case. I don't think that was the case. I don't think that this period had fully expired. That was my reading of it, but. Yeah, I'd have to read. It's not how I remember it, but I don't claim to remember things correctly. So I'd want to reread it as well. I'm in the same boat. That's why they have provision. I don't know that that works by the way, that was not an ad. Any other comments? And I want to. Labor the plane. Peggy. And witnesses. Thank you all very much.